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Open AccessJournal ArticleDOI

DOCK 6: Impact of new features and current docking performance

TLDR
This manuscript presents the latest algorithmic and methodological developments to the structure‐based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry‐corrected root‐mean‐square deviation algorithm, a database filter, and docking forensic tools.
Abstract
This manuscript presents the latest algorithmic and methodological developments to the structure-based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry-corrected root-mean-square deviation algorithm, a database filter, and docking forensic tools. An important strategy during development involved use of three orthogonal metrics for assessment and validation: pose reproduction over a large database of 1043 protein-ligand complexes (SB2012 test set), cross-docking to 24 drug-target protein families, and database enrichment using large active and decoy datasets (Directory of Useful Decoys [DUD]-E test set) for five important proteins including HIV protease and IGF-1R. Relative to earlier versions, a key outcome of the work is a significant increase in pose reproduction success in going from DOCK 4.0.2 (51.4%) → 5.4 (65.2%) → 6.7 (73.3%) as a result of significant decreases in failure arising from both sampling 24.1% → 13.6% → 9.1% and scoring 24.4% → 21.1% → 17.5%. Companion cross-docking and enrichment studies with the new version highlight other strengths and remaining areas for improvement, especially for systems containing metal ions. The source code for DOCK 6.7 is available for download and free for academic users at http://dock.compbio.ucsf.edu/.

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Journal ArticleDOI

Software for molecular docking: a review

TL;DR: Docking against homology-modeled targets also becomes possible for proteins whose structures are not known, and the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes.
Journal ArticleDOI

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings.

TL;DR: This work implemented Python bindings to facilitate scripting and the development of docking workflows in AutoDock Vina 1.2.0, an effort toward the unification of the features of the autoDock4 and AutoD Dock Vina docking engines.
Journal ArticleDOI

Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power.

TL;DR: Overall, the ligand binding poses could be identified in most cases by the evaluated docking programs but the ranks of the binding affinities for the entire dataset could not be well predicted by most docking programs.
Posted Content

AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery

TL;DR: AtomNet is introduced, the first structure-based, deep convolutional neural network designed to predict the bioactivity of small molecules for drug discovery applications and it is shown that AtomNet outperforms previous docking approaches on a diverse set of benchmarks by a large margin.
Journal ArticleDOI

Protein structure-based drug design: from docking to molecular dynamics.

TL;DR: In this review, recent advancements in applications of ligand docking tools and molecular dynamics simulations to ligand identification and optimization are highlighted.
References
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Journal ArticleDOI

UCSF Chimera--a visualization system for exploratory research and analysis.

TL;DR: Two unusual extensions are presented: Multiscale, which adds the ability to visualize large‐scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales.
Journal ArticleDOI

The Protein Data Bank

TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Journal ArticleDOI

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

TL;DR: AutoDock Vina achieves an approximately two orders of magnitude speed‐up compared with the molecular docking software previously developed in the lab, while also significantly improving the accuracy of the binding mode predictions, judging by tests on the training set used in AutoDock 4 development.
Journal ArticleDOI

AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility

TL;DR: AutoDock4 incorporates limited flexibility in the receptor and its utility in analysis of covalently bound ligands is reported, using both a grid‐based docking method and a modification of the flexible sidechain technique.
Journal ArticleDOI

Development and testing of a general amber force field.

TL;DR: A general Amber force field for organic molecules is described, designed to be compatible with existing Amber force fields for proteins and nucleic acids, and has parameters for most organic and pharmaceutical molecules that are composed of H, C, N, O, S, P, and halogens.
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