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Garcia-Recio, A.

Publications and source records attributed to Garcia-Recio, A..

3 recordsLinked to original sources

Integrative Biophysical Illumination of the 3D GPCRome Dynamics

Achieving high-resolution insights into protein dynamics remains a major challenge, particularly for membrane proteins such as G protein-coupled receptors (GPCRs) - a highly dynamic class of cell surface receptors and key drug targets. Here, we present an integrative strategy that bridges computational and experimental biophysical methods for probing protein dynamics. To illustrate its potential, we developed GPCRmd-NMR, a platform that synergistically combines molecular dynamics (MD) simulations with high-resolution nuclear magnetic resonance (NMR) spectroscopy across the 3D GPCRome. The resulting dataset maps over 20 billion NMR signals to more than 7 million conformational snapshots of GPCRs, enabling structure-resolved analysis at an unprecedented scale. Application across multiple GPCRs provides access to previously underexplored functional GPCR dynamics, receptor states, and sites, including microswitches and hidden ligand entrance gateways. Our integrated framework offers a powerful solution to long-standing challenges faced by both experimental and computational researchers. To support broad accessibility, GPCRmd-NMR is available as an open-access, web-based framework equipped with user-friendly analysis tools (https://www.gpcrmd.org/gpcrmd-nmr-tool) and is readily applicable to other dynamic protein families beyond GPCRs and other types of biophysical data.

bioinformatics↗

TMSNP: a web server to predict pathogenesis of missense mutations in transmembrane region of membrane proteins

The massive amount of data generated from genome sequencing have given rise to several mutation predictor tools although no mutation database or predictor tool have been developed specifically for the transmembrane region of membrane proteins. We present TMSNP, a database that currently contains information from 2624 pathogenic and 195964 non-pathogenic reported mutations located on the TM region of membrane proteins. The computed conservation parameters and annotations on these mutations were used to train a machine-learning model that classifies TM mutations as pathogenic or non-pathogenic. The presented tool improves considerably the prediction power of commonly used mutation predictors and additionally represents the first mutation prediction tool specific for TM mutations. TMSNP is available at http://lmc.uab.es/tmsnp/ Contactmireia.olivella@esci.upf.edu

bioinformatics↗

DIMERBOW: exploring possible GPCR dimer interfaces

G protein-coupled receptors (GPCRs) can form homo-, heterodimers and larger order oligomers that exert different functions than monomers. The pharmacological potential of such complexes is hampered by the limited information available on the type of complex formed and its quaternary structure. Several GPCR structures in the Protein Data Bank display crystallographic interfaces potentially compatible with physiological interactions. Here we present DIMERBOW, a database and web application aimed to visually browse the complete repertoire of potential GPCR dimers present in solved structures. The tool is suited to help finding the best possible structural template to model GPCR homomers. DIMERBOW is available at http://lmc.uab.es/dimerbow/.

bioinformatics↗