Genes duplicate, mutate, recombine, fuse or fission to produce new genes, or when genes are formed from de novo, novel functions arise during evolution. Researchers have tried to quantify the causes of these molecular diversification processes to know how these genes increase molecular complexity over a period of time, for instance protein domain organization. In contrast to global sequence similarity, protein domain architectures can capture key structural and functional characteristics, making them better proxies for describing functional equivalence. In Prokaryotes and eukaryotes it has proven that, domain designs are retained over significant evolutionary distances. Protein domain architectures are now being utilized to categorize and distinguish evolutionarily related proteins and find homologs among species that are evolutionarily distant from one another. Additionally, structural information stored in domain structures has accelerated homology identification and sequence search methods. Tools for functional protein annotation have been developed to discover, protein domain content, domain order, domain recurrence, and domain position as all these contribute to the prediction of protein functional accuracy. In this review, an attempt is made to summarise facts and speculations regarding the use of protein domain architecture and modularity to identify possible therapeutic targets among cellular activities based on the understanding their linked biological processes.

Two long-standing challenges in theoretical population genetics and evolution are predicting the distribution of phenotype diversity generated by mutation and available for selection, and determining the interaction of mutation, selection and drift to characterize evolutionary equilibria and dynamics. More fundamental for enabling such predictions is the current inability to causally link genotype to phenotype. There are three major mechanistic mappings required for such a linking - genetic sequence to kinetic parameters of the molecular processes, kinetic parameters to biochemical system phenotypes, and biochemical phenotypes to organismal phenotypes. This article introduces a theoretical framework, the Phenotype Design Space (PDS) framework, for addressing these challenges by focusing on the mapping of kinetic parameters to biochemical system phenotypes. It provides a quantitative theory whose key features include (1) a mathematically rigorous definition of phenotype based on biochemical kinetics, (2) enumeration of the full phenotypic repertoire, and (3) functional characterization of each phenotype independent of its context-dependent selection or fitness contributions. This framework is built on Design Space methods that relate system phenotypes to genetically determined parameters and environmentally determined variables. It also has the potential to automate prediction of phenotype-specific mutation rate constants and equilibrium distributions of phenotype diversity in microbial populations undergoing steady-state exponential growth, which provides an ideal reference to which more realistic cases can be compared. Although the framework is quite general and flexible, the details will undoubtedly differ for different functions, organisms and contexts. Here a hypothetical case study involving a small molecular system, a primordial circadian clock, is used to introduce this framework and to illustrate its use in a particular case. The framework is built on fundamental biochemical kinetics. Thus, the foundation is based on linear algebra and reasonable physical assumptions, which provide numerous opportunities for experimental testing and further elaboration to deal with complex multicellular organisms that are currently beyond its scope. The discussion provides a comparison of results from the PDS framework with those from other approaches in theoretical population genetics.

The Clp1 family proteins, consisting of the Clp1 and Nol9/Grc3 groups, have polynucleotide kinase (PNK) activity at the 5' end of RNA strands and are important enzymes in the processing of some precursor RNAs. However, it remains unclear how this enzyme family diversified in the eukaryotes. We performed a large-scale molecular evolutionary analysis of the full-length genomes of 358 eukaryotic species to classify the diverse Clp1 family proteins. The average number of Clp1 family proteins in eukaryotes was 2.3 ± 1.0, and most representative species had both Clp1 and Nol9/Grc3 proteins, suggesting that the Clp1 and Nol9/Grc3 groups were already formed in the eukaryotic ancestor by gene duplication. We also detected an average of 4.1 ± 0.4 Clp1 family proteins in members of the protist phylum Euglenozoa. For example, in Trypanosoma brucei, there are three genes of the Clp1 group and one gene of the Nol9/Grc3 group. In the Clp1 group proteins encoded by these three genes, the C-terminal domains have been replaced by unique characteristics domains, so we designated these proteins Tb-Clp1-t1, Tb-Clp1-t2, and Tb-Clp1-t3. Experimental validation showed that only Tb-Clp1-t2 has PNK activity against RNA strands. As in this example, N-terminal and C-terminal domain replacement also contributed to the diversification of the Clp1 family proteins in other eukaryotic species. Our analysis also revealed that the Clp1 family proteins in humans and plants diversified through isoforms created by alternative splicing.

The ability to encode and convert heritable information into molecular function is a defining feature of life as we know it. The conversion of information into molecular function is performed by the translation process, in which triplets of nucleotides in a nucleic acid polymer (mRNA) encode specific amino acids in a protein polymer that folds into a three-dimensional structure. The folded protein then performs one or more molecular activities, often as one part of a complex and coordinated physiological network. Prebiotic systems, lacking the ability to explicitly translate information between genotype and phenotype, would have depended upon either chemosynthetic pathways to generate its components-constraining its complexity and evolvability- or on the ambivalence of RNA as both carrier of information and of catalytic functions-a possibility which is still supported by a very limited set of catalytic RNAs. Thus, the emergence of translation during early evolutionary history may have allowed life to unmoor from the setting of its origin. The origin of translation machinery also represents an entirely novel and distinct threshold of behavior for which there is no abiotic counterpart-it could be the only known example of computing that emerged naturally at the chemical level. Here we describe translation machinery's decoding system as the basis of cellular translation's information-processing capabilities, and the four operation types that find parallels in computer systems engineering that this biological machinery exhibits.

The Nucleo-Cytoplasmic Large DNA Viruses (NCLDVs) infect a wide range of eukaryotic species, including amoeba, algae, fish, amphibia, arthropods, birds, and mammals. This group of viruses has linear or circular double-stranded DNA genomes whose size spans approximately one order of magnitude, from 100 to 2500 kbp. The ultimate origin of this peculiar group of viruses remains an open issue. Some have argued that NCLDVs' origin may lie in a bacteriophage ancestor that increased its genome size by subsequent recruitment of eukaryotic and bacterial genes. Others have suggested that NCLDVs families originated from cells that underwent an irreversible process of genome reduction. However, the hypothesis that a number of NCLDVs sequences have been recruited from the host genomes has been largely ignored. In the present work, we have performed pangenomic analyses of each of the seven known NCLDVs families. We show that these families' core- and shell genes have cellular homologs, supporting possible escaping-gene events as part of its evolution. Furthermore, the detection of sequences that belong to two protein families (small chain ribonucleotide reductase and Erv1/Air) and to one superfamily [2OG-Fe(II) oxygenases] that are for distribution in all NCLDVs core and shell clusters encoding for oxygen-dependent enzymes suggests that the highly conserved core these viruses originated after the Proterozoic Great Oxidation Event that transformed the terrestrial atmosphere 2.4-2.3 Ga ago.