Ebola Virus Potential Drug Targets and Prospects for Small Molecule Drug Discovery

2014 ◽  
Vol 1 (4) ◽  
pp. 313-321
Author(s):  
Haregewein Assefa
2020 ◽  
Author(s):  
Qiao Liu ◽  
Bohyun Lee ◽  
Lei Xie

AbstractAn increasing body of evidence suggests that microbes are not only strongly associated with many human diseases but also responsible for the efficacy, resistance, and toxicity of drugs. Small-molecule drugs which can precisely fine-tune the microbial ecosystem on the basis of individual patients may revolutionize biomedicine. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. It is often insufficient and less successful in tackling complex systematic diseases. A systematic pharmacology approach that intervenes multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution. Advances in the Human Microbiome Project have provided numerous genomics data to study microbial interactions in the complex microbiome community. Integrating microbiome data with chemical genomics and other biological information enables us to delineate the landscape for the small molecule modulation of the human microbiome network. In this paper, we construct a disease-centric signed microbe-microbe interaction network using metabolite information of microbes and curated microbe effects on human health from published work. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of pathogenic and commensal species. With a survey on the druggable and evolutionary space of microbe proteins, we find that 8-10% of them can be targeted by existing drugs or drug-like chemicals and that 25% of them have homologs to human proteins. We also demonstrate that drugs for diabetes are enriched in the potential inhibitors that target pathogenic microbe without affecting the commensal microbe, thus can be repurposed to modulate the microbiome ecosystem. We further show that periplasmic and cellular outer membrane proteins are overrepresented in the potential drug targets set in pathogenic microbe, but not in the commensal microbe. The systematic studies of polypharmacological landscape of the microbiome network may open a new avenue for the small-molecule drug discovery of microbiome.Author SummaryAs one of the most abundant components in human bodies, the microbiome has an extensive impact on human health. Pathogenic-microbes have become emerging potential therapeutic targets. Small-molecule drugs that only intervene in the growth of a specific pathogenic microbe without considering the interacting dynamics of the microbiome community may disrupt the ecosystem homeostasis, thus can cause drug side effect or prompt drug resistance. To discover novel drugs for safe and effective microbe-targeting therapeutics, a systematic approach is needed to fine-tune the microbiome ecosystem. To this end, we built a disease-centric signed microbe-microbe interaction network which accurately predicts the pathogenic or commensal effect of microbe on human health. Based on annotated and predicted pathogens and commensal species, we performed a systematic survey on therapeutic space and target landscape of existing drugs for modulating the microbiome ecosystem. Enrichment analysis on potential microbe-targeting drugs shows that drugs for diabetes could be repurposed to maintain the healthy state of microbiome. Furthermore, periplasmic and cellular outer membrane proteins are overrepresented in the potential drug targets of pathogenic-microbes, but not in proteins that perturb commensal-microbes. Our study may open a new avenue for the small molecule drug discovery of microbiome.


2020 ◽  
Vol 980 ◽  
pp. 210-219
Author(s):  
Xian Zhi Ye

Target fishing, a cutting-edge technology for drug research and development, plays a significant role in drug discovery. Varieties of methods for finding small-molecule drug targets have come into being driven by genomics, proteomics, bioinformatics and other technologies. These new methods are mainly based on the expression of gene or protein and proteins properties, including affinity and stability and so on. A serious challenge for the most widely used small molecule drugs is the discovery and identification of biological (and potential therapeutic) targets. Herein, we enumerate five biological target fishing techniques, including surface plasma resonance (SPR) techniques, random photo modified probes, drug affinity responsive target stability, fishing-rod strategy, and photo affinity labeling. And then we introduces the principles of operation, practical applications in the biological field of five methods, and analysis of their shortcomings.


2002 ◽  
Vol 4 (4) ◽  
pp. 336-341

Although many new potential drug targets have been discovered subsequent to the cloning of the human genome and the discovery of most of the relevant receptors, the role of these receptors in psychiatric disease is still not clear. We argue that research into the disease process leading to new animal models that can be transposed to man is critical to drug discovery, and present an example of an animal model for schizophrenia using electroencephalography.


2003 ◽  
Vol 25 (6) ◽  
pp. 19-21
Author(s):  
Michael Ginger

New drugs are needed urgently to win the war against parasites that cause many serious diseases that are endemic or resurgent in some of the World's poorest countries. Post-genomic technologies provide a powerful resource that can be exploited during the drug-discovery process. With genome sequencers able to uncover secrets from even the most experimentally intractable of pathogens, the complete and annotated genomes from a number of the most medically important parasites are now, or will soon be, published. Already, the information that has been released from these projects has been put to good use in identifying new potential drug targets.


2019 ◽  
Vol 24 (5) ◽  
pp. 505-514 ◽  
Author(s):  
David H. Drewry ◽  
Carrow I. Wells ◽  
William J. Zuercher ◽  
Timothy M. Willson

Although the human genome provides the blueprint for life, most of the proteins it encodes remain poorly studied. This perspective describes how one group of scientists, in seeking new targets for drug discovery, used open science through unrestricted sharing of small molecules to shed light on dark matter of the genome. Starting initially with a single pharmaceutical company before expanding to multiple companies, a precedent was established for sharing published kinase inhibitors as chemical tools. The integration of open science and kinase chemogenomics has supported the study of many new potential drug targets by the scientific community.


2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Mahantesh M. Kurjogi ◽  
Basappa B. Kaliwal

The purpose of this study is to deal with aetiology causing bovine mastitis; bovine herpes virus is also responsible for causing bovine mastitis but studies on viruses have been neglected as historical mastitis research has concentrated only on bacterial pathogens. Therefore, present study aims to make an in silico identification and characterization of potential drug targets in bovine herpes virus 4 by computational methods using various bioinformatics tools. In the current investigation 5 proteins of BoHV 4 were found to be nonhomologous to the host Bos taurus; these nonhomology proteins were believed to be inevitable proteins of BoHV 4 as they were specific to the virus; however 378 proteins were homologous to the host protein. The in silico physicochemical characterization of 5 proteins of BoHV 4 indicated that all the proteins of the virus were having more or less similar characteristics. Perhaps the knowledge of the present study may help in drug discovery which have high affinity to target site. Possible drug discovery to manage bovine mastitis with a help of bioinformatics tool is more significant and, specific and, reduces time and complications involved in clinical trials.


2020 ◽  
Vol 9 (04) ◽  
pp. 24989-24993
Author(s):  
Akula Chandra Sekhar ◽  
Ch. Ambedkar

Protein-Protein Interactions (PPI) have important role in drug binding with the Proteins called drug targets. For identifying the potential drug targets there are different techniques. In this paper we are presenting application of Centrality Measures for identifying the drug targets. Centrality measure indicates importance of node in the graph or network. Protein-Protein Interactions for proteins which are involved in a particular disease are identified and centrality measures will be calculated based on the graph built suing the PPI interactions. Further the nodes which are playing crucial role will be identified using the various centrality measures and these drug targets can be used for drug discovery of a particular disease through insilico docking studies.


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