Protein-peptide docking using CABS-dock and contact information.

CABS-dock is a computational method for protein-peptide molecular docking that does not require predefinition of the binding site. The peptide is treated as fully flexible, while the protein backbone undergoes small fluctuations and, optionally, large-scale rearrangements. Here, we present a specific CABS-dock protocol that enhances the docking procedure using fragmentary information about protein-peptide contacts. The contact information is used to narrow down the search for the binding peptide pose to the proximity of the binding site. We used information on a single-chosen and randomly chosen native protein-peptide contact to validate the protocol on the peptiDB benchmark. The contact information significantly improved CABS-dock performance. The protocol has been made available as a new feature of the CABS-dock web server (at http://biocomp.chem.uw.edu.pl/CABSdock/). SHORT ABSTRACT: CABS-dock is a tool for flexible docking of peptides to proteins. In this article, we present a protocol for CABS-dock docking driven by information about protein-peptide contact(s). Using information on individual protein-peptide contacts allows to improve the accuracy of CABS-dock docking.

CABS-flex standalone: a simulation environment for fast modeling of protein flexibility.

SUMMARY: CABS-flex standalone is a Python package for fast simulations of protein structure flexibility. The package combines simulations of protein dynamics using CABS coarse-grained protein model with the reconstruction of selected models to all-atom representation and analysis of modeling results. CABS-flex standalone is designed to allow for command-line access to the CABS computations and complete control over simulation process. CABS-flex standalone is equipped with features such as: modeling of multimeric and large-size protein systems, contact map visualizations, analysis of similarities to the reference structure and configurable modeling protocol. For instance, the user may modify the simulation parameters, distance restraints, structural clustering scheme or all-atom reconstruction parameters. With these features CABS-flex standalone can be easily incorporated into other methodologies of structural biology. AVAILABILITY AND IMPLEMENTATION: CABS-flex standalone is distributed under the MIT license, which is free for academic and non-profit users. It is implemented in Python. CABS-flex source code, wiki with examples of use and installation instructions for Linux, macOS and Windows are available from the CABS-flex standalone repository at https://bitbucket.org/lcbio/cabsflex.

CABS-dock standalone: a toolbox for flexible protein-peptide docking.

SUMMARY: 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-it introduces a number of customizable options, provides support for large-sized systems and offers a framework for deeper analysis of docking results. AVAILABILITY AND IMPLEMENTATION: CABS-dock standalone is distributed under the MIT licence, 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.

CABS-flex 2.0: a web server for fast simulations of flexibility of protein structures.

Classical simulations of protein flexibility remain computationally expensive, especially for large proteins. A few years ago, we developed a fast method for predicting protein structure fluctuations that uses a single protein model as the input. The method has been made available as the CABS-flex web server and applied in numerous studies of protein structure-function relationships. Here, we present a major update of the CABS-flex web server to version 2.0. The new features include: extension of the method to significantly larger and multimeric proteins, customizable distance restraints and simulation parameters, contact maps and a new, enhanced web server interface. CABS-flex 2.0 is freely available at http://biocomp.chem.uw.edu.pl/CABSflex2.

Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields.

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.

Modeling EphB4-EphrinB2 protein-protein interaction using flexible docking of a short linear motif.

BACKGROUND: Many protein-protein interactions are mediated by a short linear motif. Usually, amino acid sequences of those motifs are known or can be predicted. It is much harder to experimentally characterize or predict their structure in the bound form. In this work, we test a possibility of using flexible docking of a short linear motif to predict the interaction interface of the EphB4-EphrinB2 complex (a system extensively studied for its significance in tumor progression). METHODS: In the modeling, we only use knowledge about the motif sequence and experimental structures of EphB4-EphrinB2 complex partners. The proposed protocol enables efficient modeling of significant conformational changes in the short linear motif fragment during molecular docking simulation. For the docking simulations, we use the CABS-dock method for docking fully flexible peptides to flexible protein receptors (available as a server at http://biocomp.chem.uw.edu.pl/CABSdock/ ). Based on the docking result, the protein-protein complex is reconstructed and refined. RESULTS: Using this novel protocol, we obtained an accurate EphB4-EphrinB2 interaction model. CONCLUSIONS: The results show that the CABS-dock method may be useful as the primary docking tool in specific protein-protein docking cases similar to EphB4-EphrinB2 complex-that is, where a short linear motif fragment can be identified.

A protocol for CABS-dock protein-peptide docking driven by side-chain contact information.

BACKGROUND: The characterization of protein-peptide interactions is a challenge for computational molecular docking. Protein-peptide docking tools face at least two major difficulties: (1) efficient sampling of large-scale conformational changes induced by binding and (2) selection of the best models from a large set of predicted structures. In this paper, we merge an efficient sampling technique with external information about side-chain contacts to sample and select the best possible models. METHODS: In this paper we test a new protocol that uses information about side-chain contacts in CABS-dock protein-peptide docking. As shown in our recent studies, CABS-dock enables efficient modeling of large-scale conformational changes without knowledge about the binding site. However, the resulting set of binding sites and poses is in many cases highly diverse and difficult to score. RESULTS: As we demonstrate here, information about a single side-chain contact can significantly improve the prediction accuracy. Importantly, the imposed constraints for side-chain contacts are quite soft. Therefore, the developed protocol does not require precise contact information and ensures large-scale peptide flexibility in the broad contact area. CONCLUSIONS: The demonstrated protocol provides the extension of the CABS-dock method that can be practically used in the structure prediction of protein-peptide complexes guided by the knowledge of the binding interface.

Protein-peptide docking: opportunities and challenges.

Peptides have recently attracted much attention as promising drug candidates. Rational design of peptide-derived therapeutics usually requires structural characterization of the underlying protein-peptide interaction. Given that experimental characterization can be difficult, reliable computational tools are needed. In recent years, a variety of approaches have been developed for 'protein-peptide docking', that is, predicting the structure of the protein-peptide complex, starting from the protein structure and the peptide sequence, including variable degrees of information about the peptide binding site and/or conformation. In this review, we provide an overview of protein-peptide docking methods and outline their capabilities, limitations, and applications in structure-based drug design. Key challenges are also briefly discussed, such as modeling of large-scale conformational changes upon binding, scoring of predicted models, and optimal inclusion of varied types of experimental data and theoretical predictions into an integrative modeling process.

Highly Flexible Protein-Peptide Docking Using CABS-Dock.

Protein-peptide molecular docking is a difficult modeling problem. It is even more challenging when significant conformational changes that may occur during the binding process need to be predicted. In this chapter, we demonstrate the capabilities and features of the CABS-dock server for flexible protein-peptide docking. CABS-dock allows highly efficient modeling of full peptide flexibility and significant flexibility of a protein receptor. During CABS-dock docking, the peptide folding and binding process is explicitly simulated and no information about the peptide binding site or its structure is used. This chapter presents a successful CABS-dock use for docking a potentially therapeutic peptide to a protein target. Moreover, simulation contact maps, a new CABS-dock feature, are described and applied to the docking test case. Finally, a tutorial for running CABS-dock from the command line or command line scripts is provided. The CABS-dock web server is available from http://biocomp.chem.uw.edu.pl/CABSdock/ .

Protein-peptide molecular docking with large-scale conformational changes: the p53-MDM2 interaction.

Protein-peptide interactions are often associated with large-scale conformational changes that are difficult to study either by classical molecular modeling or by experiment. Recently, we have developed the CABS-dock method for flexible protein-peptide docking that enables large-scale rearrangements of the protein chain. In this study, we use CABS-dock to investigate the binding of the p53-MDM2 complex, an element of the cell cycle regulation system crucial for anti-cancer drug design. Experimental data suggest that p53-MDM2 binding is affected by significant rearrangements of a lid region - the N-terminal highly flexible MDM2 fragment; however, the details are not clear. The large size of the highly flexible MDM2 fragments makes p53-MDM2 intractable for exhaustive binding dynamics studies using atomistic models. We performed extensive dynamics simulations using the CABS-dock method, including large-scale structural rearrangements of MDM2 flexible regions. Without a priori knowledge of the p53 peptide structure or its binding site, we obtained near-native models of the p53-MDM2 complex. The simulation results match well the experimental data and provide new insights into the possible role of the lid fragment in p53 binding. The presented case study demonstrates that CABS-dock methodology opens up new opportunities for protein-peptide docking with large-scale changes of the protein receptor structure.