Biology subjects

Parks, J. M.

Publications and source records attributed to Parks, J. M..

13 recordsLinked to original sources

bioRxiv2026

Benchmarking AI Protein Structure Predictors Reveals a Persistent Bias in Multi-State Proteins

Protein structure predictors achieve high single-state accuracy, but it remains unclear whether they can recover functionally relevant conformational ensembles or account for the presence of ligands and/or binding partners. Here, we benchmark AlphaFold3, Boltz-2, Chai-1, and BioEmu on four canonical multi-state proteins (Pf-MATE, LAO, SecA, and {beta}2AR), quantifying state bias and sampling breadth against experimental reference structures. Models frequently default to a dominant state represented in the PDB; small-molecule ligands have weak or inconsistent effects, while large protein partners drive clear conformational switching between states. Multiple sequence alignment (MSA)-based approaches (AF-Cluster and random subsampling) recapitulate similar biases, indicating that this behavior is not unique to newer architectures. These results underscore current limitations for multi-state protein structure prediction and structure-guided ligand discovery. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/737860v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@278cc1org.highwire.dtl.DTLVardef@8a0b66org.highwire.dtl.DTLVardef@f28a21org.highwire.dtl.DTLVardef@14ab675_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Structural and Oligomeric Characterization of Substrate- and Product-selective Nylon Hydrolases

Enzymatic degradation of synthetic polymers has attracted broad interest because it offers environmental and manufacturing advantages compared to traditional mechanical and chemical breakdown approaches. Enzymes are highly specific and reaction conditions are generally aqueous and require low pressure and temperature, resulting in lower energy consumption and lower chemical waste production. Here we report the biochemical and structural characterization of three newly discovered enzymes capable of nylon hydrolysis: Nyl10, Nyl12 and Nyl50. Using solution characterization techniques, we found that the enzymes adopt a single oligomeric state consistent with a tetramer over a wide range of concentrations. X-ray crystallographic structures of all three enzymes support the association into tetramers. Comparison of ligand-bound X-ray crystal structures of Nyl10 and Nyl12 with the previously determined structure of Nyl50 identified key structural determinants involved in ligand binding. Noticeably, a flexible loop found in several polyamide degrading enzymes is observed to flip towards (closed conformation) and away (open conformation) from the active site upon ligand binding. Analysis of adduct and surrogate substrate-bound enzyme complex structures provide a model for substrate binding directionality. Finally, activity assays showed that both Nyl10 and Nyl12 can hydrolyze ester bonds, and that Nyl12 has the highest activity toward PA66, identifying it as the best candidate for protein engineering for efficient nylon hydrolysis.

biochemistry↗

bioRxiv2025

IRIS: A Machine Learning-Based Pose Re-Ranking Tool for RNA-Ligand Docking

RNA-ligand docking remains challenging, due in part to intrinsic properties of RNA such as structural flexibility and a highly charged phosphate backbone. rDock, a widely used RNA docking program, can generate ligand poses close to the experimental structure, but its scoring function frequently fails to rank these poses above less accurate alternatives. To supplement rDock, here we introduce the Intelligent RNA Interaction Scorer (IRIS), a regression model leveraging physicochemical and interaction-based features and trained on the largest dataset of experimental nucleic acid-ligand complexes compiled to date (1,356 structures). IRIS improves rDock RNA-ligand pose ranking relative to the use of rDock scores alone. We find that at least one of the 100 top generated poses for any given complex is within 2.0 [A] RMSD of the native pose in 79.4% of test complexes. Of these 79.4%%, the default rDock scoring function ranks the correct pose first in 40.2% of cases. IRIS improves this latter fraction to 52.7% and increases the success rate for selecting a near-native pose among the top five ranked poses from 55.4% to 73.2%. IRIS thus significantly enhances pose ranking accuracy and can be seamlessly integrated into docking pipelines to refine ligand poses in RNA-targeted drug discovery.

molecular biology↗

bioRxiv2022

Conformational restriction shapes inhibition of a multidrug efflux adaptor protein

Membrane efflux pumps play a major role in bacterial multidrug resistance. The tripartite multidrug efflux pump system from Escherichia coli, AcrAB-TolC, is a target for inhibition to lessen resistance development and restore antibiotic efficacy, with homologs in other ESKAPE pathogens. Here, we rationalize a mechanism of inhibition against the periplasmic adaptor protein, AcrA, using a combination of hydrogen/deuterium exchange mass spectrometry, cellular efflux assays, and molecular dynamics simulations. We define the structural dynamics of AcrA and find that an inhibitor can inflict long-range stabilisation across all four of its domains, whereas an interacting efflux substrate has minimal effect. Our results support a model where an inhibitor forms a molecular wedge within a cleft between the lipoyl and {beta} domains of AcrA, diminishing its conformational transmission of drug-evoked signals from AcrB to TolC. This work provides molecular insights into multidrug adaptor protein function which could be valuable for developing antimicrobial therapeutics.

biochemistry↗

bioRxiv2022

Transcriptional control of hgcAB by an ArsR-like regulator in Pseudodesulfovibrio mercurii ND132

The hgcAB gene pair encodes mercury (Hg) methylation capability in a diverse group of microorganisms, but its evolution and transcriptional regulation remain unknown. Working from the possibility that the evolutionary function of HgcAB may not be Hg methylation, we test a possible link to arsenic resistance. Using model Hg-methylator Pseudodesulfovibrio mercurii ND132, we specifically evaluated transcriptional control of hgcAB by a putative ArsR encoded upstream and co-transcribed with hgcAB. This regulator shares homology with ArsR repressors of arsenic resistance and S-adenosyl-homocysteine (SAH) responsive regulators of methionine biosynthesis but is distinct from other ArsR/SahR in Pseudodesulfovibrio mercurii ND132. Using qPCR and RNA-seq analyses we confirmed this ArsR regulates hgcAB transcription, and is responsive to arsenic and SAH. Additionally, RNA-seq indicated a possible link between hgcAB activity and arsenic transformations by Pseudodesulfovibrio mercurii ND132, with significant up-regulation of other ArsR-regulated arsenic resistance operons alongside hgcAB. Interestingly, wild-type ND132 was less sensitive to AsV (but not AsIII) than an hgcAB knockout strain, supporting the idea that hgcAB may be linked to arsenic resistance. Arsenic significantly impacted Hg-methylation rates by ND132, however, responses varied with culture conditions. Differences in growth and overall metabolic activity did not account for arsenic impacts on methylation. One goal of this research is to better predict MeHg production in nature. However, we found that hgcAB gene and transcript abundance was not a good predictor of Hg-methylation rates. Our finding that hgcAB activity is linked to arsenic may hold clues to the possible environmental drivers of horizontal transfer of hgcAB. IMPORTANCEThis work reveals a link between microbial mercury methylation and arsenic resistance and may hold clues to the evolution of mercury methylation genes (hgcAB). Microbes with hgcAB produce methylmercury, a strong neurotoxin that readily accumulates in the food web. This study addresses a critical gap in our understanding about the environmental factors that control hgcAB expression. We show that hgcAB expression is controlled by an ArsR-like regulator responsive to both arsenic and S-adenosyl-homocysteine in our model organism, Pseudodesulfovibrio mercurii ND132. Exposure to arsenic also significantly impacted Pseudodesulfovibrio mercurii ND132 mercury methylation rates. However, expression of hgcAB was not always a good predictor of Hg methylation rates, highlighting the roles of Hg bioavailability and other biochemical mechanisms in methylmercury production. This study improves our understanding of the controls on hgcAB expression which is needed to better predict environmental methylmercury production.

microbiology↗

bioRxiv2021

Predicting direct physical interactions in multimeric proteins with deep learning

Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the same neural network models from AF2 developed for single protein sequences can be adapted to predict the structures of multimeric protein complexes without retraining. In contrast to common approaches, our method, AF2Complex, does not require paired multiple sequence alignments. It achieves higher accuracy than some complex protein-protein docking strategies and provides a significant improvement over AF-Multimer, a new development of AlphaFold for multimeric proteins. Moreover, we introduce metrics for predicting direct protein-protein interactions between arbitrary protein pairs and validate AF2Complex on some challenging benchmark sets and the E. coli proteome. Lastly, using the cytochrome c biogenesis system I as an example, we present high-confidence models of three sought-after assemblies formed by eight members of this system.

bioinformatics↗

bioRxiv2021

Core cysteine residues in the PAN domain are critical for HGF/c-MET signaling

The Plasminogen-Apple-Nematode (PAN) domain, with a core of four to six cysteine residues, is found in > 28,000 proteins across 959 genera but its role in protein function is not fully understood. The PAN domain was initially characterized to be present in numerous proteins including hepatocyte growth factor (HGF). Dysregulation of HGF-mediated signaling results in numerous deadly cancers. All biological impacts of HGF in cell proliferation are triggered by binding of HGF to its cell surface receptor, cellular mesenchymal-epidermal transition (c-MET). Here, we show that four PAN domain cysteine residues are essential for HGF/c-MET signaling. Mutating these residues resulted in retardation of perinuclear localization, cellular internalization of HGF and its receptor, c-MET, and c-MET ubiquitination. Our observations indicate that the PAN domain of HGF is required for the c-MET binding and subsequent c-MET autophosphorylation and phosphorylation of its downstream targets, protein kinase B (AKT), extracellular signal-regulated kinase (ERK), and signal transducer and activator of transcription 3 (STAT3). Furthermore, transcriptional activation of HGF/c-MET signaling-related genes including matrix metalloproteinase-9 (MMP9), ETS translocation variant 1, 4, and 5 (ETV1, ETV4, ETV5), and early growth response 1 (EGR1) was impaired and cell proliferation was attenuated. These results suggest that core cysteine residues in the PAN domain are critical for HGF/c-MET interaction, c-MET mediated signal transduction, and cell survival. Thus, targeting the PAN domain of HGF may represent a mechanism for selectively regulating the binding and activation of the c-MET pathway. SignificanceHGF/c-MET signaling induces multifunctional cellular responses. Dysregulation of HGF/c-MET signaling cascade can lead to tumorigenesis by transforming normal cells to tumor cells. This work defines the importance of core cysteine residues in the PAN domain of HGF in downstream activation of HGF/c-MET signaling. To understand the role of cysteines in the PAN domain, PAN mutants of HGF were used to stimulate c-MET signaling in cells and the impact was delineated by determining phosphorylation and transcription of downstream targets. Mutations in core cysteines in the HGF-PAN domain completely blocked downstream phosphorylation and perinuclear accumulation of c-MET. These results suggest an indispensable role for the cysteine-rich PAN domain in HGF/c-MET interaction and could set the stage for future therapies that selectively disrupt the MET signaling cascade with limited off-target effects in tumors overexpressing HGF/c-MET.

cell biology↗

bioRxiv2021

Critical interactions for SARS-CoV-2 spike protein binding to ACE2 identified by machine learning

Both SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor. Based on high-resolution structures, the two viruses bind in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Here we have used molecular dynamics (MD) simulations, machine learning (ML), and free energy perturbation (FEP) calculations to elucidate the differences in RBD binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

biophysics↗

bioRxiv2020

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of Mpro, a cysteine protease, have been determined, facilitating structure-based drug design. Mpro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, Mpro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nu-cleophile Cys145 have been debated in previous studies of SARS-CoV Mpro, but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 Mpro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of Mpro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an -ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N{delta} (HD) and N{epsilon} (HE) protonation of His41 and His164, respectively, the -ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 Mpro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

biophysics↗

bioRxiv2020

Immune Selection Pressure Contributes to Pancreatic Cancer Immune Evasion

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the United States. Pancreatic tumors are minimally infiltrated by T cells and are largely refractory to immunotherapy. Accordingly, the role of T cell immunity in pancreatic cancer has been somewhat overlooked. Here, we hypothesized that immune evasion in pancreatic cancer is induced in response to T cell-based immune selection pressure, and that understanding how pancreatic tumors respond to immune attack may facilitate the development of more effective therapeutic strategies. We now provide the first evidence that T cell-dependent host immune responses induce a PDAC-derived myeloid mimicry phenomenon and stimulate immune evasion. mT3-2D cells derived from a Kras+/LSL-G12D; Trp53+/LSL-R172H; Pdx1-Cre (KPC) mouse model of pancreatic cancer were grown in immunocompetent and immunodeficient C57BL/6 mice, and analyzed to determine the impacts of adaptive immunity specifically on malignant epithelial cells as well as on whole tumors. We found that immune selection pressure, via signal transducer and activator of transcription 1 (STAT1), stimulates malignant epithelial pancreatic cells to induce the expression of genes typically expressed by myeloid cells and alters intratumoral immunosuppressive myeloid cell profiles. Targeting the Janus Kinase (JAK)/STAT signaling pathway using the FDA approved drug, ruxolitinib, overcomes these tumor-protective responses and improves anti-PD1 antibody therapeutic efficacy. These findings provide future directions for treatments that specifically disable this mechanism of resistance in PDAC.

cancer biology↗

bioRxiv2019

Hotspot coevolution at protein-protein interfaces is a key identifier of native protein complexes

Protein-protein interactions play a key role in mediating numerous biological functions, with more than half the proteins in living organisms existing as either homo- or hetero-oligomeric assemblies. Protein subunits that form oligomers minimize the free energy of the complex, but exhaustive computational search-based docking methods have not comprehensively addressed the protein docking challenge of distinguishing a natively bound complex from non-native forms. In this study, we propose a scoring function, KFC-E, that accounts for both conservation and coevolution of putative binding hotspot residues at protein-protein interfaces. For a benchmark set of 53 bound complexes, KFC-E identifies a near-native binding mode as the top-scoring pose in 38% and in the top 5 in 55% of the complexes. For a set of 17 unbound complexes, KFC-E identifies a near-native pose in the top 10 ranked poses in more than 50% of the cases. By contrast, a scoring function that incorporates information on coevolution at predicted non-hotspots performs poorly by comparison. Our study highlights the importance of coevolution at hotspot residues in forming natively bound complexes and suggests a novel approach for coevolutionary scoring in protein docking.\n\nAuthor SummaryA fundamental problem in biology is to distinguish between the native and non-native bound forms of protein-protein complexes. Experimental methods are often used to detect the native bound forms of proteins but, are demanding in terms of time and resources. Computational approaches have proven to be a useful alternative; they sample the different binding configurations for a pair of interacting proteins and then use an heuristic or physical model to score them. In this study we propose a new scoring approach, KFC-E, which focuses on the evolutionary contributions from a subset of key interface residues (hotspots) to identify native bound complexes. KFC-E capitalizes on the wealth of information in protein sequence databases by incorporating residue-level conservation and coevolution of putative binding hotspots. As hotspot residues mediate the binding energetics of protein-protein interactions, we hypothesize that the knowledge of putative hotspots coupled with their evolutionary information should be helpful in the identification of native bound protein-protein complexes.

bioinformatics↗

bioRxiv2019

Kinetics of enzymatic mercury methylation at nanomolar concentrations catalyzed by HgcAB

Methylmercury (MeHg) is a potent neurotoxin that bioaccumulates in fish. MeHg is generated by anaerobic bacteria and archaea possessing the gene pair hgcAB. Although bacterial mercury (Hg) methylation has been characterized in vivo, the specific role of HgcAB in catalyzing Hg methylation is not well understood. Here we report the kinetics of HgcAB-mediated Hg methylation in cell lysates of Desulfovibrio desulfuricans ND132 at nanomolar Hg concentrations. The enzymatic Hg methylation mediated by HgcAB is highly oxygen-sensitive, irreversible, and follows Michaelis-Menten kinetics with an apparent KM of 3.2 nM and Vmax of 19.7 fmol{middle dot}min-1{middle dot}mg-1 total protein for the substrate Hg(II). Although the abundance of HgcAB in the cell lysates is extremely low, Hg(II) was quantitatively converted to MeHg at subnanomolar substrate concentrations. Supplementation with ATP, methyltetrahydrofolate, or pyruvate did not enhance MeHg production under the experimental conditions. Insight into the kinetics of Hg methylation catalyzed by HgcAB advances our understanding of the complex global Hg cycle.

biochemistry↗

bioRxiv2018

Horizontal transfer of a pathway for coumarate catabolism unexpectedly inhibits purine nucleotide biosynthesis

Metabolic pathways are frequently transferred between bacterial strains in the environment through horizontal gene transfer (HGT), yet laboratory engineering to introduce new metabolic pathways often fails. Successful use of a pathway requires co-evolution of both pathway and host, and these interactions may be disrupted upon transfer to a new host. Here we show that two different pathways for catabolism of coumarate failed to function when initially transferred into Escherichia coli. Using laboratory evolution, we elucidated the factors limiting activity of the newly-acquired pathways and the modifications required to overcome these limitations. Both pathways required mutations to the host to enable effective growth with coumarate, but the necessary mutations differed depending on the chemistry and intermediates of the pathways. In one case, an intermediate inhibited purine nucleotide biosynthesis, and this inhibition was relieved by single amino acid mutations to IMP dehydrogenase. A strain that natively contains this coumarate catabolism pathway, Acinetobacter baumannii, is already resistant to inhibition by the relevant intermediate, suggesting that natural pathway transfers have faced and overcome similar challenges. These discoveries will aid in our understanding of HGT and ability to predictably engineer metabolism.\n\nThis manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

microbiology↗