Sign in
BioinformaticsCommunications Biology
Peer-reviewed journal article

Ovo, an Open-Source Ecosystem for De Novo Protein Design

David PříhodaiD, Marco AnconaiD, Tereza Calounova, Adam Kral, Lukas PolakiD, Hugo Hrbáň, Nicholas J. DickensiD, Danny A. BittoniD

Abstract

The protein design field is rapidly advancing, with frequent emergence of new models and pipelines for designing de novo proteins with tailored properties and functions not found in nature. However, the current tool landscape is fragmented, tools are hard to install and deploy, and require significant computational expertise to integrate into end-to-end, scalable pipelines. A particular challenge is managing many sequences, structures, and metrics for downstream testing and retrospective analysis of input parameters. To address this need, we introduce Ovo, an open-source de novo protein design ecosystem that consolidates models, workflows, data management, and interactive visualization into a scalable, infrastructure-agnostic platform. Ovo features Nextflow-based workflow orchestration, a storage layer, and both command-line and graphical interfaces that democratize scaffold design, binder design and diversification, and validation workflows. Ovos novel ProteinQC module computes comprehensive sequence and structure descriptors, contextualizing designs against reference sets. Ovo plugins let the community add new workflows and user interfaces to accelerate adoption of emerging methods and facilitate community-driven benchmarking. Ovo lowers engineering barriers and demystifies the design process, allowing experts and non-technical users to design proteins at scale. With community-driven development, Ovo can accelerate de novo protein design and advance discovery in therapeutics and biotechnology.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
4
FWCI
8.21
Field percentile
top 3%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISOlivieri '26Chacón-Sánc '25Quargnali '26Silke '26Hopf '26Stam '21
71% semantic matchSynthetic Biology
Federico Olivieri, Alina V. Konstantinova, Neža Ribnikar+5 more·bioRxiv·Jun 26, 2026· 2 citations