Mimicking the secondary structures of proteins and peptides to modulate Protein-Protein Interactions

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The human genome encodes for approximately 20,000 different proteins creating a vast network of potential protein-protein interactions (PPI), which is only partially characterized. The protein-protein interactome (network involving PPIs) is central to intracellular pathways and determines any given protein's role in physiology. Modulation of such PPI promises to shed light on the key molecular mechanisms within a biological system and is crucial to understanding how proteins perform cellular functions. At the heart of the program is the development of peptidomimetic molecules, i.e., molecules capable of mimicking the structure of peptides while advantageously adjusting their undesirable properties and the exploitation of computational sciences to analyze the dynamics of such scaffolds and to prioritize compounds to synthesize. 1. Diversity-oriented synthesis of hot-spot enriched PPI inhibitor library Meticulous analysis of the anatomy of PPIs has allowed to characterize the molecular features involved in recognition. We will take advantage of recent findings and our expertise in solid phase-support synthesis to develop a library of novel peptidomimetic PPI modulators designed to expose the same molecular recognition elements as over-represented side chains in hot-spots. These elements will be on scaffolds that provide a chemical space and shape appropriate for the PPI chemical space enriched with molecular recognition elements over-abundant in known PPI inhibitors. We performed a thorough in silico analysis to produce a class of compounds that possess the proper profile in terms of topology and molecular descriptors 2. Rational design and synthesis of secondary structures at PPI interface using 3D prediction approach. Recent advances in structural biology now allow us to elucidate, at the molecular level, the structure of complex macromolecular assemblies and characterize the interactions interface between proteins. Using an innovative and powerful 3D conformation prediction approach combining molecular dynamics, independent component analysis (tICA), and a Gaussian Mixture Hidden Markov Model (GM HMM) recently developed in our group, we will rationally design and synthesize epitope and secondary structures at PPI interfaces mimicking one of the two proteins of interest. This multidisciplinary research program at the interface of chemistry, biology, and computational science is expected to give superior hit rates compared to standard HTS libraries on PPI targets. Association of computational sciences and experimental evaluation will provide insights on the key interactions needed to access highly selective and efficient PPI modulators. Libraries are expected to become a versatile chemical biology set of tools used in phenotypic assays to decipher critical PPI pathways.