Cyrus automates a set of Rosetta protein design software protocols that have been refined and tested on experimental data sets. Cyrus Bench® is an easy-to-use, SaaS offering proven to accelerate protein optimization. • Highest Accuracy Protein Structure Prediction / Homology Modeling – optimize novel protein sequences • Protein Stabilization - via single and multiple point mutations and evolutionary redesign. • Protein / Protein Interface Redesign - with protein flexibility. • Immunogenicity Prediction. - MHC II epitope (T-cell epitope) machine learning based prediction • Enzyme Design - Support for arbitrary small molecules built in with OpenEye integration included • Fast Free Energy Calculations - ΔΔG. • Loop Modeling and Design - optimization or de novo. • Identification of Alternative Protein Structure Conformations - via powerful sampling and scoring protocols. in silico Protein Engineering using Rosetta Validated with over 1000 publications cyrusbio.com (1) Song, Y. et al., "High-Resolution Comparative Modeling with RosettaCM". Structure (2013) 21, 1735. (2) Kellogg et al., “Role of conformational sampling in computing mutation-induced changes in protein structure and stability”. Proteins (2010) 79, 830. (3) Borgo et al., ”Automated selection of stabilizing mutations in designed and natural proteins". PNAS (2012) 109, 1494. (4) Tyka et al., “Alternate states of proteins revealed by detailed energy landscape mapping”. J Mol Biol (2011) 405(2):607-18. (5) Ollikainen, de Jong and Kortemme, “Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity”. PLoS Comput Biol (2015) 11(9) (6) Stein and Kortemme, “Improvements to Robotics-Inspired Conformational Sampling in Rosetta”. PLOS ONE (2013) 8(5): e63090 (7) King et al., “Removing T-cell epitopes with computational protein design”. PNAS (2014) 111, 8581 Protein/Protein Interface Design (5) Immunogenicity Prediction (7) Loop Modeling & Design (6) Alternative Conformations (4) Stabilization (2)(3) (ΔΔG) Homology Modeling (1) Enzyme Design (5)

in silico Protein Engineering using Rosetta - Cyrus Bio · Cyrus automates a set of Rosetta protein design software protocols that have been refined and tested on experimental data

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Page 1: in silico Protein Engineering using Rosetta - Cyrus Bio · Cyrus automates a set of Rosetta protein design software protocols that have been refined and tested on experimental data

•  Highest Accuracy Protein Structure Prediction / Homology Modeling – optimize novel protein sequences

•  Protein Stabilization - via single and multiple point mutations and evolutionary redesign.

•  Protein / Protein Interface Redesign - with protein flexibility.

•  Immunogenicity Prediction. - MHC II epitope (T-cell epitope) machine learning based prediction

•  Enzyme Design - Support for arbitrary small molecules built in with OpenEye integration included

•  Fast Free Energy Calculations - ΔΔG.

•  Loop Modeling and Design - optimization or de novo.

•  Identification of Alternative Protein Structure Conformations - via powerful sampling and scoring protocols.

in silico Protein Engineering using Rosetta Validated with over 1000 publications

cyrusbio.com

(1) Song, Y. et al., "High-Resolution Comparative Modeling with RosettaCM". Structure (2013) 21, 1735.(2) Kellogg et al., “Role of conformational sampling in computing mutation-induced changes in protein structure and stability”. Proteins (2010) 79, 830.(3) Borgo et al., ”Automated selection of stabilizing mutations in designed and natural proteins". PNAS (2012) 109, 1494.(4) Tyka et al., “Alternate states of proteins revealed by detailed energy landscape mapping”. J Mol Biol (2011) 405(2):607-18.(5) Ollikainen, de Jong and Kortemme, “Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity”. PLoS Comput Biol (2015) 11(9)(6) Stein and Kortemme, “Improvements to Robotics-Inspired Conformational Sampling in Rosetta”. PLOS ONE (2013) 8(5): e63090 (7) King et al., “Removing T-cell epitopes with computational protein design”. PNAS (2014) 111, 8581

Protein/Protein Interface Design(5)

Immunogenicity Prediction(7)

Loop Modeling & Design(6)

Alternative Conformations(4)

Stabilization(2)(3)

(ΔΔG)

Homology Modeling(1)

Enzyme Design(5)