Evaluation of Protein Dihedral Angle Prediction Methods

Tertiary structure prediction of a protein from its amino acid sequence is one of the major challenges in the field of bioinformatics. Hierarchical approach is one of the persuasive techniques used for predicting protein tertiary structure, especially in the absence of homologous protein structures. In hierarchical approach, intermediate states are predicted like secondary structure, dihedral angles, C^α-C^α distance bounds, etc. These intermediate states are used to restraint the protein backbone and assist its correct folding. In the recent years, several methods have been developed for predicting dihedral angles of a protein, but it is difficult to conclude which method is better than others. In this study, we benchmarked the performance of dihedral prediction methods ANGLOR and SPINE X on various datasets, including independent datasets. TANGLE dihedral prediction method was not benchmarked (due to unavailability of its standalone) and was compared with SPINE X and ANGLOR on only ANGLOR dataset on which TANGLE has reported its results. It was observed that SPINE X performed better than ANGLOR and TANGLE, especially in case of prediction of dihedral angles of glycine and proline residues. The analysis suggested that angle shifting was the foremost reason of better performance of SPINE X. We further evaluated the performance of the methods on independent ccPDB30 dataset and observed that SPINE X performed better than ANGLOR.     

The SV40 late protein VP4 is a viroporin that forms pores to disrupt membranes for viral release

Nonenveloped viruses are generally released by the timely lysis of the host cell by a poorly understood process. For the nonenveloped virus SV40, virions assemble in the nucleus and then must be released from the host cell without being encapsulated by cellular membranes. This process appears to involve the well-controlled insertion of viral proteins into host cellular membranes rendering them permeable to large molecules. VP4 is a newly identified SV40 gene product that is expressed at late times during the viral life cycle that corresponds to the time of cell lysis. To investigate the role of this late expressed protein in viral release, water-soluble VP4 was expressed and purified as a GST fusion protein from bacteria. Purified VP4 was found to efficiently bind biological membranes and support their disruption. VP4 perforated membranes by directly interacting with the membrane bilayer as demonstrated by flotation assays and the release of fluorescent markers encapsulated into large unilamellar vesicles or liposomes. The central hydrophobic domain of VP4 was essential for membrane binding and disruption. VP4 displayed a preference for membranes comprised of lipids that replicated the composition of the plasma membranes over that of nuclear membranes. Phosphatidylethanolamine, a lipid found at high levels in bacterial membranes, was inhibitory against the membrane perforation activity of VP4. The disruption of membranes by VP4 involved the formation of pores of ～3 nm inner diameter in mammalian cells including permissive SV40 host cells. Altogether, these results support a central role of VP4 acting as a viroporin in the perforation of cellular membranes to trigger SV40 viral release.     

Common ancestry of iron oxide- and iron-sulfide-based biomineralization in magnetotactic bacteria

Magnetosomes are prokaryotic organelles produced by magnetotactic bacteria that consist of nanometer-sized magnetite (Fe₃O₄) or/and greigite (Fe₃S₄) magnetic crystals enveloped by a lipid bilayer membrane. In magnetite-producing magnetotactic bacteria, proteins present in the magnetosome membrane modulate biomineralization of the magnetite crystal. In these microorganisms, genes that encode for magnetosome membrane proteins as well as genes involved in the construction of the magnetite magnetosome chain, the mam and mms genes, are organized within a genomic island. However, partially because there are presently no greigite-producing magnetotactic bacteria in pure culture, little is known regarding the greigite biomineralization process in these organisms including whether similar genes are involved in the process. Here using culture-independent techniques, we now show that mam genes involved in the production of magnetite magnetosomes are also present in greigite-producing magnetotactic bacteria. This finding suggest that the biomineralization of magnetite and greigite did not have evolve independently (that is, magnetotaxis is polyphyletic) as once suggested. Instead, results presented here are consistent with a model in which the ability to biomineralize magnetosomes and the possession of the mam genes was acquired by bacteria from a common ancestor, that is, the magnetotactic trait is monophyletic.     

Designing of highly effective complementary and mismatch siRNAs for silencing a gene

In past, numerous methods have been developed for predicting efficacy of short interfering RNA (siRNA). However these methods have been developed for predicting efficacy of fully complementary siRNA against a gene. Best of author's knowledge no method has been developed for predicting efficacy of mismatch siRNA against a gene. In this study, a systematic attempt has been made to identify highly effective complementary as well as mismatch siRNAs for silencing a gene.Support vector machine (SVM) based models have been developed for predicting efficacy of siRNAs using composition, binary and hybrid pattern siRNAs. We achieved maximum correlation 0.67 between predicted and actual efficacy of siRNAs using hybrid model. All models were trained and tested on a dataset of 2182 siRNAs and performance was evaluated using five-fold cross validation techniques. The performance of our method desiRm is comparable to other well-known methods. In this study, first time attempt has been made to design mutant siRNAs (mismatch siRNAs). In this approach we mutated a given siRNA on all possible sites/positions with all possible nucleotides. Efficacy of each mutated siRNA is predicted using our method desiRm. It is well known from literature that mismatches between siRNA and target affects the silencing efficacy. Thus we have incorporated the rules derived from base mismatches experimental data to find out over all efficacy of mutated or mismatch siRNAs. Finally we developed a webserver, desiRm (http://www.imtech.res.in/raghava/desirm/) for designing highly effective siRNA for silencing a gene. This tool will be helpful to design siRNA to degrade disease isoform of heterozygous single nucleotide polymorphism gene without depleting the wild type protein.     

PolysacDB: a database of microbial polysaccharide antigens and their antibodies

Vaccines based on microbial cell surface polysaccharides have long been considered as attractive means to control infectious diseases. To realize this goal, detailed systematic information about the antigenic polysaccharide is necessary. However, only a few databases that provide limited knowledge in this area are available. This paper describes PolysacDB, a manually curated database of antigenic polysaccharides. We collected and compiled comprehensive information from literature and web resources about antigenic polysaccharides of microbial origin. The current version of the database has 1,554 entries of 149 different antigenic polysaccharides from 347 different microbes. Each entry provides comprehensive information about an antigenic polysaccharide, i.e., its origin, function, protocols for its conjugation to carriers, antibodies produced, details of assay systems, specificities of antibodies, proposed epitopes involved and antibody utilities. For convenience to the user, we have integrated web interface for searching, advanced searching and browsing data in database. This database will be useful for researchers working on polysaccharide-based vaccines. It is freely available from the URL: http://crdd.osdd.net/raghava/polysacdb/.     

GlycoPP: a webserver for prediction of N- and O-glycosites in prokaryotic protein sequences

Glycosylation is one of the most abundant post-translational modifications (PTMs) required for various structure/function modulations of proteins in a living cell. Although elucidated recently in prokaryotes, this type of PTM is present across all three domains of life. In prokaryotes, two types of protein glycan linkages are more widespread namely, N- linked, where a glycan moiety is attached to the amide group of Asn, and O- linked, where a glycan moiety is attached to the hydroxyl group of Ser/Thr/Tyr. For their biologically ubiquitous nature, significance, and technology applications, the study of prokaryotic glycoproteins is a fast emerging area of research. Here we describe new Support Vector Machine (SVM) based algorithms (models) developed for predicting glycosylated-residues (glycosites) with high accuracy in prokaryotic protein sequences. The models are based on binary profile of patterns, composition profile of patterns, and position-specific scoring matrix profile of patterns as training features. The study employ an extensive dataset of 107 N-linked and 116 O-linked glycosites extracted from 59 experimentally characterized glycoproteins of prokaryotes. This dataset includes validated N-glycosites from phyla Crenarchaeota, Euryarchaeota (domain Archaea), Proteobacteria (domain Bacteria) and validated O-glycosites from phyla Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria (domain Bacteria). In view of the current understanding that glycosylation occurs on folded proteins in bacteria, hybrid models have been developed using information on predicted secondary structures and accessible surface area in various combinations with training features. Using these models, N-glycosites and O-glycosites could be predicted with an accuracy of 82.71% (MCC 0.65) and 73.71% (MCC 0.48), respectively. An evaluation of the best performing models with 28 independent prokaryotic glycoproteins confirms the suitability of these models in predicting N- and O-glycosites in potential glycoproteins from aforementioned organisms, with reasonably high confidence. A web server GlycoPP, implementing these models is available freely at http:/www.imtech.res.in/raghava/glycopp/.     

Early secretory antigenic target-6 of Mycobacterium tuberculosis: enigmatic factor in pathogen–host interactions

T helper (Th) 1 and 17 cells play important roles in host protective responses against tuberculosis. Early Secretory Antigenic Target 6; a Region of Difference 1 (RD1) encoded protein, mounts Th17-responses in the lung. Therefore, lack of RD-1 region makes Bacillus Calmette–Guérin (BCG) less vaccine efficacious than parent strains.     

In silico platform for predicting and initiating β‐turns in a protein at desired locations

Numerous studies have been performed for analysis and prediction of β‐turns in a protein. This study focuses on analyzing, predicting, and designing of β‐turns to understand the preference of amino acids in β‐turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β‐turns. Based on the results, a propensity‐based method has been developed for predicting β‐turns with an accuracy of 82%. We introduced a new approach entitled “Turn level prediction method,” which predicts the complete β‐turn rather than focusing on the residues in a β‐turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β‐turns by utilizing various features of four residues present in β‐turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β‐turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β‐turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β‐turn in a protein at specified location of a protein. Proteins 2015; 83:910–921. © 2015 Wiley Periodicals, Inc.     

Water transport in epididymal and ejaculated rhesus monkey (Macaca mulatta) sperm during freezing

In the present study, we report the effects of cooling ejaculated and epididymal rhesus monkey (Macacamulatta) sperm with and without the presence of a cryoprotective agent, glycerol. Water transport data during freezing of ejaculated and epididymal sperm cell suspensions were obtained at a cooling rate of 20 °C/min in the absence of any cryoprotective agents and in the presence of 0.7 M of glycerol, as well. Using previously published values, the macaque sperm cell was modeled as a cylinder of length 73.83 μm with a radius of 0.40 μm and an osmotically inactive cell volume, V_b, of 0.772V_o, where V_o is the isotonic cell volume. This translated to a surface area, SA to initial water volume, WV ratio of ∼22 μm⁻¹. By fitting a model of water transport to the experimentally determined volumetric shrinkage data, the best-fit membrane permeability parameters (reference membrane permeability to water at 0 °C, L_pg or L_pg[cpa] and the activation energy, E_Lp or E_Lp[cpa]) were found to range from: L_pg or L_pg[cpa] = 0.0020-0.0029 μm/min-atm; E_Lp or E_Lp[cpa]) = 10.6-18.3 kcal/mole. By incorporating these membrane permeability parameters in a recently developed equation (optimal cooling rate, ; where the units of B_opt are °C/min, E_Lp or E_Lp[cpa] are kcal/mole, L_pg or L_pg[cpa] are μm/min-atm and SA/WV are μm⁻¹), we determined the optimal rates of freezing macaque sperm to be ∼23 °C/min (ejaculated sperm in the absence of CPAs), ∼29 °C/min (ejaculated sperm in the presence of glycerol), ∼24 °C/min (epididymal sperm in the absence of CPAs) and ∼24 °C/min (epididymal sperm in the presence of glycerol). In conclusion, the subzero water transport response and consequently the subzero water transport parameters are not significantly different between the ejaculated and epididymal macaque spermatozoa under corresponding cooling conditions.