Literature DB >> 25267604

Using crystallographic water properties for the analysis and prediction of lectin-carbohydrate complex structures.

C Modenutti1, D Gauto2, L Radusky3, J Blanco3, A Turjanski4, S Hajos5, Ma Marti6.   

Abstract

Understanding protein-ligand interactions is a fundamental question in basic biochemistry, and the role played by the solvent along this process is not yet fully understood. This fact is particularly relevant in lectins, proteins that mediate a large variety of biological processes through the recognition of specific carbohydrates. In the present work, we have thoroughly analyzed a nonredundant and well-curated set of lectin structures looking for a potential relationship between the structural water properties in the apo-structures and the corresponding protein-ligand complex structures. Our results show that solvent structure adjacent to the binding sites mimics the ligand oxygen structural framework in the resulting protein-ligand complex, allowing us to develop a predictive method using a Naive Bayes classifier. We also show how these properties can be used to improve docking predictions of lectin-carbohydrate complex structures in terms of both accuracy and precision, thus developing a solid strategy for the rational design of glycomimetic drugs. Overall our results not only contribute to the understanding of protein-ligand complexes, but also underscore the role of the water solvent in the ligand recognition process. Finally, we discuss our findings in the context of lectin specificity and ligand recognition properties.
© The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Naive Bayes classifier; carbohydrate; docking; hydration; lectin; sites; water sites

Mesh:

Substances:

Year:  2014        PMID: 25267604     DOI: 10.1093/glycob/cwu102

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


  6 in total

1.  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

2.  Treatment with a New Peroxisome Proliferator-Activated Receptor Gamma Agonist, Pyridinecarboxylic Acid Derivative, Increases Angiogenesis and Reduces Inflammatory Mediators in the Heart of Trypanosoma cruzi-Infected Mice.

Authors:  Federico Nicolás Penas; Davide Carta; Ganna Dmytrenko; Gerado A Mirkin; Carlos Pablo Modenutti; Ágata Carolina Cevey; Maria Jimena Rada; Maria Grazia Ferlin; María Elena Sales; Nora Beatriz Goren
Journal:  Front Immunol       Date:  2017-12-11       Impact factor: 7.561

3.  Waterdock 2.0: Water placement prediction for Holo-structures with a pymol plugin.

Authors:  Akshay Sridhar; Gregory A Ross; Philip C Biggin
Journal:  PLoS One       Date:  2017-02-24       Impact factor: 3.240

Review 4.  The Structural Biology of Galectin-Ligand Recognition: Current Advances in Modeling Tools, Protein Engineering, and Inhibitor Design.

Authors:  Carlos P Modenutti; Juan I Blanco Capurro; Santiago Di Lella; Marcelo A Martí
Journal:  Front Chem       Date:  2019-12-03       Impact factor: 5.221

5.  A Remote Secondary Binding Pocket Promotes Heteromultivalent Targeting of DC-SIGN.

Authors:  Robert Wawrzinek; Eike-Christian Wamhoff; Jonathan Lefebre; Mareike Rentzsch; Gunnar Bachem; Gary Domeniconi; Jessica Schulze; Felix F Fuchsberger; Hengxi Zhang; Carlos Modenutti; Lennart Schnirch; Marcelo A Marti; Oliver Schwardt; Maria Bräutigam; Mónica Guberman; Dirk Hauck; Peter H Seeberger; Oliver Seitz; Alexander Titz; Beat Ernst; Christoph Rademacher
Journal:  J Am Chem Soc       Date:  2021-11-08       Impact factor: 15.419

6.  Arylsulfonyl histamine derivatives as powerful and selective α-glucosidase inhibitors.

Authors:  M I Osella; M O Salazar; M D Gamarra; D M Moreno; F Lambertucci; D E Frances; R L E Furlan
Journal:  RSC Med Chem       Date:  2020-03-12
  6 in total

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