bioRxivBioinformaticsPreprint
BioChemAIgent: An AI-driven Protein Modeling and Docking Framework for Structure-Based Drug Discovery
Behnam YousefiiD, Nora Constanze LaubachiD, Sven HeinsiD, Lucia TestaiD, Søren W. GerstingiD, Stefan BonniD
Abstract
Recent advances in AI have substantially accelerated in silico drug discovery, yet most computational approaches remain task-specific and require expert knowledge. We present BioChemAIgent, an agentic framework that orchestrates state-of-the-art AI models and established computational chemistry tools to support end-to-end small-molecule analysis, protein modeling, molecular docking, and interaction analysis through a unified interface. BioChemAIgent emphasizes transparent reasoning, reproducible workflows, and community-oriented extensibility for structural biology and drug discovery applications.
- assay: protein structure
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 2
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