Network-based allosteric analysis of galectin-7: Key residues dictate functional communication and stability.

Area of Science:

• Biochemistry
• Computational Biology
• Structural Biology

Background:

• Allosteric modulation offers precise protein control but designing selective inhibitors is challenging.
• Current screening methods for allosteric modulators are costly and time-consuming, necessitating predictive computational strategies.

Purpose of the Study:

• To develop a computational approach for predicting allosteric communication nodes in homodimeric proteins.
• To identify key residues regulating the pro-apoptotic activity of human galectin-7 (GAL-7).

Main Methods:

• Combined network and shortest-path analyses to identify interprotomer communication nodes.
• Engineered protein variants by mutating identified key residues (R20, R22, D103).
• Utilized biophysical and structural analyses to validate predictions and assess dimer stability and communication.

Main Results:

• Identified a minimal electrostatic network (R20-R22-D103) as a critical allosteric node in GAL-7.
• Engineered variants (R20A, R22A, D103A, R20A-R22A) impaired GAL-7-induced apoptosis in human T cells.
• Disrupting the R20-D103 interaction weakened interprotomer communication and destabilized the GAL-7 dimer.

Conclusions:

• Residue-network fingerprinting enables predictive mapping of global communication pathways in proteins.
• R20, R22, and D103 are key allosteric determinants of GAL-7 function.
• The integrative framework provides a generalizable strategy for rational allosteric modulator design for homodimeric proteins.