TY - JOUR T1 - A new approach to prediction of short-range conformational propensities in proteins JF - Bioinformatics (Oxford, England) Y1 - 2005 A1 - Dominik Gront A1 - Andrzej KoliƄski KW - Algorithms KW - Amino Acid KW - Artificial Intelligence KW - Chemical KW - Computer Simulation KW - Databases KW - Gas Chromatography-Mass Spectrometry KW - Gas Chromatography-Mass Spectrometry: methods KW - Models KW - Protein KW - Protein Conformation KW - Protein: methods KW - Proteins KW - Proteins: analysis KW - Proteins: chemistry KW - Sequence Alignment KW - Sequence Alignment: methods KW - Sequence Analysis KW - Sequence Homology KW - Structure-Activity Relationship AB -

MOTIVATION: Knowledge-based potentials are valuable tools for protein structure modeling and evaluation of the quality of the structure prediction obtained by a variety of methods. Potentials of such type could be significantly enhanced by a proper exploitation of the evolutionary information encoded in related protein sequences. The new potentials could be valuable components of threading algorithms, ab-initio protein structure prediction, comparative modeling and structure modeling based on fragmentary experimental data. RESULTS: A new potential for scoring local protein geometry is designed and evaluated. The approach is based on the similarity of short protein fragments measured by an alignment of their sequence profiles. Sequence specificity of the resulting energy function has been compared with the specificity of simpler potentials using gapless threading and the ability to predict specific geometry of protein fragments. Significant improvement in threading sensitivity and in the ability to generate sequence-specific protein-like conformations has been achieved.

VL - 21 UR - http://www.ncbi.nlm.nih.gov/pubmed/15509604 ER -