%0 Journal Article %J Wiley Interdisciplinary Reviews: Computational Molecular Science %D 2012 %T Optimization of protein models %A Dominik Gront %A Sebastian Kmiecik %A Maciej Blaszczyk %A Dariusz Ekonomiuk %A Andrzej Koliński %X Protein structure predictions, and experimentally derived protein structures, very often require certain structure improvement (refinement), which means bringing it closer to real, usually in vivo working conformations. In respect to the variety of protein models to be refined, computational optimization procedures could be divided into localized (applied to a small part of a structure) and global (whole structure). Generally speaking, the first problem is usually tractable, and the latter remains to be extremely challenging for systems larger then peptides or small proteins: optimization complexity and difficulty dramatically increase with the size of structures to be optimized. %B Wiley Interdisciplinary Reviews: Computational Molecular Science %V 2 %P 479–493 %G eng %U http://doi.wiley.com/10.1002/wcms.1090 %R 10.1002/wcms.1090 %0 Journal Article %J Journal of Computational Chemistry %D 2007 %T Protein structure prediction: combining de novo modeling with sparse experimental data %A Dorota Latek %A Dariusz Ekonomiuk %A Andrzej Koliński %K Algorithms %K Computer Simulation %K Magnetic Resonance Spectroscopy %K Models %K Molecular %K Protein Folding %K Protein Structure %K Proteins %K Proteins: chemistry %K Secondary %K Software %X Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction. %B Journal of Computational Chemistry %V 28 %P 1668–76 %8 jul %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17342709 %R 10.1002/jcc.20657 %0 Book Section %B Structural Genomics and High Throughput Structural Biology %D 2006 %T Ab initio modeling %A Jeffrey Skolnick %A Yang Zhang %A Andrzej Koliński %A Michael Sundstrom %A Martin Norin %A Aled Edwards %B Structural Genomics and High Throughput Structural Biology %I CRC/Taylor & Francis %C Boca Raton, FL %P 137-162 %G eng %& VIII %0 Journal Article %J Journal of Computer-Aided Molecular Design %D 2006 %T Three dimensional model of severe acute respiratory syndrome coronavirus helicase ATPase catalytic domain and molecular design of severe acute respiratory syndrome coronavirus helicase inhibitors %A Marcin Hoffmann %A Krystian Eitner %A Marcin von Grotthuss %A Leszek Rychlewski %A Ewa Banachowicz %A Tomasz Grabarkiewicz %A Tomasz Szkoda %A Andrzej Koliński %K Amino Acid Sequence %K Catalytic Domain %K Conserved Sequence %K DNA Helicases %K DNA Helicases: antagonists & inhibitors %K DNA Helicases: chemistry %K Drug Design %K Enzyme Inhibitors %K Enzyme Inhibitors: pharmacology %K Models %K Molecular %K Molecular Sequence Data %K Protein %K SARS Virus %K SARS Virus: enzymology %K Sequence Alignment %K Structural Homology %K Thermodynamics %X The modeling of the severe acute respiratory syndrome coronavirus helicase ATPase catalytic domain was performed using the protein structure prediction Meta Server and the 3D Jury method for model selection, which resulted in the identification of 1JPR, 1UAA and 1W36 PDB structures as suitable templates for creating a full atom 3D model. This model was further utilized to design small molecules that are expected to block an ATPase catalytic pocket thus inhibit the enzymatic activity. Binding sites for various functional groups were identified in a series of molecular dynamics calculation. Their positions in the catalytic pocket were used as constraints in the Cambridge structural database search for molecules having the pharmacophores that interacted most strongly with the enzyme in a desired position. The subsequent MD simulations followed by calculations of binding energies of the designed molecules were compared to ATP identifying the most successful candidates, for likely inhibitors - molecules possessing two phosphonic acid moieties at distal ends of the molecule. %B Journal of Computer-Aided Molecular Design %V 20 %P 305–319 %8 may %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/16972168 %R 10.1007/s10822-006-9057-z %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