Institute for Protein Design
Google DeepMind
Google DeepMind 
EMBL-EBI
ByteDance
Memorial Sloan Kettering Cancer Center
Steinegger Lab
Steinegger Lab
Salesforce Research
Arc Institute
Calico
NCBI
Biohub
Institute for Protein Design
Biohub
Arc Institute
Google DeepMind
SIB EMBL-EBI 
PIR
NCBI
Steinegger Lab 
Söding Lab
EMBL-EBI
Profluent
Chai Discovery
Ovchinnikov Lab Steinegger Lab
Broad Institute 
The Jackson Laboratory 
Yale University
Proto
RIMD
Proto
Google DeepMind
Meta AI Biohub
Boltz 
MIT Jameel Clinic 
Recursion
Oxford Protein Informatics Group (OPIG)
Institute for Protein Design
Institute for Protein Design
NCBI
UT Southwestern Medical Center 
St. Jude Children’s Research Hospital
Meta AI Biohub
Arc Institute
TBI Vienna
Dunbrack Lab
Microsoft Research
PDBe EMBL-EBI 
wwPDB
NCBI
EMBL-EBI
Biohub
Meta AI Biohub
RosettaCommons
Google DeepMind
Google DeepMind Institute for Protein Design Google DeepMind Google DeepMind EMBL-EBI ByteDance Memorial Sloan Kettering Cancer Center Steinegger Lab Steinegger Lab Salesforce Research Arc Institute Calico NCBI Biohub Institute for Protein Design Biohub Arc Institute Google DeepMind SIB EMBL-EBI PIR NCBI Steinegger Lab Söding Lab EMBL-EBI Profluent Chai Discovery Ovchinnikov Lab Steinegger Lab Broad Institute The Jackson Laboratory Yale University Proto RIMD Proto Google DeepMind Meta AI Biohub Boltz MIT Jameel Clinic Recursion Oxford Protein Informatics Group (OPIG) Institute for Protein Design Institute for Protein Design NCBI UT Southwestern Medical Center St. Jude Children’s Research Hospital Meta AI Biohub Arc Institute TBI ViennaDunbrack Lab
Microsoft Research PDBe EMBL-EBI wwPDB NCBI EMBL-EBI Biohub Meta AI Biohub RosettaCommons Google DeepMind Google DeepMindThe Open-Source Infrastructure Layer for Biology
Proto Tools
A lot of computational biology looks like this: find a tool that does what you need, spend half a day getting it to install, spend another day figuring out how to call it, then reformat the output so the next tool can use it. Every tool has its own opinions about Python versions, CUDA, weight paths, and input formats.Proto Tools wraps these tools so they all behave the same way. Each one is a Python function with a Pydantic input and output. Fold a protein with AlphaFold3, sample sequences with ProteinMPNN, search with BLAST; the shape of the call is the same, and the first invocation quietly sets up the environment and weights in isolation.Use it on its own, or as the tools layer of the broader Proto framework.Key Features
A quick tour of what proto-tools handles for you. Each card opens a deeper guide.Unified Interface
Consistent Python APIs with standardized Pydantic Input/Config/Output models across all tools
Isolated Environments
Each tool gets its own virtual environment; weights and dependencies are fetched and cached on first use
Device Management
Automatic GPU allocation, LRU eviction, and multi-GPU routing
Parallel Execution
Fan a single tool call out across every visible GPU with ToolPool
Tool Catalog
Every wrapped tool, grouped by what it does. Open a category to see its models and a short write-up of each.
Get Started
Installation
Set up the package and optional dependencies
Quickstart
Run your first tool in 5 minutes
Concepts
Understand the tool pattern and execution model