

In silico screening for the interaction of small molecules with their targets and evaluation of therapeutic efficacy by free online tools
Praveen Kumar (1,*)





(1) Department of Biochemistry, Kuvempu University, Jnana Sahyadri 577451, Shimoga, Karnataka, India
(2) Department of Pharmaceutical Chemistry, Kuvempu University, Post Graduate Centre, Kadur 577458, Chikkamagaluru Dist., Karnataka, India
(3) Center of Excellence in Molecular Biology and Regenerative Medicine Laboratory, Department of Biochemistry, Jagadguru Sri Shivarathreeshwara Medical College, Academy of Higher Education and Research, Mysuru, Karnataka, 570015, India
(4) Department of Biotechnology, Kuvempu University, Jnana Sahyadri 577451, Shimoga, Karnataka, India
(5) Department of Biochemistry, Kuvempu University, Jnana Sahyadri 577451, Shimoga, Karnataka, India
(*) Corresponding Author
Received: 24 Jan 2020 | Revised: 17 Apr 2020 | Accepted: 21 Apr 2020 | Published: 30 Jun 2020 | Issue Date: June 2020
Abstract
Pharmaceutical chemistry deals with the process of isolating organic compounds from natural sources or chemically synthesizing them in order to explore potential drugs. Drugs are small molecules, used to prevent or treat various diseases. Of several lead molecules, only few of them reach clinical trial phases and emerge as effective drugs, whereas the majority will be eliminated at different stages. On the other hand, due to the lack of proper identification of their pharmacokinetic properties and biological potential, many small molecules fail to reach this stage. This could be because of the fact that it is either time consuming and costly or there is full of uncertainty due to lack of analyses that are necessary for the confirmation. In the post-genomic era, computational methods have been implemented in almost all stages of drug research and development owing to the drastic increase in the available knowledge about small molecules and the target biomacromolecule. This includes identifying the suitable and specific targets for drug candidates, lead discovery, lead optimization and ultimately preclinical phases. In this context, numerous websites have become highly valuable and influence the drug development and discovery process. Here, we have attempted to bring together some of the online computational approaches and tools that are available to facilitate research efforts in the field of drug discovery and drug design. The output information from these tools is extremely helpful in selecting and deciding about the future direction or specific path needed to be followed by the researchers. These computational methods are indeed help to focus the intended research in the right direction. As detailed in this review, the information provided about the servers and methods should be useful throughout the process of screening of synthesized or chemical database originated small molecules to find the appropriate targets along with the active sites without depending on any commercial tools or time-consuming and costly assays. It should however be remembered that the bioinformatics-based prediction cannot completely replace the wet lab data of chemical compounds or specific assays.
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European Journal of Chemistry
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DOI: 10.5155/eurjchem.11.2.168-178.1962
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European Journal of Chemistry 14(1), 30, 2023
DOI: 10.5155/eurjchem.14.1.30-38.2350

References
[1]. Fang, Y.; Ding, Y.; Feinstein, W. P.; Koppelman, D. M.; Moreno, J.; Jarrell, M.; Ramanujam, J.; Brylinski, M. PLoS ONE 2016, 11(7), e0158898.
https://doi.org/10.1371/journal.pone.0158898
[2]. Bode, J. W.; Reactor ChemAxon Ltd. Retrieved December 15, 2019, from https://chemaxon.com/
[3]. Cousins, K. R. Chemdraw Ultra 12. 0. Retrieved December 17, 2019 from https://chemdrawdirect.perkinelmer.cloud/js/sample/index.html
[4]. Smith, T. J. J. Mol. Graphics 1995, 13(2), 122-125.
https://doi.org/10.1016/0263-7855(94)00019-O
[5]. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Adv Drug Deliv. Rev. 2001, 46(1-3), 3-26.
https://doi.org/10.1016/S0169-409X(00)00129-0
[6]. Duffy, F. J.; Devocelle M.; Shields, D. C. Computational Approaches to Developing Short Cyclic Peptide Modulators of Protein-Protein Interactions. In: Zhou P., Huang J. (eds) Computational Peptidology. Methods in Molecular Biology, vol 1268. Humana Press, New York, NY, 2015.
https://doi.org/10.1007/978-1-4939-2285-7_11
[7]. Silverman, R. B.; Holladay, M. W. The organic chemistry of drug design and drug action. Academic press, ISBN 978-0-12-382030-3, 2016.
[8]. Kostal, J. Computational Chemistry in Predictive Toxicology: Status Quo et Quo Vadis? In Advances in Molecular Toxicology, Ed. J. Fishbein, Elsevier, San Diego, 2016, vol. 10, pp. 139-186.
https://doi.org/10.1016/B978-0-12-804700-2.00004-0
[9]. Ertl, P.; Rohde, B.; Selzer, P. J. Med. Chem. 2000, 43(20), 3714-3717.
https://doi.org/10.1021/jm000942e
[10]. Edwards, R. A.; Olsen, G. J.; Maloy, S. R. Trends Microbiol. 2002, 10(2), 94-99.
https://doi.org/10.1016/S0966-842X(01)02293-4
[11]. Murtaza, S.; Altaf, A. A.; Hamayun, M.; Iftikhar, K.; Tahir, M. N.; Tariq, J.; Faiz, K. Eur. J. Chem. 2019, 10(4), 358-366.
https://doi.org/10.5155/eurjchem.10.4.358-366.1859
[12]. Cheminformatics, M. Calculation of molecular properties and bioactivity score, Retrieved November 26, 2019, from http://www.molinspiration.com
[13]. Norinder, U.; Bergstrom, C. A. ChemMedChem 2006, 1(9), 920-937.
https://doi.org/10.1002/cmdc.200600155
[14]. Veber, D. F.; Johnson, S. R.; Cheng, H. Y.; Smith, B. R.; Ward, K. W.; Kopple, K. D. J. Med. Chem. 2002, 45(12), 2615-2623.
https://doi.org/10.1021/jm020017n
[15]. Ritchie, T. J.; Macdonald, S. J.; Peace, S.; Pickett, S. D.; Luscombe, C. N. Med. Chem. Comm. 2013, 4(4), 673-680.
https://doi.org/10.1039/c3md00003f
[16]. Thakker, D. R.; Hoyer, D.; Cryan, J. F. Pharmacol. Therapeut. 2006, 109(3), 413-438.
https://doi.org/10.1016/j.pharmthera.2005.08.006
[17]. Alavijeh, M. S.; Chishty, M.; Qaiser, M. Z.; Palmer, A. M. Neurotherapeutics 2005, 2(4), 554-571.
https://doi.org/10.1602/neurorx.2.4.554
[18]. Baringhaus, K. H.; Matter, H.; Stengelin, S.; Kramer, W. J. Lipid Res. 1999, 40, 2158-2168.
[19]. Kwon, Y., Handbook of essential pharmacokinetics, pharmaco-dynamics and drug metabolism for industrial scientists. New York: Kluwer Academic/Plenum Publishers, 2001.
[20]. Jiang, P.; Li, Q.; Lu, J. IOP Conf. Ser.: Earth Environ. Sci. 2018, 178, 012020.
https://doi.org/10.1088/1755-1315/178/1/012020
[21]. Kerns, E. H.; Di, L., Drug-like properties: concepts, structure design and methods from ADME to toxicity optimization, Academic press, ISBN 978-0-12-369520-8, 2008.
[22]. Manallack, D. T. Perspec. Med. Chem. 2007, 1, 25-48.
https://doi.org/10.1177/1177391X0700100003
[23]. Irwin, J. J.; Shoichet, B. K. J. Chem. Inform. Model. 2005, 45(1), 177-182.
https://doi.org/10.1021/ci049714+
[24]. Van De Waterbeemd, H.; Smith, D. A.; Beaumont, K.; Walker, D. K. J. Med. Chem. 2001, 44(9), 1313-1333.
https://doi.org/10.1021/jm000407e
[25]. Chan, O. H.; Stewart, B. H. Drug Discov. Today 1996, 1(11), 461-473.
https://doi.org/10.1016/1359-6446(96)10039-8
[26]. Harris, D. A. Trends Biochem. Sci. 1993, 18(9), 354.
https://doi.org/10.1016/0968-0004(93)90073-V
[27]. Baell, J. B.; Holloway, G. A. J. Med. Chem. 2010, 53(7), 2719-2740.
https://doi.org/10.1021/jm901137j
[28]. Daina, A.; Michielin, O.; Zoete, V. Sci. Reports 2017, 7, 42717.
https://doi.org/10.1038/srep42717
[29]. Yang, H.; Lou, C.; Sun, L.; Li, J.; Cai, Y.; Wang, Z.; Li, W.; Liu, G.; Tang, Y. Bioinformatics 2019, 35(6), 1067-1069.
https://doi.org/10.1093/bioinformatics/bty707
[30]. Dong, J.; Wang, N. N.; Yao, Z. J.; Zhang, L.; Cheng, Y.; Ouyang, D.; Lu, A. P.; Cao, D. S. J. Cheminfor. 2018, 10(1), 29.
https://doi.org/10.1186/s13321-018-0283-x
[31]. Pires, D. E.; Blundell, T. L.; Ascher, D. B. J. Med. Chem. 2015, 58(9), 4066-4072.
https://doi.org/10.1021/acs.jmedchem.5b00104
[32]. Schyman, P.; Liu, R.; Desai, V.; Wallqvist, A. Frontiers Pharmacol. 2017, 8, 889, 1-14.
https://doi.org/10.3389/fphar.2017.00889
[33]. Lee, S. K.; Park, S. H.; Lee, I. H.; No, K. T. PreAD-MET Ver. v2. 0, Seoul, Korea, Bioinformatics and Molecular Design Research, BMDRC, 2007.
[34]. Banerjee, P.; Eckert, A. O.; Schrey. A. K.; Preissner, R. Nucleic Acids Res. 2018, 46(W1), W257-W263.
https://doi.org/10.1093/nar/gky318
[35]. Wishart, D. S.; Feunang, Y. D.; Guo, A. C.; Lo, E. J.; Marcu, A.; Grant, J. R.; Sajed, T.; Johnson, D.; Li, C; Sayeeda, Z.; Assempour, N. Nucleic Acids Res. 2018, 46(D1), D1074-1082.
https://doi.org/10.1093/nar/gkx1037
[36]. Dalvie, D.; Kalgutkar, A. S.; Chen, W. Drug Metabol. Rev. 2015, 47(1), 56-70.
https://doi.org/10.3109/03602532.2014.984813
[37]. Rydberg, P.; Gloriam, D. E.; Olsen, L. Bioinformatics 2010, 26(23), 2988-2989.
https://doi.org/10.1093/bioinformatics/btq584
[38]. Rydberg, P.; Gloriam, D. E.; Zaretzki, J.; Breneman, C.; Olsen, L. ACS Med. Chem. Let. 2010, 1(3), 96-100.
https://doi.org/10.1021/ml100016x
[39]. Zhang, Y.; Chen, G.; Ma, H.; Guo, M. Molecules 2019, 24(1), 166, 19.
https://doi.org/10.3390/molecules24010166
[40]. Rose, P. W.; Prlic, A.; Altunkaya, A.; Bi, C.; Bradley, A. R.; Christie, C. H.; Costanzo, L. D.; Duarte, J. M.; Dutta, S.; Feng, Z.; Green, R. K.; Goodsell, D. S.; Hudson, B.; Kalro, T.; Lowe, R.; Peisach, E.; Randle, C.; Rose, A. S.; Shao, C.; Tao, Y. P.; Valasatava, Y.; Voigt, M.; Westbrook, J. D.; Woo, J.; Yang, H.; Young, J. Y.; Zardecki, C.; Berman, H. M.; Burley, S. K. Nucleic Acids Res. 2017, 45(D1), D271-D281.
[41]. Tian, W.; Chen, C.; Lei, X.; Zhao, J.; Liang, J. Nucleic Acids Res. 2018, 46(W1), W363-W367.
https://doi.org/10.1093/nar/gky473
[42]. Dundas, J.; Ouyang, Z.; Tseng, J.; Binkowski, A.; Turpaz, Y.; Liang, J. Nucleic Acids Res. 2006, 34(Suppl2), W116-W118.
https://doi.org/10.1093/nar/gkl282
[43]. Tian, W.; Chen, C.; Liang, J. Biophys. J. 2018, 114(3), (Suppl1), 50a.
https://doi.org/10.1016/j.bpj.2017.11.325
[44]. Laskowski, R. A.; Hutchinson, E. G.; Michie, A. D.; Wallace, A. C.; Jones, M. L.; Thornton, J. M. Trends Biochem. Sci. 1997, 22(12), 488-490.
https://doi.org/10.1016/S0968-0004(97)01140-7
[45]. Basta, H. A.; Sgro, J. Y.; Palmenberg, A. C. Virology. 2014, 448, 176-184.
https://doi.org/10.1016/j.virol.2013.10.006
[46]. Laskowski, R. A.; MacArthur, M. W.; Moss, D. S.; Thornton, J. M. J. Appl. Crystallog. 1993, 26(2), 283-291.
https://doi.org/10.1107/S0021889892009944
[47]. Mering, C. V.; Huynen, M.; Jaeggi, D.; Schmidt, S.; Bork, P.; Snel, B. Nucleic Acids Res. 2003, 31(1), 258-261.
https://doi.org/10.1093/nar/gkg034
[48]. Grosdidier, A.; Zoete, V.; Michielin, O. Nucleic Acids Res. 2011, 39(Suppl2), W270-W277.
https://doi.org/10.1093/nar/gkr366
[49]. Kiss, R.; Sandor, M.; Szalai, F. A. J. Cheminform. 2012, 4, P17.
https://doi.org/10.1186/1758-2946-4-S1-P17
[50]. Labbe, C. M.; Rey, J.; Lagorce, D.; Vavrusa. M.; Becot, J.; Sperandio. O.; Villoutreix, B. O.; Tuffery, P.; Miteva, M. A. Nucleic Acids Res. 2015, 43(W1), W448-W454.
https://doi.org/10.1093/nar/gkv306
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