Ligand-Based Pharmacophore Modeling and Quantum Computational Approaches for the Development of hCA XII Inhibitor

Area of Science:

• Biochemistry
• Medicinal Chemistry
• Computational Chemistry

Background:

• Cancer remains a significant global health threat, with drug resistance posing a major challenge.
• Targeting specific carbonic anhydrase (CA) isoforms, like CA XII, is a promising strategy for cancer therapy.
• CA XII is implicated as a biomarker in various hypoxic tumors, necessitating the development of selective inhibitors.

Purpose of the Study:

• To discover novel Carbonic anhydrase XII (CA XII) inhibitors.
• To move beyond the traditional benzene sulfonamide scaffold.
• To ensure selectivity against other CA isoforms.

Main Methods:

• Computational screening of existing lead molecules.
• Pharmacophore modeling and virtual screening to identify hit compounds.
• In silico pharmacokinetic (ADMET) and molecular dynamics simulations.
• Molecular docking, DFT, and MMGBSA calculations for stability and binding affinity assessment.

Main Results:

• A pharmacophore model yielded 43 hit molecules, all passing ADMET predictions.
• Compounds 3 and 26 demonstrated strong binding affinities and low energy conformations (-7.82 K/Cal and -7.36 K/Cal) via molecular docking.
• Molecular dynamics simulations indicated compounds 3 and 26 exhibit superior stability compared to acetazolamide.
• Structural insights were gained into the inhibition mechanism against CA XII.

Conclusions:

• Compounds 3 and 26 represent promising novel lead candidates for CA XII inhibition.
• These compounds offer a potential alternative scaffold to benzene sulfonamides.
• Further development of compounds 3 and 26 could lead to new anti-cancer therapeutics.