Online EB edition > 2013 Volume 9 > Article
Review
Abstract Over the last few decades significant increase in computational methods (in silico) was annotated. Novel methods have been developed and applied for hypothesis improvement and testing in regions of industrial, pharmaceutical and environmental research. The term in silico methods include variety of approaches. Considerable attention has been attracted to databases, data analysis tools, quantitative structure-activity relationships (QSAR), pharmacophore models, molecular docking and dynamics, pharmacokinetics and other molecular modelling techniques. In silico methods are often accompanied by experimental data, both to create the model and to test it. Such models are frequently used in the discovery and optimization of novel molecules with expected affinity to a target, the estimation of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The review summarizes briefly the applications of most common molecular modelling techniques and evaluates their application in environmental research. Additionally, this study considers computer aided methods as potential and complex tools that may serve as valuable partnership with wet-lab experiments and may provide a rational aid to minimize the cost and time of research.
References
Review
Molecular modelling techniques in environmental research
Rafał D. Urniaż, Ewelina Rutkowska, Jan P. Jastrzębski, Paweł Książek, Katarzyna Rudnicka
Abstract Over the last few decades significant increase in computational methods (in silico) was annotated. Novel methods have been developed and applied for hypothesis improvement and testing in regions of industrial, pharmaceutical and environmental research. The term in silico methods include variety of approaches. Considerable attention has been attracted to databases, data analysis tools, quantitative structure-activity relationships (QSAR), pharmacophore models, molecular docking and dynamics, pharmacokinetics and other molecular modelling techniques. In silico methods are often accompanied by experimental data, both to create the model and to test it. Such models are frequently used in the discovery and optimization of novel molecules with expected affinity to a target, the estimation of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The review summarizes briefly the applications of most common molecular modelling techniques and evaluates their application in environmental research. Additionally, this study considers computer aided methods as potential and complex tools that may serve as valuable partnership with wet-lab experiments and may provide a rational aid to minimize the cost and time of research.
References
| Barron, M., G. Stehly, W. Hayton. 1990. Pharmacokinetic modelling in aquatic animals. 1. Models and concepts. Aquatic Toxicology 18: 61-86. http://dx.doi.org/10.1016/0166-445X(90)90019-L |
|
| Berman, H.M., J. Westbrook, Z. Feng, G. Gilliland, T.N. Bhat, H. Weissig, I.N. Shindyalov, P.E. Bourne. 2000. The Protein Data Bank. Nucleic Acids Research 28: 235-242. http://dx.doi.org/10.1093/nar/28.1.235 |
|
| Birnbaum, L.S., D.F. Staskal. 2004. Brominated flame retardants: Cause for concern? Environmental Health Perspectives 112: 9–17. http://dx.doi.org/10.1289/ehp.6559 |
|
| Chang, A., M. Scheer, A. Grote, I. Schomburg, D. Schomburg. 2009. BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Research 37: D588-D592. http://dx.doi.org/10.1093/nar/gkn820 |
|
| Clark, B., D. Smith. 1984. Pharmacokinetics and toxicity testing. CRC Critical Reviews in Toxicology 12: 343-385. http://dx.doi.org/10.3109/10408448409044214 |
|
| Clark, R.D., E. Abrahamian. 2009. Using a staged multi-objective optimization approach to find selective pharmacophore models. Journal of Computer-Aided Molecular Design 23: 765–771. http://dx.doi.org/10.1007/s10822-008-9227-2 |
|
| Clark, R.D., U. Norinder. 2012. Two personal perspectives on a key issue in contemporary 3D QSAR. WIREs Computational Molecular Science 2: 108–113. http://dx.doi.org/10.1002/wcms.69 |
|
| Cochrane, G., I. Karsch-Mizrachi, Y. Nakamura. 2011. The international nucleotide sequence database collaboration. Nucleic Acids Research 39: D15–D18. http://dx.doi.org/10.1093/nar/gkq1150 |
|
| Cramer, R.D., D.E. Patterson, J.D. Bunce. 1988. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. Journal of the American Chemical Society 110: 5959-5967. http://dx.doi.org/10.1021/ja00226a005 |
|
| Cross, J.B., D.C. Thompson, B.K. Rai, J.C. Baber, K.Y. Fan, Y.B. Hu, C. Humblet. 2009. Comparison of several molecular docking programs: Pose prediction and virtual screening accuracy. Journal of Chemical Information and Modeling 49: 1455–1474. http://dx.doi.org/10.1021/ci900056c |
|
| Cuff, A.L., I. Sillitoe, T. Lewis, A.B. Clegg, R. Rentzsch, N. Furnham, M. Pellegrini-Calace, D. Jones, J. Thornton, C.A. Orengo. 2011. Extending CATH: increasing coverage of the protein structure universe and linking structure with function. Nucleic Acids Research 39: D420-D426. http://dx.doi.org/10.1093/nar/gkq1001 |
|
| Darnerud, P.O., G.S. Eriksen, T. Jóhannesson, P.B. Larsen, M. Viluksela. 2001. Polybrominated diphenyl ethers occurrence, dietary exposure, and toxicology. Environmental Health Perspectives 109: 49–68. | |
| Dirtu, A.C., V.L.B. Jaspers, R. Cernat, H. Neels, A. Covaci. 2010. Distribution of PCBs, their hydroxylated metabolites, and other phenolic contaminants in human serum from two European countries. Environmental Science and Technology 44: 2876-2883. http://dx.doi.org/10.1021/es902149b |
|
| Fernández-Suárez, X.M., M.Y. Galperin. 2013. The 2013 Nucleic Acids Research Database Issue and the online Molecular Biology Database Collection. Nucleic Acids Research 41: 1-7. http://dx.doi.org/10.1093/nar/gks1297 |
|
| Finn, R.D., J. Mistry, J. Tate, P. Coggill, A. Heger, J.E. Pollington, O.L. Gavin, P. Gunesekaran, G. Ceric, K. Forslund, L. Holm, E.L. Sonnhammer, S.R. Eddy, A. Bateman. 2010. The Pfam protein families database. Nucleic Acids Research 38: 211-222. http://dx.doi.org/10.1093/nar/gkp985 |
|
| Hansch, C., T. Fujita. 1964. Rho-Sigma-Pi-Analysis. A method for the correlation of biological activity and chemical structure. Journal of American Chemical Society 86: 1616–1626. http://dx.doi.org/10.1021/ja01062a035 |
|
| Hoopen, P. 2010. ENA as an Information Hub Received 25 October 2010 12:35 UTC; Posted 25 October 2010 (http://precedings.nature.com/documents/5108/version/1) (accessed September 2013). | |
| Hsu, C., M. Bouziane, L. Rattner, L. Yee. 1991. Information resources management in heterogeneous, distributed environments: A metadatabase approach. IEEE Transactions on Software Engineering 6: 604-624. http://dx.doi.org/10.1109/32.87285 |
|
| Irwin, J.J., T. Sterling, M.M. Mysinger, E.S. Bolstad, R.G. Coleman. 2012. ZINC: a free tool to discover chemistry for biology. Journal of Chemical Information and Modeling 52: 1757–1768. http://dx.doi.org/10.1021/ci3001277 |
|
| Jastrzebski, J.P., R. Urniaz. 2011. Compartmental model of the pharmacokinetics of drugs excreted by bile or by non-renal mode. Bio-algorithms and Med.-systems 7: 31-37. | |
| Kanehisa, M., S. Goto, S. Kawashima, Y. Okuno, M. Hattori. 2004. The KEGG resource for deciphering the genome. Nucleic Acids Research 32: 277-280. http://dx.doi.org/10.1093/nar/gkh063 |
|
| Kanz, C., P. Aldebert, N. Althorpe, W. Baker, A. Baldwin, K. Bates, P. Browne, A. van den Broek, M. Castro, G. Cochrane, K. Duggan, R. Eberhardt, N. Faruque, J. Gamble, F. Garcia Diez, N. Harte, T. Kulikova, Q. Lin, V. Lombard, R. Lopez, R. Mancuso, M. McHale, F. Nardone, V. Silventoinen, S. Sobhany, P. Stoehr, M.A. Tuli, K. Tzouvara, R. Vaughan, D. Wu, W. Zhu, R. Apweiler. 2005. The EMBL nucleotide sequence database. Nucleic Acids Research 33: D29-D33. http://dx.doi.org/10.1093/nar/gki098 |
|
| Karara, A., W. Hayton. 1984. Pharmacokinetic model for the uptake and disposition of di-2-etylhexylphtalane in sheepshead minnow Cyprinodon variegatus. Aquatic Toxicology 5: 181-195. http://dx.doi.org/10.1016/0166-445X(84)90019-5 |
|
| Karsch-Mizrachi, I., Y. Nakamura, G. Cochrane. 2011. International nucleotide sequence database collaboration. "The International Nucleotide Sequence Database Collaboration". Nucleic Acids Research 40: D33–D37. http://dx.doi.org/10.1093/nar/gkr1006 |
|
| Kitchen, D.B., H. Decornez, J.R. Furr, J. Bajorath. 2004. Docking and scoring in virtual screening for drug discovery: methods and applications. Nature Reviews Drug Discovery 3: 935-949. http://dx.doi.org/10.1038/nrd1549 |
|
| Koes, D.R., C.J. Camacho. 2012. ZINCPharmer: pharmacophore search of the ZINC database. Nucleic Acids Research 40: W409–W414. http://dx.doi.org/10.1093/nar/gks378 |
|
| Krewski, D., M. Westphal, M. Al-Zoughool, M.C. Croteau, M.E. Andersen. 2011. New directions in toxicity testing. Annual Review of Public Health 32: 161-78. http://dx.doi.org/10.1146/annurev-publhealth-031210-101153 |
|
| Kubinyi, H. 1995. Strategies and recent technologies in drug discovery. Pharmazie 50: 647-662. | |
| Kubinyi, H. 1997a. QSAR and 3D QSAR in drug design. I. Methodology. Drug Discovery Today 2: 457-467. http://dx.doi.org/10.1016/S1359-6446(97)01079-9 |
|
| Kubinyi, H. 1997b. QSAR and 3D QSAR in drug design. II. Applications and problems. Drug Discovery Today 2: 538-546. http://dx.doi.org/10.1016/S1359-6446(97)01084-2 |
|
| Kulikova, T., P. Aldebert, N. Althorpe, W. Baker, K. Bates, P. Browne, A. van den Broek, G. Cochrane, K. Duggan, R. Eberhardt, N. Faruque, M. Garcia-Pastor, N. Harte, C. Kanz, R. Leinonen, Q. Lin, V. Lombard, R. Lopez, R. Mancuso, M. McHale, F. Nardone, V. Silventoinen, P. Stoehr, G. Stoesser, M.A. Tuli, K. Tzouvara, R. Vaughan, D. Wu, W. Zhu, R. Apweiler. 2004. The EMBL nucleotide sequence database. Nucleic Acids Research 32: D27-D30. http://dx.doi.org/10.1093/nar/gkh120 |
|
| Kuntz, I.D., J.M. Blaney, S.J. Oatley, R. Langridge, T.E. Ferrin. 1982. A geometric approach to macromolecule–ligand interaction. Journal of Molecular Biology 162: 269-288. http://dx.doi.org/10.1016/0022-2836(82)90153-X |
|
| Landrum, P., H. Lee, M. Lydy. 1992. Toxicokinetics in aquatic systems - model comparison and use in hazard assessment. Environmental Toxicology and Chemistry 11: 1709-1725. http://dx.doi.org/10.1002/etc.5620111205 |
|
| Laskowski, R.A. 2009. PDBsum new things. Nucleic Acids Research 37: 355-359. http://dx.doi.org/10.1093/nar/gkn860 |
|
| Lee, S.H., D.K. Park, D.B. Kang. 2003. Molecular dynamics simulations for transport coefficients of liquid argon: New approaches. The Bulletin of the Korean Chemical Society 24: 178-182. http://dx.doi.org/10.5012/bkcs.2003.24.2.178 |
|
| Li, X., L. Ye, X. Wang, X. Wang, H. Liu, X. Qian, Y. Zhu, H. Yu. 2012. Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on estrogenic activity of hydroxylated polychlorinated biphenyls. Science of the Total Environment 441: 230–238. http://dx.doi.org/10.1016/j.scitotenv.2012.08.072 |
|
| Lomize, M.A., A.L. Lomize, I.D. Pogozheva, H.I. Mosberg. 2006. OPM: orientations of proteins in membranes database. Bioinformatics 22: 623-625. http://dx.doi.org/10.1093/bioinformatics/btk023 |
|
| Lomize, M.A., I.D. Pogozheva, H. Joo, H.I. Mosberg, A.L. Lomize. 2012. OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Research 40: 370-376. http://dx.doi.org/10.1093/nar/gkr703 |
|
| Lo Piparo, E., A. Worth. 2010. Review of QSAR models and software tools for predicting developmental and reproductive toxicity (http://ihcp.jrc.ec.europa.eu/our_labs/predictive_toxicology/doc/EUR_24522_EN.pdf) (accessed September 2013). | |
| López-Ramos, M., F. Perruccio. 2010. HPPD: Ligand- and target-based virtual screening on a herbicide target. Journal of Chemical Information and Modeling 50: 801–814. http://dx.doi.org/10.1021/ci900498n |
|
| Martin, Y.C., J.L. Kofron, L.M. Traphagen. 2002. Do structurally similar molecules have similar biological activity. Journal of Medicinal Chemistry 45: 4350–4358. http://dx.doi.org/10.1021/jm020155c |
|
| McGregor, M.J. 2007. A pharmacophore map of small molecule protein kinase inhibitors. Journal of Chemical Information and Modeling 47: 2374-2382. http://dx.doi.org/10.1021/ci700244t |
|
| Murzin, A.G., S.E. Brenner, T. Hubbard, C. Chothia. 1995. SCOP: a structural classification of proteins database for the investigation of sequences and structures. Journal of Molecular Biology 247: 536-540. http://dx.doi.org/10.1016/S0022-2836(05)80134-2 |
|
| O'Maille, P.E., M. Bakhtina, M.D. Tsai. 2002. Structure-based combinatorial protein engineering (SCOPE). Journal of Molecular Biology 321: 677–691. http://dx.doi.org/10.1016/S0022-2836(02)00675-7 |
|
| Orengo, C.A., A.D. Michie, S. Jones, D.T. Jones, M.B. Swindells, J.M. Thornton. 1997. CATH – a hierarchic classification of protein domain structures. Structure 5: 1093-1109. http://dx.doi.org/10.1016/S0969-2126(97)00260-8 |
|
| Oreskes, N., K. Shrader-Frechette, K. Belitz. 1994. Verification, validation, and confirmation of numerical models in the Earth sciences. Science 263: 641-646. http://dx.doi.org/10.1126/science.263.5147.641 |
|
| Pearl, F.M.G., N. Martin, J.E. Bray, D.W.A. Buchan, A.P. Harrison, D. Lee, G.A. Reeves, A.J. Shepherd, I. Sillitoe, A.E. Todd, J.M. Thornton, C.A. Orengo. 2001. A rapid classification protocol for the CATH Domain Database to support structural genomics. Nucleic Acids Research 29: 223-227. http://dx.doi.org/10.1093/nar/29.1.223 |
|
| Perola, E., W.P. Walters, P.S. Charifson. 2004. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance. PROTEINS: Structure, Function, and Bioinformatics 56: 235–249. http://dx.doi.org/10.1002/prot.20088 |
|
| Schecter, A., O. Papke, K.C. Tung, J. Joseph, T.R. Harris, J. Dahlgreen. 2005. Polybrominated diphenyl ether flame retardants in the U.S. population: Current levels, temporal trends, and comparison with dioxins, dibenzofurans, and polychlorinated biphenyls. Journal of Occupational and Environmental Medicine 47: 199–211. http://dx.doi.org/10.1097/01.jom.0000158704.27536.d2 |
|
| Schultza, T.W., M.T.D. Croninb, T.I. Netzevab. 2003. The present status of QSAR in toxicology. Journal of Molecular Structure (Theochem) 622: 23–38. http://dx.doi.org/10.1016/S0166-1280(02)00615-2 |
|
| Urniaz, R.D., K. Jozwiak. 2013. X-ray crystallographic structures as a source of ligand alignment in 3D-QSAR. Journal of Chemical Information and Modeling 53: 1406-1414. http://dx.doi.org/10.1021/ci400004e |
|
| Verma, J., V.M. Khedkar, E.C. Coutinho. 2010. 3D-QSAR in drug design - a review. Current Topics in Medicinal Chemistry 10: 95-115. http://dx.doi.org/10.2174/156802610790232260 |
|
| Wen, Y.H., J. Kalff, R.H. Peters. 1999. Pharmacokinetic modeling in toxicology: a critical perspective. Environmental Reviews 7: 1–18. http://dx.doi.org/10.1139/a99-003 |
|
| Wermuth, C.G., C.R. Ganellin, P. Lindberg, L.A. Mitscher. 1998. Glossary of terms used in medicinal chemistry (IUPAC Recommendations 1998). Pure and Applied Chemistry 70: 1129–1143. http://dx.doi.org/10.1351/pac199870051129 |
|
| Wu, C.H., L-S.L. Yeh, H. Huang, L. Arminski, J. Castro-Alvear, Y. Chen, Z. Hu, P. Kourtesis, R.S. Ledley, B.E. Suzek, C.R. Vinayaka, J. Zhang, W.C. Barker. 2003. The protein information resource. Nucleic Acids Research 31: 345-347. http://dx.doi.org/10.1093/nar/gkg040 |
|
| Yang, W.H., Z.Y. Wang, H.L. Liu, H.X. Yu. 2010. Exploring the binding features of polybrominated diphenyl ethers as estrogen receptor antagonists: docking studies. SAR and QSAR in Environmental Research 21: 351–367. http://dx.doi.org/10.1080/10629361003773971 |
|
| Young, J., J. Holson. 1978. Utility of pharmacokinetics in designing toxicological protocols and improving interspecies explorations. Journal of Environmental Pathology and Toxicology 2: 169-186. |