Local structural differences in homologous proteins: specificities in different SCOP classes

Pan-cancer structurome reveals overrepresentation of beta sandwiches and underrepresentation of alpha helical domains

The recent progress in the prediction of protein structures marked a historical milestone. AlphaFold predicted 200 million protein models with an accuracy comparable to experimental methods. Protein structures are widely used to understand evolution and to identify potential drug targets for the treatment of various diseases, including cancer. Thus, these recently predicted structures might convey previously unavailable information about cancer biology. Evolutionary classification of protein domains is challenging and different approaches exist. Recently our team presented a classification of domains from human protein models released by AlphaFold. Here we evaluated the pan-cancer structurome, domains from over and under expressed proteins in 21 cancer types, using the broadest levels of the ECOD classification: the architecture (A-groups) and possible homology (X-groups) levels. Our analysis reveals that AlphaFold has greatly increased the three-dimensional structural landscape for proteins that are differentially expressed in these 21 cancer types. We show that beta sandwich domains are significantly overrepresented and alpha helical domains are significantly underrepresented in the majority of cancer types. Our data suggest that the prevalence of the beta sandwiches is due to the high levels of immunoglobulins and immunoglobulin-like domains that arise during tumor development-related inflammation. On the other hand, proteins with exclusively alpha domains are important elements of homeostasis, apoptosis and transmembrane transport. Therefore cancer cells tend to reduce representation of these proteins to promote successful oncogeneses.

Structural and Functional Differences between Homologous Bacterial Ribonucleases

Small cationic guanyl-preferring ribonucleases (RNases) produced by the Bacillus species share a similar protein tertiary structure with a high degree of amino acid sequence conservation. However, they form dimers that differ in conformation and stability. Here, we have addressed the issues (1) whether the homologous RNases also have distinctions in catalytic activity towards different RNA substrates and interactions with the inhibitor protein barstar, and (2) whether these differences correlate with structural features of the proteins. Circular dichroism and dynamic light scattering assays revealed distinctions in the structures of homologous RNases. The activity levels of the RNases towards natural RNA substrates, as measured spectrometrically by acid-soluble hydrolysis products, were similar and decreased in the row high-polymeric RNA >>> transport RNA > double-stranded RNA. However, stopped flow kinetic studies on model RNA substrates containing the guanosine residue in a hairpin stem or a loop showed that the cleavage rates of these enzymes were different. Moreover, homologous RNases were inhibited by the barstar with diverse efficiency. Therefore, minor changes in structure elements of homologous proteins have a potential to significantly effect molecule stability and functional activities, such as catalysis or ligand binding.

Using the Evolutionary History of Proteins to Engineer Insertion-Deletion Mutants from Robust, Ancestral Templates Using Graphical Representation of Ancestral Sequence Predictions (GRASP)

Analyzing the natural evolution of proteins by ancestral sequence reconstruction (ASR) can provide valuable information about the changes in sequence and structure that drive the development of novel protein functions. However, ASR has also been used as a protein engineering tool, as it often generates thermostable proteins which can serve as robust and evolvable templates for enzyme engineering. Importantly, ASR has the potential to provide an insight into the history of insertions and deletions that have occurred in the evolution of a protein family. Indels are strongly associated with functional change during enzyme evolution and represent a largely unexplored source of genetic diversity for designing proteins with novel or improved properties. Current ASR methods differ in the way they handle indels; inclusion or exclusion of indels is often managed subjectively, based on assumptions the user makes about the likelihood of each recombination event, yet most currently available ASR tools provide limited, if any, opportunities for evaluating indel placement in a reconstructed sequence. Graphical Representation of Ancestral Sequence Predictions (GRASP) is an ASR tool that maps indel evolution throughout a reconstruction and enables the evaluation of indel variants. This chapter provides a general protocol for performing a reconstruction using GRASP and using the results to create indel variants. The method addresses protein template selection, sequence curation, alignment refinement, tree building, ancestor reconstruction, evaluation of indel variants and approaches to library development.

Molecular Characterization and Directed Evolution of a Metagenome-Derived l-Cysteine Sulfinate Decarboxylase

l-Cysteine sulfinate decarboxylase (CSD, EC 4.1.1.29), the rate-limiting enzyme in taurine synthesis pathway, catalyzes l-cysteine sulfinic acid to form hypotaurine. Identification of the novel CSD that could improve the biosynthetic efficiency of taurine is important. An unexplored decarboxylase gene named undec1A was identified in a previous work through sequence-based screening of uncultured soil microorganisms. Random mutagenesis through sequential error-prone polymerase chain reaction was used in Undec1A. A mutant Undec1A-1180, which was obtained from mutagenesis library, had 5.62-fold higher specific activity than Undec1A at 35 °C and pH=7.0. Molecular docking results indicated that amino acid residues Ala235, Val237, Asp239, Ile267, Ala268, and Lys298 in the Undec1A-1180 protein helped recognize and catalyze the substrate molecules of l-cysteine sulfinic acid. These results could serve as a basis for elucidating the characteristics of the Undec1A-1180. Directed evolution technology is a convenient way to improve the biotechnological applications of metagenome-derived genes.

Characterization of a metagenome-derived protease from contaminated agricultural soil microorganisms and its random mutagenesis

Proteases are typical key enzymes that hydrolyze proteins into amino acids and peptides. Numerous proteases have been studied, but the discovery of metagenome-derived proteases is still significant for both commercial applications and basic research. An unexplored protease gene sep1A was identified by function-based screening from a plasmid metagenomic library derived from uncultured contaminated agricultural soil microorganisms. The putative protease gene was subcloned into pET-32a (+) vector and overexpressed in E. coli BL21(DE3) pLysS, then the recombinant protein was purified to homogeneity. The detailed biochemical characterization of the Sep1A protein was performed, including its molecular characterization, specific activity, pH-activity profile, metal ion-activity profile, and enzyme kinetic assays. Furthermore, the protein engineering approach of random mutagenesis via error-prone PCR was applied on the original Sep1A protein. Biochemical characterization demonstrated that the purified recombinant Ep48 protein could hydrolyze casein. Compared with the original Sep1A protein, the best variant of Ep48 in the random mutagenesis library, with the Gln307Leu and Asp391Gly changes, exhibited 2.62-fold activity at the optimal reaction conditions of 50 °C and pH 9.0. These results are the first step toward a better understanding of the properties of Sep1A protein. Protein engineering with error-prone PCR paves the way toward the metagenome-derived genes for biotechnological applications.

Structural elucidation of estrus urinary lipocalin protein (EULP) and evaluating binding affinity with pheromones using molecular docking and fluorescence study

Transportation of pheromones bound with carrier proteins belonging to lipocalin superfamily is known to prolong chemo-signal communication between individuals belonging to the same species. Members of lipocalin family (MLF) proteins have three structurally conserved motifs for delivery of hydrophobic molecules to the specific recognizer. However, computational analyses are critically required to validate and emphasize the sequence and structural annotation of MLF. This study focused to elucidate the evolution, structural documentation, stability and binding efficiency of estrus urinary lipocalin protein (EULP) with endogenous pheromones adopting in-silico and fluorescence study. The results revealed that: (i) EULP perhaps originated from fatty acid binding protein (FABP) revealed in evolutionary analysis; (ii) Dynamic simulation study shows that EULP is highly stable at below 0.45 Å of root mean square deviation (RMSD); (iii) Docking evaluation shows that EULP has higher binding energy with farnesol and 2-iso-butyl-3-methoxypyrazine (IBMP) than 2-naphthol; and (iv) Competitive binding and quenching assay revealed that purified EULP has good binding interaction with farnesol. Both, In-silico and experimental studies showed that EULP is an efficient binding partner to pheromones. The present study provides impetus to create a point mutation for increasing longevity of EULP to develop pheromone trap for rodent pest management.

Nuclear Protein-Only Ribonuclease P2 Structure and Biochemical Characterization Provide Insight into the Conserved Properties of tRNA 5' End Processing Enzymes

Protein-only RNase Ps (PRORPs) are a recently discovered class of RNA processing enzymes that catalyze maturation of the 5' end of precursor tRNAs in Eukaryotes. PRORPs are found in the nucleus and/or organelles of most eukaryotic organisms. Arabidopsis thaliana is a representative organism that contains PRORP enzymes (PRORP1, PRORP2 and PRORP3) in both its nucleus and its organelles; PRORP2 and PRORP3 localize to the nucleus and PRORP1 localizes to the chloroplast and the mitochondria. Apart from their identification, almost nothing is known about the structure and function of PRORPs that act in the nucleus. Here, we use a combination of biochemical assays and X-ray crystallography to characterize A. thaliana PRORP2. We solved the crystal structure of PRORP2 (3.2Å) revealing an overall V-shaped protein and conserved metallonuclease active-site structure. Our biochemical studies indicate that PRORP2 requires Mg(2+) for catalysis and catalyzes the maturation of nuclear encoded substrates up to 10-fold faster than mitochondrial encoded precursor nad6 t-element under single-turnover conditions. We also demonstrate that PRORP2 preferentially binds precursor tRNAs containing short 5' leaders and 3' trailers; however, leader and trailer lengths do not significantly alter the observed rate constants of PRORP2 in single-turnover cleavage assays. Our data provide a biochemical and structural framework to begin understanding how nuclear localized PRORPs recognize and cleave their substrates.

Differential site accessibility mechanistically explains subcellular-specific N-glycosylation determinants

Glycoproteins perform extra- and intracellular functions in innate and adaptive immunity by lectin-based interactions to exposed glyco-determinants. Herein, we document and mechanistically explain the formation of subcellular-specific N-glycosylation determinants on glycoproteins trafficking through the shared biosynthetic machinery of human cells. LC-MS/MS-based quantitative glycomics showed that the secreted glycoproteins of eight human breast epithelial cells displaying diverse geno- and phenotypes consistently displayed more processed, primarily complex type, N-glycans than the high-mannose-rich microsomal glycoproteins. Detailed subcellular glycome profiling of proteins derived from three breast cell lines (MCF7/MDA468/MCF10A) demonstrated that secreted glycoproteins displayed significantly more α-sialylation and α1,6-fucosylation, but less α-mannosylation, than both the intermediately glycan-processed cell-surface glycoproteomes and the under-processed microsomal glycoproteomes. Subcellular proteomics and gene ontology revealed substantial presence of endoplasmic reticulum resident glycoproteins in the microsomes and confirmed significant enrichment of secreted and cell-surface glycoproteins in the respective subcellular fractions. The solvent accessibility of the glycosylation sites on maturely folded proteins of the 100 most abundant putative N-glycoproteins observed uniquely in the three subcellular glycoproteomes correlated with the glycan type processing thereby mechanistically explaining the formation of subcellular-specific N-glycosylation. In conclusion, human cells have developed mechanisms to simultaneously and reproducibly generate subcellular-specific N-glycosylation using a shared biosynthetic machinery. This aspect of protein-specific glycosylation is important for structural and functional glycobiology and discussed here in the context of the spatio-temporal interaction of glyco-determinants with lectins central to infection and immunity.

Identifying RNA-binding residues based on evolutionary conserved structural and energetic features

Increasing numbers of protein structures are solved each year, but many of these structures belong to proteins whose sequences are homologous to sequences in the Protein Data Bank. Nevertheless, the structures of homologous proteins belonging to the same family contain useful information because functionally important residues are expected to preserve physico-chemical, structural and energetic features. This information forms the basis of our method, which detects RNA-binding residues of a given RNA-binding protein as those residues that preserve physico-chemical, structural and energetic features in its homologs. Tests on 81 RNA-bound and 35 RNA-free protein structures showed that our method yields a higher fraction of true RNA-binding residues (higher precision) than two structure-based and two sequence-based machine-learning methods. Because the method requires no training data set and has no parameters, its precision does not degrade when applied to 'novel' protein sequences unlike methods that are parameterized for a given training data set. It was used to predict the 'unknown' RNA-binding residues in the C-terminal RNA-binding domain of human CPEB3. The two predicted residues, F430 and F474, were experimentally verified to bind RNA, in particular F430, whose mutation to alanine or asparagine nearly abolished RNA binding. The method has been implemented in a webserver called DR_bind1, which is freely available with no login requirement at http://drbind.limlab.ibms.sinica.edu.tw.