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Results for “molecular geometry”

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Molecular dynamics simulations of positively selected codons in FcγRI reveal novel biochemical binding properties.

FcγRI is a high-affinity receptor for IgG, associated with autoimmune disease pathology and determines clinical responses to antibody-based immunotherapies. FcγRI has a complex evolutionary history that is not fully understood, and to address this we explored signatures of positive selection in the receptor's functional gene, FCGR1A, using codon-based selection tests on aligned 1-1 orthologous sequences from placental mammals (n = 32). Signatures of positive selection have occurred at several locations within the gene, with two sites (H148 (M2a ω 0.997 & M8 ω = 0.993)) and (W149 (M2a ω = 0.999 & M8 ω = 1.000)) exhibiting highest posterior probabilities, suggesting strong evidence of positive selection; these positions are known to form one of the FcγRI-IgG binding interfaces. We employed ancestral reconstruction to statistically infer prior codon sequences at these sites and identified ancestral H148P and W149R codons at different nodes in the phylogeny. Employing molecular dynamics simulations, we determined how evolutionary changes at these sites may have influenced the binding of FcγRI-IgG of modern-day Homo sapiens. Measuring RMSD, free energy, radius of gyration, hydrogen bond formation, and analyzing free energy landscapes, we demonstrate that structural instability between mutant structures vs the WT counterpart; however, overall binding potential increases at position 148, yet decreases at 149 in potential. H148P protonation at physiological pH remains similar, yet during acidotic calculations, protonation is likely reduced, with predicted reduction in affinity for IgG. While ancestral W149R substitutions demonstrate an implication for electron conjugation. Examining key sites at this binding FcγRI-IgG interface, our data demonstrate that these two codons have evolved in humans to be relatively insensitive to shifts in pH promoting a more stable interaction with the Fc portion of IgG during diseases that promote acidosis.

Receptors, IgG

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

Dual solvent cavities and hydrogen-bond networks define the chromophore environment in a far-red/orange-sensing cyanobacteriochrome.

Cyanobacteriochromes (CBCRs) are bilin-binding photoreceptors that exhibit remarkable spectral diversity and mediate light-dependent signaling in cyanobacteria. Far-red/orange-sensing CBCRs (froCBCRs) have attracted interest because of their unusually red-shifted absorption properties, yet structural information for their illuminated states has been lacking. Here, we report the first high-resolution (1.8 Å) crystal structure of the orange-absorbing (Po) state of the froCBCR ToFrO from Tolypothrix sp. PCC 7910. The structure reveals a compact, cyclic bilin configuration and water-mediated hydrogen-bonding networks within two solvent-accessible cavities. Within the GAF domain, the D-ring remains nearly perpendicular to the planar A-to-C ring system through interactions involving a flexible loop region. Comparative analyses of cryogenic synchrotron and room-temperature X-ray free-electron laser (XFEL) structures, together with molecular dynamics (MD) simulations, revealed alternative Met636 conformations associated with dynamic water exchange through the solvent-accessible cavity. Site-directed mutagenesis of cavity-lining and water-interacting residues resulted in modest spectral shifts. By contrast, mutations of two Trp residues, participating in π-π stacking with the D-ring and likely imposing a steric constraint near the A-ring, resulted in substantial blue and red shifts in the dark and illuminated states, respectively. Together with the observed chromophore geometry, these findings indicate that the spectral properties of ToFrO are governed by chromophore conformation and its direct interaction with surrounding residues through hydrogen-bonding, electrostatic, and π-π interactions. These results further suggest that cavity-mediated solvent organization contributes to stabilizing the local structural environment surrounding the chromophore and adjacent protein backbone. Collectively, these findings elucidate the structural basis for photoconversion and spectral tuning in froCBCRs.

Cyanobacteria

Dynamic Protein Structure Paradox: An Integrative Framework for Endpoint-Conditioned Evidentiary Sufficiency in Structure-to-Function Claims.

Accurate coordinates for a represented protein state do not, by themselves, establish activity or any other condition-specific function. This article defines the Dynamic Protein Structure Paradox (DPSP) as the apparent conflict between structural accuracy and functional underdetermination and develops it as an integrative evidentiary assessment framework rather than a new theory or paradigm. The underlying problem has been longstanding, since structural genomics, function annotation, allostery, and disorder research each established that fold does not determine function and that function does not determine fold. DPSP consolidates those results into one endpoint-conditioned rule. Once a measurable endpoint is defined, it assesses four coupled dimensions: relevant-state completeness, context completeness, ensemble or kinetic dependence, and chemical dependence. A rubric rates each dimension as adequate, uncertain, or missing, and a materiality test determines which gaps influence the stated decision. The outcome is one of three mutually exclusive modes of utilization: geometry-led, conditional, or function-measured. The deliverable is a concise evidence statement delineating what the structure supports, which decisive variable remains unmeasured, and what corroboration is necessary. DPSP complements, rather than replaces, existing structural, ensemble, and computational approaches. The framework remains unvalidated, its thresholds are provisional, and the studies necessary to confirm or refute it are specified.

Proteins

Molecular origins of pH gradients in charge-regulated biomolecular condensates.

Biomolecular condensates exhibit spontaneous electrochemical microenvironments characterized by asymmetric ion distributions and pH gradients that emerge from protein-sequence-dependent charge regulation. Despite their biological importance, mechanistic understanding of these microenvironments has been constrained by the absence of computationally tractable frameworks capable of treating proton exchange, counterion partitioning, and buffer equilibria on consistent thermodynamic footing. Here, we introduce the buffered Charge-Regulation Monte Carlo (b-CR-MC) framework, which couples grand-canonical exchange of ions and buffer species with explicit charge regulation of titratable residues. By extending the CR-MC ion-merging strategy to multicomponent reservoirs and employing the restricted primitive model, b-CR-MC achieves computational efficiency while maintaining thermodynamic rigor, achievingquantitative agreement with the more expensive generalized grand-reaction Monte Carlo approach. Applied to full-length FUS (net positive) and PGL-3 (net negative) under physiological conditions, the framework reveals sequence-dependent pH gradients: the dense phase of FUS exhibits an alkaline shift, while that of PGL-3 exhibits an acidic shift, in both cases driving the condensate interior toward the protein's isoelectric point. Slab-geometry simulations further resolve the Donnan potential and continuous ion profiles across the condensate interface, confirming the direction of these electrochemical shifts. Additionally, we identify spatially resolved buffer depletion within dense phases, establishing that dynamic charge regulation is a primary determinant rather than a secondary correction to condensate electrochemistry. By establishing a sequence-resolved, thermodynamically consistent computational platform, b-CR-MC enables quantitative prediction of how mutations and post-translational modifications reprogram condensate microenvironments across biological and pathophysiological contexts.

Hydrogen-Ion Concentration

DNA replication fidelity.

DNA replication fidelity is a key determinant of genome stability and is central to the evolution of species and to the origins of human diseases. Here we review our current understanding of replication fidelity, with emphasis on structural and biochemical studies of DNA polymerases that provide new insights into the importance of hydrogen bonding, base pair geometry, and substrate-induced conformational changes to fidelity. These studies also reveal polymerase interactions with the DNA minor groove at and upstream of the active site that influence nucleotide selectivity, the efficiency of exonucleolytic proofreading, and the rate of forming errors via strand misalignments. We highlight common features that are relevant to the fidelity of any DNA synthesis reaction, and consider why fidelity varies depending on the enzymes, the error, and the local sequence environment.

Base Pair Mismatch

One chromatin, many structures: From ensemble contact maps to single-cell 3D organization.

Understanding how chromatin folds in three dimensions remains challenging because most experimental assays capture low-dimensional projections of an underlying, highly heterogeneous polymer. Here, we present an ensemble-based interpretive framework built on the previously introduced Self-Returning Excluded Volume (SR-EV) model, a minimal generator of chromatin conformations using a nucleosome-indexed coarse-grained representation based on stochastic return rules and excluded-volume geometry. Despite its simplicity, SR-EV recapitulates key experimental signatures across scales: heterogeneous nanoscale packing domains resembling ChromEMT and ChromSTEM observations, sparse and highly variable single-configuration contact patterns analogous to single-cell chromosome conformation capture (Hi-C), and robust ensemble-level contact enrichment consistent with topologically associating domains (TADs). In this framework, Hi-C loop and TAD signatures are interpreted as ensemble-level statistical enrichments rather than invariant features of single-cell conformations. SR-EV is explicitly designed to generate large ensembles of complete three-dimensional chromatin configurations that can be projected consistently onto two-dimensional contact maps and one-dimensional genomic profiles. By introducing architectural-protein effects only through ensemble selection rather than explicit forces, SR-EV supports a separation between intrinsic polymer geometry and regulatory bias and suggests that TAD-like features can emerge as statistical enrichments rather than deterministic three-dimensional structures. Coordination number and probe-based accessibility computed directly from SR-EV provide a unified link between three-dimensional packing, two-dimensional contact maps, and one-dimensional genomic profiles. The main contribution of this work is to show, within a single coarse-grained framework, how these multimodal observables arise as linked projections of the same heterogeneous chromatin ensemble through averaging and conditional sampling. Together, these results establish SR-EV as a minimal and geometrically grounded mesoscale reference framework for interpreting how heterogeneous chromatin ensembles give rise to multimodal experimental observables while remaining consistent with the fact that chromatin organization is realized in individual cells.

Chromatin