From the Explored to the Unexplored: Computer-Tailored Drug Design Attempts in the Discovery of Selective Caspase Inhibitors

Ransford    O.    Kumi; Abdul    R.    Issahaku; Opeyemi    S.    Soremekun; Clement       Agoni; Fisayo    A.    Olotu; Mahmoud    E.S.    Soliman
doi:10.2174/1386207322666190927143026
Abstract

The pathophysiological roles of caspases have made them attractive targets in the treatment and amelioration of neurologic diseases. In normal conditions, the expression of caspases is regulated in the brain, while at the onset of neurodegeneration, such as in Alzheimer’s disease, they are typically overexpressed. Till date, several therapeutic efforts that include the use of small endogenous binders have been put forward to curtail dysfunctionalities that drive aberrant death in neuronal cells. Caspases are highly homologous, both in structure and in sequence, which leaves us with the question: is it possible to specifically and individually target caspases, while multiple therapeutic attempts to achieve selective targeting have failed! Based on antecedent events, the use of Computer-Aided Drug Design (CADD) methods has significantly contributed to the design of small molecule inhibitors, especially with selective target ability and reduced off-target therapeutic effects. Interestingly, we found out that there still exists an enormous room for the integration of structure/ligand-based drug design techniques towards the development of highly specific reversible and irreversible caspase inhibitors. Therefore, in this review, we highlight drug discovery approaches that have been directed towards caspase inhibition in addition to an insightful focus on applicable CADD techniques for achieving selective targeting in caspase research.
Keywords: Apoptosis, caspase, caspase activation, recruitment domain, death effector domain, caspase inhibitors, covalent docking, computer-aided drug design.
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[1] 
Kumar, S. Caspase function in programmed cell death. Cell Death Differ.,  2007, 14(1), 32-43.
[http://dx.doi.org/10.1038/sj.cdd.4402060] [PMID:  17082813] 
[2] 
Das Choudhury, J.; Kumar, S.; Mayank, V.; Mehta, J.; Berdalai, D. A review on apoptosis & its different pathway. Int. J. Biol. Pharm. Res.,  2012, 3, 848-861.
[3] 
Krishna Deepak, R.N.V.; Abdullah, A.; Talwar, P.; Fan, H.; Ravanan, P. Identification of FDA-approved drugs as novel allosteric inhibitors of human executioner caspases. Proteins,  2018, 86, 202-1210.
[http://dx.doi.org/10.1002/prot.25601] [PMID:  30194780] 
[4] 
Taylor, R.C.; Cullen, S.P.; Martin, S.J. Apoptosis: Controlled demolition at the cellular level. Nat. Rev. Mol. Cell Biol.,  2008, 9(3), 231-241.
[http://dx.doi.org/10.1038/nrm2312] [PMID:  18073771] 
[5] 
Creagh, E.M. Caspase crosstalk: integration of apoptotic and innate immune signalling pathways. Trends Immunol.,  2014, 35(12), 631-640.
[http://dx.doi.org/10.1016/j.it.2014.10.004] [PMID:  25457353] 
[6] 
Cade, C.E.; Clark, A.C. Caspases – Key Players in Apoptosis.Proteases in Apoptosis: Pathways, Protocols and Translational Advances; Bose, K., Ed.; Springer: Cham, 2015, pp. 31-52.
[7] 
McCall, K.; Steller, H. Facing death in the fly: genetic analysis of apoptosis in Drosophila. Trends Genet.,  1997, 13(6), 222-226.
[http://dx.doi.org/10.1016/S0168-9525(97)01126-8] [PMID:  9196327] 
[8] 
Galluzzi, L.; López-Soto, A.; Kumar, S.; Kroemer, G. Caspases connect cell-death signaling to organismal homeostasis. Immunity,  2016, 44(2), 221-231.
[http://dx.doi.org/10.1016/j.immuni.2016.01.020] [PMID:  26885855] 
[9] 
Cao, Q.; Wang, X.J.; Liu, C.W.; Liu, D.F.; Li, L.F.; Gao, Y.Q.; Su, X.D. Inhibitory mechanism of caspase-6 phosphorylation revealed by crystal structures, molecular dynamics simulations, and biochemical assays. J. Biol. Chem.,  2012, 287(19), 15371-15379.
[http://dx.doi.org/10.1074/jbc.M112.351213] [PMID:  22433863] 
[10] 
Mcilwain, D.R.; Berger, T.; Mak, T.W. Caspase functions in cell death and disease. Cold Spring Harb. Perspect. Biol.,  2013, 5(4)a008656
[http://dx.doi.org/10.1101/cshperspect.a008656] [PMID:  23545416] 
[11] 
Cerretti, D.P.; Kozlosky, C.J.; Mosley, B.; Nelson, N.; Van Ness, K.; Greenstreet, T.A.; March, C.J.; Kronheim, S.R.; Druck, T.; Cannizzaro, L.A.; Huebner, K.; Black, R.A. Molecular cloning of the interleukin-1 β converting enzyme. Science,  1992, 256(5053), 97-100.
[http://dx.doi.org/10.1126/science.1373520] [PMID:  1373520] 
[12] 
Sadowski-Debbing, K.; Coy, J.F.; Mier, W.; Hug, H.; Los, M. Caspases--their role in apoptosis and other physiological processes as revealed by knock-out studies. Arch. Immunol. Ther. Exp. (Warsz.),  2002, 50(1), 19-34.
[PMID:  11916306] 
[13] 
Pavelka, K.; Kua, V.; Rasmussen, J.M.; Mikkelsen, K.; Tamasi, L.; Vitek, P.; Rozman, B. Clinical Effects of Pralnacasan (PRAL), an Orally-Active Interleukin-1beta Converting Enzyme (ICE) inhibitor, in a 285 patient PhII trial in rheumatoid arthritis. Sci. Open,  2002, 2002, 3415-3415.
[14] 
Rudolphi, K.; Gerwin, N.; Verzijl, N.; van der Kraan, P.; van den Berg, W. Pralnacasan, an inhibitor of interleukin-1β converting enzyme, reduces joint damage in two murine models of osteoarthritis. Osteoarthritis Cartilage,  2003, 11(10), 738-746.
[http://dx.doi.org/10.1016/S1063-4584(03)00153-5] [PMID:  13129693] 
[15] 
Barreyro, F.J.; Holod, S.; Finocchietto, P.V.; Camino, A.M.; Aquino, J.B.; Avagnina, A.; Carreras, M.C.; Poderoso, J.J.; Gores, G.J. The pan-caspase inhibitor Emricasan (IDN-6556) decreases liver injury and fibrosis in a murine model of non-alcoholic steatohepatitis. Liver Int.,  2015, 35(3), 953-966.
[http://dx.doi.org/10.1111/liv.12570] [PMID:  24750664] 
[16] 
Hoglen, N.C.; Chen, L-S.; Fisher, C.D.; Hirakawa, B.P.; Groessl, T.; Contreras, P.C. Characterization of IDN-6556 (3-[2-(2-tert-butyl-phenylaminooxalyl)-amino]-propionylamino]-4-oxo-5-(2,3,5, 6-tetrafluoro-phenoxy)-pentanoic acid): a liver-targeted caspase inhibitor. J. Pharmacol. Exp. Ther.,  2004, 309(2), 634-640.
[http://dx.doi.org/10.1124/jpet.103.062034] [PMID:  14742742] 
[17] 
Pockros, P.J.; Schiff, E.R.; Shiffman, M.L.; McHutchison, J.G.; Gish, R.G.; Afdhal, N.H.; Makhviladze, M.; Huyghe, M.; Hecht, D.; Oltersdorf, T.; Shapiro, D.A. Oral IDN-6556, an antiapoptotic caspase inhibitor, may lower aminotransferase activity in patients with chronic hepatitis C. Hepatology,  2007, 46(2), 324-329.
[http://dx.doi.org/10.1002/hep.21664] [PMID:  17654603] 
[18] 
Wang, Q.; Mach, R.H.; Reichert, D.E. Docking and 3D-QSAR studies on isatin sulfonamide analogues as caspase-3 inhibitors. J. Chem. Inf. Model.,  2009, 49(8), 1963-1973.
[http://dx.doi.org/10.1021/ci900144x] [PMID:  19610597] 
[19] 
Zhou, D.; Chu, W.; Rothfuss, J.; Zeng, C.; Xu, J.; Jones, L.; Welch, M.J.; Mach, R.H. Synthesis, radiolabeling, and in vivo evaluation of an 18F-labeled isatin analog for imaging caspase-3 activation in apoptosis. Bioorg. Med. Chem. Lett.,  2006, 16(19), 5041-5046.
[http://dx.doi.org/10.1016/j.bmcl.2006.07.045] [PMID:  16891117] 
[20] 
Ekert, P.G.; Silke, J.; Vaux, D.L. Caspase inhibitors. Cell Death Differ.,  1999, 6(11), 1081-1086.
[http://dx.doi.org/10.1038/sj.cdd.4400594] [PMID:  10578177] 
[21] 
Schotte, P.; Declercq, W.; Van Huffel, S.; Vandenabeele, P.; Beyaert, R. Non-specific effects of methyl ketone peptide inhibitors of caspases. FEBS Lett.,  1999, 442(1), 117-121.
[http://dx.doi.org/10.1016/S0014-5793(98)01640-8] [PMID:  9923616] 
[22] 
Caporuscio, F.; Tafi, A. Pharmacophore modelling: A forty year old approach and its modern synergies. Curr. Med. Chem.,  2011, 18(17), 2543-2553.
[http://dx.doi.org/10.2174/092986711795933669] [PMID:  21568893] 
[23] 
Bhunia, S.S.; Singh, S.; Saxena, S.; Saxena, A.K. Pharmacophore modeling, docking and molecular dynamics studies on caspase-3 activators binding at beta-tubulin site. Curr. Comput. Des.,2015. Curr. Comput. Aided Drug Des.,  2015, 11(1), 72-83.
[PMID:  26126610] 
[24] 
Kumar, S.P.; Jha, P.C. Multi-level structure-based pharmacophore modelling of caspase-3-non-peptide complexes: Extracting essential pharmacophore features and its application to virtual screening. Chem. Biol. Interact.,  2016, 254, 207-220.
[http://dx.doi.org/10.1016/j.cbi.2016.06.011] [PMID:  27291469] 
[25] 
Modeling, M.; Inhibitors, C. Multi-pharmacophore modeling of caspase-3 inhibitors using crystal, dock and flexible conformation schemes. Comb. Chem. High Throughput Screen.,  2018, 21(1), 26-40.
[26] 
Langer, T.; Hoffmann, R.D. Pharmacophore modelling: Applications in drug discovery. Expert Opin. Drug Discov.,  2006, 1(3), 261-267.
[http://dx.doi.org/10.1517/17460441.1.3.261] [PMID:  23495846] 
[27] 
Berendsen, H.J.C.; Postma, J.P.M.; van Gunsteren, W.F.; Hermans, J.; van Gunsteren, W.F. Interaction Models for Water in Relation to Protein Hydration. In: Intermolecular Forces; Pullman. B., Ed., 1981; pp. 331-338.  [http://10.1007/978-94-015-7658-1_21] 
[28] 
Macalino, S.J.Y.; Basith, S.; Clavio, N.A.B.; Chang, H.; Kang, S.; Choi, S. Evolution of in silico strategies for protein-protein interaction drug discovery. Molecules,  2018, 23(8)E1963
[http://dx.doi.org/10.3390/molecules23081963] [PMID:  30082644] 
[29] 
Wang, J.; Chou, K. Molecular modeling of cytochrome P450 and drug metabolism. Curr. Drug Metab.,  2010, 4, 342-346.
[http://dx.doi.org/10.2174/138920010791514180] 
[30] 
Walters, J.; Schipper, J.L.; Swartz, P.; Mattos, C.; Clark, A.C. Allosteric modulation of caspase 3 through mutagenesis. Biosci. Rep.,  2012, 32, 401-411.
[http://dx.doi.org/10.1042/BSR20120037] 
[31] 
Cai, S.X.; Nguyen, B.; Jia, S.; Herich, J.; Guastella, J.; Reddy, S.; Tseng, B.; Drewe, J.; Kasibhatla, S. Discovery of substituted N-phenyl nicotinamides as potent inducers of apoptosis using a cell- and caspase-based high throughput screening assay. J. Med. Chem.,  2003, 46(12), 2474-2481.
[http://dx.doi.org/10.1021/jm0205200] [PMID:  12773051] 
[32] 
Ruiz-Torres, V.; Encinar, J.A.; Herranz-López, M.; Pérez-Sánchez, A.; Galiano, V.; Barrajón-Catalán, E.; Micol, V. An updated review on marine anticancer compounds: The use of virtual screening for the discovery of small-molecule cancer drugs. Molecules,  2017, 22(7), 22.
[http://dx.doi.org/10.3390/molecules22071037] [PMID:  28644406] 
[33] 
Cozza, G.; Bonvini, P.; Zorzi, E.; Poletto, G.; Pagano, M.A.; Sarno, S.; Donella-Deana, A.; Zagotto, G.; Rosolen, A.; Pinna, L.A.; Meggio, F.; Moro, S. Identification of ellagic acid as potent inhibitor of protein kinase CK2: A successful example of a virtual screening application. J. Med. Chem.,  2006, 49(8), 2363-2366.
[http://dx.doi.org/10.1021/jm060112m] [PMID:  16610779] 
[34] 
Matsuno, K.; Masuda, Y.; Uehara, Y.; Sato, H.; Muroya, A.; Takahashi, O.; Yokotagawa, T.; Furuya, T.; Okawara, T.; Otsuka, M.; Ogo, N.; Ashizawa, T.; Oshita, C.; Tai, S.; Ishii, H.; Akiyama, Y.; Asai, A. Identification of a new series of STAT3 inhibitors by virtual screening. ACS Med. Chem. Lett.,  2010, 1(8), 371-375.
[http://dx.doi.org/10.1021/ml1000273] [PMID:  24900220] 
[35] 
Bhattacharjee, B.; Chatterjee, J. Identification of proapoptopic, anti-inflammatory, anti- proliferative, anti-invasive and anti-angiogenic targets of essential oils in cardamom by dual reverse virtual screening and binding pose analysis. Asian Pac. J. Cancer Prev.,  2013, 14(6), 3735-3742.
[http://dx.doi.org/10.7314/APJCP.2013.14.6.3735] [PMID:  23886174] 
[36] 
Hajimahdi, Z.; Safizadeh, F.; Zarghi, A. QSAR analysis for some 1, 2-benzisothiazol-3-one derivatives as caspase-3 inhibitors by stepwise MLR method. Iran. J. Pharm. Res.,  2016, 15(2), 439-448.
[PMID:  27642314] 
[37] 
Verma, R.P. Understanding apoptosis in terms of QSAR. Anticancer. Agents Med. Chem.,  2006, 6(1), 41-52.
[http://dx.doi.org/10.2174/187152006774755528] [PMID:  16475926] 
[38] 
Abdel-Ilah, L.; Veljovic, E.; Lejla, G.; Badnjevic, A. Applications of QSAR study in drug design. IJERT,  2017, 6, 582-587.
[39] 
Malet, G.; Martín, A.G.; Orzáez, M.; Vicent, M.J.; Masip, I.; Sanclimens, G.; Ferrer-Montiel, A.; Mingarro, I.; Messeguer, A.; Fearnhead, H.O.; Pérez-Payá, E. Small molecule inhibitors of Apaf-1-related caspase- 3/-9 activation that control mitochondrial-dependent apoptosis. Cell Death Differ.,  2006, 13(9), 1523-1532.
[http://dx.doi.org/10.1038/sj.cdd.4401828] [PMID:  16341125] 
[40] 
Endres, M.; Namura, S.; Shimizu-Sasamata, M.; Waeber, C.; Zhang, L.; Gómez-Isla, T.; Hyman, B.T.; Moskowitz, M.A. Attenuation of delayed neuronal death after mild focal ischemia in mice by inhibition of the caspase family. J. Cereb. Blood Flow Metab.,  1998, 18(3), 238-247.
[http://dx.doi.org/10.1097/00004647-199803000-00002] [PMID:  9498840] 
[41] 
Powers, J.C.; Asgian, J.L.; James, K.E. PowersJC02ChemRev_SerCysThr irreversible inhibitor.Pdf 2002.
[42] 
Poreba, M.; Strózyk, A.; Salvesen, G.S.; Drag, M. Caspase substrates and inhibitors. Cold Spring Harb. Perspect. Biol.,  2013, 5(8)a008680
[http://dx.doi.org/10.1101/cshperspect.a008680] [PMID:  23788633] 
[43] 
Gyrd-Hansen, M.; Meier, P. IAPs: from caspase inhibitors to modulators of NF-kappaB, inflammation and cancer. Nat. Rev. Cancer,  2010, 10(8), 561-574.
[http://dx.doi.org/10.1038/nrc2889] [PMID:  20651737] 
[44] 
Oberholzer, C.; Tschoeke, S.K.; Moldawer, L.L.; Oberholzer, A. Local thymic caspase-9 inhibition improves survival during polymicrobial sepsis in mice. J. Mol. Med. (Berl.),  2006, 84(5), 389-395.
[http://dx.doi.org/10.1007/s00109-005-0017-1] [PMID:  16453149] 
[45] 
Colak, A.; Karaoğlan, A.; Barut, S.; Köktürk, S.; Akyildiz, A.I.; Taşyürekli, M. Neuroprotection and functional recovery after application of the caspase-9 inhibitor z-LEHD-fmk in a rat model of traumatic spinal cord injury. J. Neurosurg. Spine,  2005, 2(3), 327-334.
[http://dx.doi.org/10.3171/spi.2005.2.3.0327] [PMID:  15796358] 
[46] 
St-Louis, M.C.; Massie, B.; Archambault, D. The bovine viral diarrhea virus (BVDV) NS3 protein, when expressed alone in mammalian cells, induces apoptosis which correlates with caspase-8 and caspase-9 activation. Vet. Res.,  2005, 36(2), 213-227.
[http://dx.doi.org/10.1051/vetres:2004059] [PMID:  15720974] 
[47] 
Medina, E.A.; Afsari, R.R.; Ravid, T.; Castillo, S.S.; Erickson, K.L.; Goldkorn, T. Tumor necrosis factor-alpha decreases Akt protein levels in 3T3-L1 adipocytes via the caspase-dependent ubiquitination of Akt. Endocrinology,  2005, 146(6), 2726-2735.
[http://dx.doi.org/10.1210/en.2004-1074] [PMID:  15746249] 
[48] 
Hardy, J.A.; Lam, J.; Nguyen, J.T.; O’Brien, T.; Wells, J.A. Discovery of an allosteric site in the caspases. Proc. Natl. Acad. Sci. USA,  2004, 101(34), 12461-12466.
[http://dx.doi.org/10.1073/pnas.0404781101] [PMID:  15314233] 
[49] 
Lee, H.; Shin, E.A.; Lee, J.H.; Ahn, D.; Kim, C.G.; Kim, J.H.; Kim, S.H. Caspase inhibitors : A review of recently patented compounds (2013-2015). Expert Opin. Ther. Pat.,  2018, 28, 47-59.
[http://dx.doi.org/10.1080/13543776.2017.1378426] [PMID:  28885866] 
[50] 
Manuscript, A. NIH Public Access.,  2013, 69, 679-689.
[51] 
Lee, D.; Long, S.A.; Adams, J.L.; Chan, G.; Vaidya, K.S.; Francis, T.A.; Kikly, K.; Winkler, J.D.; Sung, C.M.; Debouck, C.; Richardson, S.; Levy, M.A.; DeWolf, W.E., Jr; Keller, P.M.; Tomaszek, T.; Head, M.S.; Ryan, M.D.; Haltiwanger, R.C.; Liang, P.H.; Janson, C.A.; McDevitt, P.J.; Johanson, K.; Concha, N.O.; Chan, W.; Abdel-Meguid, S.S.; Badger, A.M.; Lark, M.W.; Nadeau, D.P.; Suva, L.J.; Gowen, M.; Nuttall, M.E.; Vaidya, K.S.; Francis, T.A.; Kikly, K.; Winkler, J.D.; Sung, C.; Debouck, C.; Richardson, S.; Levy, M.A.; Dewolf, W.E.; Keller, P.M.; Tomaszek, T.; Head, M.S.; Ryan, M.D.; Haltiwanger, R.C.; Liang, P.; Janson, C.A.; Mcdevitt, P.J.; Johanson, K.; Concha, N.O.; Chan, W.; Abdel-meguid, S.S.; Badger, A.M.; Lark, M.W.; Nadeau, D.P.; Suva, L.J.; Gowen, M.; Nuttall, M.E. Potent and selective nonpeptide inhibitors of caspases 3 and 7 inhibit apoptosis and maintain cell functionality. J. Biol. Chem.,  2000, 275(21), 16007-16014.
[http://dx.doi.org/10.1074/jbc.275.21.16007] [PMID:  10821855] 
[52] 
Trott, O.; Olson, A.J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem.,  2010, 31(2), 455-461.
[PMID:  19499576] 
[53] 
Lopes, P.E.M.; Guvench, O.; MacKerell, A.D.J., Jr Current status of protein force fields for molecular dynamics simulations. Methods Mol. Biol.,  2015, 1215, 47-71.
[http://dx.doi.org/10.1007/978-1-4939-1465-4_3] [PMID:  25330958] 
[54] 
Amber, C. Amber 2018 Reference Manual. 2018.
[55] 
Pol-Fachin, L.; Rusu, V.H.; Verli, H.; Lins, R.D. GROMOS 53A6GLYC, an Improved GROMOS Force Field for Hexopyranose-Based Carbohydrates. J. Chem. Theory Comput.,  2012, 8(11), 4681-4690.
[http://dx.doi.org/10.1021/ct300479h] [PMID:  26605624] 
[56] 
Halgren, T.A. Merck Molecular Force Field. I. Basis, Form, Scope, Parameterization, and Performance of MMFF94. J. Comput. Chem.,  1996, 17, 490-519.
[http://dx.doi.org/10.1002/(SICI)1096-987X(199604)17:5/6<490: AID-JCC1>3.0.CO;2-P] 
[57] 
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.,  2010, 31(4), 671-690.
[PMID:  19575467] 
[58] 
Monticelli, L.; Tieleman, D.P. Force fields for classical molecular dynamics. Methods Mol. Biol.,  2013, 924, 197-213.
[http://dx.doi.org/10.1007/978-1-62703-017-5_8] [PMID:  23034750] 
[59] 
Dastmalchi, S. Methods and algorithms for molecular docking-based. Drug Des. Discov.,  2016, 456.
[60] 
Johari, S.; Sinha, S.; Bora, S. Ligand Binding Studies of Caspase 3 Protein with Compounds of Bacopa Monneri - A Target Protein Responsible for Alzheimer’ s Disease (AD); Springer, 2012, pp. 37-43.
[61] 
Khan, S.; Ahmad, K.; Alshammari, E.M.A.; Adnan, M.; Baig, M.H.; Lohani, M.; Somvanshi, P.; Haque, S. Implication of caspase-3 as a common therapeutic target for multineurodegenerative disorders and its inhibition using nonpeptidyl natural compounds. Biomed Res. Int.,  2015, 2015, ID 379817..
[http://dx.doi.org/10.1155/2015/379817] 
[62] 
Stank, A.; Kokh, D.B.; Fuller, J.C.; Wade, R.C. Protein binding pocket dynamics. Acc. Chem. Res.,  2016, 49(5), 809-815.
[http://dx.doi.org/10.1021/acs.accounts.5b00516] [PMID:  27110726] 
[63] 
Roberts, B.C.; Mancera, R.L. Ligand-protein docking with water molecules. J. Chem. Inf. Model.,  2008, 48(2), 397-408.
[http://dx.doi.org/10.1021/ci700285e] [PMID:  18211049] 
[64] 
Corbeil, C.R.; Englebienne, P.; Moitessier, N. Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0. J. Chem. Inf. Model.,  2007, 47(2), 435-449.
[http://dx.doi.org/10.1021/ci6002637] [PMID:  17305329] 
[65] 
Waszkowycz, B.; Clark, D.E.; Gancia, E. Outstanding challenges in protein–ligand docking and structure-based virtual screening. Comput. Mol. Sci.,  2011, 1, 229-259.
[http://dx.doi.org/10.1002/wcms.18] 
[66] 
Schröder, J.; Klinger, A.; Oellien, F.; Marhöfer, R.J.; Duszenko, M.; Selzer, P.M. Docking-based virtual screening of covalently binding ligands: An orthogonal lead discovery approach. J. Med. Chem.,  2013, 56(4), 1478-1490.
[http://dx.doi.org/10.1021/jm3013932] [PMID:  23350811] 
[67] 
Zhu, K.; Borrelli, K.W.; Greenwood, J.R.; Day, T.; Abel, R.; Farid, R.S.; Harder, E. Docking covalent inhibitors: A parameter free approach to pose prediction and scoring. J. Chem. Inf. Model.,  2014, 54(7), 1932-1940.
[http://dx.doi.org/10.1021/ci500118s] [PMID:  24916536] 
[68] 
Scholz, C.; Knorr, S.; Hamacher, K.; Schmidt, B. DOCKTITE-a highly versatile step-by-step workflow for covalent docking and virtual screening in the molecular operating environment. J. Chem. Inf. Model.,  2015, 55(2), 398-406.
[http://dx.doi.org/10.1021/ci500681r] [PMID:  25541749] 
[69] 
Vilar, S.; Cozza, G.; Moro, S. Medicinal chemistry and the molecular operating environment (MOE): Application of QSAR and molecular docking to drug discovery. Curr. Top. Med. Chem.,  2008, 8(18), 1555-1572.
[http://dx.doi.org/10.2174/156802608786786624] [PMID:  19075767] 
[70] 
Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol.,  1996, 261(3), 470-489.
[http://dx.doi.org/10.1006/jmbi.1996.0477] [PMID:  8780787] 
[71] 
Ouyang, X.; Zhou, S.; Su, C.T.T.; Ge, Z.; Li, R.; Kwoh, C.K. CovalentDock: Automated covalent docking with parameterized covalent linkage energy estimation and molecular geometry constraints. J. Comput. Chem.,  2013, 34(4), 326-336.
[http://dx.doi.org/10.1002/jcc.23136] [PMID:  23034731] 
[72] 
Scarpino, A.; Ferenczy, G.G.; Keserű, G.M. Comparative evaluation of covalent docking tools. J. Chem. Inf. Model.,  2018, 58(7), 1441-1458.
[http://dx.doi.org/10.1021/acs.jcim.8b00228] [PMID:  29890081] 
[73] 
Prieto-Martínez, F.D.; Arciniega, M.; Medina-Franco, J.L. Acoplamiento Molecular: Avances Recientes y Retos. TIP Rev. Espec. en Ciencias Químico-Biológicas,  2018, 21, 65-87.
[74] 
Sharma, S.; Basu, A.; Agrawal, R.K. Pharmacophore Modeling and Docking Studies on Some Nonpeptide-Based Caspase-3 Inhibitors. BioMed Res. Int.,  2013, 2013, Article ID 306081.
[http://dx.doi.org/10.1155/2013/306081] 
[75] 
Van Drie, J.H. Strategies for the determination of pharmacophoric 3D database queries. J. Comput. Aided Mol. Des.,  1997, 11(1), 39-52.
[http://dx.doi.org/10.1023/A:1008019326401] [PMID:  9139111] 
[76] 
Wood, D.J.; de Vlieg, J.; Wagener, M.; Ritschel, T. Pharmacophore fingerprint-based approach to binding site subpocket similarity and its application to bioisostere replacement. J. Chem. Inf. Model.,  2012, 52(8), 2031-2043.
[http://dx.doi.org/10.1021/ci3000776] [PMID:  22830492] 
[77] 
Güner, O.F. History and evolution of the pharmacophore concept in computer-aided drug design. Curr. Top. Med. Chem.,  2002, 2(12), 1321-1332.
[http://dx.doi.org/10.2174/1568026023392940] [PMID:  12470283] 
[78] 
Kurczab, R.; Bojarski, A.J. New strategy for receptor-based pharmacophore query construction: a case study for 5-HT7 receptor ligands. J. Chem. Inf. Model.,  2013, 53(12), 3233-3243.
[http://dx.doi.org/10.1021/ci4005207] [PMID:  24245803] 
[79] 
Goto, J.; Kataoka, R.; Hirayama, N. Ph4Dock: pharmacophore-based protein-ligand docking. J. Med. Chem.,  2004, 47(27), 6804-6811.
[http://dx.doi.org/10.1021/jm0493818] [PMID:  15615529] 
[80] 
Wolber, G.; Seidel, T.; Bendix, F.; Langer, T. Molecule-pharmacophore superpositioning and pattern matching in computational drug design. Drug Discov. Today,  2008, 13(1-2), 23-29.
[http://dx.doi.org/10.1016/j.drudis.2007.09.007] [PMID:  18190860] 
[81] 
Qing, X.; Lee, X.Y.; De Raeymaeker, J.; Tame, J.R.; Zhang, K.Y.; De Maeyer, M.; Voet, A.R. Pharmacophore modeling: Advances, limitations, and current utility in drug discovery. J. Receptor Ligand Channel Res.,  2014, 7, 81-92.
[82] 
Ahmad, K.; Balaramnavar, V.M.; Baig, M.H.; Srivastava, A.K.; Khan, S.; Kamal, M.A. Identification of potent caspase-3 inhibitors for treatment of multi- neurodegenerative diseases using pharmacophore modeling and docking approaches. CNS Neurol. Disord. Drug Targets,  2014, 13(8), 1346-1353.
[http://dx.doi.org/10.2174/1871527313666141023120843] [PMID:  25345515] 
[83] 
Lin, J.H.; Lu, A.Y. Role of pharmacokinetics and metabolism in drug discovery and development. Pharmacol. Rev.,  1997, 49(4), 403-449.
[PMID:  9443165] 
[84] 
Christ, F.; Voet, A.; Marchand, A.; Nicolet, S.; Desimmie, B.A.; Marchand, D.; Bardiot, D.; Van der Veken, N.J.; Van Remoortel, B.; Strelkov, S.V.; De Maeyer, M.; Chaltin, P.; Debyser, Z. Rational design of small-molecule inhibitors of the LEDGF/p75-integrase interaction and HIV replication. Nat. Chem. Biol.,  2010, 6(6), 442-448.
[http://dx.doi.org/10.1038/nchembio.370] [PMID:  20473303] 
[85] 
Böhm, H.J. The computer program LUDI: A new method for the de novo design of enzyme inhibitors. J. Comput. Aided Mol. Des.,  1992, 6(1), 61-78.
[http://dx.doi.org/10.1007/BF00124387] [PMID:  1583540] 
[86] 
Lazarova, M. Virtual screening – models, methods and software systems. Int. Sci. Conf. Comput. Sci.,  2008, 2008, 55-60.
[87] 
Klopmand, G. Concepts and applications of molecular similarity, by Mark A. Johnson and Gerald M. Maggiora, Eds., John Wiley & Sons, New York, 1990, 393 Pp. Price: $65.00.J. Comput. Chem; , 1992, 13, pp. 539-540.
[88] 
Waszkowycz, B.; Perkins, T.D.J.; Sykes, R.A.; Li, J. Large-scale virtual screening for discovering leads in the postgenomic era. IBM Syst. J.,  2001, 40, 360-376.
[http://dx.doi.org/10.1147/sj.402.0360] 
[89] 
Yoshimori, A.; Takasawa, R.; Tanuma, S. A novel method for evaluation and screening of caspase inhibitory peptides by the amino acid positional fitness score. BMC Pharmacol.,  2004, 4, Article Number 7.
[http://dx.doi.org/10.1186/1471-2210-4-7] [PMID:  15154972] 
[90] 
Chothia, C.; Lesk, A.M. The relation between the divergence of sequence and structure in proteins. EMBO J.,  1986, 5(4), 823-826.
[http://dx.doi.org/10.1002/j.1460-2075.1986.tb04288.x] [PMID:  3709526] 
[91] 
Brandman, R.; Brandman, Y.; Pande, V.S. A-site residues move independently from P-site residues in all-atom molecular dynamics simulations of the 70S bacterial ribosome. PLoS One,  2012, 7(1)e29377
[http://dx.doi.org/10.1371/journal.pone.0029377] [PMID:  22235290] 
[92] 
Sulpizi, M.; Rothlisberger, U.; Carloni, P. Molecular dynamics studies of caspase-3. Biophys. J.,  2003, 84(4), 2207-2215.
[http://dx.doi.org/10.1016/S0006-3495(03)75026-7] [PMID:  12668429] 
[93] 
Patel, S.; Modi, P.; Chhabria, M. Rational approach to identify newer caspase-1 inhibitors using pharmacophore based virtual screening, docking and molecular dynamic simulation studies. J. Mol. Graph. Model.,  2018, 81, 106-115.
[http://dx.doi.org/10.1016/j.jmgm.2018.02.017] [PMID:  29549805] 
[94] 
Kumalo, H.M.; Bhakat, S.; Soliman, M.E.S. Theory and applications of covalent docking in drug discovery: Merits and pitfalls. Molecules,  2015, 20(2), 1984-2000.
[http://dx.doi.org/10.3390/molecules20021984] [PMID:  25633330] 
[95] 
Morris, G.M.; Goodsell, D.S.; Pique, M.E.; Lindstrom, W.L.; Huey, R.; Hart, W.E.; Halliday, S.; Belew, R.; Olson, A.J. AutoDock Version 4.2; User Guid, 2009, pp. 1-49.
[96] 
Friesner, R.A.; Banks, J.L.; Murphy, R.B.; Halgren, T.A.; Klicic, J.J.; Mainz, D.T.; Repasky, M.P.; Knoll, E.H.; Shelley, M.; Perry, J.K.; Shaw, D.E.; Francis, P.; Shenkin, P.S.; Glide, A. Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem.,  2004, 47(7), 1739-1749.
[http://dx.doi.org/10.1021/jm0306430] [PMID:  15027865] 
[97] 
Jones, G.; Willett, P.; Glen, R.C.; Leach, A.R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol.,  1997, 267(3), 727-748.
[http://dx.doi.org/10.1006/jmbi.1996.0897] [PMID:  9126849] 
[98] 
Xu, G.; Cirilli, M.; Huang, Y.; Rich, R.L.; Myszka, D.G.; Wu, H. Covalent inhibition revealed by the crystal structure of the caspase-8/p35 complex. Nature,  2001, 410(6827), 494-497.
[http://dx.doi.org/10.1038/35068604] [PMID:  11260720] 
[99] 
Flores, J.; Noël, A.; Foveau, B.; Lynham, J.; Lecrux, C.; LeBlanc, A.C. Caspase-1 inhibition alleviates cognitive impairment and neuropathology in an Alzheimer’s disease mouse model. Nat. Commun.,  2018, 9(1), 3916.
[http://dx.doi.org/10.1038/s41467-018-06449-x] [PMID:  30254377] 
[100] 
Smith, A.J.T.; Zhang, X.; Leach, A.G.; Houk, K.N. Beyond picormolar affinities: Quantitative aspects of noncovalent and covalent binding of drugs to proteins. J. Med.,  2010, 52, 225-233.
[101] 
Salomon-ferrer, R.; Case, D.A.; Walker, R.C. An overview of the amber biomolecular simulation package. Comput. Mol. Sci.,  2012, 3, 198-210.
[http://dx.doi.org/10.1002/wcms.1121] 
[102] 
Weedbrook, C.; Pirandola, S.; Cerf, N.J.; Ralph, T.C. Gaussian quantum information. Rev. Mod. Phys.,  2012, 84, 621.
[http://dx.doi.org/10.1103/RevModPhys.84.621] 
[103] 
Huang, J.; Rauscher, S.; Nawrocki, G.; Ran, T.; Feig, M.; de Groot, B.L.; Grubmüller, H.; MacKerell, A.D., Jr CHARMM36m: An improved force field for folded and intrinsically disordered proteins. Nat. Methods,  2017, 14(1), 71-73.
[http://dx.doi.org/10.1038/nmeth.4067] [PMID:  27819658] 
[104] 
Phillips, J.C.; Braun, R.; Wang, W.; Gumbart, J.; Tajkhorshid, E.; Villa, E.; Chipot, C.; Skeel, R.D.; Kalé, L.; Schulten, K. Scalable molecular dynamics with NAMD. J. Comput. Chem.,  2005, 26(16), 1781-1802.
[http://dx.doi.org/10.1002/jcc.20289] [PMID:  16222654] 
[105] 
Khan, S.; Bjij, I.; Olotu, F.A.; Agoni, C.; Adeniji, E.S.; Soliman, M.E. Covalent simulations of covalent/irreversible enzyme inhibition in drug discovery: A reliable technical protocol. Future Med. Chem.,  2018, 10(19), 2265-2275.
[http://dx.doi.org/10.4155/fmc-2017-0304] [PMID:  30273013] 
[106] 
Lonsdale, R.; Burgess, J.; Colclough, N.; Davies, N.L.; Lenz, E.M.; Orton, A.L.; Ward, R.A. Expanding the armory: Predicting and tuning covalent warhead reactivity. J. Chem. Inf. Model.,  2017, 57(12), 3124-3137.
[http://dx.doi.org/10.1021/acs.jcim.7b00553] [PMID:  29131621] 
[107] 
Jöst, C.; Nitsche, C.; Scholz, T.; Roux, L.; Klein, C.D. Promiscuity and selectivity in covalent enzyme inhibition: A systematic study of electrophilic fragments. J. Med. Chem.,  2014, 57(18), 7590-7599.
[http://dx.doi.org/10.1021/jm5006918] [PMID:  25148591] 
[108] 
Wishart, D.S. Introduction to cheminformatics. Curr. Protoc. Bioinforma,  2016, 2016, 14.1.1-14.1.21..
[http://dx.doi.org/10.1002/0471250953.bi1401s53] 
[109] 
Olotu, F.; Adeniji, E.; Agoni, C.; Bjij, I.; Khan, S.; Elrashedy, A.; Soliman, M. An update on the discovery and development of selective heat shock protein inhibitors as anti-cancer therapy. Expert Opin. Drug Discov.,  2018, 13(10), 903-918.
[http://dx.doi.org/10.1080/17460441.2018.1516035] [PMID:  30207185] 
[110] 
Lawal, M.; Olotu, F.A.; Soliman, M.E.S. Across the blood-brain barrier: Neurotherapeutic screening and characterization of naringenin as a novel CRMP-2 inhibitor in the treatment of Alzheimer’s disease using bioinformatics and computational tools. Comput. Biol. Med.,  2018, 98, 168-177.
[http://dx.doi.org/10.1016/j.compbiomed.2018.05.012] [PMID:  29860210] 
[111] 
Olotu, F.A.; Munsamy, G.; Soliman, M.E.S. Does size really matter? Probing the efficacy of structural reduction in the optimization of bioderived compounds - a computational “proof-of-concept”. Comput. Struct. Biotechnol. J.,  2018, 16, 573-586.
[http://dx.doi.org/10.1016/j.csbj.2018.11.005] [PMID:  30546858] 
[112] 
Drwal, M.N.; Banerjee, P.; Dunkel, M.; Wettig, M.R.; Preissner, R. ProTox: A web server for the in silico prediction of rodent oral toxicity.  Nucleic Acids Res.,  2014, 42(Web Server issue), W53-58.
[http://dx.doi.org/10.1093/nar/gku401] [PMID:  24838562] 
[113] 
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] 
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DOI https://dx.doi.org/10.2174/1386207322666190927143026	Print ISSN 1386-2073
Publisher Name Bentham Science Publisher	Online ISSN 1875-5402
Combinatorial Chemistry & High Throughput Screening

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