Identification of DNA Methyltransferase-1 Inhibitor for Breast Cancer Therapy through Computational Fragment-Based...

Area of Science:

• Biochemistry
• Medicinal Chemistry
• Computational Biology

Background:

• Epimutation by DNA Methyltransferase 1 (DNMT1) is implicated in breast cancer proliferation.
• Targeting DNMT1 offers a potential therapeutic strategy for breast cancer.

Purpose of the Study:

• To identify novel, potent, and safe inhibitors of DNMT1 from natural product databases.
• To computationally screen and optimize natural product-derived compounds for anti-cancer activity.

Main Methods:

• In silico screening of 168,686 natural products from PubChem.
• Application of Lipinski's and Veber's rules, toxicological screening, and pharmacophore-based molecular docking.
• ADME-Tox property prediction and comparative analysis against standard inhibitors (SAH, SAM, SFG).

Main Results:

• Initial screening yielded 2601 fragment candidates, refined to 51,200 ligands after modification.
• Five lead compounds (C-7756, C-5769, C-1723, C-2129, C-2140) demonstrated superior binding to DNMT1.
• C-7756 exhibited the strongest DNMT1 affinity and superior ADME-Tox profiles, including druglikeness, GI absorption, and oral bioavailability.

Conclusions:

• The study successfully identified C-7756 as a promising DNMT1 inhibitor candidate derived from natural products.
• C-7756 demonstrates potential for development as an anti-breast cancer therapeutic agent due to its efficacy and favorable pharmacokinetic properties.