Literature DB >> 33950384

Methods for Molecular Modelling of Protein Complexes.

Tejashree Rajaram Kanitkar1, Neeladri Sen1, Sanjana Nair1, Neelesh Soni1, Kaustubh Amritkar1, Yogendra Ramtirtha1, M S Madhusudhan2.   

Abstract

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular complexes.

Keywords:  3D structure modelling; Molecular docking; Protein-biomolecular complexes; Scoring and sampling

Year:  2021        PMID: 33950384     DOI: 10.1007/978-1-0716-1406-8_3

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


  141 in total

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Authors:  Neelesh Soni; M S Madhusudhan
Journal:  Curr Opin Struct Biol       Date:  2017-05-12       Impact factor: 6.809

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Review 5.  Computer-aided antibody design.

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Journal:  Protein Eng Des Sel       Date:  2012-06-02       Impact factor: 1.650

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Journal:  Nat Chem Biol       Date:  2011-09-18       Impact factor: 15.040

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Authors:  David S Wishart; Yannick D Feunang; An C Guo; Elvis J Lo; Ana Marcu; Jason R Grant; Tanvir Sajed; Daniel Johnson; Carin Li; Zinat Sayeeda; Nazanin Assempour; Ithayavani Iynkkaran; Yifeng Liu; Adam Maciejewski; Nicola Gale; Alex Wilson; Lucy Chin; Ryan Cummings; Diana Le; Allison Pon; Craig Knox; Michael Wilson
Journal:  Nucleic Acids Res       Date:  2018-01-04       Impact factor: 16.971

8.  The ChEMBL database in 2017.

Authors:  Anna Gaulton; Anne Hersey; Michał Nowotka; A Patrícia Bento; Jon Chambers; David Mendez; Prudence Mutowo; Francis Atkinson; Louisa J Bellis; Elena Cibrián-Uhalte; Mark Davies; Nathan Dedman; Anneli Karlsson; María Paula Magariños; John P Overington; George Papadatos; Ines Smit; Andrew R Leach
Journal:  Nucleic Acids Res       Date:  2016-11-28       Impact factor: 16.971

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Journal:  Nucleic Acids Res       Date:  2015-09-22       Impact factor: 16.971

10.  Predicting and designing therapeutics against the Nipah virus.

Authors:  Neeladri Sen; Tejashree Rajaram Kanitkar; Ankit Animesh Roy; Neelesh Soni; Kaustubh Amritkar; Shreyas Supekar; Sanjana Nair; Gulzar Singh; M S Madhusudhan
Journal:  PLoS Negl Trop Dis       Date:  2019-12-12
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  1 in total

1.  Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs.

Authors:  Neeladri Sen; Ivan Anishchenko; Nicola Bordin; Ian Sillitoe; Sameer Velankar; David Baker; Christine Orengo
Journal:  Brief Bioinform       Date:  2022-07-18       Impact factor: 13.994

  1 in total

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