« Previous Abstract"Flavoring Production in Kamut(R), Quinoa and Wheat Doughs Fermented by Lactobacillus paracasei, Lactobacillus plantarum, and Lactobacillus brevis: A SPME-GC/MS Study"    Next AbstractEvolution of a G protein-coupled receptor response by mutations in regulatory network interactions »

Comput Struct Biotechnol J

Title:		Computational structural-based GPCR optimization for user-defined ligand: Implications for the development of biosensors
Author(s):		Di Rienzo L; Miotto M; Milanetti E; Ruocco G;
Address:		"Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy. Department of Physics, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy"
Journal Title:		Comput Struct Biotechnol J
Year:		2023
Volume:		20230509
Issue:
Page Number:		3002 - 3009
DOI:		10.1016/j.csbj.2023.05.004
ISSN/ISBN:		2001-0370 (Print) 2001-0370 (Electronic) 2001-0370 (Linking)
Abstract:		"Organisms have developed effective mechanisms to sense the external environment. Human-designed biosensors exploit this natural optimization, where different biological machinery have been adapted to detect the presence of user-defined molecules. Specifically, the pheromone pathway in the model organism Saccharomyces cerevisiae represents a suitable candidate as a synthetic signaling system. Indeed, it expresses just one G-Protein Coupled Receptor (GPCR), Ste2, able to recognize pheromone and initiate the expression of pheromone-dependent genes. To date, the standard procedure to engineer this system relies on the substitution of the yeast GPCR with another one and on the modification of the yeast G-protein to bind the inserted receptor. Here, we propose an innovative computational procedure, based on geometrical and chemical optimization of protein binding pockets, to select the amino acid substitutions required to make the native yeast GPCR able to recognize a user-defined ligand. This procedure would allow the yeast to recognize a wide range of ligands, without a-priori knowledge about a GPCR recognizing them or the corresponding G protein. We used Monte Carlo simulations to design on Ste2 a binding pocket able to recognize epinephrine, selected as a test ligand. We validated Ste2 mutants via molecular docking and molecular dynamics. We verified that the amino acid substitutions we identified make Ste2 able to accommodate and remain firmly bound to epinephrine. Our results indicate that we sampled efficiently the huge space of possible mutants, proposing such a strategy as a promising starting point for the development of a new kind of S.cerevisiae-based biosensors"
Keywords:		Bio-sensors Gpcr Protein engineering;
Notes:		"PubMed-not-MEDLINEDi Rienzo, Lorenzo Miotto, Mattia Milanetti, Edoardo Ruocco, Giancarlo eng 855923/ERC_/European Research Council/International Netherlands 2023/05/30 Comput Struct Biotechnol J. 2023 May 9; 21:3002-3009. doi: 10.1016/j.csbj.2023.05.004. eCollection 2023"