@article {568, title = {Importance of Secondary Structure Data in Large Scale Protein Modeling using Low-Resolution SURPASS Method}, journal = {Methods in Molecular Biology, in press}, year = {2023}, author = {Aleksandra E. Badaczewska-Dawid and Andrzej Koli{\'n}ski} } @article {554, title = {Computational reconstruction of atomistic protein structures from coarse-grained models}, journal = {Computational and Structural Biotechnology Journal}, volume = {18}, year = {2020}, pages = {162-176}, abstract = {Three-dimensional protein structures, whether determined experimentally or theoretically, are often too low resolution. In this mini-review, we outline the computational methods for protein structure reconstruction from incomplete coarse-grained to all atomistic models. Typical reconstruction schemes can be divided into four major steps. Usually, the first step is reconstruction of the protein backbone chain starting from the C-alpha trace. This is followed by side-chains rebuilding based on protein backbone geometry. Subsequently, hydrogen atoms can be reconstructed. Finally, the resulting all-atom models may require structure optimization. Many methods are available to perform each of these tasks. We discuss the available tools and their potential applications in integrative modeling pipelines that can transfer coarse-grained information from computational predictions, or experiment, to all atomistic structures.}, keywords = {coarse-grained modeling, protein modeling, protein reconstruction, structure prediction, structure refinement}, issn = {2001-0370}, doi = {https://doi.org/10.1016/j.csbj.2019.12.007}, url = {http://www.sciencedirect.com/science/article/pii/S2001037019305537}, author = {Aleksandra E. Badaczewska-Dawid and Andrzej Koli{\'n}ski and Sebastian Kmiecik} } @article {561, title = {Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement}, journal = {Briefings in Bioinformatics}, year = {2020}, month = {06}, abstract = {The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein{\textendash}peptide complex structures and model scoring. We evaluated the proposed protocol on the set of seven different GPCR{\textendash}peptide complexes (including one containing a cyclic peptide), for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface root-mean-square-deviation measure.}, issn = {1477-4054}, doi = {10.1093/bib/bbaa109}, url = {https://doi.org/10.1093/bib/bbaa109}, author = {Aleksandra E. Badaczewska-Dawid and Sebastian Kmiecik and Michal Kolinski} } @article {553, title = {Flexible docking of peptides to proteins using CABS-dock}, journal = {Protein Science, 29:211-222}, year = {2020}, abstract = {Molecular docking of peptides to proteins can be a useful tool in the exploration of the possible peptide binding sites and poses. CABS-dock is a method for protein{\textendash}peptide docking that features significant conformational flexibility of both the peptide and the protein molecules during the peptide search for a binding site. The CABS-dock has been made available as a web server and a standalone package. The web server is an easy to use tool with a simple web interface. The standalone package is a command-line program dedicated to professional users. It offers a number of advanced features, analysis tools and support for large-sized systems. In this article, we outline the current status of the CABS-dock method, its recent developments, applications, and challenges ahead.}, keywords = {molecular modeling, peptide drugs, peptide therapeutics, protein{\textendash}peptide complex, protein{\textendash}peptide interactions, structure prediction}, doi = {10.1002/pro.3771}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pro.3771}, author = {Mateusz Kurcinski and Aleksandra E. Badaczewska-Dawid and Michal Kolinski and Andrzej Koli{\'n}ski and Sebastian Kmiecik} } @inbook {558, title = {Protocols for All-Atom Reconstruction and High-Resolution Refinement of Protein{\textendash}Peptide Complex Structures}, booktitle = {Protein Structure Prediction}, year = {2020}, pages = {273{\textendash}287}, publisher = {Springer US}, organization = {Springer US}, address = {New York, NY}, abstract = {Structural characterizations of protein{\textendash}peptide complexes may require further improvements. These may include reconstruction of missing atoms and/or structure optimization leading to higher accuracy models. In this work, we describe a workflow that generates accurate structural models of peptide{\textendash}protein complexes starting from protein{\textendash}peptide models in C-alpha representation generated using CABS-dock molecular docking. First, protein{\textendash}peptide models are reconstructed from their C-alpha traces to all-atom representation using MODELLER. Next, they are refined using Rosetta FlexPepDock. The described workflow allows for reliable all-atom reconstruction of CABS-dock models and their further improvement to high-resolution models.}, isbn = {978-1-0716-0708-4}, doi = {10.1007/978-1-0716-0708-4_16}, url = {https://doi.org/10.1007/978-1-0716-0708-4_16}, author = {Aleksandra E. Badaczewska-Dawid and Alisa Khramushin and Andrzej Koli{\'n}ski and Ora Schueler-Furman and Sebastian Kmiecik} } @inbook {557, title = {Protocols for Fast Simulations of Protein Structure Flexibility Using CABS-Flex and SURPASS}, booktitle = {Protein Structure Prediction}, year = {2020}, pages = {337{\textendash}353}, publisher = {Springer US}, organization = {Springer US}, address = {New York, NY}, abstract = {Conformational flexibility of protein structures can play an important role in protein function. The flexibility is often studied using computational methods since experimental characterization can be difficult. Depending on protein system size, computational tools may require large computational resources or significant simplifications in the modeled systems to speed up calculations. In this work, we present the protocols for efficient simulations of flexibility of folded protein structures that use coarse-grained simulation tools of different resolutions: medium, represented by CABS-flex, and low, represented by SUPRASS. We test the protocols using a set of 140 globular proteins and compare the results with structure fluctuations observed in MD simulations, ENM modeling, and NMR ensembles. As demonstrated, CABS-flex predictions show high correlation to experimental and MD simulation data, while SURPASS is less accurate but promising in terms of future developments.}, isbn = {978-1-0716-0708-4}, doi = {10.1007/978-1-0716-0708-4_20}, url = {https://doi.org/10.1007/978-1-0716-0708-4_20}, author = {Aleksandra E. Badaczewska-Dawid and Andrzej Koli{\'n}ski and Sebastian Kmiecik} } @article {547, title = {CABS-dock standalone: a toolbox for flexible protein-peptide docking}, journal = {Bioinformatics}, volume = {btz185}, year = {2019}, month = {03}, abstract = {CABS-dock standalone is a multiplatform Python package for protein-peptide docking with backbone flexibility. The main feature of the CABS-dock method is its ability to simulate significant backbone flexibility of the entire protein-peptide system in a reasonable computational time. In the default mode, the package runs a simulation of fully flexible peptide searching for a binding site on the surface of a flexible protein receptor. The flexibility level of the molecules may be defined by the user. Furthermore, the CABS-dock standalone application provides users with full control over the docking simulation from the initial setup to the analysis of results. The standalone version is an upgrade of the original web server implementation {\textendash} it introduces a number of customizable options, provides support for large-sized systems and offers a framework for deeper analysis of docking results.CABS-dock standalone is distributed under the MIT license, which is free for academic and non-profit users. It is implemented in Python and Fortran. The CABS-dock standalone source code, wiki with documentation and examples of use, and installation instructions for Linux, macOS, and Windows are available in the CABS-dock standalone repository at https://bitbucket.org/lcbio/cabsdock}, doi = {10.1093/bioinformatics/btz185}, url = {https://dx.doi.org/10.1093/bioinformatics/btz185}, author = {Maciej Ciemny and Tymoteusz Oleniecki and Aleksander Kuriata and Mateusz Kurcinski and Aleksandra E. Badaczewska-Dawid and Andrzej Koli{\'n}ski and Sebastian Kmiecik} } @article {546, title = {Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields}, journal = {International Journal of Molecular Sciences}, volume = {20}, year = {2019}, type = {Journal Article}, chapter = {606}, abstract = {The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling protein interactions, which involve disordered peptide partners or intrinsically disordered protein regions, and unfolded states of globular proteins. It is based on the CABS coarse-grained protein model that uses a Monte Carlo (MC) sampling scheme and a knowledge-based statistical force field. We review several case studies showing that description of protein disordered states resulting from CABS simulations is consistent with experimental data. The case studies comprise investigations of protein(-)peptide binding and protein folding processes. The CABS model has been recently made available as the simulation engine of multiscale modeling tools enabling studies of protein(-)peptide docking and protein flexibility. Those tools offer customization of the modeling process, driving the conformational search using distance restraints, reconstruction of selected models to all-atom resolution, and simulation of large protein systems in a reasonable computational time. Therefore, CABS can be combined in integrative modeling pipelines incorporating experimental data and other modeling tools of various resolution.}, keywords = {CABS model MC simulations coarse-grained disordered protein protein structure statistical force fields}, issn = {1422-0067 (Electronic) 1422-0067 (Linking)}, doi = {10.3390/ijms20030606}, url = {http://www.ncbi.nlm.nih.gov/pubmed/30708941}, author = {Maciej Ciemny and Aleksandra E. Badaczewska-Dawid and Monika Pikuzinska and Andrzej Koli{\'n}ski and Sebastian Kmiecik} }