As far as I understand the influenza genome, it has 8 chunks of genes, roughly the equivalent of a chromosome, not 8 genes. But perhaps I misunderstood that? And each of those chunks has estimated (based on base pairs) 8 to 14 genes. So in total we are in the range of 100 +/- I had guessed. But that might be wrong :) It seems regarding viruses we did not do much genome mapping. .
You are correct that it has 8 "chunks" that are essentially the equivalent of a chromosome. How ever each chunk/chromosome only encodes a single gene. Three of those genes can express 2 different proteins, either through alternatively splicing or frameshifting resulting in a total of 11 possible protein sequences expressed from the entire influenza genome. 100 genes is big for viruses, usually those are large, complex viruses like the herpesviruses which have all kinds of special viral proteins that are designed to subvert the host immune system. Here is a good illustration of the influenza genome:
http://www.virology.ws/2009/05...
The most researched and very primitive tobacco mosaic virus. It produces roughly 160 different amino acids. OTOH, the hull around the RNA strand is constructed from a single repeating peptide. I would assume that that peptide is constructed from those amino acids, but that sounds unlikely. So: how many genes do you need to produce 160 different amino acids? I thought 160 genes, but perhaps a gene can code several amino acids in a row, without stop markers and without causing them to 'stick together'.
Amino acids are just the individual components that are linked together to form peptides/proteins, there are only 20 possible amino acids in eukaryotes. The Tobacco Mosaic virus capsid protein is indeed 160 amino acids in length, but there are still only 20 amino acids used to make that protein, some are used more than twice. Here is the actual amino acid sequence of the protein, each letter represents a single amino acid, so you can see that some are used more than once:
http://www.uniprot.org/uniprot...
Regarding modeling: depends what you want to model, chemical interactions, likely challenging. High level production and accumulation and assembly of proteins? Not so challenging.
Modeling protein structures is hard, look at the "Folding at Home" project, they've got petaflops of computational power cranking away on modeling a handful of structures. And that's just individual 3-D structures, to ask how changing a single amino acid in a protein would influence the structure and then how that new structure would interact with the 20,000+ other proteins is impossible right now. I wish it were, it would make my job a hell of lot easier.