Magdalena A. Mozolewska
University of Gdańsk
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Featured researches published by Magdalena A. Mozolewska.
Proceedings of the National Academy of Sciences of the United States of America | 2013
Yi He; Magdalena A. Mozolewska; Paweł Krupa; Adam K. Sieradzan; Tomasz Wirecki; Adam Liwo; Khatuna Kachlishvili; Shalom Rackovsky; Dawid Jagieła; Rafał Ślusarz; Cezary Czaplewski; Stanisław Ołdziej; Harold A. Scheraga
Significance With the example of the coarse-grained United Residue model of polypeptide chains, this paper demonstrates that the physics-based approach for protein-structure prediction can lead to exceptionally good results when correct domain packing is an issue, even for a highly homologous target. The reason for this is probably that emphasis is placed on energetically favorable residue–residue interactions, including those with residues in relatively flexible linker regions; these regions are usually very different in the target compared with those of proteins in the databases used for template-based modeling. The results suggest that a combination of bioinformatics and a physics-based approach could result in a major increase in the prediction capacity of existing approaches. The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families determined by multiplexed replica-exchange simulations, from the 10th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180° in the experimental structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physics-based method has substantial predictive power. In particular, it has the ability to predict domain–domain orientations, which is a significant advance in the state of the art.
Journal of Molecular Modeling | 2014
Adam Liwo; Maciej Baranowski; Cezary Czaplewski; Ewa I. Gołaś; Yi He; Dawid Jagieła; Paweł Krupa; Maciej Maciejczyk; Mariusz Makowski; Magdalena A. Mozolewska; Andrei Niadzvedtski; Stanisław Ołdziej; Harold A. Scheraga; Adam K. Sieradzan; Rafał Ślusarz; Tomasz Wirecki; Yanping Yin; Bartłomiej Zaborowski
AbstractA unified coarse-grained model of three major classes of biological molecules—proteins, nucleic acids, and polysaccharides—has been developed. It is based on the observations that the repeated units of biopolymers (peptide groups, nucleic acid bases, sugar rings) are highly polar and their charge distributions can be represented crudely as point multipoles. The model is an extension of the united residue (UNRES) coarse-grained model of proteins developed previously in our laboratory. The respective force fields are defined as the potentials of mean force of biomacromolecules immersed in water, where all degrees of freedom not considered in the model have been averaged out. Reducing the representation to one center per polar interaction site leads to the representation of average site–site interactions as mean-field dipole–dipole interactions. Further expansion of the potentials of mean force of biopolymer chains into Kubo’s cluster-cumulant series leads to the appearance of mean-field dipole–dipole interactions, averaged in the context of local interactions within a biopolymer unit. These mean-field interactions account for the formation of regular structures encountered in biomacromolecules, e.g., α-helices and β-sheets in proteins, double helices in nucleic acids, and helicoidally packed structures in polysaccharides, which enables us to use a greatly reduced number of interacting sites without sacrificing the ability to reproduce the correct architecture. This reduction results in an extension of the simulation timescale by more than four orders of magnitude compared to the all-atom representation. Examples of the performance of the model are presented. FigureComponents of the Unified Coarse Grained Model (UCGM) of biological macromolecules
Proteins | 2014
George A. Khoury; Adam Liwo; Firas Khatib; Hongyi Zhou; Gaurav Chopra; Jaume Bacardit; Leandro Oliveira Bortot; Rodrigo Antonio Faccioli; Xin Deng; Yi He; Paweł Krupa; Jilong Li; Magdalena A. Mozolewska; Adam K. Sieradzan; James Smadbeck; Tomasz Wirecki; Seth Cooper; Jeff Flatten; Kefan Xu; David Baker; Jianlin Cheng; Alexandre C. B. Delbem; Christodoulos A. Floudas; Chen Keasar; Michael Levitt; Zoran Popović; Harold A. Scheraga; Jeffrey Skolnick; Silvia Crivelli; Foldit Players
The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social‐media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at “coopetition” in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org. Proteins 2014; 82:1850–1868.
Proteins | 2015
Magdalena A. Mozolewska; Paweł Krupa; Harold A. Scheraga; Adam Liwo
The iron‐sulfur protein 1 (Isu1) and the J‐type co‐chaperone Jac1 from yeast are part of a huge ATP‐dependent system, and both interact with Hsp70 chaperones. Interaction of Isu1 and Jac1 is a part of the iron‐sulfur cluster biogenesis system in mitochondria. In this study, the structure and dynamics of the yeast Isu1–Jac1 complex has been modeled. First, the complete structure of Isu1 was obtained by homology modeling using the I‐TASSER server and YASARA software and thereafter tested for stability in the all‐atom force field AMBER. Then, the known experimental structure of Jac1 was adopted to obtain initial models of the Isu1–Jac1 complex by using the ZDOCK server for global and local docking and the AutoDock software for local docking. Three most probable models were subsequently subjected to the coarse‐grained molecular dynamics simulations with the UNRES force field to obtain the final structures of the complex. In the most probable model, Isu1 binds to the left face of the Γ‐shaped Jac1 molecule by the β‐sheet section of Isu1. Residues L105, L109, and Y163 of Jac1 have been assessed by mutation studies to be essential for binding (Ciesielski et al., J Mol Biol 2012; 417:1–12). These residues were also found, by UNRES/molecular dynamics simulations, to be involved in strong interactions between Isu1 and Jac1 in the complex. Moreover, N95, T98, P102, H112, V159, L167, and A170 of Jac1, not yet tested experimentally, were also found to be important in binding. Proteins 2015; 83:1414–1426.
Journal of Chemical Information and Modeling | 2015
Paweł Krupa; Magdalena A. Mozolewska; Keehyoung Joo; Jooyoung Lee; Cezary Czaplewski; Adam Liwo
A new approach to the prediction of protein structures that uses distance and backbone virtual-bond dihedral angle restraints derived from template-based models and simulations with the united residue (UNRES) force field is proposed. The approach combines the accuracy and reliability of template-based methods for the segments of the target sequence with high similarity to those having known structures with the ability of UNRES to pack the domains correctly. Multiplexed replica-exchange molecular dynamics with restraints derived from template-based models of a given target, in which each restraint is weighted according to the accuracy of the prediction of the corresponding section of the molecule, is used to search the conformational space, and the weighted histogram analysis method and cluster analysis are applied to determine the families of the most probable conformations, from which candidate predictions are selected. To test the capability of the method to recover template-based models from restraints, five single-domain proteins with structures that have been well-predicted by template-based methods were used; it was found that the resulting structures were of the same quality as the best of the original models. To assess whether the new approach can improve template-based predictions with incorrectly predicted domain packing, four such targets were selected from the CASP10 targets; for three of them the new approach resulted in significantly better predictions compared with the original template-based models. The new approach can be used to predict the structures of proteins for which good templates can be found for sections of the sequence or an overall good template can be found for the entire sequence but the prediction quality is remarkably weaker in putative domain-linker regions.
Journal of Molecular Modeling | 2015
Agnieszka G. Lipska; Adam K. Sieradzan; Paweł Krupa; Magdalena A. Mozolewska; Sabato d’Auria; Adam Liwo
The arginine-binding protein (ArgBP) from the hyperthermophilic eubacterium Thermotoga maritima (TmArgBP) is responsible for arginine transport through the bacterial cell membrane. The protein binds a single molecule of l-arginine, which results in conformational changes due to hinge bending. Thereby, TmArgBP acquires one of two possible conformations: open (without the presence of the arginine ligand) and closed (in the presence of the arginine ligand). Here we report a molecular dynamics study of the influence of the presence or absence of the ligand on the dynamics of TmArgBP, using the coarse-grained UNRES force field. The results of our studies indicate that binding of the arginine ligand promotes a closed conformation, which agrees with experimental data. However, the sensitivity of the TmArgBP conformation to the presence of arginine decreases and the protein becomes more flexible with increasing temperature, which might be related to the functionality of this protein in the thermophilic organism T. maritima.
Proteins | 2018
Agnieszka Karczyńska; Magdalena A. Mozolewska; Paweł Krupa; Artur Giełdoń; Adam Liwo; Cezary Czaplewski
A new approach to assisted protein–structure prediction has been proposed, which is based on running multiplexed replica exchange molecular dynamics simulations with the coarse‐grained UNRES force field with restraints derived from knowledge‐based models and distance distribution from small angle X‐ray scattering (SAXS) measurements. The latter restraints are incorporated into the target function as a maximum‐likelihood term that guides the shape of the simulated structures towards that defined by SAXS. The approach was first verified with the 1KOY protein, for which the distance distribution was calculated from the experimental structure, and subsequently used to predict the structures of 11 data‐assisted targets in the CASP12 experiment. Major improvement of the GDT_TS was obtained for 2 targets, minor improvement for other 2 while, for 6 target GDT_TS deteriorated compared with that calculated for predictions without the SAXS data, partly because of assuming a wrong multimeric state (for Ts866) or because the crystal conformation was more compact than the solution conformation (for Ts942). Particularly good results were obtained for Ts909, in which use of SAXS data resulted in the selection of a correctly packed trimer and, subsequently, increased the GDT_TS of monomer prediction. It was found that running simulations with correct oligomeric state is essential for the success in SAXS‐data‐assisted prediction.
Journal of Biomolecular Structure & Dynamics | 2017
Magdalena A. Mozolewska; Adam K. Sieradzan; Andrei Niadzvedstki; Cezary Czaplewski; Adam Liwo; Paweł Krupa
Thurincin H is a small protein produced by Bacillus thuringiensis SF361 with gram-positive antimicrobial properties. The toxins produced by B. thuringiensis are widely used in the agriculture as, e.g. natural preservatives in dairy products. The structure of thurincin H possesses four covalent sulfur to -carbon bonds that involve the cysteine side-chains; these bonds are probably responsible for the shape and stability of the protein and, thereby, for its antimicrobial properties. To examine the influence of the formation of the sulfur-carbon bonds on the folding pathways and stability of the protein, a series of canonical and multiplexed replica-exchange simulations with the coarse-grained UNRES force field was carried out without and with distance restraints imposed on selected S-C atom pairs. It was found that the order of the formation and breaking of the S-C thioether bonds significantly impacts on the foldability and stability of the thurincin H. It was also observed that thioether bridges play a major role in stabilizing the global fold of the protein, although it significantly diminishes the entropy of the system. The maximum foldability of thurincin H was observed in the presence of the optimal set of three out of four thioether bridges. Thus, the results suggest that the presence of ThnB enzyme and other agents that catalyze the formation of thioether bridges can be essential for correct folding of thurincin H and that the formation of the fourth bridge does not seem to facilitate folding; instead, it seems to rigidify the loop and prevent proteolysis.
Scientific Reports | 2018
Michal Dabrowski; Michał Dramiński; Klev Diamanti; Karolina Stepniak; Magdalena A. Mozolewska; Paweł Teisseyre; Jacek Koronacki; Jan Komorowski; Bozena Kaminska; Bartosz Wojtas
In order to find clinically useful prognostic markers for glioma patients’ survival, we employed Monte Carlo Feature Selection and Interdependencies Discovery (MCFS-ID) algorithm on DNA methylation (HumanMethylation450 platform) and RNA-seq datasets from The Cancer Genome Atlas (TCGA) for 88 patients observed until death. The input features were ranked according to their importance in predicting patients’ longer (400+ days) or shorter (≤400 days) survival without prior classification of the patients. Interestingly, out of the 65 most important features found, 63 are methylation sites, and only two mRNAs. Moreover, 61 out of the 63 methylation sites are among those detected by the 450 k array technology, while being absent in the HumanMethylation27. The most important methylation feature (cg15072976) overlaps with the RE1 Silencing Transcription Factor (REST) binding site, and was confirmed to intersect with the REST binding motif in human U87 glioma cells. Six additional methylation sites from the top 63 overlap with REST sites. We found that the methylation status of the cg15072976 site affects transcription factor binding in U87 cells in gel shift assay. The cg15072976 methylation status discriminates ≤400 and 400+ patients in an independent dataset from TCGA and shows positive association with survival time as evidenced by Kaplan-Meier plots.
Scientific Reports | 2018
Chen Keasar; Liam J. McGuffin; Björn Wallner; Gaurav Chopra; Badri Adhikari; Debswapna Bhattacharya; Lauren Blake; Leandro Oliveira Bortot; Renzhi Cao; B. K. Dhanasekaran; Itzhel Dimas; Rodrigo Antonio Faccioli; Eshel Faraggi; Robert Ganzynkowicz; Sambit Ghosh; Soma Ghosh; Artur Giełdoń; Lukasz Golon; Yi He; Lim Heo; Jie Hou; Main Khan; Firas Khatib; George A. Khoury; Chris A. Kieslich; David E. Kim; Paweł Krupa; Gyu Rie Lee; Hongbo Li; Jilong Li
Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.