Integration of sequence and structural homology in search for conservation principles and similarity examples in biology

Conservation in sequence and structure abounds in biology, and is a fundamental guiding principle as we search for core tenets of biology that structures the biological diversity we see in our ecosystems. From similarity in sequence and structure, conservation helps unify biology across different domains of life, and, in a way, reduces the complexity needed for supporting the diversity of life-forms we see in our environment. Indeed, conservation principles build modules such as glycolysis that could be translated into different organisms, where evolution tweaks the system in each species depending on prevailing environmental and nutritional conditions in their native habitats. Such tweaks could manifest as missing parts of the pathway or additional side branches that connect to the main glycolytic highway. But, how do we find these examples of biological conservation? The answer is usually sequence homology search, but, more recently, searching for structural homology has entered the fold. To find relatedness and similarity in biology, a sequence homology search is the first-pass tool, and is requisite in modern bioinformatic and computational biology workflows. But, sequence is only indirectly related to function, unlike the case where structure defines function. Hence, a structural homology search is also a must, given that similarity in structure portends similarity and relatedness in function, where, for example, discovery of a similar protein fold in two proteins suggest the same class of reactions with different substrates is catalyzed. But, both sequence and homology search must work together in an integrated manner to help discover the truly similar proteins in a vast biological search space. For example, sequence homology could identify enzymes that have similar sequence motifs that define binding pockets. On the other hand, a structural homology search would identify enzymes with similar folds defined by divergent sequence motifs. Using both approaches together would expand the types and classes of similar proteins and enzymes in the search space, and help us glean new insights of what similarity means in sequence and structure at the molecular level.