Our mission is to make bioinformatics accessible

Our vision

Dear researcher,

Welcome to ProteinIQ. We’re building one place where the best open-source methods in computational biology are ready to run from a browser.

Every month brings new models for folding, docking, and design. Most never reach the scientists who could use them, because trying a tool from a paper still means days of software setup, hunting for GPUs, and moving files between analyses.

Today, 290+ tools share one workspace, and more than 14,700 researchers use them to predict structures, screen compounds, design proteins, and run simulations. Their files and results stay together, ready for the next question.

Useful methods now appear faster than any lab can install them. Before us lies a chance to change how science moves from publication to practice.

Better experiments start with better computation. If every researcher can use the right method for their question without waiting on infrastructure, good ideas get tested sooner, and fewer of them are left on the table.

Matic BrozMatic Broz's signature

How we work

ProteinIQ runs the open-source tools researchers already trust, and we keep them unchanged. Defaults, scoring, output names, and citations stay aligned with the published source code, so a result from ProteinIQ means the same thing as a result from the original software.

Every analysis should leave a complete, auditable record. That means structures, tables, logs, downloadable files, confidence scores, the settings you used, and the papers to cite, all kept with the job rather than scattered across a laptop.

Our journey

Matic Broz founded ProteinIQ on May 24, 2025, to make serious bioinformatics tools usable without local infrastructure. The first version launched a day later with 13 browser-based tools for protein parameters, sequence processing, drug discovery, and structure viewing.

The summer went into the everyday file work that sits around every analysis. Dedicated converters from FASTQ, PDB, SDF, and plain text to FASTA arrived in June. At the end of August, server-side compute opened up heavier molecular workflows that a browser alone could not run.

October 2025 brought the first generally available cloud tools, including protein parameters, ADMET-AI, and FASTA splitting. Soon after, every tool moved into one shared layout, with inputs and settings beside the output and a history of past jobs a click away.

From November the catalogue grew quickly. DiffDock-L and GNINA brought molecular docking. LigandMPNN, ProteinMPNN, and SolubleMPNN added sequence design, while Boltz-2, Chai-1, and RFdiffusion 2 covered biomolecular structure prediction and backbone design. The first paid plans went live in mid-November for researchers who needed more compute, while the core sequence and property tools became free. We also started writing guides for practical bioinformatics.

December added Protenix for AlphaFold 3-style complex prediction, then AlphaFold2, MAFFT, Foldseek, IQ-TREE, MUSCLE5, and HMMER for folding, alignment, structure search, and phylogenetics. Full-screen outputs arrived at the same time, and by the end of the year DockQ, AlphaFlow, and AutoDock-GPU had deepened docking review and conformational sampling.

In January 2026 the community passed 1,000 members. Antibody work became a focus with AbLang, AntiFold, and ImmuneBuilder, alongside the AI Assistant for day-to-day research support and gmx_MMPBSA for binding free energy estimates. Membership doubled to 2,000 by March, lighter self-serve plans for individuals and small teams followed in April, and we crossed 5,000 members at the end of that month. In September, batch runs became generally available, so one submission can test many candidates instead of one at a time.

Today more than 14,700 members run folding, docking, design, sequence, and analysis workflows across 290+ tools. They work in university labs, biotech teams, classrooms, and independent projects.

Their work is starting to appear in the literature. Researchers at Michigan State University validated predicted viral protein structures for a study in Microorganisms, a team at Zhejiang University screened AI-designed peptides for the Journal of Medicinal Chemistry, and scientists at the Barcelona Supercomputing Center and ICP-CSIC compared plastic-degrading enzymes in Microbial Biotechnology. Groups at the Czech Academy of Sciences and the Fourth Military Medical University have published with ProteinIQ in BMC Plant Biology and Translational Neurodegeneration. More are collected in our research stories.

Careers

ProteinIQ is a small team, and we hire when the right person shows up rather than on a fixed schedule. There are no dated vacancies right now, but we read every open application.

We are especially interested in computational biologists who can integrate new open-source tools and check wrapper output against the source papers, frontend engineers who enjoy dense scientific interfaces in React and TypeScript, and scientific writers who can keep guides and documentation accurate to the underlying methods.

Don't see your area? Write to hello@proteiniq.io with what you would like to work on and links to your work.