Literature DB >> 30039414

Supervised Molecular Dynamics (SuMD) Approaches in Drug Design.

Davide Sabbadin1, Veronica Salmaso2, Mattia Sturlese2, Stefano Moro3.   

Abstract

Supervised MD (SuMD) is a computational method that enables the exploration of ligand-receptor recognition pathway in a reduced timescale. The performance speedup is due to the incorporation of a tabu-like supervision algorithm on the ligand-receptor approaching distance into a classic molecular dynamics (MD) simulation. SuMD enables the investigation of ligand-receptor binding events independently from the starting position, chemical structure of the ligand (small molecules or peptides), and also from its receptor-binding affinity. The application of SuMD highlights an appreciable capability of the technique to reproduce the crystallographic structures of several ligand-protein complexes and can provide high-quality protein-ligand models of for which yet experimental confirmation of binding mode is not available.

Keywords:  Ligand–protein binding; Meta-binding site; Molecular dynamics; Peptide–protein binding; Recognition pathway; Supervised molecular dynamics

Mesh:

Substances:

Year:  2018        PMID: 30039414     DOI: 10.1007/978-1-4939-8630-9_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

1.  Comparative study of the unbinding process of some HTLV-1 protease inhibitors using unbiased molecular dynamics simulations.

Authors:  Fereshteh Noroozi Tiyoula; Hassan Aryapour; Mostafa Javaheri Moghadam
Journal:  PLoS One       Date:  2022-07-14       Impact factor: 3.752

2.  Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression.

Authors:  Mark J Wall; Emily Hill; Robert Huckstepp; Kerry Barkan; Giuseppe Deganutti; Michele Leuenberger; Barbara Preti; Ian Winfield; Sabrina Carvalho; Anna Suchankova; Haifeng Wei; Dewi Safitri; Xianglin Huang; Wendy Imlach; Circe La Mache; Eve Dean; Cherise Hume; Stephanie Hayward; Jess Oliver; Fei-Yue Zhao; David Spanswick; Christopher A Reynolds; Martin Lochner; Graham Ladds; Bruno G Frenguelli
Journal:  Nat Commun       Date:  2022-07-18       Impact factor: 17.694

3.  Reconstruction of the unbinding pathways of noncovalent SARS-CoV and SARS-CoV-2 3CLpro inhibitors using unbiased molecular dynamics simulations.

Authors:  Fereshteh Noroozi Tiyoula; Hassan Aryapour
Journal:  PLoS One       Date:  2022-02-09       Impact factor: 3.240

4.  An integrated drug repurposing strategy for the rapid identification of potential SARS-CoV-2 viral inhibitors.

Authors:  Alfonso Trezza; Daniele Iovinelli; Annalisa Santucci; Filippo Prischi; Ottavia Spiga
Journal:  Sci Rep       Date:  2020-08-17       Impact factor: 4.379

  4 in total

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