Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153892
Title: Computational design of macrocyclic binders of S100B(ββ): novel peptide theranostics
Authors: Kannan, Srinivasaraghavan
Aronica, Pietro G. A.
Nguyen, Thanh Binh
Li, Jianguo
Verma, Chandra Shekhar
Keywords: Science::Biological sciences
Issue Date: 2021
Source: Kannan, S., Aronica, P. G. A., Nguyen, T. B., Li, J. & Verma, C. S. (2021). Computational design of macrocyclic binders of S100B(ββ): novel peptide theranostics. Molecules, 26(3), 721-. https://dx.doi.org/10.3390/molecules26030721
Project: H18/01/a0/015
H17/01/a0/010
I1901E0039
Journal: Molecules
Abstract: S100B(ββ) proteins are a family of multifunctional proteins that are present in several tissues and regulate a wide variety of cellular processes. Their altered expression levels have been associated with several human diseases, such as cancer, inflammatory disorders and neurodegenerative conditions, and hence are of interest as a therapeutic target and a biomarker. Small molecule inhibitors of S100B(ββ) have achieved limited success. Guided by the wealth of available experimental structures of S100B(ββ) in complex with diverse peptides from various protein interacting partners, we combine comparative structural analysis and molecular dynamics simulations to design a series of peptides and their analogues (stapled) as S100B(ββ) binders. The stapled peptides were subject to in silico mutagenesis experiments, resulting in optimized analogues that are predicted to bind to S100B(ββ) with high affinity, and were also modified with imaging agents to serve as diagnostic tools. These stapled peptides can serve as theranostics, which can be used to not only diagnose the levels of S100B(ββ) but also to disrupt the interactions of S100B(ββ) with partner proteins which drive disease progression, thus serving as novel therapeutics.
URI: https://hdl.handle.net/10356/153892
ISSN: 1420-3049
DOI: 10.3390/molecules26030721
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SBS Journal Articles

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