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Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
Abstract
Prediction of small molecule binding modes to macromolecules of known three-dimensional structure is a problem of paramount importance in rational drug design (the "docking" problem). We report the development and validation of the program GOLD (Genetic Optimisation for Ligand Docking). GOLD is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein, and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding. Numerous enhancements and modifications have been applied to the original technique resulting in a substantial increase in the reliability and the applicability of the algorithm. The advanced algorithm has been tested on a dataset of 100 complexes extracted from the Brookhaven Protein DataBank. When used to dock the ligand back into the binding site, GOLD achieved a 71% success rate in identifying the experimental binding mode.
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“GOLD (Jones et al., 1997), Autodock4 (Bianco et al., 2016), CovalentDock (Ouyang et al., 2013), CovDock (Zhu et al., 2014), DOCKovalent (London et al., 2014), and DOCK-TITE (Scholz et al., 2015) are some examples of docking programs that developed specific methodologies to deal with covalent-docking.”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Jones et al., 1997
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Cites
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,178
Adaptation in Natural and Artificial Systems
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,340
Molecular Theory of Gases and Liquids
Hirschfelder, J. O., Curtiss, C. F., & Bird, R. B. (1955) · Physics Today · doi:10.1063/1.3061949 · Cited by 11,445
The protein data bank: A computer-based archival file for macromolecular structures
Bernstein, F. C., Koetzle, T. F., Williams, G. J. B., Meyer, E. F., Brice, M. D., Rodgers, J. R., Kennard, O., Shimanouchi, T., & Tasumi, M. (1977) · Journal of Molecular Biology · doi:10.1016/s0022-2836(77)80200-3 · Cited by 8,574
Molecular theory of gases and liquids
Scott, R. L. (1955) · Journal of Chemical Education · doi:10.1021/ed032p232.2 · Cited by 3,958
Semianalytical treatment of solvation for molecular mechanics and dynamics
Still, W. C., Tempczyk, A., Hawley, R. C., & Hendrickson, T. F. (1990) · Journal of the American Chemical Society · doi:10.1021/ja00172a038 · Cited by 3,653
A Fast Flexible Docking Method using an Incremental Construction Algorithm
Rarey, M., Kramer, B., Lengauer, T., & Klebe, G. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0477 · Cited by 2,836
Validation of the general purpose tripos 5.2 force field
Clark, M., CRAMER, R. D. I., & Opdenbosch, N. V. (1989) · Journal of Computational Chemistry · doi:10.1002/jcc.540100804 · Cited by 2,803
Analytical molecular surface calculation
Connolly, M. L. (1983) · Journal of Applied Crystallography · doi:10.1107/s0021889883010985 · Cited by 2,521
A geometric approach to macromolecule-ligand interactions
Kuntz, I. D., Blaney, J. M., Oatley, S. J., Langridge, R., & Ferrin, T. E. (1982) · Journal of Molecular Biology · doi:10.1016/0022-2836(82)90153-x · Cited by 2,287
Flagged first, then by citations
Research works printed but not linked: 2
- Dreyer, 1992, Hydroxyethylene isostere inhibitors of human immunodeficiency virus-I protease, Biochemistry, 31
- Padlan, 1985, On the specificity of antibody 3-antigen interactions, Ann. Immunol. (Paris), C136, 271
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Items 301–400 of 1,019
Neugebauer, R. C., Uciechowska, U., Meier, R., Hruby, H., Valkov, V., Verdin, E. M., Sippl, W., & Jung, M. (2008) · Journal of Medicinal Chemistry · doi:10.1021/jm700972e · Cited by 166
Antes, I. (2009) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22629 · Cited by 166
Docking-based inverse virtual screening: methods, applications, and challenges
Xu, X., Huang, M., & Zou, X. (2018) · Biophysics Reports · doi:10.1007/s41048-017-0045-8 · Cited by 165
Development and Benchmarking of Open Force Field v1.0.0—the Parsley Small-Molecule Force Field
Qiu, Y., Smith, D. G. A., Boothroyd, S., Jang, H., Hahn, D. F., Wagner, J., Bannan, C. C., Gokey, T., Lim, V. T., Stern, C., et al. (2021) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c00571 · Cited by 165
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Hawkins, P. C. D., Warren, G. L., Skillman, A. G., & Nicholls, A. O. (2008) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-007-9166-3 · Cited by 170
Fragment-based screening using X-ray crystallography and NMR spectroscopy
Jhoti, H., Cleasby, A., Verdonk, M. L., & Williams, G. (2007) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2007.07.010 · Cited by 166
Virtual screening with solvation and ligand-induced complementarity
Schnecke, V., & Kuhn, L. A. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008737207775 · Cited by 166
The FHA and BRCT domains recognize ADP-ribosylation during DNA damage responsePreprint
Mo, L., Lu, L., Yang, C., Wang, S., & Yu, X. (2013) · Genes & Development · doi:10.1101/gad.226357.113 · Cited by 178
Zhou, Z., Felts, A. K., Friesner, R. A., & Levy, R. M. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci7000346 · Cited by 168
Nguyen, D. D., Cang, Z., Wu, K., Wang, M., Cao, Y., & Wei, G.-W. (2019) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-018-0146-6 · Cited by 155
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Madani, N., Schön, A., Princiotto, A. M., LaLonde, J. M., Courter, J. R., Soeta, T., Ng, D., Wang, L., Brower, E. T., Xiang, S.-H., et al. (2008) · Structure · doi:10.1016/j.str.2008.09.005 · Cited by 166
Huang, S., & Zou, X. (2006) · Journal of Computational Chemistry · doi:10.1002/jcc.20505 · Cited by 162
Limitations and lessons in the use of X-ray structural information in drug design
Davis, A. M., St-Gallay, S. A., & Kleywegt, G. J. (2008) · Drug Discovery Today · doi:10.1016/j.drudis.2008.06.006 · Cited by 168
Nitsche, C., Schreier, V. N., Behnam, M. A. M., Kumar, A., Bartenschlager, R. F. W., & Klein, C. D. P. (2013) · Journal of Medicinal Chemistry · doi:10.1021/jm400828u · Cited by 163
Structure-Based Drug Design Strategies in Medicinal Chemistry
Andricopulo, A. D., Salum, L. B., & Abraham, D. J. (2009) · Current Topics in Medicinal Chemistry · doi:10.2174/156802609789207127 · Cited by 162
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Warren, G. L., Do, T. D., Kelley, B. P., Nicholls, A. O., & Warren, S. D. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.06.011 · Cited by 161
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Wilson, G. L., & Lill, M. A. (2011) · Future Medicinal Chemistry · doi:10.4155/fmc.11.18 · Cited by 167
Ballante, F., Kooistra, A. J., Kampen, S., de Graaf, C., & Carlsson, J. (2021) · Pharmacological Reviews · doi:10.1124/pharmrev.120.000246 · Cited by 169
Murray, C. W., Baxter, C. A., & Frenkel, A. D. (1999) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1008015827877 · Cited by 161
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Kelley, B. P., Brown, S. P., Warren, G. L., & Muchmore, S. W. (2015) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5b00142 · Cited by 163
Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)
Martin, Y. C., Abagyan, R. A., Ferenczy, G. G., Gillet, V. J., Oprea, T. I., Ulander, J., Winkler, D. A., & Zefirov, N. S. (2016) · Pure and Applied Chemistry · doi:10.1515/pac-2012-1204 · Cited by 161
Proença, C., Freitas, M., Ribeiro, D., Tomé, S. M., Oliveira, E. F., Viegas, M. F., Araújo, A. N., Ramos, M. J., Silva, A. M. S., Fernandes, P. A., et al. (2019) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.1080/14756366.2018.1558221 · Cited by 169
Bias, reporting, and sharing: computational evaluations of docking methods
Jain, A. N. (2007) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-007-9151-x · Cited by 165
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Brameyer, S., Kresovic, D., Bode, H. B., & Heermann, R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1417685112 · Cited by 158
Meli, R., Morris, G. M., & Biggin, P. C. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2022.885983 · Cited by 176
Kolossv�ry, I., & Guida, W. C. (1999) · Journal of Computational Chemistry · doi:10.1002/(sici)1096-987x(19991130)20:15 · Cited by 158
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Steinbrecher, T. B., & Labahn, A. (2010) · Current Medicinal Chemistry · doi:10.2174/092986710790514453 · Cited by 159
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Lolli, G., Cozza, G., Mazzorana, M., Tibaldi, E. V., Cesaro, L., Donella‐Deana, A., Meggio, F., Venerando, A., Franchin, C., Sarno, S., et al. (2012) · Biochemistry · doi:10.1021/bi300531c · Cited by 155
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Scarpino, A., Ferenczy, G. G., & Keserű, G. M. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00228 · Cited by 155
Khandelwal, A., Lukáčová, V., Çömez, D., Kroll, D. M., Raha, S., & Baláž, Š. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm049050v · Cited by 153
Trapp, J., Jochum, A., Meier, R., Saunders, L. R., Marshall, B. L., Kunick, C., Verdin, E. M., Goekjian, P. G., Sippl, W., & Jung, M. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm060118b · Cited by 153
Cozza, G., Bonvini, P., Zorzi, E., Poletto, G., Pagano, M. A., Sarno, S., Donella‐Deana, A., Zagotto, G., Rosolen, A., Pinna, L. A., et al. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm060112m · Cited by 153
Stankovic‐Valentin, N., Deltour, S., Seeler, J.-S., Pinte, S., Vergoten, G., Guérardel, C., Dejean, A., & Leprince, D. (2007) · Molecular and Cellular Biology · doi:10.1128/mcb.01098-06 · Cited by 153
Arikawa, Y., Nishida, H., Kurasawa, O., Hasuoka, A., Hirase, K., Inatomi, N., Hori, Y., Matsukawa, J., Imanishi, A., Kondo, M., et al. (2012) · Journal of Medicinal Chemistry · doi:10.1021/jm300318t · Cited by 153
Wang, J., Cieplak, P., Li, J., Hou, T., Luo, R., & Duan, Y. (2011) · The Journal of Physical Chemistry B · doi:10.1021/jp112133g · Cited by 153
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Dong, G., Sheng, C., Wang, S., Miao, Z., Yao, J., & Zhang, W. (2010) · Journal of Medicinal Chemistry · doi:10.1021/jm100387d · Cited by 151
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Sudhamalla, B., Gokara, M., Ahalawat, N., Damu, A. G., & Subramanyam, R. (2010) · The Journal of Physical Chemistry B · doi:10.1021/jp102730p · Cited by 150
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Kumar, S., Jaller, D., Patel, B., LaLonde, J. M., DuHadaway, J. B., Malachowski, W. P., Prendergast, G. C., & Muller, A. J. (2008) · Journal of Medicinal Chemistry · doi:10.1021/jm800512z · Cited by 150
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Ekins, S., Chang, C., Mani, S., Krasowski, M. D., Reschly, E. J., Iyer, M., Kholodovych, V. V., Ai, N., Welsh, W. J., Sinz, M., et al. (2007) · Molecular Pharmacology · doi:10.1124/mol.107.038398 · Cited by 151
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Jaramillo-Botero, A., Naserifar, S., & Goddard, W. A. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct5001044 · Cited by 147
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Amari, S., Aizawa, M., Zhang, J., Fukuzawa, K., Mochizuki, Y., Iwasawa, Y., Nakata, K., Chuman, H., & Nakano, T. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci050262q · Cited by 144
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Basith, S., Cui, M., Macalino, S. J. Y., Park, J., Clavio, N. A. B., Kang, S., & Choi, S. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.00128 · Cited by 149
Jiang, Y., Andrews, S. W., Condroski, K. R., Buckman, B. O., Serebryany, V., Wenglowsky, S., Kennedy, A. L., Madduru, M. R., Wang, B., Lyon, M. A., et al. (2013) · Journal of Medicinal Chemistry · doi:10.1021/jm400164c · Cited by 141
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Parks, C. D., Gaieb, Z., Chiu, M. W., Yang, H., Shao, C., Walters, W. P., Jansen, J. M., McGaughey, G. B., Lewis, R. A., Bembenek, S. D., et al. (2020) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-020-00289-y · Cited by 140
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Chougala, B. M., Samundeeswari, S., Holiyachi, M., Shastri, L. A., Dodamani, S., Jalalpure, S. S., Dixit, S. R., Joshi, S. D., & Sunagar, V. A. (2016) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2016.09.021 · Cited by 140
Functional aspects of the heme bound hemophore HasA by structural analysis of various crystal forms
Arnoux, P., Haser, R., Izadi‐Pruneyre, N., Lecroisey, A., & Czjzek, M. (2000) · Proteins Structure Function and Bioinformatics · doi:10.1002/1097-0134(20001101)41:2 · Cited by 43
Synthesis and Target Identification of Hymenialdisine Analogs
Wan, Y., Hur, W., Cho, C. Y., Liu, Y., Adrian, F. J., Lozach, O., Bach, S., Mayer, T., Fabbro, D., Meijer, L., et al. (2004) · Chemistry & Biology · doi:10.1016/j.chembiol.2004.01.015 · Cited by 140
Interaction of Virstatin with Human Serum Albumin: Spectroscopic Analysis and Molecular Modeling
Chatterjee, T., Pal, A., Dey, S., Chatterjee, B. K., & Chakrabarti, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037468 · Cited by 139
Hou, X., Du, J., Zhang, J., Du, L., Fang, H., & Li, M. (2012) · Journal of Chemical Information and Modeling · doi:10.1021/ci300417y · Cited by 139
de Oliveira, T. A., da Silva, M. P., Maia, E. H. B., da Silva, A. M., & Taranto, A. G. (2023) · Drugs and Drug Candidates · doi:10.3390/ddc2020017 · Cited by 159
“The CSA performance is described in Shin [138], which evaluates two existing docking programs, GOLD [139] and AutoDock [140], on the Astex diverse set.”
MethodSteuer, C., Gege, C., Fischl, W., Heinonen, K., Bartenschlager, R. F. W., & Klein, C. D. P. (2011) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2011.05.015 · Cited by 138
Galal, S. A., Khairat, S. H. M., Ragab, F. A. F., Abdelsamie, A. S., Ali, M. M., Soliman, S. M., Mortier, J., Wolber, G., & Diwani, H. I. E. (2014) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2014.08.048 · Cited by 137
Predicting Drug Metabolism: A Site of Metabolism Prediction Tool Applied to the Cytochrome P450 2C9
Zamora, I., Afzelius, L., & Cruciani, G. (2003) · Journal of Medicinal Chemistry · doi:10.1021/jm021104i · Cited by 138
Schneider, T. R. (2002) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444901019291 · Cited by 137
Molecular Docking Screens Using Comparative Models of Proteins
Fan, H., Irwin, J. J., Webb, B. M., Klebe, G., Shoichet, B. K., & Sali, A. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci9003706 · Cited by 135
Huang, S., & Zou, X. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci9002987 · Cited by 143
Tsai, T.-Y., Chang, K.-W., & Chen, C. Y. (2011) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-011-9438-9 · Cited by 135
Ouyang, X., Zhou, S., Su, C. T. T., Ge, Z., Li, R., & Kwoh, C. K. (2013) · Journal of Computational Chemistry · doi:10.1002/jcc.23136 · Cited by 134
Ghosh, A. K., Takayama, J., Aubin, Y., Ratia, K. M., Chaudhuri, R., Báez-Santos, Y. M., Sleeman, K., Coughlin, M. M., Nichols, D. B., Mulhearn, D. C., et al. (2009) · Journal of Medicinal Chemistry · doi:10.1021/jm900611t · Cited by 134
Metadata
- Authors
- Jones, G., Willett, P., Glen, R. C., Leach, A. R., & Taylor, R.
- Affiliations
- University of Sheffield (GB)
- Wellcome Trust (GB)
- Cambridge Crystallographic Data Centre (GB)
- Corresponding author
- Jones, Gareth
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 1997-04
- Volume
- 267
- Issue
- 3
- Pages
- 727-748
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W2050456292
- Cited by
- 6,763
- References
- 87
- Citations by year
- 2026: 244 · 2025: 332 · 2024: 356 · 2023: 361 · 2022: 383 · 2021: 414 · 2020: 394 · 2019: 351 · 2018: 327 · 2017: 270 · 2016: 248 · 2015: 234 · 2014: 237 · 2013: 248 · 2012: 274
- Type
- book review
- Language
- en
- Open access
- closed
- Locations
- Journal of Molecular Biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- protein-ligand docking, genetic algorithm, flexible docking, protein-ligand complex, ligand conformational flexibility, rational drug design, binding mode prediction
- MeSH terms
- Algorithms, Binding Sites, Computer Simulation, Humans, Ligands, Models, Genetic, Models, Molecular, NADP, Protein Binding, Protein Conformation, Proteins, Tetrahydrofolate Dehydrogenase, Crystallography, X-Ray
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