IMP-sampcon

IMP-sampcon evaluates sampling convergence and exhaustiveness for integrative modeling to determine whether ensembles of 3D macromolecular models generated with the Integrative Modeling Platform (IMP) adequately sample relevant configurational space.

Key Features:

• Sampling Convergence Assessment: Evaluates whether the sampling process has adequately explored the conformational space to establish ensemble convergence.
• Exhaustiveness Analysis: Assesses the thoroughness of sampling to determine whether all relevant model configurations have been considered.
• Integration with IMP: Operates within the Integrative Modeling Platform (IMP) and leverages IMP's modeling capabilities and Python-based interfaces.

Scientific Applications:

• Integrative Structure Modeling: Supports construction and validation of 3D models of complex macromolecular assemblies using integrative modeling approaches.
• Use with Experimental Data: Applied to models built from electron microscopy, solution X-ray scattering, and chemical crosslinking data to assess sampling quality.
• Studies of Complex Assemblies and Deposition: Used in research on assemblies such as the actin-tropomyosin-gelsolin system and to support validation for deposition into PDB-Dev.

Methodology:

Performs data integration of experimental inputs and prior models, converts inputs into system representations and scoring functions, conducts guided sampling using those scoring functions, and analyzes the sampled models to assess convergence and exhaustiveness.