Chandran Nithin

This paper analyzes RNA structure prediction challenges in CASP16, showing that accuracy decreases from local helices to multimer assembly due to monomer errors and interface modeling issues.

This study shows antagonist binding disrupts IL1R1 dynamics to block co-receptor recruitment, contrasting with agonist-induced stabilization of signaling conformations.

This paper evaluates blind predictions of dynamic water and ion ensembles around RNA using cryo-EM densities from CASP16, finding that molecular dynamics approaches perform best.

The paper evaluates the effectiveness of molecular dynamics simulations in refining RNA models from CASP15, finding that they improve high-quality models but not poor ones, and provides guidelines for their use.

The paper reports RNA 3D structure prediction results for SARS-CoV-2 5'- and 3'-UTRs using computational methods and expert analysis.

This study maps SARS-CoV-2 RNA structures at single-base resolution using SHAPE-MaP, identifies druggable pockets and conserved elements, and highlights targets for antisense therapeutics.