Uncovering allosteric pathways in caspase-1 using Markov transient analysis and multiscale community detection

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Allosteric regulation is crucial for cellular functions and a key target for drug development.
• Identifying intra-molecular signaling pathways to allosteric sites remains a challenge.

Purpose of the Study:

• To develop and validate an atomistic graph-theoretical method for identifying allosteric pathways.
• To analyze the structural differences between active and inactive caspase-1 conformations.
• To predict functionally important residues and bonds in allosteric communication.

Main Methods:

• Utilized an atomistic graph-theoretical approach leveraging Markov transients.
• Applied Markov stability community detection for multiscale structural analysis.
• Performed computational point mutagenesis and random walk simulations.

Main Results:

• The active caspase-1 conformation exhibits enhanced intra-protein coherence and signal propagation compared to the inactive form.
• Identified critical residues essential for maintaining structural coherence.
• Successfully predicted a known allosteric site and quantified bond contributions to the active-allosteric site communication pathway.

Conclusions:

• The developed method provides a computationally inexpensive way to identify allosteric sites and pathways.
• The findings offer new insights into caspase-1 allosteric regulation and potential drug targets.
• This approach can be broadly applied to various proteins for understanding allosteric mechanisms.