Inspired by previous work [Calabrese et al., 2009; Ng and Henikoff, 2001; Thomas et al., 2003], we have capitalized upon recent advances in the HMMER3 software suite [Eddy, 2009] to potentiate the computational prediction of the functional effects of AASs using HMMs. First, we present an unweighted/species-independent method in which homologous sequences are automatically collected and aligned using an iterative search procedure. The resulting MSA is then used to build an ab initio HMM where sequence conservation is then interrogated through the internal match states of the model. In conjunction, sequence conservation within manually curated HMMs representing the alignment of conserved protein domain families: SUPERFAMILY [Gough et al., 2001] and Pfam [Sonnhammer et al., 1997], is interrogated. This additional domain-based analysis is capable of capturing important structural and evolutionary constraints (via priors) that are potentially missed when using an automatically collected alignment of homologous sequences. Next, we introduce a weighted/species-specific method, which incorporates “pathogenicity weights”. These weights are derived from the relative frequencies of disease-associated and functionally neutral AASs mapping onto conserved protein domains. Using a model weighted for human
