A solvation potential with improved contact definitions and optimized by extensive threading
Year: 1999
Type: conference-paper
Abstract: Protein structural knowledge is essential to understanding the molecular basis of disease.Drug design and discovery are facilitated by understanding the three dimensional shape of relevant proteins, as will be future modes of disease intervention such as gene therapy.While identification of disease related protein sequences has dramatically increased through genome mapping efforts, the rate of determination of the associated structures remains relatively slow.Despite recent advancements, experimental methods of protein structure determination remain time consuming and labor intensive.Therefore, computational methods which can predict the correct protein structure for a given amino acid sequence would be a tremendous aid in biomedical research.Homology modeling is precluded if the sequence of interest has low similarity to proteins of known structure.For these sequences, structure prediction requires an energy potential which can identify the native structure out of any number of alternative conformations.We have developed a solvation energy potential which is optimized to identify the native structure as the lowest in energy.The potential has few adjustable parameters which are "trained" so the Protein Data Bank (PDB) structure for each protein in a training set is the lowest in energy when compared to a very large set of alternatives -over lo5 alternatives on average.Intramolecular contact definitions are obtained for all possible amino acid pairs from a survey of protein structures and are continuous as a function of interresidue distance.Training with only 25 native proteins produces an energy potential which is quite successful in structure identification tests.Small proteins and those with prosthetic groups pose the greatest challenge.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies arc not made or tlistrihuted for prolit or commercial advantage ;1nJ that copies bear this ntoticc and the full citation on the first page.I'0 copy othrrwise.to rcpuhlish.to post on servers or to redistribute to lists.requires prior specific permission and~or a fee.
Authors: Alan A. Dombkowski, Gordon M. Crippen
Institution: University of Michigan
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: bronze
Funder: National Institutes of Health
OpenAlex ID: W2006527675