%0 Book Section %B Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes, Springer Series in Bio-/Neuroinformatics, Adam Liwo, Ed. %D 2014 %T Coarse-Grained Modeling of Protein Dynamics %A Sebastian Kmiecik %A Jacek Wabik %A Michal Kolinski %A Maksim Kouza %A Andrzej Koliński %K coarse-grained modeling %K protein dynamics %X Simulations of protein dynamics may work on different levels of molecular detail. The levels of simplification (coarse-graining) can range from very low to atomic resolution and may concern different simulation aspects (including protein representation, interaction schemes or models of molecular motion). So-called coarse-grained (CG) models offer many advantages, unreachable by classical simulation tools, as demonstrated in numerous studies of protein dynamics. Followed by a brief introduction, we present example applications of CG models for efficient predictions of biophysical mechanisms. We discuss the following topics: mechanisms of chaperonin action, mechanical properties of proteins, membrane proteins, protein-protein interactions and intrinsically unfolded proteins. Presently, these areas represent emerging application fields of CG simulation models. %B Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes, Springer Series in Bio-/Neuroinformatics, Adam Liwo, Ed. %I Springer Berlin Heidelberg %V 1 %P 55-79 %G eng %R 10.1007/978-3-642-28554-7_3 %0 Journal Article %J Journal of Chemical Theory and Computation %D 2014 %T Mechanism of Folding and Binding of an Intrinsically Disordered Protein as Revealed by Ab Initio Simulations %A Mateusz Kurcinski %A Andrzej Koliński %A Sebastian Kmiecik %K CABS-dock %K coarse-grained modeling %K flexible docking %K intrinsically disordered proteins %K molecular docking %K peptide binding %K peptide folding %K protein dynamics %K protein-peptide docking %X A complex of the phosphorylated kinase-inducible domain (pKID) with its interacting domain (KIX) is a model system for studies of mechanisms by which intrinsically unfolded proteins perform their functions. These mechanisms are not fully understood. Using an efficient coarse-grained model, ab initio simulations were performed of the coupled folding and binding of the pKID to the KIX. The simulations start from an unbound, randomly positioned and disordered pKID structure. During the simulations the pKID chain and its position remain completely unrestricted, while the KIX backbone is limited to near-native fluctuations. Ab initio simulations of such large-scale conformational transitions, unaffected by any knowledge about the bound pKID structure, remain inaccessible to classical simulations. Our simulations recover an ensemble of transient encounter complexes in good agreement with experimental results. We find that a key folding and binding step is linked to the formation of weak native interactions between a preformed native-like fragment of a pKID helix and KIX surface. Once that nucleus forms, the pKID chain may condense from largely disordered encounter ensemble to a natively bound and ordered conformation. The observed mechanism is reminiscent of a nucleation-condensation model, a common scenario for folding of globular proteins. %B Journal of Chemical Theory and Computation %V 10 %P 2224–2231 %G eng %N 6 %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 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 International Journal of Molecular Sciences %D 2013 %T Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics %A Jacek Wabik %A Sebastian Kmiecik %A Dominik Gront %A Maksim Kouza %A Andrzej Koliński %K coarse-grained modeling %K molecular dynamics %K multiscale modeling %K protein dynamics %X We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a model system of protein folding. After reconstructing atomistic details, conformations derived from the CABS simulation were subjected to replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb force fields in explicit solvent. Such a combination accelerates system convergence several times in comparison with all-atom simulations starting from the extended chain conformation, demonstrated by the analysis of melting curves, the number of native-like conformations as a function of time and secondary structure propagation. The results strongly suggest that the proposed multiscale method could be an efficient and accurate tool for high-resolution studies of protein folding dynamics in larger systems. %B International Journal of Molecular Sciences %V 14 %P 9893–9905 %G eng %U http://www.mdpi.com/1422-0067/14/5/9893 %R 10.3390/ijms14059893 %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 The Journal of Physical Chemistry B %D 2012 %T From coarse-grained to atomic-level characterization of protein dynamics: transition state for the folding of B domain of protein A %A Sebastian Kmiecik %A Dominik Gront %A Maksim Kouza %A Andrzej Koliński %K coarse-grained modeling %K molecular dynamics %K multiscale modeling %K protein dynamics %X Atomic-level molecular dynamics simulations are widely used for the characterization of the structural dynamics of proteins; however, they are limited to shorter time scales than the duration of most of the relevant biological processes. Properly designed coarse-grained models that trade atomic resolution for efficient sampling allow access to much longer time-scales. In-depth understanding of the structural dynamics, however, must involve atomic details. In this study, we tested a method for the rapid reconstruction of all-atom models from $\alpha$ carbon atom positions in the application to convert a coarse-grained folding trajectory of a well described model system: the B domain of protein A. The results show that the method and the spatial resolution of the resulting coarse-grained models enable computationally inexpensive reconstruction of realistic all-atom models. Additionally, by means of structural clustering, we determined the most persistent ensembles of the key folding step, the transition state. Importantly, the analysis of the overall structural topologies suggests a dominant folding pathway. This, together with the all-atom characterization of the obtained ensembles, in the form of contact maps, matches the experimental results well. %B The Journal of Physical Chemistry B %V 116 %P 7026–32 %8 jun %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22486297 %R 10.1021/jp301720w %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 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 Journal Article %J Journal of the American Chemical Society %D 2011 %T Simulation of chaperonin effect on protein folding: a shift from nucleation-condensation to framework mechanism %A Sebastian Kmiecik %A Andrzej Koliński %K Chaperonins %K Chaperonins: metabolism %K Computational Biology %K Models %K Molecular %K Protein Conformation %K protein dynamics %K Protein Folding %K Protein Structure %K Staphylococcal Protein A %K Staphylococcal Protein A: chemistry %K Staphylococcal Protein A: metabolism %K Stochastic Processes %K Tertiary %X

The iterative annealing mechanism (IAM) of chaperonin-assisted protein folding is explored in a framework of a well-established coarse-grained protein modeling tool, which enables the study of protein dynamics in a time-scale well beyond classical all-atom molecular mechanics. The chaperonin mechanism of action is simulated for two paradigm systems of protein folding, B domain of protein A (BdpA) and B1 domain of protein G (GB1), and compared to chaperonin-free simulations presented here for BdpA and recently published for GB1. The prediction of the BdpA transition state ensemble (TSE) is in perfect agreement with experimental findings. It is shown that periodic distortion of the polypeptide chains by hydrophobic chaperonin interactions can promote rapid folding and leads to a decrease in folding temperature. It is also demonstrated how chaperonin action prevents kinetically trapped conformations and modulates the observed folding mechanisms from nucleation-condensation to a more framework-like.

%B Journal of the American Chemical Society %V 133 %P 10283–9 %8 jul %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3132998&tool=pmcentrez&rendertype=abstract %R 10.1021/ja203275f %0 Journal Article %J Biophysical Journal %D 2008 %T Folding pathway of the b1 domain of protein G explored by multiscale modeling %A Sebastian Kmiecik %A Andrzej Koliński %K Chemical %K coarse-grained modeling %K Computer Simulation %K Models %K Molecular %K Molecular Dynamics Simulation %K Nerve Tissue Proteins %K Nerve Tissue Proteins: chemistry %K Nerve Tissue Proteins: ultrastructure %K Protein Conformation %K protein dynamics %K Protein Folding %K Protein Structure %K Tertiary %X The understanding of the folding mechanisms of single-domain proteins is an essential step in the understanding of protein folding in general. Recently, we developed a mesoscopic CA-CB side-chain protein model, which was successfully applied in protein structure prediction, studies of protein thermodynamics, and modeling of protein complexes. In this research, this model is employed in a detailed characterization of the folding process of a simple globular protein, the B1 domain of IgG-binding protein G (GB1). There is a vast body of experimental facts and theoretical findings for this protein. Performing unbiased, ab initio simulations, we demonstrated that the GB1 folding proceeds via the formation of an extended folding nucleus, followed by slow structure fine-tuning. Remarkably, a subset of native interactions drives the folding from the very beginning. The emerging comprehensive picture of GB1 folding perfectly matches and extends the previous experimental and theoretical studies. %B Biophysical Journal %I Elsevier %V 94 %P 726–36 %8 feb %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2186257&tool=pmcentrez&rendertype=abstract %R 10.1529/biophysj.107.116095 %0 Journal Article %J Proceedings of the National Academy of Sciences of the United States of America %D 2007 %T Characterization of protein-folding pathways by reduced-space modeling %A Sebastian Kmiecik %A Andrzej Koliński %K Amino Acid Sequence %K coarse-grained modeling %K Computational Biology %K Computer Simulation %K Hydrophobic and Hydrophilic Interactions %K Models %K Molecular %K Molecular Dynamics Simulation %K Monte Carlo Method %K Protein Denaturation %K protein dynamics %K Protein Folding %K Protein Structure %K Proteins %K Proteins: chemistry %K Proteins: metabolism %K Temperature %K Tertiary %X Ab initio simulations of the folding pathways are currently limited to very small proteins. For larger proteins, some approximations or simplifications in protein models need to be introduced. Protein folding and unfolding are among the basic processes in the cell and are very difficult to characterize in detail by experiment or simulation. Chymotrypsin inhibitor 2 (CI2) and barnase are probably the best characterized experimentally in this respect. For these model systems, initial folding stages were simulated by using CA-CB-side chain (CABS), a reduced-space protein-modeling tool. CABS employs knowledge-based potentials that proved to be very successful in protein structure prediction. With the use of isothermal Monte Carlo (MC) dynamics, initiation sites with a residual structure and weak tertiary interactions were identified. Such structures are essential for the initiation of the folding process through a sequential reduction of the protein conformational space, overcoming the Levinthal paradox in this manner. Furthermore, nucleation sites that initiate a tertiary interactions network were located. The MC simulations correspond perfectly to the results of experimental and theoretical research and bring insights into CI2 folding mechanism: unambiguous sequence of folding events was reported as well as cooperative substructures compatible with those obtained in recent molecular dynamics unfolding studies. The correspondence between the simulation and experiment shows that knowledge-based potentials are not only useful in protein structure predictions but are also capable of reproducing the folding pathways. Thus, the results of this work significantly extend the applicability range of reduced models in the theoretical study of proteins. %B Proceedings of the National Academy of Sciences of the United States of America %V 104 %P 12330–5 %8 jul %G eng %U http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1941469&tool=pmcentrez&rendertype=abstract %R 10.1073/pnas.0702265104 %0 Book Section %B Advances in Chemical Physics: Monte Carlo Methods in Chemical Physics %D 1999 %T Monte Carlo approaches to the protein folding problem %A Jeffrey Skolnick %A Andrzej Koliński %K cooperativity %K dynamic Monte Carlo dynamics %K Peptides %K protein dynamics %K protein-folding dynamics %B Advances in Chemical Physics: Monte Carlo Methods in Chemical Physics %I John Wiley & Sons %C Hoboken, NJ, USA %V 105 %P 203–242 %@ 9780471196303 %G eng %U http://cssb.biology.gatech.edu/skolnick/publications/pdffiles/159.pdf