%0 Journal Article %J The Journal of Steroid Biochemistry and Molecular Biology %D 2010 %T Theoretical study of molecular mechanism of binding TRAP220 coactivator to Retinoid X Receptor alpha, activated by 9-cis retinoic acid %A Mateusz Kurcinski %A Andrzej Koliński %K Binding Sites %K Cell Nucleus %K Cell Nucleus: metabolism %K Computer Simulation %K Crystallography %K Humans %K Ligands %K Mediator Complex Subunit 1 %K Mediator Complex Subunit 1: metabolism %K Models %K Molecular %K Molecular Conformation %K Peptides %K Peptides: chemistry %K Protein Binding %K Protein Structure %K Retinoid X Receptor alpha %K Retinoid X Receptor alpha: metabolism %K Tertiary %K Theoretical %K Tretinoin %K Tretinoin: metabolism %K X-Ray %K X-Ray: methods %X

Study on molecular mechanism of conformational reorientation of RXR-alpha ligand binding domain is presented. We employed CABS–a reduced model of protein dynamics to model folding pathways of binding 9-cis retinoic acid to apo-RXR molecule and TRAP220 peptide fragment to the holo form. Based on obtained results we also propose a sequential model of RXR activation by 9-cis retinoic acid and TRAP220 coactivator. Methodology presented here may be used for investigation of binding pathways of other NR/hormone/cofactor sets.

%B The Journal of Steroid Biochemistry and Molecular Biology %I Elsevier Ltd %V 121 %P 124–9 %8 jul %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2906686&tool=pmcentrez&rendertype=abstract %R 10.1016/j.jsbmb.2010.03.086 %0 Journal Article %J Journal of Molecular Modeling %D 2007 %T Hierarchical modeling of protein interactions %A Mateusz Kurcinski %A Andrzej Koliński %K Algorithms %K Amino Acid Sequence %K Amino Acids %K Amino Acids: analysis %K Carbon %K Carbon: chemistry %K Computer Simulation %K Crystallography %K Hydrogen Bonding %K Models %K Molecular %K Monte Carlo Method %K Peptides %K Peptides: chemistry %K Peptides: metabolism %K Protein Binding %K Protein Conformation %K Protein Structure %K Proteins %K Proteins: chemistry %K Proteins: metabolism %K Secondary %K Stereoisomerism %K Theoretical %K X-Ray %X A novel approach to hierarchical peptide-protein and protein-protein docking is described and evaluated. Modeling procedure starts from a reduced space representation of proteins and peptides. Polypeptide chains are represented by strings of alpha-carbon beads restricted to a fine-mesh cubic lattice. Side chains are represented by up to two centers of interactions, corresponding to beta-carbons and the centers of mass of the remaining portions of the side groups, respectively. Additional pseudoatoms are located in the centers of the virtual bonds connecting consecutive alpha carbons. These pseudoatoms support a model of main-chain hydrogen bonds. Docking starts from a collection of random configurations of modeled molecules. Interacting molecules are flexible; however, higher accuracy models are obtained when the conformational freedom of one (the larger one) of the assembling molecules is limited by a set of weak distance restraints extracted from the experimental (or theoretically predicted) structures. Sampling is done by means of Replica Exchange Monte Carlo method. Afterwards, the set of obtained structures is subject to a hierarchical clustering. Then, the centroids of the resulting clusters are used as scaffolds for the reconstruction of the atomic details. Finally, the all-atom models are energy minimized and scored using classical tools of molecular mechanics. The method is tested on a set of macromolecular assemblies consisting of proteins and peptides. It is demonstrated that the proposed approach to the flexible docking could be successfully applied to prediction of protein-peptide and protein-protein interactions. The obtained models are almost always qualitatively correct, although usually of relatively low (or moderate) resolution. In spite of this limitation, the proposed method opens new possibilities of computational studies of macromolecular recognition and mechanisms of assembly of macromolecular complexes. %B Journal of Molecular Modeling %V 13 %P 691–698 %8 jul %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17297609 %R 10.1007/s00894-007-0177-8 %0 Journal Article %J The Journal of Steroid Biochemistry and Molecular Biology %D 2007 %T Steps towards flexible docking: modeling of three-dimensional structures of the nuclear receptors bound with peptide ligands mimicking co-activators' sequences %A Mateusz Kurcinski %A Andrzej Koliński %K Amino Acid Sequence %K Crystallography %K Cytoplasmic and Nuclear %K Cytoplasmic and Nuclear: chemistry %K Cytoplasmic and Nuclear: metabolism %K Ligands %K Models %K Molecular %K Molecular Mimicry %K Peptides %K Peptides: chemistry %K Peptides: metabolism %K Protein Binding %K Protein Structure %K Quaternary %K Receptors %K X-Ray %X We developed a fully flexible docking method that uses a reduced lattice representation of protein molecules, adapted for modeling peptide-protein complexes. The CABS model (Carbon Alpha, Carbon Beta, Side Group) employed here, incorporates three pseudo-atoms per residue-Calpha, Cbeta and the center of the side group instead of full-atomic protein representation. Force field used by CABS was derived from statistical analysis of non-redundant database of protein structures. Application of our method included modeling of the complexes between various nuclear receptors (NRs) and peptide co-activators, for which three-dimensional structures are known. We tried to rebuild the native state of the complexes, starting from separated components. Accuracy of the best obtained models, calculated as coordinate root-mean-square deviation (cRMSD) between the target and the modeled structures, was under 1A, which is competitive with experimental methods, such as crystallography or NMR. Forthcoming modeling study should lead to better understanding of mechanisms of macromolecular assembly and will explain co-activators' effects on receptors activity, especially on vitamin D receptor and other nuclear receptors. %B The Journal of Steroid Biochemistry and Molecular Biology %V 103 %P 357–60 %8 mar %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17241780 %R 10.1016/j.jsbmb.2006.12.059 %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