Morales Pastor, AdriánNerín-Fonz, FranchoAranda García, DavidDieguez-Eceolaza, MiguelMedel Lacruz, BrianTorrens Fontanals, MarionaPeralta-Garcia, AlejandroSelent, Jana2023-01-312023-01-312002Morales-Pastor A, Nerín-Fonz F, Aranda-García D, Dieguez-Eceolaza M, Medel-Lacruz B, Torrens-Fontanals M, Peralta-García A, Selent J. In silico study of allosteric communication networks in GPCR signaling bias. Int J Mol Sci. 2022 Jul 15;23(14):7809. DOI: 10.3390/ijms231478091422-0067http://hdl.handle.net/10230/55490Signaling bias is a promising characteristic of G protein-coupled receptors (GPCRs) as it provides the opportunity to develop more efficacious and safer drugs. This is because biased ligands can avoid the activation of pathways linked to side effects whilst still producing the desired therapeutic effect. In this respect, a deeper understanding of receptor dynamics and implicated allosteric communication networks in signaling bias can accelerate the research on novel biased drug candidates. In this review, we aim to provide an overview of computational methods and techniques for studying allosteric communication and signaling bias in GPCRs. This includes (i) the detection of allosteric communication networks and (ii) the application of network theory for extracting relevant information pipelines and highly communicated sites in GPCRs. We focus on the most recent research and highlight structural insights obtained based on the framework of allosteric communication networks and network theory for GPCR signaling bias.application/pdfeng© 2022 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/).info:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/ijms23147809GPCRAllosteric communication networksBiased agonistFunctional selectivityMolecular dynamicsNetwork theoryReceptor dynamicsSignaling biasinfo:eu-repo/semantics/openAccess