ORCID Profile
0000-0002-5691-5790
Current Organisations
University of Aberdeen
,
Collaborations In Chemistry
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Publisher: Springer Science and Business Media LLC
Date: 17-05-2019
Publisher: Public Library of Science (PLoS)
Date: 21-11-2019
Publisher: Elsevier BV
Date: 09-2020
Publisher: American Chemical Society (ACS)
Date: 30-01-2019
Publisher: F1000 Research Ltd
Date: 17-01-2017
DOI: 10.12688/F1000RESEARCH.7217.3
Abstract: The search for small molecule inhibitors of Ebola virus (EBOV) has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs) with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC 50 values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in vitro .
Publisher: Wiley
Date: 03-05-2011
Publisher: F1000 Research Ltd
Date: 04-01-2016
DOI: 10.12688/F1000RESEARCH.7217.2
Abstract: The search for small molecule inhibitors of Ebola virus (EBOV) has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs) with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC 50 values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in vitro .
Publisher: Elsevier BV
Date: 02-2013
Publisher: American Chemical Society (ACS)
Date: 14-10-2022
Abstract: The Zika virus (ZIKV) is a neurotropic arbovirus considered a global threat to public health. Although there have been several efforts in drug discovery projects for ZIKV in recent years, there are still no antiviral drugs approved to date. Here, we describe the results of a global collaborative crowdsourced open science project, the OpenZika project, from IBM's World Community Grid (WCG), which integrates different computational and experimental strategies for advancing a drug candidate for ZIKV. Initially, molecular docking protocols were developed to identify potential inhibitors of ZIKV NS5 RNA-dependent RNA polymerase (NS5 RdRp), NS3 protease (NS2B-NS3pro), and NS3 helicase (NS3hel). Then, a machine learning (ML) model was built to distinguish active vs inactive compounds for the cytoprotective effect against ZIKV infection. We performed three independent target-based virtual screening c aigns (NS5 RdRp, NS2B-NS3pro, and NS3hel), followed by predictions by the ML model and other filters, and prioritized a total of 61 compounds for further testing in enzymatic and phenotypic assays. This yielded five non-nucleoside compounds which showed inhibitory activity against ZIKV NS5 RdRp in enzymatic assays (IC
Publisher: Springer Science and Business Media LLC
Date: 26-06-2019
Publisher: Elsevier BV
Date: 09-2018
DOI: 10.1016/J.TUBE.2018.08.004
Abstract: The search for compounds with biological activity for many diseases is turning increasingly to drug repurposing. In this study, we have focused on the European Union-approved antimalarial pyronaridine which was found to have in vitro activity against Mycobacterium tuberculosis (MIC 5 μg/mL). In macromolecular synthesis assays, pyronaridine resulted in a severe decrease in incorporation of
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Sean Ekins.