Stiffening of flexible SUMO1 protein upon peptide-binding: Analysis with anisotropic network model.

Ranja Sarkar

Journal: Mathematical biosciences 2018;295():67-72

PMID: 29155132

Abstract

SUMO (small ubiquitin-like modifier) proteins interact with a large number of target proteins via a key regulatory event called sumoylation that encompasses activation, conjugation and ligation of SUMO proteins through specific E1, E2, and E3-type enzymes respectively. Single-molecule atomic force microscopic (AFM) experiments performed to unravel bound SUMO1 along its NC termini direction reveal that E3-ligases (in the form of small peptides) increase mechanical stability (along the axis) of the flexible protein upon binding. The experimental results are expected to correlate with the intrinsic flexibility of bound SUMO1 protein in the native state i.e., the bound conformation of SUMO1 without the binding peptide. The native protein flexibility/stiffness can be measured as a spring constant by normal mode analysis. In the present study, protein normal modes are computed from the protein structural data (as input from protein databank) via a simple anisotropic network model (ANM). ANM is computationally inexpensive and hence, can be explored to investigate and compare the native conformational dynamics of unbound and bound (without the binding partner) structures, if the corresponding structural data (NMR/X-ray) are available. The paper illustrates that SUMO1 stiffens (native flexibility decreases) along the NC termini (end-to-end) direction of the protein upon binding to small peptides; however, the degree of stiffening is peptide sequence-specific. The theoretical results are demonstrated for NMR structures of unbound SUMO1 and that bound to two peptides having short amino acid motifs and of similar size, one being an M-IR2 peptide derived from RanBP2 protein and the other one derived from PIASX protein. The peptide derived from PIASX stiffens SUMO1 remarkably which is evident from an atomic-level normal mode analysis.

Copyright © 2017 Elsevier Inc. All rights reserved.

Address: School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110 067, India. Electronic address: [email protected].

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