Cluster analysis or principal component analysis?

Hi, I am trying to identify the correct method to analyze my data. I have determined for a related protein panel if a certain property is present in the protein, resulting in an array like this:

          Site 1 Site 2
protein A  1      0
protein B  0      1
....

with 1 = yes and 0 = no.

Further, I have determined the affinity of my proteins to another protein X.

I am trying to find out which method would be approvable to determine if certain patters (Combinations of sites present in the protein panel) exist, which result in good or bad binding to protein X. Do you have any tips which method might be suitable? I think hierarchical clustering or principal component analysis might help but I am stucked right now because the properties of my protein panel are only described in 0 and 1 and I am not sure how I should adopt this properties to the examples I find on the internet: http://www.mathworks.com/help/bioinfo/examples/gene-expression-profile-analysis.html#zmw57dd0e9643

So if you have any tipps for me if I am on the right track or even how I can adapt my data for this methods, that would be great!