A distance and orientation dependent potential energy function with cluster energy

Although there have been many potential energy functions to evaluate protein structures, it is still a major challenge to develop an effective energy function. Most potential energy functions do not distinguish a pair of interacting residues in the densely packed environment from the loosely packed environment. We have developed a block pair-specific function that is both distance and orientation dependent. Instead of using the entire side-chain to represent the residue, our function is built on one or two key blocks of each side chain. We show that the probability for seeing low-energy pairs in the highly packed clusters is not the same as that in the entire protein structure for certain pairs. We introduced a cluster energy term in the potential function to represent such difference. In a test of 5 decoy sets, our cluster-energy-adjusted function using key blocks (CEAKB) appears to perform comparably as OPUS-PSP in three decoy sets in spite of its reduced representation of the side chain blocks. CEAKB has better recognition of the native structures in the other two sets of decoys.

[1]  R Samudrala,et al.  Decoys ‘R’ Us: A database of incorrect conformations to improve protein structure prediction , 2000, Protein science : a publication of the Protein Society.

[2]  Guoli Wang,et al.  PISCES: a protein sequence culling server , 2003, Bioinform..

[3]  H. Scheraga,et al.  Packing helices in proteins by global optimization of a potential energy function , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Arnab Mukherjee,et al.  Orientation-dependent potential of mean force for protein folding. , 2005, The Journal of chemical physics.

[5]  R. Jernigan,et al.  Residue-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading. , 1996, Journal of molecular biology.

[6]  A. Sali,et al.  Comparative protein structure modeling by iterative alignment, model building and model assessment. , 2003, Nucleic acids research.

[7]  R. Jernigan,et al.  Inter-residue potentials in globular proteins and the dominance of highly specific hydrophilic interactions at close separation. , 1997, Journal of molecular biology.

[8]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[9]  M J Sippl,et al.  Knowledge-based potentials for proteins. , 1995, Current opinion in structural biology.

[10]  Jianpeng Ma,et al.  OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing. , 2008, Journal of molecular biology.

[11]  David Baker,et al.  Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction. , 2004, Journal of molecular biology.

[12]  Robert L Jernigan,et al.  How effective for fold recognition is a potential of mean force that includes relative orientations between contacting residues in proteins? , 2005, The Journal of chemical physics.

[13]  Jing He,et al.  Native secondary structure topology has near minimum contact energy among all possible geometrically constrained topologies , 2009, Proteins.