iBio-GATS-A Semi-Automated Workflow for Structural Modelling of Insect Odorant Receptors.

Insects utilize seven transmembrane (7TM) odorant receptor (iOR) proteins, with an inverted topology compared to G-protein coupled receptors (GPCRs), to detect chemical cues in the environment. For pest biocontrol, chemical attractants are used to trap insect pests. However, with the influx of invasive insect pests, novel odorants are urgently needed, specifically designed to match 3D iOR structures. Experimental structural determination of these membrane receptors remains challenging and only four experimental iOR structures from two evolutionarily distant organisms have been solved. Template-based modelling (TBM) is a complementary approach, to generate model structures, selecting templates based on sequence identity. As the iOR family is highly divergent, a different template selection approach than sequence identity is needed. Bio-GATS template selection for GPCRs, based on hydrophobicity correspondence, has been morphed into iBio-GATS, for template selection from available experimental iOR structures. This easy-to-use semi-automated workflow has been extended to generate high-quality models from any iOR sequence from the selected template, using Python and shell scripting. This workflow was successfully validated on Apocrypta bakeri Orco and Machilis hrabei OR5 structures. iBio-GATS models generated for the fruit fly iOR, OR59b and Orco, yielded functional ligand binding results concordant with experimental mutagenesis findings, compared to AlphaFold2 models.

Mass spectrometry-based protein identification in proteomics-a review.

Statistically, accurate protein identification is a fundamental cornerstone of proteomics and underpins the understanding and application of this technology across all elements of medicine and biology. Proteomics, as a branch of biochemistry, has in recent years played a pivotal role in extending and developing the science of accurately identifying the biology and interactions of groups of proteins or proteomes. Proteomics has primarily used mass spectrometry (MS)-based techniques for identifying proteins, although other techniques including affinity-based identifications still play significant roles. Here, we outline the basics of MS to understand how data are generated and parameters used to inform computational tools used in protein identification. We then outline a comprehensive analysis of the bioinformatics and computational methodologies used in protein identification in proteomics including discussing the most current communally acceptable metrics to validate any identification.

Metaproteomic Analysis of an Oral Squamous Cell Carcinoma Dataset Suggests Diagnostic Potential of the Mycobiome.

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy, with an estimated 5-year survival rate of only 40-50%, largely due to late detection and diagnosis. Emerging evidence suggests that the human microbiome may be implicated in OSCC, with oral microbiome studies putatively identifying relevant bacterial species. As the impact of other microbial organisms, such as fungi and viruses, has largely been neglected, a bioinformatic approach utilizing the Trans-Proteomic Pipeline (TPP) and the R statistical programming language was implemented here to investigate not only bacteria, but also viruses and fungi in the context of a publicly available, OSCC, mass spectrometry (MS) dataset. Overall viral, bacterial, and fungal composition was inferred in control and OSCC patient tissue from protein data, with a range of proteins observed to be differentially enriched between healthy and OSCC conditions, of which the fungal protein profile presented as the best potential discriminator of OSCC within the analysed dataset. While the current project sheds new light on the fungal and viral spheres of the oral microbiome in cancer in silico, further research will be required to validate these findings in an experimental setting.

Proliferation and Apoptosis Pathways and Factors in Oral Squamous Cell Carcinoma.

Oral cancer is the most common form of head and neck squamous cell carcinoma (HNSCC) and most frequently presents as oral squamous cell carcinoma (OSCC), which is associated with an alarmingly high mortality rate. Internationally, a plethora of research to further our understanding of the molecular pathways related to oral cancer is performed. This research is of value for early diagnosis, prognosis, and the investigation of new drugs that can ameliorate the harmful effects of oral cancer and provide optimal patient outcomes with minimal long-term complications. Two pathways on which the progression of OSCC depends on are those of proliferation and apoptosis, which overlap at many junctions. Herein, we aim to review these pathways and factors related to OSCC progression. Publicly available search engines, PubMed and Google Scholar, were used with the following keywords to identify relevant literature: oral cancer, proliferation, proliferation factors, genes, mutations, and tumor suppressor. We anticipate that the use of information provided through this review will further progress translational cancer research work in the field of oral cancer.

Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1.

ML218 HCl Is More Efficient Than Capsaicin in Inhibiting Bacterial Antigen-Induced Cal 27 Oral Cancer Cell Proliferation.

The bacterial antigen, lipopolysaccharide (LPS) and disruptions in calcium channels are independently known to influence oral cancer progression. Previously, we found that bacterial antigens, LPS and lipoteichoic acid (LTA) act as confounders during the action of capsaicin on Cal 27 oral cancer proliferation. As calcium channel drugs may affect oral cancer cell proliferation, we investigated the effect of ML218 HCl, a T-type voltage-gated calcium channel blocker, on the proliferation of Cal 27 oral cancer cells. We hypothesized that ML218 HCl could effectively reduce LPS-induced oral cancer cell proliferation. LPS and LTA antigens were added to Cal 27 oral cancer cells either prior to and/or concurrently with ML218 HCl treatment, and the efficacy of the treatment was evaluated by measuring Cal 27 proliferation, cell death and apoptosis. ML218 HCl inhibited oral cancer cell proliferation, increased apoptosis and cell death, but their efficacy was significantly reduced in the presence of bacterial antigens. ML218 HCl proved more effective than capsaicin in reducing bacterial antigen-induced Cal 27 oral cancer cell proliferation. Our results also suggest an interplay of proliferation factors during the bacterial antigens and calcium channel drug interaction in Cal 27. Bacterial antigen reduction of drug efficacy should be considered for developing newer pharmacological agents or testing the efficacy of the existing oral cancer chemotherapeutic agents. Finally, voltage gated calcium channel drugs should be considered for future oral cancer research.

Bacterial Antigens Reduced the Inhibition Effect of Capsaicin on Cal 27 Oral Cancer Cell Proliferation.

Oral cancer is a major global health problem with high incidence and low survival rates. The oral cavity contains biofilms as dental plaques that harbour both Gram-negative and Gram-positive bacterial antigens, lipopolysaccharide (LPS) and lipoteichoic acid (LTA), respectively. LPS and LTA are known to stimulate cancer cell growth, and the bioactive phytochemical capsaicin has been reported to reverse this effect. Here, we tested the efficacy of oral cancer chemotherapy treatment with capsaicin in the presence of LPS, LTA or the combination of both antigens. LPS and LTA were administered to Cal 27 oral cancer cells prior to and/or concurrently with capsaicin, and the treatment efficacy was evaluated by measuring cell proliferation and apoptotic cell death. We found that while capsaicin inhibits oral cancer cell proliferation and metabolism (MT Glo assay) and increases cell death (Trypan blue exclusion assay and Caspase 3/7 expression), its anti-cancer effect was significantly reduced on cells that are either primed or exposed to the bacterial antigens. Capsaicin treatment significantly increased oral cancer cells' suppressor of cytokine signalling 3 gene expression. This increase was reversed in the presence of bacterial antigens during treatment. Our data establish a rationale for clinical consideration of bacterial antigens that may interfere with the treatment efficacy of oral cancer.

iSwathX: an interactive web-based application for extension of DIA peptide reference libraries.

Summary: Large-scale peptide mass spectrometry (MS)/MS reference libraries are essential for the comprehensive analysis of data-independent acquisition (DIA) MS datasets, providing a comprehensive set of spectra for identification and quantification of proteins. We have developed a novel web-based R-package (iSwathX) for combining reference libraries that is compatible with different DIA analysis software. This open-source web GUI automates the process of normalization and combination of spectral libraries and provides a user-friendly method for performing library format conversions, analysis and visualizations, with no need for programing familiarity. Availability and implementation: iSwathX is freely accessible at https://biolinfo.shinyapps.io/iSwathX with the R-package and Shiny source code available from GitHub (https://github.com/znoor/iSwathX). Supplementary information: Supplementary data are available at Bioinformatics online.

Diverse dynamics features of novel protein kinase C (PKC) isozymes determine the selectivity of a fluorinated balanol analogue for PKCε.

BACKGROUND: (-)-Balanol is an ATP-mimicking inhibitor that non-selectively targets protein kinase C (PKC) isozymes and cAMP-dependent protein kinase (PKA). While PKA constantly shows tumor promoting activities, PKC isozymes can ambiguously be tumor promoters or suppressors. In particular, PKCε is frequently implicated in tumorigenesis and a potential target for anticancer drugs. We recently reported that the C5(S)-fluorinated balanol analogue (balanoid 1c) had improved binding affinity and selectivity for PKCε but not to the other novel PKC isozymes, which share a highly similar ATP site. The underlying basis for this fluorine-based selectivity is not entirely comprehended and needs to be investigated further for the development of ATP mimic inhibitors specific for PKCε. RESULTS: Using molecular dynamics (MD) simulations assisted by homology modelling and sequence analysis, we have studied the fluorine-based selectivity in the highly similar ATP sites of novel PKC (nPKC) isozymes. The study suggests that every nPKC isozyme has different dynamics behaviour in both apo and 1c-bound forms. Interestingly, the apo form of PKCε, where 1c binds strongly, shows the highest degree of flexibility which dramatically decreases after binding 1c. CONCLUSIONS: For the first time to the best of our knowledge, we found that the origin of 1c selectivity for PKCε comes from the unique dynamics feature of each PKC isozyme. Fluorine conformational control in 1c can synergize with and lock down the dynamics of PKCε, which optimize binding interactions with the ATP site residues of the enzyme, particularly the invariant Lys437. This finding has implications for further rational design of balanol-based PKCε inhibitors for cancer drug development.

APBioNet's annual International Conference on Bioinformatics (InCoB) returns to India in 2018.

InCoB, one of the largest annual bioinformatics conferences in the Asia-Pacific region since its launch in 2002, returned to New Delhi, India after 12 years, with a conference attendance of 314 delegates. The 2018 conference had sessions on Big Data and Algorithms, Next Generation Sequencing and Omics Science, Structure, Function and Interactions, Disease and Drug Discovery and Plant and Agricultural Bioinformatics. The conference also featured an industry track as well as panel discussions on Women in Bioinformatics and Democratization vs. Quality control in academic publishing. Asia Pacific Bioinformatics Interaction & Networking Society (APbians) was launched as an APBionet Special Interest Group. Of the 52 oral presentations made, 22 were accepted in supplemental issues of BMC Bioinformatics, BMC Genomics or BMC Medical Genomics and are briefly reviewed here. Next year's InCoB will be held in Jakarta, Indonesia from September 10-12, 2019.

A bioinformatics potpourri.

The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018.

Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses.

BACKGROUND: Influenza viruses are undergoing continuous and rapid evolution. The fatal influenza A/H7N9 has drawn attention since the first wave of infections in March 2013, and raised more grave concerns with its increased potential to spread among humans. Experimental studies have revealed several host and virulence markers, indicating differential host binding preferences which can help estimate the potential of causing a pandemic. Here we systematically investigate the sequence pattern and structural characteristics of novel influenza A/H7N9 using computational approaches. RESULTS: The sequence analysis highlighted mutations in protein functional domains of influenza viruses. Molecular docking and molecular dynamics simulation revealed that the hemagglutinin (HA) of A/Taiwan/1/2017(H7N9) strain enhanced the binding with both avian and human receptor analogs, compared with the previous A/Shanghai/02/2013(H7N9) strain. The Molecular Mechanics - Poisson Boltzmann Surface Area (MM-PBSA) calculation revealed the change of residue-ligand interaction energy and detected the residues with conspicuous binding preference. CONCLUSION: The results are novel and specific to the emerging influenza A/Taiwan/1/2017(H7N9) strain compared with A/Shanghai/02/2013(H7N9). Its enhanced ability to bind human receptor analogs, which are abundant in the human upper respiratory tract, may be responsible for the recent outbreak. Residues showing binding preference were detected, which could facilitate monitoring the circulating influenza viruses.

Molecular Dynamics Pinpoint the Global Fluorine Effect in Balanoid Binding to PKCε and PKA.

(-)-Balanol is an adenosine triphosphate mimic that inhibits protein kinase C (PKC) isozymes and cAMP-dependent protein kinase (PKA) with limited selectivity. While PKA is known as a tumor promoter, PKC isozymes can be tumor promoters or suppressors. In particular, PKCε is frequently involved in tumorigenesis and a potential target for anticancer drugs. We recently reported that stereospecific fluorination of balanol yielded a balanoid with enhanced selectivity for PKCε over other PKC isozymes and PKA, although the global fluorine effect behind the selectivity enhancement is not fully understood. Interestingly, in contrast to PKA, PKCε is more sensitive to this fluorine effect. Here we investigate the global fluorine effect on the different binding responses of PKCε and PKA to balanoids using molecular dynamics (MD) simulations. For the first time to the best of our knowledge, we found that a structurally equivalent residue in each kinase, Thr184 in PKA and Ala549 in PKCε, is essential for the different binding responses. Furthermore, the study revealed that the invariant Lys, Lys73 in PKA and Lys437 in PKCε, already known to have a crucial role in the catalytic activity of kinases, serves as the main anchor for balanol binding. Overall, while Thr184 in PKA attenuates the effect of fluorination, Ala549 permits remote response of PKCε to fluorine substitution, with implications for rational design of future balanol-based PKCε inhibitors.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools.

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Exploration of charge states of balanol analogues acting as ATP-competitive inhibitors in kinases.

BACKGROUND: (-)-Balanol is an ATP mimic that inhibits protein kinase C (PKC) isozymes and cAMP-dependent protein kinase (PKA) with limited selectivity. While PKA is a tumour promoter, PKC isozymes act as tumour promoters or suppressors, depending on the cancer type. In particular, PKCε is frequently implicated in cancer promotion, making it a potential target for anticancer drugs. To improve isozyme selectivity of balanol, exhaustive structural and activity relationship (SAR) studies have been performed in the last two decades, but with limited success. More recently, fluorination on balanol has shown improved selectivity for PKCε, although the fluorine effect is not yet clearly understood. Understanding the origin to this fluorine-based selectivity will be valuable for designing better balanol-based ATP mimicking inhibitors. Computational approaches such as molecular dynamics (MD) simulations can decipher the fluorine effect, provided that correct charges have been assigned to a ligand. Balanol analogues have multiple ionisable functional groups and the effect of fluorine substitutions on the exact charge state of each analogue bound to PKA and to PKCε needs to be thoroughly investigated in order to design highly selective inhibitors for therapeutic applications. RESULTS: We explored the charge states of novel fluorinated balanol analogues using MD simulations. For different potential charge states of these analogues, Molecular Mechanics Generalized Born Surface Area (MMGBSA) binding energy values were computed. This study suggests that balanol and the most potent fluorinated analogue (5S fluorine substitution on the azepane ring), have charges on the azepane ring (N1), and the phenolic (C6''OH) and the carboxylate (C15''O2H) groups on the benzophenone moiety, when bound to PKCε as well as PKA. CONCLUSIONS: To the best our knowledge, this is the first study showing that the phenolate group is charged in balanol and its analogues binding to the ATP site of PKCε. Correct charge assignments of ligands are important to obtain predicted binding energy values from MD simulations that reflect experimental values. Both fluorination and the local enzymatic environment of the ATP site can influence the exact charge states of balanol analogues. Overall, this study is highly valuable for further rational design of potent balanol analogues selective to PKCε.

Human Prestin: A Candidate PE1 Protein Lacking Stringent Mass Spectrometric Evidence?

The evidence that any protein exists in the Human Proteome Project (HPP; protein evidence 1 or PE1) has revolved primarily (although not exclusively) around mass spectrometry (MS) (93% of PE1 proteins have MS evidence in the latest neXtProt release), with robust and stringent, well-curated metrics that have served the community well. This has led to a significant number of proteins still considered "missing" (i.e., PE2-4). Many PE2-4 proteins have MS evidence of unacceptable quality (small or not enough unitypic peptides and unacceptably high protein/peptide FDRs), transcriptomic, or antibody evidence. Here we use a Chromosome 7 PE2 example called Prestin to demonstrate that clear and robust criteria/metrics need to be developed for proteins that may not or cannot produce clear-cut MS evidence while possessing significant non-MS evidence, including disease-association data. Many of the PE2-4 proteins are inaccessible, spatiotemporally expressed in a limited way, or expressed at such a very low copy number as to be unable to be detected by current MS methodologies. We propose that the HPP community consider and lead a communal initiative to accelerate the discovery and characterization of these types of "missing" proteins.

Prediction of interface residue based on the features of residue interaction network.

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model.

Divergent response of homologous ATP sites to stereospecific ligand fluorination for selectivity enhancement.

Acquiring a divergent response from homologous protein domains is essential for selective ligand-protein interactions. Stereospecific fluorination of (-)-balanol, an ATP mimic, uncovers a new source of selectivity from integrated chemical and conformational perturbation that differentiates homologous sites by the level of congruency in their response to local and remote fluorine effects.

Ascaris suum draft genome.

Parasitic diseases have a devastating, long-term impact on human health, welfare and food production worldwide. More than two billion people are infected with geohelminths, including the roundworms Ascaris (common roundworm), Necator and Ancylostoma (hookworms), and Trichuris (whipworm), mainly in developing or impoverished nations of Asia, Africa and Latin America. In humans, the diseases caused by these parasites result in about 135,000 deaths annually, with a global burden comparable with that of malaria or tuberculosis in disability-adjusted life years. Ascaris alone infects around 1.2 billion people and, in children, causes nutritional deficiency, impaired physical and cognitive development and, in severe cases, death. Ascaris also causes major production losses in pigs owing to reduced growth, failure to thrive and mortality. The Ascaris-swine model makes it possible to study the parasite, its relationship with the host, and ascariasis at the molecular level. To enable such molecular studies, we report the 273 megabase draft genome of Ascaris suum and compare it with other nematode genomes. This genome has low repeat content (4.4%) and encodes about 18,500 protein-coding genes. Notably, the A. suum secretome (about 750 molecules) is rich in peptidases linked to the penetration and degradation of host tissues, and an assemblage of molecules likely to modulate or evade host immune responses. This genome provides a comprehensive resource to the scientific community and underpins the development of new and urgently needed interventions (drugs, vaccines and diagnostic tests) against ascariasis and other nematodiases.

Bioinformatics and systems biology research update from the 15th International Conference on Bioinformatics (InCoB2016).

The International Conference on Bioinformatics (InCoB) has been publishing peer-reviewed conference papers in BMC Bioinformatics since 2006. Of the 44 articles accepted for publication in supplement issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics and BMC Systems Biology, 24 articles with a bioinformatics or systems biology focus are reviewed in this editorial. InCoB2017 is scheduled to be held in Shenzen, China, September 20-22, 2017.