Prediction of neurotoxins based on their function and source

We have developed a method NTXpred for predicting neurotoxins and classifying them based on their function and origin. The dataset used in this study consists of 582 non-redundant, experimentally annotated neurotoxins obtained from Swiss-Prot. A number of modules have been developed for predicting neurotoxins using residue composition based on feed-forwarded neural network (FNN), recurrent neural network (RNN), support vector machine (SVM) and achieved maximum accuracy of 84.19%, 92.75%, 97.72% respectively. In addition, SVM modules have been developed for classifying neurotoxins based on their source (e.g., eubacteria, cnidarians, molluscs, arthropods have been and chordate) using amino acid composition and dipeptide composition and achieved maximum overall accuracy of 78.94% and 88.07% respectively. The overall accuracy increased to 92.10%, when the evolutionary information obtained from PSI-BLAST was combined with SVM module of source classification. We have also developed SVM modules for classifying neurotoxins based on functions using amino acid, dipeptide composition and achieved overall accuracy of 83.11%, 91.10% respectively. The overall accuracy of function classification improved to 95.11%, when PSI-BLAST output was combined with SVM module. All the modules developed in this study were evaluated using five-fold cross-validation technique. The NTXpred is available at www.imtech.res.in/raghava/ntxpred/ and mirror site at http://bioinformatics.uams.edu/mirror/ntxpred

Structural Analysis and Deletion Mutagenesis Define Regions of QUIVER/SLEEPLESS that Are Responsible for Interactions with Shaker-Type Potassium Channels and Nicotinic Acetylcholine Receptors.

Ly6 proteins are endogenous prototoxins found in most animals. They show striking structural and functional parallels to snake α-neurotoxins, including regulation of ion channels and cholinergic signaling. However, the structural contributions of Ly6 proteins to regulation of effector molecules is poorly understood. This question is particularly relevant to the Ly6 protein QUIVER/SLEEPLESS (QVR/SSS), which has previously been shown to suppress excitability and synaptic transmission by upregulating potassium (K) channels and downregulating nicotinic acetylcholine receptors (nAChRs) in wake-promoting neurons to facilitate sleep in Drosophila. Using deletion mutagenesis, co-immunoprecipitations, ion flux assays, surface labeling and confocal microscopy, we demonstrate that only loop 2 is required for many of the previously described properties of SSS in transfected cells, including interactions with K channels and nAChRs. Collectively our data suggest that QVR/SSS, and by extension perhaps other Ly6 proteins, target effector molecules using limited protein motifs. Mapping these motifs may be useful in rational design of drugs that mimic or suppress Ly6-effector interactions to modulate nervous system function

BTXpred: prediction of bacterial toxins

This paper describes a method developed for predicting bacterial toxins from their amino acid sequences. All the modules, developed in this study, were trained and tested on a non-redundant dataset of 150 bacterial toxins that included 77 exotoxins and 73 endotoxins. Firstly, support vector machines (SVM) based modules were developed for predicting the bacterial toxins using amino acids and dipeptides composition and achieved an accuracy of 96.07% and 92.50%, respectively. Secondly, SVM based modules were developed for discriminating entotoxins and exotoxins, using amino acids and dipeptides composition and achieved an accuracy of 95.71% and 92.86%, respectively. In addition, modules have been developed for classifying the exotoxins (e.g. activate adenylate cyclase, activate guanylate cyclase, neurotoxins) using hidden Markov models (HMM), PSI-BLAST and a combination of the two and achieved overall accuracy of 95.75%, 97.87% and 100%, respectively. Based on the above study, a web server called 'BTXpred' has been developed, which is available at http://www.imtech.res.in/raghava/btxpred/. Supplementary information is available at http://www.imtech.res.in/raghava/btxpred/supplementary.html

Predicting function from sequence in a large multifunctional toxin family

Venoms contain active substances with highly specific physiological effects and are increasingly being used as sources of novel diagnostic, research and treatment tools for human disease. Experimental characterisation of individual toxin activities is a severe rate-limiting step in the discovery process, and in-silico tools which allow function to be predicted from sequence information are essential. Toxins are typically members of large multifunctional families of structurally similar proteins that can have different biological activities, and minor sequence divergence can have significant consequences. Thus, existing predictive tools tend to have low accuracy. We investigated a classification model based on physico-chemical attributes that can easily be calculated from amino-acid sequences, using over 250 (mostly novel) viperid phospholipase A2 toxins. We also clustered proteins by sequence profiles, and carried out in-vitro tests for four major activities on a selection of isolated novel toxins, or crude venoms known to contain them. The majority of detected activities were consistent with predictions, in contrast to poor performance of a number of tested existing predictive methods. Our results provide a framework for comparison of active sites among different functional sub-groups of toxins that will allow a more targeted approach for identification of potential drug leads in the future

Bacterial Toxins and Their Modes of Action: A Review Article

Bacterial toxins; the soluble antigens, emitted by various pathogenic microorganisms has a standing notoriety of being a toxin discharged over the span of pathogenesis. Toxins can balance the cell capacities by specifically focusing on various flagging pathways inside the host cell so as to tilt the equalization in microorganisms support. With the upgraded comprehension of the poison refinements strategies, quality cloning, protein arrangements, and three-dimensional crystallographic structures today, we can appreciate the interesting conduct of toxins, for example, restricting capacity to the explicit target cell and a few chemicals capacities. Bacterial pathogens have been causing different infections in people for quite a long time and even today these pathogenic microscopic organisms are coinciding and developing with us, regardless of having diverse means for their control in clinical practices (specifically antimicrobials, immunizations, and phage treatment). Toxins can be grouped into two general classes: exotoxin and endotoxin, and can be delivered by both Gram-positive and Gram-negative microbes. Exotoxins delivered by various microorganisms like botulinum, Clostridium, diphtheria poisons displaying protein exercises like ADP-ribosylation, phospholipase, adenylate cyclase, metalloprotease, deamidase, protease, and deoxyribonuclease action. The vast majority of these microscopic organisms apply their impeding impacts in the contaminated host through toxins. The elucidation of the cellular mechanism of action of the bacterial exotoxins remains a complex problem, but they appear to share a common mechanism of action such as binding to specific receptors on the plasma membranes of the sensitive cells, pore-formation, internalization or translocation across the membrane barrier and direct secretion. Keywords: Bacterial toxins; toxin; bacteria DOI: 10.7176/JMPB/55-03 Publication date:May 31st 201

Four small puzzles that Rosetta doesn't solve

A complete macromolecule modeling package must be able to solve the simplest structure prediction problems. Despite recent successes in high resolution structure modeling and design, the Rosetta software suite fares poorly on deceptively small protein and RNA puzzles, some as small as four residues. To illustrate these problems, this manuscript presents extensive Rosetta results for four well-defined test cases: the 20-residue mini-protein Trp cage, an even smaller disulfide-stabilized conotoxin, the reactive loop of a serine protease inhibitor, and a UUCG RNA tetraloop. In contrast to previous Rosetta studies, several lines of evidence indicate that conformational sampling is not the major bottleneck in modeling these small systems. Instead, approximations and omissions in the Rosetta all-atom energy function currently preclude discriminating experimentally observed conformations from de novo models at atomic resolution. These molecular "puzzles" should serve as useful model systems for developers wishing to make foundational improvements to this powerful modeling suite.Comment: Published in PLoS One as a manuscript for the RosettaCon 2010 Special Collectio

Literature search – Exploring in silico protein toxicity prediction methods to support the food and feed risk assessment

This report is the outcome of an EFSA procurement (NP/EFSA/GMO/2018/01) reviewing relevant scientific information on in silico prediction methods for protein toxicity, that could support the food and feed risk assessment. Several proteins are associated with adverse (toxic) effects in humans and animals, by a variety of mechanisms. These are produced by plants, animals and bacteria to prevail in hostile environments. In the present report, we present an integrated pipeline to perform a comprehensive literature and database search applied to proteins with toxic effects. \u201cToxin activity\u201d and \u201ctoxin-antitoxin system\u201d strings were used as inputs for this pipeline. UniProtKB was considered as the reference database, and only the UniProtKB curator-reviewed proteins were considered in the pipeline. Experimentally- determined structures and homology-based in silico 3D models were retrieved from protein structures repositories; family-, domain-, motif- and other molecular signature-related information was also obtained from specific databases which are part of the InterPro consortium. Protein aggregation associated with adverse effects was also investigated using different search strategies. This work can serve as the basis for further exploring novel risk assessment strategies for new proteins using in silico predictive methods

Regulation of botulinum toxin complex formation in <i>Clostridium botulinum</i> type A NCTC 2916

Genomic DNA fragments encoding the silent type B neurotoxin gene from Clostridium botulinum NCTC 2916 have been cloned and the complete nucleotide sequence determined. The translated sequence revealed that the gene encoded a neurotoxin which was closely related to type B neurotoxin genes from Group I Clostridium botulinum. However among the nucleotide sequence differences, aG to T transition has interrupted the coding sequence with the formation of a stop codon. In addition the deletion of an adenine residue has resulted in a frame-shift mutation. Analysis of the DNA sequence contiguous with the silent type B neurotoxin gene revealed the presence of a gene encoding a Nontoxic-Nonhaemagglutinin protein which appears to share a bicistronic mRNA transcript with the type B neurotoxin gene. In the reverse orientation, the partial sequence of a gene encoding a haemagglutinin protein was found, typical of type A and B botulinal neurotoxin complexes. Separating the genes encoding the 'components of the neurotoxin complex was a gene of 178 amino acids which possessed features commonly associated with transcriptional factors. To facilitate the in vivo study of botulinal neurotoxin complex regulation, a gene transfer system using clostridial components has been developed. The minimal replicon of the cryptic plasmid pCB 102 from Clostridium butyricum NCIB 7423 was located to 1.6 kb DNA fragment by deletion analysis, enabling the identification of hitherto undiscovered putative ORFs and secondary structures, consistent with a replicative function. The replicon has been incorporated in to a number of Escherichia coli vectors resulting in a versatile series of shuttle vectors which have demonstrated high structural and segregational stabilities in a heterologous host Clostridium beyerinckii NCI NIB 8052. Gene transfer of a Group I Clostridium botulinum type A strain was demonstrated with a representative pCB 102-derived shuttle vector, pMTL540E. In addition, a 5.9 kb plasmid indigenous to C. botulimun NCTC 2916 was cloned and the complete nucleotide sequence determined. Eight putative ORFs have been identified, including a putative replication protein and recombinase

On botulinum neurotoxin variability

The rapidly growing number of botulinum neurotoxin sequences poses the problem of the possible evolutionary significance of the variability of these superpotent neurotoxins for toxin-producing Clostridium species. To progress in the understanding of this remarkable phenomenon, we suggest that researchers should (i) abandon an anthropocentric view of these neurotoxins as human botulism-causing agents or as human therapeutics, (ii) begin to investigate in depth the role of botulinum neurotoxins in animal botulism in the wilderness, and (iii) devote large efforts to next-generation sequencing of soil samples to identify novel botulinum neurotoxins. In order to compare the fitness of the different toxins, we suggest that assays of all the steps from toxin production to animal death should be performed