A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

Shahrukh       Qureshi; Ravina       Khandelwal; Maddala       Madhavi; Naveesha       Khurana; Neha       Gupta; Saurav    K.   Choudhary; Revathy    A.    Suresh; Lima       Hazarika; Chillamcherla    D.   Srija; Khushboo       Sharma; Mali    R.   Hindala; Tajamul       Hussain; Anuraj       Nayarisseri; Sanjeev    K.   Singh
doi:10.2174/1568026621666210119112336
Abstract

Background: Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32).
Aim: The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL.
Methodology: Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds.
Result: MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies.
Conclusion: Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.
Keywords: MMP9, Proteasome, BTK, TAK1, Mantle cell lymphoma, Molecular docking, Virtual screening, ADMET, OSIRIS.
« Previous Next »
Graphical Abstract

[1] 
Lynch, D.T.; Acharya, U. Cancer, Mantle Cell Lymphoma. StatPearls Publishing: Treasure Island. 2019.
[2] 
National Cancer Institute. SEER Stat Fact Sheets–Non-Hodgkin Lymphoma., 2020. Available from: seer.cancer.gov/statfacts/html/nhl.html
[3] 
Hoster, E.; Dreyling, M.; Klapper, W.; Gisselbrecht, C.; van Hoof, A.; Kluin-Nelemans, H.C.; Pfreundschuh, M.; Reiser, M.; Metzner, B.; Einsele, H.; Peter, N.; Jung, W.; Wörmann, B.; Ludwig, W.D.; Dührsen, U.; Eimermacher, H.; Wandt, H.; Hasford, J.; Hiddemann, W.; Unterhalt, M. German Low Grade Lymphoma Study Group (GLSG); European Mantle Cell Lymphoma Network. A new prognostic index (MIPI) for patients with advanced-stage mantle cell lymphoma. Blood,  2008, 111(2), 558-565.
[http://dx.doi.org/10.1182/blood-2007-06-095331] [PMID: 17962512] 
[4] 
Holkova, B.; Grant, S. Proteasome inhibitors in mantle cell lymphoma. Best Pract. Res. Clin. Haematol.,  2012, 25(2), 133-141.
[http://dx.doi.org/10.1016/j.beha.2012.04.007] [PMID: 22687449] 
[5] 
Hoster, E.; Rosenwald, A.; Berger, F.; Bernd, H.W.; Hartmann, S.; Loddenkemper, C.; Barth, T.F.; Brousse, N.; Pileri, S.; Rymkiewicz, G.; Kodet, R.; Stilgenbauer, S.; Forstpointner, R.; Thieblemont, C.; Hallek, M.; Coiffier, B.; Vehling-Kaiser, U.; Bouabdallah, R.; Kanz, L.; Pfreundschuh, M.; Schmidt, C.; Ribrag, V.; Hiddemann, W.; Unterhalt, M.; Kluin-Nelemans, J.C.; Hermine, O.; Dreyling, M.H.; Klapper, W. Prognostic value of Ki-67 index, cytology, and growth pattern in mantle-cell lymphoma: results from randomized trials of the European Mantle Cell Lymphoma Network. J. Clin. Oncol.,  2016, 34(12), 1386-1394.
[http://dx.doi.org/10.1200/JCO.2015.63.8387] [PMID: 26926679] 
[6] 
Owen, C.; Berinstein, N.L.; Christofides, A.; Sehn, L.H. Review of Bruton tyrosine kinase inhibitors for the treatment of relapsed or refractory mantle cell lymphoma. Curr. Oncol.,  2019, 26(2), e233-e240.
[http://dx.doi.org/10.3747/co.26.4345] [PMID: 31043832] 
[7] 
Mato, A.R.; Feldman, T.; Goy, A. Proteasome inhibition and combination therapy for non-Hodgkin’s lymphoma: From bench to bedside. Oncologist,  2012, 17(5), 694-707.
[http://dx.doi.org/10.1634/theoncologist.2011-0341] [PMID: 22566373] 
[8] 
Fisher, R.I.; Bernstein, S.H.; Kahl, B.S.; Djulbegovic, B.; Robertson, M.J.; de Vos, S.; Epner, E.; Krishnan, A.; Leonard, J.P.; Lonial, S.; Stadtmauer, E.A.; O’Connor, O.A.; Shi, H.; Boral, A.L.; Goy, A. Multicenter phase II study of bortezomib in patients with relapsed or refractory mantle cell lymphoma. J. Clin. Oncol.,  2006, 24(30), 4867-4874.
[http://dx.doi.org/10.1200/JCO.2006.07.9665] [PMID: 17001068] 
[9] 
Curran, S.; Murray, G.I. Matrix metalloproteinases in tumour invasion and metastasis. J. Pathol.,  1999, 189(3), 300-308.
[http://dx.doi.org/10.1002/(SICI)1096-9896(199911)189:3<300:AID-PATH456>3.0.CO;2-C] [PMID: 10547590] 
[10] 
Kasaoka, T.; Nishiyama, H.; Okada, M.; Nakajima, M. Matrix metalloproteinase inhibitor, MMI270 (CGS27023A) inhibited hematogenic metastasis of B16 melanoma cells in both experimental and spontaneous metastasis models. Clin. Exp. Metastasis,  2008, 25(7), 827-834.
[http://dx.doi.org/10.1007/s10585-008-9198-7] [PMID: 18668328] 
[11] 
Yan, W.; Li, S.X.; Wei, M.; Gao, H. Identification of MMP9 as a novel key gene in mantle cell lymphoma based on bioinformatic analysis and design of cyclic peptides as MMP9 inhibitors based on molecular docking. Oncol. Rep.,  2018, 40(5), 2515-2524.
[http://dx.doi.org/10.3892/or.2018.6682] [PMID: 30226602] 
[12] 
Rasmussen, H.S.; McCann, P.P. Matrix metalloproteinase inhibition as a novel anticancer strategy: a review with special focus on batimastat and marimastat. Pharmacol. Ther.,  1997, 75(1), 69-75.
[http://dx.doi.org/10.1016/S0163-7258(97)00023-5] [PMID: 9364582] 
[13] 
Kilty, I.; Green, M.P.; Bell, A.S.; Brown, D.G.; Dodd, P.G.; Hewson, C.; Hughes, S.J.; Phillips, C.; Ryckmans, T.; Smith, R.T.; van Hoorn, W.P.; Cohen, P.; Jones, L.H. TAK1 inhibition in the DFG-out conformation. Chem. Biol. Drug Des.,  2013, 82(5), 500-505.
[http://dx.doi.org/10.1111/cbdd.12169] [PMID: 23745990] 
[14] 
Tan, L.; Gurbani, D.; Weisberg, E.L.; Hunter, J.C.; Li, L.; Jones, D.S.; Ficarro, S.B.; Mowafy, S.; Tam, C.P.; Rao, S.; Du, G.; Griffin, J.D.; Sorger, P.K.; Marto, J.A.; Westover, K.D.; Gray, N.S. Structure-guided development of covalent TAK1 inhibitors. Bioorg. Med. Chem.,  2017, 25(3), 838-846.
[http://dx.doi.org/10.1016/j.bmc.2016.11.035] [PMID: 28011204] 
[15] 
Sethi, A.; Joshi, K.; Sasikala, K.; Alvala, M. Molecular docking in dern drug discovery: Principles and recent applications.Drug Discovery and Development-New Advances:; InTechOpen: London, 2019. 
[16] 
Tan, L.; Gurbani, D.; Weisberg, E.L.; Jones, D.S.; Rao, S.; Singer, W.D.; Bernard, F.M.; Mowafy, S.; Jenney, A.; Du, G.; Nonami, A.; Griffin, J.D.; Lauffenburger, D.A.; Westover, K.D.; Sorger, P.K.; Gray, N.S. Studies of TAK1-centered polypharmacology with novel covalent TAK1 inhibitors. Bioorg. Med. Chem.,  2017, 25(4), 1320-1328.
[http://dx.doi.org/10.1016/j.bmc.2016.11.034] [PMID: 28038940] 
[17] 
Rule, S.; Chen, R.W. New and emerging Bruton tyrosine kinase inhibitors for treating mantle cell lymphoma - where do they fit in? Expert Rev. Hematol.,  2018, 11(9), 749-756.
[http://dx.doi.org/10.1080/17474086.2018.1506327] [PMID: 30052472] 
[18] 
Akinleye, A.; Chen, Y.; Mukhi, N.; Song, Y.; Liu, D. Ibrutinib and novel BTK inhibitors in clinical development. J. Hematol. Oncol.,  2013, 6(1), 59.
[http://dx.doi.org/10.1186/1756-8722-6-59] [PMID: 23958373] 
[19] 
Yu, L.; Mohamed, A.J.; Simonson, O.E.; Vargas, L.; Blomberg, K.E.M.; Björkstrand, B.; Arteaga, H.J.; Nore, B.F.; Smith, C.I. Proteasome-dependent autoregulation of Bruton tyrosine kinase (Btk) promoter via NF-kappaB. Blood,  2008, 111(9), 4617-4626.
[http://dx.doi.org/10.1182/blood-2007-10-121137] [PMID: 18292289] 
[20] 
Wang, Z.; Fang, Y.; Teague, J.; Wong, H.; Morisseau, C.; Hammock, B.D.; Rock, D.A.; Wang, Z. In vitro metabolism of oprozomib, an oral proteasome inhibitor: role of epoxide hydrolases and cytochrome P450s. Drug Metab. Dispos.,  2017, 45(7), 712-720.
[http://dx.doi.org/10.1124/dmd.117.075226] [PMID: 28428366] 
[21] 
Archer, C.R.; Koomoa, D.L.T.; Mitsunaga, E.M.; Clerc, J.; Shimizu, M.; Kaiser, M.; Schellenberg, B.; Dudler, R.; Bachmann, A.S. Syrbactin class proteasome inhibitor-induced apoptosis and autophagy occurs in association with p53 accumulation and Akt/PKB activation in neuroblastoma. Biochem. Pharmacol.,  2010, 80(2), 170-178.
[http://dx.doi.org/10.1016/j.bcp.2010.03.031] [PMID: 20362557] 
[22] 
Teronen, O.; Heikkilä, P.; Konttinen, Y.T.; Laitinen, M.; Salo, T.; Hanemaaijer, R.; Teronen, A.; Maisi, P.; Sorsa, T. MMP inhibition and downregulation by bisphosphonates. Ann. N. Y. Acad. Sci.,  1999, 878(1), 453-465.
[http://dx.doi.org/10.1111/j.1749-6632.1999.tb07702.x] [PMID: 10415748] 
[23] 
Jia, F.; Yin, Y.H.; Gao, G.Y.; Wang, Y.; Cen, L.; Jiang, J.Y. MMP-9 inhibitor SB-3CT attenuates behavioral impairments and hippocampal loss after traumatic brain injury in rat. J. Neurotrauma,  2014, 31(13), 1225-1234.
[http://dx.doi.org/10.1089/neu.2013.3230] [PMID: 24661104] 
[24] 
Buglio, D.; Palakurthi, S.; Byth, K.; Vega, F.; Toader, D.; Saeh, J.; Neelapu, S.S.; Younes, A. Essential role of TAK1 in regulating mantle cell lymphoma survival. Blood,  2012, 120(2), 347-355.
[http://dx.doi.org/10.1182/blood-2011-07-369397] [PMID: 22649101] 
[25] 
Totzke, J.; Gurbani, D.; Raphemot, R.; Hughes, P.F.; Bodoor, K.; Carlson, D.A.; Loiselle, D.R.; Bera, A.K.; Eibschutz, L.S.; Perkins, M.M.; Eubanks, A.L.; Campbell, P.L.; Fox, D.A.; Westover, K.D.; Haystead, T.A.J.; Derbyshire, E.R. Takinib, a selective TAK1 inhibitor, broadens the therapeutic efficacy of TNF-α inhibition for cancer and autoimmune disease. Cell Chem. Biol.,  2017, 24(8), 1029-1039.e7.
[http://dx.doi.org/10.1016/j.chembiol.2017.07.011] [PMID: 28820959] 
[26] 
McIver, E.G.; Bryans, J.; Birchall, K.; Chugh, J.; Drake, T.; Lewis, S.J.; Osborne, J.; Smiljanic-Hurley, E.; Tsang, W.; Kamal, A.; Levy, A.; Newman, M.; Taylor, D.; Arthur, J.S.; Clark, K.; Cohen, P. Synthesis and structure-activity relationships of a novel series of pyrimidines as potent inhibitors of TBK1/IKKε kinases. Bioorg. Med. Chem. Lett.,  2012, 22(23), 7169-7173.
[http://dx.doi.org/10.1016/j.bmcl.2012.09.063] [PMID: 23099093] 
[27] 
Muraoka, T.; Ide, M.; Morikami, K.; Irie, M.; Nakamura, M.; Miura, T.; Kamikawa, T.; Nishihara, M.; Kashiwagi, H. Discovery of a potent and highly selective transforming growth factor β receptor-associated kinase 1 (TAK1) inhibitor by structure based drug design (SBDD). Bioorg. Med. Chem.,  2016, 24(18), 4206-4217.
[http://dx.doi.org/10.1016/j.bmc.2016.07.006] [PMID: 27448772] 
[28] 
Hornberger, K.R.; Chen, X.; Crew, A.P.; Kleinberg, A.; Ma, L.; Mulvihill, M.J.; Wang, J.; Wilde, V.L.; Albertella, M.; Bittner, M.; Cooke, A.; Kadhim, S.; Kahler, J.; Maresca, P.; May, E.; Meyn, P.; Romashko, D.; Tokar, B.; Turton, R. Discovery of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1: optimization of kinase selectivity and pharmacokinetics. Bioorg. Med. Chem. Lett.,  2013, 23(16), 4511-4516.
[http://dx.doi.org/10.1016/j.bmcl.2013.06.054] [PMID: 23856049] 
[29] 
Ninomiya-Tsuji, J.; Kajino, T.; Ono, K.; Ohtomo, T.; Matsumoto, M.; Shiina, M.; Mihara, M.; Tsuchiya, M.; Matsumoto, K. A resorcylic acid lactone, 5Z-7-oxozeaenol, prevents inflammation by inhibiting the catalytic activity of TAK1 MAPK kinase kinase. J. Biol. Chem.,  2003, 278(20), 18485-18490.
[http://dx.doi.org/10.1074/jbc.M207453200] [PMID: 12624112] 
[30] 
Huang, X.; Luan, B.; Wu, J.; Shi, Y. An atomic structure of the human 26S proteasome. Nat. Struct. Mol. Biol.,  2016, 23(9), 778-785.
[http://dx.doi.org/10.1038/nsmb.3273] [PMID: 27428775] 
[31] 
Bradshaw, J.M.; McFarland, J.M.; Paavilainen, V.O.; Bisconte, A.; Tam, D.; Phan, V.T.; Romanov, S.; Finkle, D.; Shu, J.; Patel, V.; Ton, T.; Li, X.; Loughhead, D.G.; Nunn, P.A.; Karr, D.E.; Gerritsen, M.E.; Funk, J.O.; Owens, T.D.; Verner, E.; Brameld, K.A.; Hill, R.J.; Goldstein, D.M.; Taunton, J. Prolonged and tunable residence time using reversible covalent kinase inhibitors. Nat. Chem. Biol.,  2015, 11(7), 525-531.
[http://dx.doi.org/10.1038/nchembio.1817] [PMID: 26006010] 
[32] 
Elkins, P.A.; Ho, Y.S.; Smith, W.W.; Janson, C.A.; D’Alessio, K.J.; McQueney, M.S.; Cummings, M.D.; Romanic, A.M. Structure of the C-terminally truncated human ProMMP9, a gelatin-binding matrix metalloproteinase. Acta Crystallogr. D Biol. Crystallogr.,  2002, 58(Pt 7), 1182-1192.
[http://dx.doi.org/10.1107/S0907444902007849] [PMID: 12077439] 
[33] 
Hornberger, K.R.; Berger, D.M.; Crew, A.P.; Dong, H.; Kleinberg, A.; Li, A.H.; Medeiros, M.R.; Mulvihill, M.J.; Siu, K.; Tarrant, J.; Wang, J.; Weng, F.; Wilde, V.L.; Albertella, M.; Bittner, M.; Cooke, A.; Gray, M.J.; Maresca, P.; May, E.; Meyn, P.; Peick, W., Jr; Romashko, D.; Tanowitz, M.; Tokar, B. Discovery and optimization of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1. Bioorg. Med. Chem. Lett.,  2013, 23(16), 4517-4522.
[http://dx.doi.org/10.1016/j.bmcl.2013.06.053] [PMID: 23850198] 
[34] 
Liu, M.; Yuan, M.; Luo, M.; Bu, X.; Luo, H.B.; Hu, X. Binding of curcumin with glyoxalase I: Molecular docking, molecular dynamics simulations, and kinetics analysis. Biophys. Chem.,  2010, 147(1-2), 28-34.
[http://dx.doi.org/10.1016/j.bpc.2009.12.007] [PMID: 20071071] 
[35] 
Okimoto, N.; Futatsugi, N.; Fuji, H.; Suenaga, A.; Morimoto, G.; Yanai, R.; Ohno, Y.; Narumi, T.; Taiji, M. High-performance drug discovery: computational screening by combining docking and molecular dynamics simulations. PLOS Comput. Biol.,  2009, 5(10), e1000528.
[http://dx.doi.org/10.1371/journal.pcbi.1000528] [PMID: 19816553] 
[36] 
Shen, M.; Zhou, S.; Li, Y.; Pan, P.; Zhang, L.; Hou, T. Discovery and optimization of triazine derivatives as ROCK1 inhibitors: molecular docking, molecular dynamics simulations and free energy calculations. Mol. Biosyst.,  2013, 9(3), 361-374.
[http://dx.doi.org/10.1039/c2mb25408e] [PMID: 23340525] 
[37] 
Shen, J.; Zhang, W.; Fang, H.; Perkins, R.; Tong, W.; Hong, H. Homology modeling, molecular docking, and molecular dynamics simulations elucidated α-fetoprotein binding modes. BMC Bioinformatics,  2013, 14(14)(Suppl. 14), S6.
[http://dx.doi.org/10.1186/1471-2105-14-S14-S6] [PMID: 24266910] 
[38] 
Di Nola, A.; Roccatano, D.; Berendsen, H.J. Molecular dynamics simulation of the docking of substrates to proteins. Proteins,  1994, 19(3), 174-182.
[http://dx.doi.org/10.1002/prot.340190303] [PMID: 7937732] 
[39] 
Keretsu, S.; Bhujbal, S.P.; Cho, S.J. Rational approach toward COVID-19 main protease inhibitors via molecular docking, molecular dynamics simulation and free energy calculation. Sci. Rep.,  2020, 10(1), 17716.
[http://dx.doi.org/10.1038/s41598-020-74468-0] [PMID: 33077821] 
[40] 
Salmaso, V.; Moro, S. Bridging molecular docking to molecular dynamics in exploring ligand-protein recognition process: An overview. Front. Pharmacol.,  2018, 9, 923.
[http://dx.doi.org/10.3389/fphar.2018.00923] [PMID: 30186166] 
[41] 
Wang, Z.; Chen, G.; Chen, L.; Liu, X.; Fu, W.; Zhang, Y.; Li, C.; Liang, G.; Cai, Y. Insights into the binding mode of curcumin to MD-2: studies from molecular docking, molecular dynamics simulations and experimental assessments. Mol. Biosyst.,  2015, 11(7), 1933-1938.
[http://dx.doi.org/10.1039/C5MB00085H] [PMID: 25923908] 
[42] 
Rampogu, S.; Baek, A.; Gajula, R.G.; Zeb, A.; Bavi, R.S.; Kumar, R.; Kim, Y.; Kwon, Y.J.; Lee, K.W. Ginger (Zingiber officinale) phytochemicals-gingerenone-A and shogaol inhibit SaHPPK: molecular docking, molecular dynamics simulations and in vitro approaches. Ann. Clin. Microbiol. Antimicrob.,  2018, 17(1), 16.
[http://dx.doi.org/10.1186/s12941-018-0266-9] [PMID: 29609660] 
[43] 
Wang, W.; Tian, Y.; Wan, Y.; Gu, S.; Ju, X.; Luo, X.; Liu, G. Insights into the key structural features of N 1-ary-benzimidazols as HIV-1 NNRTIs using molecular docking, molecular dynamics, 3D-QSAR, and pharmacophore modeling. Struct. Chem.,  2019, 30(1), 385-397.
[http://dx.doi.org/10.1007/s11224-018-1204-3] 
[44] 
Aouidate, A.; Ghaleb, A.; Chtita, S.; Aarjane, M.; Ousaa, A.; Maghat, H.; Sbai, A.; Choukrad, M.; Bouachrine, M.; Lakhlifi, T. Identification of a novel dual-target scaffold for 3CLpro and RdRp proteins of SARS-CoV-2 using 3D-similarity search, molecular docking, molecular dynamics and ADMET evaluation. J. Biomol. Struct. Dyn.,  2020, 1-14. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1779130] [PMID: 32552534] 
[45] 
Wang, Y.Q.; Lin, W.W.; Wu, N.; Wang, S.Y.; Chen, M.Z.; Lin, Z.H.; Xie, X.Q.; Feng, Z.W. Structural insight into the serotonin (5-HT) receptor family by molecular docking, molecular dynamics simulation and systems pharmacology analysis. Acta Pharmacol. Sin.,  2019, 40(9), 1138-1156.
[http://dx.doi.org/10.1038/s41401-019-0217-9] [PMID: 30814658] 
[46] 
Safarizadeh, H.; Garkani-Nejad, Z. Molecular docking, molecular dynamics simulations and QSAR studies on some of 2-arylethenylquinoline derivatives for inhibition of Alzheimer’s amyloid-beta aggregation: Insight into mechanism of interactions and parameters for design of new inhibitors. J. Mol. Graph. Model.,  2019, 87, 129-143.
[http://dx.doi.org/10.1016/j.jmgm.2018.11.019] [PMID: 30537643] 
[47] 
Hu, W.; Deng, S.; Huang, J.; Lu, Y.; Le, X.; Zheng, W. Intercalative interaction of asymmetric copper(II) complex with DNA: experimental, molecular docking, molecular dynamics and TDDFT studies. J. Inorg. Biochem.,  2013, 127, 90-98.
[http://dx.doi.org/10.1016/j.jinorgbio.2013.07.034] [PMID: 23962499] 
[48] 
Zhang, S.; Yang, H.; Zhao, L.; Gan, R.; Tang, P.; Sun, Q.; Xiong, X.; Li, H. Capecitabine as a minor groove binder of DNA: molecular docking, molecular dynamics, and multi-spectroscopic studies. J. Biomol. Struct. Dyn.,  2019, 37(6), 1451-1463.
[http://dx.doi.org/10.1080/07391102.2018.1461137] [PMID: 29620482] 
[49] 
Khelfaoui, H.; Harkati, D.; Saleh, B.A. Molecular docking, molecular dynamics simulations and reactivity, studies on approved drugs library targeting ACE2 and SARS-CoV-2 binding with ACE2. J. Biomol. Struct. Dyn.,  2020, 1-17. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1803967] [PMID: 32752951] 
[50] 
Sharma, V.K.; Nandekar, P.P.; Sangamwar, A.; Pérez-Sánchez, H.; Agarwal, S.M. Structure guided design and binding analysis of EGFR inhibiting analogues of erlotinib and AEE788 using ensemble docking, molecular dynamics and MM-GBSA. RSC Advances,  2016, 6(70), 65725-65735.
[http://dx.doi.org/10.1039/C6RA08517B] 
[51] 
Elkarhat, Z.; Charoute, H.; Elkhattabi, L.; Barakat, A.; Rouba, H. Potential inhibitors of SARS-cov-2 RNA dependent RNA polymerase protein: molecular docking, molecular dynamics simulations and MM-PBSA analyses. J. Biomol. Struct. Dyn.,  2020, 1-14. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1813628] [PMID: 32873176] 
[52] 
Zhu, J.; Wu, Y.; Xu, L.; Jin, J. Theoretical studies on the selectivity mechanisms of glycogen synthase kinase 3β (gsk3β) with pyrazine atp-competitive inhibitors by 3dqsar, molecular docking, molecular dynamics simulation and free energy calculations. Curr Comput Aided Drug Des,  2020, 16(1), 17-30.
[http://dx.doi.org/10.2174/1573409915666190708102459] [PMID: 31284868] 
[53] 
Naqvi, A.A.T.; Mohammad, T.; Hasan, G.M.; Hassan, M.I. Advancements in docking and molecular dynamics simulations towards ligand-receptor interactions and structure-function relationships. Curr. Top. Med. Chem.,  2018, 18(20), 1755-1768.
[http://dx.doi.org/10.2174/1568026618666181025114157] [PMID: 30360721] 
[54] 
Anusuya, S.; Gromiha, M.M. Quercetin derivatives as non-nucleoside inhibitors for dengue polymerase: molecular docking, molecular dynamics simulation, and binding free energy calculation. J. Biomol. Struct. Dyn.,  2017, 35(13), 2895-2909.
[http://dx.doi.org/10.1080/07391102.2016.1234416] [PMID: 27608509] 
[55] 
Lu, S.Y.; Jiang, Y.J.; Lv, J.; Wu, T.X.; Yu, Q.S.; Zhu, W.L. Molecular docking and molecular dynamics simulation studies of GPR40 receptor-agonist interactions. J. Mol. Graph. Model.,  2010, 28(8), 766-774.
[http://dx.doi.org/10.1016/j.jmgm.2010.02.001] [PMID: 20227312] 
[56] 
Lengauer, T.; Rarey, M. Computational methods for biomolecular docking. Curr. Opin. Struct. Biol.,  1996, 6(3), 402-406.
[http://dx.doi.org/10.1016/S0959-440X(96)80061-3] [PMID: 8804827] 
[57] 
Gao, Y.; Chen, Y.; Tian, Y.; Zhao, Y.; Wu, F.; Luo, X. In silico study of 3-hydroxypyrimidine-2, 4-diones as inhibitors of HIV RT-associated RNase H using molecular docking, molecular dynamics, 3D-QSAR, and pharmacophore models. New J. Chem.,  2019, 43(43), 17004-17017.
[http://dx.doi.org/10.1039/C9NJ03353J] 
[58] 
Pak, Y.; Wang, S. Application of a molecular dynamics simulation method with a generalized effective potential to the flexible molecular docking problems. J. Phys. Chem. B,  2000, 104(2), 354-359.
[http://dx.doi.org/10.1021/jp993073h] 
[59] 
Ghanbari-Ardestani, S.; Khojasteh-Band, S.; Zaboli, M.; Hassani, Z.; Mortezavi, M.; Mahani, M.; Torkzadeh-Mahani, M. The effect of different percentages of triethanolammonium butyrate ionic liquid on the structure and activity of urate oxidase: Molecular docking, molecular dynamics simulation, and experimental study. J. Mol. Liq.,  2019, 292, 111318.
[http://dx.doi.org/10.1016/j.molliq.2019.111318] 
[60] 
Manjula, S.; Kumaradhas, P. Evaluating the suitability of RNA intervention mechanism exerted by some flavonoid molecules against dengue virus MTase RNA capping site: a molecular docking, molecular dynamics simulation, and binding free energy study. J. Biomol. Struct. Dyn.,  2020, 38(12), 3533-3543.
[http://dx.doi.org/10.1080/07391102.2019.1666744] [PMID: 31514688] 
[61] 
Zhao, P.; Chen, S.K.; Cai, Y.H.; Lu, X.; Li, Z.; Cheng, Y.K.; Zhang, C.; Hu, X.; He, X.; Luo, H.B. The molecular basis for the inhibition of phosphodiesterase-4D by three natural resveratrol analogs. Isolation, molecular docking, molecular dynamics simulations, binding free energy, and bioassay. Biochim. Biophys. Acta,  2013, 1834(10), 2089-2096.
[http://dx.doi.org/10.1016/j.bbapap.2013.07.004] [PMID: 23871879] 
[62] 
Rajamanikandan, S.; Jeyakanthan, J.; Srinivasan, P. Molecular docking, molecular dynamics simulations, computational screening to design quorum sensing inhibitors targeting LuxP of Vibrio harveyi and its biological evaluation. Appl. Biochem. Biotechnol.,  2017, 181(1), 192-218.
[http://dx.doi.org/10.1007/s12010-016-2207-4] [PMID: 27535409] 
[63] 
Yuan, Y.; Hu, Z.; Bao, M.; Sun, R.; Long, X.; Long, L.; Li, J.; Wu, C.; Bao, J. Screening of novel histone deacetylase 7 inhibitors through molecular docking followed by a combination of molecular dynamics simulations and ligand-based approach. J. Biomol. Struct. Dyn.,  2019, 37(15), 4092-4103.
[http://dx.doi.org/10.1080/07391102.2018.1541141] [PMID: 30417746] 
[64] 
Shahlaei, M.; Madadkar-Sobhani, A.; Mahnam, K.; Fassihi, A.; Saghaie, L.; Mansourian, M. Homology modeling of human CCR5 and analysis of its binding properties through molecular docking and molecular dynamics simulation. Biochim. Biophys. Acta,  2011, 1808(3), 802-817.
[http://dx.doi.org/10.1016/j.bbamem.2010.12.004] [PMID: 21167131] 
[65] 
Cao, H.; Sun, Y.; Wang, L.; Zhao, C.; Fu, J.; Zhang, A. Understanding the microscopic binding mechanism of hydroxylated and sulfated polybrominated diphenyl ethers with transthyretin by molecular docking, molecular dynamics simulations and binding free energy calculations. Mol. Biosyst.,  2017, 13(4), 736-749.
[http://dx.doi.org/10.1039/C6MB00638H] [PMID: 28217795] 
[66] 
Ghamari, N.; Zarei, O.; Reiner, D.; Dastmalchi, S.; Stark, H.; Hamzeh-Mivehroud, M. Histamine H3 receptor ligands by hybrid virtual screening, docking, molecular dynamics simulations, and investigation of their biological effects. Chem. Biol. Drug Des.,  2019, 93(5), 832-843.
[http://dx.doi.org/10.1111/cbdd.13471] [PMID: 30586225] 
[67] 
Fang, J.; Wu, P.; Yang, R.; Gao, L.; Li, C.; Wang, D.; Wu, S.; Liu, A.L.; Du, G.H. Inhibition of acetylcholinesterase by two genistein derivatives: kinetic analysis, molecular docking and molecular dynamics simulation. Acta Pharm. Sin. B,  2014, 4(6), 430-437.
[http://dx.doi.org/10.1016/j.apsb.2014.10.002] [PMID: 26579414] 
[68] 
Liu, Y.; Liu, Z.; Zeng, G.; Chen, M.; Jiang, Y.; Shao, B.; Li, Z.; Liu, Y. Effect of surfactants on the interaction of phenol with laccase: Molecular docking and molecular dynamics simulation studies. J. Hazard. Mater.,  2018, 357, 10-18.
[http://dx.doi.org/10.1016/j.jhazmat.2018.05.042] [PMID: 29859460] 
[69] 
Ismail, N.A.; Jusoh, S.A. Molecular docking and molecular dynamics simulation studies to predict flavonoid binding on the surface of DENV2 E protein. Interdiscip. Sci.,  2017, 9(4), 499-511.
[http://dx.doi.org/10.1007/s12539-016-0157-8] [PMID: 26969331] 
[70] 
Hathout, R.M.; Metwally, A.A. Towards better modelling of drug-loading in solid lipid nanoparticles: Molecular dynamics, docking experiments and Gaussian Processes machine learning. Eur. J. Pharm. Biopharm.,  2016, 108, 262-268.
[http://dx.doi.org/10.1016/j.ejpb.2016.07.019] [PMID: 27449631] 
[71] 
Samsonov, S.A.; Gehrcke, J.P.; Pisabarro, M.T. Flexibility and explicit solvent in molecular-dynamics-based docking of protein-glycosaminoglycan systems. J. Chem. Inf. Model.,  2014, 54(2), 582-592.
[http://dx.doi.org/10.1021/ci4006047] [PMID: 24479827] 
[72] 
Ahmed, B.; Ali Ashfaq, U.; Usman Mirza, M. Medicinal plant phytochemicals and their inhibitory activities against pancreatic lipase: molecular docking combined with molecular dynamics simulation approach. Nat. Prod. Res.,  2018, 32(10), 1123-1129.
[http://dx.doi.org/10.1080/14786419.2017.1320786] [PMID: 28446025] 
[73] 
Zhou, H.; Wang, C.; Deng, T.; Tao, R.; Li, W. Novel urushiol derivatives as HDAC8 inhibitors: rational design, virtual screening, molecular docking and molecular dynamics studies. J. Biomol. Struct. Dyn.,  2018, 36(8), 1966-1978.
[http://dx.doi.org/10.1080/07391102.2017.1344568] [PMID: 28632421] 
[74] 
Cui, F.; Yang, K.; Li, Y. Investigate the binding of catechins to trypsin using docking and molecular dynamics simulation. PLoS One,  2015, 10(5), e0125848.
[http://dx.doi.org/10.1371/journal.pone.0125848] [PMID: 25938485] 
[75] 
Durdagi, S.; Mavromoustakos, T.; Papadopoulos, M.G. 3D QSAR CoMFA/CoMSIA, molecular docking and molecular dynamics studies of fullerene-based HIV-1 PR inhibitors. Bioorg. Med. Chem. Lett.,  2008, 18(23), 6283-6289.
[http://dx.doi.org/10.1016/j.bmcl.2008.09.107] [PMID: 18951793] 
[76] 
Ji, B.; Liu, S.; He, X.; Man, V.H.; Xie, X.Q.; Wang, J. Prediction of the binding affinities and selectivity for cb1 and cb2 ligands using homology modeling, molecular docking, molecular dynamics simulations, and mm-pbsa binding free energy calculations. ACS Chem. Neurosci.,  2020, 11(8), 1139-1158.
[http://dx.doi.org/10.1021/acschemneuro.9b00696] [PMID: 32196303] 
[77] 
Sakkiah, S.; Arooj, M.; Kumar, M.R.; Eom, S.H.; Lee, K.W. Identification of inhibitor binding site in human sirtuin 2 using molecular docking and dynamics simulations. PLoS One,  2013, 8(1), e51429.
[http://dx.doi.org/10.1371/journal.pone.0051429] [PMID: 23382805] 
[78] 
Sabbadin, D.; Ciancetta, A.; Moro, S. Bridging molecular docking to membrane molecular dynamics to investigate GPCR-ligand recognition: the human A2A adenosine receptor as a key study. J. Chem. Inf. Model.,  2014, 54(1), 169-183.
[http://dx.doi.org/10.1021/ci400532b] [PMID: 24359090] 
[79] 
Azam, F.; Alabdullah, N.H.; Ehmedat, H.M.; Abulifa, A.R.; Taban, I.; Upadhyayula, S. NSAIDs as potential treatment option for preventing amyloid β toxicity in Alzheimer’s disease: an investigation by docking, molecular dynamics, and DFT studies. J. Biomol. Struct. Dyn.,  2018, 36(8), 2099-2117.
[http://dx.doi.org/10.1080/07391102.2017.1338164] [PMID: 28571516] 
[80] 
Sharma, M.; Jha, P.; Verma, P.; Chopra, M. Combined comparative molecular field analysis, comparative molecular similarity indices analysis, molecular docking and molecular dynamics studies of histone deacetylase 6 inhibitors. Chem. Biol. Drug Des.,  2019, 93(5), 910-925.
[http://dx.doi.org/10.1111/cbdd.13488] [PMID: 30667160] 
[81] 
Botelho, F.D.; Dos Santos, M.C.; Gonçalves, A.D.S.; Kuca, K.; Valis, M.; LaPlante, S.R.; França, T.C.C.; de Almeida, J.S.F.D. Ligand-Based Virtual Screening, Molecular Docking, Molecular Dynamics, and MM-PBSA Calculations towards the Identification of Potential Novel Ricin Inhibitors. Toxins (Basel),  2020, 12(12), 746.
[http://dx.doi.org/10.3390/toxins12120746] [PMID: 33256167] 
[82] 
Wang, M.; Wang, Y.; Kong, D.; Jiang, H.; Wang, J.; Cheng, M. In silico exploration of aryl sulfonamide analogs as voltage-gated sodium channel 1.7 inhibitors by using 3D-QSAR, molecular docking study, and molecular dynamics simulations. Comput. Biol. Chem.,  2018, 77, 214-225.
[http://dx.doi.org/10.1016/j.compbiolchem.2018.10.009] [PMID: 30359866] 
[83] 
Park, J.Y.; Harris, D. Construction and assessment of models of CYP2E1: predictions of metabolism from docking, molecular dynamics, and density functional theoretical calculations. J. Med. Chem.,  2003, 46(9), 1645-1660.
[http://dx.doi.org/10.1021/jm020538a] [PMID: 12699383] 
[84] 
Saxena, S.; Abdullah, M.; Sriram, D.; Guruprasad, L. Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations. J. Biomol. Struct. Dyn.,  2018, 36(12), 3184-3198.
[http://dx.doi.org/10.1080/07391102.2017.1384398] [PMID: 28948866] 
[85] 
Daoud, I.; Melkemi, N.; Salah, T.; Ghalem, S. Combined QSAR, molecular docking and molecular dynamics study on new Acetylcholinesterase and Butyrylcholinesterase inhibitors. Comput. Biol. Chem.,  2018, 74, 304-326.
[http://dx.doi.org/10.1016/j.compbiolchem.2018.03.021] [PMID: 29747032] 
[86] 
Ding, X.; Suo, Z.; Sun, Q.; Gan, R.; Tang, P.; Hou, Q.; Wu, D.; Li, H. Study of the interaction of broad-spectrum antimicrobial drug sitafloxacin with human serum albumin using spectroscopic methods, molecular docking, and molecular dynamics simulation. J. Pharm. Biomed. Anal.,  2018, 160, 397-403.
[http://dx.doi.org/10.1016/j.jpba.2018.07.053] [PMID: 30125733] 
[87] 
Kumar, A.; Srivastava, G.; Negi, A.S.; Sharma, A. Docking, molecular dynamics, binding energy-MM-PBSA studies of naphthofuran derivatives to identify potential dual inhibitors against BACE-1 and GSK-3β. J. Biomol. Struct. Dyn.,  2019, 37(2), 275-290.
[http://dx.doi.org/10.1080/07391102.2018.1426043] [PMID: 29310523] 
[88] 
Jalkute, C.B.; Barage, S.H.; Dhanavade, M.J.; Sonawane, K.D. Molecular dynamics simulation and molecular docking studies of Angiotensin converting enzyme with inhibitor lisinopril and amyloid Beta Peptide. Protein J.,  2013, 32(5), 356-364.
[http://dx.doi.org/10.1007/s10930-013-9492-3] [PMID: 23660814] 
[89] 
Hayes, J.M.; Skamnaki, V.T.; Archontis, G.; Lamprakis, C.; Sarrou, J.; Bischler, N.; Skaltsounis, A.L.; Zographos, S.E.; Oikonomakos, N.G. Kinetics, in silico docking, molecular dynamics, and MM-GBSA binding studies on prototype indirubins, KT5720, and staurosporine as phosphorylase kinase ATP-binding site inhibitors: the role of water molecules examined. Proteins,  2011, 79(3), 703-719.
[http://dx.doi.org/10.1002/prot.22890] [PMID: 21287607] 
[90] 
Mosquera-Yuqui, F.; Lopez-Guerra, N.; Moncayo-Palacio, E.A. Targeting the 3CLpro and RdRp of SARS-CoV-2 with phytochemicals from medicinal plants of the Andean Region: molecular docking and molecular dynamics simulations. J. Biomol. Struct. Dyn.,  2020, 1-14. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020] [PMID: 33084512] 
[91] 
Li, X.; Ye, L.; Wang, X.; Wang, X.; Liu, H.; Zhu, Y.; Yu, H. Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β. Toxicol. Appl. Pharmacol.,  2012, 265(3), 300-307.
[http://dx.doi.org/10.1016/j.taap.2012.08.030] [PMID: 22982074] 
[92] 
Patel, C.N.; Kumar, S.P.; Pandya, H.A.; Rawal, R.M. Identification of potential inhibitors of coronavirus hemagglutinin-esterase using molecular docking, molecular dynamics simulation and binding free energy calculation. Mol. Divers.,  2020, 1-13. (Online ahead of Print).
[http://dx.doi.org/10.1007/s11030-020-10135-w ] [PMID: 32996011] 
[93] 
Singh, N.; Tiwari, S.; Srivastava, K.K.; Siddiqi, M.I. Identification of novel inhibitors of Mycobacterium tuberculosis PknG using pharmacophore based virtual screening, docking, molecular dynamics simulation, and their biological evaluation. J. Chem. Inf. Model.,  2015, 55(6), 1120-1129.
[http://dx.doi.org/10.1021/acs.jcim.5b00150] [PMID: 25965448] 
[94] 
Raj, S.; Sasidharan, S.; Dubey, V.K.; Saudagar, P. Identification of lead molecules against potential drug target protein MAPK4 from L. donovani: An in-silico approach using docking, molecular dynamics and binding free energy calculation. PLoS One,  2019, 14(8), e0221331.
[http://dx.doi.org/10.1371/journal.pone.0221331] [PMID: 31425543] 
[95] 
Joshi, T.; Joshi, T.; Sharma, P.; Chandra, S.; Pande, V. Molecular docking and molecular dynamics simulation approach to screen natural compounds for inhibition of Xanthomonas oryzae pv. Oryzae by targeting peptide deformylase. J. Biomol. Struct. Dyn.,  2020, 1-18. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1719200] [PMID: 31965918] 
[96] 
Yu, H.; Fang, Y.; Lu, X.; Liu, Y.; Zhang, H. Combined 3D-QSAR, molecular docking, molecular dynamics simulation, and binding free energy calculation studies on the 5-hydroxy-2H-pyridazin-3-one derivatives as HCV NS5B polymerase inhibitors. Chem. Biol. Drug Des.,  2014, 83(1), 89-105.
[http://dx.doi.org/10.1111/cbdd.12203] [PMID: 23941500] 
[97] 
Minini, L.; Álvarez, G.; González, M.; Cerecetto, H.; Merlino, A. Molecular docking and molecular dynamics simulation studies of Trypanosoma cruzi triosephosphate isomerase inhibitors. Insights into the inhibition mechanism and selectivity. J. Mol. Graph. Model.,  2015, 58, 40-49.
[http://dx.doi.org/10.1016/j.jmgm.2015.02.002] [PMID: 25829097] 
[98] 
Guttikonda, V.; Raavi, D.; Maadwar, S.K.; Gade, D.R. Molecular insights of benzodipyrazole as CDK2 inhibitors: combined molecular docking, molecular dynamics, and 3D QSAR studies. J. Recept. Signal Transduct. Res.,  2015, 35(5), 439-449.
[http://dx.doi.org/10.3109/10799893.2015.1018433] [PMID: 25902329] 
[99] 
Braga, R.C.; Alves, V.M.; Fraga, C.A.; Barreiro, E.J.; de Oliveira, V.; Andrade, C.H. Combination of docking, molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone. J. Mol. Model.,  2012, 18(5), 2065-2078.
[http://dx.doi.org/10.1007/s00894-011-1219-9] [PMID: 21901409] 
[100] 
Keretsu, S.; Bhujbal, S.P.; Cho, S.J. Molecular modeling studies of pyrrolo[2,3-d]pyrimidin-4-amine derivatives as JAK1 inhibitors based on 3D-QSAR, molecular docking, molecular dynamics (MD) and MM-PBSA calculations. J. Biomol. Struct. Dyn.,  2020, 1-13. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1714483] [PMID: 31916502] 
[101] 
Azam, M.A.; Jupudi, S.; Saha, N.; Paul, R.K. Combining molecular docking and molecular dynamics studies for modelling Staphylococcus aureus MurD inhibitory activity. SAR QSAR Environ. Res.,  2019, 30(1), 1-20.
[http://dx.doi.org/10.1080/1062936X.2018.1539034] [PMID: 30406684] 
[102] 
Kumar, V.; Saravanan, P.; Arvind, A.; Mohan, C.G. Identification of hotspot regions of MurB oxidoreductase enzyme using homology modeling, molecular dynamics and molecular docking techniques. J. Mol. Model.,  2011, 17(5), 939-953.
[http://dx.doi.org/10.1007/s00894-010-0788-3] [PMID: 20614148] 
[103] 
Rasool, N.; Hussain, W. Three major phosphoacceptor sites in hiv-1 capsid protein enhances its structural stability and resistance against the inhibitor: explication through molecular dynamics simulation, molecular docking and dft analysis. Comb. Chem. High Throughput Screen.,  2020, 23(1), 41-54.
[http://dx.doi.org/10.2174/1386207323666191213142223] [PMID: 31838993] 
[104] 
Shahraki, O.; Zargari, F.; Edraki, N.; Khoshneviszadeh, M.; Firuzi, O.; Miri, R. Molecular dynamics simulation and molecular docking studies of 1,4-Dihydropyridines as P-glycoprotein’s allosteric inhibitors. J. Biomol. Struct. Dyn.,  2018, 36(1), 112-125.
[http://dx.doi.org/10.1080/07391102.2016.1268976] [PMID: 27981890] 
[105] 
Li, C.; Wang, J.X.; Le, Y.; Chen, J.F. Studies of bicalutamide-excipients interaction by combination of molecular docking and molecular dynamics simulation. Mol. Pharm.,  2013, 10(6), 2362-2369.
[http://dx.doi.org/10.1021/mp300727d] [PMID: 23646858] 
[106] 
Berishvili, V.P.; Kuimov, A.N.; Voronkov, A.E.; Radchenko, E.V.; Kumar, P.; Choonara, Y.E.; Pillay, V.; Kamal, A.; Palyulin, V.A. Discovery of novel tankyrase inhibitors through molecular docking-based virtual screening and molecular dynamics simulation studies. Molecules,  2020, 25(14), 3171.
[http://dx.doi.org/10.3390/molecules25143171] [PMID: 32664504] 
[107] 
Wahl, J.; Smieško, M. Endocrine disruption at the androgen receptor: employing molecular dynamics and docking for improved virtual screening and toxicity prediction. Int. J. Mol. Sci.,  2018, 19(6), 1784.
[http://dx.doi.org/10.3390/ijms19061784] [PMID: 29914135] 
[108] 
Pandey, R.K.; Kumbhar, B.V.; Srivastava, S.; Malik, R.; Sundar, S.; Kunwar, A.; Prajapati, V.K. Febrifugine analogues as Leishmania donovani trypanothione reductase inhibitors: binding energy analysis assisted by molecular docking, ADMET and molecular dynamics simulation. J. Biomol. Struct. Dyn.,  2017, 35(1), 141-158.
[http://dx.doi.org/10.1080/07391102.2015.1135298] [PMID: 27043972] 
[109] 
Vats, C.; Dhanjal, J.K.; Goyal, S.; Bharadvaja, N.; Grover, A. Computational design of novel flavonoid analogues as potential AChE inhibitors: analysis using group-based QSAR, molecular docking and molecular dynamics simulations. Struct. Chem.,  2015, 26(2), 467-476.
[http://dx.doi.org/10.1007/s11224-014-0494-3] 
[110] 
Jiang, Z.Y.; Chu, H.X.; Xi, M.Y.; Yang, T.T.; Jia, J.M.; Huang, J.J.; Guo, X.K.; Zhang, X.J.; You, Q.D.; Sun, H.P. Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation. PLoS One,  2013, 8(9), e75076.
[http://dx.doi.org/10.1371/journal.pone.0075076] [PMID: 24066166] 
[111] 
Gholami, S.; Bordbar, A.K. Exploring binding properties of naringenin with bovine β-lactoglobulin: a fluorescence, molecular docking and molecular dynamics simulation study. Biophys. Chem.,  2014, 187-188, 33-42.
[http://dx.doi.org/10.1016/j.bpc.2014.01.003] [PMID: 24530705] 
[112] 
Zhang, L.; Li, D.; Cao, F.; Xiao, W.; Zhao, L.; Ding, G.; Wang, Z.Z. Identification of human acetylcholinesterase inhibitors from the constituents of EGb761 by modeling docking and molecular dynamics simulations. Comb. Chem. High Throughput Screen.,  2018, 21(1), 41-49.
[http://dx.doi.org/10.2174/1386207320666171123201910] [PMID: 29173156] 
[113] 
Zaman, Z.; Khan, S.; Nouroz, F.; Farooq, U.; Urooj, A. Targeting protein tyrosine phosphatase to unravel possible inhibitors for Streptococcus pneumoniae using molecular docking, molecular dynamics simulations coupled with free energy calculations. Life Sci.,  2021, 264, 118621.
[http://dx.doi.org/10.1016/j.lfs.2020.118621] [PMID: 33164832] 
[114] 
Vasilakaki, S.; Barbayianni, E.; Leonis, G.; Papadopoulos, M.G.; Mavromoustakos, T.; Gelb, M.H.; Kokotos, G. Development of a potent 2-oxoamide inhibitor of secreted phospholipase A2 guided by molecular docking calculations and molecular dynamics simulations. Bioorg. Med. Chem.,  2016, 24(8), 1683-1695.
[http://dx.doi.org/10.1016/j.bmc.2016.02.040] [PMID: 26970660] 
[115] 
Damale, M.G.; Patil, R.B.; Ansari, S.A.; Alkahtani, H.M.; Almehizia, A.A.; Shinde, D.B. Molecular docking, pharmacophore based virtual screening and molecular dynamics studies towards the identification of potential leads for the management of H. pylori. RSC Advances,  2019, 9(45), 26176-26208.
[http://dx.doi.org/10.1039/C9RA03281A] 
[116] 
Aghaee, E.; Ghasemi, J.B.; Manouchehri, F.; Balalaie, S. Combined docking, molecular dynamics simulations and spectroscopic studies for the rational design of a dipeptide ligand for affinity chromatography separation of human serum albumin. J. Mol. Model.,  2014, 20(10), 2446.
[http://dx.doi.org/10.1007/s00894-014-2446-7] [PMID: 25220335] 
[117] 
Sharda, S.; Khandelwal, R.; Adhikary, R.; Sharma, D.; Majhi, M.; Hussain, T. A computer-aided drug designing for pharmacological inhibition of ALK inhibitors induces apoptosis and differentiation in Non-small cell lung cancer. Curr. Top. Med. Chem.,  2019, 19(13), 1129-1144.
[http://dx.doi.org/10.2174/1568026619666190521084941] [PMID: 31109278] 
[118] 
Nayarisseri, A. Experimental and computational approaches to improve binding affinity in chemical biology and drug discovery. Curr. Top. Med. Chem.,  2020, 20(19), 1651-1660.
[http://dx.doi.org/10.2174/156802662019200701164759] [PMID: 32614747] 
[119] 
Martins, L.C.; Torres, P.H.M.; de Oliveira, R.B.; Pascutti, P.G.; Cino, E.A.; Ferreira, R.S. Investigation of the binding mode of a novel cruzain inhibitor by docking, molecular dynamics, ab initio and MM/PBSA calculations. J. Comput. Aided Mol. Des.,  2018, 32(5), 591-605.
[http://dx.doi.org/10.1007/s10822-018-0112-3] [PMID: 29564808] 
[120] 
Mao, Y.; Li, Y.; Hao, M.; Zhang, S.; Ai, C. Docking, molecular dynamics and quantitative structure-activity relationship studies for HEPTs and DABOs as HIV-1 reverse transcriptase inhibitors. J. Mol. Model.,  2012, 18(5), 2185-2198.
[http://dx.doi.org/10.1007/s00894-011-1236-8] [PMID: 21947448] 
[121] 
Fani, N.; Bordbar, A.K.; Ghayeb, Y. Spectroscopic, docking and molecular dynamics simulation studies on the interaction of two Schiff base complexes with human serum albumin. J. Lumin.,  2013, 141, 166-172.
[http://dx.doi.org/10.1016/j.jlumin.2013.03.001] 
[122] 
Choudhary, M.I.; Shaikh, M.; Tul-Wahab, A.; Ur-Rahman, A. In silico identification of potential inhibitors of key SARS-CoV-2 3CL hydrolase (Mpro) via molecular docking, MMGBSA predictive binding energy calculations, and molecular dynamics simulation. PLoS One,  2020, 15(7), e0235030.
[http://dx.doi.org/10.1371/journal.pone.0235030] [PMID: 32706783] 
[123] 
Fani, N.; Bordbar, A.K.; Ghayeb, Y. A combined spectroscopic, docking and molecular dynamics simulation approach to probing binding of a Schiff base complex to human serum albumin. Spectrochim. Acta A Mol. Biomol. Spectrosc.,  2013, 103, 11-17.
[http://dx.doi.org/10.1016/j.saa.2012.11.003] [PMID: 23228826] 
[124] 
Martínez, J.M.; Martínez, L. Packing optimization for automated generation of complex system’s initial configurations for molecular dynamics and docking. J. Comput. Chem.,  2003, 24(7), 819-825.
[http://dx.doi.org/10.1002/jcc.10216] [PMID: 12692791] 
[125] 
Hospital, A.; Goñi, J.R.; Orozco, M.; Gelpí, J.L. Molecular dynamics simulations: advances and applications. Adv. Appl. Bioinform. Chem.,  2015, 8, 37-47.
[PMID: 26604800] 
[126] 
Sarkar, S.; Gupta, S.; Chakraborty, W.; Senapati, S.; Gachhui, R. Homology modeling, molecular docking and molecular dynamics studies of the catalytic domain of chitin deacetylase from Cryptococcus laurentii strain RY1. Int. J. Biol. Macromol.,  2017, 104(PtB), 1682-1691.
[http://dx.doi.org/10.1016/j.ijbiomac.2017.03.057] [PMID: 28315437] 
[127] 
Costa, R.A.; Cruz, J.N.; Nascimento, F.C.; Silva, S.G.; Silva, S.O.; Martelli, M.C. Studies of NMR, molecular docking, and molecular dynamics simulation of new promising inhibitors of cruzaine from the parasite Trypanosoma cruzi. Med. Chem. Res.,  2019, 28(3), 246-259.
[http://dx.doi.org/10.1007/s00044-018-2280-z] 
[128] 
Sharma, A.; Vora, J.; Patel, D.; Sinha, S.; Jha, P.C.; Shrivastava, N. Identification of natural inhibitors against prime targets of SARS-CoV-2 using molecular docking, molecular dynamics simulation and MM-PBSA approaches. J. Biomol. Struct. Dyn.,  2020, 1-16. (Online ahead of Print).
[PMID: 33183178] 
[129] 
Li, K.; Zhu, J.; Xu, L.; Jin, J. Rational design of novel phosphoinositide 3-kinase gamma (pi3kγ) selective inhibitors: a computational investigation integrating 3d-qsar, molecular docking and molecular dynamics simulation. Chem. Biodivers.,  2019, 16(7), e1900105.
[http://dx.doi.org/10.1002/cbdv.201900105] [PMID: 31111650] 
[130] 
Wang, Z.; Cheng, L.; Kai, Z.; Wu, F.; Liu, Z.; Cai, M. Molecular modeling studies of atorvastatin analogues as HMGR inhibitors using 3D-QSAR, molecular docking and molecular dynamics simulations. Bioorg. Med. Chem. Lett.,  2014, 24(16), 3869-3876.
[http://dx.doi.org/10.1016/j.bmcl.2014.06.055] [PMID: 25022881] 
[131] 
Parikesit, A.A. Kinanty; Tambunan, U.S. Screening of commercial cyclic peptides as inhibitor envelope protein dengue virus (DENV) through molecular docking and molecular dynamics. Pak. J. Biol. Sci.,  2013, 16(24), 1836-1848.
[http://dx.doi.org/10.3923/pjbs.2013.1836.1848] [PMID: 24516999] 
[132] 
Peng, J.; Li, Y.; Zhou, Y.; Zhang, L.; Liu, X.; Zuo, Z. Pharmacophore modeling, molecular docking and molecular dynamics studies on natural products database to discover novel skeleton as non-purine xanthine oxidase inhibitors. J. Recept. Signal Transduct. Res.,  2018, 38(3), 246-255.
[http://dx.doi.org/10.1080/10799893.2018.1476544] [PMID: 29843539] 
[133] 
Mahmud, S.; Uddin, M.A.R.; Zaman, M.; Sujon, K.M.; Rahman, M.E.; Shehab, M.N.; Islam, A.; Alom, M.W.; Amin, A.; Akash, A.S.; Saleh, M.A. Molecular docking and dynamics study of natural compound for potential inhibition of main protease of SARSCoV-2 J. Biomol. Struct. Dyn.,  2020, 1-9. (Online ahead of Print)
[PMID: 32705962] 
[134] 
Wang, F.; Yang, W.; Shi, Y.; Le, G. 3D-QSAR, molecular docking and molecular dynamics studies of a series of RORγt inhibitors. J. Biomol. Struct. Dyn.,  2015, 33(9), 1929-1940.
[http://dx.doi.org/10.1080/07391102.2014.980321] [PMID: 25341687] 
[135] 
Chaube, U.; Chhatbar, D.; Bhatt, H. 3D-QSAR, molecular dynamics simulations and molecular docking studies of benzoxazepine moiety as mTOR inhibitor for the treatment of lung cancer. Bioorg. Med. Chem. Lett.,  2016, 26(3), 864-874.
[http://dx.doi.org/10.1016/j.bmcl.2015.12.075] [PMID: 26764189] 
[136] 
Kumar, B.K. Faheem, ; Sekhar, K.V.G.C.; Ojha, R.; Prajapati, V.K.; Pai, A.; Murugesan, S. Pharmacophore based virtual screening, molecular docking, molecular dynamics and MM-GBSA approach for identification of prospective SARS-CoV-2 inhibitor from natural product databases. J. Biomol. Struct. Dyn.,  2020, 1-24. (Online ahead of Print)
[PMID: 32981461] 
[137] 
Bhattacharjee, R.; Devi, A.; Mishra, S. Molecular docking and molecular dynamics studies reveal structural basis of inhibition and selectivity of inhibitors EGCG and OSU-03012 toward glucose regulated protein-78 (GRP78) overexpressed in glioblastoma. J. Mol. Model.,  2015, 21(10), 272.
[http://dx.doi.org/10.1007/s00894-015-2801-3] [PMID: 26419972] 
[138] 
Zhu, J.; Ke, K.; Xu, L.; Jin, J. Theoretical studies on the selectivity mechanisms of PI3Kδ inhibition with marketed idelalisib and its derivatives by 3D-QSAR, molecular docking, and molecular dynamics simulation. J. Mol. Model.,  2019, 25(8), 242.
[http://dx.doi.org/10.1007/s00894-019-4129-x] [PMID: 31338599] 
[139] 
Chander, S.; Pandey, R.K.; Penta, A.; Choudhary, B.S.; Sharma, M.; Malik, R.; Prajapati, V.K.; Murugesan, S. Molecular docking and molecular dynamics simulation based approach to explore the dual inhibitor against HIV-1 reverse transcriptase and Integrase. Comb. Chem. High Throughput Screen.,  2017, 20(8), 734-746.
[http://dx.doi.org/10.2174/1386207320666170615104703] [PMID: 28641512] 
[140] 
Gharaghani, S.; Khayamian, T.; Keshavarz, F. Docking, molecular dynamics simulation studies, and structure-based QSAR model on cytochrome P450 2A6 inhibitors. Struct. Chem.,  2012, 23(2), 341-350.
[http://dx.doi.org/10.1007/s11224-011-9874-0] 
[141] 
Zhang, C.; Li, Q.; Meng, L.; Ren, Y. Design of novel dopamine D2 and serotonin 5-HT2A receptors dual antagonists toward schizophrenia: An integrated study with QSAR, molecular docking, virtual screening and molecular dynamics simulations. J. Biomol. Struct. Dyn.,  2020, 38(3), 860-885.
[http://dx.doi.org/10.1080/07391102.2019.1590244] [PMID: 30916624] 
[142] 
Balupuri, A.; Gadhe, C.G.; Balasubramanian, P.K.; Kothandan, G.; Cho, S.J. In silico study on indole derivatives as anti HIV-1 agents: a combined docking, molecular dynamics and 3D-QSAR study. Arch. Pharm. Res.,  2014, 37(8), 1001-1015.
[http://dx.doi.org/10.1007/s12272-013-0313-1] [PMID: 24338530] 
[143] 
Wu, J.; Feng, Y.; Han, C.; Huang, W.; Shen, Z.; Yang, M.; Chen, W.; Ye, L. Germacrone derivatives: synthesis, biological activity, molecular docking studies and molecular dynamics simulations. Oncotarget,  2017, 8(9), 15149-15158.
[http://dx.doi.org/10.18632/oncotarget.14832] [PMID: 28148897] 
[144] 
Eduardo Sanabria-Chanaga, E.; Betancourt-Conde, I.; Hernández-Campos, A.; Téllez-Valencia, A.; Castillo, R. In silico hit optimization toward AKT inhibition: fragment-based approach, molecular docking and molecular dynamics study. J. Biomol. Struct. Dyn.,  2019, 37(16), 4301-4311.
[http://dx.doi.org/10.1080/07391102.2018.1546618] [PMID: 30477412] 
[145] 
Sahihi, M.; Ghayeb, Y. An investigation of molecular dynamics simulation and molecular docking: interaction of citrus flavonoids and bovine β-lactoglobulin in focus. Comput. Biol. Med.,  2014, 51, 44-50.
[http://dx.doi.org/10.1016/j.compbiomed.2014.04.022] [PMID: 24880994] 
[146] 
Huang, S.; Feng, K.; Ren, Y. Molecular modelling studies of quinazolinone derivatives as MMP-13 inhibitors by QSAR, molecular docking and molecular dynamics simulations techniques. MedChemComm,  2018, 10(1), 101-115.
[http://dx.doi.org/10.1039/C8MD00375K] [PMID: 30774858] 
[147] 
Galeazzi, R.; Massaccesi, L. Insight into the binding interactions of CYP450 aromatase inhibitors with their target enzyme: a combined molecular docking and molecular dynamics study. J. Mol. Model.,  2012, 18(3), 1153-1166.
[http://dx.doi.org/10.1007/s00894-011-1144-y] [PMID: 21681442] 
[148] 
Iraji, A.; Nouri, A.; Edraki, N.; Pirhadi, S.; Khoshneviszadeh, M.; Khoshneviszadeh, M. One-pot synthesis of thioxo-tetrahydropyrimidine derivatives as potent β-glucuronidase inhibitor, biological evaluation, molecular docking and molecular dynamics studies. Bioorg. Med. Chem.,  2020, 28(7), 115359.
[http://dx.doi.org/10.1016/j.bmc.2020.115359] [PMID: 32098709] 
[149] 
Limaye, A.; Sweta, J.; Madhavi, M.; Mudgal, U.; Mukherjee, S.; Sharma, S.; Hussain, T.; Nayarisseri, A.; Singh, S.K. In silico insights on gd2: a potential target for pediatric neuroblastoma. Curr. Top. Med. Chem.,  2019, 19(30), 2766-2781.
[http://dx.doi.org/10.2174/1568026619666191112115333] [PMID: 31721713] 
[150] 
Sinha, K.; Majhi, M.; Thakur, G.; Patidar, K.; Sweta, J.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Computer-aided drug designing for the identification of high-affinity small molecule targeting cd20 for the clinical treatment of chronic lymphocytic leukemia (cll). Curr. Top. Med. Chem.,  2018, 18(29), 2527-2542.
[http://dx.doi.org/10.2174/1568026619666181210150044] [PMID: 30526461] 
[151] 
Pinheiro, A.A.; Barros, R.P.; Assis, E.B.D.; Maia, M.S.; de Araújo, D.I.; Sales, K.A.; Scotti, L.; Tavares, J.F.; Scotti, M.T.; Silva, M.S.D. Virtual screening of secondary metabolites of the family velloziaceae j. agardh with potential antimicrobial activity. J. Braz. Chem. Soc.,  2020, 31(10), 2114-2119.
[http://dx.doi.org/10.21577/0103-5053.20200112] 
[152] 
Bandaru, S.; Sumithnath, T.G.; Sharda, S.; Lakhotia, S.; Sharma, A.; Jain, A.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Helix-coil transition signatures b-raf v600e mutation and virtual screening for inhibitors directed against mutant b-raf. Curr. Drug Metab.,  2017, 18(6), 527-534.
[http://dx.doi.org/10.2174/1389200218666170503114611] [PMID: 28472910] 
[153] 
Dunna, N.R.; Kandula, V.; Girdhar, A.; Pudutha, A.; Hussain, T.; Bandaru, S.; Nayarisseri, A. High affinity pharmacological profiling of dual inhibitors targeting RET and VEGFR2 in inhibition of kinase and angiogeneis events in medullary thyroid carcinoma. Asian Pac. J. Cancer Prev.,  2015, 16(16), 7089-7095.
[http://dx.doi.org/10.7314/APJCP.2015.16.16.7089] [PMID: 26514495] 
[154] 
Sivakumar, M.; Saravanan, K.; Saravanan, V.; Sugarthi, S.; Kumar, S.M.; Alhaji Isa, M.; Rajakumar, P.; Aravindhan, S. Discovery of new potential triplet acting inhibitor for Alzheimer’s disease via X-ray crystallography, molecular docking and molecular dynamics. J. Biomol. Struct. Dyn.,  2020, 38(7), 1903-1917.
[http://dx.doi.org/10.1080/07391102.2019.1620128] [PMID: 31099307] 
[155] 
Stitou, M.; Toufik, H.; Bouachrine, M.; Lamchouri, F. Quantitative structure-activity relationships analysis, homology modeling, docking and molecular dynamics studies of triterpenoid saponins as Kirsten rat sarcoma inhibitors. J. Biomol. Struct. Dyn.,  2020, 1-19. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2019.1707122] [PMID: 31870215] 
[156] 
Er, M.; Abounakhla, A.M.; Tahtaci, H.; Bawah, A.H.; Çınaroğlu, S.S.; Onaran, A.; Ece, A. An integrated approach towards the development of novel antifungal agents containing thiadiazole: synthesis and a combined similarity search, homology modelling, molecular dynamics and molecular docking study. Chem. Cent. J.,  2018, 12(1), 121.
[http://dx.doi.org/10.1186/s13065-018-0485-3] [PMID: 30470928] 
[157] 
Antes, I. DynaDock: A new molecular dynamics-based algorithm for protein-peptide docking including receptor flexibility. Proteins,  2010, 78(5), 1084-1104.
[http://dx.doi.org/10.1002/prot.22629] [PMID: 20017216] 
[158] 
Kant, K.; Lal, U.R.; Kumar, A.; Ghosh, M. A merged molecular docking, ADME-T and dynamics approaches towards the genus of Arisaema as herpes simplex virus type 1 and type 2 inhibitors. Comput. Biol. Chem.,  2019, 78, 217-226.
[http://dx.doi.org/10.1016/j.compbiolchem.2018.12.005] [PMID: 30579134] 
[159] 
Ren, X.; Zeng, R.; Tortorella, M.; Wang, J.; Wang, C. Structural insight into inhibition of CsrA-RNA interaction revealed by docking, molecular dynamics and free energy calculations. Sci. Rep.,  2017, 7(1), 14934.
[http://dx.doi.org/10.1038/s41598-017-14916-6] [PMID: 29097778] 
[160] 
Wu, G.; Robertson, D.H.; Brooks, C.L., III; Vieth, M. Detailed analysis of grid-based molecular docking: A case study of CDOCKER-A CHARMm-based MD docking algorithm. J. Comput. Chem.,  2003, 24(13), 1549-1562.
[http://dx.doi.org/10.1002/jcc.10306] [PMID: 12925999] 
[161] 
Sundar, S.; Thangamani, L.; Manivel, G.; Kumar, P.; Piramanayagam, S. Molecular docking, molecular dynamics and MM/PBSA studies of FDA approved drugs for protein kinase a of Mycobacterium tuberculosis; application insights of drug repurposing. Informatics in Medicine Unlocked,  2019, 16, 100210.
[http://dx.doi.org/10.1016/j.imu.2019.100210] 
[162] 
Sargolzaei, M. Effect of nelfinavir stereoisomers on coronavirus main protease: Molecular docking, molecular dynamics simulation and MM/GBSA study. J. Mol. Graph. Model.,  2020, 103, 107803.
[http://dx.doi.org/10.1016/j.jmgm.2020.107803] [PMID: 33333424] 
[163] 
Yuan, M.; Luo, M.; Song, Y.; Xu, Q.; Wang, X.; Cao, Y.; Bu, X.; Ren, Y.; Hu, X. Identification of curcumin derivatives as human glyoxalase I inhibitors: A combination of biological evaluation, molecular docking, 3D-QSAR and molecular dynamics simulation studies. Bioorg. Med. Chem.,  2011, 19(3), 1189-1196.
[http://dx.doi.org/10.1016/j.bmc.2010.12.039] [PMID: 21237663] 
[164] 
Bandaru, S.; Alvala, M.; Akka, J.; Sagurthi, S.R.; Nayarisseri, A.; Singh, S.K.; Mundluru, H.P. Identification of small molecule as a high affinity β2 agonist promiscuously targeting wild and mutated (Thr164Ile) β 2 adrenergic receptor in the treatment of bronchial asthma. Curr. Pharm. Des.,  2016, 22(34), 5221-5233.
[http://dx.doi.org/10.2174/1381612822666160513145721] [PMID: 27174812] 
[165] 
Ali, M.A.; Vuree, S.; Goud, H.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Identification of high-affinity small molecules targeting gamma secretase for the treatment of alzheimer’s disease. Curr. Top. Med. Chem.,  2019, 19(13), 1173-1187.
[http://dx.doi.org/10.2174/1568026619666190617155326] [PMID: 31244427] 
[166] 
Shen, X.L.; Takimoto-Kamimura, M.; Wei, J.; Gao, Q.Z. Computer-aided de novo ligand design and docking/molecular dynamics study of vitamin D receptor agonists. J. Mol. Model.,  2012, 18(1), 203-212.
[http://dx.doi.org/10.1007/s00894-011-1066-8] [PMID: 21523537] 
[167] 
He, Q.; Chu, H.; Wang, Y.; Guo, H.; Wang, Y.; Wang, S. In silico design novel vibsanin B derivatives as inhibitor for heat shock protein 90 based on 3D-QSAR, molecular docking and molecular dynamics simulation. J. Biomol. Struct. Dyn.,  2019, 38(14), 1-12.
[http://dx.doi.org/10.1080/07391102.2019.1671900] [PMID: 31542999] 
[168] 
Singh, R.; Pandey, P.N. Molecular docking and molecular dynamics study on SmHDAC1 to identify potential lead compounds against Schistosomiasis. Mol. Biol. Rep.,  2015, 42(3), 689-698.
[http://dx.doi.org/10.1007/s11033-014-3816-z] [PMID: 25663090] 
[169] 
Rahman, M.M.; Saha, T.; Islam, K.J.; Suman, R.H.; Biswas, S.; Rahat, E.U.; Hossen, M.R.; Islam, R.; Hossain, M.N.; Mamun, A.A.; Khan, M.; Ali, M.A.; Halim, M.A. Virtual screening, molecular dynamics and structure-activity relationship studies to identify potent approved drugs for Covid-19 treatment. J. Biomol. Struct. Dyn.,  2020, 1-11. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1794974] [PMID: 32692306] 
[170] 
Tripuraneni, N.S.; Azam, M.A. A combination of pharmacophore modeling, atom-based 3D-QSAR, molecular docking and molecular dynamics simulation studies on PDE4 enzyme inhibitors. J. Biomol. Struct. Dyn.,  2016, 34(11), 2481-2492.
[http://dx.doi.org/10.1080/07391102.2015.1119732] [PMID: 26587754] 
[171] 
Ganesan, M.S.; Raja, K.K.; Murugesan, S.; Kumar, B.K.; Rajagopal, G.; Thirunavukkarasu, S. Synthesis, biological evaluation, molecular docking, molecular dynamics and DFT studies of quinoline-fluoroproline amide hybrids. J. Mol. Struct., 2020.
[http://dx.doi.org/10.1016/j.molstruc.2020.128360] 
[172] 
Huang, L.L.; Han, J.; Ran, J.X.; Chen, X.P.; Wang, Z.H.; Wu, F.H. 3D-QSAR, molecular docking and molecular dynamics simulations of oxazepane amidoacetonitrile derivatives as novel DPPI inhibitors. J. Mol. Struct.,  2018, 1168, 223-233.
[http://dx.doi.org/10.1016/j.molstruc.2018.05.025] 
[173] 
Lu, S.J.; Chong, F.C. Combining molecular docking and molecular dynamics to predict the binding modes of flavonoid derivatives with the neuraminidase of the 2009 H1N1 influenza A virus. Int. J. Mol. Sci.,  2012, 13(4), 4496-4507.
[http://dx.doi.org/10.3390/ijms13044496] [PMID: 22605992] 
[174] 
Aher, A.; Udhwani, T.; Khandelwal, R.; Limaye, A.; Hussain, T.; Nayarisseri, A.; Singh, S.K. In silico insights on il-6: a potential target for multicentric castleman disease. Curr Comput Aided Drug Des,  2020, 16(5), 641-653.
[http://dx.doi.org/10.2174/1573409915666190902142524] [PMID: 31475901] 
[175] 
Adhikary, R.; Khandelwal, R.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Structural insights into the molecular design of ros1 inhibitor for the treatment of non-small cell lung cancer (nsclc). Curr Comput Aided Drug Des, 2020. (Online ahead of Print)
[http://dx.doi.org/10.2174/1573409916666200504105249] [PMID: 32364080] 
[176] 
Nayarisseri, A. Prospects of utilizing computational techniques for the treatment of human diseases. Curr. Top. Med. Chem.,  2019, 19(13), 1071-1074.
[http://dx.doi.org/10.2174/156802661913190827102426] [PMID: 31490742] 
[177] 
Nayarisseri, A.; Khandelwal, R.; Madhavi, M.; Selvaraj, C.; Panwar, U.; Sharma, K.; Hussain, T.; Singh, S.K. Shape-based machine learning models for the potential novel COVID-19 protease inhibitors assisted by molecular dynamics simulation. Curr. Top. Med. Chem.,  2020, 20(24), 2146-2167.
[http://dx.doi.org/10.2174/1568026620666200704135327] [PMID: 32621718] 
[178] 
Hong Enriquez, R.P.; Pavan, S.; Benedetti, F.; Tossi, A.; Savoini, A.; Berti, F.; Laio, A. Designing short peptides with high affinity for organic molecules: a combined docking, molecular dynamics, and Monte Carlo approach. J. Chem. Theory Comput.,  2012, 8(3), 1121-1128.
[http://dx.doi.org/10.1021/ct200873y] [PMID: 26593371] 
[179] 
Badavath, V.N.; Kumar, A.; Samanta, P.K.; Maji, S.; Das, A.; Blum, G.; Jha, A.; Sen, A. Determination of potential inhibitors based on isatin derivatives against SARS-CoV-2 main protease (mpro): a molecular docking, molecular dynamics and structure-activity relationship studies. J. Biomol. Struct. Dyn.,  2020, 1-19. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1845800] [PMID: 33200681] 
[180] 
Wang, X.; Yang, W.; Xu, X.; Zhang, H.; Li, Y.; Wang, Y. Studies of benzothiadiazine derivatives as hepatitis C virus NS5B polymerase inhibitors using 3D-QSAR, molecular docking and molecular dynamics. Curr. Med. Chem.,  2010, 17(25), 2788-2803.
[http://dx.doi.org/10.2174/092986710791859298] [PMID: 20586716] 
[181] 
Liu, J.; Zhang, H.; Xiao, Z.; Wang, F.; Wang, X.; Wang, Y. Combined 3D-QSAR, molecular docking and molecular dynamics study on derivatives of peptide epoxyketone and tyropeptin-boronic acid as inhibitors against the β5 subunit of human 20S proteasome. Int. J. Mol. Sci.,  2011, 12(3), 1807-1835.
[http://dx.doi.org/10.3390/ijms12031807] [PMID: 21673924] 
[182] 
Vadloori, B.; Sharath, A.K.; Prabhu, N.P.; Maurya, R. Homology modelling, molecular docking, and molecular dynamics simulations reveal the inhibition of Leishmania donovani dihydrofolate reductase-thymidylate synthase enzyme by Withaferin-A. BMC Res. Notes,  2018, 11(1), 246.
[http://dx.doi.org/10.1186/s13104-018-3354-1] [PMID: 29661206] 
[183] 
Gupta, S.; Parihar, D.; Shah, M.; Yadav, S.; Managori, H.; Bhowmick, S. Computational screening of promising beta-secretase 1 inhibitors through multi-step molecular docking and molecular dynamics simulations-Pharmacoinformatics approach. J. Mol. Struct.,  2020, 1205, 127660.
[http://dx.doi.org/10.1016/j.molstruc.2019.127660] 
[184] 
Sharma, R.; Jade, D.; Mohan, S.; Chandel, R.; Sugumar, S. In-silico virtual screening for identification of potent inhibitor for L2-β-lactamase from Stenotrophomonas maltophilia through molecular docking, molecular dynamics analysis study. J. Biomol. Struct. Dyn.,  2020, 1-15. (Online ahead of Print).
[http://dx.doi.org/10.1080/07391102.2020.1805365] [PMID: 32820691] 
[185] 
Yao, K.; Liu, P.; Liu, H.; Wei, Q.; Yang, J.; Cao, P.; Lai, Y. 3D-QSAR, molecular docking and molecular dynamics simulations study of 3-pyrimidin-4-yl-oxazolidin-2-one derivatives to explore the structure requirements of mutant IDH1 inhibitors. J. Mol. Struct.,  2019, 1189, 187-202.
[http://dx.doi.org/10.1016/j.molstruc.2019.03.092] 
[186] 
Deng, F.; Xie, M.; Zhang, X.; Li, P.; Tian, Y.; Zhai, H.; Li, Y. Combined molecular docking, molecular dynamics simulation and quantitative structure–activity relationship study of pyrimido [1, 2-c][1, 3] benzothiazin-6-imine derivatives as potent anti-HIV drugs. J. Mol. Struct.,  2014, 1067, 1-13.
[http://dx.doi.org/10.1016/j.molstruc.2014.03.008] 
[187] 
Peddi, S.R.; Peddi, S.R.; Sivan, S.; Veerati, R.; Manga, V. Integrated molecular docking, 3D QSAR and molecular dynamics simulation studies on indole derivatives for designing new Pim-1 inhibitors. J. Recept. Signal Transduct. Res.,  2020, 40(1), 1-14.
[http://dx.doi.org/10.1080/10799893.2020.1713809] [PMID: 31931654] 
[188] 
Nayarisseri, A.; Moghni, S.M.; Yadav, M.; Kharate, J.; Sharma, P.; Chandok, K.H.; Shah, K.P. In silico investigations on HSP90 and its inhibition for the therapeutic prevention of breast cancer. J. Pharm. Res.,  2013, 7(2), 150-156.
[http://dx.doi.org/10.1016/j.jopr.2013.02.020] 
[189] 
Gudala, S.; Khan, U.; Kanungo, N.; Bandaru, S.; Hussain, T.; Parihar, M.; Nayarisseri, A.; Mundluru, H.P. Identification and pharmacological analysis of high efficacy small molecule inhibitors of EGF-EGFR interactions in clinical treatment of non-small cell lung carcinoma: A computational approach. Asian Pac. J. Cancer Prev.,  2015, 16(18), 8191-8196.
[http://dx.doi.org/10.7314/APJCP.2015.16.18.8191] [PMID: 26745059] 
[190] 
Babitha, P.P.; Sahila, M.M.; Bandaru, S.; Nayarisseri, A.; Sureshkumar, S. Molecular docking and pharmacological investigations of rivastigmine-fluoxetine and coumarin-tacrine hybrids against acetyl choline esterase. Bioinformation,  2015, 11(8), 378-386.
[http://dx.doi.org/10.6026/97320630011378] [PMID: 26420918] 
[191] 
Natchimuthu, V.; Bandaru, S.; Nayarisseri, A.; Ravi, S. Design, synthesis and computational evaluation of a novel intermediate salt of N-cyclohexyl-N-(cyclohexylcarbamoyl)-4-(trifluoromethyl) benzamide as potential potassium channel blocker in epileptic paroxysmal seizures. Comput. Biol. Chem.,  2016, 64, 64-73.
[http://dx.doi.org/10.1016/j.compbiolchem.2016.05.003] [PMID: 27266485] 
[192] 
Sahila, M.M.; Babitha, P.P.; Bandaru, S.; Nayarisseri, A.; Doss, V.A. Molecular docking based screening of GABA (A) receptor inhibitors from plant derivatives. Bioinformation,  2015, 11(6), 280-289.
[http://dx.doi.org/10.6026/97320630011280] [PMID: 26229288] 
[193] 
Bandaru, S.; Tarigopula, P.; Akka, J.; Marri, V.K.; Kattamuri, R.K.; Nayarisseri, A.; Mangalarapu, M.; Vinukonda, S.; Mundluru, H.P.; Sagurthi, S.R. Association of Beta 2 adrenergic receptor (Thr164Ile) polymorphism with Salbutamol refractoriness in severe asthmatics from Indian population. Gene,  2016, 592(1), 15-22.
[http://dx.doi.org/10.1016/j.gene.2016.07.043] [PMID: 27450915] 
[194] 
Khandekar, N.; Singh, S.; Shukla, R.; Tirumalaraju, S.; Bandaru, S.; Banerjee, T.; Nayarisseri, A. Structural basis for the in vitro known acyl-depsipeptide 2 (ADEP2) inhibition to Clp 2 protease from Mycobacterium tuberculosis. Bioinformation,  2016, 12(3), 92-97.
[http://dx.doi.org/10.6026/97320630012092] [PMID: 28149041] 
[195] 
Bandaru, S.; Alvala, M.; Nayarisseri, A.; Sharda, S.; Goud, H.; Mundluru, H.P.; Singh, S.K. Molecular dynamic simulations reveal suboptimal binding of salbutamol in T164I variant of β2 adrenergic receptor. PLoS One,  2017, 12(10), e0186666.
[http://dx.doi.org/10.1371/journal.pone.0186666] [PMID: 29053759] 
[196] 
Jain, D.; Udhwani, T.; Sharma, S.; Gandhe, A.; Reddy, P.B.; Nayarisseri, A.; Singh, S.K. Design of novel JAK3 Inhibitors towards Rheumatoid Arthritis using molecular docking analysis. Bioinformation,  2019, 15(2), 68-78.
[http://dx.doi.org/10.6026/97320630015068] [PMID: 31435152] 
[197] 
Mendonça-Junior, F.J.B.; Scotti, M.T.; Nayarisseri, A.; Zondegoumba, E.N.T.; Scotti, L. Natural bioactive products with antioxidant properties useful in neurodegenerative diseases. Oxid. Med. Cell. Longev.,  2019, 2019, 7151780.
[http://dx.doi.org/10.1155/2019/7151780] [PMID: 31210847] 
[198] 
Nayarisseri, A.; Hood, E.A. Advancement in microbial cheminformatics. Curr. Top. Med. Chem.,  2018, 18(29), 2459-2461.
[http://dx.doi.org/10.2174/1568026619666181120121528] [PMID: 30457050] 
[199] 
Gokhale, P.; Chauhan, A.P.S.; Arora, A.; Khandekar, N.; Nayarisseri, A.; Singh, S.K. FLT3 inhibitor design using molecular docking based virtual screening for acute myeloid leukemia. Bioinformation,  2019, 15(2), 104-115.
[http://dx.doi.org/10.6026/97320630015104] [PMID: 31435156] 
[200] 
Shukla, P.; Khandelwal, R.; Sharma, D.; Dhar, A.; Nayarisseri, A.; Singh, S.K. Virtual screening of il-6 inhibitors for idiopathic arthritis. Bioinformation,  2019, 15(2), 121-130.
[http://dx.doi.org/10.6026/97320630015121] [PMID: 31435158] 
[201] 
Udhwani, T.; Mukherjee, S.; Sharma, K.; Sweta, J.; Khandekar, N.; Nayarisseri, A.; Singh, S.K. Design of PD-L1 inhibitors for lung cancer. Bioinformation,  2019, 15(2), 139-150.
[http://dx.doi.org/10.6026/97320630015139] [PMID: 31435160] 
[202] 
Sweta, J.; Khandelwal, R.; Srinitha, S.; Pancholi, R.; Adhikary, R.; Ali, M.A.; Nayarisseri, A.; Vuree, S.; Singh, S.K. Identification of high-affinity small molecule targeting idh2 for the clinical treatment of acute myeloid leukemia. Asian Pac. J. Cancer Prev.,  2019, 20(8), 2287-2297.
[http://dx.doi.org/10.31557/APJCP.2019.20.8.2287] [PMID: 31450897] 
[203] 
Gutlapalli, V.R.; Sykam, A.; Nayarisseri, A.; Suneetha, S.; Suneetha, L.M. Insights from the predicted epitope similarity between Mycobacterium tuberculosis virulent factors and its human homologs. Bioinformation,  2015, 11(12), 517-524.
[http://dx.doi.org/10.6026/97320630011517] [PMID: 26770024] 
[204] 
Nayarisseri, A.; Yadav, M.; Wishard, R. Computational evaluation of new homologous down regulators of Translationally Controlled Tumor Protein (TCTP) targeted for tumor reversion. Interdiscip. Sci.,  2013, 5(4), 274-279.
[http://dx.doi.org/10.1007/s12539-013-0183-8] [PMID: 24402820] 
[205] 
Praseetha, S.; Bandaru, S.; Nayarisseri, A.; Sureshkumar, S. Pharmacological analysis of vorinostat analogues as potential anti-tumor agents targeting human histone deacetylases: an epigenetic treatment stratagem for cancers. Asian Pac. J. Cancer Prev.,  2016, 17(3), 1571-1576.
[http://dx.doi.org/10.7314/APJCP.2016.17.3.1571] [PMID: 27039807] 
[206] 
Majhi, M.; Ali, M.A.; Limaye, A.; Sinha, K.; Bairagi, P.; Chouksey, M.; Shukla, R.; Kanwar, N.; Hussain, T.; Nayarisseri, A.; Singh, S.K. An In silico investigation of potential egfr inhibitors for the clinical treatment of colorectal cancer. Curr. Top. Med. Chem.,  2018, 18(27), 2355-2366.
[http://dx.doi.org/10.2174/1568026619666181129144107] [PMID: 30499396] 
[207] 
Shameer, K.; Nayarisseri, A.; Romero Duran, F.X.; González-Díaz, H. Improving neuropharmacology using big data, machine learning and computational algorithms. Curr. Neuropharmacol.,  2017, 15(8), 1058-1061.
[http://dx.doi.org/10.2174/1570159X1508171114113425] [PMID: 29199918] 
[208] 
Basak, S.C.; Nayarisseri, A.; González-Díaz, H.; Bonchev, D. Editorial (Thematic issue: chemoinformatics models for pharmaceutical design, part 2). Curr. Pharm. Des.,  2016, 22(34), 5177-5178.
[http://dx.doi.org/10.2174/138161282234161110222751] [PMID: 27852211] 
[209] 
Basak, S.C.; Nayarisseri, A.; González-Díaz, H.; Bonchev, D. Editorial (Thematic issue: chemoinformatics models for pharmaceutical design, part 1). Curr. Pharm. Des.,  2016, 22(33), 5041-5042.
[http://dx.doi.org/10.2174/138161282233161109224932] [PMID: 27852204] 
[210] 
Kelotra, A.; Gokhale, S.M.; Kelotra, S.; Mukadam, V.; Nagwanshi, K.; Bandaru, S.; Nayarisseri, A.; Bidwai, A. Alkyloxy carbonyl modified hexapeptides as a high affinity compounds for Wnt5A protein in the treatment of psoriasis. Bioinformation,  2014, 10(12), 743-749.
[http://dx.doi.org/10.6026/97320630010743] [PMID: 25670877] 
[211] 
Chandrakar, B.; Jain, A.; Roy, S.; Gutlapalli, V.R.; Saraf, S.; Suppahia, A.; Verma, A.; Tiwari, A.; Yadav, M.; Nayarisseri, A. Molecular modeling of Acetyl-CoA carboxylase (ACC) from Jatropha curcas and virtual screening for identification of inhibitors. journal of pharmacy research,  2013, 6(9), 913-918.
[212] 
Khandelwal, R.; Chauhan, A.P.S.; Bilawat, S.; Gandhe, A.; Hussain, T.; Hood, E.A.; Nayarisseri, A.; Singh, S.K. Structure-based virtual screening for the identification of high affinity small molecule towards STAT3 for the clinical treatment of Osteosarcoma. Curr. Top. Med. Chem.,  2018, 18(29), 2511-2526.
[http://dx.doi.org/10.2174/1568026618666181115092001] [PMID: 30430945] 
[213] 
Prajapati, L.; Khandelwal, R.; Yogalakshmi, K.N.; Munshi, A.; Nayarisseri, A. computer-aided structure prediction of bluetongue virus coat protein vp2 assisted by optimized potential for liquid simulations (opls). Curr. Top. Med. Chem.,  2020, 20(19), 1720-1732.
[http://dx.doi.org/10.2174/1568026620666200516153753] [PMID: 32416694] 
[214] 
Nayarisseri, A.; Singh, S.K. Functional inhibition of vegf and egfr suppressors in cancer treatment. Curr. Top. Med. Chem.,  2019, 19(3), 178-179.
[http://dx.doi.org/10.2174/156802661903190328155731] [PMID: 30950335] 
[215] 
Monteiro, A.F.M.; Viana, J.O.; Nayarisseri, A.; Zondegoumba, E.N.; Mendonça Junior, F.J.B.; Scotti, M.T.; Scotti, L. Computational Studies Applied to Flavonoids against Alzheimer’s and Parkinson’s Diseases. Oxid. Med. Cell. Longev.,  2018, 2018, 7912765.
[http://dx.doi.org/10.1155/2018/7912765] [PMID: 30693065] 
[216] 
Patidar, K.; Panwar, U.; Vuree, S.; Sweta, J.; Sandhu, M.K.; Nayarisseri, A.; Singh, S.K. An in silico approach to identify high affinity small molecule targeting m-tor inhibitors for the clinical treatment of breast cancer. Asian Pac. J. Cancer Prev.,  2019, 20(4), 1229-1241.
[http://dx.doi.org/10.31557/APJCP.2019.20.4.1229] [PMID: 31030499] 
[217] 
Tambunan, U.S.F.; Zahroh, H.; Utomo, B.B.; Parikesit, A.A. Screening of commercial cyclic peptide as inhibitor ns5 methyltransferase of dengue virus through molecular docking and molecular dynamics simulation. Bioinformation,  2014, 10(1), 23-27.
[http://dx.doi.org/10.6026/97320630010023] [PMID: 24516322] 
[218] 
Kist, R.; Caceres, R.A. New potential inhibitors of mTOR: a computational investigation integrating molecular docking, virtual screening and molecular dynamics simulation. J. Biomol. Struct. Dyn.,  2017, 35(16), 3555-3568.
[http://dx.doi.org/10.1080/07391102.2016.1262279] [PMID: 27860549] 
[219] 
Mohammadi, T.; Ghayeb, Y. Atomic insight into designed carbamate-based derivatives as acetylcholine esterase (AChE) inhibitors: a computational study by multiple molecular docking and molecular dynamics simulation. J. Biomol. Struct. Dyn.,  2018, 36(1), 126-138.
[http://dx.doi.org/10.1080/07391102.2016.1268977] [PMID: 27924680] 
[220] 
Xu, C.; Ren, Y. Molecular modeling studies of [6,6,5] Tricyclic Fused Oxazolidinones as FXa inhibitors using 3D-QSAR, Topomer CoMFA, molecular docking and molecular dynamics simulations. Bioorg. Med. Chem. Lett.,  2015, 25(20), 4522-4528.
[http://dx.doi.org/10.1016/j.bmcl.2015.08.070] [PMID: 26343829] 
[221] 
Jayachandran, G.; Shirts, M.R.; Park, S.; Pande, V.S. Parallelized-over-parts computation of absolute binding free energy with docking and molecular dynamics. J. Chem. Phys.,  2006, 125(8), 084901.
[http://dx.doi.org/10.1063/1.2221680] [PMID: 16965051] 
[222] 
Cheng, P.; Li, J.; Wang, J.; Zhang, X.; Zhai, H. Investigations of FAK inhibitors: a combination of 3D-QSAR, docking, and molecular dynamics simulations studies. J. Biomol. Struct. Dyn.,  2018, 36(6), 1529-1549.
[http://dx.doi.org/10.1080/07391102.2017.1329095] [PMID: 28490269] 
[223] 
Hritz, J.; de Ruiter, A.; Oostenbrink, C. Impact of plasticity and flexibility on docking results for cytochrome P450 2D6: a combined approach of molecular dynamics and ligand docking. J. Med. Chem.,  2008, 51(23), 7469-7477.
[http://dx.doi.org/10.1021/jm801005m] [PMID: 18998665] 
[224] 
Wang, Z.Z.; Yang, J.; Sun, X.D.; Ma, C.Y.; Gao, Q.B.; Ding, L.; Liu, H.M. Probing the binding mechanism of substituted pyridine derivatives as effective and selective lysine-specific demethylase 1 inhibitors using 3D-QSAR, molecular docking and molecular dynamics simulations. J. Biomol. Struct. Dyn.,  2018, 37(13), 3482-3495.
[225] 
Skariyachan, S.; Manjunath, M.; Bachappanavar, N. Screening of potential lead molecules against prioritised targets of multi-drug-resistant-Acinetobacter baumannii - insights from molecular docking, molecular dynamic simulations and in vitro assays. J. Biomol. Struct. Dyn.,  2019, 37(5), 1146-1169.
[http://dx.doi.org/10.1080/07391102.2018.1451387] [PMID: 29529934] 
[226] 
Guedes, I.A.; de Magalhães, C.S.; Dardenne, L.E. Receptor-ligand molecular docking. Biophys. Rev.,  2014, 6(1), 75-87.
[http://dx.doi.org/10.1007/s12551-013-0130-2] [PMID: 28509958] 
[227] 
Chhatbar, D.M.; Chaube, U.J.; Vyas, V.K.; Bhatt, H.G. CoMFA, CoMSIA, Topomer CoMFA, HQSAR, molecular docking and molecular dynamics simulations study of triazine morpholino derivatives as mTOR inhibitors for the treatment of breast cancer. Comput. Biol. Chem.,  2019, 80, 351-363.
[http://dx.doi.org/10.1016/j.compbiolchem.2019.04.017] [PMID: 31085426] 
[228] 
Asadollahi-Baboli, M.; Mani-Varnosfaderani, A. Molecular docking, molecular dynamics simulation, and QSAR model on potent thiazolidine-4-carboxylic acid inhibitors of influenza neuraminidase. Med. Chem. Res.,  2013, 22(4), 1700-1710.
[http://dx.doi.org/10.1007/s00044-012-0175-y] 
[229] 
Gan, R.; Zhao, L.; Sun, Q.; Tang, P.; Zhang, S.; Yang, H.; He, J.; Li, H. Binding behavior of trelagliptin and human serum albumin: Molecular docking, dynamical simulation, and multi-spectroscopy. Spectrochim. Acta A Mol. Biomol. Spectrosc.,  2018, 202, 187-195.
[http://dx.doi.org/10.1016/j.saa.2018.05.049] [PMID: 29787915] 
[230] 
Itteboina, R.; Ballu, S.; Sivan, S.K.; Manga, V. Molecular docking, 3D-QSAR, molecular dynamics, synthesis and anticancer activity of tyrosine kinase 2 (TYK 2) inhibitors. J. Recept. Signal Transduct. Res.,  2018, 38(5-6), 462-474.
[http://dx.doi.org/10.1080/10799893.2019.1585453] [PMID: 31038024] 
[231] 
Capoferri, L.; Leth, R.; ter Haar, E.; Mohanty, A.K.; Grootenhuis, P.D.; Vottero, E.; Commandeur, J.N.; Vermeulen, N.P.; Jørgensen, F.S.; Olsen, L.; Geerke, D.P. Insights into regioselective metabolism of mefenamic acid by cytochrome P450 BM3 mutants through crystallography, docking, molecular dynamics, and free energy calculations. Proteins,  2016, 84(3), 383-396.
[http://dx.doi.org/10.1002/prot.24985] [PMID: 26757175] 
[232] 
Shoichet, B.K.; McGovern, S.L.; Wei, B.; Irwin, J.J. Lead discovery using molecular docking. Curr. Opin. Chem. Biol.,  2002, 6(4), 439-446.
[http://dx.doi.org/10.1016/S1367-5931(02)00339-3] [PMID: 12133718] 
[233] 
Schmidtke, P.; Bidon-Chanal, A.; Luque, F.J.; Barril, X. MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories. Bioinformatics,  2011, 27(23), 3276-3285.
[http://dx.doi.org/10.1093/bioinformatics/btr550] [PMID: 21967761] 
[234] 
Guterres, H.; Im, W. Improving protein-ligand docking results with high-throughput molecular dynamics simulations. J. Chem. Inf. Model.,  2020, 60(4), 2189-2198.
[http://dx.doi.org/10.1021/acs.jcim.0c00057] [PMID: 32227880] 
[235] 
Sharda, S.; Sarmandal, P.; Cherukommu, S.; Dindhoria, K.; Yadav, M.; Bandaru, S.; Sharma, A.; Sakhi, A.; Vyas, T.; Hussain, T.; Nayarisseri, A.; Singh, S.K. A virtual screening approach for the identification of high affinity small molecules targeting BCR-ABL1 inhibitors for the treatment of chronic myeloid leukemia. Curr. Top. Med. Chem.,  2017, 17(26), 2989-2996.
[http://dx.doi.org/10.2174/1568026617666170821124512] [PMID: 28828991] 
[236] 
Daisy, P.; Vijayalakshmi, P.; Selvaraj, C.; Singh, S.K.; Saipriya, K. Targeting multidrug resistant Mycobacterium tuberculosis HtrA2 with identical chemical entities of fluoroquinolones. Indian J. Pharm. Sci.,  2012, 74(3), 217-222.
[http://dx.doi.org/10.4103/0250-474X.106063] [PMID: 23440996] 
[237] 
Pradiba, D.; Aarthy, M.; Shunmugapriya, V.; Singh, S.K.; Vasanthi, M. Structural insights into the binding mode of flavonols with the active site of matrix metalloproteinase-9 through molecular docking and molecular dynamic simulations studies. J. Biomol. Struct. Dyn.,  2018, 36(14), 3718-3739.
[http://dx.doi.org/10.1080/07391102.2017.1397058] [PMID: 29068268] 
[238] 
Shanmuganathan, B.; Suryanarayanan, V.; Sathya, S.; Narenkumar, M.; Singh, S.K.; Ruckmani, K.; Pandima Devi, K. Anti-amyloidogenic and anti-apoptotic effect of α-bisabolol against Aβ induced neurotoxicity in PC12 cells. Eur. J. Med. Chem.,  2018, 143, 1196-1207.
[http://dx.doi.org/10.1016/j.ejmech.2017.10.017] [PMID: 29150331] 
[239] 
Reddy, K.K.; Singh, S.K. Combined ligand and structure-based approaches on HIV-1 integrase strand transfer inhibitors. Chem. Biol. Interact.,  2014, 218, 71-81.
[http://dx.doi.org/10.1016/j.cbi.2014.04.011] [PMID: 24792351] 
[240] 
Singh, S.K.; Dessalew, N.; Bharatam, P.V. 3D-QSAR CoMFA study on oxindole derivatives as cyclin dependent kinase 1 (CDK1) and cyclin dependent kinase 2 (CDK2) inhibitors. Med. Chem.,  2007, 3(1), 75-84.
[http://dx.doi.org/10.2174/157340607779317517] [PMID: 17266627] 
Rights & Permissions Print Cite
Article Metrics
20
1
Journal Information
For Authors
For Editors
For Reviewers
Explore Articles
Open Access
Open Access Articles
For Visitors
DOI https://dx.doi.org/10.2174/1568026621666210119112336	Print ISSN 1568-0266
Publisher Name Bentham Science Publisher	Online ISSN 1873-4294
Current Topics in Medicinal Chemistry

A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

Abstract Play Pause

Graphical Abstract

Related Journals

Related Books

Related Articles

Abstract
