Transferable Coarse Graining via Contrastive Learning of Graph Neural Networks DOI Creative Commons
Justin Airas, Xinqiang Ding, Bin Zhang

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Сен. 12, 2023

Coarse-grained (CG) force fields are essential for molecular dynamics simulations of biomolecules, striking a balance between computational efficiency and biological realism. These employ simplified models grouping atoms into interaction sites, enabling the study complex biomolecular systems over biologically relevant timescales. Efforts underway to develop accurate transferable CG fields, guided by bottom-up approach that matches energy function with potential mean (PMF) defined finer system. However, practical challenges arise due many-body effects, lack analytical expressions PMF, limitations in parameterizing fields. To address these challenges, machine learning-based is proposed, utilizing graph neural networks (GNNs) represent contrasting parameterization from atomistic simulation data. We demonstrate effectiveness deriving GNN implicit solvent model using 600,000 configurations six proteins obtained explicit simulations. The provides solvation free estimations much more accurately than state-of-the-art models, reproducing configurational distributions also reasonable transferability outside training Our offers valuable insights building coarse-grained bottom-up.

Язык: Английский

Fundamental Aspects of Phase-Separated Biomolecular Condensates DOI
Huan‐Xiang Zhou,

Divya Kota,

Sanbo Qin

и другие.

Chemical Reviews, Год журнала: 2024, Номер 124(13), С. 8550 - 8595

Опубликована: Июнь 17, 2024

Biomolecular condensates, formed through phase separation, are upending our understanding in much of molecular, cell, and developmental biology. There is an urgent need to elucidate the physicochemical foundations behaviors properties biomolecular condensates. Here we aim fill this by writing a comprehensive, critical, accessible review on fundamental aspects phase-separated We introduce relevant theoretical background, present basis for computation experimental measurement condensate properties, give mechanistic interpretations terms interactions at molecular residue levels.

Язык: Английский

Процитировано

24
Chemically Informed Coarse-Graining of Electrostatic Forces in Charge-Rich Biomolecular Condensates DOI Creative Commons
Andrés R. Tejedor,

Anne Aguirre Gonzalez,

Maria Julia Maristany

и другие.

ACS Central Science, Год журнала: 2025, Номер 11(2), С. 302 - 321

Опубликована: Фев. 11, 2025

Biomolecular condensates composed of highly charged biomolecules, such as DNA, RNA, chromatin, and nucleic-acid binding proteins, are ubiquitous in the cell nucleus. The biophysical properties these charge-rich largely regulated by electrostatic interactions. Residue-resolution coarse-grained models that describe solvent ions implicitly widely used to gain mechanistic insights into condensates, offering transferability, computational efficiency, accurate predictions for multiple systems. However, their predictive accuracy diminishes due implicit treatment ions. Here, we present Mpipi-Recharged, a residue-resolution model improves description charge effects biomolecular containing disordered multidomain and/or single-stranded RNAs. Mpipi-Recharged introduces pair-specific asymmetric Yukawa potential, informed atomistic simulations. We show this coarse-graining forces captures intricate effects, blockiness, stoichiometry variations complex coacervates, modulation salt concentration, without requiring explicit solvation. provides excellent agreement with experiments predicting phase behavior condensates. Overall, tools available investigate physicochemical mechanisms regulating enhancing scope computer simulations field.

Язык: Английский

Процитировано

2
Transferable Implicit Solvation via Contrastive Learning of Graph Neural Networks DOI Creative Commons
Justin Airas, Xinqiang Ding, Bin Zhang

и другие.

ACS Central Science, Год журнала: 2023, Номер 9(12), С. 2286 - 2297

Опубликована: Ноя. 16, 2023

Implicit solvent models are essential for molecular dynamics simulations of biomolecules, striking a balance between computational efficiency and biological realism. Efforts underway to develop accurate transferable implicit coarse-grained (CG) force fields in general, guided by bottom-up approach that matches the CG energy function with potential mean (PMF) defined finer system. However, practical challenges arise due lack analytical expressions PMF algorithmic limitations parameterizing fields. To address these challenges, machine learning-based is proposed, utilizing graph neural networks (GNNs) represent solvation free contrasting parameter optimization. We demonstrate effectiveness deriving GNN model using 600,000 atomistic configurations six proteins obtained from explicit simulations. The provides estimations much more accurately than state-of-the-art models, reproducing configurational distributions also reasonable transferability outside training data. Our study offers valuable insights systematically improvable perspective.

Язык: Английский

Процитировано

14
Molecular condensation of the CO/NF-YB/NF-YC/FT complex gates floral transition in Arabidopsis DOI Creative Commons
Xiang Huang, Zhiming Ma, Danxia He

и другие.

The EMBO Journal, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 20, 2024

Язык: Английский

Процитировано

4
Nonspecific Yet Selective Interactions Contribute to Small Molecule Condensate Binding DOI
Cong Wang, Henry R. Kilgore, Andrew P. Latham

и другие.

Journal of Chemical Theory and Computation, Год журнала: 2024, Номер 20(22), С. 10247 - 10258

Опубликована: Ноя. 13, 2024

Biomolecular condensates are essential in various cellular processes, and their misregulation has been demonstrated to underlie disease. Small molecules that modulate condensate stability material properties offer promising therapeutic approaches, but mechanistic insights into interactions with remain largely lacking. We employ a multiscale approach enable long-time, equilibrated all-atom simulations of condensate-ligand systems. Systematic characterization the ligand binding poses reveals can form diverse heterogeneous chemical environments one or multiple chains bind small molecules. Unlike traditional protein-ligand interactions, these dominated by nonspecific hydrophobic interactions. Nevertheless, feature unique amino acid compositions physicochemical favor certain over others, resulting varied partitioning coefficients within condensates. Notably, different share similar sets at populations. This population shift drives selectivity toward specific Our enhance interpretation experimental screening data may assist rational design targeting

Язык: Английский

Процитировано

3
Nucleosome condensate and linker DNA alter chromatin folding pathways and rates DOI Creative Commons
Yunrui Qiu, Shuming Liu, Xingcheng Lin

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 16, 2024

Chromatin organization is essential for DNA packaging and gene regulation in eukaryotic genomes. While significant progresses have been made, the exact atomistic arrangement of nucleosomes remains controversial. Using a well-calibrated residue-level coarse-grained model advanced dynamics modeling techniques, particularly non-Markovian model, we map free energy landscape tetra-nucleosome systems, identify both metastable conformations intermediate states folding pathways, quantify kinetics. Our findings show that chromatin with 10

Язык: Английский

Процитировано

3
Design and Characterization of DNA-Driven Condensates: Regulating Topology, Mechanical Properties, and Immunorecognition DOI Creative Commons
Elizabeth Skelly,

Christina J. Bayard,

Joel Jarusek

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Cells maintain spatiotemporal control over biochemical processes through the formation and dissolution of biomolecular condensates, dynamic membraneless organelles formed via liquid–liquid phase separation. Composed primarily proteins nucleic acids, these condensates regulate key cellular functions, their properties are influenced by concentration type molecules involved. The structural versatility challenges de novo design assembly with predefined properties. Through feedback between computational experimental approaches, we introduce a modular system for assembling using acid nanotechnology. By utilizing programmable oligonucleotides orthogonal synthesis methods, parameters, responsive behavior, immunorecognition products. Dissipative particle dynamics simulations predict some conditions to produce larger, well-defined compact, globular cores, while others result in smaller, more diffuse analogs. Fluorescence microscopy confirms findings microrheology demonstrates viscoelastic adaptability tested condensates. Nucleases trigger disruption structures, ethidium bromide intercalation protects from digestion. Immunostimulatory assays suggest condensate-specific activation IRF pathway cGAS-STING signaling. This study provides framework developing customizable various biological applications.

Язык: Английский

Процитировано

0
Toward Predictive Coarse-Grained Simulations of Biomolecular Condensates DOI
Shuming Liu, Cong Wang, Bin Zhang

и другие.

Biochemistry, Год журнала: 2025, Номер unknown

Опубликована: Апрель 2, 2025

Phase separation is a fundamental process that enables cellular organization by forming biomolecular condensates. These assemblies regulate diverse functions creating distinct environments, influencing reaction kinetics, and facilitating processes such as genome organization, signal transduction, RNA metabolism. Recent studies highlight the complexity of condensate properties, shaped intrinsic molecular features external factors temperature pH. Molecular simulations serve an effective approach to establishing comprehensive framework for analyzing these influences, offering high-resolution insights into stability, dynamics, material properties. This review evaluates recent advancements in simulations, with particular focus on coarse-grained 1-bead-per-amino-acid (1BPA) protein models, emphasizes OpenABC, tool designed simplify streamline simulations. OpenABC supports implementation various force fields, enabling their performance evaluation. Our benchmarking identifies inconsistencies phase behavior predictions across even though models accurately capture single-chain statistics. finding underscores need enhanced field accuracy, achievable through enriched training data sets, many-body potentials, advanced optimization techniques. Such refinements could significantly improve predictive capacity bridging details emergent behaviors.

Язык: Английский

Процитировано

0
Protein Language Model Identifies Disordered, Conserved Motifs Driving Phase Separation DOI Open Access
Yumeng Zhang,

Jared Zheng,

Bin Zhang

и другие.

Опубликована: Май 7, 2025

Intrinsically disordered regions (IDRs) play a critical role in phase separation and are essential for the formation of membraneless organelles (MLOs). Mutations within IDRs can disrupt their multivalent interaction networks, altering behavior contributing to various diseases. Therefore, examining evolutionary fitness provides valuable insights into relationship between protein sequences separation. In this study, we utilized ESM2 language model map landscape IDRs. Our findings reveal that IDRs, particularly those actively participating separation, contain conserved amino acids. This conservation is evident through mutational constraints predicted by supported direct analyses multiple sequence alignments. These conserved, acids include residues traditionally identified as “stickers” well “spacers” frequently form continuous motifs. The strong conservation, combined with suggests these motifs act functional units under selection support stable MLO formation. underscore separation’s molecular grammar made possible analysis enabled models.

Язык: Английский

Процитировано

0
Protein Language Model Identifies Disordered, Conserved Motifs Driving Phase Separation DOI Open Access
Yumeng Zhang,

Jared Zheng,

Bin Zhang

и другие.

Опубликована: Май 7, 2025

Intrinsically disordered regions (IDRs) play a critical role in phase separation and are essential for the formation of membraneless organelles (MLOs). Mutations within IDRs can disrupt their multivalent interaction networks, altering behavior contributing to various diseases. Therefore, examining evolutionary fitness provides valuable insights into relationship between protein sequences separation. In this study, we utilized ESM2 language model map landscape IDRs. Our findings reveal that IDRs, particularly those actively participating separation, contain conserved amino acids. This conservation is evident through mutational constraints predicted by supported direct analyses multiple sequence alignments. These conserved, acids include residues traditionally identified as “stickers” well “spacers” frequently form continuous motifs. The strong conservation, combined with suggests these motifs act functional units under selection support stable MLO formation. underscore separation’s molecular grammar made possible analysis enabled models.

Язык: Английский

Процитировано

0