EWCL (Entropy-Weighted Collapse Likelihood) is a novel framework for assessing protein structural instability using principles of thermodynamic entropy. Unlike conventional confidence metrics such as pLDDT or crystallographic B-factors, EWCL quantifies the intrinsic likelihood of residue-level collapse based on Shannon entropy and local sequence/structure fluctuations.
The core metric is computed using a modified Shannon entropy expression:
where pj represents the probability distribution over structural conformations or identity profiles at residue i, and wi is an optional weighting factor incorporating temperature (T) or experimental uncertainty.
EWCL scores can be visualized as entropy heatmaps, 3D structure overlays, and collapse progression charts, revealing cryptic disordered zones and early collapse risk signatures even in high pLDDT regions.
This methodology provides unique insight into collapse-prone segments relevant to protein design, aggregation modeling, and mutation sensitivity analysis. It is especially useful in regions poorly resolved by traditional disorder predictors.
Developed by CristinoLLC · Backed by entropy physics and rendered with FastAPI, Plotly, and Vercel.