| Identification and Characterization of ERK2 Dimerization Inhibitors by Integrated In Silico and In Vitro Screening | | Identification and Characterization of ERK2 Dimerization Inhibitors by Integrated In Silico and In Vitro Screening | Ortiz-González C, Casar B, Gozalbes R, Serrano-Candelas E, Crespo P, Carpio LE. | 2025-11-26T23:00:00Z | <h2>Abstract</h2><p>Protein-protein interactions (PPIs) take place in many cellular processes, including the activation of cellular cascades, such as the MAPK/ERK (Mitogen-Activated Protein Kinase/Extracellular-Regulated Kinase) pathway. Deregulation of these pathways leads to the development of diseases, such as cancer. DEL-22379 is an ERK2 dimerization inhibitor, which presents anti-tumoral effects, without affecting ERK2 phosphorylation. Our aim was to identify new therapeutic molecules targeting ERK2 dimerization, based on DEL-22379 structure. In this study, we implemented a combination of computational and experimental workflow, which includes in silico techniques, such as scaffold hopping and virtual screening to generate a dataset of candidate compounds, a native PAGE (PolyAcrylamide Gel Electrophoresis) electrophoresis to experimentally screen the potential inhibitors, and a detailed molecular docking and chemical profile prediction to understand the potential mechanism of action of the selected compounds. From an initial dataset of 536 compounds, we obtained two hit molecules that exhibited inhibitory effects on ERK2 dimerization: Drug73 and Drug120. A computational analysis of the mechanism of action, unveiled that Drug73 and Drug120 presented an improved docking score, and better drug-like properties when compared to DEL-22379. This study shows that computational studies, in combination with experimental evaluation, can be useful and efficient to find new therapeutic compounds.<br></p><p><strong>Keywords: </strong>ERK dimerization; ERK1/2; MAPK/ERK inhibitors; molecular modelling.<br></p><p><strong>Conflict of interest statement</strong></p><p>Authors Eva Serrano-Candelas and Rafael Gozalbes were employed by the company ProtoQSAR SL; authors Carmen Ortiz-González, Laureano E. Carpio, and Rafael Gozalbes were employed by the company MolDrug AI Systems SL. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br></p> | <p><a href="https://doi.org/10.3390/ijms262311481" target="_blank">Int J Mol Sci. 2025 Nov 27;26(23):11481.</a><br></p> | 576 | | |
