Ab initio protein folding simulations with genetic algorithms: Simulations on the complete sequence of small proteins

Ab‐initio folding simulations have been performed on three small proteins using a genetic algorithm‐ (GA‐) based search method which operates on an all atom representation. Simulations were also performed on a number of small peptides expected to be inde pendent folding units. The present genetic algorithm incorporates the results of developments made to the method first tested in CASP1. Additional operators have been introduced into the search in order to allow the simulation of longer sequences and to avoid premature free energy convergence. Secondary structure information derived from a consensus of eight methods and Monte Carlo simulations on sets of homologous sequences has been used to bias the starting populations used in the GA simulations. For the fragment simulations, the results generally have approximately correct local structure, but tend to be too compact, leading to poor RMS error values. One of the three small protein structures has the topology and most of the general organization correct, although many of the details are incorrect. Proteins, Suppl. 1:179–184, 1997. © 1998 Wiley‐Liss, Inc.

[1]  Barry Robson,et al.  An algorithm for secondary structure determination in proteins based on sequence similarity , 1986, FEBS letters.

[2]  K. Nishikawa,et al.  Trifluoroethanol-induced Stabilization of the α-Helical Structure of β-Lactoglobulin: Implication for Non-hierarchical Protein Folding , 1995 .

[3]  T. Tanaka,et al.  High helical propensity of the peptide fragments derived from beta-lactoglobulin, a predominantly beta-sheet protein. , 1995, Journal of molecular biology.

[4]  R Langridge,et al.  Improvements in protein secondary structure prediction by an enhanced neural network. , 1990, Journal of molecular biology.

[5]  J Moult,et al.  An analysis of protein folding pathways. , 1991, Biochemistry.

[6]  G Deléage,et al.  An algorithm for protein secondary structure prediction based on class prediction. , 1987, Protein engineering.

[7]  W. Kabsch,et al.  Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.

[8]  J. Moult,et al.  Determination of the conformation of folding initiation sites in proteins by computer simulation , 1995, Proteins.

[9]  B. Rost,et al.  Prediction of protein secondary structure at better than 70% accuracy. , 1993, Journal of molecular biology.

[10]  P. K. Mehta,et al.  A simple and fast approach to prediction of protein secondary structure from multiply aligned sequences with accuracy above 70% , 1995, Protein science : a publication of the Protein Society.

[11]  A A Salamov,et al.  Prediction of protein secondary structure by combining nearest-neighbor algorithms and multiple sequence alignments. , 1995, Journal of molecular biology.

[12]  S. Wodak,et al.  Prediction of protein backbone conformation based on seven structure assignments. Influence of local interactions. , 1991, Journal of molecular biology.

[13]  J Moult,et al.  Role of electrostatic screening in determining protein main chain conformational preferences. , 1995, Biochemistry.

[14]  J Moult,et al.  Protein folding simulations with genetic algorithms and a detailed molecular description. , 1997, Journal of molecular biology.

[15]  F. Avbelj,et al.  Use of a potential of mean force to analyze free energy contributions in protein folding. , 1992, Biochemistry.

[16]  Christophe Geourjon,et al.  SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments , 1995, Comput. Appl. Biosci..

[17]  G. Otting,et al.  Pathway of chymotrypsin evolution suggested by the structure of the FMN-binding protein from Desulfovibrio vulgaris (Miyazaki F) , 1997, Nature Structural Biology.

[18]  J. Moult,et al.  Ab initio structure prediction for small polypeptides and protein fragments using genetic algorithms , 1995, Proteins.

[19]  Gottfried Otting,et al.  Saposin fold revealed by the NMR structure of NK-lysin , 1997, Nature Structural Biology.