Juan José Galano-Frutos

arXiv2026

Pore-level Quantitative Structure-Activity Relationship (QSAR) for Water Permeation Rate in Aquaporins

Aquaporins (AQPs) and aquaglyceroporins (AQGPs) play a crucial role in regulating water transport and solute selectivity across biological membranes. Besides their biological relevance, AQPs have at-tracted growing interest as models for the design of next-generation biomimetic membranes for water filtration. In this work, we present a pore-level Quantitative Structure-Activity Relationship (QSAR) approach that relates structural and physicochemical pore descriptors with experimentally reported water permeation rates across a set of AQ(G)Ps with high-resolution 3D structures. This data-driven methodology, presented here as a proof of concept, introduces a multi-feature framework for determining pore descriptors associated with water transport efficiency in AQ(G)Ps. Applied to two compiled permeation rate datasets, this framework recapitulates determinants previously reported in single-feature studies, while also highlighting additional pore descriptors that emerge as relevant in a multi-variable context. The insights gained through this approach may, in perspective, contribute to advancing the rational design of AQP-based filtration devices and to deepening the molecular understanding of the function of these valuable macromolecules in health and disease.

q-bio.BM↗

arXiv2025

ILVES: Accurate and efficient bond length and angle constraints in molecular dynamics

All-atom, force field-based molecular dynamics simulations are essential tools in computational chemistry, enabling the prediction and analysis of biomolecular systems with atomic-level resolution. However, as system sizes and simulation timescales increase, so does the associated computational cost. To extend simulated time using the same resources, a common strategy is to constrain the fastest degrees of freedom, such as bond lengths, allowing for larger integration time steps without compromising accuracy. The de facto state-of-the-art algorithms for this purpose (SHAKE, LINCS, and P-LINCS) are integrated into most molecular dynamics packages and widely adopted across the field. Despite their impact, these methods exhibit limitations: all converge slowly when high numerical accuracy is required, and the LINCS and P-LINCS algorithms cannot handle general angular constraints, limiting further increases in time step. In this article, we introduce ILVES, a family of parallel algorithms that converge so rapidly that it is now practical to solve bond length and associated angular constraint equations as accurately as the hardware will allow. We have integrated ILVES into Gromacs and our analysis demonstrates that it is superior to the state-of-the-art when constraining bond lengths. Due to its better convergence properties, we also show that if the time step is increased up to 3.5 fs by enforcing angular constraints, ILVES enables a 1.65x increase in simulated time using the same computational resources and wall-clock time, an outcome unattainable with current methods. This advance can significantly reduce the computational cost of most all-atom molecular dynamics simulations while improving their accuracy and extending access to larger systems and longer timescales.

physics.chem-ph↗