Use of computationally derived protein structures of genetic polymorphisms in pharmacogenomics for drug design and clinical applications

A computer-based method for predicting clinical responses in subjects based on genetic polymorphisms, comprising:

• obtaining one or more amino acid sequences for a target protein that is the product of a gene exhibiting genetic polymorphisms;
• generating 3-D protein structural variant models from the sequences;
• building a relational database of protein structural variants derived based on genetic polymorphisms and observed clinical data associated with particular polymorphisms exhibited in the subjects, wherein the database comprises:
• 3-D molecular coordinates for the structural variant models;
• a molecular graphics interface for 3-D molecular structure visualization;
• computer functionality for protein sequence and structural analysis;
• database searching tools;
• and
• observed clinical data associated with the genetic polymorphisms, subject medical history and subject history associated with the genetic polymorphisms;
• obtaining a target protein structural variant based on the same gene associated with a polymorphism in a subject;
• generating a 3-D protein model based on the subject's gene sequence;
• screening/comparing the 3-D model derived from the subject to the structures contained in the database by:
• identifying structures in the database that are similar to the model derived from the subject;
• and
• predicting a clinical outcome for the subject based on the clinical data associated with the identified structures.

A computer-based method for designing therapeutic agents that are active against biological targets that have become drug resistant due to genetic mutations, comprising:

• obtaining a first 3-D protein structural variant model of a target protein against which a given drug has biological activity;
• generating a second 3-D protein structural variant model of the target in which genetic mutations have occurred and against which the same drug is no longer biologically active;
• comparing the structures of the first and second model to identify structural differences;
• and
• performing structure-based drug design calculations in order to identify new drugs or modifications to the existing drug to bring about biological activity against the second model.

A computer-based method for identifying compensatory mutations in a target protein, comprising:

• obtaining the amino acid sequence of a target protein containing multiple amino acid mutations that is expressed in a subject, wherein the structure of a form of the target protein that responds to a particular drug, including the active site, has been structurally characterized;
• generating a 3-D structural model of the mutated protein;
• comparing the structure of the mutated protein with the form of the protein that responds to the drug to identify structural differences and/or similarities arising from the mutations;
• comparing the biological activities of the drug against both the mutated protein and the form of the protein that responds to the drug to determine the effects of the mutations on drug response;
• and
• identifying the mutations in the protein that affect biological activity based on the comparisons.

A method for creating a 3-D structural polymorphism relational database, comprising:

• obtaining one or more amino acid sequences of a target protein that is the product of a gene exhibiting a genetic polymorphism, wherein sequences represent different genetic polymorphisms;
• generating 3-D protein structural variant models from the sequences;
• energetically refining the models;
• evaluating the quality of the models;
• optionally obtaining associated clinical properties or data;
• and
• inputting the model and any associated properties and/or data into a relational database.

A database, comprising:

• sequences of nucleotides encoding a protein or portions thereof, wherein proteins comprise polymorphic variants;
• and the portions encode a domain of the protein that comprises a site in the protein that binds to a drug candidate;
• and
• the coordinates of 3-dimensional (3-D) structures of the encoded proteins or portions thereof.

A method for predicting clinical responses in subjects based on a genetic polymorphism, comprising:

• comparing a three-dimensional (3-D) model of a structure of a protein from a biological sample from a subject to 3-D structures contained in a database;
• identifying a structure in the database that is similar to the model of a protein from the subject;
• and
• predicting a clinical outcome for the subject based on the clinical data associated with the identified structures.

A method for predicting resistance or susceptibility to a particular drug therapy, comprising:

• generating a 3-D structural model of a target protein from a subject;
• performing protein-drug binding analyses in silico;
• and
• predicting drug sensitivity or resistance based on the protein-drug binding analyses.