Advanced Situation with Recombinant Toxins: Diversity, Production and Application Purposes

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Abstract

Today, the production and use of various samples of recombinant protein/polypeptide toxins is known and is actively developing. This review presents state-of-the-art in research and development of such toxins and their mechanisms of action and useful properties that have allowed them to be implemented into practice to treat various medical conditions (including oncology and chronic inflammation applications) and diseases, as well as to identify novel compounds and to detoxify them by diverse approaches (including enzyme antidotes). Special attention is given to the problems and possibilities of the toxicity control of the obtained recombinant proteins. The recombinant prions are discussed in the frame of their possible detoxification by enzymes. The review discusses the feasibility of obtaining recombinant variants of toxins in the form of protein molecules modified with fluorescent proteins, affine sequences and genetic mutations, allowing us to investigate the mechanisms of toxins’ bindings to their natural receptors.

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Gene Ontology Consortium: going forward

emmanuel boutet, Jurg Bahler, Claire O'Donovan (2015)

The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology.

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In Silico Approach for Predicting Toxicity of Peptides and Proteins

Sudheer Gupta, Pallavi Kapoor, Kumardeep Chaudhary … (2013)

Background Over the past few decades, scientific research has been focused on developing peptide/protein-based therapies to treat various diseases. With the several advantages over small molecules, including high specificity, high penetration, ease of manufacturing, peptides have emerged as promising therapeutic molecules against many diseases. However, one of the bottlenecks in peptide/protein-based therapy is their toxicity. Therefore, in the present study, we developed in silico models for predicting toxicity of peptides and proteins. Description We obtained toxic peptides having 35 or fewer residues from various databases for developing prediction models. Non-toxic or random peptides were obtained from SwissProt and TrEMBL. It was observed that certain residues like Cys, His, Asn, and Pro are abundant as well as preferred at various positions in toxic peptides. We developed models based on machine learning technique and quantitative matrix using various properties of peptides for predicting toxicity of peptides. The performance of dipeptide-based model in terms of accuracy was 94.50% with MCC 0.88. In addition, various motifs were extracted from the toxic peptides and this information was combined with dipeptide-based model for developing a hybrid model. In order to evaluate the over-optimization of the best model based on dipeptide composition, we evaluated its performance on independent datasets and achieved accuracy around 90%. Based on above study, a web server, ToxinPred has been developed, which would be helpful in predicting (i) toxicity or non-toxicity of peptides, (ii) minimum mutations in peptides for increasing or decreasing their toxicity, and (iii) toxic regions in proteins. Conclusion ToxinPred is a unique in silico method of its kind, which will be useful in predicting toxicity of peptides/proteins. In addition, it will be useful in designing least toxic peptides and discovering toxic regions in proteins. We hope that the development of ToxinPred will provide momentum to peptide/protein-based drug discovery (http://crdd.osdd.net/raghava/toxinpred/).

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The role of vaccines in combatting antimicrobial resistance

Francesca Micoli, Fabio Bagnoli, Rino Rappuoli … (2021)

The use of antibiotics has enabled the successful treatment of bacterial infections, saving the lives and improving the health of many patients worldwide. However, the emergence and spread of antimicrobial resistance (AMR) has been highlighted as a global threat by different health organizations, and pathogens resistant to antimicrobials cause substantial morbidity and death. As resistance to multiple drugs increases, novel and effective therapies as well as prevention strategies are needed. In this Review, we discuss evidence that vaccines can have a major role in fighting AMR. Vaccines are used prophylactically, decreasing the number of infectious disease cases, and thus antibiotic use and the emergence and spread of AMR. We also describe the current state of development of vaccines against resistant bacterial pathogens that cause a substantial disease burden both in high-income countries and in low- and medium-income countries, discuss possible obstacles that hinder progress in vaccine development and speculate on the impact of next-generation vaccines against bacterial infectious diseases on AMR.

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Elena Efremenko: (View ORCID Profile)

Aysel Aslanli: (View ORCID Profile)

Ilya Lyagin: (View ORCID Profile)

Journal

Journal ID (publisher-id): IJMCFK

Title: International Journal of Molecular Sciences

Abbreviated Title: IJMS

Publisher: MDPI AG

ISSN (Electronic): 1422-0067

Publication date Created: March 2023

Publication date (Electronic): February 27 2023

Volume: 24

Issue: 5

Page: 4630

Article

DOI: 10.3390/ijms24054630

SO-VID: c12d2202-6c83-45dd-84e2-3792f1c7c181

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https://creativecommons.org/licenses/by/4.0/

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Advanced Situation with Recombinant Toxins: Diversity, Production and Application Purposes

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International Journal of Applied Technology in Medical Sciences

Most cited references 130

Gene Ontology Consortium: going forward

In Silico Approach for Predicting Toxicity of Peptides and Proteins

The role of vaccines in combatting antimicrobial resistance

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