Pharmacophore Mapping of Ligand Based Virtual Screening, Molecular Docking and Molecular Dynamic Simulation Studies for Finding Potent NS2B/NS3 Protease Inhibitors as Potential Anti-dengue Drug Compounds

Fathima, A. Jainul; Murugaboopathi, G.; Selvam, Periyasamy

doi:10.2174/1574893613666180118105659

Cited by 19 publications

(13 citation statements)

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“…The ZINC92615064 compound was found to be the best binder to the proteases keeping in mind its toxic properties too. The pharmacological properties assessed and MD stimulations were performed, for both Bromocriptine and ZINC9261504 .While Bromocriptine was shown to have 22 points of contact with the NS2B-NS3 complex, ZINC9261504 established 25 contacts, showing to have a better binding capacity [39].…”

Section: A Ns2b/ns3 Protease Target Specific Inhibitors As Anti-dengmentioning

confidence: 99%

“…Molecular docking simulations and MD stimulations were performed to further validate the compound pharmacologically. There were 27 contacts found in between the compound 3718 and the protease target compared to only 25 bonds with the compounds ZINC92615064, thus having a better binding potential [39] [5].…”

Section: B Lead Optimization Studies Using Zinc92615064 Towards Findmentioning

confidence: 99%

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Computer Aided Drug Design for finding a therapeutics for Dengue Virus Targets

2019

IJITEE

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The dengue epidemic has taken aback the entire world today. It affects millions of people worldwide sometimes causing severe manifestation, affecting body metabolomics. It’s caused by an arthropod-bornesingle-stranded RNA virus that has been distributed across the coastal regions of the globe with the advent of commercialization and trade. There is no effective treatment for dengue till date, but different forms of anti-viral vaccines are in the process of clinical trials for human use. Computational methods are being developed to unravel the viral transmission mechanics and evolution. Numerous networking models are being proposed to understand the phylogeny and inheritance pattern of the virus. Data models are projected in terms of mechanics or statistics to consider the distribution pattern of dengue in the future. This article talk about dengue virus targets at its genomics level.Several case scenario of applying CADD tools for finding the lead molecule for dengue targets were discussed. Advancement in dengue research with recent developments in computational methods were analyzed. The outcome of the present study suggested advancement in computational approaches may offer focused development of drugs for dengue.

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Section: A Ns2b/ns3 Protease Target Specific Inhibitors As Anti-dengmentioning

confidence: 99%

Section: B Lead Optimization Studies Using Zinc92615064 Towards Findmentioning

confidence: 99%

Computer Aided Drug Design for finding a therapeutics for Dengue Virus Targets

2019

IJITEE

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“…Several ligand databases are available that gives all the information about known chemical compounds. Some of the ligand databases include PubChem, drug bank, chemDB, ZINC, LIGAND [8]. Ligand databases are often built with better quality ligands which satisfy drug-likeness properties.…”

Section: Pharmaceutical Big Data Sources For Drug Discoverymentioning

confidence: 99%

A Novel Customized Big Data Analytics Framework for Drug Discovery

Fathima

Murugaboopathi

2018

JCSM

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Drug discovery is related to analytics as the method requires a technique to handle the extremely large volume of structured and unstructured biomedical data of multi-dimensional and complexity from pharmaceutical companies. To tackle the complexity of data and to get better insight into the data, big data analytics can be used to integrate the massive amount of pharmaceutical data and computational tools in an analytic framework. This paper presents an overview of big data analytics in the field of drug discovery and outlines an analytic framework which can be applied to computational drug discovery process and briefly discuss the challenges. Hence, big data analytics may contribute to better drug discovery.

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“…Drug repositioning, i.e., the discovery of new indications of existing drugs, beyond their original indications, is an increasingly attractive new-use discovery model. In addition to saving time and money, one advantage of the drug reuse approach is that existing drugs have been reviewed for safety, dose and toxicity (Ashburn and Thor, 2004;Fathima et al, 2018;Su et al, 2019;Yu et al, 2019). As a result, repurposed drugs usually go into clinical trials faster than newly developed drugs (Yu et al, 2017a(Yu et al, , 2018.…”

Section: Introductionmentioning

confidence: 99%

Predict New Therapeutic Drugs for Hepatocellular Carcinoma Based on Gene Mutation and Expression

Gao

2020

Front. Bioeng. Biotechnol.

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Hepatocellular carcinoma (HCC) is the fourth most common primary liver tumor and is an important medical problem worldwide. However, the use of current therapies for HCC is no possible to be cured, and despite numerous attempts and clinical trials, there are not so many approved targeted treatments for HCC. So, it is necessary to identify additional treatment strategies to prevent the growth of HCC tumors. We are looking for a systematic drug repositioning bioinformatics method to identify new drug candidates for the treatment of HCC, which considers not only aberrant genomic information, but also the changes of transcriptional landscapes. First, we screen the collection of HCC feature genes, i.e., kernel genes, which frequently mutated in most samples of HCC based on human mutation data. Then, the gene expression data of HCC in TCGA are combined to classify the kernel genes of HCC. Finally, the therapeutic score (TS) of each drug is calculated based on the kolmogorov-smirnov statistical method. Using this strategy, we identify five drugs that associated with HCC, including three drugs that could treat HCC and two drugs that might have side-effect on HCC. In addition, we also make Connectivity Map (CMap) profiles similarity analysis and KEGG enrichment analysis on drug targets. All these findings suggest that our approach is effective for accurate predicting novel therapeutic options for HCC and easily to be extended to other tumors.

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Pharmacophore Mapping of Ligand Based Virtual Screening, Molecular Docking and Molecular Dynamic Simulation Studies for Finding Potent NS2B/NS3 Protease Inhibitors as Potential Anti-dengue Drug Compounds

Cited by 19 publications

References 0 publications

Computer Aided Drug Design for finding a therapeutics for Dengue Virus Targets

Computer Aided Drug Design for finding a therapeutics for Dengue Virus Targets

A Novel Customized Big Data Analytics Framework for Drug Discovery

Predict New Therapeutic Drugs for Hepatocellular Carcinoma Based on Gene Mutation and Expression

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