Structural, functional, and stability change predictions in human telomerase upon specific point mutations.

Area of Science:

• Biochemistry
• Molecular Biology
• Computational Biology

Background:

• Telomerase is crucial for chromosome maintenance and its overexpression is a hallmark of cancer.
• Mutations in telomerase (hTERT or hTR) cause telomere shortening and are linked to human disease syndromes and organ failure.
• Understanding telomerase mutations is vital for developing targeted cancer therapies.

Purpose of the Study:

• To computationally identify potential human telomerase mutations.
• To predict the effects of these mutations on ligand binding affinity using molecular docking.
• To evaluate the interactions of specific ligands (C_9i, C_9k, 16A, NSC749234) with wild-type and mutant telomerase.

Main Methods:

• Systematic computational approach for identifying potential human telomerase mutations.
• Molecular docking to predict ligand-telomerase binding affinities.
• Molecular dynamics (MD) simulations to analyze ligand-protein interactions and conformational changes.

Main Results:

• The C_9k inhibitor exhibited the highest binding affinity for wild-type (WT) telomerase.
• Ligands C_9i and C_9k demonstrated improved interactions with human telomerase across most identified mutant models.
• Specific residues (R631, Y717) in WT telomerase consistently interacted with all tested ligands, with similar interactions observed in mutant models.
• MD simulations revealed distinct conformational behaviors of C_9i and C_9k when bound to WT telomerase.

Conclusions:

• Computational identification of telomerase mutations provides insights into their functional impact.
• Ligands C_9i and C_9k show potential as therapeutic agents targeting both WT and mutant telomerase.
• Key telomerase residues involved in ligand binding offer targets for drug design and development.