Distinct Protein Sequences Research Articles

Accurate prediction of immunoglobulin proteins using machine learning model

IntroductionIn recent years, researchers have become increasingly interested in immunoglobulins. The antibodies, also known as immunoglobulins, are serum proteins that bind to specific antigens produced by B cells. The complicated nature of the proteins has been emphasized for over 100 years of research on the structure and function of immunoglobulin. A major B-cell protein, which is utilized by the immune system to identify and neutralize foreign objects such as bacteria and viruses, is the Antibody (Ab), also known as immunoglobulin (Ig). MethodsThis research focuses on the molecular mechanisms that allow these numerous and diverse roles. Therefore, it is very important to improve the accuracy of immunoglobulin classification by applying effective methods for disease research. We use the immunoglobulin features which reduced feature dimension were selected to extract immunoglobulin features, based on the BLOSUM vector score matrix. We've developed an ensemble learning method called Extreme Gradient Boosting (XGBoost). ResultsWe proposed learning method called Extreme Gradient Boosting (XGBoost) to predict immunoglobulins with 0.9727% accuracy with quintuple cross-validation of data used. In addition, the best method for identifying mixed 2D key features was used to BLOSUM62 to distinguish immunoglobulins with an ROC AUC predicted score of 0.9700%. The methods used in this paper are very accurate in predicting immunoglobulin levels and finding the key features. ConclusionsThe aim of this study was to calculate appropriate concentrations of immunoglobulin and to identify important traits. In this investigation, the BLOSUM62 matrix was employed, which is a frequently utilized device for calculating the alignment of two distinct protein sequences. The value of the BLOSUM62 Matrix is determined through a large-scale analysis of observed polypeptide alignments. The best feature set created by BLOSUM62 matrix was found to reliably predict 0.9727% accuracy score of immunoglobulins using the learning method called Extreme Gradient Boosting (XGBoost) classification model.

A mechanistic view of enzyme evolution.

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Alternative Transcription at Venom Genes and Its Role as a Complementary Mechanism for the Generation of Venom Complexity in the Common House Spider.

The complex composition of venom, a proteinaceous secretion used by diverse animal groups for predation or defense, is typically viewed as being driven by gene duplication in conjunction with positive selection, leading to large families of diversified toxins with selective venom gland expression. Yet, the production of alternative transcripts at venom genes is often overlooked as another potentially important process that could contribute proteins to venom, and requires comprehensive datasets integrating genome and transcriptome sequences together with proteomic characterization of venom to be fully documented. In the common house spider, Parasteatoda tepidariorum, we used RNA sequencing of four tissue types in conjunction with the sequenced genome to provide a comprehensive transcriptome annotation. We also used mass spectrometry to identify a minimum of 99 distinct proteins in P tepidariorum venom, including at least 33 latrotoxins, pore-forming neurotoxins shared with the confamilial black widow. We found that venom proteins are much more likely to come from multiple transcript genes, whose transcripts produced distinct protein sequences. The presence of multiple distinct proteins in venom from transcripts at individual genes was confirmed for eight loci by mass spectrometry, and is possible at 21 others. Alternative transcripts from the same gene, whether encoding or not encoding a protein found in venom, showed a range of expression patterns, but were not necessarily restricted to the venom gland. However, approximately half of venom protein encoding transcripts were found among the 1,318 transcripts with strongly venom gland biased expression. Our findings revealed an important role for alternative transcription in generating venom protein complexity and expanded the traditional model of venom evolution.

The SUPERFAMILY 2.0 database: a significant proteome update and a new webserver.

Here, we present a major update to the SUPERFAMILY database and the webserver. We describe the addition of new SUPERFAMILY 2.0 profile HMM library containing a total of 27 623 HMMs. The database now includes Superfamily domain annotations for millions of protein sequences taken from the Universal Protein Recourse Knowledgebase (UniProtKB) and the National Center for Biotechnology Information (NCBI). This addition constitutes about 51 and 45 million distinct protein sequences obtained from UniProtKB and NCBI respectively. Currently, the database contains annotations for 63 244 and 102 151 complete genomes taken from UniProtKB and NCBI respectively. The current sequence collection and genome update is the biggest so far in the history of SUPERFAMILY updates. In order to the deal with the massive wealth of information, here we introduce a new SUPERFAMILY 2.0 webserver (http://supfam.org). Currently, the webserver mainly focuses on the search, retrieval and display of Superfamily annotation for the entire sequence and genome collection in the database.

The use of stable isotope-labeled glycerol and oleic acid to differentiate the hepatic functions of DGAT1 and -2

Diacylglycerol acyltransferase (DGAT) catalyzes the final step in triglyceride (TG) synthesis. There are two isoforms, DGAT1 and DGAT2, with distinct protein sequences and potentially different physiological functions. To date, the ability to determine clear functional differences between DGAT1 and DGAT2, especially with respect to hepatic TG synthesis, has been elusive. To dissect the roles of these two key enzymes, we pretreated HepG2 hepatoma cells with (13)C(3)-D(5)-glycerol or (13)C(18)-oleic acid, and profiled the major isotope-labeled TG species by liquid chromatography tandem mass spectrometry. Selective DGAT1 and DGAT2 inhibitors demonstrated that (13)C(3)-D(5)-glycerol-incorporated TG synthesis was mediated by DGAT2, not DGAT1. Conversely, (13)C(18)-oleoyl-incorporated TG synthesis was predominantly mediated by DGAT1. To trace hepatic TG synthesis and VLDL triglyceride (VLDL-TG) secretion in vivo, we administered D(5)-glycerol to mice and measured plasma levels of D(5)-glycerol-incorporated TG. Treatment with an antisense oligonucleotide (ASO) to DGAT2 led to a significant reduction in D(5)-glycerol incorporation into VLDL-TG. In contrast, the DGAT2 ASO had no effect on the incorporation of exogenously administered (13)C(18)-oleic acid into VLDL-TG. Thus, our results indicate that DGAT1 and DGAT2 mediate distinct hepatic functions: DGAT2 is primarily responsible for incorporating endogenously synthesized FAs into TG, whereas DGAT1 plays a greater role in esterifying exogenous FAs to glycerol.

Grounding annotations in published literature with an emphasis on the functional roles used in metabolic models

Accurate genome annotations in databases are a critical resource available to the scientific community for analysis and research. Inaccurate and inconsistent annotations exist as a result of errors generated from mass automated annotation, and currently act as a barrier to the application of bioinformatics. The purpose of this effort was to improve the SEED by improving the connection of functional roles to literature references. Direct literature references (DLits), found through searches of PubMed and other online databases such as SwissProt, were attached to protein sequences within the PubSEED to provide literature support for the roughly 2,500 distinct functional roles used to construct metabolic models within the Model SEED. Only DLits in which a researcher asserted the function of a protein were attached to sequences. Starting from a list of 1,072 functional roles that did not previously have DLit support, we were able to connect sequences to literature for 655 functional roles, at least 484 of which were in the original list of unsupported roles. When added to the existing set of sequences having DLits, the resulting set of DLit-sequence pairs (the foundation set) now connects approximately 4,300 DLits to approximately 5,600 distinct protein sequences obtained from approximately 16,000 genes (some of these genes have identical protein sequences). From the foundation set, we construct projection sets such that each set contains one member of the foundation set and projections of its functional role onto similar genes. The projection sets revealed 120 inconsistent annotations within the SEED. Two types of inconsistencies were corrected through manual annotation in the PubSEED: instances in which two identical protein sequences had been annotated with different functions, and instances when projected functions contradicted previous annotations. 26,785 changes to gene function assignment, 219 of which were to previously uncharacterized proteins, resulted in a more consistent and accurate set of input data from which to construct revised metabolic models within the Model SEED.Electronic supplementary materialThe online version of this article (doi:10.1007/s13205-011-0039-z) contains supplementary material, which is available to authorized users.

Characterisation of low abundance wool proteins through novel differential extraction techniques

Fibres from human hair and wool are characterised by two main types of proteins: intermediate filament proteins (IFPs) and keratin associated proteins (KAPs). The IFPs, comprising over 50% of the fibre, tend to dominate 2-D electrophoretic maps, hindering identification of the less-abundant KAPs. This has been compounded in wool fibres by the relatively limited amount of sequence information available, with approximately 35 distinct protein sequences from ten KAP families being available, in contrast to human hair, where the sequences from well over 80 proteins from 26 KAP families are known. Additional complications include the high degree of homology within these families, ranging from 70 to 95%, and the dominance of cysteine residues in a number of KAP families with their high propensity to form cross-links. The lack of sequence information for wool KAPs has been partly overcome through the recent acquisition of new sequences. Fractionation of the proteins on the basis of their solubility with pH, urea and DTT concentration has resulted in protein extracts in which the IFP concentration has been considerably reduced. These improvements have enabled the identification of low-abundance proteins in 2-D electrophoretic maps and represent a significant advance in our knowledge of the wool proteome.

Phylogenetic analysis of mRNA polyadenylation sites reveals a role of transposable elements in evolution of the 3′-end of genes

mRNA polyadenylation is an essential step for the maturation of almost all eukaryotic mRNAs, and is tightly coupled with termination of transcription in defining the 3′-end of genes. Large numbers of human and mouse genes harbor alternative polyadenylation sites [poly(A) sites] that lead to mRNA variants containing different 3′-untranslated regions (UTRs) and/or encoding distinct protein sequences. Here, we examined the conservation and divergence of different types of alternative poly(A) sites across human, mouse, rat and chicken. We found that the 3′-most poly(A) sites tend to be more conserved than upstream ones, whereas poly(A) sites located upstream of the 3′-most exon, also termed intronic poly(A) sites, tend to be much less conserved. Genes with longer evolutionary history are more likely to have alternative polyadenylation, suggesting gain of poly(A) sites through evolution. We also found that nonconserved poly(A) sites are associated with transposable elements (TEs) to a much greater extent than conserved ones, albeit less frequently utilized. Different classes of TEs have different characteristics in their association with poly(A) sites via exaptation of TE sequences into polyadenylation elements. Our results establish a conservation pattern for alternative poly(A) sites in several vertebrate species, and indicate that the 3′-end of genes can be dynamically modified by TEs through evolution.

MCEF is localized to the nucleus by protein sequences encoded within three distinct exons, where it represses HIV-1 Tat-transactivation of LTR-directed transcription

Translocations between the human Mixed Lineage Leukemia (MLL) and AF4 Family (AFF) member genes, are implicated in leukemia. Mutations to AFFs can disrupt lymphopoesis, CNS development and spermatogenesis. However, despite the growing list of pathologies linked to AFF members, their evolutionary relationship and the structure/function of individual members, remain to be elucidated. Here, we first report that database mining and phylogenetic analysis with AFF proteins from multiple species, revealed two monophyletic sister clades, suggesting a common Bilateria ancestor. We then examined the structure/function of the most recently discovered AFF member, MCEF (also known as AF5q31 or AFF4). In silico, the human MCEF gene was found to have 21 exons, and code for a protein with seven nuclear localization sequences (NLS). In HeLa cells, an MCEF-EGFP fusion protein, localized exclusively to the nucleus. Consequently, we made twenty constructs, expressing MCEF deletion mutants fused to EGFP and/or DsRed fluorescent proteins. Three distinct protein sequences, encoded by three separate MCEF exons, were found to mediate nuclear localization, only two of which were predicted in silico. Importantly, we also found that ectopic expression of MCEF, repressed HIV-1 LTR-directed RNA Polymerase II transcription, at the level of Tat-transactivation. We suggest that portions of MCEF could be exploited for chimeric transcription factor repression (CTFR) of HIV-1.

Distinct hox protein sequences determine specificity in different tissues.

Hox genes encode evolutionarily conserved transcription factors that control the morphological diversification along the anteroposterior (A/P) body axis. Expressed in precise locations in the ectoderm, mesoderm, and endoderm, Hox proteins have distinct regulatory activities in different tissues. How Hox proteins achieve tissue-specific functions and why cells lying at equivalent A/P positions but in different germ layers have distinctive responses to the same Hox protein remains to be determined. Here, we examine this question by identifying parts of Hox proteins necessary for Hox function in different tissues. Available genetic markers allow the regulatory effects of two Hox proteins, Abdominal-A (AbdA) and Ultrabithorax (Ubx), to be distinguished in the Drosophila embryonic epidermis and visceral mesoderm (VM). Chimeric Ubx/AbdA proteins were tested in both tissues and used to identify protein sequences that endow AbdA with a different target gene specificity from Ubx. We found that distinct protein sequences define AbdA, as opposed to Ubx, function in the epidermis vs. the VM. These sequences lie mostly outside the homeodomain (HD), emphasizing the importance of non-HD residues for specific Hox activities. Hox tissue specificity is therefore achieved by sensing distinct Hox protein structures in different tissues.

Genetic characterization of the mRNAs encoding alpha-bungarotoxin: isoforms and RNA editing in Bungarus multicinctus gland cells.

The mRNA encoding alpha-bungarotoxin (alpha-Butx) was prepared from the venom glands of Bungarus multicinctus by Cap-finder cDNA synthesis. The sequences of the 3'- and 5'-flanking regions including a signal peptide of alpha-Butx were almost identical with those of Elapidae and Hydrophiidae toxins, suggesting that they may have the same origin. Sixteen polymorphic mRNA sequences of alpha-Butx were detected from B.multicinctus gland cells. Analysis of the genomic DNA of alpha-Butx indicated that the polymorphic mRNA originated from one DNA sequence. Most of the mutations in alpha-Butx mRNA were silent and the hot-spot variations occurred at 78, 107, 129, 198 and 201 nt in alpha-Butx mRNA. Ten distinct protein sequences of alpha-Butx could be deduced from the polymorphic mRNA and one of the isoforms has already been isolated. Since alpha-Butx DNA is a single copy in the genome, the RNA polymorphism might result from post-transcriptional editing. These results indicate that the authentic alpha-Butx is in fact derived from edited mRNAs. RNA editing may contribute a common mechanism toward the diversity of alpha-neurotoxins in snake glands.