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US 9,665,694 B2Granted
Methods, systems, and software for identifying bio-molecules with interacting components
AssigneeCodexis, Inc.
InventorGregory Allan Cope
Life of this patent
Estimating the term…
Abstract
The present invention provides methods for rapidly and efficiently searching biologically-related data space. More specifically, the present invention provides methods for 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 present invention also provides methods for modeling sequence-activity relationships, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods. The present invention further provides digital systems and software for performing the methods provided herein.
Claims20
A method for activity conducting directed evolution of one or more polypeptide or polynucleotide molecules, the method comprising:
- (a) receiving sequence data of a plurality of polypeptide molecules or a plurality of polynucleotide molecules encoding the plurality of polypeptide molecules, wherein the sequence data comprises identities and positions of a plurality of amino acids for each molecule of the plurality of polypeptide molecules or a plurality of nucleotides for each molecule of the plurality of polynucleotide molecules;
- (b) receiving activity data of the plurality of polypeptide molecules;
- (c) fitting a base model to the received sequence data and the received activity data,
- wherein
- the base model receives as one or more inputs one or more amino acids of a polypeptide molecule or one or more nucleotides of a polynucleotide molecule encoding the polypeptide molecule and provides as an output an activity of the polypeptide molecule,
- the base model includes either (i) a plurality of linear terms and no interaction term or (ii) a plurality of linear terms and one or more interaction terms,
- each linear term comprises a coefficient and an independent variable representing an amino acid or a nucleotide at a sequence position, and
- each interaction term comprises a coefficient and two or more independent variables representing two or more interacting amino acids at two or more sequence positions or nucleotides encoding the two or more interacting amino acids;
- (d) determining a predictive ability of the base model in predicting activity from the identities and the positions of the plurality of amino acids or the plurality of nucleotides, wherein the predictive ability is determined with a bias against including additional terms;
- (e) fitting at least one new model to the received sequence data and the received activity data, wherein the at least one new model is obtained by adding at least one new interaction term to the base model of (i) or (ii) or subtracting at least one new interaction term to or from the base model of (ii);
- (f) determining a predictive ability of the at least one new model in predicting activity from the identities and the positions of the plurality of amino acids or the plurality of nucleotides, wherein the predictive ability is determined with a bias against including additional terms;
- (g) selecting a model from among the base model and the at least one new model based on the predictive ability of the base model and the predictive ability of the at least one new model;
- (h) determining one or more amino acid sequences or one or more nucleic acid sequences using the selected model;
- (i) synthesizing one or more amino acid molecules or one or more nucleic acid molecules based on the one or more amino acid sequences or one or more nucleic acid sequences;
- and
- (j) recombining or performing mutagenesis on the one or more amino acid molecules or one or more nucleic acid molecules to provide the one or more polypeptide or polynucleotide molecules.
13 more elements
A computer program product comprising one or more computer-readable non-transitory storage media having stored thereon computer-executable instructions that, when executed by one or more processors of a computer system, cause the computer system to implement a method for identifying biological molecules to affect a desired activity, the method comprising:
- (a) receiving sequence data of a plurality of polypeptide molecules or a plurality of polynucleotide molecules encoding the plurality of polypeptide molecules, wherein the sequence data comprises identities and positions of a plurality of amino acids for each molecule of the plurality of polypeptide molecules or a plurality of nucleotides for each molecule of the plurality of polynucleotide molecules;
- (b) receiving activity data of the plurality of polypeptide molecules;
- (c) fitting a base model to the received sequence data and the received activity data
- wherein
- the base model receives as one or more inputs one or more amino acids of a polypeptide molecule or one or more nucleotides of a polynucleotide molecule encoding the polypeptide molecule and provides as an output an activity of the polypeptide molecule,
- the base model includes either (i) a plurality of linear terms and no interaction term or (ii) a plurality of linear terms and one or more interaction terms,
- each linear term comprises a coefficient and an independent variable representing an amino acid or a nucleotide at a sequence position, and
- each interaction term comprises a coefficient and two or more independent variables representing two or more interacting amino acids at two or more sequence positions or nucleotides encoding the two or more interacting amino acids;
- (d) determining a predictive ability of the base model in predicting activity from the identities and the positions of the plurality of amino acids or the plurality of nucleotides, wherein the predictive ability is determined with a bias against including additional terms;
- (e) fitting at least one new model to the received sequence data and the received activity data, wherein the at least one new model is obtained by adding at least one new interaction term to the base model of (i) or (ii) or subtracting at least one new interaction term to or from the base model of (ii);
- (f) determining a predictive ability of the at least one new model in predicting activity from the identities and the positions of the plurality of amino acids or the plurality of nucleotides, wherein the predictive ability is determined with a bias against including additional terms;
- (g) selecting a model from among the base model and the at least one new model based on the predictive ability of the base model and the predictive ability of the at least one new model;
- and
- (h) determining one or more amino acid sequences or one or more nucleic acid sequences using the selected model.
11 more elements
A computer system, comprising:
- one or more processors;
- system memory;
- and
- one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computer system to implement a method for conducting directed evolution of biological molecules, the method comprising:
- (a) receiving sequence data of a plurality of polypeptide molecules or a plurality of polynucleotide molecules encoding the plurality of polypeptide molecules, wherein the sequence data comprises identities and positions of a plurality of amino acids for each molecule of the plurality of polypeptide molecules or a plurality of nucleotides for each molecule of the plurality of polynucleotide molecules;
- (b) receiving activity data of the plurality of polypeptide molecules;
- (c) fitting a base model to the received sequence data and the received activity data,
- wherein
- the base model receives as one or more inputs one or more amino acids of a polypeptide molecule or one or more nucleotides of a polynucleotide molecule encoding the polypeptide molecule and provides as an output an activity of the polypeptide molecule,
- the base model includes either (i) a plurality of linear terms and no interaction term or (ii) a plurality of linear terms and one or more interaction terms,
- each linear term comprises a coefficient and an independent variable representing an amino acid or a nucleotide at a sequence position, and
- each interaction term comprises a coefficient and two or more independent variables representing two or more interacting amino acids at two or more sequence positions or nucleotides encoding the two or more interacting amino acids;
- (d) determining a predictive ability of the base model in predicting activity from the identities and the positions of the plurality of amino acids or the plurality of nucleotides, wherein the predictive ability is determined with a bias against including additional terms;
- (e) fitting at least one new model to the received sequence data and the received activity data, wherein the at least one new model is obtained by adding at least one new interaction term to the base model of (i) or (ii) or subtracting at least one new interaction term from the base model of (ii);
- (f) determining a predictive ability of the at least one new model in predicting activity from the identities and the positions of the plurality of amino acids or the plurality of nucleotides, wherein the predictive ability is determined with a bias against including additional terms;
- (g) selecting a model from among the base model and the at least one new model based on the predictive ability of the base model and the predictive ability of the at least one new model;
- (g) selecting a model from among the base model and the at least one new model based on the predictive ability of the base model and the predictive ability of the at least one new model;
- and
- (h) determining one or more amino acid sequences or one or more nucleic acid sequences using the selected model;
- (i) synthesizing one or more amino acid molecules or one or more nucleic acid molecules based on the one or more amino acid sequences or one or more nucleic acid sequences;
- and
- (j) recombining or performing mutagenesis on the one or more amino acid molecules or one or more nucleic acid molecules to provide the one or more polypeptide or polynucleotide molecules.
19 more elements
Dependencies are inferred from the claim text.