How does life adapt to the diverse environmental conditions found on earth? In the ongoing mission to answer this question, genome sequencing efforts identify the genes and proteins that provide the mechanism for growth, reproduction and adaptation. In this study, we took advantage of this exceptional opportunity to investigate whether sequences and structures from different organisms exhibited features that were species-specific. We analyzed the amino acid composition of sequences and structures of up to 150 completely sequenced genomes and explored the effectiveness of predictive methods that take advantage of amino acid composition bias. As a first case, we demonstrate a fast and simple method to predict domain linkers from sequence composition alone. Since the number of solved protein structures for any complete genome is rather nominal, we built a database of conservative, domain-based homology models called the species-specific fold database. Our analysis indicates that species-specific sequence and structure optimizations are significantly attributable to lifestyle and environment. Predictive scoring functions based on genome composition biases are shown to be effective in the identification of the taxonomic origin from sequence composition alone. Our predictive contact potentials derived from residue contacts in the structure models captures species-specific contact preferences that may be useful in evaluating structure optimizations. Finally, we demonstrate the ability of novel, asymmetric, species-specific substitution matrices in the alignment of compositionally biased sequences. Taken together, this work presents an original exploration into the adaptation of organisms from diverse environments using both sequence and structure information.