COVARIABILITY OF V3 LOOP AMINO-ACIDS

We reanalyzed for covariability a set of 308 human immunodeficiency vi rus type 1 (HIV-1) V3 loop amino acid sequences from the B envelope se quence subtype previously analyzed by Korber et al.,(1) as well as a n ew set of 440 sequences that also included substantial numbers of sequ ences from subtypes A, D, and E. We used the measure employed by Korbe r et al., essentially the likelihood ratio statistic for independence, plus two additional measures as well as clade information to examine the new set and both data sets simultaneously. We set forth the follow ing conclusions and observations. The eight most highly connected site s identified through these statistical approaches included all of the six residues previously shown to have determining roles in structure, immunologic recognition, virus phenotype, and host range; each of the seven pairs of covariant sites found by Korber were signaled by our ad ditional two measures in the set of 308 sequences, although 2 or 3 dro pped out of the examination of the set of 440 when the requirement of stringent significance was applied for some or all of the three tests, respectively; using the same criteria, a total of 20 (including 5 Kor ber et al. pairs) or a total of 6 (including 4 Korber et al. pairs) we re found when the set of 440 was added. Several limitations to statist ical analysis of this type of HIV sequence data were also noted. For e xample, the data sets were, by historical necessity, collected haphaza rdly. For example, it was not possible to separate substantially sized groups out according to time of or since infection, disease status, a ntiviral treatment, geography, etc. There was also an enormous ''wealt h of significance'' within the data. For example, for one measure the 440 data set showed 233 of the 465 pairs of sites with a likelihood ra tio statistic of <0.001. Last, most sites had consensus amino acids in 80% or more of the sequences; hence, there was an absence of data on many combinations of amino acids. Given the observed linkage between s ites shown to be covariable and those known to have critical biologica l function, the statistical approaches we and Korber et al. have outli ned may find use in predicting critical structural features of HIV pro teins as targets for therapeutic intervention.