Investigating Synergistic Strategies: Integrating Linear Regression, Quantum Mechanics, and Molecular Dynamics for the Discovery of Novel Anticancer Drugs Targeting MTH1 Inhibition

This comprehensive study demonstrates that computational chemistry, statistical analysis, and MD simulations can be effectively integrated. Our findings from this combined approach illustrate that our newly designed MTH1 inhibitor, Xyl-Trp, can be a promising candidate for MTH1 inhibition.

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Publication Details

Journal
Current Medicinal Chemistry
Published
2025-03-20
DOI
https://doi.org/10.2174/0109298673342605241214044429
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Investigating Synergistic Strategies: Integrating Linear Regression, Quantum Mechanics, and Molecular Dynamics for the Discovery of Novel Anticancer Drugs Targeting MTH1 Inhibition

Alireza Fattahi, Sepideh Kalhor, Milad Nonahal Nahr
1 citations
Current Medicinal Chemistry
Computational Drug Discovery Methods
1.50
article

Investigating Synergistic Strategies: Integrating Linear Regression, Quantum Mechanics, and Molecular Dynamics for the Discovery of Novel Anticancer Drugs Targeting MTH1 Inhibition

Alireza Fattahi, Sepideh Kalhor, Milad Nonahal Nahr
article en
1 citations

Abstract

This comprehensive study demonstrates that computational chemistry, statistical analysis, and MD simulations can be effectively integrated. Our findings from this combined approach illustrate that our newly designed MTH1 inhibitor, Xyl-Trp, can be a promising candidate for MTH1 inhibition.

Current Medicinal ChemistryVol. 33(3)
Sharif University of Technology (IR)
Good health and well-being
Openalex Percentile: Top 19%
Computational Drug Discovery Methods
1.50
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