Literature DB >> 29117680

Molecular Determinants and Bottlenecks in the Dissociation Dynamics of Biotin-Streptavidin.

Pratyush Tiwary1.   

Abstract

Biotin-streptavidin is a very popular system used to gain insight into protein-ligand interactions. In its tetrameric form, it is well-known for its exceptionally high kinetic stability, being one of the strongest known noncovalent interactions in nature, and it is heavily used across the biotechnological industry. In this work, we gain understanding of the molecular determinants and bottlenecks in the dissociation of the dimeric biotin-streptavidin system in wild type and with a point mutation. Using recently proposed enhanced sampling methods with full atomistic resolution, we reproduce the experimentally reported effect of the mutation on the dissociation rate. We also answer a longstanding question regarding cause/effect in the coupled events of bond stretching and bond hydration during dissociation and establish that in this system, it is the bond stretching and not hydration which forms the bottleneck in the early parts of the dissociation process. We believe these calculations represent a step forward in the use of atomistic simulations to study pharmacokinetics. An improved understanding of biotin-streptavidin dissociation dynamics should also have direct benefits in biotechnological and nanobiotechnological applications.

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Year:  2017        PMID: 29117680     DOI: 10.1021/acs.jpcb.7b09510

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  4 in total

1.  Role of Molecular Interactions and Protein Rearrangement in the Dissociation Kinetics of p38α MAP Kinase Type-I/II/III Inhibitors.

Authors:  Wanli You; Chia-En A Chang
Journal:  J Chem Inf Model       Date:  2018-04-16       Impact factor: 4.956

2.  Assessing models of force-dependent unbinding rates via infrequent metadynamics.

Authors:  Willmor J Peña Ccoa; Glen M Hocky
Journal:  J Chem Phys       Date:  2022-03-28       Impact factor: 3.488

3.  Mechanistic insights of key host proteins and potential repurposed inhibitors regulating SARS-CoV-2 pathway.

Authors:  Debabrata Pramanik; Aiswarya B Pawar; Sudip Roy; Jayant Kumar Singh
Journal:  J Comput Chem       Date:  2022-05-10       Impact factor: 3.672

4.  A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors.

Authors:  João Marcelo Lamim Ribeiro; Davide Provasi; Marta Filizola
Journal:  J Chem Phys       Date:  2020-09-28       Impact factor: 3.488

  4 in total

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