Abstract
This article describes the application of genetic algorithms to the problem of protein tertiary structure prediction. The genetic algorithm is used to search a set of energetically sub-optimal conformations. A hybrid representation of proteins, three operators MUTATE, SELECT and CROSSOVER and a fitness function, that consists of a simple force field were used. The prototype was applied to the ab initio prediction of Crambin. None of the conformations generated by the genetic algorithm are similar to the native conformation, but all show much lower energy than the native structure on the same force field. This means the genetic algorithm's search was successful but the fitness function was not a good indicator for native structure. In another experiment, the backbone was held constant in the native state and only side chains were allowed to move. For Crambin, this produced an alignment of 1.86 Å r.m.s. from the native structure.
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F. C. Bernstein, T. F. Koetzle, G. J. B. Williams, E. F. Meyer Jr., M. D. Brice, J. R. Rodgers, O. Kennard, T. Shimanouchi, M. Tasumi, The Protein Data Bank: A Computer-based Archival File for Macromolecular Structures, Journal of Molecular Biology. 112, pp. 535–542, 1977
C. Branden, J. Tooze, Introduction to Protein Structure, Garland Publishing New York, 1991
B. R. Brooks, R. E. Bruccoleri, B. D. Olafson, D. J. States, S. Swaminathan, M. Karplus, Charmm: A program for Macromolecular Energy, Minimization and Dynamics Calculations, J. Comp. Chem., vol 4, no 2, pp. 187–217, 1983
L. Davis, (ed.) Handbook of Genetic Algorithms, New York, 1991
W. F. Gunsteren, H. J. C. Berendsen, Computer Simulation of Molecular Dynamics: Methodology, Applications and Perspectives in Chemistry, Angew. Chem. Int. Ed. Engl. vol 29, pp. 992–1023, 1990
W. A. Hendrickson, M. M. Teeter, Structure of the Hydrophobic Protein Crambin Determined directly from the Anomalous Scattering of Sulphur, Nature, vol 290, pp. 107, 1981
J. H. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, 1975
S. M. Le Grand, K. M. Merz, The Application of the Genetic Algorithm to the Minimization of Potential Energy Functions, submitted to The Journal of Global Optimization. 1991
C. Lee, S. Subbiah, Prediction of protein side chain conformation by packing optimization, J. Mol. Biol. no 217, pp. 373–388, 1991
A. M. Lesk, Protein Architecture — A Practical Approach, IRL Press, 1991
C. B. Lucasius, G. Kateman, Application of Genetic Algorithms to Chemometrics, Proceedings 3rd International Conference on Genetic Algorithms. George Mason University, 1989
G. E. Schulz, R. H. Schirmer, Principles of Protein Structure, Springer Verlag, 1979
P. Tuffery, C. Etchebest, S. Hazout, R. Lavery, A new approach to the rapid determination of protein side chain conformations, J. Biomol. Struct. Dvn., vol 8, no 6, pp. 1267–1289, 1991
J. G. Vinter, A. Davis, M. R. Saunders, Strategic approaches to drug design. An integrated software framework for molecular modelling, J. Comput.-Aided Mol. Des., no 1, pp. 31–51, 1987
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© 1993 Springer-Verlag Berlin Heidelberg
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Schulze-Kremer, S. (1993). Genetic algorithms for protein tertiary structure prediction. In: Brazdil, P.B. (eds) Machine Learning: ECML-93. ECML 1993. Lecture Notes in Computer Science, vol 667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56602-3_141
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DOI: https://doi.org/10.1007/3-540-56602-3_141
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