Kinase Scaffold Repurposing for Neglected Disease Drug Discovery: Discovery of an Efficacious, Lapatanib-Derived Lead Compound for Trypanosomiasis
Gautam PatelCaitlin E. KarverRanjan Kumar BeheraPaul J. GuyettCatherine SullenbergerPeter EdwardsNorma RoncalKojo Mensa‐WilmotMichael P. Pollastri
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Abstract:
Human African trypanosomiasis (HAT) is a neglected tropical disease caused by the protozoan parasite Trypanosoma brucei . Because drugs in use against HAT are toxic and require intravenous dosing, new drugs are needed. Initiating lead discovery campaigns by using chemical scaffolds from drugs approved for other indications can speed up drug discovery for neglected diseases. We demonstrated recently that the 4-anilinoquinazolines lapatinib (GW572016, 1) and canertinib (CI-1033) kill T. brucei with low micromolar EC50 values. We now report promising activity of analogues of 1, which provided an excellent starting point for optimization of the chemotype. Our compound optimization that has led to synthesis of several potent 4-anilinoquinazolines, including NEU617, 23a, a highly potent, orally bioavailable inhibitor of trypanosome replication. At the cellular level, 23a blocks duplication of the kinetoplast and arrests cytokinesis, making it a new chemical tool for studying regulation of the trypanosome cell cycle.Keywords:
Drug repositioning
Repurposing
Lead compound
Lead (geology)
Neglected Tropical Diseases
Drug Development
The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices-including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PLpro, and Mpro) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results. PMID: 34313439
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To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.
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Abstract Motivation Drug repurposing speeds up the development of new treatments, being less costly, risky, and time consuming than de novo drug discovery. There are numerous biological elements that contribute to the development of diseases and, as a result, to the repurposing of drugs. Methods In this article, we analysed the potential role of protein sequences in drug repurposing scenarios. For this purpose, we embedded the protein sequences by performing four state of the art methods and validated their capacity to encapsulate essential biological information through visualization. Then, we compared the differences in sequence distance between protein-drug target pairs of drug repurposing and non - drug repurposing data. Thus, we were able to uncover patterns that define protein sequences in repurposing cases. Results We found statistically significant sequence distance differences between protein pairs in the repurposing data and the rest of protein pairs in non-repurposing data. In this manner, we verified the potential of using numerical representations of sequences to generate repurposing hypotheses in the future.
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The discovery of drug compounds has a long history in drug repurposing, notably by fortuitous findings. It has taken a new path in the creation of novel therapeutics based on existent or authorized drugs in recent years. Importantly, our knowledge of cancer biology and the related cancer hallmarks is growing. This, together with repurposing studies that use modern bioinformatics and comprehensive screening of the complete pharmacopeia, should lead to the discovery of novel medicines and targets. Furthermore, the usage of non-oncology pharmaceuticals, which make up most of our treatments, has the potential to speed up drug repurposing even further. We looked at both phenotypic-based and target-based methods of medication repurposing as well as described and assessed old non-oncology medications as prospective candidates for drug repurposing based on a broad knowledge of these principles and associated investigations of drug repurposing over the previous decade. Some of these medications successfully regulate at least one characteristic of cancer, whereas the others have a broad anticancer activity by regulating several targets through different signaling pathways, which is often brought on by various simultaneous signaling pathways. Furthermore, the emergence of computerized databases of disease gene targets, functional readouts, and clinical data encompassing inter-individual genetic variants and toxicities has allowed an alternative "big data" approach to grow at an unheard-of rate during the past decade. Here, we review the sources that are now on hand and speculate on significant upside possibilities.
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This article describes the Literature-Related Discovery technique and its application to Treatment Repurposing (which includes, but goes well beyond, Drug Repurposing). Illustrative results of potential repurposed treatments were shown from a study on preventing and reversing Alzheimer’s disease. The detailed query used to generate these results is presented. The approach has the potential to identify voluminous amounts of candidate treatments for repurposing. Additionally, a broad review of the Drug Repurposing literature is provided. A Drug Repurposing database is retrieved and the structure and content are analyzed using Text Clustering and Factor Analysis. Two taxonomies of the Drug Repurposing literature are presented and specific major themes are shown.
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Drug repurposing has become a widely used strategy to accelerate the process of finding treatments. While classical de novo drug development involves high costs, risks, and time-consuming paths, drug repurposing allows to reuse already-existing and approved drugs for new indications. Numerous research has been carried out in this field, both in vitro and in silico. Computational drug repurposing methods make use of modern heterogeneous biomedical data to identify and prioritize new indications for old drugs. In the current paper, we present a new complete methodology to evaluate new potentially repurposable drugs based on disease-gene and disease-phenotype associations, identifying significant differences between repurposing and non-repurposing data. We have collected a set of known successful drug repurposing case studies from the literature and we have analysed their dissimilarities with other biomedical data not necessarily participating in repurposing processes. The information used has been obtained from the DISNET platform. We have performed three analyses (at the genetical, phenotypical, and categorization levels), to conclude that there is a statistically significant difference between actual repurposing-related information and non-repurposing data. The insights obtained could be relevant when suggesting new potential drug repurposing hypotheses.
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To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction networks integrating the top ranked host factors, drug target proteins, and directed protein-protein interaction data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.
Drug repositioning
Repurposing
Cite
Citations (1)
The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices—including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PLpro, and Mpro) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results.
Drug repositioning
Repurposing
2019-20 coronavirus outbreak
Pandemic
Approved drug
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Citations (22)