miRNAProtPred

miRNAProtPred consolidates seed complementarity matching and ViennaRNA-based thermodynamic analysis into a workflow for predicting human miRNA binding sites on DNA, RNA, or protein target sequences.

Key Features:

• SeqFinder module: A discovery engine to find all potential miRNA interactions across a genome or target sequence.
• Validator module: A targeted verification engine to test specific user-provided miRNAs against a target sequence.
• Integrated miRNA database: Contains 2,656 curated human miRNAs from miRDB and miRBase.
• Multi-input format support: Accepts DNA, RNA, or protein sequences as input.
• Multi-criteria confidence framework: Classifies predictions through seed complementarity, thermodynamic stability (minimum free energy, MFE), flanking AU content, motif identity, and match type.
• Strict search mode: Requires exact Watson-Crick seed complementarity.
• Relaxed search mode: Extends sensitivity to G:U wobble-supported interactions through a hierarchical exact-first fallback strategy.
• Biological evaluation engine: Evaluates exact seed matching, wobble pairing, AU-rich context, and RNAduplex thermodynamic stability.

Scientific Applications:

• Viral miRNA target prediction: Identifies experimentally supported inhibitory miRNAs in viral systems such as SARS-CoV-2 and HIV-1.
• Large-scale miRNA-target benchmarking: Evaluates precision-oriented performance on datasets such as miRAW (62,215 miRNA-target pairs).
• Experimental candidate prioritization: Facilitates prioritization of miRNA binding site predictions for experimental validation through MFE-based confidence classification.

Methodology:

miRNAProtPred uses seed complementarity matching and ViennaRNA-based thermodynamic analysis, incorporating RNAduplex for thermodynamic stability calculations. The tool evaluates exact seed matching, wobble pairing, AU-rich context, and minimum free energy (MFE). Predictions are classified through a multi-criteria confidence framework incorporating seed complementarity, thermodynamic stability, flanking AU content, motif identity, and match type.