RLDOCK

RLDOCK predicts RNA–ligand binding sites and poses using an iterative multiscale sampling and search algorithm combined with energy-based evaluation. It identifies energetically favorable RNA–small molecule interaction configurations for structural and drug discovery studies.

Key Features:

• Iterative Multiscale Sampling: Explores potential RNA binding sites and ligand poses through hierarchical sampling and search strategies.
• Energy-Based Scoring: Evaluates predicted RNA–ligand complexes using interaction energy calculations to select stable binding configurations.

Scientific Applications:

• RNA–Ligand Interaction Analysis: Predicts binding modes for RNA-targeted drug design, including docking of Flavin mononucleotide (FMN) to the F. nucleatum FMN riboswitch.

Methodology:

RLDOCK performs iterative multiscale sampling of ligand conformations on RNA structures, followed by energy-based scoring to rank poses and identify energetically favorable RNA–ligand binding configurations.