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

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.

[1]  David S. Goodsell,et al.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility , 2009, J. Comput. Chem..

[2]  Anna M. Costa,et al.  Synthesis of (-)-amphidinolide K fragment C9-C22. , 2005, Organic letters.

[3]  Jürgen Bajorath,et al.  Predicting bioactive conformations and binding modes of macrocycles , 2016, Journal of Computer-Aided Molecular Design.

[4]  Elizabeth Yuriev,et al.  Challenges and advances in computational docking: 2009 in review , 2011, Journal of molecular recognition : JMR.

[5]  I. Barasoain,et al.  Mechanism of Action of the Cytotoxic Macrolides Amphidinolide X and J , 2011, Chembiochem : a European journal of chemical biology.

[6]  J. Vilarrasa,et al.  Stereocontrolled total synthesis of amphidinolide X via a silicon-tethered metathesis reaction. , 2008, Organic letters.

[7]  Youngchang Kim,et al.  The Structural Basis for Substrate Anchoring, Active Site Selectivity, and Product Formation by P450 PikC from Streptomyces venezuelae* , 2006, Journal of Biological Chemistry.

[8]  Xiaoqin Zou,et al.  Advances and Challenges in Protein-Ligand Docking , 2010, International journal of molecular sciences.

[9]  Jacob D. Durrant,et al.  Comparing Neural-Network Scoring Functions and the State of the Art: Applications to Common Library Screening , 2013, J. Chem. Inf. Model..

[10]  Anna M. Costa,et al.  A synthetic approach to palmerolides via Negishi cross coupling. The challenge of the C15–C16 bond formation , 2014 .

[11]  I. Kuntz,et al.  DOCK 6: combining techniques to model RNA-small molecule complexes. , 2009, RNA.

[12]  Gregory D. Hawkins,et al.  Parametrized Models of Aqueous Free Energies of Solvation Based on Pairwise Descreening of Solute Atomic Charges from a Dielectric Medium , 1996 .

[13]  Elizabeth Yuriev,et al.  Latest developments in molecular docking: 2010–2011 in review , 2013, Journal of molecular recognition : JMR.

[14]  Anna M. Costa,et al.  Iododesilylation of TIPS-, TBDPS-, and TBS-substituted alkenes in connection with the synthesis of amphidinolides B/D. , 2011, Organic letters.

[15]  Anna M. Costa,et al.  Synthesis of amphidinolide E C10-C26 fragment. , 2008, Organic letters.

[16]  Kenji Onodera,et al.  Evaluations of Molecular Docking Programs for Virtual Screening , 2007, J. Chem. Inf. Model..

[17]  Andrew J. Tebben,et al.  Macrocycle Conformational Sampling with MacroModel , 2014, J. Chem. Inf. Model..

[18]  Kwong-Sak Leung,et al.  Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets , 2015, Molecular informatics.

[19]  A. Kukol.  Consensus virtual screening approaches to predict protein ligands. , 2011, European journal of medicinal chemistry.

[20]  V. Aviyente,et al.  Molecular Docking Study Based on Pharmacophore Modeling for Novel PhosphodiesteraseIV Inhibitors , 2012, Molecular informatics.

[21]  António J. M. Ribeiro,et al.  Protein-ligand docking in the new millennium--a retrospective of 10 years in the field. , 2013, Current medicinal chemistry.

[22]  Hung‐wen Liu,et al.  The Structure of SpnF, a Standalone Enzyme that Catalyzes [4+2] Cycloaddition , 2015, Nature chemical biology.

[23]  I. Barasoain,et al.  Cyclostreptin binds covalently to microtubule pores and lumenal taxoid binding sites. , 2007, Nature chemical biology.

[24]  D. Case,et al.  Rescoring docking hit lists for model cavity sites: predictions and experimental testing. , 2008, Journal of molecular biology.

[25]  Simona Distinto,et al.  Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—What can we learn from earlier mistakes? , 2008, J. Comput. Aided Mol. Des..

[26]  Esben J. Bjerrum,et al.  Machine learning optimization of cross docking accuracy , 2016, Comput. Biol. Chem..

[27]  C. Uma,et al.  Molecular Docking Studies of 1,3,4-Thiadiazoles as Novel Peptide Deformylase Inhibitors as Potential Antibacterial Agents , 2015 .

[28]  Giulio Rastelli,et al.  BEAR, a Molecular Docking Refinement and Rescoring Method , 2013 .

[29]  Yu-chian Chen.  Beware of docking! , 2015, TIPS - Trends in Pharmacological Sciences.

[30]  Xiaoqin Zou,et al.  Challenges, Applications, and Recent Advances of Protein-Ligand Docking in Structure-Based Drug Design , 2014, Molecules.

[31]  Young Ji Yoo,et al.  Combinatorial biosynthesis and antibacterial evaluation of glycosylated derivatives of 12-membered macrolide antibiotic YC-17. , 2013, Journal of biotechnology.

[32]  Nicolas Foloppe,et al.  Tackling the conformational sampling of larger flexible compounds and macrocycles in pharmacology and drug discovery. , 2013, Bioorganic & medicinal chemistry.

[33]  D. Case,et al.  Theory and applications of the generalized born solvation model in macromolecular simulations , 2000, Biopolymers.

[34]  Zhihai Liu,et al.  Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes , 2010, J. Comput. Chem..

[35]  Gerhard Klebe,et al.  Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures , 1994, J. Chem. Inf. Comput. Sci..

[36]  Matthew P. Repasky,et al.  Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. , 2006, Journal of medicinal chemistry.

[37]  Simon Fong,et al.  PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking , 2015, J. Bioinform. Comput. Biol..

[38]  Aleksey A. Porollo,et al.  Survey of public domain software for docking simulations and virtual screening , 2011, Human Genomics.

[39]  M. Botta,et al.  Computational comparison of microtubule-stabilising agents laulimalide and peloruside with taxol and colchicine. , 2004, Bioorganic & medicinal chemistry letters.

[40]  J. Vilarrasa,et al.  Efficient approach to fluvirucins B2-B5, Sch 38518, and Sch 39185. First synthesis of their aglycon, via CM and RCM reactions. , 2009, Organic letters.

[41]  Dariusz Plewczynski,et al.  Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database , 2011, J. Comput. Chem..

[42]  Maurizio Botta,et al.  Lennard-Jones Potential and Dummy Atom Settings to Overcome the AUTODOCK Limitation in Treating Flexible Ring Systems , 2007, J. Chem. Inf. Model..

[43]  Dima Kozakov,et al.  How Proteins Bind Macrocycles , 2014, Nature chemical biology.

[44]  Renxiao Wang,et al.  Comparative evaluation of 11 scoring functions for molecular docking. , 2003, Journal of medicinal chemistry.

[45]  Arthur J. Olson,et al.  AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading , 2009, J. Comput. Chem..

[46]  Conrad C. Huang,et al.  UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..

[47]  Yongbo Hu,et al.  Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy , 2009, J. Chem. Inf. Model..

[48]  I. Barasoain,et al.  Cyclostreptin derivatives specifically target cellular tubulin and further map the paclitaxel site. , 2012, Biochemistry.

[49]  Nikolay V Dokholyan,et al.  Dynamic Docking of Conformationally Constrained Macrocycles: Methods and Applications. , 2016, ACS chemical biology.

[50]  Christian Kramer,et al.  Improving Docking Results via Reranking of Ensembles of Ligand Poses in Multiple X-ray Protein Conformations with MM-GBSA , 2014, J. Chem. Inf. Model..

[51]  I. Barasoain,et al.  Molecular Recognition of Peloruside A by Microtubules. The C24 Primary Alcohol is Essential for Biological Activity , 2010, Chembiochem : a European journal of chemical biology.

[52]  David S. Goodsell,et al.  Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function , 1998, J. Comput. Chem..