Codexis, Inc.

Donald Scott Baskerville

Xiyun Zhang

Jonathan Vroom

Nikki Dellas

David Elgart

Mathew G Miller

Russell Javiniar Sarmiento

Sandy M Gomes

Gjalt W Huisman

Jovana Nazor

Vesna Mitchell

Ericka Bermudez

Nandhitha Subramanian

Judy Victoria Antonio Viduya

Gjait W Huisman

The present invention provides engineered ligase polypeptides and compositions thereof, as well as polynucleotides encoding the engineered ligase polypeptides. The invention also provides methods for use of the compositions comprising the engineered ligase polypeptides for diagnostic and other purposes.

Engineered ligase variants

The present invention provides engineered DNA polymerase polypeptides and compositions thereof, as well as polynucleotides encoding the engineered DNA polymerase polypeptides. The invention also provides methods for use of the compositions comprising the engineered DNA polymerase polypeptides for diagnostic and other purposes.

Engineered DNA polymerase variants

Disclosed are methods for identifying bio-molecules with desired properties (or which are most suitable for a round of directed evolution) from complex bio-molecule libraries or sets of such libraries. Some embodiments of the present disclosure provide methods for virtually screening proteins for beneficial properties. Some embodiments of the present disclosure provide methods for virtually screening enzymes for desired activity and/or selectivity for catalytic reactions involving particular substrates. Some embodiments combine screening and directed evolution to design and develop proteins and enzymes having desired properties. Systems and computer program products implementing the methods are also provided.

Automated screening of enzyme variants

Disclosed are methods for building a sequence activity model with reference to structural data, which model can be used to guide directed evolution of proteins having beneficial properties. Some embodiments use genetic algorithms and structural data to filter out uninformative data. Some embodiments use a support vector machine to train the sequence activity model. The filtering and training methods can generate a sequence activity model having higher predictive power than conventional modeling methods. Systems and computer program products implementing the methods are also provided.

Methods and systems for engineering biomolecules

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Burlingame, CA, United States of America

Donald Scott Baskerville