In silico study of allosteric communication networks in GPCR signaling bias

Morales Pastor, Adrián; Nerín-Fonz, Francho; Aranda García, David; Dieguez-Eceolaza, Miguel; Medel Lacruz, Brian; Torrens Fontanals, Mariona; Peralta-Garcia, Alejandro; Selent, Jana

doi:http://dx.doi.org/10.3390/ijms23147809

In silico study of allosteric communication networks in GPCR signaling bias

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Citació

Morales-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/ijms23147809

Resum

Signaling 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.