Atomwise
Atomwise is an AI-powered Science tool — AI for structure-based drug discovery (atom-by-atom). Best for: Science Research & Data Analysis. Pricing: Paid (GateOnAI Score: 52/100).
AI for structure-based drug discovery (atom-by-atom).
Provides AI-driven virtual screening for small‑molecule drug candidates by analyzing three‑dimensional protein structures. The platform runs deep convolutional neural networks trained on millions of protein‑ligand complexes to predict binding affinity and pose accuracy. Users upload target structures in PDB format, set screening parameters, and receive ranked hit lists within hours, replacing weeks of manual docking. Atomwise also offers an API that returns probability scores for each compound, enabling integration with existing cheminformatics pipelines. The engine also cross‑references public bioactivity databases to enrich predictions with known assay results. Key capabilities include AtomNet, a proprietary 3D CNN model that evaluates chemical interactions atom by atom; batch processing of libraries up to billions of molecules; built‑in ADMET filter that flags toxicity and metabolic liabilities; and visualization tools that overlay predicted poses onto the target structure; and a collaboration workspace where chemists can annotate hits and share reports. The system supports cloud deployment on AWS or on‑premise clusters for data‑sensitive projects, and logs all activity for audit compliance. Export options cover SDF, CSV, and JSON formats for downstream synthesis planning. Pharma R&D teams, biotech start‑ups, and academic labs use the service to narrow down hit identification, accelerate lead optimization, and reduce wet‑lab costs. The subscription model provides unlimited screening cycles, priority support, and quarterly model updates, with pricing tiers based on library size and compute allocation. Because the tool requires a paid plan, it is best suited for organizations that can allocate budget for high‑throughput in‑silico screening rather than occasional ad‑hoc queries.
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Works Well With
Tools that Atomwise genuinely connects with, based on real input/output compatibility data (not just shared category):
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