References
| Title | Molecular surface recognition: Determination of geometric fit between proteins and their ligands by correlation techniques |
| Authors | Ephraim Katchalski-Katzir, Isaac Shariv, Miriam Eisenstein, Asher A. Friesem, Claude Aflalo, Ilya A. Vakser |
| Location | Departments of Membrane Research & Biophysics, Electronics, Structural Biology and Biochemistry Weizmann Institute of Science Rehovot 76100 Israel |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Volume | 89 |
| Number | 6 |
| Pages | 2195-2199 |
| Abstract | A geometric recognition algorithm was developed to identify molecular surface complementarity. It is based on a purely geometric approach and takes advantage of techniques applied in the field of pattern recognition. The algorithm involves an automated procedure including (i) a digital representation of the molecules (derived from atomic coordinates) by three-dimensional discrete functions that distinguishes between the surface and the interior; (ii) the calculation, using Fourier transformation, of a correlation function that assesses the degree of molecular surface overlap and penetration upon relative shifts of the molecules in three dimensions; and (iii) a scan of the relative orientations of the molecules in three dimensions. The algorithm provides a list of correlation values indicating the extent of geometric match between the surfaces of the molecules; each of these values is associated with six numbers describing the relative position (translation and rotation) of the molecules. The procedure is thus equivalent to a six-dimensional search but much faster by design, and the computation time is only moderately dependent on molecular size. The procedure was tested and validated by using five known complexes for which the correct relative position of the molecules in the respective adducts was successfully predicted. The molecular pairs were deoxyhemoglobin and methemoglobin, tRNA synthetase-tyrosinyl adenylate, aspartic proteinase-peptide inhibitor, and trypsin-trypsin inhibitor. A more realistic test was performed with the last two pairs by using the structures of uncomplexed aspartic proteinase and trypsin inhibitor, respectively. The results are indicative of the extent of conformational changes in the molecules tolerated by the algorithm. |
| Title | Modelling Protein Docking using Shape Complimentarity, Electrostatics and Biochemical Information |
| Authors | Henry A. Gabb, Richard M. Jackson, Michael J. E. Sternberg |
| Location | Biomolecular Modelling Laboratory Imperial Cancer Research Fund Lincoln's Inn Fields P.O. Box 123 London WC2A 3PX United Kingdom |
| Journal | Journal of Molecular Biology |
| Volume | 272 |
| Number | 1 |
| Pages | 106-120 |
| Abstract | A protein docking study was performed for two classes of biomolecular complexes: six enzyme/inhibitor and four antibody/antigen. Biomolecular complexes for which crystal structures of both the complexed and uncomplexed proteins are available were used for eight of the ten test systems. Our docking experiments consist of a global search of translational and rotational space followed by refinement of the best predictions. Potential complexes are scored on the basis of shape complementarity and favourable electrostatic interactions using Fourier correlation theory. Since proteins undergo conformational changes upon binding, the scoring function must be sufficiently soft to dock unbound structures successfully. Some degree of surface overlap is tolerated to account for sidechain flexibility. Similarly for electrostatics, the interaction of the dispersed point charges of one protein with the Coulombic field of the other is measured rather than precise atomic interactions. We tested our docking protocol using the native rather than the complexed forms of the proteins to address the more scientifically interesting problem of predictive docking. In all but one of our test cases, correctly docked geometries (interface C-alpha RMS deviation less than or equal to 2 Angstrom from the experimental structure) are found during a global search of translational and rotational space in a list that was always less than 250 complexes and often less than 30. Varying degrees of biochemical information are still necessary to remove most of the incorrectly docked complexes. (C) 1997 Academic Press Limited. |
| Title | Modelling Protein Docking using Shape Complimentarity, Electrostatics and Biochemical Information |
| Authors | Patrick Aloy, Gidon Moont, Henry A. Gabb, Enrique Querol, Francesc X. Aviles, Michael J. E. Sternberg |
| Location | Biomolecular Modelling Laboratory Imperial Cancer Research Fund Lincoln's Inn Fields P.O. Box 123 London WC2A 3PX United Kingdom |
| Journal | Proteins: Structure, Function, and Genetics |
| Volume | 33 |
| Number | 4 |
| Pages | 535-549 |
| Year | 1998 |
| Abstract | The docking of repressor proteins to DNA starting from the unbound protein and model-built DNA coordinates is modeled computationally. The approach was evaluated on eight repressor/DNA complexes that employed different modes for protein/DNA recognition. The global search is based on a protein-protein docking algorithm that evaluates shape and electrostatic complementarity, which was modified to consider the importance of electrostatic features in DNA- protein recognition. Complexes were then ranked by an empirical score for the observed amino acid/nucleotide pairings (i.e,, protein-DNA pair potentials) derived from a database of 20 protein/DNA complexes. A good prediction had at least 65% of the correct contacts modeled. This approach was able to identify a good solution at rank four or better for three out of the eight complexes. Predicted complexes were filtered by a distance constraint based on experimental data defining the DNA footprint. This improved coverage to four out of eight complexes having a good model at rank four or better. The additional use of amino acid mutagenesis and phylogenetic data defining residues on the repressor resulted in between 2 and 27 models that would have to be examined to find a good solution for seven of the eight test systems. This study shows that starting with unbound coordinates one can predict three dimensional models for protein/DNA complexes that do not involve gross conformational changes on association. (C) 1998 Wiley-liss, Inc. |
| Title | Use of Pair Potentials Across Protein Interfaces in Screening Predicted Docked Complexes |
| Authors | Gidon Moont, Henry A. Gabb, Michael J. E. Sternberg |
| Location | Biomolecular Modelling Laboratory Imperial Cancer Research Fund Lincoln's Inn Fields P.O. Box 123 London WC2A 3PX United Kingdom |
| Journal | Proteins: Structure, Function, and Genetics |
| Volume | 35 |
| Number | 3 |
| Pages | 364-373 |
| Year | 1999 |
| Abstract | Empirical residue-residue pair potentials are used to screen possible complexes for protein-protein dockings. A correct docking is defined as a complex with not more than 2.5 Angstrom root-mean-square distance from the known experimental structure. The complexes were generated by ''ftdock'' (Gabb et al. J Mol Biol 1997;272:106-120) that ranks using shape complementarity. The complexes studied were 5 enzyme-inhibitors and 2 antibody-antigens, starting from the unbound crystallographic coordinates, with a further 2 antibody-antigens where the antibody was from the bound crystallographic complex. The pair potential functions tested were derived both from observed intramolecular pairings in a database of nonhomologous protein domains, and from observed intermolecular pairings across the interfaces in sets of nonhomologous heterodimers and homodimers. Out of various alternate strategies, we found the optimal method used a mole-fraction calculated random model from the intramolecular pairings. For all the systems, a correct docking was placed within the top 12% of the pair potential score ranked complexes. A combined strategy was developed that incorporated ''multidock,'' a side-chain refinement algorithm (Jackson et al. J Mol Biol 1998;276:265-285). This placed a correct docking within the top 5 complexes for enzyme-inhibitor systems, and within the top 40 complexes for antibody- antigen systems. (C) 1999 Wiley-Liss, Inc. |
| Title | Evaluation of the CASP2 Docking Section |
| Authors | J. Scott Dixon |
| Location | SmithKline Beecham Pharmaceutical R&D King of Prussia Pennsylvania U.S.A. |
| Journal | Proteins: Structure, Function, and Genetics |
| Volume | Supplement 1 |
| Pages | 198-204 |
| Year | 1997 |
| Abstract | The docking section of CASP2 is reviewed. Seven small molecule ligand-protein targets and one protein-protein target were available for predictions, Many of the small molecule ligand complexes involved serine proteases. Overall results for the small molecule targets were good, with at least one prediction for each target being within 3 Angstrom root-mean-square deviation (RMSD) for nearly all targets and within 2 Angstrom RMSD for over half the targets, However no single docking method seemed to consistently perform best, In addition, the predictions closest to tile experimental results were not always those ranked the highest, pointing out that the evaluation (scoring) of potential solutions is still an area Chef, needs improvement, The protein-protein target proved more difficult, None of the predictions did well in reproducing the geometry of the complex, although in many cases the interacting surfaces of the two proteins were predicted with reasonable accuracy. This target consisted of two large proteins and, therefore was a demanding target for docking methods. (C) 1998 Wiley-Liss, Inc. |
| Title | Rapid refinement of protein interfaces incorporating solvation: application to the docking problem |
| Authors | Richard M. Jackson, Henry A. Gabb, Michael J. E. Sternberg |
| Location | Biomolecular Modelling Laboratory Imperial Cancer Research Fund Lincoln's Inn Fields P.O. Box 123 London WC2A 3PX United Kingdom |
| Journal | Journal of Molecular Biology |
| Volume | 276 |
| Number | 1 |
| Pages | 265-285 |
| Year | 1998 |
| Abstract | A computationally tractable strategy has been developed to refine protein-protein interfaces that models the effects of side-chain conformational change, solvation and limited rigid-body movement of the subunits. The proteins are described at the atomic level by a multiple copy representation of side-chains modelled according to a rotamer library on a fixed peptide backbone. The surrounding solvent environment is described by "soft" sphere Langevin dipoles for water that interact with the protein via electrostatic, van der Waals and field-dependent hydrophobic terms. Energy refinement is based on a two-step process in which (1) a probability-based conformational matrix of the protein side-chains is refined iteratively by a mean field method. A side-chain interacts with the protein backbone and the probability-weighted average of the surrounding protein side-chains and solvent molecules. The resultant protein conformations then undergo (2) rigid-body energy minimization to relax the protein interface. Steps (1) and (2) are repeated until convergence of the interaction energy. The influence of refinement on side-chain conformation starting from unbound conformations found improvement in the RMSD of side-chains in the interface of protease-inhibitor complexes, and shows that the method leads to an improvement in interface geometry. In terms of discriminating between docked structures, the refinement was applied to two classes of protein-protein complex: five protease-protein inhibitor and four antibody-antigen complexes. A large number of putative docked complexes have already been generated for the test systems using our rigid-body docking program, FTDOCK. They include geometries that closely resemble the crystal complex, and therefore act as a test for the refinement procedure. In the protease-inhibitors, geometries that resemble the crystal complex are ranked in the top four solutions for four out of five systems when solvation is included in the energy function, against a background of between 26 and 364 complexes in the data set. The results for the antibody-antigen complexes are not as encouraging, with only two of the four systems showing discrimination. It would appear that these results reflect the somewhat different binding mechanism dominant in the two types of protein-protein complex. Binding in the protease-inhibitors appears to be "lock and key" in nature. The fixed backbone and mobile side-chain representation provide a good model for binding. Movements in the backbone geometry of antigens on binding represent an "induced-fit" and provides more of a challenge for the model. Given the limitations of the conformational sampling, the ability of the energy function to discriminate between native and non-native states is encouraging. Development of the approach to include greater conformational sampling could lead to a more general solution to the protein docking problem. Copyright 1998 Academic Press |
| Title | Application of a Self-consistent Mean Field Theory to Predict Protein Side-chains Conformation and Estimate Their Conformational Entropy |
| Authors | Patrice Koehl and Marc Delarue |
| Location | UPR Cancérogénèse et Mutagénèse Moléculaire et Structurale du CNRS 15 rue Descartes 67084 Strasbourg Cedex France and UPR de Biologie Structurale du CNRS 15 rue Descartes 67084 Strasbourg Cedex France |
| Journal | Journal of Molecular Biology |
| Volume | 239 |
| Number | 2 |
| Pages | 249-275 |
| Year | 1994 |
| Abstract | Understanding the relations between the conformation of the side-chains and the backbone geometry is crucial for structure prediction as well as for homology modelling. To attempt to unravel these rules, we have developed a method which allows us to predict the position of the side-chains from the co-ordinates of the main-chain atoms. This method is based on a rotamer library and refines iteratively a conformational matrix of the side-chains of a protein, CM, such that its current element at each cycle CM (ij) gives the probability that side-chain i of the protein adopts the conformation of its possible rotamer j. Each residue feels the average of all possible environments, weighted by their respective probabilities. The method converges in only a few cycles, thereby deserving the name of self consistent mean field method. Using the rotamer with the highest probability in the optimized conformational matrix to define the conformation of the side-chain leads to the result that on average 72% of 1 75% of 2 and 62% of 1+2 are correctly predicted for a set of 30 proteins. Tests with six pairs of homologous proteins have shown that the method is quite successful even when the protein backbone deviates from the correct conformation. The second application of the optimized conformational matrix was to provide estimates of the conformational entropy of the side-chains in the folded state of the protein. The relevance of this entropy is discussed. Copyright 1994, 1999 Academic Press |