Inference of joint conformational distributions from separately-acquired experimental measurements

TL;DR

This paper introduces a novel method to accurately infer joint conformational distributions of flexible biomolecules from separately acquired experimental measurements, overcoming limitations of traditional independent assumptions.

Contribution

The authors developed a new approach to estimate true joint distributions from separate measurements, enabling better understanding of biomolecular flexibility.

Findings

Method accurately reproduces known joint distributions.

Generates testable predictions for complex conformational ensembles.

Applicable to biological systems with flexible structures.

Abstract

Many biomolecules have flexible structures, requiring distributional estimates of their conformations. Experiments to acquire distributional data typically measure pairs of labels separately, losing information on the joint distribution. These data are assumed independent when estimating the conformational ensemble. We developed a method to estimate the true joint distribution from separately acquired measurements, testing it on two biological systems. This method accurately reproduces the joint distribution where known and generates testable predictions about complex conformational ensembles.