Literature DB >> 29768914

Exploring Cryptic Pockets Formation in Targets of Pharmaceutical Interest with SWISH.

Federico Comitani1, Francesco Luigi Gervasio1,2.   

Abstract

Cryptic (hidden) pockets are sites that are not visible on unliganded target proteins' structures and only become apparent when a ligand binds. They might provide a valid alternative to classical binding sites in otherwise "undruggable" targets, but their hidden nature makes it difficult to use standard structure-based or computer-aided drug discovery approaches. Our group recently developed a Hamiltonian replica-exchange method (sampling water interfaces through scaled Hamiltonians or SWISH) that improves the sampling of hydrophobic cavities by scaling the interactions between water molecules and protein atoms. Here, we discuss further improvements to SWISH and its combination with fragment probe simulations. We tested the robustness and general applicability of the improved approach in a variety of pharmaceutically relevant targets. The chosen proteins: NPC2, p38α, LfrR, and hPNMT, represent a set of diversified and interesting targets harboring nontrivial cryptic binding sites. In all cases, the updated version of our algorithm efficiently explored the cryptic sites.

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Year:  2018        PMID: 29768914     DOI: 10.1021/acs.jctc.8b00263

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  8 in total

Review 1.  Investigating Cryptic Binding Sites by Molecular Dynamics Simulations.

Authors:  Antonija Kuzmanic; Gregory R Bowman; Jordi Juarez-Jimenez; Julien Michel; Francesco L Gervasio
Journal:  Acc Chem Res       Date:  2020-03-05       Impact factor: 22.384

2.  A non-beta-lactam antibiotic inhibitor for enterohemorrhagic Escherichia coli O104:H4.

Authors:  Haoqi Wang; Arul Jayaraman; Rani Menon; Varun Gejji; R Karthikeyan; Sandun Fernando
Journal:  J Mol Med (Berl)       Date:  2019-06-28       Impact factor: 4.599

Review 3.  New perspectives in cancer drug development: computational advances with an eye to design.

Authors:  Matteo Castelli; Stefano A Serapian; Filippo Marchetti; Alice Triveri; Valentina Pirota; Luca Torielli; Simona Collina; Filippo Doria; Mauro Freccero; Giorgio Colombo
Journal:  RSC Med Chem       Date:  2021-07-07

4.  Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies.

Authors:  Rhys Evans; Ladislav Hovan; Gareth A Tribello; Benjamin P Cossins; Carolina Estarellas; Francesco L Gervasio
Journal:  J Chem Theory Comput       Date:  2020-06-04       Impact factor: 6.006

Review 5.  Molecular Docking: Shifting Paradigms in Drug Discovery.

Authors:  Luca Pinzi; Giulio Rastelli
Journal:  Int J Mol Sci       Date:  2019-09-04       Impact factor: 5.923

6.  Analyzing In Silico the Relationship Between the Activation of the Edema Factor and Its Interaction With Calmodulin.

Authors:  Irène Pitard; Damien Monet; Pierre L Goossens; Arnaud Blondel; Thérèse E Malliavin
Journal:  Front Mol Biosci       Date:  2020-12-04

7.  Opening of a cryptic pocket in β-lactamase increases penicillinase activity.

Authors:  Catherine R Knoverek; Upasana L Mallimadugula; Sukrit Singh; Enrico Rennella; Thomas E Frederick; Tairan Yuwen; Shreya Raavicharla; Lewis E Kay; Gregory R Bowman
Journal:  Proc Natl Acad Sci U S A       Date:  2021-11-23       Impact factor: 11.205

8.  Extraction and high-throughput sequencing of oak heartwood DNA: Assessing the feasibility of genome-wide DNA methylation profiling.

Authors:  Federico Rossi; Alessandro Crnjar; Federico Comitani; Rodrigo Feliciano; Leonie Jahn; George Malim; Laura Southgate; Emily Kay; Rebecca Oakey; Richard Buggs; Andy Moir; Logan Kistler; Ana Rodriguez Mateos; Carla Molteni; Reiner Schulz
Journal:  PLoS One       Date:  2021-11-18       Impact factor: 3.240

  8 in total

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