PTools: an opensource molecular docking library (original) (raw)
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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.
ClusPro: a fully automated algorithm for protein-protein docking
Nucleic Acids Research, 2004
ClusPro (http://nrc.bu.edu/cluster) represents the first fully automated, web-based program for the computational docking of protein structures. Users may upload the coordinate files of two protein structures through ClusPro's web interface, or enter the PDB codes of the respective structures, which ClusPro will then download from the PDB server (http:// www.rcsb.org/pdb/). The docking algorithms evaluate billions of putative complexes, retaining a preset number with favorable surface complementarities. A filtering method is then applied to this set of structures, selecting those with good electrostatic and desolvation free energies for further clustering. The program output is a short list of putative complexes ranked according to their clustering properties, which is automatically sent back to the user via email.
Insights into molecular docking: A comprehensive view
International Journal of Pharmaceutical Chemistry and Analysis, 2023
Molecular docking software is mainly used in drug development. Molecular docking offers a wide range of useful techniques for the creation and analysis of pharmaceuticals. Before now, predicting the target for a receptor was extremely challenging however, docking the target protein with a ligand is a straightforward and dependable procedure presently and binding affinity is designed. To see a molecule's three-dimensional structure, a variety of docking tools have been created. The docking score can also be examined using a variety of computational techniques. This review mainly emphases on the core idea of molecular docking, as well as its major uses and many kinds of interaction, Basics requirements for molecular docking, Molecular Approach, Application, and Software available for the Docking of molecules. Keywords: CADD, Computational Method, Protein databank, Docking, Virtual Screening
rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids
PLoS Computational Biology, 2014
Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrö dinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock. sourceforge.net/ Citation: Ruiz-Carmona S, Alvarez-Garcia D, Foloppe N, Garmendia-Doval AB, Juhos S, et al. (2014) rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids. PLoS Comput Biol 10(4): e1003571.
DOT2: Macromolecular docking with improved biophysical models
Journal of Computational Chemistry, 2013
Computational docking is a useful tool for predicting macromolecular complexes, which are often difficult to determine experimentally. Here we present the DOT2 software suite, an updated version of the DOT intermolecular docking program. DOT2 provides straightforward, automated construction of improved biophysical models based on molecular coordinates, offering checkpoints that guide the user to include critical features. DOT has been updated to run more quickly, allow flexibility in grid size and spacing, and generate a complete list of favorable candidate configurations. Output can be filtered by experimental data and rescored by the sum of electrostatic and atomic desolvation energies. We show that this rescoring method improves the ranking of correct complexes for a wide range of macromolecular interactions, and demonstrate that biologically relevant models are essential for biologically relevant results. The flexibility and versatility of DOT2 accommodate realistic models of complex biological systems, improving the likelihood of a successful docking outcome.
DockIT: a tool for interactive molecular docking and molecular complex construction
Bioinformatics, 2020
Summary DockIT is a tool that has a unique set of physical and graphical features for interactive molecular docking. It enables the user to bring a ligand and a receptor into a docking pose by controlling relative position and orientation, either with a mouse and keyboard, or with a haptic device. Atomic interactions are modelled using molecular dynamics-based force-fields with the force on the ligand being felt on a haptic device. Real-time calculation and display of intermolecular hydrogen bonds and multipoint collision detection either using maximum force or maximum atomic overlap, mean that together with the ability to monitor selected intermolecular atomic distances, the user can find physically feasible docking poses that satisfy distance constraints derived from experimental methods. With these features and the ability to output and reload docked structures it can be used to accurately build up large multi-component molecular systems in preparation for molecular dynamics simu...
The ClusPro web server for protein–protein docking
Nature Protocols, 2017
The ClusPro server (https://cluspro.org) is a widely used tool for protein-protein docking. The server provides a simple home page for basic use, requiring only two files in Protein Data Bank format. However, ClusPro also offers a number of advanced options to modify the search that include the removal of unstructured protein regions, applying attraction or repulsion, accounting for pairwise distance restraints, constructing homo-multimers, considering small angle X-ray scattering (SAXS) data, and finding heparin binding sites. Six different energy functions can be used depending on the type of proteins. Docking with each energy parameter set results in ten models defined by centers of highly populated clusters of low energy docked structures. This protocol describes the use of the various options, the construction of auxiliary restraints files, the selection of the energy parameters, and the analysis of the results. Although the server is heavily used, runs are generally completed in < 4 hours.
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.