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01-12-2019 | Original Article | Issue 1/2019

Network Modeling Analysis in Health Informatics and Bioinformatics 1/2019

Computational screening and ADMET-based study for targeting Plasmodium S-adenosyl-l-homocysteine hydrolase: top scoring inhibitors

Journal:
Network Modeling Analysis in Health Informatics and Bioinformatics > Issue 1/2019
Authors:
Dev Bukhsh Singh, Seema Dwivedi
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s13721-019-0183-7) contains supplementary material, which is available to authorized users.

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Abstract

S-adenosyl-l-homocysteine hydrolase (SAHH) is a ubiquitous enzyme that plays a significant role in methylation-based processes by maintaining the intracellular balance between S-adenosylhomocysteine and S-adenosylmethionine. In the past years, some analogs and derivatives of aristeromycin have been reported as a potential inhibitor of Plasmodium falciparum’s SAHH (PfSAHH), but no effective therapy has been developed yet. In our previous studies, molecular dynamics simulation study of 2-fluoroaristeromycin in complex with PfSAHH was carried out, and a stable complex with favorable binding energy and interaction was observed. In the presented work, 2-fluoroaristeromycin was used as a central compound for finding the vast set of similar compounds using PubChem database search (65 compounds), pharmacophore-based search (1219 compounds) and ZINC database search for biogenic compounds (approximately 1, 82000 compounds). All these compounds were docked with PfSAHH drug target to screen compounds with energetically favorable binding and stable conformation. Binding energy and different ADMET based parameters were used for screening some potential compound from each set. Binding affinity and interaction of top scoring 15 compounds from the biogenic subset were again evaluated using other docking tools such as AutoDock and AutoDock Vina. These top scoring compounds satisfy the binding and most of the ADMET parameters, and their activity can be further optimized to find a more potent inhibitor of PfSAHH.

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Supplementary Material
Supplementary material 1 (DOCX 18 KB)
13721_2019_183_MOESM1_ESM.docx
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