In-silico Design of Covalently Bonding Catechol based Urease Inhibitors as Potential Candidates for Treatment of Helicobacter pylori Infection

Chopdar, Kumar Sambhav; Dash, Ganesh Chandra; Mohapatra, Pranab Kishor; Nayak, Binata; Raval, Mukesh Kumar

doi:10.21276/ijprhs.2019.06.08

IJPRHS

2019

DOI: 10.21276/ijprhs.2019.06.08

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In-silico Design of Covalently Bonding Catechol based Urease Inhibitors as Potential Candidates for Treatment of Helicobacter pylori Infection

Kumar Sambhav Chopdar¹,

Ganesh Chandra Dash²,

Pranab Kishor Mohapatra³

et al.

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Monte-Carlo method-based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors

Chopdar

Dash²,

Mohapatra³

et al. 2021

Journal of Biomolecular Structure and Dynamics

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We developed a Monte-Carlo method based QSAR model to predict urease inhibiting potency of molecules using SMILES and GRAPH descriptors on an existing diverse database of urease inhibitors. The QSAR model satisfies all the statistical parameters required for acceptance as a good model. The model is applied to identify urease inhibitors among the wide range of compounds in the phytochemical database, NPACT, as a test case. We combine the ligand-based and structure-based drug discovery methods to improve the accuracy of the prediction. The method predicts pIC50 and estimates docking score of compounds in the database. The method may be applied to any other database or compounds designed in silico to discover novel drugs targeting urease. File list (6) download file view on ChemRxiv Manuscript_Smiles_2020Modified.pdf (2.46 MiB) download file view on ChemRxiv Fig.S1_Ligand_Interaction.pdf (818.05 KiB) download file view on ChemRxiv Fig.S2_Ligand_Inophyllum.pdf (379.61 KiB) download file view on ChemRxiv Data Sheet S1-UreaseInhDB436pic50.txt (31.44 KiB) download file view on ChemRxiv TableS1_FinallyAceeptedFAF.xls (46.00 KiB) download file view on ChemRxiv TableS2_qed_table.xls (38.50 KiB) Monte-Carlo method based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors.

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Monte-Carlo method-based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors

Chopdar

Dash²,

Mohapatra³

et al. 2021

Journal of Biomolecular Structure and Dynamics

Self Cite

View full text Add to dashboard Cite

show abstract

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In-silico Design of Covalently Bonding Catechol based Urease Inhibitors as Potential Candidates for Treatment of Helicobacter pylori Infection

Cited by 1 publication

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Monte-Carlo method-based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors

Monte-Carlo method-based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors

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