Disruption of shape-complementarity markers to create cytotoxic variants of ribonuclease A

Area of Science:

• Biochemistry
• Molecular Biology
• Cancer Therapeutics

Background:

• Onconase (ONC), an amphibian ribonuclease, is in clinical trials for malignant mesothelioma.
• Bovine pancreatic ribonuclease A (RNase A) is a potent RNA catalyst but lacks cytotoxicity due to strong binding with ribonuclease inhibitor protein (RI).
• ONC's cytotoxicity is attributed to its ability to evade RI, unlike RNase A.

Purpose of the Study:

• To design and develop novel RNase A variants with enhanced cytotoxicity against cancer cells.
• To investigate the role of RI evasion in RNase A-mediated cytotoxicity.
• To demonstrate the utility of the FADE algorithm in protein-protein interface analysis for drug design.

Main Methods:

• Utilized the Fast Atomic Density Evaluation (FADE) algorithm to identify geometric complementarity at the RI.RNase A interface.
• Designed and created RNase A variants by substituting specific amino acid residues (e.g., D38R/R39D/N67R/G88R) to reduce RI binding affinity.
• Assessed the catalytic activity, conformational stability, RI binding affinity (K(d)), and cytotoxicity of engineered RNase A variants against human cancer cells.

Main Results:

• Engineered RNase A variants exhibited a significant increase (20 x 10^6-fold) in K(d) for RI, reaching 1.4 microM, indicating reduced binding affinity.
• These variants retained catalytic activity and conformational stability comparable to wild-type RNase A.
• The novel RNase A variants displayed greater and more selective cytotoxicity against human cancer cells than Onconase (ONC).

Conclusions:

• The FADE algorithm is effective for analyzing protein-protein interfaces and guiding the design of modified proteins.
• Evasion of RI is a key factor in achieving cytotoxicity for RNase A-based therapeutics.
• Engineered RNase A variants represent a promising new class of targeted cancer chemotherapeutics.