Chemical space of naturally occurring compounds

References

[1] Dobson CM. Chemical space and biology. Nature. 2004;432:824–8.10.1038/nature03192Search in Google Scholar PubMed

[2] Lipinski C, Hopkins A. Navigating chemical space for biology and medicine. Nature. 2004;432:855–61.10.1038/nature03193Search in Google Scholar PubMed

[3] Awale M, Visini R, Probst D, Arús-Pous J, Reymond J-L. Chemical space: big data challenge for molecular diversity. Chimia. 2017;71:661–6.10.2533/chimia.2017.661Search in Google Scholar PubMed

[4] Naveja JJ, Rico-Hidalgo MP, Medina-Franco JL. Analysis of a large food chemical database: chemical space, diversity, and complexity. F1000Res. 2018;7.10.12688/f1000research.15440.1Search in Google Scholar PubMed

[5] López-Vallejo F, Giulianotti MA, Houghten RA, Medina-Franco JL. Expanding the medicinally relevant chemical space with compound libraries. Drug Discov Today. 2012;17:718–26.10.1016/j.drudis.2012.04.001Search in Google Scholar PubMed

[6] López-Vallejo F, Waddell J, Yongye AB, Houghten RA, Medina-Franco JL. A large scale classification of molecular fingerprints for the chemical space representation and SAR analysis. J Cheminform. 2012;4:P26.10.1186/1758-2946-4-S1-P26Search in Google Scholar

[7] Medina-Franco JL, Martinez-Mayorga K, Giulianotti MA, Houghten RA, Pinilla C. Visualization of the chemical space in drug discovery. Current Comput - Aided Drug Des. 2008;4:322–33.10.2174/157340908786786010Search in Google Scholar

[8] Osolodkin DI, Radchenko EV, Orlov AA, Voronkov AE, Palyulin VA, Zefirov NS. Progress in visual representations of chemical space. Expert Opin Drug Discov. 2015;10:959–73.10.1517/17460441.2015.1060216Search in Google Scholar PubMed

[9] Opassi G, Gesù A, Massarotti A. The hitchhiker’s guide to the chemical-biological galaxy. Drug Discov Today. 2018;23:565–74.10.1016/j.drudis.2018.01.007Search in Google Scholar PubMed

[10] Newman DJ, Cragg GM. Natural products as sources of new drugs from 1981 to 2014. J Nat Prod. 2016;79:629–61.10.1021/acs.jnatprod.5b01055Search in Google Scholar PubMed

[11] Bauer A, Brönstrup M. Industrial natural product chemistry for drug discovery and development. Nat Prod Rep. 2014;31:35–60.10.1039/C3NP70058ESearch in Google Scholar PubMed

[12] Harvey AL, Edrada-Ebel R, Quinn RJ. The re-emergence of natural products for drug discovery in the genomics era. Nat Rev Drug Discov. 2015;14:111–29.10.1038/nrd4510Search in Google Scholar PubMed

[13] Alvarec-Ruiz E, Collis AJ, Dann AS, Forsbury AP, Reddy SJ, Vázquez Muniz MJ, Microbiological process. Patent. 2017. https://patentimages.storage.googleapis.com/96/8b/de/87242640defaa1/CN106687596A.pdf. Accessed: 30 Sep 2018.Search in Google Scholar

[14] Pereira DM, Valentão P, Andrade PB. Tuning protein folding in lysosomal storage diseases: the chemistry behind pharmacological chaperones. Chem Sci. 2018;9:1740–52.10.1039/C7SC04712FSearch in Google Scholar PubMed

[15] Zhanel GG, Lawson CD, Zelenitsky S, Findlay B, Schweizer F, Adam H, et al. Comparison of the next-generation aminoglycoside plazomicin to gentamicin, tobramycin and amikacin. Expert Rev Anti Infect Ther. 2012;10:459–73.10.1586/eri.12.25Search in Google Scholar PubMed

[16] Cobb R, Boeckh A. Moxidectin: a review of chemistry, pharmacokinetics and use in horses. Parasit Vectors. 2009;2:S5.10.1186/1756-3305-2-S2-S5Search in Google Scholar PubMed PubMed Central

[17] Ca G, Ci F, Ag P, Chen C, Tipping R, Cm C, et al. Safety, tolerability, and pharmacokinetics of escalating high doses of ivermectin in healthy adult subjects. J Clin Pharmacol. 2002;42:1122–33.10.1177/009127002401382731Search in Google Scholar PubMed

[18] Brandt W, Haupt VJ, Wessjohann LA. Chemoinformatic analysis of biologically active macrocycles. Curr Top Med Chem. 2010;10:1361–79.10.2174/156802610792232060Search in Google Scholar PubMed

[19] Wessjohann LA, Ruijter E, Garcia-Rivera D, Brandt W. What can a chemist learn from nature’s macrocycles? – A brief, conceptual view. Mol Divers. 2005;9:171–86.10.1007/s11030-005-1314-xSearch in Google Scholar PubMed

[20] Cuevas C, Francesch A. Development of Yondelis (trabectedin, ET-743). A semisynthetic process solves the supply problem. Nat Prod Rep. 2009;26:322–37.10.1039/b808331mSearch in Google Scholar PubMed

[21] Gajdos C, Elias A. Trabectedin: safety and efficacy in the treatment of advanced sarcoma. Clin Med Insights Oncol. 2011;5:35–43.10.4137/CMO.S4907Search in Google Scholar PubMed PubMed Central

[22] Scotti L, Ferreira EI, Ms S, Mt S. Chemometric studies on natural products as potential inhibitors of the NADH oxidase from Trypanosoma cruzi using the VolSurf approach. Molecules. 2010;15:7363–77.10.3390/molecules15107363Search in Google Scholar PubMed PubMed Central

[23] Scotti MT, Scotti L. Editorial: chemometrics in drug discovery. Comb Chem High Throughput Screen 2015;18:702–03.10.2174/138620731808150904121214Search in Google Scholar PubMed

[24] Rodrigues T, Reker D, Schneider P, Schneider G. Counting on natural products for drug design. Nat Chem. 2016;8:531–41.10.1038/nchem.2479Search in Google Scholar PubMed

[25] Chen Y, de Bruyn Kops C, Kirchmair J. Data resources for the computer-guided discovery of bioactive natural products. J Chem Inf Model. 2017;57:2099–111.10.1021/acs.jcim.7b00341Search in Google Scholar PubMed

[26] Maier ME. Design and synthesis of analogues of natural products. Org Biomol Chem. 2015;13:5302–43.10.1039/C5OB00169BSearch in Google Scholar PubMed

[27] Wilk W, Zimmermann TJ, Kaiser M, Waldmann H. Principles, implementation, and application of biology-oriented synthesis (BIOS). Biol Chem. 2010;391:491–97.10.1515/bc.2010.013Search in Google Scholar PubMed

[28] Cy-C C. TCM Database@Taiwan: the world’s largest traditional Chinese medicine database for drug screening in silico. PLoS One. 2011;6:e15939.10.1371/journal.pone.0015939Search in Google Scholar PubMed PubMed Central

[29] Tsai T-Y, Chang K-W, Chen CY. iScreen: world’s first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan. J Comput Aided Mol Des. 2011;25:525–31.10.1007/s10822-011-9438-9Search in Google Scholar PubMed

[30] Gu J, Gui Y, Chen L, Yuan G, Lu H-Z XX. Use of natural products as chemical library for drug discovery and network pharmacology. PLoS One. 2013;8:e62839.10.1371/journal.pone.0062839Search in Google Scholar PubMed PubMed Central

[31] Ntie-Kang F, Zofou D, Babiaka SB, Meudom R, Scharfe M, Lifongo LL, et al. AfroDb: a select highly potent and diverse natural product library from African medicinal plants. PLoS One. 2013;8:e78085.10.1371/journal.pone.0078085Search in Google Scholar PubMed PubMed Central

[32] Ntie-Kang F, Onguéné PA, Scharfe M, Owono Owono LC, Megnassan E, Mbaze LM, et al. ConMedNP: a natural product library from Central African medicinal plants for drug discovery. RSC Adv. 2014;4:409–19.10.1039/C3RA43754JSearch in Google Scholar

[33] Valli M, Dos Santos RN, Ld F, Ch N, Castro-Gamboa I, Ad A, et al. Development of a natural products database from the biodiversity of Brazil. J Nat Prod. 2013;76:439–44.10.1021/np3006875Search in Google Scholar PubMed

[34] Pilon AC, Valli M, Dametto AC, Pinto MEF, Freire RT, Castro-Gamboa I, et al. NuBBE DB: an updated database to uncover chemical and biological information from Brazilian biodiversity. Sci Rep. 2017;7:7215.10.1038/s41598-017-07451-xSearch in Google Scholar PubMed PubMed Central

[35] NuBBE - Núcleo de Bioensaios, Biossíntese e Ecofisiologia de Produtos Naturais (Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products Database). http://nubbe.iq.unesp.br/portal/nubbedb.html. Accessed 30 Sep 2018.Search in Google Scholar

[36] Naveja JJ, Oviedo-Osornio CI, Trujillo-Minero NN, Medina-Franco JL. Chemoinformatics: a perspective from an academic setting in Latin America. Mol Divers. 2018;22:247–58.10.1007/s11030-017-9802-3Search in Google Scholar PubMed

[37] Medina-Franco JL. Chemoinformatic Characterization of the Chemical Space and Molecular Diversity of Compound Libraries. In: Trabocchi A, editor. Diversity-Oriented Synthesis. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013:325–52.10.1002/9781118618110.ch10Search in Google Scholar

[38] Gaspar HA, Sidorov P, Horvath D, Marcou G. Generative topographic mapping approach to chemical space analysis. ACS Symp Ser. 2016. https://elibrary.ru/item.asp?id=27576908.10.1021/bk-2016-1222.ch011Search in Google Scholar

[39] Tino P, Nabney I. Hierarchical GTM: constructing localized nonlinear projection manifolds in a principled way. IEEE Trans Pattern Anal Mach Intell. 2002;24:639–56.10.1109/34.1000238Search in Google Scholar

[40] Naveja JJ, Medina-Franco JL. ChemMaps: towards an approach for visualizing the chemical space based on adaptive satellite compounds. F1000Res. 2017;6:1134.10.12688/f1000research.12095.1Search in Google Scholar

[41] Feher M, Schmidt JM. Property distributions: differences between drugs, natural products, and molecules from combinatorial chemistry. J Chem Inf Comput Sci. 2003;43:218–27.10.1021/ci0200467Search in Google Scholar PubMed

[42] Shelat AA, Guy RK. The interdependence between screening methods and screening libraries. Curr Opin Chem Biol. 2007;11:244–51.10.1016/j.cbpa.2007.05.003Search in Google Scholar PubMed

[43] Singh SB, Chris Culberson J. Chapter 2: chemical space and the difference between natural products and synthetics. In: Antony D Buss, Mark S Butler (editors). Natural product chemistry for drug discovery, Cambridge, UK: Royal Society of Chemistry. 2009:28–43.10.1039/9781847559890-00028Search in Google Scholar

[44] Chen H, Engkvist O, Blomberg N, Li J. A comparative analysis of the molecular topologies for drugs, clinical candidates, natural products, human metabolites and general bioactive compounds. Med Chem Commun. 2012;3:312–21.10.1039/C2MD00238HSearch in Google Scholar

[45] Ertl P, Schuffenhauer A. Cheminformatics analysis of natural products: lessons from nature inspiring the design of new drugs. Prog Drug Res. 2008;66:217, 219–35.10.1007/978-3-7643-8595-8_4Search in Google Scholar PubMed

[46] Pascolutti M, Campitelli M, Nguyen B, Pham N, Gorse A-D, Quinn RJ. Capturing nature’s diversity. PLoS One. 2015;10:e0120942.10.1371/journal.pone.0120942Search in Google Scholar PubMed PubMed Central

[47] González-Medina M, Prieto-Martínez FD, Naveja JJ, Méndez-Lucio O, El-Elimat T, Pearce CJ, et al. Chemoinformatic expedition of the chemical space of fungal products. Future Med Chem. 2016;8:1399–412.10.4155/fmc-2016-0079Search in Google Scholar PubMed PubMed Central

[48] Chen Y, Garcia de Lomana M, N-O F, Kirchmair J. Characterization of the chemical space of known and readily obtainable natural products. J Chem Inf Model. 2018;58:1518–32.10.1021/acs.jcim.8b00302Search in Google Scholar PubMed

[49] Shang J, Hu B, Wang J, Zhu F, Kang Y, Li D, et al. Cheminformatic Insight into the differences between terrestrial and marine originated natural products. J Chem Inf Model. 2018;58:1182–93.10.1021/acs.jcim.8b00125Search in Google Scholar PubMed

[50] Ertl P, Schuffenhauer A. Cheminformatics analysis of natural products: lessons from nature inspiring the design of new drugs. Prog Drug Res. 2008;66:217, 219–35.10.1007/978-3-7643-8595-8_4Search in Google Scholar PubMed

[51] Muigg P, Rosén J, Bohlin L, Backlund A. In silico comparison of marine, terrestrial and synthetic compounds using ChemGPS-NP for navigating chemical space. Phytochem Rev. 2013;12:449–57.10.1007/s11101-012-9256-2Search in Google Scholar

[52] Saldívar-González FI, Valli M, Da Silva Bolzani V, Medina-Franco JL. Chemical diversity of NuBBE database: A chemoinformatic characterization 2018.10.1021/acs.jcim.8b00619Search in Google Scholar PubMed

[53] Larsson J, Gottfries J, Muresan S, Backlund A. ChemGPS-NP: tuned for navigation in biologically relevant chemical space. J Nat Prod. 2007;70:789–94.10.1021/np070002ySearch in Google Scholar PubMed

[54] Rosén J, Rickardson L, Backlund A, Gullbo J, Bohlin L, Larsson R, et al. ChemGPS-NP mapping of chemical compounds for prediction of anticancer mode of action. QSAR Comb Sci. 2009;28:436–46.10.1002/qsar.200810162Search in Google Scholar

[55] Korinek M, Tsai Y-H, El-Shazly M, Lai K-H, Backlund A, Wu S-F, et al. Anti-allergic Hydroxy Fatty Acids from Typhonium blumei Explored through ChemGPS-NP. Front Pharmacol. 2017;8:356.10.3389/fphar.2017.00356Search in Google Scholar PubMed PubMed Central

[56] Rosén J, Lövgren A, Kogej T, Muresan S, Gottfries J, Backlund A. ChemGPS-NP(Web): chemical space navigation online. J Comput Aided Mol Des. 2009;23:253–9.10.1007/s10822-008-9255-ySearch in Google Scholar PubMed

[57] Frédérick R, Bruyère C, Vancraeynest C, Reniers J, Meinguet C, Pochet L, et al. Novel trisubstituted harmine derivatives with original in vitro anticancer activity. J Med Chem. 2012;55:6489–501.10.1021/jm300542eSearch in Google Scholar PubMed

[58] Ertl P, Rohde B. The molecule cloud - compact visualization of large collections of molecules. J Cheminform. 2012;4:12.10.1186/1758-2946-4-12Search in Google Scholar PubMed PubMed Central

[59] Schuffenhauer A, Ertl P, Roggo S, Wetzel S, Koch MA, Waldmann H. The scaffold tree--visualization of the scaffold universe by hierarchical scaffold classification. J Chem Inf Model. 2007;47:47–58.10.1021/ci600338xSearch in Google Scholar PubMed

[60] Medina-Franco JL, Petit J, Maggiora GM. Hierarchical strategy for identifying active chemotype classes in compound databases. Chem Biol Drug Des. 2006;67:395–408.10.1111/j.1747-0285.2006.00397.xSearch in Google Scholar PubMed

[61] Koch MA, Schuffenhauer A, Scheck M, Wetzel S, Casaulta M, Odermatt A, et al. Charting biologically relevant chemical space: A structural classification of natural products (SCONP). Proc Natl Acad Sci USA. 2005;102:17272–77.10.1073/pnas.0503647102Search in Google Scholar PubMed PubMed Central

[62] Schäfer T, Kriege N, Humbeck L, Klein K, Koch O, Mutzel P. Scaffold Hunter: a comprehensive visual analytics framework for drug discovery. J Cheminform. 2017;9:28.10.1186/s13321-017-0213-3Search in Google Scholar PubMed PubMed Central

[63] Tao L, Zhu F, Qin C, Zhang C, Chen S, Zhang P, et al. Clustered distribution of natural product leads of drugs in the chemical space as influenced by the privileged target-sites. Sci Rep. 2015;5:9325.10.1038/srep09325Search in Google Scholar PubMed PubMed Central

[64] Pye CR, Bertin MJ, Lokey RS, Gerwick WH, Linington RG. Retrospective analysis of natural products provides insights for future discovery trends. Proc Natl Acad Sci USA. 2017;114:5601–6.10.1073/pnas.1614680114Search in Google Scholar PubMed PubMed Central

[65] Camp D, Garavelas A, Campitelli M. Analysis of physicochemical properties for drugs of natural origin. J Nat Prod. 2015;78:1370–82.10.1021/acs.jnatprod.5b00255Search in Google Scholar PubMed

[66] Stratton CF, Newman DJ, Tan DS. Cheminformatic comparison of approved drugs from natural product versus synthetic origins. Bioorg Med Chem Lett. 2015;25:4802–7.10.1016/j.bmcl.2015.07.014Search in Google Scholar PubMed PubMed Central

[67] Clemons PA, Bodycombe NE, Carrinski HA, Wilson JA, Shamji AF, Wagner BK, et al. Small molecules of different origins have distinct distributions of structural complexity that correlate with protein-binding profiles. Proc Natl Acad Sci USA. 2010;107:18787–92.10.1073/pnas.1012741107Search in Google Scholar PubMed PubMed Central

[68] Medina-Franco JL, Navarrete-Vázquez G, Méndez-Lucio O. Activity and property landscape modeling is at the interface of chemoinformatics and medicinal chemistry. Future Med Chem. 2015;7:1197–211.10.4155/fmc.15.51Search in Google Scholar PubMed

[69] Reddy AS, Zhang S. Polypharmacology: drug discovery for the future. Expert Rev Clin Pharmacol. 2013;6:41–7.10.1586/ecp.12.74Search in Google Scholar PubMed PubMed Central

[70] Medina-Franco JL, Martinez-Mayorga K, Meurice N. Balancing novelty with confined chemical space in modern drug discovery. Expert Opin Drug Discov. 2014;9:151–65.10.1517/17460441.2014.872624Search in Google Scholar PubMed

[71] van Hattum H, Waldmann H. Biology-oriented synthesis: harnessing the power of evolution. J Am Chem Soc. 2014;136:11853–9.10.1021/ja505861dSearch in Google Scholar PubMed

[72] Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res. 2016;44:D1202–13.10.1093/nar/gkv951Search in Google Scholar PubMed PubMed Central

[73] Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, et al. ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 2012;40:D1100–7.10.1093/nar/gkr777Search in Google Scholar PubMed PubMed Central

[74] Gaulton A, Hersey A, Nowotka M, Bento AP, Chambers J, Mendez D, et al. The ChEMBL database in 2017. Nucleic Acids Res. 2017;45:D945–54.10.1093/nar/gkw1074Search in Google Scholar PubMed PubMed Central

[75] Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2018;46:D1074–82.10.1093/nar/gkx1037Search in Google Scholar PubMed PubMed Central

[76] Boufridi A, Quinn RJ. Harnessing the properties of natural products. Annu Rev Pharmacol Toxicol. 2018;58:451–70.10.1146/annurev-pharmtox-010716-105029Search in Google Scholar PubMed

[77] Rosén J, Gottfries J, Muresan S, Backlund A, Oprea TI. Novel chemical space exploration via natural products. J Med Chem. 2009;52:1953–62.10.1021/jm801514wSearch in Google Scholar PubMed PubMed Central

[78] Martinez-Mayorga K, Medina-Franco JL, editors. Foodinformatics: applications of chemical information to food chemistry, Switzerland: Springer. 2014. https://www.springer.com/gp/book/9783319102252.10.1007/978-3-319-10226-9Search in Google Scholar

[79] Medina-Franco JL, Martínez-Mayorga K, Peppard TL, Del Rio A. Chemoinformatic analysis of GRAS (Generally recognized as safe) flavor chemicals and natural products. PLoS One. 2012;7:e50798.10.1371/journal.pone.0050798Search in Google Scholar PubMed PubMed Central

[80] Medina-Franco JL. Advances in computational approaches for drug discovery based on natural products. Revista Latinoamericana de Química. 2013;41:95–110.Search in Google Scholar

[81] Houghten RA, Pinilla C, Giulianotti MA, Appel JR, Dooley CT, Nefzi A, et al. Strategies for the use of mixture-based synthetic combinatorial libraries: scaffold ranking, direct testing in vivo, and enhanced deconvolution by computational methods. J Comb Chem. 2008;10:3–19.10.1021/cc7001205Search in Google Scholar PubMed

[82] Brown N, Jacoby E. On scaffolds and hopping in medicinal chemistry. Mini Rev Med Chem. 2006;6:1217–29.10.2174/138955706778742768Search in Google Scholar PubMed

[83] Singh N, Guha R, Giulianotti MA, Pinilla C, Houghten RA, Medina-Franco JL. Chemoinformatic analysis of combinatorial libraries, drugs, natural products, and molecular libraries small molecule repository. J Chem Inf Model. 2009;49:1010–24.10.1021/ci800426uSearch in Google Scholar PubMed PubMed Central

[84] Yongye AB, Waddell J, Medina-Franco JL. Molecular scaffold analysis of natural products databases in the public domain. Chem Biol Drug Des. 2012;80:717–24.10.1111/cbdd.12011Search in Google Scholar PubMed

[85] Lipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol. 2004;1:337–41.10.1016/j.ddtec.2004.11.007Search in Google Scholar PubMed

[86] Veber DF, Johnson SR, Cheng H-Y, Smith BR, Ward KW, Kopple KD. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002;45:2615–23.10.1021/jm020017nSearch in Google Scholar PubMed

[87] Maldonado AG, Doucet JP, Petitjean M, Fan B-T. Molecular similarity and diversity in chemoinformatics: from theory to applications. Mol Divers. 2006;10:39–79.10.1007/s11030-006-8697-1Search in Google Scholar PubMed

[88] Schuffenhauer A, Varin T. Rule-based classification of chemical structures by scaffold. Mol Inform. 2011;30:646–64.10.1002/minf.201100078Search in Google Scholar PubMed

[89] Schneider G, Neidhart W, Giller T, Schmid G. “Scaffold-hopping” by topological pharmacophore search: a contribution to virtual screening. Angew Chem Int Ed. 1999;38:2894–96.10.1002/(SICI)1521-3773(19991004)38:19<2894::AID-ANIE2894>3.0.CO;2-FSearch in Google Scholar

[90] Evans BE, Rittle KE, Bock MG, DiPardo RM, Freidinger RM, Whitter WL, et al. Methods for drug discovery: development of potent, selective, orally effective cholecystokinin antagonists. J Med Chem. 1988;31:2235–46.10.1021/jm00120a002Search in Google Scholar PubMed

[91] Medina-Franco JL, Martínez-Mayorga K, Bender A, Scior T. Scaffold diversity analysis of compound data sets using an entropy-based measure. QSAR Comb Sci. 2009;28:1551–60.10.1002/qsar.200960069Search in Google Scholar

[92] González-Medina M, Prieto-Martínez FD, Owen JR, Medina-Franco JL. Consensus diversity plots: a global diversity analysis of chemical libraries. J Cheminform. 2016;8:63.10.1186/s13321-016-0176-9Search in Google Scholar PubMed

[93] González-Medina M, Owen JR, El-Elimat T, Pearce CJ, Oberlies NH, Figueroa M, et al. Scaffold diversity of fungal metabolites. Front Pharmacol. 2017;8:180.10.3389/fphar.2017.00180Search in Google Scholar PubMed

[94] Olmedo DA, González-Medina M, Gupta MP, Medina-Franco JL. Cheminformatic characterization of natural products from Panama. Mol Divers. 2017;21:779–89.10.1007/s11030-017-9781-4Search in Google Scholar PubMed