%0 Journal Article %J Acta Biochimica Polonica %D 2004 %T Protein modeling and structure prediction with a reduced representation %A Andrzej Koliński %K Amino Acid Sequence %K Animals %K Carbon %K Carbon: chemistry %K Crystallography %K Databases as Topic %K Humans %K Hydrogen Bonding %K Mathematics %K Models %K Molecular %K Molecular Sequence Data %K Protein Conformation %K Protein Structure %K Proteins %K Proteins: chemistry %K Proteomics %K Proteomics: methods %K Tertiary %K Theoretical %K X-Ray %X

Protein modeling could be done on various levels of structural details, from simplified lattice or continuous representations, through high resolution reduced models, employing the united atom representation, to all-atom models of the molecular mechanics. Here I describe a new high resolution reduced model, its force field and applications in the structural proteomics. The model uses a lattice representation with 800 possible orientations of the virtual alpha carbon-alpha carbon bonds. The sampling scheme of the conformational space employs the Replica Exchange Monte Carlo method. Knowledge-based potentials of the force field include: generic protein-like conformational biases, statistical potentials for the short-range conformational propensities, a model of the main chain hydrogen bonds and context-dependent statistical potentials describing the side group interactions. The model is more accurate than the previously designed lattice models and in many applications it is complementary and competitive in respect to the all-atom techniques. The test applications include: the ab initio structure prediction, multitemplate comparative modeling and structure prediction based on sparse experimental data. Especially, the new approach to comparative modeling could be a valuable tool of the structural proteomics. It is shown that the new approach goes beyond the range of applicability of the traditional methods of the protein comparative modeling.

%B Acta Biochimica Polonica %V 51 %P 349–71 %8 jan %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/15218533 %R 035001349 %0 Journal Article %J Protein Science: a Publication of the Protein Society %D 1995 %T Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets %A Adam Godzik %A Andrzej Koliński %A Jeffrey Skolnick %K Amino Acid Sequence %K Amino Acids %K Crystallography %K Databases %K Factual %K Magnetic Resonance Spectroscopy %K Mathematics %K Models %K Protein Conformation %K Protein Folding %K Proteins %K Proteins: chemistry %K Theoretical %K Thermodynamics %K X-Ray %X Various existing derivations of the effective potentials of mean force for the two-body interactions between amino acid side chains in proteins are reviewed and compared to each other. The differences between different parameter sets can be traced to the reference state used to define the zero of energy. Depending on the reference state, the transfer free energy or other pseudo-one-body contributions can be present to various extents in two-body parameter sets. It is, however, possible to compare various derivations directly by concentrating on the "excess" energy-a term that describes the difference between a real protein and an ideal solution of amino acids. Furthermore, the number of protein structures available for analysis allows one to check the consistency of the derivation and the errors by comparing parameters derived from various subsets of the whole database. It is shown that pair interaction preferences are very consistent throughout the database. Independently derived parameter sets have correlation coefficients on the order of 0.8, with the mean difference between equivalent entries of 0.1 kT. Also, the low-quality (low resolution, little or no refinement) structures show similar regularities. There are, however, large differences between interaction parameters derived on the basis of crystallographic structures and structures obtained by the NMR refinement. The origin of the latter difference is not yet understood. %B Protein Science: a Publication of the Protein Society %V 4 %P 2107–2117 %8 oct %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2142984&tool=pmcentrez&rendertype=abstract %R 10.1002/pro.5560041016