1
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Lee C, Yang J, Kwon S, Seok C. GalaxyDock2-HEME: Protein-ligand docking for heme proteins. J Comput Chem 2023; 44:1369-1380. [PMID: 36809651 DOI: 10.1002/jcc.27092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/20/2023] [Accepted: 02/08/2023] [Indexed: 02/23/2023]
Abstract
Prediction of protein-ligand binding poses is an essential component for understanding protein-ligand interactions and computer-aided drug design. Various proteins involve prosthetic groups such as heme for their functions, and adequate consideration of the prosthetic groups is vital for protein-ligand docking. Here, we extend the GalaxyDock2 protein-ligand docking algorithm to handle ligand docking to heme proteins. Docking to heme proteins involves increased complexity because the interaction of heme iron and ligand has covalent nature. GalaxyDock2-HEME, a new protein-ligand docking program for heme proteins, has been developed based on GalaxyDock2 by adding an orientation-dependent scoring term to describe heme iron-ligand coordination interaction. This new docking program performs better than other noncommercial docking programs such as EADock with MMBP, AutoDock Vina, PLANTS, LeDock, and GalaxyDock2 on a heme protein-ligand docking benchmark set in which ligands are known to bind iron. In addition, docking results on two other sets of heme protein-ligand complexes in which ligands do not bind iron show that GalaxyDock2-HEME does not have a high bias toward iron binding compared to other docking programs. This implies that the new docking program can distinguish iron binders from noniron binders for heme proteins.
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Affiliation(s)
- Changsoo Lee
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Jinsol Yang
- Galux Inc, Gwanak-gu, Seoul, Republic of Korea
| | - Sohee Kwon
- Galux Inc, Gwanak-gu, Seoul, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea.,Galux Inc, Gwanak-gu, Seoul, Republic of Korea
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2
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Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives. Appl Soft Comput 2019. [DOI: 10.1016/j.asoc.2019.03.044] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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3
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Joung I, Kim JY, Joo K, Lee J. Non-sequential protein structure alignment by conformational space annealing and local refinement. PLoS One 2019; 14:e0210177. [PMID: 30699145 PMCID: PMC6353097 DOI: 10.1371/journal.pone.0210177] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 12/18/2018] [Indexed: 11/18/2022] Open
Abstract
Protein structure alignment is an important tool for studying evolutionary biology and protein modeling. A tool which intensively searches for the globally optimal non-sequential alignments is rarely found. We propose ALIGN-CSA which shows improvement in scores, such as DALI-score, SP-score, SO-score and TM-score over the benchmark set including 286 cases. We performed benchmarking of existing popular alignment scoring functions, where the dependence of the search algorithm was effectively eliminated by using ALIGN-CSA. For the benchmarking, we set the minimum block size to 4 to prevent much fragmented alignments where the biological relevance of small alignment blocks is hard to interpret. With this condition, globally optimal alignments were searched by ALIGN-CSA using the four scoring functions listed above, and TM-score is found to be the most effective in generating alignments with longer match lengths and smaller RMSD values. However, DALI-score is the most effective in generating alignments similar to the manually curated reference alignments, which implies that DALI-score is more biologically relevant score. Due to the high demand on computational resources of ALIGN-CSA, we also propose a relatively fast local refinement method, which can control the minimum block size and whether to allow the reverse alignment. ALIGN-CSA can be used to obtain much improved alignment at the cost of relatively more extensive computation. For faster alignment, we propose a refinement protocol that improves the score of a given alignment obtained by various external tools. All programs are available from http://lee.kias.re.kr.
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Affiliation(s)
- InSuk Joung
- Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea
| | - Jong Yun Kim
- Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea
| | - Keehyoung Joo
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea
- Center for Advanced Computation, Korea Institute for Advanced Study, Seoul, Korea
| | - Jooyoung Lee
- Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea
- Center for Advanced Computation, Korea Institute for Advanced Study, Seoul, Korea
- * E-mail:
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4
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GalaxyDock BP2 score: a hybrid scoring function for accurate protein–ligand docking. J Comput Aided Mol Des 2017. [DOI: 10.1007/s10822-017-0030-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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5
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Joo K, Joung I, Lee J, Lee J, Lee W, Brooks B, Lee SJ, Lee J. Protein structure determination by conformational space annealing using NMR geometric restraints. Proteins 2015; 83:2251-62. [PMID: 26454251 DOI: 10.1002/prot.24941] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2015] [Revised: 09/19/2015] [Accepted: 09/22/2015] [Indexed: 11/06/2022]
Abstract
We have carried out numerical experiments to investigate the applicability of the global optimization method of conformational space annealing (CSA) to the enhanced NMR protein structure determination over existing PDB structures. The NMR protein structure determination is driven by the optimization of collective multiple restraints arising from experimental data and the basic stereochemical properties of a protein-like molecule. By rigorous and straightforward application of CSA to the identical NMR experimental data used to generate existing PDB structures, we redetermined 56 recent PDB protein structures starting from fully randomized structures. The quality of CSA-generated structures and existing PDB structures were assessed by multiobjective functions in terms of their consistencies with experimental data and the requirements of protein-like stereochemistry. In 54 out of 56 cases, CSA-generated structures were better than existing PDB structures in the Pareto-dominant manner, while in the remaining two cases, it was a tie with mixed results. As a whole, all structural features tested improved in a statistically meaningful manner. The most improved feature was the Ramachandran favored portion of backbone torsion angles with about 8.6% improvement from 88.9% to 97.5% (P-value <10(-17)). We show that by straightforward application of CSA to the efficient global optimization of an energy function, NMR structures will be of better quality than existing PDB structures.
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Affiliation(s)
- Keehyoung Joo
- Center for in Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea.,Center for Advanced Computation, Korea Institute for Advanced Study, Seoul, 130-722, Korea
| | - InSuk Joung
- Center for in Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea.,School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 130-722, Korea
| | - Jinhyuk Lee
- Korean Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology, Daejeon, 305-806, Korea.,Department of Nanobiotechnology and Bioinformatics, University of Sciences and Technology, Daejeon, 305-350, Korea
| | - Jinwoo Lee
- Department of Mathematics, Kwangwoon University, Nowon-Gu, Seoul, 139-701, Korea
| | - Weontae Lee
- Department of Biochemistry, Yonsei University, Seodaemun-Gu, Seoul, 120-749, Korea
| | - Bernard Brooks
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, 20852
| | - Sung Jong Lee
- Center for in Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea.,Department of Physics, University of Suwon, Hwaseong-Si, Gyeonggi-Do, 445-743, Korea
| | - Jooyoung Lee
- Center for in Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea.,School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 130-722, Korea
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Heo L, Shin WH, Lee MS, Seok C. GalaxySite: ligand-binding-site prediction by using molecular docking. Nucleic Acids Res 2014; 42:W210-4. [PMID: 24753427 PMCID: PMC4086128 DOI: 10.1093/nar/gku321] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Knowledge of ligand-binding sites of proteins provides invaluable information for
functional studies, drug design and protein design. Recent progress in
ligand-binding-site prediction methods has demonstrated that using information
from similar proteins of known structures can improve predictions. The
GalaxySite web server, freely accessible at http://galaxy.seoklab.org/site, combines such information with
molecular docking for more precise binding-site prediction for non-metal
ligands. According to the recent critical assessments of structure prediction
methods held in 2010 and 2012, this server was found to be superior or
comparable to other state-of-the-art programs in the category of
ligand-binding-site prediction. A strong merit of the GalaxySite program is that
it provides additional predictions on binding ligands and their binding poses in
terms of the optimized 3D coordinates of the protein–ligand complexes,
whereas other methods predict only identities of binding-site residues or copy
binding geometry from similar proteins. The additional information on the
specific binding geometry would be very useful for applications in functional
studies and computer-aided drug discovery.
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Affiliation(s)
- Lim Heo
- Department of Chemistry, Seoul National University, Seoul 151-747, Korea
| | - Woong-Hee Shin
- Department of Chemistry, Seoul National University, Seoul 151-747, Korea
| | - Myeong Sup Lee
- Department of Biomedical Sciences, University of Ulsan College of Medicine, Seoul 138-736, Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul 151-747, Korea
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7
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Okur A, Miller BT, Joo K, Lee J, Brooks BR. Generating reservoir conformations for replica exchange through the use of the conformational space annealing method. J Chem Theory Comput 2013; 9:1115-1124. [PMID: 23585739 PMCID: PMC3621806 DOI: 10.1021/ct300996m] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Temperature replica exchange molecular dynamics (T-REM) has been successfully used to improve the conformational search for model peptides and small proteins. However, for larger and more complicated systems, the use of T-REM is computationally intensive since the complexity of the free energy landscape and number of replicas required increase with system size. Achieving convergence of systems with slow transition kinetics is often difficult. Several methods have been proposed to overcome the size and convergence speed issues of standard T-REM. One of these is the Reservoir Replica Exchange Method (R-REM), in which the conformational search and temperature equilibration are separated by exchanging with a pre-existing reservoir of structures. This approach allows the integration of computationally efficient search algorithms with replica exchange. The Conformational Space Annealing (CSA) method has been shown to be able to determine the global energy minimum of proteins efficiently and has been used in structure prediction successfully. CSA uses a genetic algorithm to generate a diverse set of conformations to determine the minimum energy structure. We combine these methods by using conformations generated by the CSA method to build a reservoir. R-REM is then used to seed the top replica with the structures from the reservoir; fast convergence at every temperature is observed. The efficiency of this method is then demonstrated with model peptides and small proteins, and significant improvement of efficiency is observed while maintaining the overall shape of the free energy landscape.
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Affiliation(s)
- Asim Okur
- Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda MD
| | - Benjamin T. Miller
- Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda MD
| | | | - Jooyoung Lee
- Korea Institute of Advanced Sciences, Seoul, Korea
| | - Bernard R. Brooks
- Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda MD
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8
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Abstract
An important issue in developing protein-ligand docking methods is how to incorporate receptor flexibility. Consideration of receptor flexibility using an ensemble of precompiled receptor conformations or by employing an effectively enlarged binding pocket has been reported to be useful. However, direct consideration of receptor flexibility during energy optimization of the docked conformation has been less popular because of the large increase in computational complexity. In this paper, we present a new docking program called GalaxyDock that accounts for the flexibility of preselected receptor side-chains by global optimization of an AutoDock-based energy function trained for flexible side-chain docking. This method was tested on 3 sets of protein-ligand complexes (HIV-PR, LXRβ, cAPK) and a diverse set of 16 proteins that involve side-chain conformational changes upon ligand binding. The cross-docking tests show that the performance of GalaxyDock is higher or comparable to previous flexible docking methods tested on the same sets, increasing the binding conformation prediction accuracy by 10%-60% compared to rigid-receptor docking. This encouraging result suggests that this powerful global energy optimization method may be further extended to incorporate larger magnitudes of receptor flexibility in the future. The program is available at http://galaxy.seoklab.org/softwares/galaxydock.html .
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Affiliation(s)
- Woong-Hee Shin
- Department of Chemistry, Seoul National University, Seoul 151-747, Republic of Korea
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9
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Curuksu J. Adaptive conformational sampling based on replicas. J Math Biol 2012; 64:917-31. [DOI: 10.1007/s00285-011-0432-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2010] [Revised: 04/09/2011] [Indexed: 11/28/2022]
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10
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Shin WH, Heo L, Lee J, Ko J, Seok C, Lee J. LigDockCSA: Protein-ligand docking using conformational space annealing. J Comput Chem 2011; 32:3226-32. [DOI: 10.1002/jcc.21905] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2010] [Revised: 06/17/2011] [Accepted: 07/06/2011] [Indexed: 11/12/2022]
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11
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Lee J, Lee J, Sasaki TN, Sasai M, Seok C, Lee J. De novo
protein structure prediction by dynamic fragment assembly and conformational space annealing. Proteins 2011; 79:2403-17. [DOI: 10.1002/prot.23059] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2010] [Revised: 03/24/2011] [Accepted: 04/12/2011] [Indexed: 12/25/2022]
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12
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Kim SY. An off-lattice frustrated model protein with a six-stranded β-barrel structure. J Chem Phys 2010; 133:135102. [DOI: 10.1063/1.3494038] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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13
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Liu X, Bai F, Ouyang S, Wang X, Li H, Jiang H. Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation. BMC Bioinformatics 2009; 10:101. [PMID: 19335906 PMCID: PMC2678094 DOI: 10.1186/1471-2105-10-101] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2008] [Accepted: 03/31/2009] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. RESULTS The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105-112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 A to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 +/- 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. CONCLUSION On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.
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Affiliation(s)
- Xiaofeng Liu
- Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, PR China.
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14
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Kang L, Li H, Jiang H, Wang X. An improved adaptive genetic algorithm for protein–ligand docking. J Comput Aided Mol Des 2008; 23:1-12. [DOI: 10.1007/s10822-008-9232-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2007] [Accepted: 07/30/2008] [Indexed: 11/24/2022]
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15
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Computational study for protein-protein docking using global optimization and empirical potentials. Int J Mol Sci 2008; 9:65-77. [PMID: 19325720 PMCID: PMC2635596 DOI: 10.3390/ijms9010065] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2007] [Accepted: 01/15/2008] [Indexed: 11/17/2022] Open
Abstract
Protein-protein interactions are important for biochemical processes in biological systems. The 3D structure of the macromolecular complex resulting from the protein-protein association is a very useful source to understand its specific functions. This work focuses on computational study for protein-protein docking, where the individually crystallized structures of interacting proteins are treated as rigid, and the conformational space generated by the two interacting proteins is explored extensively. The energy function consists of intermolecular electrostatic potential, desolvation free energy represented by empirical contact potential, and simple repulsive energy terms. The conformational space is six dimensional, represented by translational vectors and rotational angles formed between two interacting proteins. The conformational sampling is carried out by the search algorithms such as simulated annealing (SA), conformational space annealing (CSA), and CSA combined with SA simulations (combined CSA/SA). Benchmark tests are performed on a set of 18 protein-protein complexes selected from various protein families to examine feasibility of these search methods coupled with the energy function above for protein docking study.
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16
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Müller W, Sticht H. A protein-specifically adapted scoring function for the reranking of docking solutions. Proteins 2007; 67:98-111. [PMID: 17243180 DOI: 10.1002/prot.21310] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
In this work, we developed a protein-specifically adapted scoring function and applied it to the reranking of protein-protein docking solutions generated with a conventional docking program. The approach was validated using experimentally determined structures of the bacterial HPr-protein in complex with four structurally nonhomologous binding partners as an example. A sufficiently large data basis for the generation of protein-specifically adapted pair potentials was generated by modeling all orthologous complexes for each type of interaction resulting in a total of 224 complexes. The parameters for potential generation were systematically varied and resulted in a total of 66,132 different scoring functions that were tested for their ability of successful reranking of 1000 docking solutions generated from modeled structures of the unbound binding partners. Parameters that proved critical for the generation of good scoring functions were the distance cutoff used for the generation of the pair potential, and an additional cutoff that allows a proper weighting of conserved and nonconserved contacts in the interface. Compared to the original scoring function, application of this novel type of scoring functions resulted in a significant accumulation of acceptable docking solutions within the first 10 ranks. Depending on the type of complex investigated one to five acceptable complex geometries are found among the 10 highest-ranked solutions and for three of the four systems tested, an acceptable solution was placed on the first rank.
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Affiliation(s)
- Wolfgang Müller
- Institut für Biochemie, Abteilung Bioinformatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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17
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Méndez R, Leplae R, Lensink MF, Wodak SJ. Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures. Proteins 2006; 60:150-69. [PMID: 15981261 DOI: 10.1002/prot.20551] [Citation(s) in RCA: 269] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst.
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Affiliation(s)
- Raúl Méndez
- Service de Conformation de Macromolécules Biologiques et Bioinformatique, Centre de Biologie Structurale et Bioinformatique, Université Libre de Bruxelles, Bruxelles, Belgium
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18
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Rohs R, Bloch I, Sklenar H, Shakked Z. Molecular flexibility in ab initio drug docking to DNA: binding-site and binding-mode transitions in all-atom Monte Carlo simulations. Nucleic Acids Res 2005; 33:7048-57. [PMID: 16352865 PMCID: PMC1312361 DOI: 10.1093/nar/gki1008] [Citation(s) in RCA: 202] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The dynamics of biological processes depend on the structure and flexibility of the interacting molecules. In particular, the conformational diversity of DNA allows for large deformations upon binding. Drug–DNA interactions are of high pharmaceutical interest since the mode of action of anticancer, antiviral, antibacterial and other drugs is directly associated with their binding to DNA. A reliable prediction of drug–DNA binding at the atomic level by molecular docking methods provides the basis for the design of new drug compounds. Here, we propose a novel Monte Carlo (MC) algorithm for drug–DNA docking that accounts for the molecular flexibility of both constituents and samples the docking geometry without any prior binding-site selection. The binding of the antimalarial drug methylene blue at the DNA minor groove with a preference of binding to AT-rich over GC-rich base sequences is obtained in MC simulations in accordance with experimental data. In addition, the transition between two drug–DNA-binding modes, intercalation and minor-groove binding, has been achieved in dependence on the DNA base sequence. The reliable ab initio prediction of drug–DNA binding achieved by our new MC docking algorithm is an important step towards a realistic description of the structure and dynamics of molecular recognition in biological systems.
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Affiliation(s)
- Remo Rohs
- Department of Structural Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
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19
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Huang PS, Love JJ, Mayo SL. Adaptation of a fast Fourier transform-based docking algorithm for protein design. J Comput Chem 2005; 26:1222-32. [PMID: 15962277 DOI: 10.1002/jcc.20252] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Designing proteins with novel protein/protein binding properties can be achieved by combining the tools that have been developed independently for protein docking and protein design. We describe here the sequence-independent generation of protein dimer orientations by protein docking for use as scaffolds in protein sequence design algorithms. To dock monomers into sequence-independent dimer conformations, we use a reduced representation in which the side chains are approximated by spheres with atomic radii derived from known C2 symmetry-related homodimers. The interfaces of C2-related homodimers are usually more hydrophobic and protein core-like than the interfaces of heterodimers; we parameterize the radii for docking against this feature to capture and recreate the spatial characteristics of a hydrophobic interface. A fast Fourier transform-based geometric recognition algorithm is used for docking the reduced representation protein models. The resulting docking algorithm successfully predicted the wild-type homodimer orientations in 65 out of 121 dimer test cases. The success rate increases to approximately 70% for the subset of molecules with large surface area burial in the interface relative to their chain length. Forty-five of the predictions exhibited less than 1 A C(alpha) RMSD compared to the native X-ray structures. The reduced protein representation therefore appears to be a reasonable approximation and can be used to position protein backbones in plausible orientations for homodimer design.
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Affiliation(s)
- Po-Ssu Huang
- Howard Hughes Medical Institute and Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA
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20
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Lee K, Sim J, Lee J. Study of protein-protein interaction using conformational space annealing. Proteins 2005; 60:257-62. [PMID: 15981254 DOI: 10.1002/prot.20567] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We apply conformational space annealing (CSA), an efficient global optimization method, to the study of protein-protein interaction. The CSA is incorporated into the Tinker molecular modeling package along with a B-spline method for CAPRI Round 5 experiments. We have used an energy function for the protein-protein interaction that consists of electrostatic interaction, van der Waals interaction, and solvation energy terms represented by the occupancy desolvation method. The parameters of the AMBER94 all-atom empirical force field are used. Each energy term is calculated by precalculated grid potentials and B-spline method approximation. The ligand protein is placed inside a sphere of 50 A radius centered at an appropriate location, and the CSA rigid docking studies are carried out to find stable complexes. Up to 10 complexes are selected using the K-mean clustering method and biological information when available. These complexes are energy-minimized for further refinement by considering the flexibility of interacting proteins. The results show that the CSA method has a potential for the study of protein-protein interaction.
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Affiliation(s)
- Kyoungrim Lee
- School of Computational Sciences, Korea Institute for Advanced Study, Dongdaemun-gu, Seoul, Korea
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