Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-28T05:54:54.452Z Has data issue: false hasContentIssue false

Protein flexibility in docking and surface mapping

Published online by Cambridge University Press:  09 May 2012

Katrina W. Lexa
Affiliation:
Department of Medicinal Chemistry, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USA
Heather A. Carlson*
Affiliation:
Department of Medicinal Chemistry, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USA
*
*Author for correspondence: Heather A. Carlson. Email: carlsonh@umich.edu

Abstract

Structure-based drug design has become an essential tool for rapid lead discovery and optimization. As available structural information has increased, researchers have become increasingly aware of the importance of protein flexibility for accurate description of the native state. Typical protein–ligand docking efforts still rely on a single rigid receptor, which is an incomplete representation of potential binding conformations of the protein. These rigid docking efforts typically show the best performance rates between 50 and 75%, while fully flexible docking methods can enhance pose prediction up to 80–95%. This review examines the current toolbox for flexible protein–ligand docking and receptor surface mapping. Present limitations and possibilities for future development are discussed.

Type
Review Article
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abagyan, R., Totrov, M. & Kuznetsov, D. A. (1994). ICM – a new method for protein modeling and design: applications to docking and structure prediction from the distorted native conformation. Journal of Computational Chemistry 15, 488506.CrossRefGoogle Scholar
Alberts, I. L., Todorov, N. P. & Dean, P. M. (2005a). Receptor flexibility in de novo ligand design and docking. Journal of Medicinal Chemistry 48, 65856596.CrossRefGoogle ScholarPubMed
Alberts, I. L., Todorov, N. P., Kallblad, P. & Dean, P. M. (2005b). Ligand docking and design in a flexible receptor site. QSAR and Combinatorial Science 24, 503507.CrossRefGoogle Scholar
Alonso, H., Bliznyuk, A. A. & Gready, J. E. (2006). Combining docking and molecular dynamic simulations in drug design. Medicinal Research Reviews 26, 531568.CrossRefGoogle ScholarPubMed
Amaro, R. E., Baron, R. & McCammon, J. A. (2008). An improved relaxed complex scheme for receptor flexibility in computer-aided drug design. Journal of Computer-Aided Molecular Design 22, 693705.CrossRefGoogle ScholarPubMed
Anderson, A. C., O'Neil, R. H., Surti, T. S. & Stroud, R. M. (2001). Approaches to solving the rigid receptor problem by identifying a minimal set of flexible residues during ligand docking. Chemistry and Biology 8, 445457.CrossRefGoogle ScholarPubMed
Babakhani, A., Talley, T. T., Taylor, P. & McCammon, J. A. (2009). A virtual screening study of the acetylcholine binding protein using a relaxed-complex approach. Computational Biology and Chemistry 33, 160170.CrossRefGoogle ScholarPubMed
Barakat, K., Mane, J., Friesen, D. & Tuszynski, J. (2010). Ensemble-based virtual screening reveals dual-inhibitors for the p53-MDM2/MDMX interactions. Journal of Molecular Graphics and Modelling 28, 555568.CrossRefGoogle ScholarPubMed
Barakat, K. & Tuszynski, J. (2010). Relaxed complex scheme suggests novel inhibitors for the lyase activity of DNA polymerase beta. Journal of Molecular Graphics and Modelling 29, 702716.CrossRefGoogle ScholarPubMed
Barril, X. & Morley, S. D. (2005). Unveiling the full potential of flexible receptor docking using multiple crystallographic structures. Journal of Medicinal Chemistry 48, 44324443.CrossRefGoogle ScholarPubMed
Berger, C., Weber-Bornhauser, S., Eggenberger, J., Hanes, J., Pluckthun, A. & Bosshard, H. R. (1999). Antigen recognition by conformational selection. FEBS Letters 450, 149153.CrossRefGoogle ScholarPubMed
Berman, H. M., Bhat, T. N., Bourne, P. E., Feng, Z., Gilliland, G., Weissig, H. & Westbrook, J. (2000). The Protein Data Bank and the challenge of structural genomics. Nature Structural Biology 7 (Suppl), 957959.CrossRefGoogle ScholarPubMed
Bisson, W. H., Cheltsov, A. V., Bruey-Sedano, N., Lin, B., Chen, J., Goldberger, N., May, L. T., Christopoulos, A., Dalton, J. T., Sexton, P. M., Zhang, X. K. & Abagyan, R. (2007). Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs. Proceedings of the National Academy of Sciences of the United States of America 104, 1192711932.CrossRefGoogle ScholarPubMed
Bolstad, E. S. & Anderson, A. C. (2008). In pursuit of virtual lead optimization: the role of the receptor structure and ensembles in accurate docking. Proteins 73, 566580.CrossRefGoogle ScholarPubMed
Bolstad, E. S. & Anderson, A. C. (2009). In pursuit of virtual lead optimization: pruning ensembles of receptor structures for increased efficiency and accuracy during docking. Proteins 75, 6274.CrossRefGoogle ScholarPubMed
Bottegoni, G. (2011). Protein–ligand docking. Frontiers in Bioscience 16, 22892306.CrossRefGoogle ScholarPubMed
Bottegoni, G., Kufareva, I., Totrov, M. & Abagyan, R. (2008). A new method for ligand docking to flexible receptors by dual alanine scanning and refinement (SCARE). Journal of Computer-Aided Molecular Design 22, 311325.CrossRefGoogle ScholarPubMed
Bottegoni, G., Kufareva, I., Totrov, M. & Abagyan, R. (2009). Four-dimensional docking: a fast and accurate account of discrete receptor flexibility in ligand docking. Journal of Medicinal Chemistry 52, 397406.CrossRefGoogle Scholar
Bowman, A. L., Nikolovska-Coleska, Z., Zhong, H., Wang, S. & Carlson, H. A. (2007). Small molecule inhibitors of the MDM2-p53 interaction discovered by ensemble-based receptor models. Journal of the American Chemical Society 129, 1280912814.CrossRefGoogle ScholarPubMed
Brenke, R., Kozakov, D., Chuang, G. Y., Beglov, D., Hall, D., Landon, M. R., Mattos, C. & Vajda, S. (2009). Fragment-based identification of druggable ‘hot spots’ of proteins using Fourier domain correlation techniques. Bioinformatics 25, 621627.CrossRefGoogle ScholarPubMed
Broughton, H. B. (2000). A method for including protein flexibility in protein–ligand docking: improving tools for database mining and virtual screening. Journal of Molecular Graphics and Modelling 18, 247–257, 302–244.CrossRefGoogle ScholarPubMed
Buhrman, G., de Serrano, V. & Mattos, C. (2003). Organic solvents order the dynamic switch II in Ras crystals. Structure 11, 747751.CrossRefGoogle Scholar
Carlson, H. A., Masukawa, K. M. & McCammon, J. A. (1999). Method for including the dynamic fluctuations of a protein in computer-aided drug design. Journal of Physical Chemistry A 103, 1021310219.CrossRefGoogle Scholar
Carlson, H. A., Masukawa, K. M., Rubins, K., Bushman, F. D., Jorgensen, W. L., Lins, R. D., Briggs, J. M. & McCammon, J. A. (2000). Developing a dynamic pharmacophore model for HIV-1 integrase. Journal of Medicinal Chemistry 43, 21002114.CrossRefGoogle ScholarPubMed
Cavasotto, C. N. & Abagyan, R. A. (2004). Protein flexibility in ligand docking and virtual screening to protein kinases. Journal of Molecular Biology 337, 209225.CrossRefGoogle ScholarPubMed
Cavasotto, C. N., Kovacs, J. A. & Abagyan, R. A. (2005). Representing receptor flexibility in ligand docking through relevant normal modes. Journal of the American Chemical Society 127, 96329640.CrossRefGoogle ScholarPubMed
Cheng, L. S., Amaro, R. E., Xu, D., Li, W. W., Arzberger, P. W. & McCammon, J. A. (2008). Ensemble-based virtual screening reveals potential novel antiviral compounds for avian influenza neuraminidase. Journal of Medicinal Chemistry 51, 38783894.CrossRefGoogle ScholarPubMed
Chopra, G., Summa, C. M. & Levitt, M. (2008). Solvent dramatically affects protein structure refinement. Proceedings of the National Academy of Sciences USA 105, 2023920244.CrossRefGoogle ScholarPubMed
Clark, M., Guarnieri, F., Shkurko, I. & Wiseman, J. (2006). Grand canonical Monte Carlo simulation of ligand-protein binding. Journal of Chemical Information and Modeling 46, 231242.CrossRefGoogle ScholarPubMed
Clark, M., Meshkat, S. & Wiseman, J. S. (2009). Grand canonical free-energy calculations of protein-ligand binding. Journal of Chemical Information and Modeling 49, 934943.CrossRefGoogle ScholarPubMed
Claussen, H., Buning, C., Rarey, M. & Lengauer, T. (2001). FlexE: efficient molecular docking considering protein structure variations. Journal of Molecular Biology 308, 377395.CrossRefGoogle ScholarPubMed
Corbeil, C. R., Englebienne, P. & Moitessier, N. (2007). Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0. Journal of Chemical Information and Modeling 47, 435449.CrossRefGoogle ScholarPubMed
Corbeil, C. R., Englebienne, P., Yannopoulos, C. G., Chan, L., Das, S. K., Bilimoria, D., L'Heureux, L. & Moitessier, N. (2008). Docking ligands into flexible and solvated macromolecules. 2. Development and application of FITTED 1.5 to the virtual screening of potential HCV polymerase inhibitors. Journal of Chemical Information and Modeling 48, 902909.CrossRefGoogle Scholar
Corbeil, C. R. & Moitessier, N. (2009). Docking ligands into flexible and solvated macromolecules. 3. Impact of input ligand conformation, protein flexibility, and water molecules on the accuracy of docking programs. Journal of Chemical Information and Modeling 49, 9971009.CrossRefGoogle ScholarPubMed
Cozzini, P., Kellogg, G. E., Spyrakis, F., Abraham, D. J., Costantino, G., Emerson, A., Fanelli, F., Gohlke, H., Kuhn, L. A., Morris, G. M., Orozco, M., Pertinhez, T. A., Rizzi, M. & Sotriffer, C. A. (2008). Target flexibility: an emerging consideration in drug discovery and design. Journal of Medicinal Chemistry 51, 62376255.CrossRefGoogle ScholarPubMed
Craig, I. R., Essex, J. W. & Spiegel, K. (2010). Ensemble docking into multiple crystallographically derived protein structures: an evaluation based on the statistical analysis of enrichments. Journal of Chemical Information and Modeling 50, 511524.CrossRefGoogle Scholar
Damm, K. L. & Carlson, H. A. (2007). Exploring experimental sources of multiple protein conformations in structure-based drug design. Journal of the American Chemical Society 129, 82258235.CrossRefGoogle ScholarPubMed
Damm, K. L., Ung, P. M., Quintero, J. J., Gestwicki, J. E. & Carlson, H. A. (2008). A poke in the eye: inhibiting HIV-1 protease through its flap-recognition pocket. Biopolymers 89, 643652.CrossRefGoogle ScholarPubMed
Davis, I. W. & Baker, D. (2009). ROSETTALIGAND docking with full ligand and receptor flexibility. Journal of Molecular Biology 385, 381392.CrossRefGoogle ScholarPubMed
Davis, I. W., Raha, K., Head, M. S. & Baker, D. (2009). Blind docking of pharmaceutically relevant compounds using ROSETTALIGAND. Protein Science 19, 19982002.CrossRefGoogle Scholar
Dechene, M., Wink, G., Smith, M., Swartz, P. & Mattos, C. (2009). Multiple solvent crystal structures of ribonuclease A: an assessment of the method. Proteins 76, 861881.CrossRefGoogle ScholarPubMed
Dunbar, J. B., Smith, R. D., Yang, C.-Y., Ung, P. M. U., Lexa, K. W., Khazanov, N. A., Stuckey, J. A., Wang, S. & Carlson, H. A. (2011). CSAR benchmark exercise of 2010: selection of the protein-ligand complexes. Journal of Chemical Information and Modeling 51, 20362046.CrossRefGoogle ScholarPubMed
Dunbrack, R. L. Jr. & Karplus, M. (1993). Backbone-dependent rotamer library for proteins. Application to side-chain prediction. Journal of Molecular Biology 230, 543574.CrossRefGoogle ScholarPubMed
Durrant, J. D., Keranen, H., Wilson, B. A. & McCammon, J. A. (2010). Computational identification of uncharacterized cruzain binding sites. PLoS Neglected Tropical Diseases 4, e676.CrossRefGoogle ScholarPubMed
Durrant, J. D. & McCammon, J. A. (2010). Computer-aided drug-discovery techniques that account for receptor flexibility. Current Opinion in Pharmacology 10, 770774.CrossRefGoogle ScholarPubMed
Englebienne, P. & Moitessier, N. (2009). Docking ligands into flexible and solvated macromolecules. 4. Are popular scoring functions accurate for this class of proteins? Journal of Chemical Information and Modeling 49, 15681580.CrossRefGoogle ScholarPubMed
English, A. C., Done, S. H., Caves, L. S. D., Groom, C. R. & Hubbard, R. E. (1999). Locating interaction sites on proteins: the crystal structure of thermolysin soaked in 2% to 100% is opropanol. Proteins-Structure Function and Genetics 37, 628640.3.0.CO;2-G>CrossRefGoogle Scholar
English, A. C., Groom, C. R. & Hubbard, R. E. (2001). Experimental and computational mapping of the binding surface of a crystalline protein. Protein Engineering 14, 4759.CrossRefGoogle ScholarPubMed
Erlanson, D. A., McDowell, R. S. & O'Brien, T. (2004). Fragment-based drug discovery. Journal of Medicinal Chemistry 47, 34633482.CrossRefGoogle ScholarPubMed
Eyal, E., Gerzon, S., Potapov, V., Edelman, M. & Sobolev, V. (2005). The limit of accuracy of protein modeling: influence of crystal packing on protein structure. Journal of Molecular Biology 351, 431442.CrossRefGoogle ScholarPubMed
Fedorov, A. A., Joseph-McCarthy, D., Fedorov, E., Sirakova, D., Graf, I. & Almo, S. C. (1996). Ionic interactions in crystalline bovine pancreatic ribonuclease A. Biochemistry 35, 1596215979.CrossRefGoogle ScholarPubMed
Ferrari, A. M., Wei, B. Q., Costantino, L. & Shoichet, B. K. (2004). Soft docking and multiple receptor conformations in virtual screening. Journal of Medicinal Chemistry 47, 50765084.CrossRefGoogle ScholarPubMed
Firth-Clark, S., Willems, H. M., Williams, A. & Harris, W. (2006). Generation and selection of novel estrogen receptor ligands using the de novo structure-based design tool, SkelGen. Journal of Chemical Information and Modeling 46, 642647.CrossRefGoogle Scholar
Fischer, E. (1890). Synthese des traubenzuckers. Berichte der deutschen chemischen Gesellschaft 23, 799805.CrossRefGoogle Scholar
Fitzpatrick, P. A., Steinmetz, A. C., Ringe, D. & Klibanov, A. M. (1993). Enzyme crystal structure in a neat organic solvent. Proceedings of the National Academy of Sciences of the United States of America 90, 86538657.CrossRefGoogle Scholar
Foote, J. & Milstein, C. (1994). Conformational isomerism and the diversity of antibodies. Proceedings of the National Academy of Sciences of the United States of America 91, 1037010374.CrossRefGoogle ScholarPubMed
Frembgen-Kesner, T. & Elcock, A. H. (2006). Computational sampling of a cryptic drug binding site in a protein receptor: explicit solvent molecular dynamics and inhibitor docking to p38 MAP kinase. Journal of Molecular Biology 359, 202214.CrossRefGoogle Scholar
Fuentes, G., Dastidar, S. G., Madhumalar, A. & Verma, C. S. (2011). Role of protein flexibility in the discovery of new drugs. Drug Development Research 72, 2635.CrossRefGoogle Scholar
Gunasekaran, K., Ma, B. & Nussinov, R. (2004). Is allostery an intrinsic property of all dynamic proteins? Proteins 57, 433443.CrossRefGoogle ScholarPubMed
Guvench, O. & MacKerell, A. D. Jr. (2009). Computational fragment-based binding site identification by ligand competitive saturation. PLoS Computational Biology 5, e1000435.CrossRefGoogle ScholarPubMed
Hammes, G. G., Chang, Y. C. & Oas, T. G. (2009). Conformational selection or induced fit: a flux description of reaction mechanism. Proceedings of the National Academy of Sciences of the United States of America 106, 1373713741.CrossRefGoogle ScholarPubMed
Hartshorn, M. J., Verdonk, M. L., Chessari, G., Brewerton, S. C., Mooij, W. T., Mortenson, P. N. & Murray, C. W. (2007). Diverse, high-quality test set for the validation of protein–ligand docking performance. Journal of Medicinal Chemistry 50, 726741.CrossRefGoogle ScholarPubMed
Henzler, A. M. & Rarey, M. (2010). In pursuit of fully flexible protein–ligand docking: modeling the bilateral mechanism of binding. Molecular Informatics 29, 164173.CrossRefGoogle ScholarPubMed
Ho, W. C., Luo, C., Zhao, K. H., Chai, X. M., Fitzgerald, M. X. & Marmorstein, R. (2006). High-resolution structure of the p53 core domain: implications for binding small-molecule stabilizing compounds. Acta Crystallographica Section D Biological Crystallography 62, 14841493.CrossRefGoogle ScholarPubMed
Howard, S., Berdini, V., Boulstridge, J. A., Carr, M. G., Cross, D. M., Curry, J., Devine, L. A., Early, T. R., Fazal, L., Gill, A. L., Heathcote, M., Maman, S., Matthews, J. E., McMenamin, R. L., Navarro, E. F., O'Brien, M. A., O'Reilly, M., Rees, D. C., Reule, M., Tisi, D., Williams, G., Vinkovic, M. & Wyatt, P. G. (2009). Fragment-based discovery of the pyrazol-4-yl urea (AT9283), a multitargeted kinase inhibitor with potent aurora kinase activity. Journal of Medicinal Chemistry 52, 379388.CrossRefGoogle ScholarPubMed
Huang, S. Y., Grinter, S. Z. & Zou, X. (2010). Scoring functions and their evaluation methods for protein–ligand docking: recent advances and future directions. Physical Chemistry Chemical Physics 12, 1289912908.CrossRefGoogle ScholarPubMed
Huang, Z. & Wong, C. F. (2009). Docking flexible peptide to flexible protein by molecular dynamics using two implicit-solvent models: an evaluation in protein kinase and phosphatase systems. Journal of Physical Chemistry B 113, 1434314354.CrossRefGoogle ScholarPubMed
Huang, S. Y. & Zou, X. (2007). Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking. Proteins 66, 399421.CrossRefGoogle ScholarPubMed
Jain, A. N. (2003). Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. Journal of Medicinal Chemistry 46, 499511.CrossRefGoogle ScholarPubMed
Jain, A. N. (2007). Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. Journal of Computer-Aided Molecular Design 21, 281306.CrossRefGoogle ScholarPubMed
Jain, A. N. (2009). Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation. Journal of Computer-Aided Molecular Design 23, 355374.CrossRefGoogle ScholarPubMed
Jiang, F. & Kim, S. H. (1991). “Soft docking”: matching of molecular surface cubes. Journal of Molecular Biology 219, 79102.CrossRefGoogle ScholarPubMed
Jorgensen, W. L. (2004). The many roles of computation in drug discovery. Science 303, 18131818.CrossRefGoogle ScholarPubMed
Joseph-McCarthy, D., Fedorov, A. A. & Almo, S. C. (1996). Comparison of experimental and computational functional group mapping of an RNase A structure: implications for computer-aided drug design. Protein Engineering 9, 773780.CrossRefGoogle ScholarPubMed
Kairys, V. & Gilson, M. K. (2002). Enhanced docking with the mining minima optimizer: acceleration and side-chain flexibility. Journal of Computational Chemistry 23, 16561670.CrossRefGoogle ScholarPubMed
Kallblad, P. & Dean, P. M. (2003). Efficient conformational sampling of local side-chain flexibility. Journal of Molecular Biology 326, 16511665.CrossRefGoogle ScholarPubMed
Kastenholz, M. A., Pastor, M., Cruciani, G., Haaksma, E. E. & Fox, T. (2000). GRID/CPCA: a new computational tool to design selective ligands. Journal of Medicinal Chemistry 43, 30333044.CrossRefGoogle ScholarPubMed
Keseru, G. M. & Kolossvary, I. (2001). Fully flexible low-mode docking: application to induced fit in HIV integrase. Journal of the American Chemical Society 123, 1270812709.CrossRefGoogle ScholarPubMed
Klebe, G. (2006). Virtual ligand screening: strategies, perspectives and limitations. Drug Discovery Today 11, 580594.CrossRefGoogle ScholarPubMed
Knegtel, R. M., Kuntz, I. D. & Oshiro, C. M. (1997). Molecular docking to ensembles of protein structures. Journal of Molecular Biology 266, 424440.CrossRefGoogle ScholarPubMed
Kollman, P. A., Massova, I., Reyes, C., Kuhn, B., Huo, S., Chong, L., Lee, M., Lee, T., Duan, Y., Wang, W., Donini, O., Cieplak, P., Srinivasan, J., Case, D. A. & Cheatham, T. E. (2000). Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Accounts of Chemical Research 33, 889897.CrossRefGoogle ScholarPubMed
Koshland, D. E. (1958). Application of a theory of enzyme specificity to protein synthesis. Proceedings of the National Academy of Sciences of the United States of America 44, 98104.CrossRefGoogle ScholarPubMed
Kranjc, A., Bongarzone, S., Rossetti, G., Biarnes, X., Cavalli, A., Bolognesi, M. L., Roberti, M., Legname, G. & Carloni, P. (2009). Docking ligands on protein surfaces: the case study of prion protein. Journal of Chemical Theory and Computation 5, 25652573.CrossRefGoogle ScholarPubMed
Kumar, S., Ma, B., Tsai, C. J., Sinha, N. & Nussinov, R. (2000). Folding and binding cascades: dynamic landscapes and population shifts. Protein Science 9, 1019.CrossRefGoogle ScholarPubMed
Landon, M. R., Amaro, R. E., Baron, R., Ngan, C. H., Ozonoff, D., McCammon, J. A. & Vajda, S. (2008). Novel druggable hot spots in avian influenza neuraminidase H5N1 revealed by computational solvent mapping of a reduced and representative receptor ensemble. Chemical Biology and Drug Design 71, 106116.CrossRefGoogle ScholarPubMed
Laughton, C. A., Orozco, M. & Vranken, W. (2009). COCO: a simple tool to enrich the representation of conformational variability in NMR structures. Proteins 75, 206216.CrossRefGoogle Scholar
Leach, A. R. (1994). Ligand docking to proteins with discrete side-chain flexibility. Journal of Molecular Biology 235, 345356.CrossRefGoogle ScholarPubMed
Leach, A. R., Shoichet, B. K. & Peishoff, C. E. (2006). Prediction of protein-ligand interactions. Docking and scoring: successes and gaps. Journal of Medicinal Chemistry 49, 58515855.CrossRefGoogle ScholarPubMed
Leong, M. K. (2007). A novel approach using pharmacophore ensemble/support vector machine (phe/svm) for prediction of hERG liability. Chemical Research in Toxicology 20, 217226.CrossRefGoogle ScholarPubMed
Leong, M. K. & Chen, T. H. (2008). Prediction of cytochrome P450 2B6-substrate interactions using pharmacophore ensemble/support vector machine (PhE/SVM) approach. Medicinal Chemistry 4, 396406.CrossRefGoogle ScholarPubMed
Leong, M. K., Chen, Y. M., Chen, H. B. & Chen, P. H. (2009). Development of a new predictive model for interactions with human cytochrome P450 2A6 using pharmacophore ensemble/support vector machine (PhE/SVM) approach. Pharmaceutical Research 26, 9871000.CrossRefGoogle ScholarPubMed
Lexa, K. W. & Carlson, H. A. (2011). Full protein flexibility is essential for proper hot-spot mapping. Journal of the American Chemical Society 133, 200202.CrossRefGoogle ScholarPubMed
Lin, J. H., Perryman, A. L., Schames, J. R. & McCammon, J. A. (2002). Computational drug design accommodating receptor flexibility: the relaxed complex scheme. Journal of the American Chemical Society 124, 56325633.CrossRefGoogle ScholarPubMed
Lin, J. H., Perryman, A. L., Schames, J. R. & McCammon, J. A. (2003). The relaxed complex method: accommodating receptor flexibility for drug design with an improved scoring scheme. Biopolymers 68, 4762.CrossRefGoogle ScholarPubMed
Lindahl, E. & Delarue, M. (2005). Refinement of docked protein–ligand and protein–DNA structures using low frequency normal mode amplitude optimization. Nucleic Acids Research 33, 44964506.CrossRefGoogle ScholarPubMed
Marti-Renom, M. A., Stuart, A. C., Fiser, A., Sanchez, R., Melo, F. & Sali, A. (2000). Comparative protein structure modeling of genes and genomes. Annual Reviews of Biophysics and Biomolecular Structure 29, 291325.CrossRefGoogle ScholarPubMed
Mattos, C. & Ringe, D. (1996). Locating and characterizing binding sites on proteins. Nature Biotechnology 14, 595599.CrossRefGoogle ScholarPubMed
May, A., Sieker, F. & Zacharias, M. (2008). How to efficiently include receptor flexibility during computational docking. Current Computer-Aided Drug Design 4, 143153.CrossRefGoogle Scholar
May, A. & Zacharias, M. (2005). Accounting for global protein deformability during protein–protein and protein–ligand docking. Biochimica and Biophysica Acta 1754, 225231.CrossRefGoogle ScholarPubMed
May, A. & Zacharias, M. (2008). Protein–ligand docking accounting for receptor side chain and global flexibility in normal modes: evaluation on kinase inhibitor cross docking. Journal of Medicinal Chemistry 51, 34993506.CrossRefGoogle ScholarPubMed
McCammon, J. A. (2005). Target flexibility in molecular recognition. Biochimica and Biophysica Acta 1754, 221224.CrossRefGoogle ScholarPubMed
Meiler, J. & Baker, D. (2006). ROSETTALIGAND: protein-small molecule docking with full side-chain flexibility. Proteins 65, 538548.CrossRefGoogle ScholarPubMed
Miranker, A. & Karplus, M. (1991). Functionality maps of binding sites: a multiple copy simultaneous search method. Proteins 11, 2934.CrossRefGoogle ScholarPubMed
Mizutani, M. Y., Takamatsu, Y., Ichinose, T., Nakamura, K. & Itai, A. (2006). Effective handling of induced-fit motion in flexible docking. Proteins 63, 878891.CrossRefGoogle ScholarPubMed
Mobley, D. L. & Dill, K. A. (2009). Binding of small-molecule ligands to proteins: “What you see” is not always “what you get”. Structure 17, 489498.CrossRefGoogle Scholar
Moitessier, N., Englebienne, P., Lee, D., Lawandi, J. & Corbeil, C. R. (2008). Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go. British Journal of Pharmacology 153 (Suppl. 1), S726.CrossRefGoogle ScholarPubMed
Monod, J., Wyman, J. & Changeux, J. P. (1965). On the nature of allosteric transitions: a plausible model. Journal of Molecular Biology 12, 88118.CrossRefGoogle ScholarPubMed
Moore, W. R. Jr. (2005). Maximizing discovery efficiency with a computationally driven fragment approach. Current Opinion in Drug Discovery and Development 8, 355364.Google ScholarPubMed
Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S. & Olson, A. J. (2009). AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. Journal of Computational Chemistry 30, 2785–2781.CrossRefGoogle ScholarPubMed
Mukherjee, S., Balius, T. E. & Rizzo, R. C. (2010). Docking validation resources: protein family and ligand flexibility experiments. Journal of Chemical Information and Modeling 50, 19862000.CrossRefGoogle ScholarPubMed
Murray, C. W., Baxter, C. A. & Frenkel, A. D. (1999). The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase. Journal of Computer-Aided Molecular Design 13, 547562.CrossRefGoogle ScholarPubMed
Murray, C. W. & Rees, D. C. (2009). The rise of fragment-based drug discovery. Nature Chemistry 1, 187192.CrossRefGoogle ScholarPubMed
Mustata, G. I. & Briggs, J. M. (2002). A structure-based design approach for the identification of novel inhibitors: application to an alanine racemase. Journal of Computer-Aided Molecular Design 16, 935953.CrossRefGoogle Scholar
Mustata, G. I., Soares, T. A. & Briggs, J. M. (2003). Molecular dynamics studies of alanine racemase: a structural model for drug design. Biopolymers 70, 186200.CrossRefGoogle ScholarPubMed
Nabuurs, S. B., Wagener, M. & De Vlieg, J. (2007). A flexible approach to induce fit docking. Journal of Medicinal Chemistry 50, 65076518.CrossRefGoogle ScholarPubMed
Najmanovich, R., Kuttner, J., Sobolev, V. & Edelman, M. (2000). Side-chain flexibility in proteins upon ligand binding. Proteins 39, 261268.3.0.CO;2-4>CrossRefGoogle ScholarPubMed
Nichols, S. E., Baron, R., Ivetac, A. & McCammon, J. A. (2011). Predictive power of molecular dynamics receptor structures in virtual screening. Journal of Chemical Information and Modeling 51, 14391446.CrossRefGoogle ScholarPubMed
Osterberg, F., Morris, G. M., Sanner, M. F., Olson, A. J. & Goodsell, D. S. (2002). Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock. Proteins 46, 3440.CrossRefGoogle ScholarPubMed
Ota, N. & Agard, D. A. (2001). Binding mode prediction for a flexible ligand in a flexible pocket using multi-conformation simulated annealing pseudo crystallographic refinement. Journal of Molecular Biology 314, 607617.CrossRefGoogle Scholar
Pencheva, T., Lagorce, D., Pajeva, I., Villoutreix, B. O. & Miteva, M. A. (2008). AMMOS: automated molecular mechanics optimization tool for in silico screening. BMC Bioinformatics 9, 438.CrossRefGoogle ScholarPubMed
Perryman, A. L., Lin, J. H. & McCammon, J. A. (2006). Optimization and computational evaluation of a series of potential active site inhibitors of the V82F/I84V drug-resistant mutant of HIV-1 protease: an application of the relaxed complex method of structure-based drug design. Chemical Biology and Drug Design 67, 336345.CrossRefGoogle ScholarPubMed
Philippopoulos, M. & Lim, C. (1999). Exploring the dynamic information content of a protein NMR structure: comparison of a molecular dynamics simulation with the NMR and X-ray structures of Escherichia coli ribonuclease HI. Proteins 36, 87110.3.0.CO;2-R>CrossRefGoogle ScholarPubMed
Plewczynski, D., Lazniewski, M., Augustyniak, R. & Ginalski, K. (2011). Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database. Journal of Computational Chemistry 32, 742755.CrossRefGoogle ScholarPubMed
Popov, V. M., Yee, W. A. & Anderson, A. C. (2007). Towards in silico lead optimization: scores from ensembles of protein/ligand conformations reliably correlate with biological activity. Proteins 66, 375387.CrossRefGoogle ScholarPubMed
Raman, E. P., Yu, W., Guvench, O. & Mackerell, A. D. (2011). Reproducing crystal binding modes of ligand functional groups using site-identification by ligand competitive saturation (SILCS) simulations. Journal of Chemical Information and Modeling 51, 877896.CrossRefGoogle ScholarPubMed
Rao, C. B., Subramanian, J. & Sharma, S. D. (2009). Managing protein flexibility in docking and its applications. Drug Discovery Today 14, 394400.CrossRefGoogle Scholar
Rarey, M., Kramer, B., Lengauer, T. & Klebe, G. (1996). A fast flexible docking method using an incremental construction algorithm. Journal of Molecular Biology 261, 470489.CrossRefGoogle ScholarPubMed
Rueda, M., Bottegoni, G. & Abagyan, R. (2009). Consistent improvement of cross-docking results using binding site ensembles generated with elastic network normal modes. Journal of Chemical Information and Modeling 49, 716725.CrossRefGoogle ScholarPubMed
Rueda, M., Bottegoni, G. & Abagyan, R. (2010). Recipes for the selection of experimental protein conformations for virtual screening. Journal of Chemical Information and Modeling 50, 186193.CrossRefGoogle ScholarPubMed
Schafferhans, A. & Klebe, G. (2001). Docking ligands onto binding site representations derived from proteins built by homology modelling. Journal of Molecular Biology 307, 407427.CrossRefGoogle ScholarPubMed
Schmitke, J. L., Stern, L. J. & Klibanov, A. M. (1997). The crystal structure of subtilisin Carlsberg in anhydrous dioxane and its comparison with those in water and acetonitrile. Proceedings of the National Academy of Sciences of the United States of America 94, 42504255.CrossRefGoogle ScholarPubMed
Schmitke, J. L., Stern, L. J. & Klibanov, A. M. (1998). Comparison of x-ray crystal structures of an acyl-enzyme intermediate of subtilisin Carlsberg formed in anhydrous acetonitrile and in water. Proceedings of the National Academy of Sciences of the United States of America 95, 1291812923.CrossRefGoogle ScholarPubMed
Schnecke, V. & Kuhn, L. A. (2000). Virtual screening with solvation and ligand-induced complementarity. Perspectives in Drug Discovery and Design 20, 171190.CrossRefGoogle Scholar
Schubert, C. R. & Stultz, C. M. (2009). The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design. Journal of Computer-Aided Molecular Design 23, 475489.CrossRefGoogle ScholarPubMed
Seco, J., Luque, F. J. & Barril, X. (2009). Binding site detection and druggability index from first principles. Journal of Medicinal Chemistry 52, 23632371.CrossRefGoogle ScholarPubMed
Sherman, W., Beard, H. S. & Farid, R. (2006a). Use of an induced fit receptor structure in virtual screening. Chemical Biology and Drug Design 67, 8384.CrossRefGoogle ScholarPubMed
Sherman, W., Day, T., Jacobson, M. P., Friesner, R. A. & Farid, R. (2006b). Novel procedure for modeling ligand/receptor induced fit effects. Journal of Medicinal Chemistry 49, 534553.CrossRefGoogle ScholarPubMed
Shuker, S. B., Hajduk, P. J., Meadows, R. P. & Fesik, S. W. (1996). Discovering high-affinity ligands for proteins: SAR by NMR. Science 274, 15311534.CrossRefGoogle ScholarPubMed
Smith, L. J., Redfield, C., Smith, R. A., Dobson, C. M., Clore, G. M., Gronenborn, A. M., Walter, M. R., Naganbushan, T. L. & Wlodawer, A. (1994). Comparison of four independently determined structures of human recombinant interleukin-4. Nature Structural Biology 1, 301310.CrossRefGoogle ScholarPubMed
Smith, R. D., Dunbar, J. B. Jr., Ung, P. M. U., Esposito, E. X., Yang, C.-Y., Wang, S. & Carlson, H. A. (2011). CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions. Journal of Chemical Information and Modeling 51(9), 20362046.CrossRefGoogle ScholarPubMed
Sotriffer, C. A. (2011). Accounting for induced-fit effects in docking: what is possible and what is not? Current Topics in Medicinal Chemistry 11, 179191.CrossRefGoogle ScholarPubMed
Sousa, S. F., Fernandes, P. A. & Ramos, M. J. (2006). Protein–ligand docking: current status and future challenges. Proteins 65, 1526.CrossRefGoogle ScholarPubMed
Sperandio, O., Mouawad, L., Pinto, E., Villoutreix, B. O., Perahia, D. & Miteva, M. A. (2010). How to choose relevant multiple receptor conformations for virtual screening: a test case of Cdk2 and normal mode analysis. European Biophysics Journal 39, 13651372.CrossRefGoogle ScholarPubMed
Stultz, C. M. & Karplus, M. (1999). MCSS functionality maps for a flexible protein. Proteins 37, 512529.3.0.CO;2-O>CrossRefGoogle ScholarPubMed
Subramanian, J., Sharma, S. & B-Rao, C. (2006). A novel computational analysis of ligand-induced conformational changes in the ATP binding sites of cyclin dependent kinases. Journal of Medicinal Chemistry 49, 54345441.CrossRefGoogle ScholarPubMed
Subramanian, J., Sharma, S. & B-Rao, C. (2008). Modeling and selection of flexible proteins for structure-based drug design: backbone and side chain movements in p38 MAPK. ChemMedChem 3, 336344.CrossRefGoogle ScholarPubMed
Sullivan, S. M. & Holyoak, T. (2008). Enzymes with lid-gated active sites must operate by an induced fit mechanism instead of conformational selection. Proceedings of the National Academy of Sciences of the United States of America 105, 1382913834.CrossRefGoogle ScholarPubMed
Sweeney, Z. K., Harris, S. F., Arora, N., Javanbakht, H., Li, Y., Fretland, J., Davidson, J. P., Billedeau, J. R., Gleason, S. K., Hirschfeld, D., Kennedy-Smith, J. J., Mirzadegan, T., Roetz, R., Smith, M., Sperry, S., Suh, J. M., Wu, J., Tsing, S., Villaseñor, A. G., Paul, A., Su, G., Heilek, G., Hang, J. Q., Zhou, A. S., Jernelius, J. A., Zhang, F-J. & Klumpp, K. (2008). Design of annulated pyrazoles as inhibitors of HIV-1 reverse transcriptase. Journal of Medicinal Chemistry 51, 74497458.CrossRefGoogle ScholarPubMed
Taft, C. A., Da Silva, V. B. & Da Silva, C. H. (2008). Current topics in computer-aided drug design. Journal of Pharmaceutical Sciences 97, 10891098.CrossRefGoogle ScholarPubMed
Talele, T. T., Khedkar, S. A. & Rigby, A. C. (2010). Successful applications of computer aided drug discovery: moving drugs from concept to the clinic. Current Topics in Medicinal Chemistry 10, 127141.CrossRefGoogle ScholarPubMed
Taylor, R. D., Jewsbury, P. J. & Essex, J. W. (2003). FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function. Journal of Computational Chemistry 24, 16371656.CrossRefGoogle ScholarPubMed
Teague, S. J. (2003). Implications of protein flexibility for drug discovery. Nature Reviews Drug Discovery 2, 527541.CrossRefGoogle ScholarPubMed
Teodoro, M. L. & Kavraki, L. E. (2003). Conformational flexibility models for the receptor in structure based drug design. Current Pharmaceutical Design 9, 16351648.CrossRefGoogle ScholarPubMed
Totrov, M. & Abagyan, R. (2008). Flexible ligand docking to multiple receptor conformations: a practical alternative. Current Opinions in Structural Biology 18, 178184.CrossRefGoogle ScholarPubMed
Tsai, C. J., Kumar, S., Ma, B. & Nussinov, R. (1999a). Folding funnels, binding funnels, and protein function. Protein Science 8, 11811190.CrossRefGoogle ScholarPubMed
Tsai, C. J., Ma, B. & Nussinov, R. (1999b). Folding and binding cascades: shifts in energy landscapes. Proceedings of the National Academy of Sciences of the United States of America 96, 99709972.CrossRefGoogle ScholarPubMed
Tsai, C. J., Ma, B., Sham, Y. Y., Kumar, S. & Nussinov, R. (2001). Structured disorder and conformational selection. Proteins 44, 418427.CrossRefGoogle ScholarPubMed
van Westen, G. J. P., Wegner, J. K., Bender, A., Ijzerman, A. P. & van Vlijmen, H. W. T. (2010). Mining protein dynamics from sets of crystal structures using “consensus structures”. Protein Science 19, 742752.CrossRefGoogle ScholarPubMed
Velec, H. F., Gohlke, H. & Klebe, G. (2005). DrugScore(CSD)-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction. Journal of Medicinal Chemistry 48, 62966303.CrossRefGoogle ScholarPubMed
Verdonk, M. L., Mortenson, P. N., Hall, R. J., Hartshorn, M. J. & Murray, C. W. (2008). Protein-ligand docking against non-native protein conformers. Journal of Chemical Information and Modeling 48, 22142225.CrossRefGoogle ScholarPubMed
Wang, Z., Zhu, G., Huang, Q., Qian, M., Shao, M., Jia, Y. & Tang, Y. (1998). X-ray studies on cross-linked lysozyme crystals in acetonitrile–water mixture. Biochimica and Biophysica Acta 1384, 335344.CrossRefGoogle ScholarPubMed
Warren, G. L., Andrews, C. W., Capelli, A. M., Clarke, B., LaLonde, J., Lambert, M. H., Lindvall, M., Nevins, N., Semus, S. F., Senger, S., Tedesco, G., Wall, I. D., Woolven, J. M., Peishoff, C. E. & Head, M. S. (2006). A critical assessment of docking programs and scoring functions. Journal of Medicinal Chemistry 49, 59125931.CrossRefGoogle ScholarPubMed
Wei, B. Q., Weaver, L. H., Ferrari, A. M., Matthews, B. W. & Shoichet, B. K. (2004). Testing a flexible-receptor docking algorithm in a model binding site. Journal of Molecular Biology 337, 11611182.CrossRefGoogle Scholar
Weikl, T. R. & von Deuster, C. (2009). Selected-fit versus induced-fit protein binding: kinetic differences and mutational analysis. Proteins 75, 104110.CrossRefGoogle ScholarPubMed
Wiesmann, C., Barr, K. J., Kung, J., Zhu, J., Erlanson, D. A., Shen, W., Fahr, B. J., Zhong, M., Taylor, L., Randal, M., McDowell, R. S. & Hansen, S. K. (2004). Allosteric inhibition of protein tyrosine phosphatase 1B. Nature Structural and Molecular Biology 11, 730737.CrossRefGoogle ScholarPubMed
Wong, S. & Jacobson, M. P. (2008). Conformational selection in silico: loop latching motions and ligand binding in enzymes. Proteins 71, 153164.CrossRefGoogle ScholarPubMed
Yang, C. & Wang, S. (2010). Computational analysis of protein hotspots. ACS Medicinal Chemistry Letters 1, 125129.CrossRefGoogle ScholarPubMed
Yang, L. W., Eyal, E., Chennubhotla, C., Jee, J., Gronenborn, A. M. & Bahar, I. (2007). Insights into equilibrium dynamics of proteins from comparison of NMR and X-ray data with computational predictions. Structure 15, 741749.CrossRefGoogle ScholarPubMed
Zacharias, M. (2004). Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP. Proteins: Structure, Function, and Bioinformatics 54, 759767.CrossRefGoogle ScholarPubMed
Zacharias, M. (2008). Combining elastic network analysis and molecular dynamics simulations by hamiltonian replica exchange. Journal of Chemical Theory and Computation 4, 477487.CrossRefGoogle ScholarPubMed
Zacharias, M. & Sklenar, H. (1999). Harmonic modes as variables to approximately account for receptor flexibility in ligand-receptor docking simulations: application to DNA minor groove ligand complex. Journal of Computational Chemistry 20, 287300.3.0.CO;2-H>CrossRefGoogle Scholar
Zavodszky, M. I. & Kuhn, L. A. (2005). Side-chain flexibility in protein–ligand binding: the minimal rotation hypothesis. Protein Science 14, 11041114.CrossRefGoogle ScholarPubMed
Zavodszky, M. I., Lei, M., Thorpe, M. F., Day, A. R. & Kuhn, L. A. (2004). Modeling correlated main-chain motions in proteins for flexible molecular recognition. Proteins: Structure, Function, and Bioinformatics 57, 243261.CrossRefGoogle ScholarPubMed
Zavodszky, M. I., Sanschagrin, P. C., Korde, R. S. & Kuhn, L. A. (2002). Distilling the essential features of a protein surface for improving protein–ligand docking, scoring, and virtual screening. Journal of Computer-Aided Molecular Design 16, 883902.CrossRefGoogle ScholarPubMed
Zentgraf, M., Fokkens, J. & Sotriffer, C. A. (2006). Addressing protein flexibility and ligand selectivity by “in situ cross-docking”. ChemMedChem 1, 13551359.CrossRefGoogle ScholarPubMed
Zentgraf, M., Steuber, H., Koch, C., La Motta, C., Sartini, S., Sotriffer, C. A. & Klebe, G. (2007). How reliable are current docking approaches for structure-based drug design? Lessons from aldose reductase. Angewandte Chemie 46, 35753578.CrossRefGoogle ScholarPubMed
Zhao, Y. & Sanner, M. F. (2007). FLIPDock: docking flexible ligands into flexible receptors. Proteins: Structure, Function, and Bioinformatics 68, 726737.CrossRefGoogle ScholarPubMed
Zhao, Y. & Sanner, M. F. (2008). Protein-ligand docking with multiple flexible side chains. Journal of Computer-Aided Molecular Design 22, 673679.CrossRefGoogle ScholarPubMed
Zhu, J., Fan, H., Liu, H. & Shi, Y. (2001). Structure-based ligand design for flexible proteins: application of new F-DycoBlock. Journal of Computer-Aided Molecular Design 15, 979996.CrossRefGoogle ScholarPubMed