Biology subjects

Payne, A. M.

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

10 recordsLinked to original sources

bioRxiv2026

Physical priors improve performance of structure-based binding affinity models

Structure-based drug discovery is a widely used paradigm for the rational design of novel small molecule therapeutics. However, the benefits conferred by the use of structural information has seen limited adoption in machine learning, where ligand-only ("2D") models are still the industry standard for molecular property or binding affinity prediction. Structure-based ("3D") ML models for binding-affinity prediction promise to present a clear advantage, but have not yet overtaken existing 2D models. Here, we show that physics-based priors can improve predictive performance of structure-based models by comparing different model architectures with varying physical priors on several prediction tasks. We present the Modular Training and Evaluation of Neural Networks (mtenn) package, where we decompose affinity prediction into separate steps of embedding structure into learned representations and combining those embeddings into a predicted binding affinity. We consider both E(3)-invariant and E(3)-equivariant architectures to determine the importance of encoding roto-translational inductive biases, as well as different methods for combining learned embeddings. By first optimizing several aspects of model construction using the general purpose PDBBind dataset, we are able to improve the performance and data efficiency of structure-based models. When subsequently trained and evaluated on the COVID Moonshot small molecule drug discovery dataset, our tuned models perform on par with industry standard ligand-only models. Our decomposed model framework highlights that encoding some physical priors improves model performance, while more complex biases such as equivariance offer limited benefit. Additionally, structure-based models generalize better to an unseen target and display higher training efficiency. Overall, these results emphasize that structure-based models benefit from their ability to incorporate physics-informed constraints, giving promising directions for model architecture development. These results also suggest that the strength of these models may be in tasks specifically aimed at generalizability, providing guidelines for their use in early-stage drug discovery campaigns.

bioinformatics↗

bioRxiv2025

How many crystal structures do you need to trust your docking results?

Structure-based drug discovery relies on the prediction of protein-bound poses of new molecule designs, the accuracy of which can impact downstream prioritization. While it is expected that crystal structures of similar molecules would provide the best template for predicting the poses of new designs, the time and cost required motivates identifying a point of diminishing returns for collecting new structures. Using 403 crystal structures of SARS-CoV-2 main protease from the open science COVID Moonshot project, we explore the tradeoff between the cost and utility of obtaining crystal structures for accurately predicting poses of designed molecules. We observe that similar reference ligands enable superior pose prediction and show that success plateaus after approximately five crystal structures per generic Bemis-Murcko scaffold, exceeding 95% for the campaign's lead series. This work provides practical recommendations for resource allocation in structure-enabled drug discovery campaigns.

biophysics↗

bioRxiv2025

A Structure-Based Computational Pipeline for Broad-Spectrum Antiviral Discovery

The rapid emergence of viruses with pandemic potential continues to pose a threat to public health worldwide. With the typical drug discovery pipeline taking an average of 5-10 years to reach clinical readiness, there is an urgent need for strategies to develop broad-spectrum antivirals that can target multiple viral family members and variants of concern. We present a structure-based computational pipeline designed to identify and evaluate broad-spectrum inhibitors across viral family members for a given target in order to support spectrum breadth assessment and prioritization in lead optimization programs. This pipeline comprises three key steps: (1) an automated search to identify viral sequences related to a specified target construct, (2) pose prediction leveraging any available structural data, and (3) scoring of protein-ligand complexes to estimate antiviral activity breadth. The pipeline is implemented using the drugforge package: an open-source toolkit for structure-based antiviral discovery. To validate this framework, we retrospectively evaluated two overlapping datasets of ligands bound to the SARS-CoV-2 and MERS-CoV main protease (Mpro), observing useful predictive power with respect to experimental binding affinities. Additionally, we screened known SARS-CoV-2 Mpro inhibitors against a panel of human and non-human coronaviruses, demonstrating the potential of this approach to assess broad-spectrum antiviral activity. Our computational strategy aims to accelerate the identification of antiviral therapies for current and emerging viruses with pandemic potential, contributing to global preparedness for future outbreaks.

bioinformatics↗

bioRxiv2024

Cortically-mediated muscle responses to balance perturbations increase with perturbation magnitude in older adults with and without Parkinson's disease

We lack a clear understanding of how cortical contributions to balance are altered in aging and Parkinsons disease (PD), which limits development of rehabilitation strategies. Processes like balance control are typically mediated through brainstem circuits, with higher-order circuits becoming engaged as needed. Using reactive balance recovery, we investigated how hierarchical neural mechanisms shape balance- correcting muscle activity across task difficulty in older adults (OAs) with and without PD. We hypothesize that feedback loops involving brainstem and cortical circuits contribute to balance control, and cortical engagement increases with challenge, aging, and PD. We decomposed perturbation-evoked agonist and antagonist muscle activity into hierarchical components based on latency using neuromechanical models consisting of two feedback loops with different delays to reflect different neural conduction and processing times. Agonist muscle activity was decomposed into two components that both increased with balance challenge in both groups. The first component occurred [~]120ms and the second occurred [~]210ms, consistent with the latencies of brainstem and transcortical circuits, respectively. Exploratory comparisons to young adults revealed larger transcortical components in OA and PD groups at lower balance challenge levels, consistent with increased cortical involvement with aging. Antagonist muscle activity included destabilizing and stabilizing components, with the destabilizing component correlating to balance ability in OAs but not in PD. These findings demonstrate that neuromechanical models can identify changes in the hierarchical control of balance without direct brain measurements. Identifying cortical contributions during balance control may complement clinical measures of balance ability to inform balance rehabilitation and assistive devices. NEW & NOTEWORTHYA neuromechanical model can decompose perturbation evoked muscle activity into components attributed to brainstem and higher-order sensorimotor feedback based on latency. In older adults with and without PD contributions from higher-order neural circuits increase with balance challenge and are related to clinical measures of balance ability. Interpreting the neural substrates of motor output for balance may reveal individual differences in the hierarchical control of balance, that could inform rehabilitation.

neuroscience↗

bioRxiv2024

Test-retest reliability of perturbation-evoked cortical activity reflects stable individual differences in reactive balance control

There is a growing interest in measuring cortical activity during balance control for understanding mechanisms of impaired balance with aging and neurological dysfunction. The most well-characterized electrophysiological signal elicited by a balance disturbance is the perturbation-evoked N1 potential that peaks 100-200 msec post-perturbation and is thought to reflect error processing. We previously found associations between the N1 and individual differences in balance ability, suggesting it may be a potential biomarker of balance health. However, a potential biomarker of balance function will be limited by its reliability and clinical feasibility, which has yet to be established. Here, we characterized the reliability of the N1 elicited by standing balance perturbations within and between sessions over a one-week interval in 10 younger and 14 older adults. A subset of older adults (n=12) completed a session approximately one year prior to the main experiment. We extracted N1 amplitude and latency from the Cz electrode using an advanced, computationally-intensive approach that relies on large amounts of data (e.g., 64 channels, many trials), Test-retest reliability was assessed using the intra-class correlation coefficient (ICC). Internal consistency was quantified by split-half reliability using the Spearman correlation coefficient. N1s varied across individuals (amplitude:12-82{micro}V, latency: 142-282ms), yet within individuals, the N1 showed excellent test-retest reliability (ICC>0.9) across a one-week and one-year time span. N1 amplitude reached excellent internal reliability for each session and group (r>0.9), that generally plateaued within 6 trials, while more trials were needed to reliably measure N1 latency. Similar results were obtained when quantifying N1s using a minimal approach performed with only three electrodes and simple preprocessing. Overall, the N1 is stable within and across sessions, and is largely independent of approach suggesting it could be a clinically-feasible biomarker of balance function. Characterizing reliability in populations with neurologic dysfunction and in different environmental contexts will be necessary to enhance our understanding of the N1, optimize experimental design, and determine its predictive validity of clinical outcomes (e.g., falls risk).

neuroscience↗

bioRxiv2022

Disturbing standing balance evokes an error-related negativity

The error-related negativity (ERN) is a neural correlate of error monitoring often used to investigate individual differences in developmental, mental health, and adaptive contexts. However, limited experimental control over errors presents several confounds to its measurement. An experimentally controlled disturbance to standing balance evokes the balance N1, which we previously suggested may share underlying mechanisms with the ERN based on a number of shared features and factors. We now measure whether the balance N1 and ERN are correlated across individuals within two small groups (N=21 young adults and N=20 older adults). ERNs were measured in arrow flanker tasks using hand and foot response modalities (ERN-hand and ERN-foot). The balance N1 was evoked by sudden slip-like movements of the floor while standing. The ERNs and the balance N1 showed good and excellent internal consistency, respectively, and were correlated in amplitude in both groups. One principal component strongly loaded on all three evoked potentials, suggesting that the majority of individual differences are shared across the three ERPs. However, there remains a significant component of variance shared between the ERN-hand and ERN-foot beyond what they share with the balance N1. It is unclear whether this component of variance is specific to the arrow flanker task, or something fundamentally related to error processing that is not evoked by a sudden balance disturbance. If the balance N1 were to reflect error processing mechanisms indexed by the ERN, balance paradigms offer several advantages in terms of experimental control over errors.

neuroscience↗

bioRxiv2022

Distinct features of the cortical N1 response to balance perturbation are associated with balance and cognitive impairments in Parkinson's disease

Mechanisms underlying associations between balance and cognitive impairments in older adults with and without Parkinsons disease are poorly understood. Balance disturbances evoke a cortical N1 response that is associated with both balance and cognitive abilities in unimpaired populations. We hypothesized that the N1 response reflects neural mechanisms that are shared between balance and cognitive function, and would therefore be associated with both balance and cognitive impairments in Parkinsons disease. Although N1 responses did not differ at the group level, they showed different associations with balance and cognitive function in the Parkinsons disease vs. control groups. In the control group, higher N1 amplitudes were correlated with lower cognitive set shifting ability and lower balance confidence. However, in Parkinsons disease, narrower N1 widths (i.e., shorter durations) were associated with greater parkinsonian motor symptom severity, lower balance ability and confidence, lower mobility, and lower overall cognitive function. Despite different relationships across populations, the present results suggest the N1 response reflects neural processes related to both balance and cognitive function. A better understanding of neural mechanisms linking balance and cognitive function could provide insight into associations between balance and cognitive decline in aging populations.

neuroscience↗

bioRxiv2021

Prefrontal-motor and somatosensory-motor cortical network interactions during reactive balance are associated with distinct aspects of balance behavior in older adults

Heightened reliance on the cerebral cortex for postural stability with aging is well-known, yet the cortical dynamics of balance control, particularly in relationship to balance function, is unclear. Here we aimed to investigate motor cortical activity in relationship to the level of balance challenge presented during reactive balance recovery, and identify circuit-specific interactions between motor cortex and prefrontal or somatosensory regions to metrics of balance function that predict fall risk. Using electroencephalography, we assessed motor cortical beta power, and beta coherence during balance reactions to perturbations in older adults. We found that individuals with greater somatosensory-motor beta coherence at baseline and lower beta power evoked over motor regions following perturbations demonstrated higher general clinical balance function. At the group-level, beta coherence between prefrontal-motor regions reduced during balance reactions. Older adults with the highest post-perturbation prefrontal-motor coherence showed greater cognitive dual-task interference and elicited stepping reactions at lower perturbation magnitudes. Our results support motor cortical beta activity as a potential biomarker for individual level of balance challenge and implicate prefrontal-and somatosensory-motor cortical networks in different aspects of balance control in older adults. Cortical network activity during balance may provide a neural target for precision-medicine efforts aimed at fall-prevention with aging.

neuroscience↗

bioRxiv2020

Unusual mode of dimerization of retinitis pigmentosa-associated F220C rhodopsin

Mutations in the G protein-coupled receptor (GPCR) rhodopsin are a common cause of autosomal dominant retinitis pigmentosa, a blinding disease. Rhodopsin self-associates in the membrane, and the purified monomeric apo-protein opsin dimerizes in vitro as it transitions from detergent micelles to reconstitute into a lipid bilayer. We previously reported that the retinitis pigmentosa-linked F220C opsin mutant fails to dimerize in vitro, reconstituting as a monomer. Using fluorescence-based assays and molecular dynamics simulations we now report that whereas wildtype and F220C opsin display distinct dimerization propensities in vitro as previously shown, they both dimerize in the plasma membrane of HEK293 cells. Unexpectedly, molecular dynamics simulations show that F220C opsin forms an energetically favored dimer in the membrane when compared with the wild-type protein. The conformation of the F220C dimer is unique, with transmembrane helices 5 and 6 splayed apart, promoting widening of the intracellular vestibule of each protomer and influx of water into the protein interior. FRET experiments with SNAP-tagged wild-type and F220C opsin expressed in HEK293 cells are consistent with this conformational difference. We speculate that the unusual mode of dimerization of F220C opsin in the membrane may have physiological consequences.

biophysics↗

bioRxiv2020

Cortical beta oscillatory activity evoked during reactive balance recovery scales with perturbation difficulty and individual balance ability

I.Cortical beta oscillations (13-30 Hz) reflect sensorimotor cortical activity, but have not been fully investigated in balance recovery behavior. We hypothesized that more challenging balance conditions would lead to greater recruitment of cortical sensorimotor brain regions for balance recovery. We predicted that beta power would be enhanced when balance recovery is more challenging, either due to more difficult perturbations or due to lower intrinsic balance ability. In 19 young adults, we measured beta power evoked over motor cortical areas (Cz electrode) during 3 magnitudes of backward support-surface translational perturbations using electroencephalography. Peak beta power was measured during early (50-150 ms), late (150-250 ms), and overall (0-400 ms) time bins, and wavelet-based analyses quantified the time course of evoked beta power and agonist and antagonist ankle muscle activity. We further assessed the relationship between individual balance ability measured in a challenging beam walking task and perturbation-evoked beta power within each time bin. In balance perturbations, cortical beta power increased [~]50 ms after perturbation onset, demonstrating greater increases with increasing perturbation magnitude. Balance ability was negatively associated with peak beta power in only the late (150-250 ms) time bin, with higher beta power in individuals who performed worse in the beam walking task. Additionally, the time course of cortical beta power followed a similar waveform as the evoked muscle activity, suggesting these evoked responses may be initially evoked by shared underlying mechanisms. These findings support the active role of sensorimotor cortex in balance recovery behavior, with greater recruitment of cortical resources under more challenging balance conditions. Cortical beta power may therefore provide a biomarker for engagement of sensorimotor cortical resources during reactive balance recovery and reflect the individual level of balance challenge.

neuroscience↗