Rapid Evolutionary Conservation Mapping with Face Lifted ConSurf
The ConSurf pipeline provides a quick and accurate estimate of the evolutionary conservation profile of proteins, RNA and DNA. Mapping of the conservation profile on AlphaFold models readily reveals functionally important regions, e.g., catalytic and binding sites, which are often conserved. ConSurf is available for academic and commercial use using a web-server, as well as a stand-alone pipeline.
Unmet Need
Researchers and biotech companies require fast, accurate tools to identify functionally critical regions (e.g., active or binding sites) in macromolecules. Existing solutions are limited in scale, speed, or usability, and often lack integration with modern AI-generated structural data.
Our Solution
A revamped ConSurf platform that:
• Integrates AlphaFold structural models seamlessly
• Uses HMM-based homolog retrieval for cleaner datasets
• Offers an intuitive web interface and a downloadable Python pipeline
• Enables rich visualization output: 3D protein coloring and PyMOL/ChimeraX sessions
Unique Advantages
• Cloud and local deployment options: use via web or standalone Python toolkit
• High-throughput compatibility: scalable for proteome-wide or RNA analyses
• Seamless integration with AlphaFold ChimeraX and PyMOL, streamlining discovery workflows
• We are developing an AI-based ConSurf, which will leverage the flood of sequence data. ConSurf-AI should allow full genome/proteome analysis within a few minutes only.

Potential Applications
• Drug & ligand binding site prediction
• Mutation prioritization in precision medicine
• RNA functional motif detection
• Structure-guided enzyme engineering and synthetic biology
Status
ConSurf is available for non exclusive licensing with commercial and academic terms.
References
ConSurf site has a lot of information: http://consurf.tau.ac.il/
Using evolutionary data to make sense of macromolecules with a “face-lifted” ConSurf. Yariv et al; https://onlinelibrary.wiley.com/doi/full/10.1002/pro.4582
ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Ashkenazy et al; https://academic.oup.com/nar/article/44/W1/W344/2499373
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