Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus

Karthick, V.; Nagasundaram, N.; Doss, C. George Priya; Chakraborty, Chiranjib; Siva, Ramamoorthy; Lü, Aiping; Zhang, Ge; Zhu, Hailong

doi:10.1186/s40249-016-0105-1

Cited by 48 publications

(38 citation statements)

References 46 publications

(49 reference statements)

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“…Consequently, such compounds should be removed to prevent possible toxicity during early stages of drug development [61]. Limonin [62] and Neoglucobrassicin [63] were predicted as anti-Ebola compounds but showed high-risk structural alerts, including (a) high-risk epoxides that form protein adducts, thus potentially disturbing signal transduction cascades [64] and (b) high-risk quinones that lead to the formation of reactive oxygen species (ROS) and cause severe oxidative stress [65]. Furthermore, quinone-like compounds comprise structures that are widely reported to yield false positives or are inactive [60].…”

Section: Discussionmentioning

confidence: 99%

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Mirza

Ikram

2016

IJMS

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The Ebola virus (EBOV) has been recognised for nearly 40 years, with the most recent EBOV outbreak being in West Africa, where it created a humanitarian crisis. Mortalities reported up to 30 March 2016 totalled 11,307. However, up until now, EBOV drugs have been far from achieving regulatory (FDA) approval. It is therefore essential to identify parent compounds that have the potential to be developed into effective drugs. Studies on Ebola viral proteins have shown that some can elicit an immunological response in mice, and these are now considered essential components of a vaccine designed to protect against Ebola haemorrhagic fever. The current study focuses on chemoinformatic approaches to identify virtual hits against Ebola viral proteins (VP35 and VP40), including protein binding site prediction, drug-likeness, pharmacokinetic and pharmacodynamic properties, metabolic site prediction, and molecular docking. Retrospective validation was performed using a database of non-active compounds, and early enrichment of EBOV actives at different false positive rates was calculated. Homology modelling and subsequent superimposition of binding site residues on other strains of EBOV were carried out to check residual conformations, and hence to confirm the efficacy of potential compounds. As a mechanism for artefactual inhibition of proteins through non-specific compounds, virtual hits were assessed for their aggregator potential compared with previously reported aggregators. These systematic studies have indicated that a few compounds may be effective inhibitors of EBOV replication and therefore might have the potential to be developed as anti-EBOV drugs after subsequent testing and validation in experiments in vivo.

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Section: Discussionmentioning

confidence: 99%

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Mirza

Ikram

2016

IJMS

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“…In Ebola's case, several studies have been conducted to find new drug candidates from various target proteins through this method [22,[27][28][29][30]. Natural products have been considered as one of the most potential lead compound sources because of their interesting bioactivities.…”

Section: Introductionmentioning

confidence: 99%

Identification of novel Ebola virus (EBOV) VP24 inhibitor from Indonesian natural products through in silico drug design approach

Tambunan¹,

Nasution²

2017

AIP Conference Proceedings

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Sensitivity differences between microporous NaY and hierarchical ZSM-5 modified electrodes as ammonia gas sensor AIP Conference Proceedings 1862, 030081 (2017) Abstract. Ebola remains as one of the deadliest diseases in the world, with almost 29,000 cases were reported and kill 11,000 of them, and yet neither treatment nor vaccine that can combat this disease effectively. This disease is caused by ebolavirus (EBOV), a primary member of Filoviridae family. The life cycle of this virus has been operated by several key proteins, one of them is VP24 protein, which has been known for its crucial role in the transcription and replication of EBOV. Therefore, targeting VP24 protein can be a solution for treating this pathogenic disease. In this study, virtual screening of Indonesian natural products as EBOV VP24 inhibitor was performed. About 2,020 ligands from many sources, including HerbalDB database, were obtained and screened by using DataWarrior software to measure its molecular and pharmacological properties, resulting 301 ligands in the process. Then, the molecular docking simulation was performed to check the ligand's binding interaction and affinity with EBOV VP24 protein; this simulation was done by using MOE 2014.09 software. This study resulted that cycloartocarpin was the best ligand to inhibit the EBOV VP24 protein. Therefore, this ligand should be checked its stability through molecular dynamics simulation and performed in vitro test to verify its bioactivity against the EBOV VP24 protein.

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“…Recently, virtual screening has been used to find anitiviral inhibitors that target the Ebola virus. This study found a lead candidate from the TCM database that shows a decrease in activity for the protein encoded by the virus [3]. This promising candidate also shows good pharmacokinetic properties.…”

Section: Reviewmentioning

confidence: 99%

“…Further, analogs have been generated using this starting structure which showed high potency. Many studies show how CADD can influence the development of novel therapeutics [3–6]. …”

Section: Introductionmentioning

confidence: 99%

Computational methods in drug discovery

Leelananda

Lindert

2016

Beilstein J. Org. Chem.

431

286

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The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

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Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus

Cited by 48 publications

References 46 publications

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Identification of novel Ebola virus (EBOV) VP24 inhibitor from Indonesian natural products through in silico drug design approach

Computational methods in drug discovery

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