# Protein Loop Modeling via the Discretizable Distance Geometry Problem with Hydrogen-Based NMR Constraints

## TL;DR

This paper introduces a new method for modeling protein loops by including hydrogen atoms, which improves accuracy using NMR data.

## Contribution

The novel use of hydrogen atoms in distance geometry for protein loop modeling with NMR constraints.

## Key findings

- Including hydrogen atoms reduces conformational space and improves model realism.
- Hydrogen-based constraints enhance agreement with known protein structures.
- Distance geometry methods are validated for structural refinement with NMR data.

## Abstract

Protein loop modeling remains a fundamental challenge
in computational
biology due to the inherent flexibility of loops and their critical
role in biological functions. In this work, we employ a discrete distance
geometry formulation, efficiently solved using the Branch-and-Prune
algorithm, with a key innovation being the incorporation of hydrogen
atoms into the model. Hydrogen atoms bonded to N and C
α in the protein backbone introduce additional
geometric constraints, and their inclusion is particularly justified
in the context of nuclear magnetic resonance (NMR) experiments, where
short-range hydrogen–hydrogen distances can be detected and
provide valuable structural information. By integrating these experimentally
accessible constraints into the modeling process, we refine the representation
of protein conformations. Computational experiments demonstrate that
incorporating hydrogen atoms reduces the conformational space, leading
to a more constrained and biologically realistic model. Comparisons
with hydrogen-free formulations confirm that our approach improves
agreement with known protein structures, further highlighting the
relevance of distance geometry methods in structural refinement.