%0 Journal Article %J Journal of Computer-Aided Molecular Design %D 2008 %T Fast and accurate methods for predicting short-range constraints in protein models %A Dominik Gront %A Andrzej Koliński %K Algorithms %K Amino Acid Sequence %K Models %K Molecular %K Molecular Sequence Data %K Predictive Value of Tests %K Protein %K Proteins %K Proteins: chemistry %K Proteins: genetics %K Proteins: metabolism %K Sequence Analysis %K Software %X

Protein modeling tools utilize many kinds of structural information that may be predicted from amino acid sequence of a target protein or obtained from experiments. Such data provide geometrical constraints in a modeling process. The main aim is to generate the best possible consensus structure. The quality of models strictly depends on the imposed conditions. In this work we present an algorithm, which predicts short-range distances between Calpha atoms as well as a set of short structural fragments that possibly share structural similarity with a query sequence. The only input of the method is a query sequence profile. The algorithm searches for short protein fragments with high sequence similarity. As a result a statistics of distances observed in the similar fragments is returned. The method can be used also as a scoring function or a short-range knowledge-based potential based on the computed statistics.

%B Journal of Computer-Aided Molecular Design %V 22 %P 783–8 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/18415023 %R 10.1007/s10822-008-9213-8 %0 Journal Article %J Proceedings of the National Academy of Sciences of the United States of America %D 2007 %T Characterization of protein-folding pathways by reduced-space modeling %A Sebastian Kmiecik %A Andrzej Koliński %K Amino Acid Sequence %K coarse-grained modeling %K Computational Biology %K Computer Simulation %K Hydrophobic and Hydrophilic Interactions %K Models %K Molecular %K Molecular Dynamics Simulation %K Monte Carlo Method %K Protein Denaturation %K protein dynamics %K Protein Folding %K Protein Structure %K Proteins %K Proteins: chemistry %K Proteins: metabolism %K Temperature %K Tertiary %X Ab initio simulations of the folding pathways are currently limited to very small proteins. For larger proteins, some approximations or simplifications in protein models need to be introduced. Protein folding and unfolding are among the basic processes in the cell and are very difficult to characterize in detail by experiment or simulation. Chymotrypsin inhibitor 2 (CI2) and barnase are probably the best characterized experimentally in this respect. For these model systems, initial folding stages were simulated by using CA-CB-side chain (CABS), a reduced-space protein-modeling tool. CABS employs knowledge-based potentials that proved to be very successful in protein structure prediction. With the use of isothermal Monte Carlo (MC) dynamics, initiation sites with a residual structure and weak tertiary interactions were identified. Such structures are essential for the initiation of the folding process through a sequential reduction of the protein conformational space, overcoming the Levinthal paradox in this manner. Furthermore, nucleation sites that initiate a tertiary interactions network were located. The MC simulations correspond perfectly to the results of experimental and theoretical research and bring insights into CI2 folding mechanism: unambiguous sequence of folding events was reported as well as cooperative substructures compatible with those obtained in recent molecular dynamics unfolding studies. The correspondence between the simulation and experiment shows that knowledge-based potentials are not only useful in protein structure predictions but are also capable of reproducing the folding pathways. Thus, the results of this work significantly extend the applicability range of reduced models in the theoretical study of proteins. %B Proceedings of the National Academy of Sciences of the United States of America %V 104 %P 12330–5 %8 jul %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1941469&tool=pmcentrez&rendertype=abstract %R 10.1073/pnas.0702265104 %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 Acta Biochimica Polonica %D 2005 %T Protein modeling with reduced representation: statistical potentials and protein folding mechanism %A Dariusz Ekonomiuk %A Marcin Kielbasinski %A Andrzej Koliński %K Biophysical Phenomena %K Biophysics %K Computer Simulation %K Models %K Molecular %K Monte Carlo Method %K Protein Conformation %K Protein Folding %K Proteins %K Proteins: chemistry %K Proteins: metabolism %X A high resolution reduced model of proteins is used in Monte Carlo dynamics studies of the folding mechanism of a small globular protein, the B1 immunoglobulin-binding domain of streptococcal protein G. It is shown that in order to reproduce the physics of the folding transition, the united atom based model requires a set of knowledge-based potentials mimicking the short-range conformational propensities and protein-like chain stiffness, a model of directional and cooperative hydrogen bonds, and properly designed knowledge-based potentials of the long-range interactions between the side groups. The folding of the model protein is cooperative and very fast. In a single trajectory, a number of folding/unfolding cycles were observed. Typically, the folding process is initiated by assembly of a native-like structure of the C-terminal hairpin. In the next stage the rest of the four-ribbon beta-sheet folds. The slowest step of this pathway is the assembly of the central helix on the scaffold of the beta-sheet. %B Acta Biochimica Polonica %V 52 %P 741–8 %8 jan %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/15933762 %0 Journal Article %J Biopolymers %D 2003 %T A simple lattice model that exhibits a protein-like cooperative all-or-none folding transition %A Andrzej Koliński %A Dominik Gront %A Piotr Pokarowski %A Jeffrey Skolnick %K Biopolymers %K Biopolymers: chemistry %K Biopolymers: metabolism %K Chemical %K Models %K Molecular %K Monte Carlo Method %K Protein Folding %K Protein Structure %K Proteins %K Proteins: chemistry %K Proteins: metabolism %K Secondary %K Thermodynamics %X In a recent paper (D. Gront et al., Journal of Chemical Physics, Vol. 115, pp. 1569, 2001) we applied a simple combination of the Replica Exchange Monte Carlo and the Histogram methods in the computational studies of a simplified protein lattice model containing hydrophobic and polar units and sequence-dependent local stiffness. A well-defined, relatively complex Greek-key topology, ground (native) conformations was found; however, the cooperativity of the folding transition was very low. Here we describe a modified minimal model of the same Greek-key motif for which the folding transition is very cooperative and has all the features of the "all-or-none" transition typical of real globular proteins. It is demonstrated that the all-or-none transition arises from the interplay between local stiffness and properly defined tertiary interactions. The tertiary interactions are directional, mimicking the packing preferences seen in proteins. The model properties are compared with other minimal protein-like models, and we argue that the model presented here captures essential physics of protein folding (structurally well-defined protein-like native conformation and cooperative all-or-none folding transition). %B Biopolymers %V 69 %P 399–405 %8 jul %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/12833266 %R 10.1002/bip.10385