Methods, systems, and software for identifying functional biomolecules

Abstract

The present invention generally relates to methods of rapidly and efficiently searching biologically-related data space. More specifically, the invention includes methods of identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The invention also provides methods of modeling sequence-activity relationships. As many of the methods are computer-implemented, the invention additionally provides digital systems and software for performing these methods.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a continuation of U.S. patent application Ser. No. 11 / 429,628, filed May 5, 2006, naming Gustafsson et al. as inventors, and titled “Methods, Systems, and Software for Identifying Functional Biomolecules” which is a divisional of U.S. patent application Ser. No. 10 / 629,351, filed Jul. 29, 2003, naming Gustafsson et al. as inventors, and titled “Methods, Systems, and Software for Identifying Functional Bio-Molecules” which is a continuation in part of U.S. patent application Ser. No. 10 / 379,378, filed Mar. 3, 2003, naming Gustafsson et al. as inventors, and titled “Methods, Systems, and Software for Identifying Functional Bio-Molecules.” U.S. patent application Ser. No. 10 / 629,351 is also a continuation in part of International Application No. PCT / US03 / 06551 filed Mar. 3, 2003, naming Gustafsson et al. as inventors. Both U.S. patent application Ser. No. 10 / 379,378 and International Application No. PCT / US03 / 06551 claim t...

AI Technical Summary

Benefits of technology

[0006]One aspect of the present invention pertains to methods, apparatus, and software for identifying amino acid residues for variation in a protein variant library. These residues are then varied in the sequences of protein variants in the library in order to affect a desired activity such as stability, catalytic activity, therapeutic activity, resistance to a pathogen or toxin, toxicity, etc. The method of this aspect may be described by the following sequence of operations: (a) receiving data characterizing a training set of a protein variant library; (b) from the data, developing a sequence activity model that predicts activity as a function of amino acid residue type and corresponding position in the sequence; and (c) using the sequence activity model to identify one or more amino acid residues at specific positions in the systematically varied sequences that are to be varied in order to impact the desired activity. In this method, the protein variants in the library may have systematically varied sequences. Further, the data provides activity and sequence information for each protein variant in the training set.

Problems solved by technology

Protein design has long been known to be a difficult task if for no other reason than the combinatorial explosion of possible molecules that constitute searchable sequence space.

The sequence space of proteins is immense and is impossible to explore exhaustively.

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