%0 Journal Article %J Bioorganic Chemistry %D 2020 %T Isoxazole-containing 5′ mRNA cap analogues as inhibitors of the translation initiation process %A Karolina Piecyk %A Maciej Lukaszewicz %A Karol Kamel %A Maria Janowska %A Paulina Pietrow %A Sebastian Kmiecik %A Marzena Jankowska-Anyszka %K Cap analogue %K Cycloaddition reaction %K Isoxazol %K mRNA %K Translation initiation %X Herein we describe a synthesis of new isoxazole-containing 5′ mRNA cap analogues via a cycloaddition reaction. The obtained analogues show a capability to inhibit cap-dependent translation in vitro and are characterized by a new binding mode in which an isoxazolic ring, instead of guanine, is involved in the stacking effect. Our study provides valuable information toward designing new compounds that can be potentially used as anticancer therapeutics. %B Bioorganic Chemistry %V 96 %P 103583 %G eng %U https://www.sciencedirect.com/science/article/pii/S004520681931819X %R https://doi.org/10.1016/j.bioorg.2020.103583 %0 Journal Article %J Molecular Pharmaceutics %D 2018 %T Combining Structural Aggregation Propensity and Stability Predictions To Redesign Protein Solubility %A Marcos Gil-Garcia %A Manuel Bañó-Polo %A Nathalia Varejão %A Michal Jamroz %A Aleksander Kuriata %A Marta Díaz-Caballero %A Jara Lascorz %A Bertrand Morel %A Susanna Navarro %A David Reverter %A Sebastian Kmiecik %A Salvador Ventura %X The aggregation propensity of each particular protein seems to be shaped by evolution according to its natural abundance in the cell. The production and downstream processing of recombinant polypeptides implies attaining concentrations that are orders of magnitude above their natural levels, often resulting in their aggregation; a phenomenon that precludes the marketing of many globular proteins for biomedical or biotechnological applications. Therefore, there is a huge interest in methods aimed to increase the proteins solubility above their natural limits. Here, we demonstrate that an updated version of our AGGRESCAN 3D structural aggregation predictor, that now takes into account protein stability, allows for designing mutations at specific positions in the structure that improve the solubility of proteins without compromising their conformation. Using this approach, we have designed a highly soluble variant of the green fluorescent protein and a human single-domain VH antibody displaying significantly reduced aggregation propensity. Overall, our data indicate that the solubility of unrelated proteins can be easily tuned by in silico-designed nondestabilizing amino acid changes at their surfaces. %B Molecular Pharmaceutics %V 15 %P 3846-3859 %G eng %U https://doi.org/10.1021/acs.molpharmaceut.8b00341 %R 10.1021/acs.molpharmaceut.8b00341 %0 Journal Article %J European Journal of Medicinal Chemistry %D 2018 %T Design and synthesis of novel 1H-tetrazol-5-amine based potent antimicrobial agents: DNA topoisomerase IV and gyrase affinity evaluation supported by molecular docking studies %A Daniel Szulczyk %A Michał A. Dobrowolski %A Piotr Roszkowski %A Anna Bielenica %A Joanna Stefańska %A Michal Kolinski %A Sebastian Kmiecik %A Michał Jóźwiak %A Małgorzata Wrzosek %A Wioletta Olejarz %A Marta Struga %K 1H-tetrazol-5-amine %K Antimicrobial activity %K Cytotoxicity %K DNA gyrase %K molecular docking %K Topoisomerase type IV %X A total of 14 of 1,5-disubstituted tetrazole derivatives were prepared by reacting appropriate thiourea and sodium azide in the presence of mercury (II) chloride and triethylamine. All compounds were evaluated in vitro for their antimicrobial activity. Derivatives 10 and 11 showed the highest inhibition against Gram-positive and Gram-negative strains (standard and hospital strains). The observed minimal inhibitory concentrations values were in the range of 1–208 μM (0.25–64 μg/ml). Inhibitory activity of 1,5-tetrazole derivatives 10 and 11 against gyrase and topoisomerase IV isolated from S. aureus was studied. Evaluation was supported by molecular docking studies for all synthesized derivatives and reference ciprofloxacin. Moreover, selected tetrazoles (2, 3, 5, 6, 8, 9, 10 and 11) were evaluated for their cytotoxicity. All tested compounds are non-cytotoxic against HaCaT and A549 cells (CC50 ≤ 60 μM). %B European Journal of Medicinal Chemistry %V 156 %P 631 - 640 %G eng %U http://www.sciencedirect.com/science/article/pii/S022352341830597X %R https://doi.org/10.1016/j.ejmech.2018.07.041 %0 Book Section %B Methods in Molecular Biology %D 2017 %T Predicting real-valued protein residue fluctuation using FlexPred %A Lenna Peterson %A Michal Jamroz %A Andrzej Koliński %A Daisuke Kihara %X The conventional view of a protein structure as static provides only a limited picture.There is increasing evidence that protein dynamics are often vital to protein function including interaction with partners such as other proteins, nucleic acids, and small molecules. Considering flexibility is also important in applications such as computational protein docking and protein design. While residue flexibility is partially indicated by experimental measures such as the B‐factor from X‐ray crystallography and ensemble fluctuation from nuclear magnetic resonance (NMR) spectroscopy as well as computational molecular dynamics (MD) simulation, these techniques are resource‐intensive. In this chapter, we describe the web server and standalone version of FlexPred, which rapidly predicts absolute per‐residue fluctuation from a three‐dimensional protein structure. On a set of 592 non‐redundant structures, comparing the fluctuations predicted by FlexPred to the observed fluctuations in MD simulations showed an average correlation coefficient of 0.669 and an average root mean square error of 1.07 Å. FlexPred is available at http://kiharalab.org/flexPred/. %B Methods in Molecular Biology %V 1484 %P 175-186 %G eng %R 10.1007/978-1-4939-6406-2_13 %0 Journal Article %J Journal of Chemical Information and Modeling %D 2016 %T Coarse-grained simulations of membrane insertion and folding of small helical proteins using CABS model %A Wojciech Pulawski %A Michal Jamroz %A Michal Kolinski %A Andrzej Koliński %A Sebastian Kmiecik %X The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics and interactions). Here we introduce an extension of CABS representation and force field (CABS-membrane) to the modeling of the effect of biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to all-atom representation and all-atom scoring. In conclusion, the CABS-membrane model is a promising approach for further development towards modeling of large protein-membrane systems. %B Journal of Chemical Information and Modeling %V 56 %P 2207–2215 %G eng %U https://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00350 %N 11 %R 10.1021/acs.jcim.6b00350 %0 Journal Article %J Bioinformatics %D 2016 %T Ensemble-based evaluation for protein structure models %A Michal Jamroz %A Andrzej Koliński %A Daisuke Kihara %X Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computa- tional protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect in- trinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displace- ments and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. %B Bioinformatics %V 32 %P i314–i321 %8 jun %G eng %U http://bioinformatics.oxfordjournals.org/lookup/doi/10.1093/bioinformatics/btw262 %R 10.1093/bioinformatics/btw262 %0 Journal Article %J Nucleic Acids Research %D 2015 %T AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures %A Rafael Zambrano %A Michal Jamroz %A Agata Szczasiuk %A Jordi Pujols %A Sebastian Kmiecik %A Salvador Ventura %X Protein aggregation underlies an increasing number of disorders and constitutes a major bottleneck in the development of therapeutic proteins. Our present understanding on the molecular determinants of protein aggregation has crystalized in a series of predictive algorithms to identify aggregation-prone sites. A majority of these methods rely only on sequence. Therefore, they find difficulties to predict the aggregation properties of folded globular proteins, where aggregation-prone sites are often not contiguous in sequence or buried inside the native structure. The AGGRESCAN3D (A3D) server overcomes these limitations by taking into account the protein structure and the experimental aggregation propensity scale from the well-established AGGRESCAN method. Using the A3D server, the identified aggregation-prone residues can be virtually mutated to design variants with increased solubility, or to test the impact of pathogenic mutations. Additionally, A3D server enables to take into account the dynamic fluctuations of protein structure in solution, which may influence aggregation propensity. This is possible in A3D Dynamic Mode that exploits the CABS-flex approach for the fast simulations  of flexibility of globular proteins. The A3D server can be accessed at http://biocomp.chem.uw.edu.pl/A3D/ %B Nucleic Acids Research %V 43 (W1) %P W306-W313 %G eng %0 Journal Article %J Nucleic Acids Research %D 2015 %T CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site %A Mateusz Kurcinski %A Michal Jamroz %A Maciej Blaszczyk %A Andrzej Koliński %A Sebastian Kmiecik %K CABS-dock %K flexible docking %K molecular docking %K peptide binding %K peptide folding %K protein-peptide docking %K protein-peptide interactions %X Protein-peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein-peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock doesn’t require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of non-redundant protein-peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Additionally, as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments. CABS-dock is freely available as a web server at http://biocomp.chem.uw.edu.pl/CABSdock %B Nucleic Acids Research %V 43 (W1) %P W419-W424 %G eng %0 Journal Article %J Nucleic Acids Research %D 2015 %T KnotProt: a database of proteins with knots and slipknots %A Michal Jamroz %A Wanda Niemyska %A Eric J Rawdon %A Andrzej Stasiak %A Kenneth C Millett %A Piotr Sułkowski %A Joanna I. Sulkowska %X The protein topology database KnotProt, http://knotprot.cent.uw.edu.pl/ , collects information about protein structures with open polypeptide chains forming knots or slipknots. The knotting complexity of the catalogued proteins is presented in the form of a matrix diagram that shows users the knot type of the entire polypeptide chain and of each of its subchains. The pattern visible in the matrix gives the knotting fingerprint of a given protein and permits users to determine, for example, the minimal length of the knotted regions (knots’ core size) or the depth of a knot, i.e. how many aminoacids can be removed from either end of the catalogued protein structure before converting it from a knot to a different type of knot. In addition, the database presents extensive information about the biological function of proteins with non-trivial knotting and the families and fold types of these proteins. As an additional feature, the KnotProt database enables users to submit protein or polymer structures and generate their knotting fingerprints. http://knotprot.cent.uw.edu.pl/ %B Nucleic Acids Research %V 43 %P D306-D314 %8 01/2015 %G eng %U http://nar.oxfordjournals.org/content/43/D1/D306 %N D1 %R 10.1093/nar/gku1059 %0 Journal Article %J J Phys Condens Matter %D 2015 %T Prediction of the optimal set of contacts to fold the smallest knotted protein. %A Dabrowski-Tumanski, P %A Jarmolinska, A I %A Joanna I. Sulkowska %X Knotted protein chains represent a new motif in protein folds. They have been linked to various diseases, and recent extensive analysis of the Protein Data Bank shows that they constitute 1.5% of all deposited protein structures. Despite thorough theoretical and experimental investigations, the role of knots in proteins still remains elusive. Nonetheless, it is believed that knots play an important role in mechanical and thermal stability of proteins. Here, we perform a comprehensive analysis of native, shadow-specific and non-native interactions which describe free energy landscape of the smallest knotted protein (PDB id 2efv). We show that the addition of shadow-specific contacts in the loop region greatly enhances folding kinetics, while the addition of shadow-specific contacts along the C-terminal region (H3 or H4) results in a new folding route with slower kinetics. By means of direct coupling analysis (DCA) we predict non-native contacts which also can accelerate kinetics. Next, we show that the length of the C-terminal knot tail is responsible for the shape of the free energy barrier, while the influence of the elongation of the N-terminus is not significant. Finally, we develop a concept of a minimal contact map sufficient for 2efv protein to fold and analyze properties of this protein using this map. %B J Phys Condens Matter %V 27 %P 354109 %8 2015 Sep 9 %G eng %N 35 %R 10.1088/0953-8984/27/35/354109 %0 Journal Article %J Bioinformatics %D 2014 %T CABS-flex predictions of protein flexibility compared with NMR ensembles %A Michal Jamroz %A Andrzej Koliński %A Sebastian Kmiecik %X Motivation: Identification of flexible regions of protein structures is important for understanding of their biological functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom molecular dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles. Results: Based on a benchmark set of 140 proteins, we show that the relative fluctuations of protein residues obtained from CABS-flex are well correlated to those of NMR ensembles. On average, this correlation is stronger than that between MD and NMR ensembles. In conclusion, CABS-flex is useful and complementary to MD in predicting of protein regions that undergo conformational changes and the extent of such changes. Availability: The CABS-flex is freely available to all users at http://biocomp.chem.uw.edu.pl/CABSflex. %B Bioinformatics %V 30 %P 2150-2154 %8 04/2014 %G eng %N 15 %& - %R 10.1093/bioinformatics/btu184 %0 Conference Proceedings %B TASK Quarterly %D 2014 %T Coarse-grained modeling of protein structure, dynamics and protein-protein interactions %A Andrzej Koliński %A Sebastian Kmiecik %A Michal Jamroz %A Maciej Blaszczyk %A Maksim Kouza %A Mateusz Kurcinski %X Theoretical prediction of protein structures and dynamics is essential for understanding the molecular basis of drug action, metabolic and signaling pathways in living cells, designing new technologies in the life science and material sciences. We developed and validated a novel multiscale methodology for the study of protein folding processes including flexible docking of proteins and peptides. The new modeling technique starts from coarse-grained large-scale simulations, followed by selection of the most plausible final structures and intermediates and, finally, by an all-atom rectification of the obtained structures. Except for the most basic bioinformatics tools, the entire computational methodology is based on the models and algorithms developed in our lab. The coarse-grained simulations are based on a high-resolution lattice representation of protein structures, a knowledge based statistical force field and efficient Monte Carlo dynamics schemes, including Replica Exchange algorithms. This paper focuses on the description of the coarse-grained CABS model and its selected applications. %B TASK Quarterly %V 18 %P 219–229 %G eng %6 3 %0 Conference Proceedings %B TASK Quarterly %D 2014 %T Mechanical unfolding of DDFLN4 studied by the coarse-grained knowledge-based CABS model %A Maksim Kouza %A Michal Jamroz %A Dominik Gront %A Sebastian Kmiecik %A Andrzej Koliński %X Mechanical unfolding of the fourth domain of Distyostelium discoideum filamin (DDFLN4) was studied using a CABS – coarse-grained knowledge-based protein model. Our study demonstrates that CABS is capable of reproducing the unfolding free energy landscape of protein unfolding and highlights an important role of non-native interactions in the protein unfolding process. The obtained three peaks in the force-extension profile suggest a four-state picture of DDFLN4 protein unfolding and correspond reasonably to the results of the all-atom simulation in explicit solvent. %B TASK Quarterly %V 18 %P 373–378 %G eng %6 4 %0 Journal Article %J PLoS computational biology %D 2014 %T Pierced Lasso Bundles are a New Class of Knot Motifs %A Haglund, Ellinor %A Joanna I. Sulkowska %A Noel, Jeffrey K. %A Lammert, H %A Onuchic, José N. %A Jennings, Patricia A %X A four-helix bundle is a well-characterized motif often used as a target for designed pharmaceutical therapeutics and nutritional supplements. Recently, we discovered a new structural complexity within this motif created by a disulphide bridge in the long-chain helical bundle cytokine leptin. When oxidized, leptin contains a disulphide bridge creating a covalent-loop through which part of the polypeptide chain is threaded (as seen in knotted proteins). We explored whether other proteins contain a similar intriguing knot-like structure as in leptin and discovered 11 structurally homologous proteins in the PDB. We call this new helical family class the Pierced Lasso Bundle (PLB) and the knot-like threaded structural motif a Pierced Lasso (PL). In the current study, we use structure-based simulation to investigate the threading/folding mechanisms for all the PLBs along with three unthreaded homologs as the covalent loop (or lasso) in leptin is important in folding dynamics and activity. We find that the presence of a small covalent loop leads to a mechanism where structural elements slipknot to thread through the covalent loop. Larger loops use a piercing mechanism where the free terminal plugs through the covalent loop. Remarkably, the position of the loop as well as its size influences the native state dynamics, which can impact receptor binding and biological activity. This previously unrecognized complexity of knot-like proteins within the helical bundle family comprises a completely new class within the knot family, and the hidden complexity we unraveled in the PLBs is expected to be found in other protein structures outside the four-helix bundles. The insights gained here provide critical new elements for future investigation of this emerging class of proteins, where function and the energetic landscape can be controlled by hidden topology, and should be take into account in ab initio predictions of newly identified protein targets. %B PLoS computational biology %V 10(6) %G eng %& e1003613 %R doi: 10.1371/journal.pcbi.1003613 %0 Book Section %B Protein structure prediction (3rd Edition), Methods in Molecular Biology, Daisuke Kihara, Ed. %D 2014 %T Protocols for efficient simulations of long time protein dynamics using coarse-grained CABS model %A Michal Jamroz %A Andrzej Koliński %A Sebastian Kmiecik %K coarse-grained modeling %K protein dynamics %X Coarse-grained (CG) modeling is a well-acknowledged simulation approach for getting insight into long timescale protein folding events at reasonable computational cost. Depending on the design of a CG model, the simulation protocols vary from highly case-specific – requiring user-defined assumptions about the folding scenario, to more sophisticated blind prediction methods for which only a protein sequence is required. Here we describe the framework protocol for the simulations of long-term dynamics of globular proteins, with the use of the CABS CG protein model and sequence data. The simulations can start from a random or selected (e.g. native) structure. The described protocol has been validated using experimental data for protein folding model systems – the prediction results agreed well with the experimental results. %B Protein structure prediction (3rd Edition), Methods in Molecular Biology, Daisuke Kihara, Ed. %7 Protein structure prediction (3rd Edition) %V 1137 %P 235-250 %G eng %R 10.1007/978-1-4939-0366-5 %0 Journal Article %J Biophysical Journal %D 2014 %T Structure prediction of the second extracellular loop in G-protein-coupled receptors %A Sebastian Kmiecik %A Michal Jamroz %A Michal Kolinski %X G protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in thirteen GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its X-ray conformation. The modeling procedure utilized theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available X-ray structures. Predicted loop fragments resemble X-ray structures with comparable accuracy to those obtained by other state-of-the-art methods. Our results extend other studies by including newly crystallized GPCRs. %B Biophysical Journal %V 106 %P 2408–2416 %G eng %N 11 %0 Journal Article %J Nucleic Acids Research %D 2013 %T CABS-flex: server for fast simulation of protein structure fluctuations %A Michal Jamroz %A Andrzej Koliński %A Sebastian Kmiecik %K molecular dynamics %K near-native dynamics %K protein dynamics %K protein flexibility %K simulation %X The CABS-flex server (http://biocomp.chem.uw.edu.pl/CABSflex) implements CABS-model-based protocol for the fast simulations of near-native dynamics of globular proteins. In this application, the CABS model was shown to be a computationally efficient alternative to all-atom molecular dynamics-a classical simulation approach. The simulation method has been validated on a large set of molecular dynamics simulation data. Using a single input (user-provided file in PDB format), the CABS-flex server outputs an ensemble of protein models (in all-atom PDB format) reflecting the flexibility of the input structure, together with the accompanying analysis (residue mean-square-fluctuation profile and others). The ensemble of predicted models can be used in structure-based studies of protein functions and interactions. %B Nucleic Acids Research %V 41 %P W427-W431 %8 2013 May 8 %G eng %U http://nar.oxfordjournals.org/cgi/content/full/gkt332 %N W1 %R 10.1093/nar/gkt332 %0 Journal Article %J Nucleic Acids Research %D 2013 %T CABS-fold: server for the de novo and consensus-based prediction of protein structure %A Maciej Blaszczyk %A Michal Jamroz %A Sebastian Kmiecik %A Andrzej Koliński %K coarse-grained modeling %K homology modeling %K protein structure prediction %X The CABS-fold web server provides tools for protein structure prediction from sequence only (de novo modeling) and also using alternative templates (consensus modeling). The web server is based on the CABS modeling procedures ranked in previous CASP competitions (Critical Assessment of techniques for protein Structure Prediction) as one of the leading approaches for de novo< and template-based modeling. Except for template data, fragmentary distance restraints can also be incorporated into the modeling process. The web server output is a coarse-grained trajectory of generated conformations, its Jmol representation and predicted models in all-atom resolution (together with accompanying analysis). CABS-fold can be freely accessed at http://biocomp.chem.uw.edu.pl/CABSfold %B Nucleic Acids Research %V 41 %P W406-W411 %G eng %N W1 %R 10.1093/nar/gkt462 %0 Journal Article %J BMC Bioinformatics %D 2013 %T ClusCo: clustering and comparison of protein models %A Michal Jamroz %A Andrzej Koliński %X BACKGROUND: The development, optimization and validation of protein modeling methods require efficient tools forstructural comparison. Frequently, a large number of models need to be compared with the targetnative structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of thebottlenecks in the protein modeling pipeline. RESULTS: Clusco is fast and easy-to-use software for high-throughput comparison of protein models with dif-ferent similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap)and clustering of the comparison results with standard methods: K-means Clustering or HierarchicalAgglomerative Clustering. CONCLUSIONS: The application was highly optimized and written in C/C++, including the code for parallel execu-tion on CPU and GPU, which resulted in a significant speedup over similar clustering and scoringcomputation programs. %B BMC Bioinformatics %V 14 %P 62 %G eng %N 1 %0 Journal Article %J Journal of Chemical Theory and Computation %D 2013 %T Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field %A Michal Jamroz %A Modesto Orozco %A Andrzej Koliński %A Sebastian Kmiecik %K molecular dynamics %K near-native dynamics %K protein dynamics %K protein flexibility %K simulation %X It is widely recognized that atomistic Molecular Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theoretical study showing that various MD force-fields provide a consensus picture of protein fluctuations in aqueous solution [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biologically relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale molecular modeling of protein systems with atomistic resolution. %B Journal of Chemical Theory and Computation %V 9 %P 119 - 125 %8 12/2012 %@ 1549-9618 %G eng %U http://dx.doi.org/10.1021/ct300854w %N 1 %! J. Chem. Theory Comput. %R 10.1021/ct300854w %0 Journal Article %J Journal of Molecular Modeling %D 2013 %T Distributions of amino acids suggest that certain residue types more effectively determine protein secondary structure %A Saras Saraswathi %A J. L. Fernández-Martínez %A Andrzej Koliński %A Robert L. Jernigan %A Andrzej Kloczkowski %X Exponential growth in the number of available protein sequences is unmatched by the slower growth in the number of structures. As a result, the development of efficient and fast protein secondary structure prediction methods is essential for the broad comprehension of protein structures. Computational methods that can efficiently determine secondary structure can in turn facilitate protein tertiary structure prediction, since most methods rely initially on secondary structure predictions. Recently, we have developed a fast learning optimized prediction methodology (FLOPRED) for predicting protein secondary structure (Saraswathi et al. in JMM 18:4275, 2012). Data are generated by using knowledge-based potentials combined with structure information from the CATH database. A neural network-based extreme learning machine (ELM) and advanced particle swarm optimization (PSO) are used with this data to obtain better and faster convergence to more accurate secondary structure predicted results. A five-fold cross-validated testing accuracy of 83.8 % and a segment overlap (SOV) score of 78.3 % are obtained in this study. Secondary structure predictions and their accuracy are usually presented for three secondary structure elements: α-helix, β-strand and coil but rarely have the results been analyzed with respect to their constituent amino acids. In this paper, we use the results obtained with FLOPRED to provide detailed behaviors for different amino acid types in the secondary structure prediction. We investigate the influence of the composition, physico-chemical properties and position specific occurrence preferences of amino acids within secondary structure elements. In addition, we identify the correlation between these properties and prediction accuracy. The present detailed results suggest several important ways that secondary structure predictions can be improved in the future that might lead to improved protein design and engineering. %B Journal of Molecular Modeling %V 19 %P 4337-48 %8 2013 Oct %G eng %N 10 %R 10.1007/s00894-013-1911-z %0 Journal Article %J Journal of Physicak Chemistry Letters %D 2013 %T Hysteresis as a Marker for Complex, Overlapping Landscapes in Proteins. %A Andrews, Benjamin T %A Capraro, Dominique T %A Joanna I. Sulkowska %A Onuchic, José N %A Jennings, Patricia A %X Topologically complex proteins fold by multiple routes as a result of hard-to-fold regions of the proteins. Oftentimes these regions are introduced into the protein scaffold for function and increase frustration in the otherwise smooth-funneled landscape. Interestingly, while functional regions add complexity to folding landscapes, they may also contribute to a unique behavior referred to as hysteresis. While hysteresis is predicted to be rare, it is observed in various proteins, including proteins containing a unique peptide cyclization to form a fluorescent chromophore as well as proteins containing a knotted topology in their native fold. Here, hysteresis is demonstrated to be a consequence of the decoupling of unfolding events from the isomerization or hula-twist of a chromophore in one protein and the untying of the knot in a second protein system. The question now is- can hysteresis be a marker for the interplay of landscapes where complex folding and functional regions overlap? %B Journal of Physicak Chemistry Letters %V 4 %P 180-188 %8 2013 Jan 3 %G eng %N 1 %R 10.1021/jz301893w %0 Journal Article %J The Journal of Chemical Physics %D 2012 %T Elastic network normal modes provide a basis for protein structure refinement %A Pawel Gniewek %A Andrzej Koliński %A Robert L. Jernigan %A Andrzej Kloczkowski %X

It is well recognized that thermal motions of atoms in the protein native state, the fluctuations about the minimum of the global free energy, are well reproduced by the simple elastic network models (ENMs) such as the anisotropic network model (ANM). Elastic network models represent protein dynamics as vibrations of a network of nodes (usually represented by positions of the heavy atoms or by the C($\alpha$) atoms only for coarse-grained representations) in which the spatially close nodes are connected by harmonic springs. These models provide a reliable representation of the fluctuational dynamics of proteins and RNA, and explain various conformational changes in protein structures including those important for ligand binding. In the present paper, we study the problem of protein structure refinement by analyzing thermal motions of proteins in non-native states. We represent the conformational space close to the native state by a set of decoys generated by the I-TASSER protein structure prediction server utilizing template-free modeling. The protein substates are selected by hierarchical structure clustering. The main finding is that thermal motions for some substates, overlap significantly with the deformations necessary to reach the native state. Additionally, more mobile residues yield higher overlaps with the required deformations than do the less mobile ones. These findings suggest that structural refinement of poorly resolved protein models can be significantly enhanced by reduction of the conformational space to the motions imposed by the dominant normal modes.

%B The Journal of Chemical Physics %V 136 %P 195101 %8 may %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22612113 %R 10.1063/1.4710986 %0 Journal Article %J Journal of Molecular Modeling %D 2012 %T Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction %A Saras Saraswathi %A Juan Luis Fernandez Martinez %A Andrzej Koliński %A Robert L. Jernigan %A Andrzej Kloczkowski %K knowledge-based potentials %K learning %K machine %K neural networks %K particle swarm optimization %K protein secondary structure prediction %X

Computational methods are rapidly gaining importance in the field of structural biology, mostly due to the explosive progress in genome sequencing projects and the large disparity between the number of sequences and the number of structures. There has been an exponential growth in the number of available protein sequences and a slower growth in the number of structures. There is therefore an urgent need to develop computational methods to predict structures and identify their functions from the sequence. Developing methods that will satisfy these needs both efficiently and accurately is of paramount importance for advances in many biomedical fields, including drug development and discovery of biomarkers. A novel method called fast learning optimized prediction methodology (FLOPRED) is proposed for predicting protein secondary structure, using knowledge-based potentials combined with structure information from the CATH database. A neural network-based extreme learning machine (ELM) and advanced particle swarm optimization (PSO) are used with this data that yield better and faster convergence to produce more accurate results. Protein secondary structures are predicted reliably, more efficiently and more accurately using FLOPRED. These techniques yield superior classification of secondary structure elements, with a training accuracy ranging between 83 % and 87 % over a widerange of hidden neurons and a cross-validated testing accuracy ranging between 81 % and 84 % and a segment overlap (SOV) score of 78 % that are obtained with different sets of proteins. These results are comparable to other recently published studies, but are obtained with greater efficiencies, in terms of time and cost.

%B Journal of Molecular Modeling %V 18 %P 4275–89 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22562230 %R 10.1007/s00894-012-1410-7 %0 Journal Article %J Proteins %D 2012 %T How noise in force fields can affect the structural refinement of protein models? %A Pawel Gniewek %A Andrzej Koliński %A Robert L. Jernigan %A Andrzej Kloczkowski %K force field %K knowledge-based potentials %K normal modes analysis %K protein structure prediction %K protein structure refinement %K white noise %X Structural refinement of predicted models of biological macromolecules using atomistic or coarse-grained molecular force fields having various degree of error is investigated. The goal of this analysis is to estimate what is the probability for designing an effective structural refinement based on computations of conformational energies using force field, and starting from a structure predicted from the sequence (using template-based or template-free modeling), and refining it to bring the structure into closer proximity to the native state. It is widely believed that it should be possible to develop such a successful structure refinement algorithm by applying an iterative procedure with stochastic sampling and appropriate energy function, which assesses the quality (correctness) of protein decoys. Here, an analysis of noise in an artificially introduced scoring function is investigated for a model of an ideal sampling scheme, where the underlying distribution of RMSDs is assumed to be Gaussian. Sampling of the conformational space is performed by random generation of RMSD values. We demonstrate that whenever the random noise in a force field exceeds some level, it is impossible to obtain reliable structural refinement. The magnitude of the noise, above which a structural refinement, on average is impossible, depends strongly on the quality of sampling scheme and a size of the protein. Finally, possible strategies to overcome the intrinsic limitations in the force fields for impacting the development of successful refinement algorithms are discussed. Proteins 2011;. © 2011 Wiley Periodicals, Inc. %B Proteins %V 80 %P 335–341 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22223184 %R 10.1002/prot.23240 %0 Conference Proceedings %B From Computational Biophysics to Systems Biology (CBSB11) Proceedings %D 2012 %T Protein Structure Prediction Using CABS – A Consensus Approach %A Maciej Blaszczyk %A Michal Jamroz %A Dominik Gront %A Andrzej Koliński %X We have designed a new pipeline for protein structure prediction based on the CABS engine. The procedure is fully automated and generates consensus models from a set of templates. Restraints derived from the templates define a region of conformational space, which is then sampled by Replica Exchange Monte Carlo algorithm implemented in CABS. Results from CASP9 show, that for great majority of targets this approach leads to better models than the mean quality of templates (in respect to GDT TS). In five cases the obtained models were the best among all predictions submitted to CASP9 as the first models. %B From Computational Biophysics to Systems Biology (CBSB11) Proceedings %V 8 %P 29–32 %G eng %0 Journal Article %J Proteins %D 2012 %T Structural features that predict real-value fluctuations of globular proteins %A Michal Jamroz %A Andrzej Koliński %A Daisuke Kihara %K fluctuation prediction %K molecular dynamics %K protein dynamics %K protein flexibility %K structure-dynamics relationship %K support vector regression %X It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 \AA. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. %B Proteins %V 80 %P 1425–35 %8 may %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22328193 %R 10.1002/prot.24040 %0 Journal Article %J PLoS One %D 2012 %T The unique cysteine knot regulates the pleotropic hormone leptin. %A Haglund, Ellinor %A Joanna I. Sulkowska %A He, Zhao %A Feng, Gen-Sheng %A Jennings, Patricia A %A Onuchic, José N %K Cysteine %K Humans %K Kinetics %K Leptin %K MCF-7 Cells %K Models, Molecular %K Oxidation-Reduction %K Signal Transduction %X Leptin plays a key role in regulating energy intake/expenditure, metabolism and hypertension. It folds into a four-helix bundle that binds to the extracellular receptor to initiate signaling. Our work on leptin revealed a hidden complexity in the formation of a previously un-described, cysteine-knotted topology in leptin. We hypothesized that this unique topology could offer new mechanisms in regulating the protein activity. A combination of in silico simulation and in vitro experiments was used to probe the role of the knotted topology introduced by the disulphide-bridge on leptin folding and function. Our results surprisingly show that the free energy landscape is conserved between knotted and unknotted protein, however the additional complexity added by the knot formation is structurally important. Native state analyses led to the discovery that the disulphide-bond plays an important role in receptor binding and thus mediate biological activity by local motions on distal receptor-binding sites, far removed from the disulphide-bridge. Thus, the disulphide-bridge appears to function as a point of tension that allows dissipation of stress at a distance in leptin. %B PLoS One %V 7 %P e45654 %8 2012 %G eng %N 9 %R 10.1371/journal.pone.0045654 %0 Conference Proceedings %B Proceedings of the National Academy of Sciences of the United States of America %D 2011 %T Human telomerase model shows the role of the TEN domain in advancing the double helix for the next polymerization step %A Kamil Steczkiewicz %A Michael T. Zimmermann %A Mateusz Kurcinski %A Benjamin A. Lewis %A Drena Dobbs %A Andrzej Kloczkowski %A Robert L. Jernigan %A Andrzej Koliński %A Krzysztof Ginalski %K Amino Acid %K Amino Acid Sequence %K Binding Sites %K Binding Sites: genetics %K Catalytic Domain %K Computer Simulation %K DNA %K DNA: chemistry %K DNA: genetics %K DNA: metabolism %K Humans %K Kinetics %K Models %K Molecular %K Molecular Sequence Data %K Nucleic Acid Conformation %K Nucleic Acid Heteroduplexes %K Nucleic Acid Heteroduplexes: chemistry %K Nucleic Acid Heteroduplexes: genetics %K Nucleic Acid Heteroduplexes: metabolism %K Polymerization %K Protein Binding %K Protein Structure %K RNA %K RNA: chemistry %K RNA: genetics %K RNA: metabolism %K Secondary %K Sequence Homology %K Telomerase %K Telomerase: chemistry %K Telomerase: genetics %K Telomerase: metabolism %K Telomere %K Telomere: chemistry %K Telomere: genetics %K Telomere: metabolism %K Tertiary %X Telomerases constitute a group of specialized ribonucleoprotein enzymes that remediate chromosomal shrinkage resulting from the "end-replication" problem. Defects in telomere length regulation are associated with several diseases as well as with aging and cancer. Despite significant progress in understanding the roles of telomerase, the complete structure of the human telomerase enzyme bound to telomeric DNA remains elusive, with the detailed molecular mechanism of telomere elongation still unknown. By application of computational methods for distant homology detection, comparative modeling, and molecular docking, guided by available experimental data, we have generated a three-dimensional structural model of a partial telomerase elongation complex composed of three essential protein domains bound to a single-stranded telomeric DNA sequence in the form of a heteroduplex with the template region of the human RNA subunit, TER. This model provides a structural mechanism for the processivity of telomerase and offers new insights into elongation. We conclude that the RNADNA heteroduplex is constrained by the telomerase TEN domain through repeated extension cycles and that the TEN domain controls the process by moving the template ahead one base at a time by translation and rotation of the double helix. The RNA region directly following the template can bind complementarily to the newly synthesized telomeric DNA, while the template itself is reused in the telomerase active site during the next reaction cycle. This first structural model of the human telomerase enzyme provides many details of the molecular mechanism of telomerase and immediately provides an important target for rational drug design. %B Proceedings of the National Academy of Sciences of the United States of America %V 108 %P 9443–8 %8 jun %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3111281&tool=pmcentrez&rendertype=abstract %R 10.1073/pnas.1015399108 %0 Journal Article %J Proteins %D 2011 %T Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models %A Pawel Gniewek %A Sumudu P. Leelananda %A Andrzej Koliński %A Robert L. Jernigan %A Andrzej Kloczkowski %K Amino Acids %K Amino Acids: chemistry %K Computational Biology %K Computational Biology: methods %K Models %K Molecular %K Protein Conformation %K Proteins %K Proteins: chemistry %X 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 'R'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. %B Proteins %V 79 %P 1923–9 %8 jun %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3093657&tool=pmcentrez&rendertype=abstract %R 10.1002/prot.23015 %0 Book Section %B Multiscale Approaches to Protein Modeling %D 2011 %T Multiscale approach to protein folding dynamics %A Sebastian Kmiecik %A Michal Jamroz %A Andrzej Koliński %A Andrzej Koliński %K coarse-grained modeling %K Molecular Dynamics Simulation %K protein dynamics %X Dynamic behavior of proteins is a key factor for understanding the functions of a living cell. Description of the conformational transitions of proteins remains extremely difficult for the computational simulation as well as the experimental techniques. No technique is able to span extremely short dynamic events together with long-timescale processes when the most interesting transitions occur. Thus new methods for simulation and utilization of all accessible experimental data are needed. The advances in the development of hybrid models, which attempt to combine a simplified modeling efficiency with atomic resolution accuracy, should provide new opportunities for the use of computer simulation in the integration of different kinds of data to study folding dynamics at relevant timescales. This review outlines the advances in description of protein dynamics and discusses recent applications of the CABS-reduced modeling tool to the studies of protein folding dynamics. %B Multiscale Approaches to Protein Modeling %I Springer %C New York %P 281-294 %G eng %0 Book Section %B Multiscale Approaches to Protein Modeling %D 2011 %T Multiscale protein and peptide docking %A Mateusz Kurcinski %A Michal Jamroz %A Andrzej Koliński %X The number of functional protein complexes in a cell is larger by an order of magnitude than the number of proteins. The experimentally determined three-dimensional structures exist for only a very small fraction of these complexes. Thus, the methods for theoretical prediction of structures of protein assemblies are extremely important for molecular biology. Association of two (or more proteins) always induces conformational changes of the individual components. In many cases, these induced changes are relatively small and involve mostly the side chains at the association interface. In such cases, the approaches of rigid-body docking of two (or more) structures are quite successful. Quite frequently, however, the docking-induced conformational changes are significant. In such cases, prediction of the resulting structures is extremely challenging. The cases, where experimental structures of some components do not exist, are yet even more difficult. In this chapter, we briefly overview the existing in silico docking methods and describe a multiscale strategy of unrestricted flexible docking of proteins and peptides. %B Multiscale Approaches to Protein Modeling %I Springer %C New York %P 21-34 %G eng %0 Journal Article %J BMC Structural Biology %D 2010 %T Modeling of loops in proteins: a multi-method approach %A Michal Jamroz %A Andrzej Koliński %K Databases %K Models %K Molecular %K Protein %K Protein Structure %K Proteins %K Proteins: chemistry %K Software %K Tertiary %X BACKGROUND: Template-target sequence alignment and loop modeling are key components of protein comparative modeling. Short loops can be predicted with high accuracy using structural fragments from other, not necessairly homologous proteins, or by various minimization methods. For longer loops multiscale approaches employing coarse-grained de novo modeling techniques should be more effective. RESULTS: For a representative set of protein structures of various structural classes test predictions of loop regions have been performed using MODELLER, ROSETTA, and a CABS coarse-grained de novo modeling tool. Loops of various length, from 4 to 25 residues, were modeled assuming an ideal target-template alignment of the remaining portions of the protein. It has been shown that classical modeling with MODELLER is usually better for short loops, while coarse-grained de novo modeling is more effective for longer loops. Even very long missing fragments in protein structures could be effectively modeled. Resolution of such models is usually on the level 2-6 A, which could be sufficient for guiding protein engineering. Further improvement of modeling accuracy could be achieved by the combination of different methods. In particular, we used 10 top ranked models from sets of 500 models generated by MODELLER as multiple templates for CABS modeling. On average, the resulting molecular models were better than the models from individual methods. CONCLUSIONS: Accuracy of protein modeling, as demonstrated for the problem of loop modeling, could be improved by the combinations of different modeling techniques. %B BMC Structural Biology %V 10 %P 5 %8 jan %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2837870&tool=pmcentrez&rendertype=abstract %R 10.1186/1472-6807-10-5 %0 Conference Proceedings %B International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation %D 2010 %T Protein secondary structure prediction using knowledge-based potentials %A Saras Saraswathi %A Robert L. Jernigan %A Andrzej Kloczkowski %A Andrzej Koliński %B International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation %P 370-375 %8 2010 %G eng %0 Journal Article %J Journal of Structural and Functional Genomics %D 2009 %T Distance matrix-based approach to protein structure prediction %A Andrzej Kloczkowski %A Robert L. Jernigan %A Zhijun Wu %A Guang Song %A Lei Yang %A Andrzej Koliński %A Piotr Pokarowski %K Binding Sites %K Computer Simulation %K Databases %K Models %K Molecular %K Principal Component Analysis %K Protein %K Protein Conformation %K Proteins %K Proteins: chemistry %X

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)–the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the dynamics. After structure matching, we apply principal component analysis (PCA) to obtain the important apparent motions for both bound and unbound structures. There are significant similarities between the first few key motions and the first few low-frequency normal modes calculated from a static representative structure with an elastic network model (ENM) that is based on the contact matrix C (related to D), strongly suggesting that the variations among the observed structures and the corresponding conformational changes are facilitated by the low-frequency, global motions intrinsic to the structure. Similarities are also found when the approach is applied to an NMR ensemble, as well as to atomic molecular dynamics (MD) trajectories. Thus, a sufficiently large number of experimental structures can directly provide important information about protein dynamics, but ENM can also provide a similar sampling of conformations. Finally, we use distance constraints from databases of known protein structures for structure refinement. We use the distributions of distances of various types in known protein structures to obtain the most probable ranges or the mean-force potentials for the distances. We then impose these constraints on structures to be refined or include the mean-force potentials directly in the energy minimization so that more plausible structural models can be built. This approach has been successfully used by us in 2006 in the CASPR structure refinement (http://predictioncenter.org/caspR).

%B Journal of Structural and Functional Genomics %V 10 %P 67–81 %8 mar %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3018873&tool=pmcentrez&rendertype=abstract %R 10.1007/s10969-009-9062-2 %0 Conference Proceedings %B From Computational Biophysics to Systems Biology (CBSB08) %D 2008 %T Designing an Automatic Pipeline for Protein Structure Prediction Designing an Automatic Pipeline for Protein Structure Prediction %A Sebastian Kmiecik %A Michal Jamroz %A Anna Zwolinska %A Pawel Gniewek %A Andrzej Koliński %A Ulrich H. E. Hansmann %A Jan H. Meinke %A Sandipan Mohanty %A Walter Nadler %A Olav Zimmermann %X Building accurate 3D structural models of proteins and protein assemblies is a challenging task. Our modeling technology is based on the CABS model, extensively tested, state-of-theart approach to protein structure prediction. The modeling process is divided into two stages: CABS fold assembly followed by the model refinement/selection procedure, using an all-atom representation and a more exact interaction scheme enabling high resolution structure prediction. Fold assembly can be done in a framework of a standard comparative modeling procedure, where spatial restraints are derived from alternative sequence alignments with a template/ templates. Preferentially in more difficult modeling cases, a new approach to comparative modeling can be used, which does not require the prior alignment. Selvita’s goal is to provide an integrated tool-kit for automated protein structure predictions. However, like blind prediction experiments show, due to high complexity of prediction tasks, fully automated approach often doesn’t guarantee the highest possible performance. Therefore, human intervention is made possible at every stage of modeling. %B From Computational Biophysics to Systems Biology (CBSB08) %V 40 %P 105–108 %@ 9783981084368 %G eng %0 Journal Article %J Biophysical journal %D 2008 %T Predicting the complex structure and functional motions of the outer membrane transporter and signal transducer FecA %A Taner Z. Sen %A Margaret Kloster %A Robert L. Jernigan %A Andrzej Koliński %A Janusz M. Bujnicki %A Andrzej Kloczkowski %K Cell Membrane %K Cell Membrane: chemistry %K Cell Surface %K Cell Surface: chemistry %K Cell Surface: ultrastructure %K Chemical %K Computer Simulation %K Escherichia coli Proteins %K Escherichia coli Proteins: chemistry %K Escherichia coli Proteins: ultrastructure %K Models %K Molecular %K Motion %K Protein Conformation %K Receptors %X Escherichia coli requires an efficient transport and signaling system to successfully sequester iron from its environment. FecA, a TonB-dependent protein, serves a critical role in this process: first, it binds and transports iron in the form of ferric citrate, and second, it initiates a signaling cascade that results in the transcription of several iron transporter genes in interaction with inner membrane proteins. The structure of the plug and barrel domains and the periplasmic N-terminal domain (NTD) are separately available. However, the linker connecting the plug and barrel and the NTD domains is highly mobile, which may prevent the determination of the FecA structure as a whole assembly. Here, we reduce the conformation space of this linker into most probable structural models using the modeling tool CABS, then apply normal-mode analysis to investigate the motions of the whole structure of FecA by using elastic network models. We relate the FecA domain motions to the outer-inner membrane communication, which initiates transcription. We observe that the global motions of FecA assign flexibility to the TonB box and the NTD, and control the exposure of the TonB box for binding to the TonB inner membrane protein, suggesting how these motions relate to FecA function. Our simulations suggest the presence of a communication between the loops on both ends of the protein, a signaling mechanism by which a signal could be transmitted by conformational transitions in response to the binding of ferric citrate. %B Biophysical journal %I Elsevier %V 94 %P 2482–91 %8 apr %@ 5152944294 %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2267147&tool=pmcentrez&rendertype=abstract %R 10.1529/biophysj.107.116046 %0 Journal Article %J Proteins %D 2008 %T Predicting the order in which contacts are broken during single molecule protein stretching experiments. %A Joanna I. Sulkowska %A Kloczkowski, Andrzej %A Sen, Taner Z %A Cieplak, Marek %A Jernigan, Robert L %K Green Fluorescent Proteins %K Models, Chemical %K Protein Denaturation %K Proteins %K Tensile Strength %X We combine two methods to enable the prediction of the order in which contacts are broken under external stretching forces in single molecule experiments. These two methods are Gō-like models and elastic network models. The Gō-like models have shown remarkable success in representing many aspects of protein behavior, including the reproduction of experimental data obtained from atomic force microscopy. The simple elastic network models are often used successfully to predict the fluctuations of residues around their mean positions, comparing favorably with the experimentally measured crystallographic B-factors. The behavior of biomolecules under external forces has been demonstrated to depend principally on their elastic properties and the overall shape of their structure. We have studied in detail the muscle protein titin and green fluorescent protein and tested for ten other proteins. First, we stretch the proteins computationally by performing stochastic dynamics simulations with the Gō-like model. We obtain the force-displacement curves and unfolding scenarios of possible mechanical unfolding. We then use the elastic network model to calculate temperature factors (B-factors) and compare the slowest modes of motion for the stretched proteins and compare them with the predicted order of breaking contacts between residues in the Gō-like model. Our results show that a simple Gaussian network model is able to predict contacts that break in the next time stage of stretching. Additionally, we have found that the contact disruption is strictly correlated with the highest force exerted by the backbone on these residues. Our prediction of bond-breaking agrees well with the unfolding scenario obtained with the Gō-like model. We anticipate that this method will be a useful new tool for interpreting stretching experiments. %B Proteins %V 71 %P 45-60 %8 2008 Apr %G eng %N 1 %R 10.1002/prot.21652 %0 Journal Article %J Proteins: Structure, Function, Bioinformatics %D 2007 %T Ideal amino acid exchange forms for approximating substitution matrices %A Piotr Pokarowski %A Andrzej Kloczkowski %A Szymon Nowakowski %A Maria Pokarowska %A Robert L. Jernigan %A Andrzej Koliński %K protein contact potentials %K protein structure prediction %K Sequence Alignment %K substitution matrices %X We have analyzed 29 published substitution matrices (SMs) and five statistical protein contact potentials (CPs) for comparison. We find that popular, ‘classical’ SMs obtained mainly from sequence alignments of globular proteins are mostly correlated by at least a value of 0.9. The BLOSUM62 is the central element of this group. A second group includes SMs derived from alignments of remote homologs or transmembrane proteins. These matrices correlate better with classical SMs (0.8) than among themselves (0.7). A third group consists of intermediate links between SMs and CPs - matrices and potentials that exhibit mutual correlations of at least 0.8. Next, we show that SMs can be approximated with a correlation of 0.9 by expressions c0 + xixj + yiyj + zizj, 1≤ i, j ≤ 20, where c0 is a constant and the vectors (xi), (yi), (zi) correlate highly with hydrophobicity, molecular volume and coil preferences of amino acids, respectively. The present paper is the continuation of our work (Pokarowski et al., Proteins 2005;59:49–57), where similar approximation were used to derive ideal amino acid interaction forms from CPs. Both approximations allow us to understand general trends in amino acid similarity and can help improve multiple sequence alignments using the fast Fourier transform (MAFFT), fast threading or another methods based on alignments of physicochemical profiles of protein sequences. The use of this approximation in sequence alignments instead of a classical SM yields results that differ by less than 5%. Intermediate links between SMs and CPs, new formulas for approximating these matrices, and the highly significant dependence of classical SMs on coil preferences are new findings. %B Proteins: Structure, Function, Bioinformatics %V 69 %P 379–393 %G eng %U http://onlinelibrary.wiley.com/doi/10.1002/prot.21509/full %R 10.1002/prot %0 Journal Article %J Proteins %D 2005 %T Inferring ideal amino acid interaction forms from statistical protein contact potentials %A Piotr Pokarowski %A Andrzej Kloczkowski %A Robert L. Jernigan %A Neha S. Kothari %A Maria Pokarowska %A Andrzej Koliński %K Amino Acids %K Amino Acids: chemistry %K Binding Sites %K Models %K Molecular %K Proteins %K Proteins: chemistry %K Statistical %K Theoretical %X We have analyzed 29 different published matrices of protein pairwise contact potentials (CPs) between amino acids derived from different sets of proteins, either crystallographic structures taken from the Protein Data Bank (PDB) or computer-generated decoys. Each of the CPs is similar to 1 of the 2 matrices derived in the work of Miyazawa and Jernigan (Proteins 1999;34:49-68). The CP matrices of the first class can be approximated with a correlation of order 0.9 by the formula e(ij) = h(i) + h(j), 1