ILbind

ILbind predicts inverse ligand–protein binding interactions to identify potential off-target protein partners of small-molecule ligands for elucidating unintended molecular interactions and drug side-effect mechanisms.

Key Features:

• Comprehensive Prediction: Generates a detailed set of putative protein targets for ligands, identifying over 100 potential partners for Cyclosporine A (CSA) in reported analyses.
• Consensus Integration: Combines FINDSITE and SMAP into a consensus predictor augmented by Support Vector Machines (SVM) for refined scoring.
• Improved Predictive Quality: Empirical evaluations indicate predictive performance that surpasses other available predictors for specific compounds such as CSA.
• Structural Proteomics Input: Leverages structural proteomics data from the human proteome to inform target prediction.

Scientific Applications:

• Off-target identification: Predicts unintended protein interactions of ligands to support pharmacology and toxicology research.
• Mechanistic toxicology: Links predicted targets (for example, calpain 2, caspase 3, and p38 MAP kinase 14) to apoptotic pathways and nephrotoxicity associated with cyclosporine A.
• Drug safety and design: Informs safer drug design and personalized medicine strategies by revealing potential molecular bases of side effects.

Methodology:

Integrates FINDSITE and SMAP into a consensus algorithm using Support Vector Machines (SVM), employs a novel inverse ligand binding prediction algorithm, leverages structural proteomics data, and has been evaluated using molecular docking and molecular dynamics simulations.