Login Register Cart 0
Generic placeholder image

Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

In silico Identification of HDAC Inhibitors for Multiple Myeloma: A Structure-based Virtual Screening, Drug Likeness, ADMET Profiling, Molecular Docking, and Molecular Dynamics Simulation Study

Author(s): Abhijit Debnath*, Rupa Mazumder, Avijit Mazumder, Rajesh Singh and Shikha Srivastava

Volume 21, Issue 5, 2024

Published on: 14 February, 2023

Page: [961 - 978] Pages: 18

DOI: 10.2174/1570180820666230125102954

Price: $65

conference banner
Abstract

Background: Multiple myeloma (MM) is a hematological malignancy of plasma cells that produce a monoclonal immunoglobulin protein. Despite significant advances in the treatment of MM, currently available therapies are associated with toxicity and resistance. As a result, there is an increasing demand for novel, effective therapeutics. Inhibition of histone deacetylases (HDACs) is emerging as a potential method for treating cancer. HDAC6 is one of 18 different HDAC isoforms that regulate tubulin lysine 40 and function in the microtubule network. HDAC6 participates in tumorigenesis and metastasis through protein ubiquitination, tubulin, and Hsp90. Several studies have found that inhibiting HDAC6 causes AKT and ERK dephosphorylation, which leads to decreased cell proliferation and promotes cancer cell death via the PI3K/AKT and MAPK/ERK signaling pathways.

Objective: The objective of this study is to target HDAC6 and identify potent inhibitors for the treatment of multiple myeloma by employing computer-aided drug design.

Materials and Methods: A total of 199,611,439 molecules from five different chemical databases, such as CHEMBL25, ChemSpace, Mcule, MolPort, and ZINC, have been screened against HDAC6 by structure- based virtual screening, followed by filtering for various drug-likeness, ADME, toxicity, consensus molecular docking, and 100 ns MD simulation.

Results: Our research work resulted in three molecules that have shown strong binding affinity (CHEMBL2425964 -9.99 kcal/mol, CHEMBL2425966 -9.89 kcal/mol, and CSC067477144 -9.86 kcal/mol) at the active site HDAC6, along with effective ADME properties, low toxicity, and high stability. Inhibiting HDAC6 with these identified molecules will induce AKT and ERK dephosphorylation linked to reduced cell proliferation and promote cancer cell death.

Conclusion: CHEMBL2425964, CHEMBL2425966, and CSC067477144 could be effective against multiple myeloma.

« Previous Next »
Graphical Abstract

[1]
Kyle, R.A.; Rajkumar, S.V. Treatment of multiple myeloma: A comprehensive review. Clin. Lymphoma Myeloma, 2009, 9(4), 278-288.
[http://dx.doi.org/10.3816/CLM.2009.n.056] [PMID: 19717377]
[2]
Cohen, Y.C.; Zada, M.; Wang, S.Y.; Bornstein, C.; David, E.; Moshe, A.; Li, B.; Shlomi-Loubaton, S.; Gatt, M.E.; Gur, C.; Lavi, N.; Ganzel, C.; Luttwak, E.; Chubar, E.; Rouvio, O.; Vaxman, I.; Pasvolsky, O.; Ballan, M.; Tadmor, T.; Nemets, A.; Jarchowcky-Dolberg, O.; Shvetz, O.; Laiba, M.; Shpilberg, O.; Dally, N.; Avivi, I.; Weiner, A.; Amit, I. Identification of resistance pathways and therapeutic targets in relapsed multiple myeloma patients through single-cell sequencing. Nat. Med., 2021, 27(3), 491-503.
[http://dx.doi.org/10.1038/s41591-021-01232-w] [PMID: 33619369]
[3]
Palumbo, A.; Anderson, K. Multiple myeloma. N. Engl. J. Med., 2011, 364(11), 1046-1060.
[http://dx.doi.org/10.1056/NEJMra1011442] [PMID: 21410373]
[4]
Chavda, S.J.; Yong, K. Multiple myeloma. Br. J. Hosp. Med. (Lond.), 2017, 78(2), C21-C27.
[http://dx.doi.org/10.12968/hmed.2017.78.2.C21] [PMID: 28165783]
[5]
Mateo, G.; Montalbán, M.A.; Vidriales, M.B.; Lahuerta, J.J.; Mateos, M.V.; Gutiérrez, N.; Rosiñol, L.; Montejano, L.; Bladé, J.; Martínez, R.; de la Rubia, J.; Diaz-Mediavilla, J.; Sureda, A.; Ribera, J.M.; Ojanguren, J.M.; de Arriba, F.; Palomera, L.; Terol, M.J.; Orfao, A.; San Miguel, J.F. Prognostic value of immunophenotyping in multiple myeloma: a study by the PETHEMA/GEM cooperative study groups on patients uniformly treated with high-dose therapy. J. Clin. Oncol., 2008, 26(16), 2737-2744.
[http://dx.doi.org/10.1200/JCO.2007.15.4120] [PMID: 18443352]
[6]
Bobin, A.; Liuu, E.; Moya, N.; Gruchet, C.; Sabirou, F.; Lévy, A.; Gardeney, H.; Nsiala, L.; Cailly, L.; Guidez, S.; Tomowiak, C.; Systchenko, T.; Javaugue, V.; Durand, G.; Leleu, X.; Puyade, M. Multiple myeloma: An overview of the current and novel therapeutic approaches in 2020. Cancers (Basel), 2020, 12(10), 2885.
[http://dx.doi.org/10.3390/cancers12102885] [PMID: 33050025]
[7]
Marzin, Y; Jamet, D; Douet-Guilbert, N; Morel, F; Le Bris, MJ Morice, P Chromosome 1 abnormalities in multiple myeloma. Anticancer Res., 2006, 262 A, 953-9.
[8]
Håland, E.; Moen, I.N.; Veidal, E.; Hella, H.; Misund, K.; Slørdahl, T.S.; Starheim, K.K. TAK1-inhibitors are cytotoxic for multiple myeloma cells alone and in combination with melphalan. Oncotarget, 2021, 12(21), 2158-2168.
[http://dx.doi.org/10.18632/oncotarget.28073] [PMID: 34676048]
[9]
Chapman, M.A.; Lawrence, M.S.; Keats, J.J.; Cibulskis, K.; Sougnez, C.; Schinzel, A.C.; Harview, C.L.; Brunet, J.P.; Ahmann, G.J.; Adli, M.; Anderson, K.C.; Ardlie, K.G.; Auclair, D.; Baker, A.; Bergsagel, P.L.; Bernstein, B.E.; Drier, Y.; Fonseca, R.; Gabriel, S.B.; Hofmeister, C.C.; Jagannath, S.; Jakubowiak, A.J.; Krishnan, A.; Levy, J.; Liefeld, T.; Lonial, S.; Mahan, S.; Mfuko, B.; Monti, S.; Perkins, L.M.; Onofrio, R.; Pugh, T.J.; Rajkumar, S.V.; Ramos, A.H.; Siegel, D.S.; Sivachenko, A.; Stewart, A.K.; Trudel, S.; Vij, R.; Voet, D.; Winckler, W.; Zimmerman, T.; Carpten, J.; Trent, J.; Hahn, W.C.; Garraway, L.A.; Meyerson, M.; Lander, E.S.; Getz, G.; Golub, T.R. Initial genome sequencing and analysis of multiple myeloma. Nature, 2011, 471(7339), 467-472.
[http://dx.doi.org/10.1038/nature09837] [PMID: 21430775]
[10]
Skinner, M. Multiple myeloma in the spotlight. Nat. Rev. Cancer, 2011, 11(5), 312-312.
[http://dx.doi.org/10.1038/nrc3059] [PMID: 21508965]
[11]
Padala, S.A.; Barsouk, A.; Barsouk, A.; Rawla, P.; Vakiti, A.; Kolhe, R.; Kota, V.; Ajebo, G.H. Epidemiology, staging, and management of multiple myeloma. Med. Sci. (Basel), 2021, 9(1), 3.
[http://dx.doi.org/10.3390/medsci9010003] [PMID: 33498356]
[12]
Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin., 2021, 71(3), 209-249.
[http://dx.doi.org/10.3322/caac.21660] [PMID: 33538338]
[13]
Lonial, S.; Dimopoulos, M.; Palumbo, A.; White, D.; Grosicki, S.; Spicka, I.; Walter-Croneck, A.; Moreau, P.; Mateos, M.V.; Magen, H.; Belch, A.; Reece, D.; Beksac, M.; Spencer, A.; Oakervee, H.; Orlowski, R.Z.; Taniwaki, M.; Röllig, C.; Einsele, H.; Wu, K.L.; Singhal, A.; San-Miguel, J.; Matsumoto, M.; Katz, J.; Bleickardt, E.; Poulart, V.; Anderson, K.C.; Richardson, P. Elotuzumab therapy for relapsed or refractory multiple myeloma. N. Engl. J. Med., 2015, 373(7), 621-631.
[http://dx.doi.org/10.1056/NEJMoa1505654] [PMID: 26035255]
[14]
Kuiper, R.; van Duin, M.; van Vliet, M.H.; Broijl, A.; van der Holt, B.; el Jarari, L.; van Beers, E.H.; Mulligan, G.; Avet-Loiseau, H.; Gregory, W.M.; Morgan, G.; Goldschmidt, H.; Lokhorst, H.M.; Sonneveld, P. Prediction of high- and low-risk multiple myeloma based on gene expression and the International Staging System. Blood, 2015, 126(17), 1996-2004.
[http://dx.doi.org/10.1182/blood-2015-05-644039] [PMID: 26330243]
[15]
Oortgiesen, BE; Driessen, JHM; Hoogendoorn, M; Kibbelaar, RE; Veeger, NJGM van den Bergh, JPW No decrease in fracture risk despite 15 years of treatment evolution for multiple myeloma patients: A Danish nationwide case-control study. Bone, 2020, 134, 115299.
[http://dx.doi.org/10.1182/blood-2019-122563]
[16]
European Medicine Agency. EU/3/19/2204 | Orphan designation for the treatment of multiple myeloma. European Medicines Agency Domenico Scarlattilaan 6 1083 HS Amsterdam, The Netherlands, 2020. Available from: https://www.ema.europa.eu/en/medicines/human/orphan-designations/eu3192204
[17]
Pinto, V.; Bergantim, R.; Caires, H.R.; Seca, H.; Guimarães, J.E.; Vasconcelos, M.H. Multiple myeloma: available therapies and causes of drug resistance. Cancers, 2020, 12(2), 407. 10.3390/cancers 12020407.
[18]
Vo, J.N.; Wu, Y.M.; Mishler, J.; Hall, S.; Mannan, R.; Wang, L.; Ning, Y.; Zhou, J.; Hopkins, A.C.; Estill, J.C.; Chan, W.K.B.; Yesil, J.; Cao, X.; Rao, A.; Tsodikov, A.; Talpaz, M.; Cole, C.E.; Ye, J.C.; Ailawadhi, S.; Berdeja, J.G.; Hofmeister, C.C.; Jagannath, S.; Jakubowiak, A.; Krishnan, A.; Kumar, S.; Levy, M.Y.; Lonial, S.; Orloff, G.J.; Siegel, D.; Trudel, S.; Usmani, S.Z.; Vij, R.; Wolf, J.L.; Zonder, J.A.; Bergsagel, P.L.; Auclair, D.; Cho, H.J.; Robinson, D.R.; Chinnaiyan, A.M. The genetic heterogeneity and drug resistance mechanisms of relapsed refractory multiple myeloma. Nat. Commun., 2022, 13(1), 3750.
[http://dx.doi.org/10.1038/s41467-022-31430-0] [PMID: 35768438]
[19]
Davis, L.N.; Sherbenou, D.W. Emerging therapeutic strategies to overcome drug resistance in multiple myeloma. Cancers (Basel), 2021, 13(7), 1686.
[http://dx.doi.org/10.3390/cancers13071686] [PMID: 33918370]
[20]
Robak, P.; Drozdz, I.; Szemraj, J.; Robak, T. Drug resistance in multiple myeloma. Cancer Treat. Rev., 2018, 70(September), 199-208.
[http://dx.doi.org/10.1016/j.ctrv.2018.09.001] [PMID: 30245231]
[21]
Ludwig, H.; Delforge, M.; Facon, T.; Einsele, H.; Gay, F.; Moreau, P.; Avet-Loiseau, H.; Boccadoro, M.; Hajek, R.; Mohty, M.; Cavo, M.; Dimopoulos, M.A.; San-Miguel, J.F.; Terpos, E.; Zweegman, S.; Garderet, L.; Mateos, M.V.; Cook, G.; Leleu, X.; Goldschmidt, H.; Jackson, G.; Kaiser, M.; Weisel, K.; van de Donk, N.W.C.J.; Waage, A.; Beksac, M.; Mellqvist, U.H.; Engelhardt, M.; Caers, J.; Driessen, C.; Bladé, J.; Sonneveld, P. Prevention and management of adverse events of novel agents in multiple myeloma: a consensus of the European Myeloma Network. Leukemia, 2018, 32(7), 1542-1560.
[http://dx.doi.org/10.1038/s41375-018-0040-1] [PMID: 29720735]
[22]
Wanchoo, R.; Abudayyeh, A.; Doshi, M.; Edeani, A.; Glezerman, I.G.; Monga, D.; Rosner, M.; Jhaveri, K.D. Renal toxicities of novel agents used for treatment of multiple myeloma. Clin. J. Am. Soc. Nephrol., 2017, 12(1), 176-189.
[http://dx.doi.org/10.2215/CJN.06100616] [PMID: 27654928]
[23]
Yoon, S.; Eom, G.H. HDAC and HDAC inhibitor: From cancer to cardiovascular diseases. Chonnam Med. J., 2016, 52(1), 1-11.
[http://dx.doi.org/10.4068/cmj.2016.52.1.1] [PMID: 26865995]
[24]
Nass, J.; Efferth, T. Drug targets and resistance mechanisms in multiple myeloma. Cancer Drug Resist., 2018, 1(2), 87-117.
[http://dx.doi.org/10.20517/cdr.2018.04]
[25]
Pulya, S.; Amin, S.A.; Adhikari, N.; Biswas, S.; Jha, T.; Ghosh, B. HDAC6 as privileged target in drug discovery: A perspective. Pharmacol. Res., 2021, 163, 105274.
[http://dx.doi.org/10.1016/j.phrs.2020.105274] [PMID: 33171304]
[26]
Hai, Y.; Christianson, D.W. Histone deacetylase 6 structure and molecular basis of catalysis and inhibition. Nat. Chem. Biol., 2016, 12(9), 741-747.
[http://dx.doi.org/10.1038/nchembio.2134] [PMID: 27454933]
[27]
Hontecillas-Prieto, L.; Flores-Campos, R.; Silver, A.; de Álava, E.; Hajji, N.; García-Domínguez, D.J. Synergistic enhancement of cancer therapy using hdac inhibitors: opportunity for clinical trials. Front. Genet., 2020, 11(September), 578011.
[http://dx.doi.org/10.3389/fgene.2020.578011] [PMID: 33024443]
[28]
Sun, X.; Xie, Y.; Sun, X.; Yao, Y.; Li, H.; Li, Z.; Yao, R.; Xu, K. The selective HDAC6 inhibitor Nexturastat A induces apoptosis, overcomes drug resistance and inhibits tumor growth in multiple myeloma. Biosci. Rep., 2019, 39(3), BSR20181916.
[http://dx.doi.org/10.1042/BSR20181916] [PMID: 30782785]
[29]
Berman, H.M.; Battistuz, T.; Bhat, T.N.; Bluhm, W.F.; Bourne, P.E.; Burkhardt, K.; Feng, Z.; Gilliland, G.L.; Iype, L.; Jain, S.; Fagan, P.; Marvin, J.; Padilla, D.; Ravichandran, V.; Schneider, B.; Thanki, N.; Weissig, H.; Westbroo, J.D.; Zardecki, C. The protein data bank. Acta Cryst., 2002, D58, 899-907.
[http://dx.doi.org/10.1107/S0907444902003451]
[30]
Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera?A visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612.
[http://dx.doi.org/10.1002/jcc.20084] [PMID: 15264254]
[31]
Tian, W; Chen, C; Lei, X; Zhao, J; Liang, J CASTp 3. 0: computed atlas of surface topography of proteins. Nucleic Acids Res., 2018, 46(W1), W363-W367.
[http://dx.doi.org/10.1093/nar/gky473]
[32]
Singh, T.; Biswas, D.; Jayaram, B. AADS - An automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors. J. Chem. Inf. Mod., 2011, 51(10), 2515-2527.
[http://dx.doi.org/10.1021/ci200193z]
[33]
O’Boyle, N.M.; Banck, M.; James, C.A.; Morley, C.; Vandermeersch, T.; Hutchison, G.R. Open Babel: An open chemical toolbox. J. Cheminform., 2011, 3(1), 33.
[http://dx.doi.org/10.1186/1758-2946-3-33] [PMID: 21982300]
[34]
Li, H.; Leung, K.S.; Wong, M.H. Idock: A multithreaded virtual screening tool for flexible ligand docking. 2012 IEEE Symp Comput Intell Comput Biol CIBCB 2012, 2012, pp. 77-84.
[http://dx.doi.org/10.1109/CIBCB.2012.6217214]
[35]
Daina, A.; Michielin, O.; Zoete, V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep., 2017, 7(1), 42717.
[http://dx.doi.org/10.1038/srep42717] [PMID: 28256516]
[36]
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev, 2001, 46(1-3), 3-26.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0]
[37]
Ghose, A.K.; Viswanadhan, V.N.; Wendoloski, J.J. A knowledge based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. A qualitative and quantitative characterization of known drug databases. J. Comb. Chem., 1999, 1, 1, 55-68.
[38]
Veber, DF; Johnson, SR; Cheng, H; Smith, BR; Ward, KW; Kopple, KD Molecular properties that influence the oral bioavailability of drug candidates. 2002, 2615-23..
[http://dx.doi.org/10.1021/jm020017n]
[39]
Muegge, I.; Heald, S.L.; Brittelli, D. Simple selection criteria for drug-like chemical matter. J. Med. Chem., 2001, 44(12), 1841-1846.
[http://dx.doi.org/10.1021/jm015507e]
[40]
Sander, T.; Freyss, J.; von Korff, M.; Rufener, C. DataWarrior: an open-source program for chemistry aware data visualization and analysis. J. Chem. Inf. Model., 2015, 55(2), 460-473.
[http://dx.doi.org/10.1021/ci500588j] [PMID: 25558886]
[41]
Allen, W.J.; Balius, T.E.; Mukherjee, S.; Brozell, S.R.; Moustakas, D.T.; Lang, P.T.; Case, D.A.; Kuntz, I.D.; Rizzo, R.C. DOCK 6: Impact of new features and current docking performance. J. Comput. Chem., 2015, 36(15), 1132-1156.
[http://dx.doi.org/10.1002/jcc.23905] [PMID: 25914306]
[42]
Grosdidier, A.; Zoete, V.; Michielin, O. SwissDock, a protein-small molecule docking web service based on EADock DSS. Nucleic Acids Res.,, 2011, 39(Web Server issue)(Suppl.), W270-W277.
[http://dx.doi.org/10.1093/nar/gkr366] [PMID: 21624888]
[43]
Trott, O.; Olson, AJ AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2009.
[http://dx.doi.org/10.1002/jcc.21334]
[44]
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30(16), 2785-2791.
[http://dx.doi.org/10.1002/jcc.21256] [PMID: 19399780]
[45]
Feinstein, W.P.; Brylinski, M. Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets. J. Cheminform., 2015, 7(1), 18.
[http://dx.doi.org/10.1186/s13321-015-0067-5] [PMID: 26082804]
[46]
Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A.E.; Berendsen, H.J.C. GROMACS: Fast, flexible, and free. J. Comput. Chem., 2005, 26(16), 1701-1718.
[http://dx.doi.org/10.1002/jcc.20291] [PMID: 16211538]
[47]
Brooks, B.R.; Brooks, C.; Mackerell, A.D.; Nilsson, L.; Petrella, R.J.; Roux, B. CHARMM: Molecular dynamics simulation package. J. Comput. Chem., 2009, 30(10), 1545-1614.
[http://dx.doi.org/10.1002/jcc.21287] [PMID: 19444816]
[48]
Berendsen, H.J.C.; van der Spoel, D.; van Drunen, R. GROMACS: A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun., 1995, 91(1-3), 43-56.
[http://dx.doi.org/10.1016/0010-4655(95)00042-E]
[49]
Pillai, G.G. Jupyter notebook for MD using gromacs. zenodo, 2020.
[50]
Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I.; Mackerell, A.D., Jr CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem., 2009, 31(4), 671-690.
[http://dx.doi.org/10.1002/jcc.21367] [PMID: 19575467]
[51]
Huang, J.; MacKerell, A.D., Jr CHARMM36 all-atom additive protein force field: Validation based on comparison to NMR data. J. Comput. Chem., 2013, 34(25), 2135-2145.
[http://dx.doi.org/10.1002/jcc.23354] [PMID: 23832629]
[52]
Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys., 1983, 79(2), 926-935.
[http://dx.doi.org/10.1063/1.445869]
[53]
Bondi, A. van der Waals Volumes and Radii. J. Phys. Chem., 1964, 68(3), 441-451.
[54]
Berendsen, H.J.C.; Postma, J.P.M.; van Gunsteren, W.F.; DiNola, A.; Haak, J.R. Molecular dynamics with coupling to an external bath. J. Chem. Phys., 1984, 81(8), 3684-3690.
[http://dx.doi.org/10.1063/1.448118]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy