FlexAIDdS: A Modern Flexible AI Molecular Docking Tool to Accelerate Drug Discovery Processes

FlexAIDdS is a flexible molecular docking tool redeveloped based on C++26. Integrating AI technology and modern software engineering, it provides an efficient and user-friendly molecular simulation solution for computational chemistry and drug design. With "Fast, Flexible, Free" as its core values, it aims to accelerate drug discovery processes, lower the barrier to use, and is suitable for various research teams.

Drug discovery takes 10-15 years and is costly, making molecular docking technology in computational chemistry crucial. Molecular docking simulates the binding mode between ligands and target proteins, but molecular conformational changes (side chain rotation, loop flexibility, etc.) in real processes make rigid docking inaccurate. The significance of flexible docking research lies in considering these dynamic changes.

FlexAIDdS is a modern redeveloped version of FlexAID. Key upgrades include: 1. Implemented with C++26 standard, using features like modules, coroutines, and concepts to enhance code safety and performance; 2. Python bindings, supporting integration with frameworks like PyTorch and interaction with Jupyter; 3. PyMOL plugin NRGsuite provides a GUI to visualize docking results and intermolecular interactions.

Traditional scoring functions (force field, empirical, knowledge-based) have limitations. AI/ML methods discover complex patterns from massive data through feature engineering (atomic descriptors, etc.), model selection (graph neural networks, etc.), and end-to-end learning, improving prediction accuracy.

Compared with mainstream tools: AutoDock Vina (rigid/semi-flexible), GROMACS (molecular dynamics), Glide (commercial), DeepDock (AI-driven), FlexAIDdS emphasizes full flexible docking, AI scoring, ease of use, and open-source free access, making it suitable for fast virtual screening.

Applicable to multiple stages of drug discovery: virtual screening (large-scale compound libraries), lead compound optimization (structural modification prediction), off-target effect evaluation (side effect risk identification), natural product research (handling complex flexible molecules).

Limitations: Large conformational search space makes it hard to find the global optimum, limited accuracy of scoring functions, insufficient handling of large backbone movements. Future directions: Integrate AlphaFold structures, introduce generative AI, combine FEP calculations, develop cloud service versions.

FlexAIDdS integrates AI, high-performance computing, and modern software engineering to provide a "Fast, Flexible, Free" solution, with a focus on user experience. It is suitable for researchers in drug discovery, computational chemistry, and other fields, and is expected to become an open-source benchmark.