Biology subjects

Riveros, I.

Publications and source records attributed to Riveros, I..

3 recordsLinked to original sources

bioRxiv2026

MOFF2: A Transferable Coarse-Grained Protein Force Field for Predictive Condensate Simulations

Coarse-grained protein force fields enable simulations of biomolecular systems at length and time scales that are difficult to access with atomistic models, but achieving transferability across folded, intrinsically disordered, and multidomain proteins remains challenging. A central difficulty is that one-bead-per-residue models must represent chemically specific residue interactions while also absorbing solvent-mediated and many-body effects into a simplified energy function. Here, we present MOFF2, a transferable coarse-grained protein force field that combines residue-pair-specific interactions with a density-dependent many-body potential. MOFF2 is optimized using a two-stage strategy: bottom-up parameter learning from heterogeneous reference ensembles followed by refinement against experimental conformational observables. The resulting model provides balanced performance across ordered proteins, intrinsically disordered proteins, and multidomain proteins, and predicts condensate saturation-concentration trends for A1-LCD variant systems. Analysis of the learned parameters reveals chemically interpretable interaction patterns and density-dependent effects that explain the models improved transferability. These results demonstrate that combining a generalized coarse-grained energy function with data-driven optimization can produce a practical and interpretable force field for protein conformational and condensate simulations.

biophysics↗

bioRxiv2025

NEAT-DNA: A Chemically Accurate, Sequence-Dependent Coarse-Grained Model for Large-Scale DNA Simulations

DNAs physical properties play a central role in genome organization and regulation, but simulating its behavior across biologically relevant scales remains a major computational challenge. Coarse grained DNA models have enabled faster simulations, yet they often sacrifice chemical accuracy or produce unphysical conformations, limiting their utility for studying genome structure. A key difficulty has been constructing a model that is both efficient enough for large-scale simulations and faithful to the molecular mechanics of DNA. Here we introduce NEAT-DNA, a new coarse-grained DNA model that resolves longstanding limitations in physical realism and parameter optimization. By combining a physically principled energy formulation with a unified training framework that integrates data from both atomistic simulations and experiments, NEAT-DNA accurately reproduces sequence-dependent structure and flexibility while remaining computationally efficient. This approach marks a significant advance over previous models, which either lacked sequence specificity or introduced distortions inconsistent with experimental observations. NEAT-DNA bridges this gap, offering a high-fidelity yet tractable representation of DNA suitable for exploring chromatin folding. More broadly, it provides a foundation for large-scale simulations that couple molecular detail with gene-level chromatin organization, opening new avenues for predictive modeling in structural genomics.

biophysics↗

bioRxiv2025

Free energy spectroscopy reveals the mechanistic landscape of chromatin compaction

Eukaryotic genomic DNA is repeatedly wrapped into nucleosome spools: the basic building block of chromatin. This organization regulates the physical accessibility of the genome to gene transcription, replication, and repair regulatory factors. Chromatin compaction is controlled by multivalent weak interactions, resulting in a complicated conformational landscape that remains challenging to characterize. This work reports a method for characterizing chromatin compaction, Free Energy Spectroscopy (FES), which is based on DNA nanotechnology and transmission electron microscopy. This method experimentally determines the chromatin compaction free energy landscape in terms of end-to-end distance and nucleosome stacking interactions. By deconvolving the free energy landscapes of partially and fully compact tetranucleosomes, FES revealed three separate mechanisms by which linker histones reshape the compaction energetics to condense chromatin. This study establishes FES as a method with the potential to help answer a broad range of mechanistic questions about genome and epigenome function.

biophysics↗