Sequence covariance networks, methods and uses therefor
Methods of identifying targets for designing a therapeutic agent are disclosed. These methods comprise: determining an amino acid sequence of one or more polypeptides of each isolate of a plurality of isolates of a biological system; identifying covariance pairs of amino acid residues; establishing a network comprising the covariance pairs; and identifying one or more hub residue positions, wherein a hub residue position comprises a target for designing a therapeutic agent if the hub residue position has a rank order in the 40 th percentile or greater. In other aspects, methods are disclosed for selecting a therapy for an infectious disorder. In various configurations, these methods comprise: determining amino acids occupying a plurality of diagnostic amino acid residue positions comprised by one or more polypeptides encoded by an infectious agent infecting a subject; and assigning the infectious agent infecting the subject to one covariance network selected from a plurality of covariance networks, wherein each network comprises a unique rank order of hubs with respect to the other networks, and whereby the therapy is selected on the basis of the covariance network assignment.
1. A method of establishing a plurality of sequence covariance networks useful to determine whether to treat a patient with an antiviral therapy, comprising:
(i) obtaining a plurality of hepatitis C isolates, grouped by response to an antiviral therapy;
(ii) determining the amino acid sequence of a plurality of hepatitis C polypeptides from each isolate;
(iii) identifying covariance pairs of residues in the amino acid sequences of each group; and
(iv) identifying a plurality of sequence covariance networks among the covariance pairs in each group, thereby establishing a plurality of sequence covariance networks in which each network comprises a unique rank order of hubs;
(v) using the plurality of sequence covariance networks to determine whether to treat a specific hepatitis C-infected patient with the antiviral therapy.
2. A method in accordance with claim 1 , wherein the plurality of sequence covariance networks consists of a first sequence covariance network and a second sequence covariance network.
3. A method in accordance with claim 1 , further comprising identifying one or more hub residue positions.
4. A method in accordance with claim 3 , wherein the one or more hub residue positions are of a rank order in the 40 th percentile or greater.
5. A method in accordance with claim 1 , wherein the Hepatitis C virus is selected from the group consisting of a Hepatitis C virus subtype 1a and a Hepatitis C virus subtype 1b.
6. A method in accordance with claim 1 , wherein the therapy is selected from the group consisting of an interferon-based therapy, a guanosine analog-based therapy, and a combination thereof.
7. A method in accordance with claim 6 , wherein the antiviral therapy is treatment with ribavirin and pegylated interferon-α.
8. A method in accordance with claim 1 , wherein the identifying covariance pairs of amino acid residues in each group comprises:
(i) generating a sequence alignment for the sequences in each group; and
(ii) calculating the observed minus expected square (OMES) for each amino acid pair.