Journal of Molecular ModelingBioinformaticsPeer-reviewed journal article
Computational investigation for modelling the protein-protein interaction of TasA(28-261)with TapA(33-253); a decisive process in biofilm formation by Bacillus subtilis
Nidhi VermaiD, Shubham SrivastavaiD, Ruchi MalikiD, Jay Kant YadaviD, Pankaj GoyaliD, Janmejay PandeyiD
Abstract
Biofilms have significant role in microbial persistence, antibiotic resistance and chronic infections; consequently, there is a pressing need for development of novel "anti-biofilm strategies". One of the fundamental mechanisms involved in biofilm formation is protein-protein interactions of amyloid like proteins (ALPs) in extracellular matrix. Such interactions could be potential targets for development of novel anti-biofilm strategies; therefore, assessing the structural features of these interactions could be of great scientific value. Characterization of biomolecular interaction with conventional structure biology tools including X-Ray diffraction and Nuclear Magnetic Resonance is technically challenging, expensive and time-consuming. In contrast, modelling such interactions is time-efficient, economical and might provide deeper understanding of structural basis of interactions. Therefore, during the present study, protein-protein interaction of TasA(28-261)-TapA(33-253) (which is a decisive process for biofilm formation by Bacillus subtilis) was modeled using in silico approaches viz., molecular modelling, protein-protein docking and molecular dynamics simulations. Results identified amino-acid residues present within intrinsically disordered regions of both proteins to be critical for interaction. These results were further supported with PCA and FEL analyses. Results presented here represent novel finding and we hypothesize that aa identified during the present study could be targeted for inhibition of biofilm formation by B. subtilis.
- organism: bacteria (other)
- assay: protein structure
- research focus: protein structure prediction
- approach: mixed model
- Citations
- 11
- FWCI
- 0.73
- Field percentile
- top 35%
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