Literature DB >> 23089616

Solvent structure improves docking prediction in lectin-carbohydrate complexes.

Diego F Gauto1, Ariel A Petruk, Carlos P Modenutti, Juan I Blanco, Santiago Di Lella, Marcelo A Martí.   

Abstract

Recognition and complex formation between proteins and carbohydrates is a key issue in many important biological processes. Determination of the three-dimensional structure of such complexes is thus most relevant, but particularly challenging because of their usually low binding affinity. In silico docking methods have a long-standing tradition in predicting protein-ligand complexes, and allow a potentially fast exploration of a number of possible protein-carbohydrate complex structures. However, determining which of these predicted complexes represents the correct structure is not always straightforward. In this work, we present a modification of the scoring function provided by AutoDock4, a widely used docking software, on the basis of analysis of the solvent structure adjacent to the protein surface, as derived from molecular dynamics simulations, that allows the definition and characterization of regions with higher water occupancy than the bulk solvent, called water sites. They mimic the interaction held between the carbohydrate -OH groups and the protein. We used this information for an improved docking method in relation to its capacity to correctly predict the protein-carbohydrate complexes for a number of tested proteins, whose ligands range in size from mono- to tetrasaccharide. Our results show that the presented method significantly improves the docking predictions. The resulting solvent-structure-biased docking protocol, therefore, appears as a powerful tool for the design and optimization of development of glycomimetic drugs, while providing new insights into protein-carbohydrate interactions. Moreover, the achieved improvement also underscores the relevance of the solvent structure to the protein carbohydrate recognition process.

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Year:  2012        PMID: 23089616     DOI: 10.1093/glycob/cws147

Source DB:  PubMed          Journal:  Glycobiology        ISSN: 0959-6658            Impact factor:   4.313


  12 in total

1.  AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.

Authors:  Juan Pablo Arcon; Carlos P Modenutti; Demian Avendaño; Elias D Lopez; Lucas A Defelipe; Francesca Alessandra Ambrosio; Adrian G Turjanski; Stefano Forli; Marcelo A Marti
Journal:  Bioinformatics       Date:  2019-10-01       Impact factor: 6.937

2.  Biased Docking for Protein-Ligand Pose Prediction.

Authors:  Juan Pablo Arcon; Adrián G Turjanski; Marcelo A Martí; Stefano Forli
Journal:  Methods Mol Biol       Date:  2021

3.  Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity.

Authors:  Zdeněk Kříž; Jan Adam; Jana Mrázková; Petros Zotos; Thomais Chatzipavlou; Michaela Wimmerová; Jaroslav Koča
Journal:  J Comput Aided Mol Des       Date:  2014-07-12       Impact factor: 3.686

Review 4.  Predicting the Structures of Glycans, Glycoproteins, and Their Complexes.

Authors:  Robert J Woods
Journal:  Chem Rev       Date:  2018-08-09       Impact factor: 60.622

5.  Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

Authors:  Spandana Makeneni; David F Thieker; Robert J Woods
Journal:  J Chem Inf Model       Date:  2018-03-09       Impact factor: 4.956

6.  The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations.

Authors:  Vijaya Kumar Hinge; Nikolay Blinov; Dipankar Roy; David S Wishart; Andriy Kovalenko
Journal:  J Comput Aided Mol Des       Date:  2019-11-04       Impact factor: 3.686

7.  Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking.

Authors:  Anita K Nivedha; David F Thieker; Spandana Makeneni; Huimin Hu; Robert J Woods
Journal:  J Chem Theory Comput       Date:  2016-01-19       Impact factor: 6.006

Review 8.  Recent advances in employing molecular modelling to determine the specificity of glycan-binding proteins.

Authors:  Oliver C Grant; Robert J Woods
Journal:  Curr Opin Struct Biol       Date:  2014-08-07       Impact factor: 6.809

9.  Calcium-Binding Generates the Semi-Clathrate Waters on a Type II Antifreeze Protein to Adsorb onto an Ice Crystal Surface.

Authors:  Tatsuya Arai; Yoshiyuki Nishimiya; Yasushi Ohyama; Hidemasa Kondo; Sakae Tsuda
Journal:  Biomolecules       Date:  2019-04-27

10.  Carbohydrate-Protein Interactions: Advances and Challenges.

Authors:  Shuang Zhang; Kyle Yu Chen; Xiaoqin Zou
Journal:  Commun Inf Syst       Date:  2021
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