ABSTRACT
Rigid body docking approaches are not sufficient to predict the structure of a protein complex from the unbound (native) structures of the two proteins. Accounting for side—chain flexibility is an important step towards fully flexible protein docking. This work describes an approach that allows conformational flexibility for the side—chains while keeping the protein backbone rigid. Starting from candidates created by a rigid docking algorithm, we demangle the side—chains of the docking site, thus creating reasonable approximations of the true complex structure. These structures are ranked with respect to the binding free energy. We present two new techniques for side—chain demangling. Both approaches are based on a discrete representation of the side—chain conformational space by the use of a rotamer library. This leads to a combinatorial optimization problem. For the solution of this problem we propose a fast heuristic approach and an exact, albeit slower method using branch—&—cut techniques. As a test set we use the unbound structures of three proteases and the corresponding protein inhibitors. For each of the examples the highest—ranking conformation produced was a good approximation of the true complex structure.
- 1.R Abagyan and M. Totrov. Biased probability Monte Carlo conformatlonal searches and electrostatic calculations for pept~des and proteins. J. Mol. Bsol., 235:983- 1002, 1994.]]Google ScholarCross Ref
- 2.F Ackermann, G. Herrmann, F Kummert, S. Posch, G. Sagerer, and D. Schomburg Protein docking combining symbolic descriptions of molecular surfaces and gridbased scoring functions. In Proceedings of the Third International Conference on Intelhgent Systems m Molecular Bzology, pages 3-11, Menlo Park, California, 1995. AAAI Press.]]Google Scholar
- 3.E. Althaus, O. Kohlbacher, H.-P. Lenhof, and P. Mfiller. A branch-&-cut algorithm for the optimal solution of the side-chain placement problem. Techmcal Report MPI-I-2000-1-001, Max-Planck-Institut fiir Informatik, Saarbrficken, Jan. 2000]]Google Scholar
- 4.D. J. Bacon and J. Moult. Docking by least-squares fitting of molecular surface patterns. J. Mol. B~ol., 225:849-858, 1992.]]Google ScholarCross Ref
- 5.F Bernstein, T Koetzle, G. Wfiliams, E. Meyer Jr, M. Brice, J. Rodgers, O Kennard, T. Shimanouchi, and M. Tasumi. The prote~n data bank: a computerbased archival file for macromolecular structures. J. Mol. Bwl., 112.535, 1977]]Google Scholar
- 6.N. Boghossian, O. Kohlbacher, and H-P. Lenhof. BALL: Biochemical Algorithms Library. In J Vitter and C. Zaroliagls, editors, Algorithm Engineermg, 3rd Internatmnal Workshop, WAE'99, Proceedings, volume 1668 of Lecture Notes m Computer Science (LNCS), pages 330-344. Springer, 1999.]] Google ScholarDigital Library
- 7.R. E. Bruccoleri and J. Novotny. Antibody modehng using the conformational search program CONGEN Immunomethods, 1:96-1{16, 1992.]]Google Scholar
- 8.J. Cherfils, S. Duquerroy, and J. 3amn. Protein-protein recogmtion analysis by docking simulation Proteins, 11.271-280, 1991]]Google Scholar
- 9.M L. Connolly. Shape complementarity at the hemoglobin alfil subumt interface. Btopolymers, 25:1229-1247, 1986.]]Google ScholarCross Ref
- 10.W D. Cornell, P. Cieplak, C. I. Bayly, I. R. Gould, K. M. Merz Jr., D. M Ferguson, D. C. Spellmeyer, T Fox, J. W. Caldwell, and P. A. Kollman. A second generation force field for the simulation of proteins, nucleic acids and organic molecules. J. Am. Chem. Soc., 117:5179-5197, 1995.]]Google ScholarCross Ref
- 11.J. Desmet, M. D. Maeyer, B Hazes, and I. Lasters. The dead-end ehminatJon theorem and its use in the protein rode-chain positioning. Nature, 356:539-542, April 1992.]]Google ScholarCross Ref
- 12.R L. Dunbrack and F E. Cohen. Bayesian statistical analysis of protein s~de-cham retainer preferences. Protern Science, 6'1661-1681, 1997]]Google Scholar
- 13.D. Fmcher, S L Lin, H J Wolfson, and R Nuss~nov A geometry-based suite of molecular docking processes J. Mol. Bzol., 248'459-477, 1995.]]Google Scholar
- 14.M. Helmer-Citterich and A. Tramontano. PUZZLE: a new method for automated protein docking based on surface shape complementarity. J. Mol. Biol., 235.1021- 1031, 1994.]]Google Scholar
- 15.L. Holm and C. Sander. Fast and simple monte carlo algorithm for side-chain optimization in proteins: application to model building by homology. Proteins, 14.213- 223, 1992.]]Google Scholar
- 16.ILOG. ILOG CPLEX 6.5: user's manual. ILOG, Bad Homburg, march 1999 edition, 1999.]]Google Scholar
- 17.R. M. Jackson, H. A Gabb, and M. J. E. Sternberg Rapid refinement of protein interfaces incorporating sok vation: Application to the protein docking problem d. Mol. B, ol., 276.265-285, 1998.]]Google Scholar
- 18.R. M. Jackson and M. J. E. Sternberg. A continuum model for protein-protein interactions: Applicatmn to the protein docking problem. J. Mol. Biol., 25(!:258- 275, 1995.]]Google Scholar
- 19.F. Jiang and S. H, Kim. Soft docking: matching of molecular surface cubes Y. Mol. Bsol., 219 79-102, 1991.]]Google ScholarCross Ref
- 20.M. Jiinger and S Thienel. introduction to ABACUS - A branch-and-CUt system. Technical report, Informat~k, Universit~it zu KSln, 1997.]]Google Scholar
- 21.E. Katchalski-Katzir, I Shariv, M. Eisenstein, A A Friesem, C. Afalo, and I. A. Vakser. Molecular surface recognition: Determination of geometric fit between proteins and their ligands by correlation techniques. Prec. Natl. Acid. Sci. USA~ 89:2195-2199, 1992]]Google ScholarCross Ref
- 22.P. Koehl and M. Delarue. Application of a selfconsistent mean field theory to predict prote~n sidechains conformation and estimate their conformational entropy. J. Mol. Biol, 239:249-275, 1994.]]Google ScholarCross Ref
- 23.O. Kohlbacher and H.-P. Lenhof Rapid software prototyping tn computational molecular biology. In Proce~dmgs of the German Conference on B~oinformat~cs (GCB'99), 1999.]]Google Scholar
- 24.C. A. Laughton. Predlction of protein side-chain conformations from local three-dimensional homology relationships. S. Mol. B~of., 235:1fi88~1097, 1994.]]Google Scholar
- 25.A. R. Leach Ligand docking to proteins w~th discrete side-chain flexibfiity. J. }Viol. BioL, 235:345-356, 1994.]]Google Scholar
- 26.A R. Leach and A P. Lemon. Exploring the confermatlonal space of protein side chains using dead-end ehmmation and the a* algorithm. Proteins: Struct., Fhnctzon, and Genet., 33:227-239, 1998.]]Google Scholar
- 27.H-P. Lenhof An algorithm for the protein docking problem. In D. Schomburg and U. Lessel, editors, BzomJormat~cs: From nucle,c acids and proteins to cell metabohsm. GBF Monographs Volume 18, pages 125- 139, 1995.]]Google Scholar
- 28.H.-P Lenhof. New contact measores for the protein docking problem. In Proc. of the F, rst Ann~al Internatwnal Conference on Computational Molecular Bwlogy RECOMB 97, pages 182-191, 1.997.]] Google ScholarDigital Library
- 29.K Mehlhorn, S. Naher, M Seel, and C. Uhrig The LEDA user manual.' version 3.8. Max-Planck-lnstitut fiJr {nformatlk, Saarbriicken, 1999]]Google Scholar
- 30.M. Meyer, P Wilson, and D. Schomburg. Hydrogen bonding and molecular surface shape complementarity a~s a basts for protein docking. J. Mol. Biol., 264(1) 199- 210, 1996.]]Google ScholarCross Ref
- 31.J. Moon and W. Howe Computer design of bioactlve molecules A method for receptor-based de nov<) hgand design Proteins; Struct Funct. Genetics, 11 314-328, 1991]]Google ScholarCross Ref
- 32.R. Norel, S. L. Lin, D. Xu, H. J. Wolfson, and R Nussinov Molecular surface variability and induced conformational changes upon protein-protein association In R H. Sarma and M. H. Saxma, editors, Structure, Motion, lnterac~mon and Expresswn of Biological Macromolecules. Proceedings of the Tenth Conversatwn. State Unzversity of New York, pages 33-51. Adenine Press, 1998.]]Google Scholar
- 33.J. Ponder and F. Richards. Tertiary templates for proterns - use of packing criteria in the enumeration of allowed sequences for different structural classes J. Mol. B~ol., 193.775-791, 1987.]]Google Scholar
- 34.M. Rarey, B. Kramer, T. Lengauer, and G. K!ebe. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol., 261:470-489~ 1997.]]Google ScholarCross Ref
- 35.B. K Shomhet and I. D. Kuntz. Protein docking and complementarity. J. Mot. Biol., 221:79-102, 1991.]]Google Scholar
- 36.D Sitkoff, K A. Sharp, and B. Honig. Accurate calculation of hydration free energies using macroscopic solvent models. J. Phys. Chem., 98(7):1978-1988, 1994.]]Google ScholarCross Ref
- 37.M Totrov and R. Abagyan. Detailed ab initio prediction of lysozyme-antlbody complex with 1.6 ~ accuracy. Nat. Struct. Bsol., 1:259-263, 1994.]]Google ScholarCross Ref
- 38.P. H. I Walls and M. J. E. Sternberg. New algorithm to model protein-protein recognition based on surface complementarity. J. Mo/. Biol., 228:277-297, 1992.]]Google Scholar
- 39.Z. Weng, S Vajda, and C. Delisi. Prediction of protein complexes using empirical free energy functions. Protein Scsence, 5'614-626, 1996.]]Google Scholar
- 40.L A. Wolsey. Integer programming. Wiley-interscience serms m discrete mathematics and optimization. Wiley g~ Sons, New York, 1998.]]Google Scholar
- 41.R. Wunderling. Paralleler und Objektortentierter Simplex-A!gorithmus. Technical report, Konrad-Zuse- Zentrum fiir Informationstechnik Berlin, 1997.]]Google Scholar
- A combinatorial approach to protein docking with flexible side-chains
Recommendations
Spatial clustering of protein binding sites for template based protein docking
Motivation: In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or ...
Application of asymmetric statistical potentials to antibody–protein docking
Motivation: An effective docking algorithm for antibody–protein antigen complex prediction is an important first step toward design of biologics and vaccines. We have recently developed a new class of knowledge-based interaction potentials called ...
Comments