Biology subjects

Zerze, G. H.

Publications and source records attributed to Zerze, G. H..

7 recordsLinked to original sources

bioRxiv2025

Full-Length Context Disrupts Folding of IgG-Binding Domains of Protein A

Multidomain proteins are often thought to fold as collections of independently stable domains, a modularity that underpins many assumptions in structural biology and design. Here, we challenge this view by examining the folding behavior of full-length Staphylococcal protein A (SpA), a 516-residue multidomain protein containing five immunoglobulin (Ig)-binding domains. Although each of the five Ig-binding domains of SpA folds stably in isolation (as it is already known experimentally and also confidently predicted by AI models), here, we show that the full-length construct and the individual Ig-binding domains in the full-length construct fail to adopt a stable three-dimensional structure in solution (despite being predicted to be folded by AI models). Instead, full-length SpA populates a compact yet predominantly disordered ensemble with residual secondary structure, where the folded state of each Ig-binding domain is thermodynamically unfavorable. These findings not only challenge long-held assumptions about the modular architecture and stability of SpA but also underscore the limitations of AI-based predictors when decoupled from the thermodynamic context. This work has implications for validating structure predictions, understanding multidomain architecture, and designing modular proteins for biotechnology and medicine.

biophysics↗

bioRxiv2025

Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16

Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo-EM densities observed around the Tetrahymena ribozyme at 2.2-2.3 [A] resolution, collected through target R1260 in the CASP16 competition. 26 groups participated in this solvation cryo-ensemble prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo-EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo-EM densities using Pearson correlation, Spearman correlation, mutual information, and precision-recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo-EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo-EM maps. We propose that further community-wide blind challenges can drive and evaluate progress in modeling water, ions and other previously hidden components of biomolecular systems.

biophysics↗

bioRxiv2025

Classification of Human Transcription Factors Based on Their Effector Domains via Unsupervised Learning

TFs combine DBDs, which anchor them to DNA, with EDs that regulate transcription through activation or repression, yet the sequence logic linking ED composition to function remains unclear. Here, we systematically define proxy regions--disordered segments adjacent to DBDs--to enable quantitative analysis of ED-like sequences across the human TF repertoire. Using a biophysically interpretable 22-feature classifier (FALK22) together with an embedding-based model (ESM), we map ED diversity and identify composition and charge-pattern signatures that correspond to regulatory activity along a disorder continuum, separating activation-from repression-associated regions. FALK22 identified classes align well with those identified from ESM while providing transparent, sequence-level features. Proxy regions near C-termini exhibit gradients that track DBD families, suggesting that EDs and DBDs might have co-evolved rather than evolved independently. These results establish proxy regions and FALK22 as a framework to connect sequence features with transcriptional activity and to generate testable hypotheses about effector-domain function and co-evolution with DNA-binding domains. HIGHLIGHTSO_LIWe define proxy regions as systematically identified disordered segments adjacent to DNA-binding domains (DBD), enabling quantitative analysis of effector domain (ED)-like sequences across the human transcription factor (TF) repertoire. C_LIO_LIWe develop FALK22, a 22-feature classification algorithm that classifies transcription factors based on simple sequence properties of their EDs and shows strong alignment with complex embedding-based representations from the Evolutionary Scale Model (ESM). C_LIO_LIFALK22 and ESM uncover distinct amino-acid composition and patterning signatures of EDs that correlate with transcriptional function, separating activation- and repression-associated regions along a disorder continuum. C_LIO_LIProxy regions located at the C-termini exhibit gradients that correspond to their DBD families, suggesting that EDs did not evolve as independent modular units but rather co-evolved with, or became selectively matched to, their DBD contexts. C_LI

bioinformatics↗

bioRxiv2025

A Dynamical Density Functional Theory Framework for Non-Equilibrium Phase Dynamics in Biomolecular Condensates

Biomolecular condensates, membrane-less organelles that arise from liquid-liquid phase separation (LLPS) of proteins and nucleic acids, play vital roles in cellular organization and regulation. Computational modeling is crucial for uncovering the molecular mechanisms behind LLPS; however, the fluctuations across a wide range of spatial scales and the inherently non-equilibrium nature of these systems make capturing their long-timescale dynamics particularly challenging. Here, we present a continuum dynamical density functional theory (DDFT) framework that captures the non-equilibrium dynamics of LLPS by integrating a physics-based statistical mechanical theory with key experimentally-derived parameters. Our model couples DDFT with a continuum free energy functional, incorporating two-body correlations between monomers and surface tension effects to determine binodal densities under phase coexistence. By solving the DDFT equations, we describe the time evolution of phase-separated domains, capturing key long-timescale processes such as droplet maturation, coalescence, and interface relaxation, phenomena that are difficult to probe using atomistic or mesoscale coarse-grained simulations. This implementation integrates experimental phase equilibrium data with molecular-scale descriptors, such as amino acid properties, to construct a quantitative link between molecular interactions and macroscopic phase behavior. However, the approach is generalizable, providing a foundation for self-contained molecular-to-continuum modeling bridge platforms.

biophysics↗

bioRxiv2025

Nucleation Landscape of Biomolecular Condensates in the Grand Canonical Ensemble via Monte Carlo Simulations

We present a Monte Carlo framework for simulating the nucleation of biomolecular condensates in the grand canonical ensemble, which overcomes the limitations of fixed particle number and allows direct control of the dilute-phase concentration. Our approach combines conformation sampling with bias-enhanced cluster size sampling, enabling accurate sampling of individual cluster sizes in various conformations. Our method resolves nucleation free energy surfaces and is capable of capturing both classical and nonclassical nucleation mechanisms. We validated our method by reproducing structural properties of disordered proteins across a diverse benchmark set and by applying it to study nucleation in two phase-separating proteins, FUS-LC and NDDX4, using both HPS and MPIPI coarse-grained force fields. While both proteins exhibit classical nucleation behavior under the HPS model, only FUS-LC remains classical with MPIPI. In contrast, NDDX4 shows a distinctly nonclassical nucleation pathway under MPIPI, characterized by a metastable intermediate state near the cluster size of 53 protein chains. Morphological analysis reveals that clusters up to this point are compact and spherical, whereas larger clusters adopt a nonspherical, two-lobed geometry indicative of frustrated coalescence. These findings underscore the critical role of sequence composition and force field parameterization in shaping nucleation pathways and demonstrate the utility of our framework for uncovering complex, mechanism-rich free energy landscapes in biomolecular condensation.

biophysics↗

bioRxiv2024

The Molecular Picture of the Local Environment in a Stable Model Coacervate

Polymers with electric charge, known as polyelectrolytes, are well known to form complex coacervates, which have vital implications in various biological processes and beyond. While significant advancements have been made in comprehending the molecular interactions that drive complex coacervation, the interactions that stabilize the coacervates against coalescence present an intricate experimental challenge and remain a subject of ongoing investigation. In a recent experimental study, polydiallyldimethylammonium chloride polycationic (PDDA) and anionic adenosine triphosphate (ATP) coacervates have been shown to stabilize upon transferring them to deionized water. Here, we perform molecular dynamics simulations of PDDA-ATP coacervates both in supernatant and in DI water, to understand the ion dynamics and structure within stable coacervates. We produced and analyzed an aggregated sum of 63 s simulation data of PDDA-ATP coacervates in explicit water when they are in supernatant and deionized (DI) water. We found that discarding the supernatant and transferring the coacervates to DI water causes an immediate ejection of a significant amount (more than 50%) of small ions (Na+ and Cl-) from the coacervates to the bulk solution. Subsequently, the DI water environment alters the ionic density profiles in coacervates and the surface ion dynamics. We calculated a notable slowdown for the coacervate ions when they were transferred to the DI water. These results suggest that the initial ejection of the ions from the coacervates in DI water potentially brings the outer layer of the coacervates to a physically bound state that prevents or slows down the further mobility of ions. Significance StatementComplex coacervates are promising agents for encapsulating and delivering various materials in living organisms, however, they are often prone to coalesce, limiting the range of their applications. Recently, these coacervates have been stabilized by transferring them to deionized water. However, a molecular understanding of this stability against coalescence remained elusive. This study utilizes computer simulations to model a stable coacervate system previously probed experimentally. When the coacervates were transferred to deionized water, a significant portion of the ions were immediately ejected into the solution, modifying the coacervates total charge and facilitating formation of possible surface crust. These molecular insights into the stable coacervates will enable their controllable design for encapsulation and delivery applications.

biophysics↗

bioRxiv2019

TDP-43 α-helical structure tunes liquid-liquid phase separation and function

Liquid-liquid phase separation (LLPS) is involved in the formation of membraneless organelles (MLOs) associated with RNA processing. Present in several MLOs, TDP-43 undergoes LLPS and is linked to the pathogenesis of amyotrophic lateral sclerosis (ALS). While some disease variants of TDP-43 disrupt self-interaction and function, here we show that designed single mutations can enhance TDP-43 assembly and function via modulating helical structure. Using molecular simulation and NMR spectroscopy, we observe large structural changes in a dimeric TDP-43. Two conserved glycine residues (G335 and G338) are potent inhibitors of helical extension and helix-helix interaction, which are removed in part by variants including the ALS-associated G335D. Substitution to helix-enhancing alanine at either of these positions dramatically enhances phase separation in vitro and decreases fluidity of phase separated TDP-43 reporter compartments in cells. Furthermore, G335A increases TDP-43 splicing function in a mini-gene assay. Therefore, TDP-43 helical region serves as a short but uniquely tunable module that shows promise as for controlling assembly and function in cellular and synthetic biology applications of LLPS.

biochemistry↗