What is it about?

Understanding of structure-function relationships and sequence analysis are important for protein structure decoding. In our previous studies, we demonstrated that conformational dynamics of amino acid residues in oligopeptides derived from regulatory proteins such as alpha-fetoprotein (AFP), carcino-embryonic antigen (CEA), and pregnancy specific β1-glycoproteins (PSGs) contributes greatly to their biological activities. In the present work, we studied conformational dynamics of human EGF receptor-binding residues located within 22-member linear modules composed of direct and reverse AFP14–20-like heptapeptide motifs linked by CxxGY/FxGx consensus motif.

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Why is it important?

The most important findings of this work include the following: (i) similarity exists in amino acid signatures of both direct and reverse motifs in terms of their physicochemical properties; (ii) molecular dynamics (MD) simulation study demonstrated that key receptor-binding residues in human EGF in the aligned positions of the direct and reverse motifs may have similar distribution of conformational probability densities and dynamic behavior despite their distinct physicochemical properties; (iii) a length of a polypeptide chain (from 7 to 53 residues) has no effect, while disulfide bridging and backbone direction significantly influence the conformational distribution and dynamics of the residues. Our data may contribute to the atomic level structure–function analysis and protein structure decoding; additionally, they may provide a basis for novel protein/peptide engineering and peptide-mimetic drug design.

Perspectives

My ambicious plan is to resolve one the crucial issues in structural biology - protein structure decoding.

Professor Nurbubu T. Moldogazieva
I.M. Sechenov First Moscow State Medical University (Sechenov University)

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This page is a summary of: Human EGF-derived direct and reverse short linear motifs: conformational dynamics insight into the receptor-binding residues, Journal of Biomolecular Structure and Dynamics, May 2017, Taylor & Francis,
DOI: 10.1080/07391102.2017.1321502.
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