A multiple-template approach to protein threading

AI-based AlphaFold2 significantly expands the structural space of the autophagy pathway

ABBREVIATIONS

AF2: AlphaFold2; AF2-Mult: AlphaFold2 multimer; ATG: autophagy-related; CTD: C-terminal domain; ECTD: extreme C-terminal domain; FR: flexible region; MD: molecular dynamics; NTD: N-terminal domain; pLDDT: predicted local distance difference test; UBL: ubiquitin-like.

CADD, AI and ML in drug discovery: A comprehensive review

Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest because of its potential to expedite and lower the cost of the drug development process. Drug discovery research is expensive and time-consuming, and it frequently took 10-15 years for a drug to be commercially available. CADD has significantly impacted this area of research. Further, the combination of CADD with Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies to handle enormous amounts of biological data has reduced the time and cost associated with the drug development process. This review will discuss how CADD, AI, ML, and DL approaches help identify drug candidates and various other steps of the drug discovery process. It will also provide a detailed overview of the different in silico tools used and how these approaches interact.

Contact-Assisted Threading in Low-Homology Protein Modeling

The ability to successfully predict the three-dimensional structure of a protein from its amino acid sequence has made considerable progress in the recent past. The progress is propelled by the improved accuracy of deep learning-based inter-residue contact map predictors coupled with the rising growth of protein sequence databases. Contact map encodes interatomic interaction information that can be exploited for highly accurate prediction of protein structures via contact map threading even for the query proteins that are not amenable to direct homology modeling. As such, contact-assisted threading has garnered considerable research effort. In this chapter, we provide an overview of existing contact-assisted threading methods while highlighting the recent advances and discussing some of the current limitations and future prospects in the application of contact-assisted threading for improving the accuracy of low-homology protein modeling.

New highly antigenic linear B cell epitope peptides from PvAMA-1 as potential vaccine candidates

Peptide-based vaccines have demonstrated to be an important way to induce long-lived immune responses and, therefore, a promising strategy in the rational of vaccine development. As to malaria, among the classic vaccine targets, the Apical membrane antigen (AMA-1) was proven to have important B cell epitopes that can induce specific immune response and, hence, became key players for a vaccine approach. The peptides selection was carried out using a bioinformatic approach based on Hidden Markov Models profiles of known antigens and propensity scale methods based on hydrophilicity and secondary structure prediction. The antigenicity of the selected B-cell peptides was assessed by multiple serological assays using sera from acute P.vivax infected subjects. The synthetic peptides were recognized by 45.5%, 48.7% and 32.2% of infected subjects for peptides I, II and III respectively. Moreover, when synthetized together (tripeptide), the reactivity increases up to 62%, which is comparable to the reactivity found against the whole protein PvAMA-1 (57%). Furthermore, IgG reactivity against the tripeptide after depletion was reduced by 42%, indicating that these epitopes may be responsible for a considerable part of the protein immunogenicity. These results represent an excellent perspective regarding future chimeric vaccine constructions that may come to contemplate several targets with the potential to generate the robust and protective immune response that a vivax malaria vaccine needs to succeed.

Recent Advances in Protein Homology Detection Propelled by Inter-Residue Interaction Map Threading

Sequence-based protein homology detection has emerged as one of the most sensitive and accurate approaches to protein structure prediction. Despite the success, homology detection remains very challenging for weakly homologous proteins with divergent evolutionary profile. Very recently, deep neural network architectures have shown promising progress in mining the coevolutionary signal encoded in multiple sequence alignments, leading to reasonably accurate estimation of inter-residue interaction maps, which serve as a rich source of additional information for improved homology detection. Here, we summarize the latest developments in protein homology detection driven by inter-residue interaction map threading. We highlight the emerging trends in distant-homology protein threading through the alignment of predicted interaction maps at various granularities ranging from binary contact maps to finer-grained distance and orientation maps as well as their combination. We also discuss some of the current limitations and possible future avenues to further enhance the sensitivity of protein homology detection.

Remote homology search with hidden Potts models

Most methods for biological sequence homology search and alignment work with primary sequence alone, neglecting higher-order correlations. Recently, statistical physics models called Potts models have been used to infer all-by-all pairwise correlations between sites in deep multiple sequence alignments, and these pairwise couplings have improved 3D structure predictions. Here we extend the use of Potts models from structure prediction to sequence alignment and homology search by developing what we call a hidden Potts model (HPM) that merges a Potts emission process to a generative probability model of insertion and deletion. Because an HPM is incompatible with efficient dynamic programming alignment algorithms, we develop an approximate algorithm based on importance sampling, using simpler probabilistic models as proposal distributions. We test an HPM implementation on RNA structure homology search benchmarks, where we can compare directly to exact alignment methods that capture nested RNA base-pairing correlations (stochastic context-free grammars). HPMs perform promisingly in these proof of principle experiments.

Vaccine design of coronavirus spike (S) glycoprotein in chicken: immunoinformatics and computational approaches

BACKGROUND

Infectious bronchitis (IB) is a highly contagious respiratory disease in chickens and produces economic loss within the poultry industry. This disease is caused by a single stranded RNA virus belonging to Cronaviridae family. This study aimed to design a potential multi-epitopes vaccine against infectious bronchitis virus spike protein (S). Protein characterization was also performed for IBV spike protein.

METHODS

The present study used various tools in Immune Epitope Database (IEDB) to predict conserved B and T cell epitopes against IBV spike (S) protein that may perform a significant role in provoking the resistance response to IBV infection.

RESULTS

In B cell prediction methods, three epitopes ( ₁₁₃₉ KKSSYY ₁₁₄₄ , ₁₁₄₀ KSSYYT ₁₁₄₅ , ₁₁₄₁ SSYYT ₁₁₄₅ ) were selected as surface, linear and antigenic epitopes.Many MHCI and MHCII epitopes were predicted for IBV S protein. Among them ₉₈₂YYITARDMY₉₉₀ and ₉₈₃ YITARDMYM ₉₉₁ epitopes displayed high antigenicity, no allergenicity and no toxicity as well as great linkage with MHCI and MHCII alleles. Moreover, docking analysis of MHCI epitopes produced strong binding affinity with BF₂ alleles.

CONCLUSION

Five conserved epitopes were expected from spike glycoprotein of IBV as the best B and T cell epitopes due to high antigenicity, no allergenicity and no toxicity. In addition, MHC epitopes showed great linkage with MHC alleles as well as strong interaction with BF2 alleles. These epitopes should be designed and incorporated and then tested as multi-epitope vaccine against IBV.

Refined template selection and combination algorithm significantly improves template-based modeling accuracy

In contrast to ab-initio protein modeling methodologies, comparative modeling is considered as the most popular and reliable algorithm to model protein structure. However, the selection of the best set of templates is still a major challenge. An effective template-ranking algorithm is developed to efficiently select only the reliable hits for predicting the protein structures. The algorithm employs the pairwise as well as multiple sequence alignments of template hits to rank and select the best possible set of templates. It captures several key sequences and structural information of template hits and converts into scores to effectively rank them. This selected set of templates is used to model a target. Modeling accuracy of the algorithm is tested and evaluated on TBM-HA domain containing CASP8, CASP9 and CASP10 targets. On an average, this template ranking and selection algorithm improves GDT-TS, GDT-HA and TM_Score by 3.531, 4.814 and 0.022, respectively. Further, it has been shown that the inclusion of structurally similar templates with ample conformational diversity is crucial for the modeling algorithm to maximally as well as reliably span the target sequence and construct its near-native model. The optimal model sampling also holds the key to predict the best possible target structure.

Aerobic Glycolysis in the Retina: Functional Roles of Pyruvate Kinase Isoforms

One hundred years ago, Otto Heinrich Warburg observed that postmitotic retinal cells are the highest oxygen-consuming cells in the body. He compared these cells to actively growing mitotic tumor cells since both cells reprogram glucose for anabolic processes, which include lipid, protein, and RNA/DNA synthesis, and for antioxidant metabolism. To achieve this metabolic reprogramming, cancer cells preferentially express a less active dimeric form, the M2 isoform of pyruvate kinase (PKM2), which shuttles glucose toward the accumulation of glycolytic intermediates that redirect cell activities into anabolic processes. Similar to cancer cells, retinal photoreceptors predominantly express the M2 isoform of PKM2. This isoform performs both metabolic and non-metabolic functions in photoreceptor cells. This review focuses on the metabolic and non-metabolic roles of pyruvate kinases in photoreceptor cell functions.

Cell-line specific RNA editing patterns in Trypanosoma brucei suggest a unique mechanism to generate protein variation in a system intolerant to genetic mutations

Trypanosoma brucei possesses a highly complex RNA editing system that uses guide RNAs to direct the insertion and deletion of uridines in mitochondrial mRNAs. These changes extensively alter the target mRNAs and can more than double them in length. Recently, analyses showed that several of the edited genes possess the capacity to encode two different protein products. The overlapped reading frames can be accessed through alternative RNA editing that shifts the translated reading frame. In this study, we analyzed the editing patterns of three putative dual-coding genes, ribosomal protein S12 (RPS12), the 5′ editing domain of NADH dehydrogenase subunit 7 (ND7 5′), and C-rich region 3 (CR3). We found evidence that alternatively 5′-edited ND7 5′ and CR3 transcripts are present in the transcriptome, providing evidence for the use of dual ORFs in these transcripts. Moreover, we found that CR3 has a complex set of editing pathways that vary substantially between cell lines. These findings suggest that alternative editing can work to introduce genetic variation in a system that selects against nucleotide mutations.

Immunoinformatics Approach for Multiepitope Vaccine Prediction from H, M, F, and N Proteins of Peste des Petits Ruminants Virus

Background

Small ruminant morbillivirus or peste des petits ruminants virus (PPRV) is an acute and highly contagious viral disease of goats, sheep, and other livestock. This study aimed at predicting an effective multiepitope vaccine against PPRV from the immunogenic proteins haemagglutinin (H), matrix (M), fusion (F), and nucleoprotein (N) using immunoinformatics tools.

Materials and Methods

The sequences of the immunogenic proteins were retrieved from GenBank of the National Center for Biotechnology Information (NCBI). BioEdit software was used to align each protein from the retrieved sequences for conservancy. Immune Epitope Database (IEDB) analysis resources were used to predict B and T cell epitopes. For B cells, the criteria for electing epitopes depend on the epitope linearity, surface accessibility, and antigenicity.

Results

Nine epitopes from the H protein, eight epitopes from the M protein, and ten epitopes from each of the F and N proteins were predicted as linear epitopes. The surface accessibility method proposed seven surface epitopes from each of the H and F proteins in addition to six and four epitopes from the M and N proteins, respectively. For antigenicity, only two epitopes ₁₄₂PPERV₁₄₆ and ₆₃DPLSP₆₇ were predicted as antigenic from H and M, respectively. For T cells, MHC-I binding prediction tools showed multiple epitopes that interacted strongly with BoLA alleles. For instance, the epitope ₄₅MFLSLIGLL₅₃ from the H protein interacted with four BoLA alleles, while ₂₇₆FKKILCYPL₂₈₄ predicted from the M protein interacted with two alleles. Although F and N proteins demonstrated no favorable interaction with B cells, they strongly interacted with T cells. For instance, ₃₅₈STKSCARTL₃₆₆ from the F protein interacted with five alleles, followed by ₃₄₀SQNALYPMS₃₄₈ and ₄₄₂IDLGPAISL₄₅₀ that interacted with three alleles each. The epitopes from the N protein displayed strong interaction with BoLA alleles such as ₄₉₀RSAEALFRL₄₉₈ that interacted with five alleles, followed by two epitopes ₂ATLLKSLAL₁₀ and ₃₀₄QQLGEVAPY₃₁₂ that interacted with four alleles each. In addition to that, four epitopes ₃TLLKSLALF₁₁, ₃₅₆YFDPAYFRL₃₆₄, ₃₆₀AYFRLGQEM₃₆₈, and ₄₁₂PRQAQVSFL₄₂₀ interacted with three alleles each.

Conclusion

Fourteen epitopes were predicted as promising vaccine candidates against PPRV from four immunogenic proteins. These epitopes should be validated experimentally through in vitro and in vivo studies.

Immunoinformatics: In Silico Approaches and Computational Design of a Multi-epitope, Immunogenic Protein

Immunoinformatics is a new critical field with several tools and databases that conduct the eyesight of experimental selection and facilitate analysis of the great amount of immunologic data obtained from experimental researches and helps to design and introducing new hypothesis. Given these visages, immunoinformatics seems to be the way that develop and progress the immunological research. Bioinformatics methods and applications are successfully employed in vaccine informatics to assist different sites of the preclinical, clinical, and post-licensure vaccine enterprises. On the other hand, the progression of molecular biology and immunology caused epitope vaccines have become the focus of research on molecular vaccines. Moreover, reverse vaccinology could improve vaccine production and vaccination protocols by in silico prediction of protein-vaccine candidates from genome sequences. B- and T-cell immune epitopes could be predicted by immunoinformatics algorithms and computational methods to improve the vaccine design, protective immunity analysis, assessment of vaccine safety and efficacy, and immunization modeling. This review aims to discuss the power of computational approaches in vaccine design and their relevance to the development of effective vaccines. Furthermore, the various divisions of this field and available tools in each item are introduced and reviewed.

Protein threading using residue co-variation and deep learning

Motivation

Template-based modeling, including homology modeling and protein threading, is a popular method for protein 3D structure prediction. However, alignment generation and template selection for protein sequences without close templates remain very challenging.

Results

We present a new method called DeepThreader to improve protein threading, including both alignment generation and template selection, by making use of deep learning (DL) and residue co-variation information. Our method first employs DL to predict inter-residue distance distribution from residue co-variation and sequential information (e.g. sequence profile and predicted secondary structure), and then builds sequence-template alignment by integrating predicted distance information and sequential features through an ADMM algorithm. Experimental results suggest that predicted inter-residue distance is helpful to both protein alignment and template selection especially for protein sequences without very close templates, and that our method outperforms currently popular homology modeling method HHpred and threading method CNFpred by a large margin and greatly outperforms the latest contact-assisted protein threading method EigenTHREADER.

Availability and implementation

http://raptorx.uchicago.edu/

Supplementary information

Supplementary data are available at Bioinformatics online.

Improved homology modeling of the human & rat EP4 prostanoid receptors

Background

The EP₄ prostanoid receptor is one of four GPCRs that mediate the diverse actions of prostaglandin E₂ (PGE₂). Novel selective EP₄ receptor agonists would assist to further elucidate receptor sub-type function and promote development of therapeutics for bone healing, heart failure, and other receptor associated conditions. The rat EP₄ (rEP₄) receptor has been used as a surrogate for the human EP₄ (hEP₄) receptor in multiple SAR studies. To better understand the validity of this traditional approach, homology models were generated by threading for both receptors using the RaptorX server. These models were fit to an implicit membrane using the PPM server and OPM database with refinement of intra and extracellular loops by Prime (Schrödinger). To understand the interaction between the receptors and known agonists, induced-fit docking experiments were performed using Glide and Prime (Schrödinger), with both endogenous agonists and receptor sub-type selective, small-molecule agonists. The docking scores and observed interactions were compared with radioligand displacement experiments and receptor (rat & human) activation assays monitoring cAMP.

Results

Rank-ordering of in silico compound docking scores aligned well with in vitro activity assay EC₅₀ and radioligand binding K_i. We observed variations between rat and human EP₄ binding pockets that have implications in future small-molecule receptor-modulator design and SAR, specifically a S103G mutation within the rEP4 receptor. Additionally, these models helped identify key interactions between the EP₄ receptor and ligands including PGE₂ and several known sub-type selective agonists while serving as a marked improvement over the previously reported models.

Conclusions

This work has generated a set of novel homology models of the rEP₄ and hEP₄ receptors. The homology models provide an improvement upon the previously reported model, largely due to improved solvation. The hEP₄ docking scores correlates best with the cAMP activation data, where both data sets rank order Rivenprost>CAY10684 > PGE₁ ≈ PGE₂ > 11-deoxy-PGE₁ ≈ 11-dexoy-PGE₂ > 8-aza-11-deoxy-PGE₁. This rank-ordering matches closely with the rEP₄ receptor as well. Species-specific differences were noted for the weak agonists Sulprostone and Misoprostol, which appear to dock more readily within human receptor versus rat receptor.

Electronic supplementary material

The online version of this article (10.1186/s12860-019-0212-5) contains supplementary material, which is available to authorized users.

Structure of the SARS-Unique Domain C From the Bat Coronavirus HKU4

Coronaviruses (CoVs) that cause infections such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome phylogenetically originate from bat CoVs. The coronaviral nonstructural protein 3 (nsp3) has been implicated in viral replication, polyprotein cleavage, and host immune interference. We report the structure of the C domain from the SARS-Unique Domain of bat CoV HKU4. The protein has a frataxin fold, consisting of 5 antiparallel β strands packed against 2 α helices. Bioinformatics analyses and nuclear magnetic resonance experiments were conducted to investigate the function of HKU4 C. The results showed that HKU4 C engages in protein-protein interactions with the nearby M domain of nsp3. The HKU4 C residues involved in protein-protein interactions are conserved in group 2c CoVs, indicating a conserved function.

Identification of alternative oxidase encoding genes in Caulerpa cylindracea by de novo RNA-Seq assembly analysis

Alternative oxidases (AOX) are defined in plants, fungi and algae. The main function of AOX proteins has been described for electron flow through electron transport chain and regulation of mitochondrial retrograde signaling pathway. The roles of AOX proteins have been characterized in reproduction and resistance against oxidative stress, cold stress, starvation, and biotic attacks. Caulerpa cylindracea is an invasive marine green alga. Although the natural habitats of the species are Australia coasts, the impact of the invasion has been monitored through the Mediterranean Sea and the Aegean Sea. C. cylindracea species have advantages against others by showing higher resistance to stress conditions such as cold, starvation, pathogen attacks and by their capability of sexual and vegetative reproduction. Comparing the advantages of C. cylindracea over the niche and defined functional roles of mitochondrial AOX proteins, it is evident that AOX proteins are likely involved in developing those advantageous skills in C. cylindracea. However, there is limited data about biochemical and molecular mechanisms that take part in stress resistance and invasion characteristics. We aimed to identify mitochondrial alternative oxidase encoding genes in C. cylindracea while annotating whole transcriptome data for the species. Samples were collected from Seferihisar/İzmir. Transcriptome analysis from pooled RNA samples revealed 47,400 assembled contigs represented by 33,340 unigenes. Using standalone Blast analysis, we were able to identify two alternative oxidase encoding genes.

Does inclusion of residue-residue contact information boost protein threading?

Template-based modeling is considered as one of the most successful approaches for protein structure prediction. However, reliably and accurately selecting optimal template proteins from a library of known protein structures having similar folds as the target protein and making correct alignments between the target sequence and the template structures, a template-based modeling technique known as threading, remains challenging, particularly for non- or distantly-homologous protein targets. With the recent advancement in protein residue-residue contact map prediction powered by sequence co-evolution and machine learning, here we systematically analyze the effect of inclusion of residue-residue contact information in improving the accuracy and reliability of protein threading. We develop a new threading algorithm by incorporating various sequential and structural features, and subsequently integrate residue-residue contact information as an additional scoring term for threading template selection. We show that the inclusion of contact information attains statistically significantly better threading performance compared to a baseline threading algorithm that does not utilize contact information when everything else remains the same. Experimental results demonstrate that our contact based threading approach outperforms popular threading method MUSTER, contact-assisted ab initio folding method CONFOLD2, and recent state-of-the-art contact-assisted protein threading methods EigenTHREADER and map_align on several benchmarks. Our study illustrates that the inclusion of contact maps is a promising avenue in protein threading to ultimately help to improve the accuracy of protein structure prediction.

Immunoinformatics Approach for Multiepitopes Vaccine Prediction against Glycoprotein B of Avian Infectious Laryngotracheitis Virus

Infectious laryngotracheitis virus (ILTV) is a gallid herpesvirus type 1, a member of the genus Iltovirus. It causes an infection in the upper respiratory tract mainly trachea which results in significant economic losses in the poultry industry worldwide. Vaccination against ILTV produced latent infected carriers' birds, which become a source of virus transmission to nonvaccinated flocks. Thus this study aimed to design safe multiepitopes vaccine against glycoprotein B of ILT virus using immunoinformatic tools. Forty-four sequences of complete envelope glycoprotein B were retrieved from GenBank of National Center for Biotechnology Information (NCBI) and aligned for conservancy by multiple sequence alignment (MSA). Immune Epitope Database (IEDB) analysis resources were used to predict and analyze candidate epitopes that could act as a promising peptide vaccine. For B cell epitopes, thirty-one linear epitopes were predicted using Bepipred. However eight epitopes were found to be on both surface and antigenic epitopes using Emini surface accessibility and antigenicity, respectively. Three epitopes (₁₉₀KKLP₁₉₃, ₃₈₆YSSTHVRS₃₉₃, and ₃₁₇KESV₃₂₀) were proposed as B cell epitopes. For T cells several epitopes were interacted with MHC class I with high affinity and specificity, but the best recognized epitopes were ₁₁₈YVFNVTLYY₁₂₆, ₃₃₅VSYKNSYHF₃₄₃, and ₆₂₂YLLYEDYTF₆₃₀. MHC-II binding epitopes, ₃₀₁FLTDEQFTI₃₀₉,₂₇₇FLEIANYQV₂₈₅, and ₇₄₃IASFLSNPF₇₅₁, were proposed as promising epitopes due to their high affinity for MHC-II molecules. Moreover the docked ligand epitopes from MHC-1 molecule exhibited high binding affinity with the receptors; BF chicken alleles (BF2 2101 and 0401) expressed by the lower global energy of the molecules. In this study nine epitopes were predicted as promising vaccine candidate against ILTV. In vivo and in vitro studies are required to support the effectiveness of these predicted epitopes as a multipeptide vaccine through clinical trials.

A multi-method and structure-based in silico vaccine designing against Echinococcus granulosus through investigating enolase protein

Introduction: Hydatid disease is a ubiquitous parasitic zoonotic disease, which causes different medical, economic and serious public health problems in some parts of the world. The causal organism is a multi-stage parasite named Echinococcus granulosus whose life cycle is dependent on two types of mammalian hosts viz definitive and intermediate hosts.

Methods: In this study, enolase, as a key functional enzyme in the metabolism of E. granulosus (EgEnolase), was targeted through a comprehensive in silico modeling analysis and designing a host-specific multi-epitope vaccine. Three-dimensional (3D) structure of enolase was modeled using MODELLER v9.18 software. The B-cell epitopes (BEs) were predicted based on the multi-method approach and via some authentic online predictors. ClusPro v2.0 server was used for docking-based T-helper epitope prediction. The 3D structure of the vaccine was modeled using the RaptorX server. The designed vaccine was evaluated for its immunogenicity, physicochemical properties, and allergenicity. The codon optimization of the vaccine sequence was performed based on the codon usage table of E. coli K12. Finally, the energy minimization and molecular docking were implemented for simulating the vaccine binding affinity to the TLR-2 and TLR-4 and the complex stability.

Results: The designed multi-epitope vaccine was found to induce anti-EgEnolase immunity which may have the potential to prevent the survival and proliferation of E. granulosus into the definitive host.

Conclusion: Based on the results, this step-by-step immunoinformatics approach could be considered as a rational platform for designing vaccines against such multi-stage parasites. Furthermore, it is proposed that this multi-epitope vaccine is served as a promising preventive anti-echinococcosis agent.

Exploring sand fly salivary proteins to design multiepitope subunit vaccine to fight against visceral leishmaniasis

Visceral leishmaniasis (VL) is caused by the parasites of Leishmania donovani complex, leads to the death of 20 000 to 40 000 people from 56 affected countries, worldwide. Till date, there is not a single available vaccine candidate to prevent the VL infection, and treatment only relies upon expensive and toxic chemotherapeutic options. Consequently, immunoinformatics approach was applied to design a multiepitope-based subunit vaccine to enhance the humoral as well as cell-mediated immunity. Constructed vaccine candidate was further subjected to evaluation on allergenicity and antigenicity and physiochemical parameters. Later on, disulfide engineering was performed to increase the stability of vaccine construct. Also, molecular docking and molecular dynamics simulation study were performed to check the binding affinity and stability of toll-like receptor-4 to vaccine construct complex. Finally, codon optimization and in silico cloning were performed to ensure the expression of proposed vaccine construct in a microbial expression system.

Partner-specific prediction of RNA-binding residues in proteins: A critical assessment

RNA-protein interactions play essential roles in regulating gene expression. While some RNA-protein interactions are "specific", that is, the RNA-binding proteins preferentially bind to particular RNA sequence or structural motifs, others are "non-RNA specific." Deciphering the protein-RNA recognition code is essential for comprehending the functional implications of these interactions and for developing new therapies for many diseases. Because of the high cost of experimental determination of protein-RNA interfaces, there is a need for computational methods to identify RNA-binding residues in proteins. While most of the existing computational methods for predicting RNA-binding residues in RNA-binding proteins are oblivious to the characteristics of the partner RNA, there is growing interest in methods for partner-specific prediction of RNA binding sites in proteins. In this work, we assess the performance of two recently published partner-specific protein-RNA interface prediction tools, PS-PRIP, and PRIdictor, along with our own new tools. Specifically, we introduce a novel metric, RNA-specificity metric (RSM), for quantifying the RNA-specificity of the RNA binding residues predicted by such tools. Our results show that the RNA-binding residues predicted by previously published methods are oblivious to the characteristics of the putative RNA binding partner. Moreover, when evaluated using partner-agnostic metrics, RNA partner-specific methods are outperformed by the state-of-the-art partner-agnostic methods. We conjecture that either (a) the protein-RNA complexes in PDB are not representative of the protein-RNA interactions in nature, or (b) the current methods for partner-specific prediction of RNA-binding residues in proteins fail to account for the differences in RNA partner-specific versus partner-agnostic protein-RNA interactions, or both.

Cell signalling pathway regulation by RanBPM: molecular insights and disease implications

RanBPM (Ran-binding protein M, also called RanBP9) is an evolutionarily conserved, ubiquitous protein which localizes to both nucleus and cytoplasm. RanBPM has been implicated in the regulation of a number of signalling pathways to regulate several cellular processes such as apoptosis, cell adhesion, migration as well as transcription, and plays a critical role during development. In addition, RanBPM has been shown to regulate pathways implicated in cancer and Alzheimer's disease, implying that RanBPM has important functions in both normal and pathological development. While its functions in these processes are still poorly understood, RanBPM has been identified as a component of a large complex, termed the CTLH (C-terminal to LisH) complex. The yeast homologue of this complex functions as an E3 ubiquitin ligase that targets enzymes of the gluconeogenesis pathway. While the CTLH complex E3 ubiquitin ligase activity and substrates still remain to be characterized, the high level of conservation between the complexes in yeast and mammals infers that the CTLH complex could also serve to promote the degradation of specific substrates through ubiquitination, therefore suggesting the possibility that RanBPM's various functions may be mediated through the activity of the CTLH complex.

Development of multi-epitope driven subunit vaccine in secretory and membrane protein of Plasmodium falciparum to convey protection against malaria infection

Malaria infection is the severe health concern for a long time. As per the WHO reports, the malarial infection causes huge mortality all around the world and is incomparable with any other infectious diseases. The absence of effective treatment options and increasing drug resistance to the available therapeutics like artemisinin and other derivatives demand an efficient alternative to overcome this death burden. Here, we performed the literature survey and sorted the Plasmodium falciparum secretory and membrane proteins to design multi-epitope subunit vaccine using an adjuvant, B-cell- and T-cell epitopes. Every helper T-lymphocyte (HTL) epitope was IFN-γ positive and IL-4 non-inducer. The physicochemical properties, allergenicity, and antigenicity of designed vaccine were analyzed for the safety concern. Homology modeling and refinement were performed to obtain the functional tertiary structure of vaccine protein followed by its molecular docking with the toll-like receptor-4 (TLR-4) immune receptor. Molecular dynamics simulation was performed to check the interaction and stability of the receptor-ligand complex. Lastly, in silico cloning was performed to generate the restriction clone of designed vaccine for the futuristic expression in a microbial expression system. This way, we designed the multi-epitope subunit vaccine to serve the people living in the global endemic zone.

Acyl-CoA Oxidases Fine-Tune the Production of Ascaroside Pheromones with Specific Side Chain Lengths

Caenorhabditis elegans produces a complex mixture of ascaroside pheromones to control its development and behavior. Acyl-CoA oxidases, which participate in β-oxidation cycles that shorten the side chains of the ascarosides, regulate the mixture of pheromones produced. Here, we use CRISPR-Cas9 to make specific nonsense and missense mutations in acox genes and determine the effect of these mutations on ascaroside production in vivo. Ascaroside production in acox-1.1 deletion and nonsense strains, as well as a strain with a missense mutation in a catalytic residue, confirms the central importance of ACOX-1.1 in ascaroside biosynthesis and suggests that ACOX-1.1 functions in part by facilitating the activity of other acyl-CoA oxidases. Ascaroside production in an acox-1.1 strain with a missense mutation in an ATP-binding site at the ACOX-1.1 dimer interface suggests that ATP binding is important for the enzyme to function in ascaroside biosynthesis in vivo. Ascaroside production in strains with deletion, nonsense, and missense mutations in other acox genes demonstrates that ACOX-1.1 works with ACOX-1.3 in processing ascarosides with 7-carbon side chains, ACOX-1.4 in processing ascarosides with 9- and 11-carbon side chains, and ACOX-3 in processing ascarosides with 13- and 15-carbon side chains. It also shows that ACOX-1.2, but not ACOX-1.1, processes ascarosides with 5-carbon ω-side chains. By modeling the ACOX structures, we uncover characteristics of the enzyme active sites that govern substrate preferences. Our work demonstrates the role of specific acyl-CoA oxidases in controlling the length of ascaroside side chains and thus in determining the mixture of pheromones produced by C. elegans.

The physiological effect of heavy metals and volatile fatty acids on Methanococcus maripaludis S2

BACKGROUND

Methanogenic archaea are of importance to the global C-cycle and to biological methane (CH₄) production through anaerobic digestion and pure culture. Here, the individual and combined effects of copper (Cu), zinc (Zn), acetate, and propionate on the metabolism of the autotrophic, hydrogenotrophic methanogen Methanococcus maripaludis S2 were investigated. Cu, Zn, acetate, and propionate may interfere directly and indirectly with the acetyl-CoA synthesis and biological CH₄ production. Thus, these compounds can compromise or improve the performance of M. maripaludis, an organism which can be applied as biocatalyst in the carbon dioxide (CO₂)-based biological CH₄ production (CO₂-BMP) process or of methanogenic organisms applied in anaerobic digestion.

RESULTS

Here, we show that Cu concentration of 1.9 µmol L^-1 reduced growth of M. maripaludis, whereas 4.4 and 6.3 µmol L^-1 of Cu even further retarded biomass production. However, 1.0 mmol L^-1 of Zn enhanced growth, but at Zn concentrations > 2.4 mmol L^-1 no growth could be observed. When both, Cu and Zn, were supplemented to the medium, growth and CH₄ production could even be observed at the highest tested concentration of Cu (6.3 µmol L^-1). Hence, it seems that the addition of 1 mmol L^-1 of Zn enhanced the ability of M. maripaludis to counteract the toxic effect of Cu. The physiological effect to rising concentrations of acetate (12.2, 60.9, 121.9 mmol L^-1) and/or propionate (10.3, 52.0, 104.1 mmol L^-1) was also investigated. When instead of acetate 10.3 mmol L^-1 propionate was provided in the growth medium, M. maripaludis could grow without reduction of the specific growth rate (µ) or the specific CH₄ productivity (qCH₄). A combination of inorganic and/or organic compounds resulted in an increase of µ and qCH₄ for Zn/Cu and Zn/acetate beyond the values that were observed if only the individual concentrations of Zn, Cu, acetate were used.

CONCLUSIONS

Our study sheds light on the physiological effect of VFAs and heavy metals on M. maripaludis. Differently from µ and qCH₄, MER was not influenced by the presence of these compounds. This indicated that each of these compounds directly interacted with the C-fixation machinery of M. maripaludis. Until now, the uptake of VFAs other than acetate was not considered to enhance growth and CH₄ production of methanogens. The finding of propionate uptake by M. maripaludis is important for the interpretation of VFA cycling in anaerobic microenvironments. Due to the importance of methanogens in natural and artificial anaerobic environments, our results help to enhance the understanding the physiological and biotechnological importance with respect to anaerobic digestion, anaerobic wastewater treatment, and CO₂-BMP. Finally, we propose a possible mechanism for acetate uptake into M. maripaludis supported by in silico analyses.

EigenTHREADER: analogous protein fold recognition by efficient contact map threading

MOTIVATION

Protein fold recognition when appropriate, evolutionarily-related, structural templates can be identified is often trivial and may even be viewed as a solved problem. However in cases where no homologous structural templates can be detected, fold recognition is a notoriously difficult problem ( Moult et al., 2014 ). Here we present EigenTHREADER, a novel fold recognition method capable of identifying folds where no homologous structures can be identified. EigenTHREADER takes a query amino acid sequence, generates a map of intra-residue contacts, and then searches a library of contact maps of known structures. To allow the contact maps to be compared, we use eigenvector decomposition to resolve the principal eigenvectors these can then be aligned using standard dynamic programming algorithms. The approach is similar to the Al-Eigen approach of Di Lena et al. (2010) , but with improvements made both to speed and accuracy. With this search strategy, EigenTHREADER does not depend directly on sequence homology between the target protein and entries in the fold library to generate models. This in turn enables EigenTHREADER to correctly identify analogous folds where little or no sequence homology information is.

RESULTS

EigenTHREADER outperforms well-established fold recognition methods such as pGenTHREADER and HHSearch in terms of True Positive Rate in the difficult task of analogous fold recognition. This should allow template-based modelling to be extended to many new protein families that were previously intractable to homology based fold recognition methods.

AVAILABILITY AND IMPLEMENTATION

All code used to generate these results and the computational protocol can be downloaded from https://github.com/DanBuchan/eigen_scripts . EigenTHREADER, the benchmark code and the data this paper is based on can be downloaded from: http://bioinfadmin.cs.ucl.ac.uk/downloads/eigenTHREADER/ .

CONTACT

d.t.jones@ucl.ac.uk.

Identification of a conserved 8 aa insert in the PIP5K protein in the Saccharomycetaceae family of fungi and the molecular dynamics simulations and structural analysis to investigate its potential functional role

Homologs of the phosphatidylinositol-4-phosphate-5-kinase (PIP5K), which controls a multitude of essential cellular functions, contain a 8 aa insert in a conserved region that is specific for the Saccharomycetaceae family of fungi. Using structures of human PIP4K proteins as templates, structural models were generated of the Saccharomyces cerevisiae and human PIP5K proteins. In the modeled S. cerevisiae PIP5K, the 8 aa insert forms a surface exposed loop, present on the same face of the protein as the activation loop of the kinase domain. Electrostatic potential analysis indicates that the residues from 8 aa conserved loop form a highly positively charged surface patch, which through electrostatic interaction with the anionic portions of phospholipid head groups, is expected to play a role in the membrane interaction of the yeast PIP5K. To unravel this prediction, molecular dynamics (MD) simulations were carried out to examine the binding interaction of PIP5K, either containing or lacking the conserved signature insert, with two different membrane lipid bilayers. The results from MD studies provide insights concerning the mechanistic of interaction of PIP5K with lipid bilayer, and support the contention that the identified 8 aa conserved insert in fungal PIP5K plays an important role in the binding of this protein with membrane surface. Proteins 2017; 85:1454-1467. © 2017 Wiley Periodicals, Inc.

Feeding recombinant E. coli with GST-mBmKTX fusion protein increases the fecundity and lifespan of Caenorhabditis elegans

Scorpion venom could be a useful treatment for a variety of diseases, such as cancer, epilepsy and analgesia. BmKTX is a polypeptide extracts from scorpion venom (PESV), which have attracted much attention from researchers in recent years. mBmKTX is a mutant polypeptide according to the amino acid sequence of BmKTX. We expressed it with the vector pGEX-4T-1 in Escherichia coli, and Caenorhabditis elegans were used as the animal model and fed with the strains. In this study, the expression of pGEX-mBmKTX was analyzed by SDS-PAGE, and GST-mBmKTX purified from pGEX-mBmKTX as a glutathione S-transferase (GST)-tagged fusion protein is approximately 30kDa. The secondary structure prediction shows that mBmKTX is mainly composed of approximately 13% β-sheet and 86% loop. A food clearance assay and brood size assay indicated that the worms fed pGEX-mBmKTX ate more and had greater fecundity than those fed the empty vector. A lifespan analysis demonstrated that mBmKTX could significantly prolong the lifespan of C. elegans, with an increase of 22.5% compared with the control. Behavioral assays confirmed that mBmKTX had no influence on the locomotion of C. elegans. In addition, microarray analysis and quantitative real-time PCR demonstrated that there are 320 differentially expressed genes, 182 of which are related to reproduction, growth and lifespan. In conclusion, the data suggested that mBmKTX has potential utility for increasing fecundity and animal survival.

Mitochondrial-nuclear co-evolution leads to hybrid incompatibility through pentatricopeptide repeat proteins

Mitochondrial-nuclear incompatibility has a major role in reproductive isolation between species. However, the underlying mechanism and driving force of mitochondrial-nuclear incompatibility remain elusive. Here, we report a pentatricopeptide repeat-containing (PPR) protein, Ccm1, and its interacting partner, 15S rRNA, to be involved in hybrid incompatibility between two yeast species, Saccharomyces cerevisiae and Saccharomyces bayanus S. bayanus-Ccm1 has reduced binding affinity for S. cerevisiae-15S rRNA, leading to respiratory defects in hybrid cells. This incompatibility can be rescued by single mutations on several individual PPR motifs, demonstrating the highly evolvable nature of PPR proteins. When we examined other PPR proteins in the closely related Saccharomyces sensu stricto yeasts, about two-thirds of them showed detectable incompatibility. Our results suggest that fast co-evolution between flexible PPR proteins and their mitochondrial RNA substrates may be a common driving force in the development of mitochondrial-nuclear hybrid incompatibility.

gmos: Rapid Detection of Genome Mosaicism over Short Evolutionary Distances

Prokaryotic and viral genomes are often altered by recombination and horizontal gene transfer. The existing methods for detecting recombination are primarily aimed at viral genomes or sets of loci, since the expensive computation of underlying statistical models often hinders the comparison of complete prokaryotic genomes. As an alternative, alignment-free solutions are more efficient, but cannot map (align) a query to subject genomes. To address this problem, we have developed gmos (Genome MOsaic Structure), a new program that determines the mosaic structure of query genomes when compared to a set of closely related subject genomes. The program first computes local alignments between query and subject genomes and then reconstructs the query mosaic structure by choosing the best local alignment for each query region. To accomplish the analysis quickly, the program mostly relies on pairwise alignments and constructs multiple sequence alignments over short overlapping subject regions only when necessary. This fine-tuned implementation achieves an efficiency comparable to an alignment-free tool. The program performs well for simulated and real data sets of closely related genomes and can be used for fast recombination detection; for instance, when a new prokaryotic pathogen is discovered. As an example, gmos was used to detect genome mosaicism in a pathogenic Enterococcus faecium strain compared to seven closely related genomes. The analysis took less than two minutes on a single 2.1 GHz processor. The output is available in fasta format and can be visualized using an accessory program, gmosDraw (freely available with gmos).

Reversible thermal unfolding of a yfdX protein with chaperone-like activity

yfdX proteins are ubiquitously present in a large number of virulent bacteria. A member of this family of protein in E. coli is known to be up-regulated by the multidrug response regulator. Their abundance in such bacteria suggests some important yet unidentified functional role of this protein. Here, we study the thermal response and stability of yfdX protein STY3178 from Salmonella Typhi using circular dichroism, steady state fluorescence, dynamic light scattering and nuclear magnetic resonance experiments. We observe the protein to be stable up to a temperature of 45 °C. It folds back to the native conformation from unfolded state at temperature as high as 80 °C. The kinetic measurements of unfolding and refolding show Arrhenius behavior where the refolding involves less activation energy barrier than that of unfolding. We propose a homology model to understand the stability of the protein. Our molecular dynamic simulation studies on this model structure at high temperature show that the structure of this protein is quite stable. Finally, we report a possible functional role of this protein as a chaperone, capable of preventing DTT induced aggregation of insulin. Our studies will have broader implication in understanding the role of yfdX proteins in bacterial function and virulence.

Characterization of Five Novel Brevibacillus Bacteriophages and Genomic Comparison of Brevibacillus Phages

Brevibacillus laterosporus is a spore-forming bacterium that causes a secondary infection in beehives following European Foulbrood disease. To better understand the contributions of Brevibacillus bacteriophages to the evolution of their hosts, five novel phages (Jenst, Osiris, Powder, SecTim467, and Sundance) were isolated and characterized. When compared with the five Brevibacillus phages currently in NCBI, these phages were assigned to clusters based on whole genome and proteome synteny. Powder and Osiris, both myoviruses, were assigned to the previously described Jimmer-like cluster. SecTim467 and Jenst, both siphoviruses, formed a novel phage cluster. Sundance, a siphovirus, was assigned as a singleton phage along with the previously isolated singleton, Emery. In addition to characterizing the basic relationships between these phages, several genomic features were observed. A motif repeated throughout phages Jenst and SecTim467 was frequently upstream of genes predicted to function in DNA replication, nucleotide metabolism, and transcription, suggesting transcriptional co-regulation. In addition, paralogous gene pairs that encode a putative transcriptional regulator were identified in four Brevibacillus phages. These paralogs likely evolved to bind different DNA sequences due to variation at amino acid residues predicted to bind specific nucleotides. Finally, a putative transposable element was identified in SecTim467 and Sundance that carries genes homologous to those found in Brevibacillus chromosomes. Remnants of this transposable element were also identified in phage Jenst. These discoveries provide a greater understanding of the diversity of phages, their behavior, and their evolutionary relationships to one another and to their host. In addition, they provide a foundation with which further Brevibacillus phages can be compared.

Protein rethreading: A novel approach to protein design

Protein engineering is an important tool for the design of proteins with novel and desirable features. Templates from the protein databank (PDB) are often used as initial models that can be modified to introduce new properties. We examine whether it is possible to reconnect a protein in a manner that generates a new topology yet preserves its structural integrity. Here, we describe the rethreading of dihydrofolate reductase (DHFR) from E. coli (wtDHFR). The rethreading process involved the removal of three native loops, and the introduction of three new loops with alternate connections. The structure of the rethreaded DHFR (rDHFR-1) was determined to 1.6 Å, demonstrating the success of the rethreading process. Both wtDHFR and rDHFR-1 exhibited similar affinities towards methotrexate. However, rDHFR-1 showed no reducing activity towards dihydrofolate, and exhibited about ~6-fold lower affinity towards NADPH than wtDHFR. This work demonstrates that protein rethreading can be a powerful tool for the design of a large array of proteins with novel structures and topologies, and that by careful rearrangement of a protein sequence, the sequence to structure relationship can be expanded substantially.

A Stochastic Point Cloud Sampling Method for Multi-Template Protein Comparative Modeling

Generating tertiary structural models for a target protein from the known structure of its homologous template proteins and their pairwise sequence alignment is a key step in protein comparative modeling. Here, we developed a new stochastic point cloud sampling method, called MTMG, for multi-template protein model generation. The method first superposes the backbones of template structures, and the Cα atoms of the superposed templates form a point cloud for each position of a target protein, which are represented by a three-dimensional multivariate normal distribution. MTMG stochastically resamples the positions for Cα atoms of the residues whose positions are uncertain from the distribution, and accepts or rejects new position according to a simulated annealing protocol, which effectively removes atomic clashes commonly encountered in multi-template comparative modeling. We benchmarked MTMG on 1,033 sequence alignments generated for CASP9, CASP10 and CASP11 targets, respectively. Using multiple templates with MTMG improves the GDT-TS score and TM-score of structural models by 2.96–6.37% and 2.42–5.19% on the three datasets over using single templates. MTMG’s performance was comparable to Modeller in terms of GDT-TS score, TM-score, and GDT-HA score, while the average RMSD was improved by a new sampling approach. The MTMG software is freely available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/mtmg.html.

A novel follicle-stimulating hormone receptor mutation causing primary ovarian failure: a fertility application of whole exome sequencing

STUDY QUESTION

Can whole exome sequencing (WES) and in vitro validation studies be used to find the causative genetic etiology in a patient with primary ovarian failure and infertility?

SUMMARY ANSWER

A novel follicle-stimulating hormone receptor (FSHR) mutation was found by WES and shown, via in vitro flow cytometry studies, to affect membrane trafficking.

WHAT IS KNOWN ALREADY

WES may diagnose up to 25-35% of patients with suspected disorders of sex development (DSD). FSHR mutations are an extremely rare cause of 46, XX gonadal dysgenesis with primary amenorrhea due to hypergonadotropic ovarian failure.

STUDY DESIGN, SIZE, DURATION

A WES study was followed by flow cytometry studies of mutant protein function.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The study subjects were two Turkish sisters with hypergonadotropic primary amenorrhea, their parents and two unaffected sisters. The affected siblings and both parents were sequenced (trio-WES). Transient transfection of HEK 293T cells was performed with a vector containing wild-type FSHR as well as the novel FSHR variant that was discovered by WES. Cellular localization of FSHR protein as well as FSH-stimulated cyclic AMP (cAMP) production was evaluated using flow cytometry.

MAIN RESULTS AND THE ROLE OF CHANCE

Both affected sisters were homozygous for a previously unreported missense mutation (c.1222G>T, p.Asp408Tyr) in the second transmembrane domain of FSHR. Modeling predicted disrupted secondary structure. Flow cytometry demonstrated an average of 48% reduction in cell-surface signal detection (P < 0.01). The mean fluorescent signal for cAMP (second messenger of FSHR), stimulated by FSH, was reduced by 50% in the mutant-transfected cells (P < 0.01).

LIMITATIONS, REASONS FOR CAUTION

This is an in vitro validation. All novel purported genetic variants can be clinically reported only as 'variants of uncertain significance' until more patients with a similar phenotype are discovered with the same variant.

WIDER IMPLICATIONS OF THE FINDINGS

We report the first WES-discovered FSHR mutation, validated by quantitative flow cytometry. WES is a valuable tool for diagnosis of rare genetic diseases, and flow cytometry allows for quantitative characterization of purported variants. WES-assisted diagnosis allows for treatments aimed at the underlying molecular etiology of disease. Future studies should focus on pharmacological and assisted reproductive treatments aimed at the disrupted FSHR, so that patients with FSH resistance can be treated by personalized medicine.

STUDY FUNDING/COMPETING INTERESTS

E.V. is partially funded by the DSD Translational Research Network (NICHD 1R01HD068138). M.S.B. is funded by the Neuroendocrinology, Sex Differences and Reproduction training grant (NICHD 5T32HD007228). The authors have no competing interests to disclose.

Expression analysis and characterization of an autosome-localized tesk1 gene in half-smooth tongue sole (Cynoglossus semilaevis)

Testis-specific protein kinase 1 (tesk1) represents a conserved gene family functioning in many cellular processes. In this study, we cloned and characterized an autosome-localized tesk1 gene (Altesk1) from Cynoglossus semilaevis. The open reading frame consists of 2088 nucleotides and encodes a 665 amino acid polypeptide. Phylogenetic analyses show that vertebrate Tesk1s are divided into two clusters based on protein length and AlTesk1 belongs to "long-type" group. Semi-quantitative PCR reveals that Altesk1 is predominantly expressed in ovary, despite of relatively low detection in some other tissues. Among different development stages, Altesk1 transcripts are only observed in ovary samples of 210-day and 1-year fish. In situ hybridization analyses have further confirmed its major localization in oocyte cells. Comparison of methylation patterns in different sexual genotypes reveals the low methylation level of Altesk1 promoter in female, which is consistent with Altesk1 high expression level in female. Taken together, this is the first time that tesk1 gene has been found to show female-biased expression and in view of this, we postulate that AlTesk1 might be involved in some cellular processes specific in ovary, e.g. oogenesis.

Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning

MOTIVATION

Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However, contact prediction is still challenging especially for proteins without a large number of sequence homologs.

RESULTS

This article presents a group graphical lasso (GGL) method for contact prediction that integrates joint multi-family EC analysis and supervised learning to improve accuracy on proteins without many sequence homologs. Different from existing single-family EC analysis that uses residue coevolution information in only the target protein family, our joint EC analysis uses residue coevolution in both the target family and its related families, which may have divergent sequences but similar folds. To implement this, we model a set of related protein families using Gaussian graphical models and then coestimate their parameters by maximum-likelihood, subject to the constraint that these parameters shall be similar to some degree. Our GGL method can also integrate supervised learning methods to further improve accuracy. Experiments show that our method outperforms existing methods on proteins without thousands of sequence homologs, and that our method performs better on both conserved and family-specific contacts.

AVAILABILITY AND IMPLEMENTATION

See http://raptorx.uchicago.edu/ContactMap/ for a web server implementing the method.

CONTACT

j3xu@ttic.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Computational tools for epitope vaccine design and evaluation

Rational approaches will be required to develop universal vaccines for viral pathogens such as human immunodeficiency virus, hepatitis C virus, and influenza, for which empirical approaches have failed. The main objective of a rational vaccine strategy is to design novel immunogens that are capable of inducing long-term protective immunity. In practice, this requires structure-based engineering of the target neutralizing epitopes and a quantitative readout of vaccine-induced immune responses. Therefore, computational tools that can facilitate these two areas have played increasingly important roles in rational vaccine design in recent years. Here we review the computational techniques developed for protein structure prediction and antibody repertoire analysis, and demonstrate how they can be applied to the design and evaluation of epitope vaccines.

Functional analysis of C1 family cysteine peptidases in the larval gut of Тenebrio molitor and Tribolium castaneum

BACKGROUND

Larvae of the tenebrionids Tenebrio molitor and Tribolium castaneum have highly compartmentalized guts, with primarily cysteine peptidases in the acidic anterior midgut that contribute to the early stages of protein digestion.

RESULTS

High throughput sequencing was used to quantify and characterize transcripts encoding cysteine peptidases from the C1 papain family in the gut of tenebrionid larvae. For T. castaneum, 25 genes and one questionable pseudogene encoding cysteine peptidases were identified, including 11 cathepsin L or L-like, 11 cathepsin B or B-like, and one each F, K, and O. The majority of transcript expression was from two cathepsin L genes on chromosome 10 (LOC659441 and LOC659502). For cathepsin B, the major expression was from genes on chromosome 3 (LOC663145 and LOC663117). Some transcripts were expressed at lower levels or not at all in the larval gut, including cathepsins F, K, and O. For T. molitor, there were 29 predicted cysteine peptidase genes, including 14 cathepsin L or L-like, 13 cathepsin B or B-like, and one each cathepsin O and F. One cathepsin L and one cathepsin B were also highly expressed, orthologous to those in T. castaneum. Peptidases lacking conservation in active site residues were identified in both insects, and sequence analysis of orthologs indicated that changes in these residues occurred prior to evolutionary divergence. Sequences from both insects have a high degree of variability in the substrate binding regions, consistent with the ability of these enzymes to degrade a variety of cereal seed storage proteins and inhibitors. Predicted cathepsin B peptidases from both insects included some with a shortened occluding loop without active site residues in the middle, apparently lacking exopeptidase activity and unique to tenebrionid insects. Docking of specific substrates with models of T. molitor cysteine peptidases indicated that some insect cathepsins B and L bind substrates with affinities similar to human cathepsin L, while others do not and have presumably different substrate specificity.

CONCLUSIONS

These studies have refined our model of protein digestion in the larval gut of tenebrionid insects, and suggest genes that may be targeted by inhibitors or RNA interference for the control of cereal pests in storage areas.

Investigating the role of the physiological isoform switch of cytochrome c oxidase subunits in reversible mitochondrial disease

Reversible infantile respiratory chain deficiency is characterised by spontaneous recovery of mitochondrial myopathy in infants. We studied whether a physiological isoform switch of nuclear cytochrome c oxidase subunits contributes to the age-dependent manifestation and spontaneous recovery in reversible mitochondrial disease. Some nuclear-encoded subunits of cytochrome c oxidase are present as tissue-specific isoforms. Isoforms of subunits COX6A and COX7A expressed in heart and skeletal muscle are different from isoforms expressed in the liver, kidney and brain. Furthermore, in skeletal muscle both the heart and liver isoforms of subunit COX7A have been demonstrated with variable levels, indicating that the tissue-specific expression of nuclear-encoded subunits could provide a basis for the fine-tuning of cytochrome c oxidase activity to the specific metabolic needs of the different tissues. We demonstrate a developmental isoform switch of COX6A and COX7A subunits in human and mouse skeletal muscle. While the liver type isoforms are more present soon after birth, the heart/muscle isoforms gradually increase around 3 months of age in infants, 4 weeks of age in mice, and these isoforms persist in muscle throughout life. Our data in follow-up biopsies of patients with reversible infantile respiratory chain deficiency indicate that the physiological isoform switch does not contribute to the clinical manifestation and to the spontaneous recovery of this disease. However, understanding developmental changes of the different cytochrome c oxidase isoforms may have implications for other mitochondrial diseases. This article is part of a Directed Issue entitled: Energy Metabolism Disorders and Therapies.

MRFy: Remote Homology Detection for Beta-Structural Proteins Using Markov Random Fields and Stochastic Search

We introduce MRFy, a tool for protein remote homology detection that captures beta-strand dependencies in the Markov random field. Over a set of 11 SCOP beta-structural superfamilies, MRFy shows a 14 percent improvement in mean Area Under the Curve for the motif recognition problem as compared to HMMER, 25 percent improvement as compared to RAPTOR, 14 percent improvement as compared to HHPred, and a 18 percent improvement as compared to CNFPred and RaptorX. MRFy was implemented in the Haskell functional programming language, and parallelizes well on multi-core systems. MRFy is available, as source code as well as an executable, from http://mrfy.cs.tufts.edu/.

CenH3 evolution in diploids and polyploids of three angiosperm genera

BACKGROUND

Centromeric DNA sequences alone are neither necessary nor sufficient for centromere specification. The centromere specific histone, CenH3, evolves rapidly in many species, perhaps as a coevolutionary response to rapidly evolving centromeric DNA. To gain insight into CenH3 evolution, we characterized patterns of nucleotide and protein diversity among diploids and allopolyploids within three diverse angiosperm genera, Brassica, Oryza, and Gossypium (cotton), with a focus on evidence for diversifying selection in the various domains of the CenH3 gene. In addition, we compare expression profiles and alternative splicing patterns for CenH3 in representatives of each genus.

RESULTS

All three genera retain both duplicated CenH3 copies, while Brassica and Gossypium exhibit pronounced homoeologous expression level bias. Comparisons among genera reveal shared and unique aspects of CenH3 evolution, variable levels of diversifying selection in different CenH3 domains, and that alternative splicing contributes significantly to CenH3 diversity.

CONCLUSIONS

Since the N terminus is subject to diversifying selection but the DNA binding domains do not appear to be, rapidly evolving centromere sequences are unlikely to be the primary driver of CenH3 sequence diversification. At present, the functional explanation for the diversity generated by both conventional protein evolution in the N terminal domain, as well as alternative splicing, remains unexplained.

An integrative computational approach for prioritization of genomic variants

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.

A new structural insight into XPA-DNA interactions

XPA (xeroderma pigmentosum group A) protein is an essential factor for NER (nucleotide excision repair) which is believed to be involved in DNA damage recognition/verification, NER factor recruiting and stabilization of repair intermediates. Past studies on the structure of XPA have focused primarily on XPA interaction with damaged DNA. However, how XPA interacts with other DNA structures remains unknown though recent evidence suggest that these structures could be important for its roles in both NER and non-NER activities. Previously, we reported that XPA recognizes undamaged DNA ds/ssDNA (double-strand/single-strandDNA) junctions with a binding affinity much higher than its ability to bind bulky DNA damage. To understand how this interaction occurs biochemically we implemented a structural determination of the interaction using a MS-based protein footprinting method and limited proteolysis. By monitoring surface accessibility of XPA lysines to NHS-biotin modification in the free protein and the DNA junction-bound complex we show that XPA physically interacts with the DNA junctions via two lysines, K168 and K179, located in the previously known XPA(98–219) DBD (DNA-binding domain). Importantly, we also uncovered new lysine residues, outside of the known DBD, involved in the binding. We found that residues K221, K222, K224 and K236 in the C-terminal domain are involved in DNA binding. Limited proteolysis analysis of XPA–DNA interactions further confirmed this observation. Structural modelling with these data suggests a clamp-like DBD for the XPA binding to ds/ssDNA junctions. Our results provide a novel structure-function view of XPA–DNA junction interactions.