Biology subjects

Bronstein, A. M.

Publications and source records attributed to Bronstein, A. M..

9 recordsLinked to original sources

bioRxiv2026

The turn less taken: Investigating patterns in β-turn dynamics using large-scale molecular dynamics data

{beta}-turns are among the most common structural motifs in proteins, yet their conformational dynamics and sequence determinants remain incompletely understood. Here we present a data-driven classification and dynamic analysis of {beta}-turn conformations using large-scale molecular dynamics trajectories from the mdCATH database. Clustering of backbone dihedral angles using a cross-bond Ramachandran representation identifies six {beta}-turn types, including a previously uncharacterized hybrid I/I' cluster that combines geometric features of canonical type I and I' conformations. Time-resolved analysis indicates that this hybrid state acts as a transient intermediate state of {beta}-turns. Transitions observed in molecular dynamics simulations closely match NMR ensembles and altlocs detected in X-ray crystal structures, with the most dominant exchanges occurring between type I and II, and between type I' and II' turns. Sequence analysis shows that each turn type exhibits characteristic amino acid preferences at the central residues (i + 1 and i + 2). Within these overall preferences, specific residue pairs display distinct biases toward static or dynamic behavior. Targeted in silico substitutions that interchange dynamic- and static-enriched residue pairs shift the conformational behavior of turns accordingly, providing direct support for these sequence-dynamics relationships. Analysis of flanking secondary-structure environments reveals that structural context further modulates turn flexibility, with strand- and coil-associated turns exhibiting higher dynamic propensity than helix-associated turns. Together, these results reveal how sequence composition and structural context jointly shape the conformational landscape of {beta}-turns.

biochemistry↗

bioRxiv2026

Statistical signals indicate a dependence between amino acid backbone conformation and the translated synonymous codon

Synonymous codons encode the same amino acid but can differ in their usage and translational properties. In previous work we reported statistical differences in backbone dihedral angle distributions associated with synonymous codons in the Escherichia coli proteome. This finding has been questioned due to concerns regarding the statistical methodology used. Here we revisit the dataset using corrected statistical procedures and alternative statistical tests. Across multiple frameworks, the real dataset consistently shows an excess of small p-values relative to randomized controls, indicating detectable codon-associated differences in backbone conformation.

bioinformatics↗

bioRxiv2026

Density-guided AlphaFold3 uncovers unmodelled conformations in β2-microglobulin

Although X-ray crystallography captures the ensemble of conformations present within the crystal lattice, models typically depict only the most dominant conformation, obscuring the existence of alternative states. Applying the electron density-guided AlphaFold3 approach to {beta}2-Microglobulin highlights how ensembles of alternate backbone conformations can be systematically modeled directly from crystallographic maps. This study also highlights how the detection of conformational ensembles is affected by the local quality of electron density and subtle variations in crystallization conditions and lattice packing. These results demonstrate that density-guided AlphaFold3 can uncover conformational heterogeneity missed by conventional refinement, offering a robust, systematic framework to capture the full structural landscape of proteins in crystals and enhancing the interpretive power of macromolecular crystallography. SynopsisElectron-density-guided AlphaFold3 reveals previously unmodeled conformational heterogeneity in {beta}2-Microglobulin and shows how crystal packing influences ensemble detection in X-ray crystallography.

bioinformatics↗

bioRxiv2025

Perceiving Instability: How Expectations Bias Sensorimotor Processing in Balance Control

Maintaining balance requires rapid integration of sensory input with top-down sensorimotor predictions. Predictive coding frameworks propose that mismatches between expected and actual sensory input ("prediction errors") drive perceptual inference. Although these frameworks have been highly influential in sensory neuroscience, it remains unclear whether they operate similarly in fast-acting sensorimotor systems such as human balance. Using electroencephalography (EEG) and discrete postural perturbations via support surface translations, we independently manipulated expectations and sensory input. Participants were primed to expect small or large perturbations, with occasional violations in which the delivered perturbation differed from expectation. We found that subjective perception of instability was shaped by expectation alone, regardless of perturbation magnitude. Similarly, pre-perturbation beta-band suppression and post-perturbation gamma activity tracked expected perturbation magnitude, with the latter strongly associated with expectation-induced perceptual biases (r = 0.69, pBON = 0.001). In contrast, both the balance N1 (a well-established stimulus-evoked cortical potential linked to the postural response) and objective behavioural markers of postural instability were determined primarily by perturbation magnitude. Crucially, neither perception nor early neural or behavioural markers appeared to encode prediction errors arising from expectation violations. Together, these findings identify boundary conditions on predictive coding in sensorimotor control, showing that during fast, reactive behaviour, perceptual inference may be shaped more strongly by expectations than by mismatch signals, even as early neural and motor responses remain driven primarily by sensory input. Significance StatementPerception is often explained through predictive coding, a framework in which the brain compares incoming sensory input with internal expectations and updates representations based on mismatches, or prediction errors. However, it remains unclear whether these perceptual inference processes operate similarly in fast, ecologically relevant sensorimotor systems, such as postural control. Our results show that top-down expectations shape perceptual experience and early cortical responses to postural perturbations, even when sensory input contradicts those expectations. Notably, these early neural markers showed limited sensitivity to prediction errors in this rapid, reactive context. Together, these findings identify conditions under which perceptual inference may rely more strongly on expectations than on sensory mismatch, refining predictive coding accounts of fast, reactive behaviour. ClassificationBiological Science (Neuroscience)

neuroscience↗

bioRxiv2025

Experiment-guided AlphaFold3 resolves accurate protein ensembles

AlphaFold3 predicts highly accurate protein structures from sequence, but tends to collapse to a single dominant conformation, even when the underlying structure is inherently heterogeneous. Moreover, its predictions are oblivious to experimental conditions that can alter local sequence conformation. In this work we show that AlphaFold3 can be guided to match data obtained by NMR spectroscopy, X-ray crystallography and cryo-EM experiments, and combinations thereof. Our approach can also incorporate data that explicitly report on dynamics, such as site-resolved order parameters. We demonstrate that this methodology can generate ensembles of conformations having less distance restraint violations than traditionally resolved NMR structures and uncover unmodelled alternate conformations detectable in electron density. This methodology paves the way for the development of experimentally aware predictive models that capture the ensemble nature of protein structures.

molecular biology↗

bioRxiv2024

The end of protein structure prediction: Improving prediction accuracy in chimeric proteins by windowed multiple sequence alignment

AlphaFold2 has predicted the structures of almost every known protein. A simple means to create proteins beyond those found in nature, is by unnaturally fusing together two known proteins. Here we demonstrate that dependence on multiple sequence alignment, limits the success with which AlphaFold and ESMfold capture such chimeric forms of otherwise well predicted, individual, proteins. Specifically we show that peptides are predicted with significantly reduced accuracy when added to the terminal ends of scaffold proteins. Appending the multiple sequence alignment for the individual peptide tags to that of the scaffold protein often restores prediction accuracy.

bioinformatics↗

bioRxiv2024

Seeing Double: Molecular dynamics simulations reveal the stability of certain alternate protein conformations in crystal structures

Proteins jiggle around, adopting ensembles of interchanging conformations. Here we show through a large-scale analysis of the Protein Data Bank and using molecular dynamics simulations, that segments of protein chains can also commonly adopt dual, transiently stable conformations which is not explained by direct interactions. Our analysis highlights how alternate conformations can be maintained as non-interchanging, separated states intrinsic to the protein chain, namely through steric barriers or the adoption of transient secondary structure elements. We further demonstrate that despite the commonality of the phenomenon, current structural ensemble prediction methods fail to capture these bimodal distributions of conformations.

biochemistry↗

bioRxiv2023

Water stabilizes an alternate turn conformation in horse heart myoglobin

Comparison of myoglobin structures reveals that protein isolated from horse heart consistently adopts an alternate turn conformation in comparison to its homologues. Analysis of hundreds of high-resolution structures discounts crystallization conditions or the surrounding amino acid protein environment as explaining this difference, that is also not captured by the AlphaFold prediction. Rather, a water molecule is identified as stabilizing the conformation in the horse heart structure, which immediately reverts to the whale conformation in molecular dynamics simulations excluding that structural water.

cell biology↗

bioRxiv2022

Defining amino acid pairs as structural units suggests mutation sensitivity toadjacent residues

Proteins fold from chains of amino acids, forming secondary structures, -helices and {beta}-strands, that, at least for globular proteins, subsequently fold into a three-dimensional structure. A large-scale analysis of high-resolution protein structures suggests that amino acid pairs constitute another layer of ordered structure, more local than these conventionally defined secondary structures. We develop a cross-peptide-bond Ramachandran plot that captures the conformational preferences of the amino acid pairs and show that the effect of a particular mutation on the stability of a protein depends in a predictable manner on the adjacent amino acid context. One-Sentence SummaryLarge-scale protein backbone analysis reveals amino acid pair conformational preferences and predicts how sequence context affects mutant stability.

molecular biology↗