Methods of generating broadly protective vaccine compositions comprising hemagglutinin

1. A method for producing a recombinant influenza hemagglutinin (HA) polypeptide comprising consensus amino acids, wherein the method comprises:

a. selecting more than one influenza HA polypeptide sequence and aligning the sequences;

b. calculating pairwise similarity/dissimilarity matrices;

c. identifying and creating clusters of similar sequences from the pairwise similarity/dissimilarity matrices;

d. within each cluster, determining whether there is a consensus amino acid for each position in the sequence alignment using a pairwise alignment method, wherein if the frequency of the amino acid at a given position is 50% or greater, that amino acid is designated a consensus amino acid, and if the frequency of the amino acid at a given position is less than 50%, that amino acid is designated as a variable amino acid;

e. generating a first sequence comprising consensus amino acids and variable amino acids for each cluster;

f. within the first sequence generated in step (e), determining a consensus amino acid for each variable amino acid position, by:

i. generating a set of test sequences based on the first sequence, wherein test amino acids are placed at the variable amino acid positions;

ii. performing molecular modeling for each of the test sequences;

iii. determining a consensus amino acid for each variable amino acid position by selecting amino acid(s) that result in a polypeptide having a negative total energy value;

g. producing the recombinant influenza HA polypeptide comprising the consensus amino acids; and

h. isolating the produced recombinant influenza HA polypeptide.

2. The method of claim 1 , wherein aligning the sequences comprises using MAFFT, MUSCLE, CLUSTAL OMEGA, FASTA, a combination thereof, or any other multiple sequence alignment software packages.

3. The method of claim 1 , wherein calculating the pairwise similarity/dissimilarity matrices comprises using BLOSUM, PAM, IDENTITY substitution matrices, or a combination thereof.

4. The method of claim 1 , wherein identifying and creating clusters of similar sequences from the pairwise similarity/dissimilarity matrices comprise using K-means clustering, minimax clustering, principle component analysis (PCA), multidimensional scaling (MDS), or a combination thereof.

5. The method of claim 1 , wherein molecular modeling comprises comparing to a crystal structure of an influenza HA polypeptide or protein.

6. The method of claim 1 , wherein molecular modeling comprises use of Rosetta or any other molecular modeling software.

7. The method of claim 1 , wherein the test amino acids comprise any natural or non-natural amino acid found in proteins.

8. The method of claim 1 , wherein further comprising after step (e) if a plurality of clusters is analyzed, comparing the first sequence generated in step (e) of a cluster with a first sequence generated in another cluster or multiple clusters by:

i. aligning the sequences generated in step (e) for each cluster;

ii. determining whether there is a consensus amino acid for each position in the sequence alignment using a pairwise alignment method, wherein if the frequency of the amino acid at a given position is 50% or greater, that amino acid is designated a consensus amino acid, and if the frequency of the amino acid at a given position is less than 50%, that amino acid is designated as a variable amino acid; and

iii. generating a second sequence comprising consensus amino acids and variable amino acids, wherein the consensus amino acid is determined in step (f) within said second sequence generated.

9. The method of claim 8 , wherein in step (f)(i) the set of test sequence is generated based on the second sequence.