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Current Topics in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

Research Article

Identification of High-affinity Small Molecules Targeting Gamma Secretase for the Treatment of Alzheimer’s Disease

Author(s): Meer Asif Ali, Sugunakar Vuree, Himshikha Goud, Tajamul Hussain, Anuraj Nayarisseri* and Sanjeev Kumar Singh*

Volume 19, Issue 13, 2019

Page: [1173 - 1187] Pages: 15

DOI: 10.2174/1568026619666190617155326

Price: $65

Abstract

Background: Alzheimers Disease (AD) is a neurodegenerative disease which is characterized by the deposition of amyloid plaques in the brain- a concept supported by most of the researchers worldwide. The main component of the plaques being amyloid-beta (Aβ42) results from the sequential cleavage of Amyloid precursor protein (APP) by beta and gamma secretase. This present study intends to inhibit the formation of amyloid plaques by blocking the action of gamma secretase protein with Inhibitors (GSI).

Methods: A number of Gamma Secretase Inhibitors (GSI) were targeted to the protein by molecular docking. The inhibitor having the best affinity was used as a subject for further virtual screening methods to obtain similar compounds. The generated compounds were docked again at the same docking site on the protein to find a compound with higher affinity to inhibit the protein. The highlights of virtually screened compound consisted of Pharmacophore Mapping of the docking site. These steps were followed by comparative assessments for both the compounds, obtained from the two aforesaid docking studies, which included interaction energy descriptors, ADMET profiling and PreADMET evaluations.

Results: 111 GSI classified as azepines, sulfonamides and peptide isosteres were used in the study. By molecular docking an amorpholino-amide, compound (22), was identified to be the high affinity compound GSI along with its better interaction profiles.The virtually screened pubchem compound AKOS001083915 (CID:24462213) shows the best affinity with gamma secretase. Collective Pharmacophore mapping (H bonds, electrostatic profile, binding pattern and solvent accesibility) shows a stable interaction. The resulting ADMETand Descriptor values were nearly equivalent.

Conclusion: These compounds identified herein hold a potential as Gamma Secretase inhibitors.According to PreADMET values the compound AKOS001083915 is effective and specific to the target protein. Its BOILED-egg plot analysis infers the compound permeable to blood brain barrier.Comparative study for both the compounds resulted in having nearly equivalent properties. These compounds have the capacity to inhibit the protein which is indirectly responsible for the formation of amyloid plaques and can be further put to in vitro pharmacokinetic and dynamic studies.

Keywords: Gamma-secretase inhibitors, Alzheimer's diseases, Drug designing, Molecular docking, Virtual screening, ADMET.

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[1]
Imbimbo, B.P.; Panza, F.; Frisardi, V.; Solfrizzi, V.; D’Onofrio, G.; Logroscino, G.; Seripa, D.; Pilotto, A. Therapeutic intervention for Alzheimer’s disease with γ-secretase inhibitors: Still a viable option? Expert Opin. Investig. Drugs, 2011, 20(3), 325-341.
[http://dx.doi.org/10.1517/13543784.2011.550572] [PMID: 21222550]
[2]
Hebert, L.E.; Weuve, J.; Scherr, P.A.; Evans, D.A. Alzheimer disease in the United States (2010–2050) estimated using the 2010 census. Neurology, 2013, 80(19), 1778-1783.
[3]
Hebert, L.E.; Beckett, L.A.; Scherr, P.A.; Evans, D.A. Annual incidence of Alzheimer disease in the United States projected to the years 2000 through 2050. Alzheimer Dis. Assoc. Disord., 2001, 15(4), 169-173.
[http://dx.doi.org/10.1097/00002093-200110000-00002] [PMID: 11723367]
[4]
Kurosumi, M.; Nishio, Y.; Osawa, S.; Kobayashi, H.; Iwatsubo, T.; Tomita, T.; Miyachi, H. Novel Notch-sparing γ-secretase inhibitors derived from a peroxisome proliferator-activated receptor agonist library. Bioorg. Med. Chem. Lett., 2010, 20(17), 5282-5285.
[http://dx.doi.org/10.1016/j.bmcl.2010.06.131] [PMID: 20650635]
[5]
Olson, R.E.; Albright, C.F. Recent progress in the medicinal chemistry of γ-secretase inhibitors. Curr. Top. Med. Chem., 2008, 8(1), 17-33.
[http://dx.doi.org/10.2174/156802608783334088] [PMID: 18220929]
[6]
Basi, G.S.; Hemphill, S.; Brigham, E.F.; Liao, A.; Aubele, D.L.; Baker, J.; Barbour, R.; Bova, M.; Chen, X.H.; Dappen, M.S.; Eichenbaum, T.; Goldbach, E.; Hawkinson, J.; Lawler-Herbold, R.; Hu, K.; Hui, T.; Jagodzinski, J.J.; Keim, P.S.; Kholodenko, D.; Latimer, L.H.; Lee, M.; Marugg, J.; Mattson, M.N.; McCauley, S.; Miller, J.L.; Motter, R.; Mutter, L.; Neitzel, M.L.; Ni, H.; Nguyen, L.; Quinn, K.; Ruslim, L.; Semko, C.M.; Shapiro, P.; Smith, J.; Soriano, F.; Szoke, B.; Tanaka, K.; Tang, P.; Tucker, J.A.; Ye, X.M.; Yu, M.; Wu, J.; Xu, Y.Z.; Garofalo, A.W.; Sauer, J.M.; Konradi, A.W.; Ness, D.; Shopp, G.; Pleiss, M.A.; Freedman, S.B.; Schenk, D. Amyloid precursor protein selective gamma-secretase inhibitors for treatment of Alzheimer’s disease. Alzheimers Res. Ther., 2010, 2(6), 36.
[http://dx.doi.org/10.1186/alzrt60] [PMID: 21190552]
[7]
Townsend, M.; Qu, Y.; Gray, A.; Wu, Z.; Seto, T.; Hutton, M.; Shearman, M.S.; Middleton, R.E. Oral treatment with a γ-secretase inhibitor improves long-term potentiation in a mouse model of Alzheimer’s disease. J. Pharmacol. Exp. Ther., 2010, 333(1), 110-119.
[http://dx.doi.org/10.1124/jpet.109.163691] [PMID: 20056779]
[8]
Martone, R.L.; Zhou, H.; Atchison, K.; Comery, T.; Xu, J.Z.; Huang, X.; Gong, X.; Jin, M.; Kreft, A.; Harrison, B.; Mayer, S.C.; Aschmies, S.; Gonzales, C.; Zaleska, M.M.; Riddell, D.R.; Wagner, E.; Lu, P.; Sun, S.C.; Sonnenberg-Reines, J.; Oganesian, A.; Adkins, K.; Leach, M.W.; Clarke, D.W.; Huryn, D.; Abou-Gharbia, M.; Magolda, R.; Bard, J.; Frick, G.; Raje, S.; Forlow, S.B.; Balliet, C.; Burczynski, M.E.; Reinhart, P.H.; Wan, H.I.; Pangalos, M.N.; Jacobsen, J.S. Begacestat (GSI-953): A novel, selective thiophene sulfonamide inhibitor of amyloid precursor protein γ-secretase for the treatment of Alzheimer’s disease. J. Pharmacol. Exp. Ther., 2009, 331(2), 598-608.
[http://dx.doi.org/10.1124/jpet.109.152975] [PMID: 19671883]
[9]
Henley, D.B.; May, P.C.; Dean, R.A.; Siemers, E.R. Development of semagacestat (LY450139), a functional γ-secretase inhibitor, for the treatment of Alzheimer’s disease. Expert Opin. Pharmacother., 2009, 10(10), 1657-1664.
[http://dx.doi.org/10.1517/14656560903044982] [PMID: 19527190]
[10]
Pasinetti, G.M. Compositions and methods for treating Alzheimer`s disease and related disorders and promoting a healthy nervous system. U.S. Patent 20160151301, 2nd June 2016. (Available at:. http://www.google.ch/patents/US20160151301?hl=de&cl=en
[11]
Gillman, K.W.; Starrett, J.E., Jr; Parker, M.F.; Xie, K.; Bronson, J.J.; Marcin, L.R.; McElhone, K.E.; Bergstrom, C.P.; Mate, R.A.; Williams, R.; Meredith, J.E., Jr; Burton, C.R.; Barten, D.M.; Toyn, J.H.; Roberts, S.B.; Lentz, K.A.; Houston, J.G.; Zaczek, R.; Albright, C.F.; Decicco, C.P.; Macor, J.E.; Olson, R.E. Discovery and evaluation of BMS-708163, a potent, selective and orally bioavailable γ-secretase inhibitor. ACS Med. Chem. Lett., 2010, 1(3), 120-124.
[http://dx.doi.org/10.1021/ml1000239] [PMID: 24900185]
[12]
Imbimbo, B.P.; Panza, F.; Frisardi, V.; Solfrizzi, V.; D’Onofrio, G.; Logroscino, G.; Seripa, D.; Pilotto, A. Therapeutic intervention for Alzheimer’s disease with γ-secretase inhibitors: still a viable option? Expert Opin. Investig. Drugs, 2011, 20(3), 325-341.
[http://dx.doi.org/10.1517/13543784.2011.550572] [PMID: 21222550]
[13]
Groth, C.; Alvord, W.G.; Quiñones, O.A.; Fortini, M.E. Pharmacological analysis of Drosophila melanogaster γ-secretase with respect to differential proteolysis of Notch and APP. Mol. Pharmacol., 2010, 77(4), 567-574.
[http://dx.doi.org/10.1124/mol.109.062471] [PMID: 20064975]
[14]
Okochi, M.; Fukumori, A.; Jiang, J.; Itoh, N.; Kimura, R.; Steiner, H.; Haass, C.; Tagami, S.; Takeda, M. Secretion of the Notch-1 Abeta-like peptide during Notch signaling. J. Biol. Chem., 2006, 281(12), 7890-7898.
[http://dx.doi.org/10.1074/jbc.M513250200] [PMID: 16434391]
[15]
Petit, A.; Pasini, A.; Alves Da Costa, C.; Ayral, E.; Hernandez, J.F.; Dumanchin-Njock, C.; Phiel, C.J.; Marambaud, P.; Wilk, S.; Farzan, M.; Fulcrand, P.; Martinez, J.; Andrau, D.; Checler, F. JLK isocoumarin inhibitors: Selective γ-secretase inhibitors that do not interfere with notch pathway in vitro or in vivo. J. Neurosci. Res., 2003, 74(3), 370-377.
[http://dx.doi.org/10.1002/jnr.10747] [PMID: 14598313]
[16]
De Strooper, B.; Annaert, W.; Cupers, P.; Saftig, P.; Craessaerts, K.; Mumm, J.S.; Schroeter, E.H.; Schrijvers, V.; Wolfe, M.S.; Ray, W.J.; Goate, A.; Kopan, R. A presenilin-1-dependent γ-secretase-like protease mediates release of Notch intracellular domain. Nature, 1999, 398(6727), 518-522.
[http://dx.doi.org/10.1038/19083] [PMID: 10206645]
[17]
Golde, T.E.; Koo, E.H.; Felsenstein, K.M.; Osborne, B.A.; Miele, L. γ-Secretase inhibitors and modulators. BiochimicaetBiophysicaActa (BBA)-. Biomembranes, 2013, 1828(12), 2898-2907.
[http://dx.doi.org/10.1016/j.bbamem.2013.06.005]
[18]
Wolfe, M.S. γ-Secretase inhibitors and modulators for Alzheimer’s disease. J. Neurochem., 2012, 120(s1)(Suppl. 1), 89-98.
[http://dx.doi.org/10.1111/j.1471-4159.2011.07501.x] [PMID: 22122056]
[19]
Augelli-Szafran, C.E.; Wei, H.X.; Lu, D.; Zhang, J.; Gu, Y.; Yang, T.; Osenkowski, P.; Ye, W.; Wolfe, M.S. Discovery of notch-sparing γ-secretase inhibitors. Curr. Alzheimer Res., 2010, 7(3), 207-209.
[http://dx.doi.org/10.2174/156720510791050920] [PMID: 20088802]
[20]
Krämer, A.; Mentrup, T.; Kleizen, B.; Rivera-Milla, E.; Reichenbach, D.; Enzensperger, C.; Nohl, R.; Täuscher, E.; Görls, H.; Ploubidou, A.; Englert, C.; Werz, O.; Arndt, H.D.; Kaether, C. Small molecules intercept Notch signaling and the early secretory pathway. Nat. Chem. Biol., 2013, 9(11), 731-738.
[http://dx.doi.org/10.1038/nchembio.1356] [PMID: 24077179]
[21]
Kurosumi, M.; Nishio, Y.; Osawa, S.; Kobayashi, H.; Iwatsubo, T.; Tomita, T.; Miyachi, H. Novel Notch-sparing γ-secretase inhibitors derived from a peroxisome proliferator-activated receptor agonist library. Bioorg. Med. Chem. Lett., 2010, 20(17), 5282-5285.
[http://dx.doi.org/10.1016/j.bmcl.2010.06.131] [PMID: 20650635]
[22]
Wolfe, M.S. γ-Secretase inhibitors and modulators for Alzheimer’s disease. J. Neurochem., 2012, 120(s1)(Suppl. 1), 89-98.
[http://dx.doi.org/10.1111/j.1471-4159.2011.07501.x] [PMID: 22122056]
[23]
Hopkins, C.R. ACS chemical neuroscience molecule spotlight on ELND006: another γ-secretase inhibitor fails in the clinic. ACS Chem. Neurosci., 2011, 2(6), 279-280.
[http://dx.doi.org/10.1021/cn2000469]
[24]
Bai, X.C.; Yan, C.; Yang, G.; Lu, P.; Ma, D.; Sun, L. An atomic structure of human [ggr]-secretase. Nature, 2015, 525(7568), 212-217.
[http://dx.doi.org/10.1038/nature14892]
[25]
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]
[26]
Nasr, A.B.; Ponnala, D.; Sagurthi, S.R.; Kattamuri, R.K.; Marri, V.K.; Gudala, S.; Lakkaraju, C.; Bandaru, S.; Nayarisseri, A. Molecular docking studies of FKBP12-mTOR inhibitors using binding predictions. Bioinformation, 2015, 11(6), 307-315.
[http://dx.doi.org/10.6026/97320630011307] [PMID: 26229292]
[27]
Cheng, F.; Li, W.; Zhou, Y.; Shen, J.; Wu, Z.; Liu, G.; Lee, P.W.; Tang, Y. (2012). admetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties. J. Chem. Inf. Model., 2012, 52(11), 3099-3105.
[http://dx.doi.org/ 10.1021/ci300367a]
[28]
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]
[29]
Sinha, C.; Nischal, A.; Bandaru, S.; Kasera, P.; Rajput, A.; Nayarisseri, A.; Khattri, S. An in silico approach for identification of novel inhibitors as a potential therapeutics targeting HIV-1 viral infectivity factor. Curr. Top. Med. Chem., 2015, 15(1), 65-72.
[http://dx.doi.org/10.2174/1568026615666150112114337] [PMID: 25579575]
[30]
Sinha, C.; Nischal, A.; Pant, K.K.; Bandaru, S.; Nayarisseri, A.; Khattri, S. Molecular docking analysis of RN18 and VEC5 in A3G-Vif inhibition. Bioinformation, 2014, 10(10), 611-616.
[http://dx.doi.org/10.6026/97320630010611] [PMID: 25489169]
[31]
Bandaru, S.; Marri, V.K.; Kasera, P.; Kovuri, P.; Girdhar, A.; Mittal, D.R.; Ikram, S.; Gv, R.; Nayarisseri, A. Structure based virtual screening of ligands to identify cysteinyl leukotriene receptor 1 antagonist. Bioinformation, 2014, 10(10), 652-657.
[http://dx.doi.org/10.6026/97320630010652] [PMID: 25489175]
[32]
Dunna, N.R.; Bandaru, S.; Akare, U.R.; Rajadhyax, S.; Gutlapalli, V.R.; Yadav, M.; Nayarisseri, A. Multiclass comparative virtual screening to identify novel Hsp90 inhibitors: a therapeutic breast cancer drug target. Curr. Top. Med. Chem., 2015, 15(1), 57-64.
[http://dx.doi.org/10.2174/1568026615666150112113627] [PMID: 25579569]
[33]
Bandaru, S.; Ponnala, D.; Lakkaraju, C.; Bhukya, C.K.; Shaheen, U.; Nayarisseri, A. Identification of high affinity non-peptidic small molecule inhibitors of MDM2-p53 interactions through structure-based virtual screening strategies. Asian Pac. J. Cancer Prev., 2015, 16(9), 3759-3765.
[http://dx.doi.org/10.7314/APJCP.2015.16.9.3759] [PMID: 25987034]
[34]
Akare, U.R.; Bandaru, S.; Shaheen, U.; Singh, P.K.; Tiwari, G.; Singare, P.; Nayarisseri, A.; Banerjee, T. Molecular docking approaches in identification of High affinity inhibitors of Human SMO receptor. Bioinformation, 2014, 10(12), 737-742.
[http://dx.doi.org/10.6026/97320630010737] [PMID: 25670876]
[35]
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]
[36]
Bandaru, S.; Prasad, M.H.; Jyothy, A.; Nayarisseri, A.; Yadav, M. Binding modes and pharmacophoric features of muscarinic antagonism and β2 agonism (MABA) conjugates. Curr. Top. Med. Chem., 2013, 13(14), 1650-1655.
[http://dx.doi.org/10.2174/15680266113139990115] [PMID: 23889054]
[37]
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]
[38]
Shaheen, U.; Akka, J.; Hinore, J.S.; Girdhar, A.; Bandaru, S.; Sumithnath, T.G.; Nayarisseri, A.; Munshi, A. Computer aided identification of sodium channel blockers in the clinical treatment of epilepsy using molecular docking tools. Bioinformation, 2015, 11(3), 131-137.
[http://dx.doi.org/10.6026/97320630011131] [PMID: 25914447]
[39]
Vuree, S.; Dunna, N.R.; Khan, I.A.; Alharbi, K.K.; Vishnupriya, S.; Soni, D.; Shah, P.; Chandok, H.; Yadav, M.; Nayarisseri, A. Pharmacogenomics of drug resistance in Breast Cancer Resistance Protein (BCRP) and its mutated variants. J. Pharm. Res., 2013, 6(7), 791-798.
[http://dx.doi.org/10.1016/j.jopr.2013.06.020]
[40]
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]
[41]
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]
[42]
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) ben-zamide 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]
[43]
Patidar, K.; Deshmukh, A.; Bandaru, S.; Lakkaraju, C.; Girdhar, A.; Vr, G.; Banerjee, T.; Nayarisseri, A.; Singh, S.K. Virtual Screening Approaches in Identification of Bioactive Compounds Akin to Delphinidin as Potential HER2 Inhibitors for the Treatment of Breast Cancer. Asian Pac. J. Cancer Prev., 2016, 17(4), 2291-2295.
[http://dx.doi.org/10.7314/APJCP.2016.17.4.2291] [PMID: 27221932]
[44]
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]
[45]
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]
[46]
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]
[47]
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]
[48]
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]
[49]
Divya Jain, T.U. Design of novel JAK3 Inhibitors towards rheumatoid arthritis using molecular docking analysis. Bioinformation, 2019, 15(2), 68-78.
[50]
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, 20187912765
[http://dx.doi.org/10.1155/2018/7912765] [PMID: 30693065]
[51]
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]
[52]
Padmini Gokhale, A.P.S.C. FLT3 inhibitor design using molecular docking based virtual screening for acute myeloid leukemia. Bioinformation, 2019, 15(2), 104-115.
[53]
Palak Shukla, R.K. Virtual Screening of IL-6 Inhibitors for Idiopathic Arthritis. Bioinformation, 2019, 15(2), 121-130.
[http://dx.doi.org/ 10.6026/97320630015121]
[54]
Trishang Udhwani, S.M. Design of PD-L1 inhibitors for lung cancer. Bioinformation, 2019, 15(2), 139-150.
[http://dx.doi.org/ 10.1177/1758835918763493]
[55]
Rao, D.M.; Nayarisseri, A.; Yadav, M.; Patel, D. Comparative modeling of methylentetrahydrofolate reductase (MTHFR) enzyme and its mutational assessment: In silico approach. Int. J. Bioinform.Res., 2010, 2(1), 5-9.
[http://dx.doi.org/10.9735/0975-3087.2.1.5-9]
[56]
Kelotra, S.; Jain, M.; Kelotra, A.; Jain, I.; Bandaru, S.; Nayarisseri, A.; Bidwai, A. An in silico appraisal to identify high affinity anti-apoptotic synthetic tetrapeptide inhibitors targeting the mammalian caspase 3 enzyme. Asian Pac. J. Cancer Prev., 2014, 15(23), 10137-10142.
[http://dx.doi.org/10.7314/APJCP.2014.15.23.10137] [PMID: 25556438]
[57]
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]
[58]
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]
[59]
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]
[60]
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]
[61]
Sharma, K.; Patidar, K.; Ali, M.A.; Patil, P.; Goud, H.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Structure-based virtual screening for the identification of high affinity compounds as potent VEGFR2 inhibitors for the treatment of renal cell carcinoma. Curr. Top. Med. Chem., 2018, 18(25), 2174-2185.
[http://dx.doi.org/10.2174/1568026619666181130142237] [PMID: 30499413]
[62]
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]
[63]
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]
[64]
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]
[65]
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]
[66]
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]
[67]
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. J. Pharm. Res., 2013, 6(9), 913-918.
[68]
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]
[69]
Singh, S.K.; Nayarisseri, A. 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]

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