Biology subjects

Dickson, A.

Publications and source records attributed to Dickson, A..

18 recordsLinked to original sources

bioRxiv2026

Fatty Acid β-oxidation and Ferroptosis Define a Survival-Productivity Trade Off in CHO fed-Batch Bioreactors

Fed-batch production in Chinese hamster ovary cells is usually optimised empirically, yet the intracellular mechanisms that determine whether cells sustain productivity or enter terminal decline remain poorly resolved. Here, we combine longitudinal proteomics and intracellular metabolomics across differential ambr250 fed-batch processes to define the metabolic programmes associated with CHO cell viability and antibody production. Across media/feed combinations and an intensified seeding regime, culture progression followed a conserved trajectory from proliferation to metabolic transition and terminal stress. The high-stress state was characterised by a switch toward mitochondrial and peroxisomal fatty acid {beta}-oxidation, lipid remodelling, oxidative burden and activation of ferroptosis-associated pathways. Enriched feed conditions delayed this transition through enhanced redox and glutathione-linked defence, but did not proportionally increase antibody titre, revealing a trade-off in which cellular resources are diverted from recombinant protein production toward survival. These data identify fatty acid metabolism and ferroptosis as key constraints on late-stage CHO fed-batch performance and provide a mechanistic framework for rational feed design and host-cell engineering.

cell biology↗

bioRxiv2026

Preserving Native Cellulose-Xylan Architecture Enables Structure-Property Control in Holocellulose Nanofibrils and High-Performance Sustainable Materials

The hierarchical organization of cellulose microfibrils and their intimate interactions with hemicelluloses such as xylan underpin the exceptional mechanical performance of plant cell walls. However, translating these biological design principles into sustainable nanocellulosic materials remains limited by conventional cellulose nanofibril production routes, which rely on harsh chemical treatments that disrupt the native cellulose-hemicellulose architecture. Here, we present an optimized isolation strategy for holocellulose nanofibrils (hCNFs) that preserves native cellulose structure, xylan substitution and conformation, and cellulose-xylan interactions. Using wild-type Arabidopsis thaliana, a xylan glucuronidation-deficient gux1/2 mutant, and Brassica napus straw as model systems, we systematically elucidate how xylan content and substitution pattern govern nanofibril isolation, interfacial interactions, and macroscopic properties. Two-dimensional 13C magic-angle spinning NMR demonstrates retention of native cellulose glucosyl environments, the presence of two-fold and three-fold helical xylan conformations, and cellulose-associated two-fold helical xylan. Cryogenic transmission electron microscopy reveals fibril widths of [~]3 nm, consistent with elementary cellulose I{beta} microfibrils. We show that xylan glucuronidation regulates colloidal stability, hydration behavior, and interfibrillar cohesion, whereas xylan content controls nanofibrillation efficiency. These multiscale structural features translate directly into moisture sorption, thermal behavior, and mechanical performance. Notably, Brassica napus hCNF films exhibit exceptional strength and extensibility, surpassing many chemically modified CNF systems. This work demonstrates that preserving the native cellulose-hemicellulose architecture enables high-performance, sustainable nanocellulosic materials without chemical reconstruction.

biochemistry↗

bioRxiv2026

Expanding the genetic code with diverse backbone structures across diverse sequence contexts

Expanding the genetic code to enable the selective and specific incorporation of non-canonical monomers (ncMs), beyond -L amino acids with variant sidechains, is a key outstanding challenge. Here we discover orthogonal aminoacyl-tRNA synthetases that selectively and specifically acylate their cognate orthogonal tRNA in vivo with eleven new ncMs spanning five different chemical classes: ,-disubstituted-amino acids, malonic acids, carboxylic acids, {beta}2-amino acids and N-cyclic amino acids. We demonstrate that co-translational incorporation of ,-disubstituted-amino acids, {beta}2-amino acids, {beta}3-amino acids and N-cyclic amino acids is strongly dependent on the codons either side of the codon used to direct ncM incorporation, with several ncMs incorporated at less than 1% of sequence contexts. We evolve orthogonal tRNAs that enable the incorporation of previously unincorporated ncMs, enable the incorporation of ncMs at >95% of sequence contexts and, increase the incorporation efficiency at challenging sequence contexts up to 40-fold. We demonstrate the encoded cellular synthesis of proteins and macrocycles containing ncMs and, explicitly demonstrate that our evolved tRNAs provide direct access to a wider range of genetically encoded macrocyclic sequences containing ncMs. Our results provide a foundation for composing, discovering and manufacturing proteins and peptides with functions augmented by ncMs.

synthetic biology↗

bioRxiv2026

Assessing the Stability of Molecular Glues with Weighted Ensemble Simulations

Targeted protein degradation is an emerging approach that utilizes cellular degradation pathways to inhibit a target protein. Small molecules such as molecular glues or PROTACs can be used to mediate the formation of a ternary complex with an E3 ligase and the target protein, which can dramatically enhance the degradation process. This approach is promising for cancer therapy, where degradation of oncogenic proteins can lead to cancer cell toxicity. To design new molecular glues, it is important to develop methods that predict how well a given molecule stabilizes a protein-protein interaction. However, conventional molecular dynamics simulations face challenges in capturing the long-timescale binding and unbinding events that would be used to evaluate this stabilization. In this study, we developed a strategy that allows us to evaluate the stability of protein-protein interactions in the presence of a glue molecule using weighted ensemble simulations in combination with weakened protein-protein interactions. Using this strategy, we generated unbinding trajectories of the DCAF15-RBM39 system with small molecules E7820, Indisulam, and several other Indisulam analogs. We were able to observe distinctly different behaviors between systems with different glues, which was in agreement with their reported EC50 values. We believe this approach could aid drug discovery efforts by expanding the set of druggable targets and improving the success rate of molecular glue development.

biophysics↗

bioRxiv2026

Conformation Driven Enhancement of Neurolysin Activity in Presence of a Small Molecule Activator

Neurolysin (Nln) is an M3 metallopeptidase that regulates neuropeptide concentration in the central nervous system. It has emerged as a therapeutic target for mitigating post-ischemic injury by hydrolyzing and inactivating several neuropeptides. It has been recently shown that small molecule activators, such as pyridine piperazine (Py-Pip) derivatives, can enhance Nln catalytic activity, facilitating hydrolysis of Nln substrate peptides. However, binding sites of these molecules and the mechanism of action remain unclear due to the dynamic nature of Nln. Here, we use molecular dynamics (MD) simulation of the apo and activator-bound Nln systems along with Markov state modeling to identify three binding sites of Py-Pip, and quantify their effects on the Nln conformational landscape and kinetics. Two of these sites have opposing functional outcomes: Binding inside the interhelical channel favors closed conformations by slowing down channel opening, thus allowing the substrates to orient favorably for the catalytic reaction, while binding at the exterior region of the channel stabilizes open states, potentially facilitating both substrate entry and cleaved product release. These findings suggest a possibility of a multi-site allosteric activation model in which distinct binding locations selectively modulate different steps within a catalytic cycle. This framework provides a structural and kinetic model for the action of small molecule Nln activators, offering insight into the design of cerebro-protective therapeutics that reduce neuropeptide accumulation after ischemic injury.

biophysics↗

bioRxiv2025

Determinants of Improved CGRP Peptide Binding Kinetics Revealed by Enhanced Molecular Simulations

Peptides are desirable therapeutics due to their inherent potency, safety, cost-effectiveness and ability to engage large or more complex protein surfaces. Slower kinetics of protein-peptide (un)binding can directly influence their drug efficacy and duration of action, in part by improving plasma stability of the peptide. The CLR:RAMP1 complex and its endogenous agonist peptide CGRP are of particularly high interest because of their central role in migraine pathophysiology. A better understanding of peptide binding mechanisms is needed for the development of next-generation peptide-based drugs with optimized kinetic properties. In this study, we comparatively analyze constructs of native CGRP and "ssCGRP", an engineered variant with 430-fold longer residence time on the CLR:RAMP1 complex. Using large-scale computational resources and our high-dimensional weighted-ensemble algorithm, we then thoroughly sample and compare unbinding path ensembles for the two peptides. This elucidates the basis of the engineered residence time enhancement for ssCGRP and provides a detailed view of the intra- and intermolecular stabilizing interactions for both peptides in the bound ensemble and along the unbinding transition path. The bias-free nature of the sampling approach in combination with Markov state modeling allows for the calculation of committor values and the first analysis of protein-peptide binding transition state ensembles. Through analysis of the unbinding committor, we find that ssCGRP(27-37) also demonstrates enhanced ligand recapture of intermediate unbinding conformations and samples a more heterogeneous bound-state ensemble that entropically stabilizes the bound basin. This study shows the molecular determinants of peptide residence time at CLR:RAMP1 and provides valuable insight for the design of long-acting peptide therapeutics.

molecular biology↗

bioRxiv2025

Metabolic syndrome enhances SARS-CoV-2 disease severity and reduces mRNA vaccine efficacy in a mouse model

Metabolic syndrome (MetS) is a cluster of pathophysiological conditions linked to the disruption of metabolic processes associated with energy storage and consumption. Approximately one-third of adults in the United States are currently diagnosed with MetS. Patients with MetS experience higher mortality rates following SARS-CoV-2 infection and exhibit poor vaccine efficacy following influenza virus vaccination compared to metabolically healthy individuals. However, the specific impact of MetS on immune responses to SARS-CoV-2 infection and vaccination has not been widely studied. To address this gap, we utilized high-fat diet feeding to establish a murine model of MetS, in which mice exhibit the same diagnostic criteria for MetS as human patients. We then used high-fat diet-induced MetS mice and regular chow diet-fed wild-type mice to analyze immune responses to SARS-CoV-2 infection and vaccination. Following SARS-CoV-2 infection, we monitored mice for disease severity, measured levels of virally induced inflammation, and quantified viral titers in various tissues. Our results indicate that MetS mice exhibit accelerated mortality post-infection, accompanied by elevated mRNA levels of inflammatory cytokine transcripts at sites of infection. Additionally, MetS alters the degree of viral replication across various tissues. Furthermore, our vaccination studies revealed that MetS reduces the potency of vaccine-induced neutralizing antibodies against both the ancestral SARS-CoV-2 strain and the Delta variant. Overall, our findings suggest that MetS exacerbates SARS-CoV-2 disease severity and diminishes vaccine efficacy, underscoring the need for tailored strategies to protect individuals with MetS from severe outcomes following infection and vaccination. ImpactThis study represents the first detailed account of the failure to generate protective neutralizing antibody responses to SARS-CoV-2 in mice with metabolic syndrome (MetS) following vaccination. The insights gained from this research inform future vaccine design and aid in identifying individuals at greater risk of breakthrough infections. By specifically isolating the risk associated with MetS, rather than obesity alone, these findings lay the groundwork for future investigations aimed at enhancing immune responses in individuals with MetS. This work is highly relevant to a broad audience, as it addresses a critical unmet need in vaccine development and provides essential guidance for the rational design of vaccines to protect vulnerable populations affected by MetS.

immunology↗

bioRxiv2023

Adrenomedullin 2/intermedin is a slow off-rate, long-acting endogenous agonist of theadrenomedullin2 G protein-coupled receptor

The signaling peptides adrenomedullin 2/intermedin (AM2/IMD), adrenomedullin (AM), and CGRP have overlapping and distinct functions in the cardiovascular, lymphatic, and nervous systems by activating three shared receptors comprised of the class B GPCR CLR in complex with a RAMP1, -2, or -3 modulatory subunit. Here, we report that AM2/IMD, which is thought to be a non-selective agonist, is kinetically selective for CLR-RAMP3, known as the AM2R. AM2/IMD-AM2R elicited substantially longer duration cAMP signaling than the eight other peptide-receptor combinations due to AM2/IMD slow off-rate binding kinetics. The regions responsible for the slow off-rate were mapped to the AM2/IMD mid-region and the RAMP3 extracellular domain. MD simulations revealed how these bestow enhanced stability to the complex. Our results uncover AM2/IMD-AM2R as a cognate pair with unique temporal features, define the mechanism of kinetic selectivity, and explain how AM2/IMD and RAMP3 collaborate to shape the signaling output of a clinically important GPCR.

biochemistry↗

bioRxiv2022

HSD3B1 is an Oxysterol 3β-Hydroxysteroid Dehydrogenase in Human Placenta

Most biologically active oxysterols have a 3{beta}-hydroxy-5-ene function in the ring system with an additional site of oxidation at C-7 or on the side-chain. In blood plasma oxysterols with a 7-hydroxy group are also observed with the alternative 3-oxo-4-ene function in the ring system formed by ubiquitously expressed 3{beta}-hydroxy-{Delta}5-C27-steroid oxidoreductase {Delta}5-isomerase, HSD3B7. However, oxysterols without a 7-hydroxy group are not substrates for HSD3B7 and are not usually observed with the 3-oxo-4-ene function. Here we report the unexpected identification of oxysterols in plasma derived from umbilical cord blood and blood from pregnant women taken before delivery at 37+ weeks of gestation, of side-chain oxysterols with a 3-oxo-4-ene function but no 7-hydroxy group. These 3-oxo-4-ene oxysterols were also identified in placenta, leading to the hypothesis that they may be formed by a previously unrecognised 3{beta}-hydroxy-{Delta}5-C27-steroid oxidoreductase {Delta}5-isomerase activity of HSD3B1, an enzyme which is highly expressed in placenta. Proof of principle experiments confirmed that HSD3B1 has this activity. We speculate that HSD3B1 in placenta is the source of the unexpected 3-oxo-4-ene oxysterols in cord and pregnant womens plasma and may have a role in controlling the abundance of biologically active oxysterols delivered to the fetus.

biochemistry↗

bioRxiv2021

Atomic-Resolution Prediction of Degrader-mediated Ternary Complex Structures by Combining Molecular Simulations with Hydrogen Deuterium Exchange

Targeted protein degradation (TPD) has emerged as a powerful approach in drug discovery for removing (rather than inhibiting) proteins implicated in diseases. A key step in this approach is the formation of an induced proximity complex, where a degrader molecule recruits an E3 ligase to the protein of interest (POI), facilitating the transfer of ubiquitin to the POI and initiating the proteasomal degradation process. Here, we address three critical aspects of the TPD process: 1) formation of the ternary complex induced by a degrader molecule, 2) conformational heterogeneity of the ternary complex, and 3) assessment of ubiquitination propensity via the full Cullin Ring Ligase (CRL) macromolecular assembly. The novel approach presented here combines experimental biophysical data--in this case hydrogen-deuterium exchange mass spectrometry (HDX-MS, which measures the solvent exposure of protein residues)--with all-atom explicit solvent molecular dynamics (MD) simulations aided by enhanced sampling techniques to predict structural ensembles of ternary complexes at atomic resolution. We present results demonstrating the efficiency, accuracy, and reliability of our approach to predict ternary structure ensembles using the bromodomain of SMARCA2 (SMARCA2BD) with the E3 ligase VHL as the system of interest. The simulations reproduce X-ray crystal structures - including prospective simulations validated on a new structure that we determined in this work (PDB ID: 7S4E) - with root mean square deviations (RMSD) of 1.1 to 1.6 [A]. The simulations also reveal a structural ensemble of low-energy conformations of the ternary complex within a broad energy basin. To further characterize the structural ensemble, we used snapshots from the aforementioned simulations as seeds for Hamiltonian replica exchange molecular dynamics (HREMD) simulations, and then perform 7.1 milliseconds of aggregate simulation time using Folding@home. The resulting free energy surface identifies the crystal structure conformation within a broad low-energy basin and the dynamic ensemble is consistent with solution-phase biophysical experimental data (HDX-MS and small-angle x-ray scattering, SAXS). Finally, we graft structures from the ternary complexes onto the full CRL and perform enhanced sampling simulations, where we find that differences in degradation efficiency can be explained by the proximity distribution of lysine residues on the POI relative to the E2-loaded ubiquitin. Several of the top predicted ubiquitinated lysine residues are validated prospectively through a ubiquitin mapping proteomics experiment.

biophysics↗

bioRxiv2021

A biosensor to gauge protein homeostasis resilience differences in the nucleus compared to cytosol of mammalian cells

An extensive network of chaperones and other proteins maintain protein homeostasis and guard against inappropriate protein aggregation that is a hallmark of neurodegenerative diseases. Using a fluorescence resonance energy-based biosensor that simultaneously reports on intact cellular chaperone holdase activity and detrimental aggregation propensity, we investigated the buffering capacity of the systems managing protein homeostasis in the nucleus of the human cell line HEK293 compared to the cytosol. We found that the nucleus showed lower net holdase activity and reduced capacity to suppress protein aggregation, suggesting that the nuclear quality control resources are less effective compared to those in the cytosol. Aggregation of mutant huntingtin exon 1 protein (Httex1) in the cytosol appeared to deplete cytosolic chaperone supply by depleting holdase activity. Unexpectedly, the same stress increased holdase activity in the nucleus suggesting that proteostasis stress can trigger a rebalance of chaperone supply in different subcellular compartments. Collectively the findings suggest the cytosol has more capacity to manage imbalances in proteome foldedness than the nucleus, but chaperone supply can be redirected into the nucleus under conditions of proteostasis stress caused by cytosolic protein aggregation.

biochemistry↗

bioRxiv2021

Perturbation of ACE2 structural ensembles by SARS-CoV-2 spike protein binding

The human ACE2 enzyme serves as a critical first recognition point of coronaviruses, including SARS-CoV-2. In particular, the extracellular domain of ACE2 interacts directly with the S1 tailspike protein of the SARS-CoV-2 virion through a broad protein-protein interface. Although this interaction has been characterized by X-ray crystallography and Cryo-EM, these structures do not reveal significant differences in ACE2 structure upon S1 protein binding. In this work, using several all-atom molecular dynamics simulations, we show persistent differences in ACE2 structure upon binding. These differences are determined with the Linear Discriminant Analysis (LDA) machine learning method and validated using independent training and testing datasets, including long trajectories generated by D. E. Shaw Research on the Anton 2 supercomputer. In addition, long trajectories for 78 potent ACE2-binding compounds, also generated by D. E. Shaw Research, were projected onto the LDA classification vector in order to determine whether the ligand-bound ACE2 structures were compatible with S1 protein binding. This allows us to predict which compounds are "apo-like" vs "complex-like", as well as to pinpoint long-range ligand-induced allosteric changes of ACE2 structure.

biophysics↗

bioRxiv2020

Characterization of cells susceptible to SARS-COV-2 and methods for detection of neutralizing antibody by focus forming assay

The SARS-CoV-2 outbreak and subsequent COVID-19 pandemic have highlighted the urgent need to determine what cells are susceptible to infection and for assays to detect and quantify SARS-CoV-2. Furthermore, the ongoing efforts for vaccine development have necessitated the development of rapid, high-throughput methods of quantifying infectious SARS-CoV-2, as well as the ability to screen human polyclonal sera samples for neutralizing antibodies against SARS-CoV-2. To this end, our lab has adapted focus forming assays for SARS-CoV-2 using Vero CCL-81 cells, referred to in this text as Vero WHO. Using the focus forming assay as the basis for screening cell susceptibility and to develop a focus reduction neutralization test. We have shown that this assay is a sensitive tool for determining SARS-CoV-2 neutralizing antibody titer in human, non-human primate, and mouse polyclonal sera following SARS-CoV-2 exposure. Additionally, we describe the viral growth kinetics of SARS-CoV-2 in a variety of different immortalized cell lines and demonstrate via human ACE2 and viral spike protein expression that these cell lines can support viral entry and replication.

pathology↗

bioRxiv2020

mRNA induced expression of human angiotensin-converting enzyme 2 in mice for the study of the adaptive immune response to severe acute respiratory syndrome coronavirus 2

The novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic resulting in nearly 20 million infections across the globe, as of August 2020. Critical to the rapid evaluation of vaccines and antivirals is the development of tractable animal models of infection. The use of common laboratory strains of mice to this end is hindered by significant divergence of the angiotensin-converting enzyme 2 (ACE2), which is the receptor required for entry of SARS-CoV-2. In the current study, we designed and utilized an mRNA-based transfection system to induce expression of the hACE2 receptor in order to confer entry of SARS-CoV-2 in otherwise non-permissive cells. By employing this expression system in an in vivo setting, we were able to interrogate the adaptive immune response to SARS-CoV-2 in type 1 interferon receptor deficient mice. In doing so, we showed that the T cell response to SARS-CoV-2 is enhanced when hACE2 is expressed during infection. Moreover, we demonstrated that these responses are preserved in memory and are boosted upon secondary infection. Interestingly, we did not observe an enhancement of SARS-CoV-2 specific antibody responses with hACE2 induction. Importantly, using this system, we functionally identified the CD4+ and CD8+ peptide epitopes targeted during SARS-CoV-2 infection in H2b restricted mice. Antigen-specific CD8+ T cells in mice of this MHC haplotype primarily target peptides of the spike and membrane proteins, while the antigen-specific CD4+ T cells target peptides of the nucleocapsid, membrane, and spike proteins. The functional identification of these T cell epitopes will be critical for evaluation of vaccine efficacy in murine models of SARS-CoV-2. The use of this tractable expression system has the potential to be used in other instances of emerging infections in which the rapid development of an animal model is hindered by a lack of host susceptibility factors.

immunology↗

bioRxiv2020

Membrane-mediated ligand unbinding of the PK-11195 ligand from the translocator protein (TSPO)

The translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor, is of longstanding medical interest as both a biomarker for neuroinjury and a potential drug target for neuroinflammation and other disorders. Recently it was shown that ligand residence time is a key factor determining steroidogenic efficacy of TSPO-binding compounds. This spurs interest in simulations of (un)binding pathways of TSPO ligands, which could reveal the molecular interactions governing ligand residence time. In this study, we use a weighted ensemble algorithm to determine the unbinding pathway for different poses of PK-11195, a TSPO ligand used in neuroimaging. In contrast with previous studies, our results show that PK-11195 does not dissociate directly into the solvent but instead dissociates via the lipid membrane by going between the transmembrane helices. We analyze this path ensemble in detail, constructing descriptors that can facilitate a general understanding of membrane-mediated ligand binding. We construct a Markov state model using additional straightforward simulations to determine pose stability and kinetics of ligand unbinding. Together we combine over 40 {micro}s of trajectory data to form a coherent picture of the ligand binding landscape. We find that all poses are able to interconvert before unbinding, leading to single mean first passage time estimate for all starting poses which roughly agrees with the experimental quantity. The ligand binding transition state predicted by our combined model occurs when PK-11195 is already in the membrane and does not involve direct ligand-protein interactions. This has implications for the design of new long residence-time TSPO ligands. SIGNIFICANCEKinetics-oriented drug design is an emerging objective in drug discovery. However, while ligand binding affinity (or the binding free energy) is purely a function of the bound and unbound states, the binding kinetics depends on the nature of the paths by which the (un)binding occurs. This underscores the importance of approaches that can reveal information about the ensemble of (un)binding paths. Here we used advanced molecular dynamics approaches to study the unbinding of PK-11195 from TSPO and find it dissociates from the protein by dissolving into the membrane, and that the transition state occurs after the PK-11195 molecule has already separated from TSPO. These results motivate the design of future long-residence time TSPO ligands that destabilize the membrane-solvated transition state.

biophysics↗

bioRxiv2019

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange--while displaying very small variance--can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.

biophysics↗

bioRxiv2019

Chk1 Phosphorylates Cdh1 to Promote SCFβTRCP-Dependent Degradation of Cdh1 During S-Phase

The interplay of the Anaphase-Promoting Complex/Cyclosome (APC/C) and Skp1-Cul1-F-box (SCF) E3 ubiquitin ligases is necessary for controlling cell cycle transitions and checkpoint responses, which are critical for maintaining genomic stability. Yet, the mechanisms underlying the coordinated activity of these enzymes are not completely understood. Recently, Cyclin A- and Plk1- mediated phosphorylation of Cdh1 was demonstrated to trigger its ubiquitination by SCF{beta}TRCP at the G1/S transition. However, Cyclin A-Cdk and Plk1 activities peak in G2 so it is unclear why Cdh1 is targeted at G1/S but not in G2. Here, we show that phosphorylation of Cdh1 by Chk1 contributes to its recognition by SCF{beta}TRCP, promotes efficient S-phase entry, and is important for cellular proliferation. Conversely, Chk1 activity in G2 inhibits Cdh1 accumulation. Overall, these data suggest a model whereby the rise and fall of Chk1 activity is a key factor in the feedback loop between APC/CCdh1 and the replication machinery that enhances the G1/S and S/G2 transitions, respectively.

cell biology↗

bioRxiv2018

Mapping the ligand binding landscape

The interaction between a ligand and a protein involves a multitude of conformational states. To achieve a particular deeply-bound pose the ligand must search across a rough free energy landscape, with many metastable minima. Creating maps of the ligand binding landscape is a great challenge, as binding and release events typically occur on timescales that are beyond the reach of molecular simulation. The WExplore enhanced sampling method is well-suited to build these maps, as it is designed to broadly explore free-energy landscapes, and is capable of simulating ligand release pathways that occur on timescales as long as minutes. WExplore also uses only unbiased trajectory segments, allowing for the construction of Markov state models (MSM) and conformation space networks that combine the results of multiple simulations. Here we use WExplore to study two bromodomain-inhibitor systems using multiple docked starting poses (Brd4-MS436 and Baz2B-ICR7), and synthesize our results using a series of MSMs using time-lagged independent component analysis. Ranking the starting poses by exit rate agrees with the crystal structure pose in both cases. We also predict the most stable pose using the equilibrium populations from the MSM, but find that the prediction is not robust as a function of MSM parameters. The simulated trajectories are synthesized into network models that visualize the entire binding landscape for each system, and we examine transition paths between deeply-bound stable states. We find that, on average, transitions between deeply bound states convert through the unbound state 81% of the time, implying a trial-and-error approach to ligand binding. We conclude with a discussion of the implications of this result for both kinetics-based drug discovery and virtual screening pipelines that incorporate molecular dynamics.

biophysics↗