DockingMD provides a web‑based platform that combines AI‑assisted docking with fast GPU‑accelerated molecular dynamics to rank and prioritize compounds before wet‑lab assays. Users upload protein and ligand files, run simulations or traditional docking, and receive reproducible reports with built‑in analysis tools such as OpenMM and AutoDock Vina, enabling high‑throughput virtual screening and protein engineering without any local installation.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers often rely on separate, locally installed tools for molecular docking and molecular dynamics (MD) simulations, leading to complex setup, long runtimes, and difficulty reproducing results. This hampers rapid virtual screening and the ability to prioritize compounds before costly wet‑lab assays.
Solution
DockingMD offers a web‑based platform that integrates AI‑assisted docking with GPU‑accelerated MD simulations in a single, no‑install workflow. Users upload protein and ligand files, select either traditional or AI‑enhanced docking, then run predefined or custom MD presets that leverage OpenMM and AMBER force fields. The system automatically generates reproducible analysis reports, including trajectory visualizations and ranking metrics, which can be exported with full configuration metadata. By combining high‑throughput virtual screening, fast MD validation, and built‑in ranking, the platform enables scientists to identify and prioritize promising candidates before committing to experimental assays.
Target Audience
Primary users are academic researchers, biotech startups, and pharmaceutical teams conducting virtual screening and hit‑identification workflows.
Features
- AI‑assisted pose prediction using AutoDock Vina and machine‑learning models
- GPU‑accelerated MD simulations with OpenMM and AMBER force fields, available in standard, high‑memory, and multi‑GPU classes
- In‑browser trajectory visualization and interactive analysis dashboards
- One‑click export of reproducible configuration files and metadata for auditability
- API access for automation and integration with existing pipelines
- Flexible credit‑based usage model allowing pay‑as‑you‑go simulation time