Bioinformatics Computing
Biomedical AI cloud for drug discovery and protein design
Overview
A biomedical smart-cloud platform built on NVIDIA NIM microservices — integrating OpenFold3, RFdiffusion and ProteinMPNN to deliver one-stop cloud compute for protein-structure prediction, molecular design and drug discovery.
Bioinformatics Computing follows the BioViMo pattern — a notebook-first platform that exposes 9+ frontier biomedical AI models as ready-to-call services, plus visual workflow orchestration that chains structure prediction, sequence design, molecular generation and docking into a single end-to-end run. GPU elastic scheduling on NVIDIA RTX PRO 6000 (96 GB GDDR7) keeps cost aligned to actual research throughput — large enough to hold AlphaFold2 weights and a target complex in card memory, fast enough for batch molecular-docking sweeps, and quiet/power-efficient enough for interactive lab notebooks.
What you get
Frontier biomedical models
9+ pre-trained models exposed as services — AlphaFold2, AF2 Multimer, OpenFold3, OpenFold2, RFdiffusion, ProteinMPNN, MSA-Search, GenMol and DiffDock — covering structure prediction, sequence design and molecular docking.
NVIDIA NIM microservices
Models are packaged as NVIDIA NIM microservices for consistent, GPU-accelerated, production-grade inference — versioned, monitored and instantly swappable.
Automated workflows
Two prebuilt pipelines ready to run: Protein Binder Design (AlphaFold2 → RFdiffusion → ProteinMPNN → AF2-Multimer) and Virtual Screening (OpenFold3 → MSA-Search → GenMol → DiffDock).
Visual workflow engine
Drag-and-drop editor for chaining models into custom biomedical pipelines — multi-model serial execution from input to output, with shareable, reproducible runs.
Data management
Secure storage and management for standard formats (PDB, FASTA, SDF), with upload, task-result viewing and download built into the workspace.
Elastic GPU scheduling on RTX PRO 6000
GPU resources scale on demand across NVIDIA RTX PRO 6000 cards (96 GB GDDR7) — ideal for protein-structure prediction (AlphaFold2 / OpenFold3 hold weights and a target in card memory), generative protein design (RFdiffusion, ProteinMPNN), molecular docking sweeps (DiffDock), and interactive Jupyter notebooks for in-silico research. Pay only for the compute you use, with no idle-allocation overhead.
Benefits
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Talk to our Bioinformatics Computing team
Discuss your requirements with a bioinformatics computing specialist.