ArticleCurrent medicinal chemistry2026
Investigating Synergistic Strategies: Integrating Linear Regression, Quantum Mechanics, and Molecular Dynamics for the Discovery of Novel Anticancer Drugs Targeting MTH1 Inhibition.
Article in Current medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Interdisciplinary Frontiers in Medicinal Chemistry: Nanomedicine, Photodynamic Therapy, and Computational Drug Design.Current medicinal chemistry · 2026Article
- Combinatorial QM and MD in silico design of natural product-based DHFR inhibitors.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCancer remains a leading cause of mortality worldwide. Specific proteins play critical roles in cancer development, and MTH1 is one such protein. MTH1 removes the terminal phosphate groups from oxidized nucleotides like 8-oxo-dGTP and 2- OH-dATP, generated by oxidative stress in tumor cells.
methodsThese oxidized nucleotides can disrupt DNA replication and cell division. By preventing their incorporation into newly synthesized DNA, MTH1 promotes cancer cell proliferation. Developing new anticancer drugs is complex, but interdisciplinary research can significantly contribute to this endeavor. For the first time, we propose a multipronged approach utilizing computational chemistry, statistical analysis, machine learning, molecular dynamics simulations, and synthesis to design novel MTH1 inhibitors.
resultsThis approach underscores the power of collaboration between diverse scientific disciplines. Our research aims to identify potent MTH1 inhibitors through a synergy of these methodologies.
conclusionThis 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.
Indexed as
Identifiers
40108915What Socratic holds
Registered trials
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.