In silico analysis of MALAT1 and H19 lncRNA interactions with the diabetes-related proteins ASK1 and YAP1
TL;DR
A hypothesis-generating in silico approach provides a framework for experimental validation of lncRNA-mediated regulation in diabetes-related signalling pathways by identifying structurally plausible RNA–protein interaction interfaces that overlap with known regulatory hotspots in YAP1.
Abstract
Dysregulation of RNA–protein signalling networks contributes to the progression of diabetes-associated complications, yet the structural mechanisms underlying lncRNA interactions with key signalling proteins remain largely unknown. This study investigates potential interaction interfaces between MALAT1–ASK1 and H19–YAP1 using a hypothesis-generating in silico approach. A computational pipeline integrating structure prediction, molecular docking, and molecular dynamics simulations was employed. Structural assessment showed high local confidence for both proteins and lncRNAs (PAE < 1 Å) but low global lncRNA folding reliability (pTM < 0.5), consistent with intrinsic structural flexibility. ASK1 and YAP1 exhibited multiple surface cavities and disordered regions involved in signalling regulation. Docking and simulations suggested MALAT1 binding to exposed ASK1 surfaces, while H19 was predicted to associate with YAP1 regions encompassing the TEAD-binding domain and conserved regulatory phosphorylation sites, including residues corresponding to Ser109, Ser127, and Thr119. Molecular dynamics indicated transient stabilisation with persistent conformational heterogeneity. These results identify structurally plausible RNA–protein interaction interfaces that overlap with known regulatory hotspots in YAP1. Overall, this work provides a framework for experimental validation of lncRNA-mediated regulation in diabetes-related signalling pathways.
