deltaGseg

deltaGseg estimates macrostates and binding free energy subpopulations from replicated molecular dynamics free energy time series to characterize conformational heterogeneity and refine interpretation of binding free energy estimates.

Key Features:

• Statistical modeling: Identifies and estimates multiple statistically distinct subpopulations within free energy time series rather than assuming a single conformational state.
• Wavelet denoising: Applies wavelet-based denoising to reduce noise in raw MD-derived free energy data prior to analysis.
• Hierarchical clustering: Groups similar conformational states to facilitate identification of candidate macrostates.
• Macrostate estimation from replicated MD: Estimates macrostates using multiple replicated series of MD-derived binding free energy snapshots.

Scientific Applications:

• Molecular biology and chemistry: Reveal conformational subpopulations and interaction modes relevant to binding thermodynamics and mechanistic studies.
• Computational complement to experiments: Provide computational access to molecular details and subpopulation structures that are difficult to resolve with experimental techniques alone.

Methodology:

Implements wavelet denoising, statistical modeling to detect multiple statistically distinct subpopulations, and hierarchical clustering to estimate macrostates from replicated molecular dynamics binding free energy time series.