The language of the protein universe

Abstract

Proteins, the main cell machinery which play a major role in nearly every cellular process, have always been a central focus in biology. We live in the post-genomic era, and inferring information from massive data sets is a steadily growing universal challenge. The increasing availability of fully sequenced genomes can be regarded as the 'Rosetta Stone' of the protein universe, allowing the understanding of genomes and their evolution, just as the original Rosetta Stone allowed Champollion to decipher the ancient Egyptian hieroglyphics. In this review, we consider aspects of the protein domain architectures repertoire that are closely related to those of human languages and aim to provide some insights about the language of proteins.

Figure 1. Analogy between human and proteins languages

In this comparison, the vocabulary (domains) of proteins is built from an alphabet of amino acids. The syntax principles enable domain association to form multi-domain architectures, a process governed by hierarchical rules (grammar), that determine the structure and hence the biological function (semantics) of proteins. In several languages, for example in English, a number of different classes of words exist (nouns, adjectives ,verbs, adverbs, pronouns, conjunctions). Each class has its task in the language, i.e. nouns name words, adjectives describe nouns, verbs are action words, conjunction connect words. Analogously, one can also distinguish different classes of domains with different tasks (motors, binding proteins, enzymes, signaling proteins, structural proteins, targeting proteins).

Figure 2. Sequence profile databases can be sequence-based (blue circles) or structure-based (orange circles)

Sequence-based profiles are derived by mainly two methods: HMMs (Hidden Markov Models) or PSSMs. (Position Sensitive Sequence Matrices). Structure-based profiles in Gene3D and superfamily are generated from HMMs built from actual structures coming from CATH and SCOP, respectively. Two main integrative resources, CDART and InterPro, are shown (green circles) with the databases they include.

Figure 3. Mechanisms of Domain Architecture Change

New domain architectures can be created by (A) insertion or loss of existing domains (duplication), (B) insertion or loss of novel domains or by (C) substitution of one domain for another (exchange), which is almost always a two-step process comprising loss / fission and fusion. Domain insertion and loss are a consequence of gene fusion and fission respectively. Domain insertions or losses can be (D) internal (between two domains, also called domain shuffling) or may occur either at the N or C terminus (A) & (B).