Align the HIV-1 Gag protein with the Gag protein of Visna virus
Both are lentiviruses and env is a fast evolving gene. What you are looking at here is the location of indels and this will vary between alignment algorithms.
There will always be an element of error in attempting to align over this genetic distance. It depends what you end goal is, if it is to maximise homology than okay, however optical enhancement of alignments are common if your downstream analysis is phylogenetics. If it is protein structure homology style modelling, where you have the protein structure of HIV env experimentally determined mulitple times you want to use it to help estimate that of the cat lentivirus then optimising a scoring metric is okay.
What you have to understand is there is no 'right' method, in phylogenetics this doesn't matter as much because indels are excluded in the subsequent calculation, so it is less sensative to indel positioning errors and optical enhancement is used. You can also simply exclude regions that appear 'garbled'. For protein homology modeling this is a big problem, because the indels will make drastic changes to the structure prediction. So the only approach here in my opinion is to produce a separate structural prediction for every variation in indel alignment you have obtained. In the latter context getting the alignment right is everything and I suspect thats the output here, because its a classic surface antigen to understand, which will readily crystalise.