Abstract
A methodology for elucidation of structural, functional, and mechanistic knowledge on promiscuous proteins is proposed that constitutes a workflow of integrated bioinformatics analysis. Sequence alignments with closely related homologues can reveal conserved regions which are functionally important. Scanning protein motif databases, along with secondary and surface accessibility predictions integrated with post-translational modification sites (PTMs) prediction reveal functional and protein-binding motifs. Integrating this information about the protein with the GO, SCOP, and CATH annotations of the templates can help to formulate a 3D model with reasonable accuracy even in the case of distant sequence homology. A novel integrative model of the non-structural protein 5A of Hepatitis C virus: a hub promiscuous protein with roles in virus replication and host interactions is proposed. The 3D structure for domain II was predicted based on, the Homo sapiens Replication factor-A protein-1 (RPA1), as a template using consensus meta-servers results. Domain III is an intrinsically unstructured domain with a fold from the retroviral matrix protein, which conducts diverse protein interactions and is involved in viral replication and protein interactions. It also has a single-stranded DNA-binding protein motif (SSDP) signature for pyrimidine binding during viral replication. Two protein-binding motifs with high sequence conservation and disordered regions are proposed; the first corresponds to an Interleukin-8B receptor signature (IL-8R-B), while the second has a lymphotoxin beta receptor (LTβR) high local similarity. A mechanism is proposed to their contribution to NS5A Interferon signaling pathway interception. Lastly, the overlapping between LTβR and SSDP is considered as a sign for NS5A date hubs.
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ElHefnawi, M.M., Youssif, A.A., Ghalwash, A.Z., Behaidy, W.H.E. (2010). An Integrated Methodology for Mining Promiscuous Proteins: A Case Study of an Integrative Bioinformatics Approach for Hepatitis C Virus Non-structural 5a Protein. In: Arabnia, H. (eds) Advances in Computational Biology. Advances in Experimental Medicine and Biology, vol 680. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5913-3_34
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