CABS-dock standalone: a toolbox for flexible protein–peptide docking (original) (raw)
Related papers
Flexible docking of peptides to proteins using CABS‐dock
Protein Science, 2019
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-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.
Nucleic Acids Research, 2015
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 does not 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 nonredundant 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 userselected 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.
Methods, 2015
Protein-peptide interactions play essential functional roles in living organisms and their structural characterization is a hot subject of current experimental and theoretical research. Computational modeling of the structure of protein-peptide interactions is usually divided into two stages: prediction of the binding site at a protein receptor surface, and then docking (and modeling) the peptide structure into the known binding site. This paper presents a comprehensive CABS-dock method for the simultaneous search of binding sites and flexible protein-peptide docking, available as a user's friendly web server. We present example CABS-dock results obtained in the default CABS-dock mode and using its advanced options that enable the user to increase the range of flexibility for chosen receptor fragments or to exclude user-selected binding modes from docking search. Furthermore, we demonstrate a strategy to improve CABS-dock performance by assessing the quality of models with classical molecular dynamics. Finally, we discuss the promising extensions and applications of the CABS-dock method and provide a tutorial appendix for the convenient analysis and visualization of CABS-dock results. The CABS-dock web server is freely available at
MOLS 2.0: software package for peptide modeling and protein-ligand docking
Journal of molecular modeling, 2016
We previously developed an algorithm to perform conformational searches of proteins and peptides, and to perform the docking of ligands to protein receptors. In order to identify optimal conformations and docked poses, this algorithm uses mutually orthogonal Latin squares (MOLS) to rationally sample the vast conformational (or docking) space, and then analyzes this relatively small sample using a variant of mean field theory. The conformational search part of the algorithm was denoted MOLS 1.0. The docking portion of the algorithm, which allows only "flexible ligand/rigid receptor" docking, was denoted MOLSDOCK. Both are FORTRAN-based command-line-only molecular docking computer programs, though a GUI was developed later for MOLS 1.0. Both the conformational search and the rigid receptor docking parts of the algorithm have been extensively validated. We have now further enhanced the capabilities of the program by incorporating "induced fit" side-chain receptor fl...
Development and Application of a Fully Blind Flexible Peptide-protein Docking Protocol, pepATTRACT
BIO-PROTOCOL
Peptide-mediated interactions are involved in many signaling and regulatory pathways as well as the DNA replication machinery and are linked to many pathological disorders. Many research groups are currently working towards a more detailed understanding of these important interactions by characterizing the 3D complex structures with experimental methods like X-ray crystallography and NMR. However, for a large number of peptide-protein complexes such atomistic structural information is lacking to date. Computational peptide docking methods can yield information complementary to experimental information by predicting the protein-peptide complex structure from the 3D structure of the protein and the peptide sequence. This approach can also be used to study interactions between folded and disordered proteins/protein regions (e.g., the interactions of the disordered regions in tumor suppressor p53 with its different partners). Here, we describe the development and usage of the fully blind, flexible peptide-protein docking protocol pepATTRACT. The ATTRACT docking engine is implemented as a suite of command line tools and options that can be combined at will. Therefore, ATTRACT protocols like pepATTRACT are typically invoked via a custom, handwritten shell script. Although this approach is very flexible, it limits the accessibility of ATTRACT to expert users only. To make pepATTRACT easily accessible to non-expert users, we created a web-interface which helps the user set up a peptide docking protocol by editing parameters in a web browser (www.attract.ph.tum.de/peptide.html). pepATTRACT docking scripts can then executed on the user's local machine, once the ATTRACT software has been installed. Here, we describe all the steps necessary for setting up a pepATTRACT docking run via the web-interface including installation of the ATTRACT software. Materials and Reagents 1. Atomic 3D structure of protein of interest in PDB file format (www.pdb.org) 2. Sequence of peptide of interest in one-letter code Note: The protocol was tested on peptide lengths of up to 15 residues. 3. Optional: information on protein residues involved in binding (literature research)
ATTRACT and PTOOLS: Open Source Programs for Protein–Protein Docking
Computational Drug Discovery and Design, 2012
The prediction of the structure of protein-protein complexes based on structures or structural models of 8 isolated partners is of increasing importance for structural biology and bioinformatics. The ATTRACT 9 program can be used to perform systematic docking searches based on docking energy minimization. It is 10 part of the object-oriented PTools library written in Python and C++. The library contains various 11 routines to manipulate protein structures, to prepare and perform docking searches as well as analyzing 12 docking results. It also intended to facilitate further methodological developments in the area of macro-13 molecular docking that can be easily integrated. Here, we describe the application of PTools to perform 14 systematic docking searches and to analyze the results. In addition, the possibility to perform multi-15 component docking will also be presented. 16 face prediction, Normal mode analysis 18 24 (1-7) employs energy minimization in rotational and translational 25 degrees of freedom (+ potential conformational variables) of one 26 protein partner (ligand) with respect to the second protein (receptor). 27 It can be used as a stand alone program but has also been integrated 28 into the PTools molecular docking library. Flexibility of the partner 29 structures can be taken into account by representing flexible surface 30 side chains (and also loops) as multiple conformational copies. 31 The ATTRACT docking minimization employs a reduced or 32 coarse-grained protein model which is intermediated between a to account for global and local flexibility. Pro-412 teins 69, 774-780.
Protein-ligand docking: A review of recent advances and future perspectives
Current …, 2008
Understanding the interactions between proteins and ligands is crucial for the pharmaceutical and functional food industries. The experimental structures of these protein/ligand complexes are usually obtained, under highly expert control, by time-consuming techniques such as X-ray crystallography or NMR. These techniques are therefore not suitable for routinely screening the possible interaction between one receptor and thousands of ligands. To overcome this limitation, computational algorithms (i.e. docking algorithms) have been developed that use the individual structures of the receptor and ligand to predict the structure of their complex. The present review, then, summarizes: (a) the fundamentals of the algorithms of the most commontly used docking programmes (with particular emphasis on their strengths and limitations); (b) how the results from different docking algorithms compare (i.e. which software gives the best predictions); and (c) the future perspectives and challenges for docking techniques.
Journal of Chemical Information and Modeling, 2007
In this study, we present GlamDock, a new docking tool for flexible ligand docking. GlamDock (version 1.0) is based on a simple Monte Carlo with minimization procedure. The main features of the method are the energy function, which is a continuously differentiable empirical potential, and the definition of the search space, which combines internal coordinates for the conformation of the ligand, with a mappingbased description of the rigid body translation and rotation. First, we validate GlamDock on a standard benchmark, a set of 100 protein-ligand complexes, which allows comparative evaluation to existing docking tools. The results on this benchmark show that GlamDock is at least comparable in efficiency and accuracy to the best existing docking tools. The main focus of this work is the validation on the scPDB database of protein-ligand complexes. The size of this data set allows a thorough analysis of the dependencies of docking accuracy on features of the protein-ligand system. In particular, it allows a two-dimensional analysis of the results, which identifies a number of interesting dependencies that are generally lost or even misinterpreted in the one-dimensional approach. The overall result that GlamDock correctly predicts the complex structure in practically half of the cases in the scPDB is important not only for screening ligands against a particular protein but even more so for inverse screening, that is, the identification of the correct targets for a particular ligand.
MADAMM: A multistaged docking with an automated molecular modeling protocol
Proteins: Structure, Function, and Bioinformatics, 2009
Dealing with receptor flexibility in docking methodology is still a problem. The main reason behind this difficulty is the large number of degrees of freedom that have to be considered in this kind of calculations. In this paper, we present an automated procedure, called MADAMM, that allows flexibilization of both the receptor and the ligand during a multistaged docking with an automated molecular modeling protocol. We show that the orientation of particular residues at the interface between the protein and the ligand have a crucial influence on the way they interact during the docking process, and the standard docking methodologies failed to predict their correct mode of binding. We present some examples that demonstrate the capabilities of this approach when compared with traditional docking methodologies.