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Reported are the results of meta-analyses of data derived collectively from a sample of 56 published research studies on electric response audiometry (ERA) using auditory steady-state responses (ASSRs). Several specific methodological issues were examined and hypotheses were posited to rigorously test common conclusions drawn from the ASSR literature on the accuracy of ASSR-ERA. Explanatory variables for analyses were type of population (normally hearing and hearing-impaired), type of modulation, number of sweeps acquired during response analysis, electrode montage, and modulation rate (80 vs. 40 Hz). No explanatory variables were found to be significantly related to the degree of disparity between thresholds obtained by ASSR-ERA versus behavioral audiometry in the normally hearing population. Conversely, all but one explanatory variable (i.e. electrode montage) was found to be significantly related to mean threshold differences in the hearing-impaired and combined populations. Results both substantiate some of common conclusions drawn from the literature but call others into question, helping to identify those methodological issues which appear to, or not to, significantly affect the accuracy of estimating threshold using ASSR measurement. In addition to these findings, another practical outcome of this study was the development of various summary tables of the data analysed from the literature sampled. [ABSTRACT FROM AUTHOR]

Electrocochleography (ECochG) has evolved as an important tool in the diagnosis/assessment/monitoring of Ménière's disease/endolymphatic hydrops (MD/ELH). This manuscript provides an update on the use of ECochG for these purposes. The material presented includes descriptions of the components of the electrocochleogram; ECochG recording approaches and parameters; how to prepare for an exam, including subject/patient considerations; construction and placement of a tympanic membrane recording electrode; and interpretation the electrocochleogram. Various approaches aimed at improving ECochG's sensitivity and specificity to MD/ELH also are described. These approaches go beyond simple measurement of the now-conventional summating potential (SP)/action potential (AP) magnitude ratio to include the SP magnitude to tonebursts, the SP/AP area ratio, and the AP latency difference to clicks of opposing polarity. [ABSTRACT FROM AUTHOR]

The aims of this work were to characterize the electrophysiologic response obtained by measurement of the auditory steady-state response (ASSR) in patients with a cochlear implant (MXM Digisonic) and to study the relationship between the subjective thresholds of the implantees and those estimated using electrical auditory steady-state response (ASSR)-based objective audiometry. Five subjects were examined with the use of four carrier frequencies-600, 1000, 2000 and 3500 Hz--modulated at frequencies between 70 and 85 Hz, a particular frequency of modulation being represented at a specific electrode (for each carrier frequency) as a particular pulse-width modulation frequency. The protocol consisted of testing output and thresholds for different overall pulse durations for several stimulus (pulse) intensities, rendering multiple threshold measures (in duration) for each subject tested. The non-linearity of response growth, as a function of duration, provided the basis for teasing apart physiologic response and electrical artefact in the supra-threshold recorded responses. Thresholds estimated with use of the electrical ASSR demonstrated reasonably good agreement with the subjective thresholds. The results obtained thus demonstrated the efficacy of the approach and are encouraging for further advances in cochlear implant applications. [ABSTRACT FROM AUTHOR]

The chief complaint of individuals with hearing impairment is difficulty hearing in noise, with directional microphones emerging as the most capable remediation. Our purpose was to determine the impact of directional microphones on localization disability and concurrent handicap. Fifty-seven individuals participated unaided and then in groups of 19, using omni-directional microphones, directional-microphones, or toggle-switch equipped amplification. The outcome measure was a localization disabilities and handicaps questionnaire. Comparisons between the unaided group versus the aided groups, and the directional-microphone groups versus the other two aided groups revealed no significant differences. None of the microphone schemes either increased or decreased self-perceived localization disability or handicap. Objective measures of localization ability are warranted and if significance is noted, clinicians should caution patients when moving in their environment. If no significant objective differences exist, in light of the subjective findings in this investigation concern over decreases in quality of life and safety with directional microphones need not be considered. [ABSTRACT FROM AUTHOR]

Psychometric evaluations were performed on a self-perceived localization disabilities and handicaps questionnaire. Twenty individuals with normal hearing bilaterally, twenty with profound unilateral hearing impairment (UHI), and ten with any degree of bilateral hearing impairment participated. Each subject completed the questionnaire. Comparisons of the responses of the subjects with normal hearing and those with UHI revealed significant differences among the groups for both disabilities and handicaps, establishing construct validity. Cronbach's Alpha correlational analyses of the responses of all subjects with hearing impairment revealed correlations of .900 (disabilities) and .800 (handicaps), establishing internal consistency. Each participant with hearing impairment was asked to complete the questionnaire again after three weeks. Pearson's correlational analyses of the responses at time one versus time two revealed correlations of .900 (disabilities) and .700 (handicaps), establishing test/retest reliability. This questionnaire is an appropriate tool for investigating the self-perceived localization disabilities and handicaps of individuals with hearing impairment. [ABSTRACT FROM AUTHOR]

We here introduce Ensemble Optimizer (EnOpt), a machine-learning tool to improve the accuracy and interpretability of ensemble virtual screening (VS). Ensemble VS is an established method for predicting protein/small-molecule (ligand) binding. Unlike traditional VS, which focuses on a single protein conformation, ensemble VS better accounts for protein flexibility by predicting binding to multiple protein conformations. Each compound is thus associated with a spectrum of scores (one score per protein conformation) rather than a single score. To effectively rank and prioritize the molecules for further evaluation (including experimental testing), researchers must select which protein conformations to consider and how best to map each compound's spectrum of scores to a single value, decisions that are system-specific. EnOpt uses machine learning to address these challenges. We perform benchmark VS to show that for many systems, EnOpt ranking distinguishes active compounds from inactive or decoy molecules more effectively than traditional ensemble VS methods. To encourage broad adoption, we release EnOpt free of charge under the terms of the MIT license., (© 2024. The Author(s).)

Pathogenic bacteria rely on secreted virulence factors to cause disease in susceptible hosts. However, in Gram-positive bacteria, the mechanisms underlying secreted protein activation and regulation post-membrane translocation remain largely unknown. Using proteomics, we identified several proteins that are dependent on the secreted chaperone PrsA2. We followed with phenotypic, biochemical, and biophysical assays and computational analyses to examine the regulation of a detected key secreted virulence factor, listeriolysin O (LLO), and its interaction with PrsA2 from the bacterial pathogen Listeria monocytogenes ( Lm ). Critical to Lm virulence is internalization by host cells and the subsequent action of the cholesterol-dependent pore-forming toxin, LLO, which enables bacterial escape from the host cell phagosome. Since Lm is a Gram-positive organism, the space between the cell membrane and wall is solvent exposed. Therefore, we hypothesized that the drop from neutral to acidic pH as the pathogen is internalized into a phagosome is critical to regulating the interaction of PrsA2 with LLO. Here, we demonstrate that PrsA2 directly interacts with LLO in a pH-dependent manner. We show that PrsA2 protects and sequesters LLO under neutral pH conditions where LLO can be observed to aggregate. In addition, we identify molecular features of PrsA2 that are required for interaction and ultimately the folding and activity of LLO. Moreover, protein-complex modeling suggests that PrsA2 interacts with LLO via its cholesterol-binding domain. These findings highlight a mechanism by which a Gram-positive secretion chaperone regulates the secretion, stability, and folding of a pore-forming toxin under conditions relevant to host cell infection., Importance: Lm is a ubiquitous food-borne pathogen that can cause severe disease to vulnerable populations. During infection, Lm relies on a wide repertoire of secreted virulence factors including the LLO that enables the bacterium to invade the host and spread from cell to cell. After membrane translocation, secreted factors must become active in the challenging bacterial cell membrane-wall interface. However, the mechanisms required for secreted protein folding and function are largely unknown. Lm encodes a chaperone, PrsA2, that is critical for the activity of secreted factors. Here, we show that PrsA2 directly associates and protects the major Lm virulence factor, LLO, under conditions corresponding to the host cytosol, where LLO undergoes irreversible denaturation. Additionally, we identify molecular features of PrsA2 that enable its interaction with LLO. Together, our results suggest that Lm and perhaps other Gram-positive bacteria utilize secreted chaperones to regulate the activity of pore-forming toxins during infection., Competing Interests: The authors declare no conflict of interest.

Molecular docking advances early-stage drug discovery by predicting the geometries and affinities of small-molecule compounds bound to drug-target receptors, predictions that researchers can leverage in prioritizing drug candidates for experimental testing. Unfortunately, existing docking tools often suffer from poor usability, data security, and maintainability, limiting broader adoption. Additionally, the complexity of the docking process, which requires users to execute a series of specialized steps, often poses a substantial barrier for non-expert users. Here, we introduce MolModa, a secure, accessible environment where users can perform molecular docking entirely in their web browsers. We provide two case studies that illustrate how MolModa provides valuable biological insights. We further compare MolModa to other docking tools to highlight its strengths and limitations. MolModa is available free of charge for academic and commercial use, without login or registration, at https://durrantlab.com/molmoda., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

We present a novel and interpretable approach for assessing small-molecule binding using context explanation networks. Given the specific structure of a protein/ligand complex, our CENsible scoring function uses a deep convolutional neural network to predict the contributions of precalculated terms to the overall binding affinity. We show that CENsible can effectively distinguish active vs inactive compounds for many systems. Its primary benefit over related machine-learning scoring functions, however, is that it retains interpretability, allowing researchers to identify the contribution of each precalculated term to the final affinity prediction, with implications for subsequent lead optimization.

Convergent evolution is a widespread phenomenon. While there are many examples of convergent evolution at the phenotypic scale, convergence at the molecular level has been more difficult to identify. A classic example of convergent evolution across scales is that of the digestive lysozyme found in ruminants and Colobine monkeys. These herbivorous species rely on foregut fermentation, which has evolved to function more optimally under acidic conditions. Here, we explored if rodents with similar dietary strategies and digestive morphologies have convergently evolved a lysozyme with digestive functions. At the phenotypic level, we find that rodents with bilocular stomach morphologies exhibited a lysozyme that maintained higher relative activities at low pH values, similar to the lysozymes of ruminants and Colobine monkeys. Additionally, the lysozyme of Peromyscus leucopus shared a similar predicted protonation state as that observed in previously identified digestive lysozymes. However, we found limited evidence of positive selection acting on the lysozyme gene in foregut-fermenting species and did not identify patterns of convergent molecular evolution in this gene. This study emphasizes that phenotypic convergence need not be the result of convergent genetic modifications, and we encourage further exploration into the mechanisms regulating convergence across biological scales., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors have no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Bartter syndrome is a group of rare genetic disorders that compromise kidney function by impairing electrolyte reabsorption. Left untreated, the resulting hyponatremia, hypokalemia, and dehydration can be fatal, and there is currently no cure. Bartter syndrome type II specifically arises from mutations in KCNJ1, which encodes the renal outer medullary potassium channel, ROMK. Over 40 Bartter syndrome-associated mutations in KCNJ1 have been identified, yet their molecular defects are mostly uncharacterized. Nevertheless, a subset of disease-linked mutations compromise ROMK folding in the endoplasmic reticulum (ER), which in turn results in premature degradation via the ER associated degradation (ERAD) pathway. To identify uncharacterized human variants that might similarly lead to premature degradation and thus disease, we mined three genomic databases. First, phenotypic data in the UK Biobank were analyzed using a recently developed computational platform to identify individuals carrying KCNJ1 variants with clinical features consistent with Bartter syndrome type II. In parallel, we examined genomic data in both the NIH TOPMed and ClinVar databases with the aid of Rhapsody, a verified computational algorithm that predicts mutation pathogenicity and disease severity. Subsequent phenotypic studies using a yeast screen to assess ROMK function-and analyses of ROMK biogenesis in yeast and human cells-identified four previously uncharacterized mutations. Among these, one mutation uncovered from the two parallel approaches (G228E) destabilized ROMK and targeted it for ERAD, resulting in reduced cell surface expression. Another mutation (T300R) was ERAD-resistant, but defects in channel activity were apparent based on two-electrode voltage clamp measurements in X. laevis oocytes. Together, our results outline a new computational and experimental pipeline that can be applied to identify disease-associated alleles linked to a range of other potassium channels, and further our understanding of the ROMK structure-function relationship that may aid future therapeutic strategies to advance precision medicine., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: S. Sarangi is an employee of Paradigm4, and Z.W.P. is a former employee of Paradigm4., (Copyright: © 2023 Nguyen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

Given the ever-present threat of antibacterial resistance, there is an urgent need to identify new antibacterial drugs and targets. One such target is alanine racemase (Alr), an enzyme required for bacterial cell-wall biosynthesis. Alr is an attractive drug target because it is essential for bacterial survival but is absent in humans. Existing drugs targeting Alr lack specificity and have severe side effects. We here investigate alternative mechanisms of Alr inhibition. Alr functions exclusively as an obligate homodimer, so we probed seven conserved interactions on the dimer interface, distant from the enzymatic active site, to identify possible allosteric influences on activity. Using the Alr from Mycobacterium tuberculosis (MT) as a model, we found that the Lys261/Asp135 salt bridge is critical for catalytic activity. The Lys261Ala mutation completely inactivated the enzyme, and the Asp135Ala mutation reduced catalytic activity eight-fold. Further investigation suggested a potential drug-binding site near the Lys261/Asp135 salt bridge that may be useful for allosteric drug discovery., (© 2023 Wiley Periodicals LLC.)

Glucose is the preferred carbon source for most eukaryotes, and the first step in its metabolism is phosphorylation to glucose-6-phosphate. This reaction is catalyzed by hexokinases or glucokinases. The yeast Saccharomyces cerevisiae encodes three such enzymes, Hxk1, Hxk2, and Glk1. In yeast and mammals, some isoforms of this enzyme are found in the nucleus, suggesting a possible moonlighting function beyond glucose phosphorylation. In contrast to mammalian hexokinases, yeast Hxk2 has been proposed to shuttle into the nucleus in glucose-replete conditions, where it reportedly moonlights as part of a glucose-repressive transcriptional complex. To achieve its role in glucose repression, Hxk2 reportedly binds the Mig1 transcriptional repressor, is dephosphorylated at serine 15 and requires an N-terminal nuclear localization sequence (NLS). We used high-resolution, quantitative, fluorescent microscopy of live cells to determine the conditions, residues, and regulatory proteins required for Hxk2 nuclear localization. Countering previous yeast studies, we find that Hxk2 is largely excluded from the nucleus under glucose-replete conditions but is retained in the nucleus under glucose-limiting conditions. We find that the Hxk2 N-terminus does not contain an NLS but instead is necessary for nuclear exclusion and regulating multimerization. Amino acid substitutions of the phosphorylated residue, serine 15, disrupt Hxk2 dimerization but have no effect on its glucose-regulated nuclear localization. Alanine substation at nearby lysine 13 affects dimerization and maintenance of nuclear exclusion in glucose-replete conditions. Modeling and simulation provide insight into the molecular mechanisms of this regulation. In contrast to earlier studies, we find that the transcriptional repressor Mig1 and the protein kinase Snf1 have little effect on Hxk2 localization. Instead, the protein kinase Tda1 regulates Hxk2 localization. RNAseq analyses of the yeast transcriptome dispels the idea that Hxk2 moonlights as a transcriptional regulator of glucose repression, demonstrating that Hxk2 has a negligible role in transcriptional regulation in both glucose-replete and limiting conditions. Our studies define a new model of cis- and trans-acting regulators of Hxk2 dimerization and nuclear localization. Based on our data, the nuclear translocation of Hxk2 in yeast occurs in glucose starvation conditions, which aligns well with the nuclear regulation of mammalian orthologs. Our results lay the foundation for future studies of Hxk2 nuclear activity., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Lesko et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

β-lactam antibiotics target DD-transpeptidases, enzymes that perform the last step of bacterial cell-wall synthesis. To block the antimicrobial activity of these antibiotics, bacteria have evolved lactamases that render them inert. Among these, TEM-1, a class A lactamase, has been extensively studied. In 2004, Horn et al. described a novel allosteric TEM-1 inhibitor, FTA, that binds distant from the TEM-1 orthosteric (penicillin-binding) pocket. TEM-1 has subsequently become a model for the study of allostery. In the present work, we perform molecular dynamics simulations of FTA-bound and FTA-absent TEM-1, totaling ~3 μS, that provide new insight into TEM-1 inhibition. In one of the simulations, bound FTA assumed a conformation different than that observed crystallographically. We provide evidence that the alternate pose is physiologically plausible and describe how it impacts our understanding of TEM-1 allostery., (© 2023 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Molecular visualization is a cornerstone of structural biology, providing insights into the form and function of biomolecules that are difficult to achieve any other way. Scientific analysis, publication, education, and outreach often benefit from photorealistic molecular depictions rendered using advanced computer-graphics programs such as Maya, 3ds Max, and Blender. However, setting up molecular scenes in these programs is laborious even for expert users, and rendering often requires substantial time and computer resources. We have created a deep-learning model called Prot2Prot that quickly imitates photorealistic visualization styles, given a much simpler, easy-to-generate molecular representation. The resulting images are often indistinguishable from images rendered using industry-standard 3D graphics programs, but they can be created in a fraction of the time, even when running in a web browser. To the best of our knowledge, Prot2Prot is the first example of image-to-image translation applied to macromolecular visualization. Prot2Prot is available free of charge, released under the terms of the Apache License, Version 2.0. Users can access a Prot2Prot-powered web app without registration at http://durrantlab.com/prot2prot ., (© 2022. The Author(s).)

Detecting macromolecular (e.g., protein) cavities where small molecules bind is an early step in computer-aided drug discovery. Multiple pocket-detection algorithms have been developed over the past several decades. Among them, fpocket, created by Schmidtke and Le Guilloux, is particularly popular. Like many programs used in computational-biology research, fpocket requires users to download and install an executable file. That file must also be run via a command-line interface, further complicating use. An existing fpocket server application effectively addresses these challenges, but it requires users to upload their possibly proprietary structures to a third-party server. The FPocketWeb web app builds on this prior work. It runs the fpocket3 executable entirely in a web browser without requiring installation. The pocket-finding calculations occur on the user's computer rather than on a remote server. A working version of the open-source FPocketWeb app can be accessed free of charge from http://durrantlab.com/fpocketweb ., (© 2022. The Author(s).)

TransMEMbrane 16A (TMEM16A) is a Ca 2+ -activated Cl - channel that plays critical roles in regulating diverse physiologic processes, including vascular tone, sensory signal transduction, and mucosal secretion. In addition to Ca 2+ , TMEM16A activation requires the membrane lipid phosphatidylinositol 4,5-bisphosphate (PI(4,5)P 2 ). However, the structural determinants mediating this interaction are not clear. Here, we interrogated the parts of the PI(4,5)P 2 head group that mediate its interaction with TMEM16A by using patch- and two-electrode voltage-clamp recordings on oocytes from the African clawed frog Xenopus laevis, which endogenously express TMEM16A channels. During continuous application of Ca 2+ to excised inside-out patches, we found that TMEM16A-conducted currents decayed shortly after patch excision. Following this rundown, we show that the application of a synthetic PI(4,5)P 2 analog produced current recovery. Furthermore, inducible dephosphorylation of PI(4,5)P 2 reduces TMEM16A-conducted currents. Application of PIP 2 analogs with different phosphate orientations yielded distinct amounts of current recovery, and only lipids that include a phosphate at the 4' position effectively recovered TMEM16A currents. Taken together, these findings improve our understanding of how PI(4,5)P 2 binds to and potentiates TMEM16A channels., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

We here outline the importance of open-source, accessible tools for computer-aided drug discovery (CADD). We begin with a discussion of drug discovery in general to provide context for a subsequent discussion of structure-based CADD applied to small-molecule ligand discovery. Next, we identify usability challenges common to many open-source CADD tools. To address these challenges, we propose a browser-based approach to CADD tool deployment in which CADD calculations run in modern web browsers on users' local computers. The browser app approach eliminates the need for user-initiated download and installation, ensures broad operating system compatibility, enables easy updates, and provides a user-friendly graphical user interface. Unlike server apps-which run calculations "in the cloud" rather than on users' local computers-browser apps do not require users to upload proprietary information to a third-party (remote) server. They also eliminate the need for the difficult-to-maintain computer infrastructure required to run user-initiated calculations remotely. We conclude by describing some CADD browser apps developed in our lab, which illustrate the utility of this approach. Aside from introducing readers to these specific tools, we are hopeful that this review highlights the need for additional browser-compatible, user-friendly CADD software.

Glucose is central to many biological processes, serving as an energy source and a building block for biosynthesis. After glucose enters the cell, hexokinases convert it to glucose-6-phosphate (Glc-6P) for use in anaerobic fermentation, aerobic oxidative phosphorylation, and the pentose-phosphate pathway. We here describe a genetic screen in Saccharomyces cerevisiae that generated a novel spontaneous mutation in hexokinase-2, hxk2G238V, that confers resistance to the toxic glucose analog 2-deoxyglucose (2DG). Wild-type hexokinases convert 2DG to 2-deoxyglucose-6-phosphate (2DG-6P), but 2DG-6P cannot support downstream glycolysis, resulting in a cellular starvation-like response. Curiously, though the hxk2G238V mutation encodes a loss-of-function allele, the affected amino acid does not interact directly with bound glucose, 2DG, or ATP. Molecular dynamics simulations suggest that Hxk2G238V impedes sugar binding by altering the protein dynamics of the glucose-binding cleft, as well as the large-scale domain-closure motions required for catalysis. These findings shed new light on Hxk2 dynamics and highlight how allosteric changes can influence catalysis, providing new structural insights into this critical regulator of carbohydrate metabolism. Given that hexokinases are upregulated in some cancers and that 2DG and its derivatives have been studied in anti-cancer trials, the present work also provides insights that may apply to cancer biology and drug resistance., Competing Interests: The authors have declared that no competing interests exist.

BINding ANAlyzer (BINANA) is an algorithm for identifying and characterizing receptor/ligand interactions and other factors that contribute to binding. We recently updated BINANA to make the algorithm more accessible to a broader audience. We have also ported the Python3 codebase to JavaScript, thus enabling BINANA analysis in the web browser. As proof of principle, we created a web-browser application so students and chemical-biology researchers can quickly visualize receptor/ligand complexes and their unique binding interactions.

In vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in Saccharomyces cerevisiae. Sequence analysis identified many genes contributing to the resistance phenotype as well as numerous amino acids in potential targets that may play a role in compound binding. Our work shows that compound-target pairs can be conserved across multiple species. The set of 25 most frequently mutated genes was enriched for transcription factors, and for almost 25 percent of the compounds, resistance was mediated by one of 100 independently derived, gain-of-function SNVs found in a 170 amino acid domain in the two Zn 2 C 6 transcription factors YRR1 and YRM1 (p < 1 × 10 -100 ). This remarkable enrichment for transcription factors as drug resistance genes highlights their important role in the evolution of antifungal xenobiotic resistance and underscores the challenge to develop antifungal treatments that maintain potency., (© 2022. The Author(s).)

Poly(ADP-ribose) polymerase 1 (PARP1, also known as ADPRT1) is a multifunctional human ADP-ribosyltransferase. It plays a role in multiple DNA repair pathways, including the base excision repair (BER), non-homologous end joining (NHEJ), homologous recombination (HR), and Okazaki-fragment processing pathways. In response to DNA strand breaks, PARP1 covalently attaches ADP-ribose moieties to arginine, glutamate, aspartate, cysteine, lysine, and serine acceptor sites on both itself and other proteins. This signal recruits DNA repair proteins to the site of DNA damage. PARP1 binding to these sites enhances ADP-ribosylation via allosteric communication between the distant DNA binding and catalytic domains. In this review, we provide a general overview of PARP1 and emphasize novel potential approaches for pharmacological inhibition. Clinical PARP1 inhibitors bind the catalytic pocket, where they directly interfere with ADP-ribosylation. Some inhibitors may further enhance potency by "trapping" PARP1 on DNA via an allosteric mechanism, though this proposed mode of action remains controversial. PARP1 inhibitors are used clinically to treat some cancers, but resistance is common, so novel pharmacological approaches are urgently needed. One approach may be to design novel small molecules that bind at inter-domain interfaces that are essential for PARP1 allostery. To illustrate these points, this review also includes instructive videos showing PARP1 structures and mechanisms., (Copyright © 2021. Published by Elsevier B.V.)

Lead optimization, a critical step in early stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve properties such as binding affinity. We recently developed DeepFrag, a deep-learning model capable of recommending such modifications. Though a powerful hypothesis-generating tool, DeepFrag is currently implemented in Python and so requires a certain degree of computational expertise. To encourage broader adoption, we have created the DeepFrag browser app, which provides a user-friendly graphical user interface that runs the DeepFrag model in users' web browsers. The browser app does not require users to upload their molecular structures to a third-party server, nor does it require the separate installation of any third-party software. We are hopeful that the app will be a useful tool for both researchers and students. It can be accessed free of charge, without registration, at http://durrantlab.com/deepfrag. The source code is also available at http://git.durrantlab.com/jdurrant/deepfrag-app, released under the terms of the open-source Apache License, Version 2.0.

Machine learning has been increasingly applied to the field of computer-aided drug discovery in recent years, leading to notable advances in binding-affinity prediction, virtual screening, and QSAR. Surprisingly, it is less often applied to lead optimization, the process of identifying chemical fragments that might be added to a known ligand to improve its binding affinity. We here describe a deep convolutional neural network that predicts appropriate fragments given the structure of a receptor/ligand complex. In an independent benchmark of known ligands with missing (deleted) fragments, our DeepFrag model selected the known (correct) fragment from a set over 6500 about 58% of the time. Even when the known/correct fragment was not selected, the top fragment was often chemically similar and may well represent a valid substitution. We release our trained DeepFrag model and associated software under the terms of the Apache License, Version 2.0., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predicting the geometry with which a given compound might bind a target receptor (e.g., the docked "pose" relative to a protein target). Candidate ligands predicted to participate in the same intermolecular interactions typical of known ligands (or ligands that bind related proteins) are arguably more likely to be true binders. Some docking programs allow users to apply constraints during the docking process with the goal of prioritizing these critical interactions. But these programs often have restrictive and/or expensive licenses, and many popular open-source docking programs (e.g., AutoDock Vina) lack this important functionality. We present LigGrep, a free, open-source program that addresses this limitation. As input, LigGrep accepts a protein receptor file, a directory containing many docked-compound files, and a list of user-specified filters describing critical receptor/ligand interactions. LigGrep evaluates each docked pose and outputs the names of the compounds with poses that pass all filters. To demonstrate utility, we show that LigGrep can improve the hit rates of test VS targeting H. sapiens poly(ADPribose) polymerase 1 (HsPARP1), H. sapiens peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (HsPin1p), and S. cerevisiae hexokinase-2 (ScHxk2p). We hope that LigGrep will be a useful tool for the computational biology community. A copy is available free of charge at http://durrantlab.com/liggrep/ .

MutantHuntWGS is a user-friendly pipeline for analyzing Saccharomyces cerevisiae whole-genome sequencing data. It uses available open-source programs to: (1) perform sequence alignments for paired and single-end reads, (2) call variants, and (3) predict variant effect and severity. MutantHuntWGS outputs a shortlist of variants while also enabling access to all intermediate files. To demonstrate its utility, we use MutantHuntWGS to assess multiple published datasets; in all cases, it detects the same causal variants reported in the literature. To encourage broad adoption and promote reproducibility, we distribute a containerized version of the MutantHuntWGS pipeline that allows users to install and analyze data with only two commands. The MutantHuntWGS software and documentation can be downloaded free of charge from https://github.com/mae92/MutantHuntWGS., (Copyright © 2020 Ellison et al.)

Motivation: Molecular docking is a computational technique for predicting how a small molecule might bind a macromolecular target. Among docking programs, AutoDock Vina is particularly popular. Like many docking programs, Vina requires users to download/install an executable file and to run that file from a command-line interface. Choosing proper configuration parameters and analyzing Vina output is also sometimes challenging. These issues are particularly problematic for students and novice researchers., Results: We created Webina, a new version of Vina, to address these challenges. Webina runs Vina entirely in a web browser, so users need only visit a Webina-enabled webpage. The docking calculations take place on the user's own computer rather than a remote server., Availability and Implementation: A working version of the open-source Webina app can be accessed free of charge from http://durrantlab.com/webina., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

We here present AutoGrow4, an open-source program for semi-automated computer-aided drug discovery. AutoGrow4 uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual library of pre-enumerated compounds. It is a useful tool for generating entirely novel drug-like molecules and for optimizing preexisting ligands. By leveraging recent computational and cheminformatics advancements, AutoGrow4 is faster, more stable, and more modular than previous versions. It implements new docking-program compatibility, chemical filters, multithreading options, and selection methods to support a wide range of user needs. To illustrate both de novo design and lead optimization, we here apply AutoGrow4 to the catalytic domain of poly(ADP-ribose) polymerase 1 (PARP-1), a well characterized DNA-damage-recognition protein. AutoGrow4 produces drug-like compounds with better predicted binding affinities than FDA-approved PARP-1 inhibitors (positive controls). The predicted binding modes of the AutoGrow4 compounds mimic those of the known inhibitors, even when AutoGrow4 is seeded with random small molecules. AutoGrow4 is available under the terms of the Apache License, Version 2.0. A copy can be downloaded free of charge from http://durrantlab.com/autogrow4.

Protein structure determines biological function. Accurately conceptualizing 3D protein/ligand structures is thus vital to scientific research and education. Virtual reality (VR) enables protein visualization in stereoscopic 3D, but many VR molecular-visualization programs are expensive and challenging to use; work only on specific VR headsets; rely on complicated model-preparation software; and/or require the user to install separate programs or plugins. Here we introduce ProteinVR, a web-based application that works on various VR setups and operating systems. ProteinVR displays molecular structures within 3D environments that give useful biological context and allow users to situate themselves in 3D space. Our web-based implementation is ideal for hypothesis generation and education in research and large-classroom settings. We release ProteinVR under the open-source BSD-3-Clause license. A copy of the program is available free of charge from http://durrantlab.com/protein-vr/, and a working version can be accessed at http://durrantlab.com/pvr/., Competing Interests: The authors have declared that no competing interests exist.

Influenza virus circulates in human, avian, and swine hosts, causing seasonal epidemic and occasional pandemic outbreaks. Influenza neuraminidase, a viral surface glycoprotein, has two sialic acid binding sites. The catalytic (primary) site, which also binds inhibitors such as oseltamivir carboxylate, is responsible for cleaving the sialic acid linkages that bind viral progeny to the host cell. In contrast, the functional annotation of the secondary site remains unclear. Here, we better characterize these two sites through the development of an all-atom, explicitly solvated, and experimentally based integrative model of the pandemic influenza A H1N1 2009 viral envelope, containing ∼160 million atoms and spanning ∼115 nm in diameter. Molecular dynamics simulations of this crowded subcellular environment, coupled with Markov state model theory, provide a novel framework for studying realistic molecular systems at the mesoscale and allow us to quantify the kinetics of the neuraminidase 150-loop transition between the open and closed states. An analysis of chloride ion occupancy along the neuraminidase surface implies a potential new role for the neuraminidase secondary site, wherein the terminal sialic acid residues of the linkages may bind before transfer to the primary site where enzymatic cleavage occurs. Altogether, our work breaks new ground for molecular simulation in terms of size, complexity, and methodological analyses of the components. It also provides fundamental insights into the understanding of substrate recognition processes for this vital influenza drug target, suggesting a new strategy for the development of anti-influenza therapeutics., Competing Interests: The authors declare the following competing financial interest(s): R.E.A. is a cofounder and on the scientific advisory board of, and has equity interest in, Actavalon, Inc., (Copyright © 2020 American Chemical Society.)

The RNA-binding protein La-related protein 1 (LARP1) plays a central role in ribosome biosynthesis. Its C-terminal DM15 region binds the 7-methylguanosine (m 7 G) cap and 5' terminal oligopyrimidine (TOP) motif characteristic of transcripts encoding ribosomal proteins and translation factors. Under the control of mammalian target of rapamycin complex 1 (mTORC1), LARP1 regulates translation of these transcripts. Characterizing the dynamics of DM15-TOP recognition is essential to understanding this fundamental biological process. We use molecular dynamics simulations, biophysical assays, and X-ray crystallography to reveal the mechanism of DM15 binding to TOP transcripts. Residues C-terminal to the m 7 G-binding site play important roles in cap recognition. Furthermore, we show that the unusually static pocket that recognizes the +1 cytosine characteristic of TOP transcripts drives binding specificity. Finally, we demonstrate that the DM15 pockets involved in TOP-specific m 7 GpppC-motif recognition are likely druggable. Collectively, these studies suggest unique opportunities for further pharmacological development., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Molecules that mediate reproductive interactions are some of the most rapidly evolving traits. Researchers have often suggested that this is due to coevolution at key physiological interfaces. However, very few of these interfaces are well understood at the functional level. One such interface is the digestion of the spermatophore in Lepidoptera. Female Lepidoptera have a specialized reproductive organ called the bursa copulatrix that receives and processes the male spermatophore, a complex proteinaceous ejaculate. In the cabbage white butterfly, Pieris rapae , the bursa secretes a mixture of proteases hypothesized to digest the spermatophore. However, these proteases remain biochemically uncharacterized. Using a zymogram approach, we identified six proteases in bursal extracts at sufficiently high concentrations to characterize their in vitro activity. We assessed the modes of action of these bursal enzymes by quantifying their activity following exposure to diagnostic protease inhibitors. A serine protease-specific inhibitor failed to reduce bursal protease digestion of casein. However, a cysteine protease-specific inhibitor did decrease the activity of some proteases. To explore the possible molecular mechanisms responsible for these responses, we created protease homology models. The models mirrored the results of our in vitro experiments, indicating that protease homology models may offer insight into underlying functional mechanisms. Whether the observed bursal protease resistance to known inhibitors is important in the context of spermatophore digestion remains to be tested. However, our results suggest the exciting possibility that bursal protease specificity may have evolved in response to interactions with various proteins and inhibitors present within the female tract during the reproductive process.

Molecular dynamics (MD) simulations reveal molecular motions at atomic resolution. Recent advances in high-performance computing now enable microsecond-long simulations capable of sampling a wide range of biologically relevant events. But the disk space required to store an MD trajectory increases with simulation length and system size, complicating collaborative sharing and visualization. To overcome these limitations, we created PCAViz, an open-source toolkit for sharing and visualizing MD trajectories via the web browser. PCAViz includes two components: the PCAViz Compressor, which compresses and saves simulation data; and the PCAViz Interpreter, which decompresses the data in users' browsers and feeds it to any of several browser-based molecular-visualization libraries (e.g., 3Dmol.js, NGL Viewer, etc.). An easy-to-install WordPress plugin enables "plug-and-play" trajectory visualization. PCAViz will appeal to a broad audience of researchers and educators. The source code is available at http://durrantlab.com/pcaviz/ , and the WordPress plugin is available via the official WordPress Plugin Directory.

Summary: Programs such as VMD and PyMOL are excellent tools for analyzing macromolecular structures, but they do not implement many of the advanced rendering techniques common in the film and video-game industries. In contrast, the open-source program Blender is a general-purpose tool for industry-standard rendering/visualization, but its user interface is poorly suited for rigorous scientific analysis. We present BlendMol, a Blender plugin that imports VMD or PyMOL scenes into Blender. BlendMol-generated images are well suited for use in manuscripts, outreach programs, websites and classes., Availability and Implementation: BlendMol is available free of charge from http://durrantlab.com/blendmol/. It is written in Python., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2018. Published by Oxford University Press.)