Evidence mapPaperPMID 38982021Full record

ArticleCell biochemistry and biophysics2024

In Silico Investigation against Inhibitors of Alpha-Amylase Using Structure-based Screening, Molecular Docking, and Molecular Simulations Studies.

Fariya Khan, Altaf Ahmad Shah, Ajay Kumar, Salman Akhtar

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Article in Cell biochemistry and biophysics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

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4citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Fariya KhanDepartment of Bioengineering, Integral University, Lucknow, India.
Altaf Ahmad ShahDepartment of Biosciences, Integral University, Lucknow, India.
Ajay KumarDepartment of Biotechnology, Faculty of Engineering & Technology, Rama University, Kanpur, India.
Salman AkhtarDepartment of Bioengineering, Integral University, Lucknow, India. salmanakhtar18@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type-II diabetes mellitus is a chronic disorder that results from fluctuations in the glucose level leading to hyperglycemia with severe adverse effects increasing worldwide. Alpha-Amylase is the key enzyme involved in the mechanism of glucose formation therefore Alpha-Amylase inhibitors have become a therapeutic target in the development of new leads as they have the potential to suppress glucose levels. Existing drugs targeting Alpha-Amylase highlight major drawbacks in terms of poor absorption rate that causes several gastrointestinal issues. So, this research is aimed to develop novel inhibitors interacting with Alpha-Amylase's active site using structural-based screening, binding pattern analysis, and molecular dynamic simulation. Hence, to search for a potential lead, we analyzed a total of 133 valiolamine derivatives and 535 desoxynojirimycin derivatives that exhibited drug-like properties screened through Lipinski filters. Virtual screening followed by binding interaction analysis we identified ten compounds that exhibited better binding energy scores compared to the standard drugs voglibose and miglitol, used in our study. The docking analysis, ADMET and metabolic site prediction estimated the best top two compounds with good drug profiles. Further, top compounds VG9 and VG15 were promoted to simulation study using the Biovia Discovery study to access the stability at a time interval of 100 ns. MD simulation results revealed that our compound VG9 possesses better conformational stability in the complex to the active site residues of Alpha-Amylase target protein than standard drug voglibose. Thus, our investigation revealed that compound VG9 also exhibits the best pharmacokinetic as well as binding affinity results and could act as a potential lead compound targeting Alpha-Amylase for Type II diabetes.

Indexed as

alpha-AmylasesCatalytic DomainEnzyme InhibitorsMolecular Docking SimulationMolecular Dynamics Simulation1-DeoxynojirimycinBinding SitesHumansInositolProtein Binding1-Deoxynojirimycinalpha-AmylasesEnzyme InhibitorsInositolmiglitolvogliboseAlpha-AmylaseLipinski filtersSimulationType-II diabetes mellitusVirtual screeningVoglibose

Identifiers

PMID38982021

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.