Next Article in Journal
Inhibitory Effects of Constituents from the Aerial Parts of Rosmarinus officinalis L. on Triglyceride Accumulation
Next Article in Special Issue
Molecular Simulations of Disulfide-Rich Venom Peptides with Ion Channels and Membranes
Previous Article in Journal
Advances in Solid-State Transformations of Coordination Bonds: From the Ball Mill to the Aging Chamber
Previous Article in Special Issue
Intrinsic Dynamics Analysis of a DNA Octahedron by Elastic Network Model
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Molecules 2017, 22(1), 136;

The Performance of Several Docking Programs at Reproducing Protein–Macrolide-Like Crystal Structures

Organic Chemistry Section, Facultat de Química, Diagonal 645, Universitat de Barcelona, 08028 Barcelona, Catalonia, Spain
Author to whom correspondence should be addressed.
Academic Editor: Roberta Galeazzi
Received: 20 December 2016 / Revised: 8 January 2017 / Accepted: 11 January 2017 / Published: 17 January 2017
(This article belongs to the Special Issue Biomolecular Simulations)
Full-Text   |   PDF [1609 KB, uploaded 17 January 2017]   |  


The accuracy of five docking programs at reproducing crystallographic structures of complexes of 8 macrolides and 12 related macrocyclic structures, all with their corresponding receptors, was evaluated. Self-docking calculations indicated excellent performance in all cases (mean RMSD values ≤ 1.0) and confirmed the speed of AutoDock Vina. Afterwards, the lowest-energy conformer of each molecule and all the conformers lying 0–10 kcal/mol above it (as given by Macrocycle, from MacroModel 10.0) were subjected to standard docking calculations. While each docking method has its own merits, the observed speed of the programs was as follows: Glide 6.6 > AutoDock Vina 1.1.2 > DOCK 6.5 >> AutoDock 4.2.6 > AutoDock 3.0.5. For most of the complexes, the five methods predicted quite correct poses of ligands at the binding sites, but the lower RMSD values for the poses of highest affinity were in the order: Glide 6.6 ≈ AutoDock Vina ≈ DOCK 6.5 > AutoDock 4.2.6 >> AutoDock 3.0.5. By choosing the poses closest to the crystal structure the order was: AutoDock Vina > Glide 6.6 ≈ DOCK 6.5 ≥ AutoDock 4.2.6 >> AutoDock 3.0.5. Re-scoring (AutoDock 4.2.6//AutoDock Vina, Amber Score and MM-GBSA) improved the agreement between the calculated and experimental data. For all intents and purposes, these three methods are equally reliable. View Full-Text
Keywords: macrolides; natural products; docking; AutoDock; Vina; DOCK; Glide macrolides; natural products; docking; AutoDock; Vina; DOCK; Glide

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material


Share & Cite This Article

MDPI and ACS Style

Castro-Alvarez, A.; Costa, A.M.; Vilarrasa, J. The Performance of Several Docking Programs at Reproducing Protein–Macrolide-Like Crystal Structures. Molecules 2017, 22, 136.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Molecules EISSN 1420-3049 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top