@article {Gniewek2011a, title = {Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models}, journal = {Proteins}, volume = {79}, number = {6}, year = {2011}, month = {jun}, pages = {1923{\textendash}9}, abstract = {Multibody potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Our goal was to combine long range multibody potentials and short range potentials to improve recognition of native structure among misfolded decoys. We optimized the weights for four-body nonsequential, four-body sequential, and short range potentials to obtain optimal model ranking results for threading and have compared these data against results obtained with other potentials (26 different coarse-grained potentials from the Potentials {\textquoteright}R{\textquoteright}Us web server have been used). Our optimized multibody potentials outperform all other contact potentials in the recognition of the native structure among decoys, both for models from homology template-based modeling and from template-free modeling in CASP8 decoy sets. We have compared the results obtained for this optimized coarse-grained potentials, where each residue is represented by a single point, with results obtained by using the DFIRE potential, which takes into account atomic level information of proteins. We found that for all proteins larger than 80 amino acids our optimized coarse-grained potentials yield results comparable to those obtained with the atomic DFIRE potential.}, keywords = {Amino Acids, Amino Acids: chemistry, Computational Biology, Computational Biology: methods, Models, Molecular, Protein Conformation, Proteins, Proteins: chemistry}, issn = {1097-0134}, doi = {10.1002/prot.23015}, url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3093657\&tool=pmcentrez\&rendertype=abstract}, author = {Pawel Gniewek and Sumudu P. Leelananda and Andrzej Koli{\'n}ski and Robert L. Jernigan and Andrzej Kloczkowski} } @article {Trojanowski2010, title = {TRACER. A new approach to comparative modeling that combines threading with free-space conformational sampling}, journal = {Acta Biochimica Polonica}, volume = {57}, number = {1}, year = {2010}, month = {jan}, pages = {125{\textendash}33}, abstract = {A new approach to comparative modeling of proteins, TRACER, is described and benchmarked against classical modeling procedures. The new method unifies true three-dimensional threading with coarse-grained sampling of query protein conformational space. The initial sequence alignment of a query protein with a template is not required, although a template needs to be somehow identified. The template is used as a multi-featured fuzzy three-dimensional scaffold. The conformational search for the query protein is guided by intrinsic force field of the coarse-grained modeling engine CABS and by compatibility with the template scaffold. During Replica Exchange Monte Carlo simulations the model chain representing the query protein finds the best possible structural alignment with the template chain, that also optimizes the intra-protein interactions as approximated by the knowledge based force field of CABS. The benchmark done for a representative set of query/template pairs of various degrees of sequence similarity showed that the new method allows meaningful comparative modeling also for the region of marginal, or non-existing, sequence similarity. Thus, the new approach significantly extends the applicability of comparative modeling.}, keywords = {Computational Biology, Computational Biology: methods, Imaging, Models, Molecular, Protein Conformation, Proteins, Proteins: chemistry, Three-Dimensional, Three-Dimensional: methods}, issn = {1734-154X}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20309433}, author = {Sebastian Trojanowski and Aleksandra Rutkowska and Andrzej Koli{\'n}ski} } @article {Gront2008, title = {Utility library for structural bioinformatics}, journal = {Bioinformatics (Oxford, England)}, volume = {24}, number = {4}, year = {2008}, month = {feb}, pages = {584{\textendash}5}, abstract = {In this Note we present a new software library for structural bioinformatics. The library contains programs, computing sequence- and profile-based alignments and a variety of structural calculations with user-friendly handling of various data formats. The software organization is very flexible. Algorithms are written in Java language and may be used by Java programs. Moreover the modules can be accessed from Jython (Python scripting language implemented in Java) scripts. Finally, the new version of BioShell delivers several utility programs that can do typical bioinformatics task from a command-line level. Availability The software is available for download free of charge from its website: http://bioshell.chem.uw.edu.pl. This website provides also numerous examples, code snippets and API documentation.}, keywords = {Computational Biology, Computational Biology: methods, Libraries, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btm627}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18227118}, author = {Dominik Gront and Andrzej Koli{\'n}ski} } @article {Gront2007, title = {T-Pile{\textendash}a package for thermodynamic calculations for biomolecules}, journal = {Bioinformatics (Oxford, England)}, volume = {23}, number = {14}, year = {2007}, month = {jul}, pages = {1840{\textendash}1842}, abstract = {Molecular dynamics and Monte Carlo, usually conducted in canonical ensemble, deliver a plethora of biomolecular conformations. Proper analysis of the simulation data is a crucial part of biophysical and bioinformatics studies. Sequence alignment problem can be also formulated in terms of Boltzmann distribution. Therefore tools for efficient analysis of canonical ensemble data become extremely valuable. T-Pile package, presented here provides a user-friendly implementation of most important algorithms such as multihistogram analysis and reweighting technique. The package can be used in studies of virtually any system governed by Boltzmann distribution. AVAILABILITY: T-Pile can be downloaded from: http://biocomp.chem.uw.edu.pl/services/tpile. These pages provide a comprehensive tutorial and documentation with illustrative examples of applications. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.}, keywords = {Algorithms, Biophysics, Biophysics: methods, Computational Biology, Computational Biology: methods, Computers, Hot Temperature, Models, Molecular Conformation, Monte Carlo Method, Probability, Proteins, Proteins: chemistry, Software, Temperature, Theoretical, Thermodynamics}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btm259}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17510173}, author = {Dominik Gront and Andrzej Koli{\'n}ski} } @article {Ibryashkina2007, title = {Type II restriction endonuclease R.Eco29kI is a member of the GIY-YIG nuclease superfamily}, journal = {BMC Structural Biology}, volume = {7}, year = {2007}, month = {jan}, pages = {48}, abstract = {BACKGROUND: The majority of experimentally determined crystal structures of Type II restriction endonucleases (REases) exhibit a common PD-(D/E)XK fold. Crystal structures have been also determined for single representatives of two other folds: PLD (R.BfiI) and half-pipe (R.PabI), and bioinformatics analyses supported by mutagenesis suggested that some REases belong to the HNH fold. Our previous bioinformatic analysis suggested that REase R.Eco29kI shares sequence similarities with one more unrelated nuclease superfamily, GIY-YIG, however so far no experimental data were available to support this prediction. The determination of a crystal structure of the GIY-YIG domain of homing endonuclease I-TevI provided a template for modeling of R.Eco29kI and prompted us to validate the model experimentally. RESULTS: Using protein fold-recognition methods we generated a new alignment between R.Eco29kI and I-TevI, which suggested a reassignment of one of the putative catalytic residues. A theoretical model of R.Eco29kI was constructed to illustrate its predicted three-dimensional fold and organization of the active site, comprising amino acid residues Y49, Y76, R104, H108, E142, and N154. A series of mutants was constructed to generate amino acid substitutions of selected residues (Y49A, R104A, H108F, E142A and N154L) and the mutant proteins were examined for their ability to bind the DNA containing the Eco29kI site 5{\textquoteright}-CCGCGG-3{\textquoteright} and to catalyze the cleavage reaction. Experimental data reveal that residues Y49, R104, E142, H108, and N154 are important for the nuclease activity of R.Eco29kI, while H108 and N154 are also important for specific DNA binding by this enzyme. CONCLUSION: Substitutions of residues Y49, R104, H108, E142 and N154 predicted by the model to be a part of the active site lead to mutant proteins with strong defects in the REase activity. These results are in very good agreement with the structural model presented in this work and with our prediction that R.Eco29kI belongs to the GIY-YIG superfamily of nucleases. Our study provides the first experimental evidence for a Type IIP REase that does not belong to the PD-(D/E)XK or HNH superfamilies of nucleases, and is instead a member of the unrelated GIY-YIG superfamily.}, keywords = {Amino Acid Sequence, Binding Sites, Computational Biology, Computational Biology: methods, Deoxyribonucleases, DNA, DNA Cleavage, DNA: metabolism, Electrophoretic Mobility Shift Assay, Models, Molecular, Molecular Sequence Data, Mutation, Protein, Protein Conformation, Sequence Alignment, Structural Homology, Type II Site-Specific, Type II Site-Specific: chemist, Type II Site-Specific: metabol}, isbn = {1472680774}, issn = {1472-6807}, doi = {10.1186/1472-6807-7-48}, url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1952068\&tool=pmcentrez\&rendertype=abstract}, author = {Elena M. Ibryashkina and Marina V. Zakharova and Vladimir B. Baskunov and Ekaterina S. Bogdanova and Maxim O. Nagornykh and Marat M Den{\textquoteright}mukhamedov and Bogdan S. Melnik and Andrzej Koli{\'n}ski and Dominik Gront and Marcin Feder and Alexander S. Solonin and Janusz M. Bujnicki} } @article {Gront2006, title = {BioShell{\textendash}a package of tools for structural biology computations}, journal = {Bioinformatics (Oxford, England)}, volume = {22}, number = {5}, year = {2006}, month = {mar}, pages = {621{\textendash}622}, abstract = {

SUMMARY: BioShell is a suite of programs performing common tasks accompanying protein structure modeling. BioShell design is based on UNIX shell flexibility and should be used as its extension. Using BioShell various molecular modeling procedures can be integrated in a single pipeline. AVAILABILITY: BioShell package can be downloaded from its website http://biocomp.chem.uw.edu.pl/BioShell and these pages provide many examples and a detailed documentation for the newest version.

}, keywords = {Chemical, Computational Biology, Computational Biology: methods, Computer Simulation, Databases, Models, Protein, Protein: methods, Proteins, Proteins: analysis, Proteins: chemistry, Proteins: classification, Sequence Alignment, Sequence Alignment: methods, Sequence Analysis, Software}, issn = {1367-4803}, doi = {10.1093/bioinformatics/btk037}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16407320}, author = {Dominik Gront and Andrzej Koli{\'n}ski} } @article {Kolinski2005, title = {Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models}, journal = {Proteins}, volume = {61 Suppl. 7}, number = {April}, year = {2005}, month = {jan}, pages = {84{\textendash}90}, abstract = {To predict the tertiary structure of full-length sequences of all targets in CASP6, regardless of their potential category (from easy comparative modeling to fold recognition to apparent new folds) we used a novel combination of two very different approaches developed independently in our laboratories, which ranked quite well in different categories in CASP5. First, the GeneSilico metaserver was used to identify domains, predict secondary structure, and generate fold recognition (FR) alignments, which were converted to full-atom models using the "FRankenstein{\textquoteright}s Monster" approach for comparative modeling (CM) by recombination of protein fragments. Additional models generated "de novo" by fully automated servers were obtained from the CASP website. All these models were evaluated by VERIFY3D, and residues with scores better than 0.2 were used as a source of spatial restraints. Second, a new implementation of the lattice-based protein modeling tool CABS was used to carry out folding guided by the above-mentioned restraints with the Replica Exchange Monte Carlo sampling technique. Decoys generated in the course of simulation were subject to the average linkage hierarchical clustering. For a representative decoy from each cluster, a full-atom model was rebuilt. Finally, five models were selected for submission based on combination of various criteria, including the size, density, and average energy of the corresponding cluster, and the visual evaluation of the full-atom structures and their relationship to the original templates. The combination of FRankenstein and CABS was one of the best-performing algorithms over all categories in CASP6 (it is important to note that our human intervention was very limited, and all steps in our method can be easily automated). We were able to generate a number of very good models, especially in the Comparative Modeling and New Folds categories. Frequently, the best models were closer to the native structure than any of the templates used. The main problem we encountered was in the ranking of the final models (the only step of significant human intervention), due to the insufficient computational power, which precluded the possibility of full-atom refinement and energy-based evaluation.}, keywords = {Algorithms, Computational Biology, Computational Biology: methods, Computer Simulation, Computers, Data Interpretation, Databases, Dimerization, Models, Molecular, Monte Carlo Method, Protein, Protein Conformation, Protein Folding, Protein Structure, Proteomics, Proteomics: methods, Reproducibility of Results, Secondary, Sequence Alignment, Software, Statistical, Tertiary}, issn = {1097-0134}, doi = {10.1002/prot.20723}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16187348}, author = {Andrzej Koli{\'n}ski and Janusz M. Bujnicki} } @article {Fetrow2002, title = {The protein folding problem: a biophysical enigma}, journal = {Current Pharmaceutical Biotechnology}, volume = {3}, number = {4}, year = {2002}, month = {dec}, pages = {329{\textendash}347}, abstract = {Protein folding, the problem of how an amino acid sequence folds into a unique three-dimensional shape, has been a long-standing problem in biology. The success of genome-wide sequencing efforts has increased the interest in understanding the protein folding enigma, because realizing the value of the genomic sequences rests on the accuracy with which the encoded gene products are understood. Although a complete understanding of the kinetics and thermodynamics of protein folding has remained elusive, there has been considerable progress in techniques to predict protein structure from amino acid sequences. The prediction techniques fall into three general classes: comparative modeling, threading and ab initio folding. The current state of research in each of these three areas is reviewed here in detail. Efforts to apply each method to proteome-wide analysis are reviewed, and some of the key technical hurdles that remain are presented. Protein folding technologies, while not yet providing a full understanding of the protein folding process, have clearly progressed to the point of being useful in enabling structure-based annotation of genomic sequences.}, keywords = {Animals, Biophysical Phenomena, Biophysics, Computational Biology, Computational Biology: methods, Computational Biology: trends, Humans, Protein Folding}, issn = {1389-2010}, url = {http://www.ncbi.nlm.nih.gov/pubmed/12463416}, author = {Jacquelyn S. Fetrow and A. Giammona and Andrzej Koli{\'n}ski and Jeffrey Skolnick} } @article {Kolinski2001, title = {Generalized comparative modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement}, journal = {Proteins}, volume = {44}, number = {2}, year = {2001}, month = {aug}, pages = {133{\textendash}149}, abstract = {An improved generalized comparative modeling method, GENECOMP, for the refinement of threading models is developed and validated on the Fischer database of 68 probe-template pairs, a standard benchmark used to evaluate threading approaches. The basic idea is to perform ab initio folding using a lattice protein model, SICHO, near the template provided by the new threading algorithm PROSPECTOR. PROSPECTOR also provides predicted contacts and secondary structure for the template-aligned regions, and possibly for the unaligned regions by garnering additional information from other top-scoring threaded structures. Since the lowest-energy structure generated by the simulations is not necessarily the best structure, we employed two structure-selection protocols: distance geometry and clustering. In general, clustering is found to generate somewhat better quality structures in 38 of 68 cases. When applied to the Fischer database, the protocol does no harm and in a significant number of cases improves upon the initial threading model, sometimes dramatically. The procedure is readily automated and can be implemented on a genomic scale.}, keywords = {Algorithms, Chemical, Combinatorial Chemistry Techniques, Combinatorial Chemistry Techniques: methods, Computational Biology, Computational Biology: methods, Computer Simulation, Databases, Factual, Models, Molecular, Monte Carlo Method, Protein Folding, Proteins, Proteins: chemistry, Sequence Alignment, Sequence Alignment: methods}, issn = {0887-3585}, url = {http://www.ncbi.nlm.nih.gov/pubmed/11391776}, author = {Andrzej Koli{\'n}ski and Marcos Betancourt and Daisuke Kihara and Piotr Rotkiewicz and Jeffrey Skolnick} }