01
Open source models stay unchanged
ProteinIQ runs the open-source tools researchers already trust. Defaults, scoring, output names, and citations stay aligned with the source code.
Our mission
Make bioinformaticseasily accessible.
We make state-of-the-art bioinformatics models accessible to everyone with a browser. Protein folding, screening, sequence alignment, docking, and molecular dynamics.
6,500+ members
Researchers, students, and biotech teams running real analyses.
227+ scientific tools
Folding, docking, design, RNA, genomics, and structure analysis.
25,000+ analyses run
Tracked result history with files, settings, and exports.
Research stories
Published work using ProteinIQ in real studies.
At our core
We are focused on one thing: making serious computational biology practical without compromising scientific detail.
02
Complete results by default
Every analysis should leave an auditable record: structures, tables, logs, downloadable files, confidence scores, settings, and source citations.
03
Move quickly and verify things
We ship new scientific capabilities quickly, then keep tightening validation, error handling, output review, and reproducibility details.
Community
Collaboration across labs
ProteinIQ is used from universities, biotech teams, classrooms, and independent research projects. The common need is the same: reproducible computation without a local infrastructure project first.
Academic labs
Biotech teams
Students
Drug discovery
Protein design
Our path of progress
From accessible execution to broad computational biology coverage.
Latest research
All storiesCoa6-CoQ10 binding site modeled with Protenix
Researchers used Protenix to model how CoQ10 binds Coa6 in a mouse study of mitochondrial memory impairment.
Anticancer plant peptides profiled with ProteinIQ
Researchers in Poland used ProteinIQ to compute physicochemical properties of bioactive peptides derived from in silico hydrolysis of anticancer plant antimicrobial peptides.
Molecules review recommends GNINA and PocketFlow for enzyme engineering
A comprehensive Molecules review of AI-driven enzyme engineering cited ProteinIQ as a recommended interface for GNINA and PocketFlow molecular docking tools.