KIF-Key Interactions Finder: A program to identify the key molecular interactions that regulate protein...

Area of Science:

• Computational biology
• Structural biology
• Biophysics

Background:

• Proteins' non-covalent interaction networks regulate their conformation and function.
• Identifying key interactions driving specific conformational changes is crucial for understanding protein mechanisms and engineering.
• Most non-covalent interactions in proteins are irrelevant to a single conformational change.

Purpose of the Study:

• To develop an automated tool for identifying non-covalent interactions associated with specific protein conformational changes.
• To provide insights for basic research on protein mechanisms and for protein engineering applications.
• To introduce the open-source Python package Key Interactions Finder (KIF).

Main Methods:

• KIF processes protein simulation datasets (e.g., molecular dynamics).
• Users define conformational changes as continuous or categorical variables.
• Statistical and machine learning methods identify and rank relevant interactions and residues.

Main Results:

• KIF successfully identified key interactions regulating conformational dynamics in diverse protein systems.
• Demonstrated the package's ability to pinpoint functionally important features.
• Validated KIF's utility across protein tyrosine phosphatase 1B, PDZ3 domain, and Kemp eliminases.

Conclusions:

• KIF is a valuable open-source tool for analyzing protein conformational dynamics.
• It enables researchers to identify critical non-covalent interactions driving specific functional changes.
• The insights from KIF can advance basic research and protein engineering efforts.