Selective Aurora A-TPX2 Interaction Inhibitors Have In Vivo Efficacy as Targeted Antimitotic Agents.

Aurora A kinase, a cell division regulator, is frequently overexpressed in various cancers, provoking genome instability and resistance to antimitotic chemotherapy. Localization and enzymatic activity of Aurora A are regulated by its interaction with the spindle assembly factor TPX2. We have used fragment-based, structure-guided lead discovery to develop small molecule inhibitors of the Aurora A-TPX2 protein-protein interaction (PPI). Our lead compound, CAM2602, inhibits Aurora A:TPX2 interaction, binding Aurora A with 19 nM affinity. CAM2602 exhibits oral bioavailability, causes pharmacodynamic biomarker modulation, and arrests the growth of tumor xenografts. CAM2602 acts by a novel mechanism compared to ATP-competitive inhibitors and is highly specific to Aurora A over Aurora B. Consistent with our finding that Aurora A overexpression drives taxane resistance, these inhibitors synergize with paclitaxel to suppress the outgrowth of pancreatic cancer cells. Our results provide a blueprint for targeting the Aurora A-TPX2 PPI for cancer therapy and suggest a promising clinical utility for this mode of action.

Evolution and host-specific adaptation of Pseudomonas aeruginosa.

The major human bacterial pathogen Pseudomonas aeruginosa causes multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

Melodia: A Python Library for Protein Structure Analysis.

SUMMARY: Analysing protein structure similarities is an important step in protein engineering and drug discovery. Methodologies that are more advanced than simple RMSD are available but often require extensive mathematical or computational knowledge for implementation. Grouping and optimising such tools in an efficient open-source library increases accessibility and encourages the adoption of more advanced metrics. Melodia is a Python library with a complete set of components devised for describing, comparing and analysing the shape of protein structures using differential geometry of three-dimensional curves and knot theory. It can generate robust geometric descriptors for thousands of shapes in just a few minutes. Those descriptors are more sensitive to structural feature variation than RMSD deviation. Melodia also incorporates sequence structural annotation and three-dimensional visualisations. AVAILABILITY AND IMPLEMENTATION: Melodia is an open-source Python library freely available on https://github.com/rwmontalvao/Melodia_py, along with interactive Jupyter Notebook tutorials. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evaluating Representation Learning on the Protein Structure Universe.

We introduce ProteinWorkshop, a comprehensive benchmark suite for representation learning on protein structures with Geometric Graph Neural Networks. We consider large-scale pre-training and downstream tasks on both experimental and predicted structures to enable the systematic evaluation of the quality of the learned structural representation and their usefulness in capturing functional relationships for downstream tasks. We find that: (1) large-scale pretraining on AlphaFold structures and auxiliary tasks consistently improve the performance of both rotation-invariant and equivariant GNNs, and (2) more expressive equivariant GNNs benefit from pretraining to a greater extent compared to invariant models. We aim to establish a common ground for the machine learning and computational biology communities to rigorously compare and advance protein structure representation learning. Our open-source codebase reduces the barrier to entry for working with large protein structure datasets by providing: (1) storage-efficient dataloaders for large-scale structural databases including AlphaFoldDB and ESM Atlas, as well as (2) utilities for constructing new tasks from the entire PDB. ProteinWorkshop is available at: github.com/a-r-j/ProteinWorkshop.

Moderate-Intensity Exercise Enhances Mitochondrial Biogenesis Markers in the Skeletal Muscle of a Mouse Model Affected by Diet-Induced Obesity.

Skeletal muscle is composed of bundles of muscle fibers with distinctive characteristics. Oxidative muscle fiber types contain higher mitochondrial content, relying primarily on oxidative phosphorylation for ATP generation. Notably, as a result of obesity, or following prolonged exposure to a high-fat diet, skeletal muscle undergoes a shift in fiber type toward a glycolytic type. Mitochondria are highly dynamic organelles, constantly undergoing mitochondrial biogenesis and dynamic processes. Our study aims to explore the impact of obesity on skeletal muscle mitochondrial biogenesis and dynamics and also ascertain whether the skeletal muscle fiber type shift occurs from the aberrant mitochondrial machinery. Furthermore, we investigated the impact of exercise in preserving the oxidative muscle fiber types despite obesity. Mice were subjected to a normal standard chow and water or high-fat diet with sugar water (HFS) with or without exercise training. After 12 weeks of treatment, the HFS diet resulted in a noteworthy reduction in the markers of mitochondrial content, which was recovered by exercise training. Furthermore, higher mitochondrial biogenesis markers were observed in the exercised group with a subsequent increase in the mitochondrial fission marker. In conclusion, these findings imply a beneficial impact of moderate-intensity exercise on the preservation of oxidative capacity in the muscle of obese mouse models.

Testing the Shamiri Intervention and Its Components With Kenyan Adolescents During the COVID-19 Pandemic: Outcomes of a Universal, 5-Arm Randomized Controlled Trial.

OBJECTIVE: Mental health problems are prevalent among African adolescents, but professional treatment capacity is limited. Shamiri, an efficient lay provider-delivered intervention, has significantly reduced depression and anxiety symptoms in previous randomized controlled trials (RCTs). This trial investigated effects of the full Shamiri intervention and its components (growth-only, gratitude-only, and values-only) against a study skills control. METHOD: In a 5-group RCT with adolescents from Kenyan high schools, anxiety, depression, and well-being were self-reported through 8-month follow-up. The RCT occurred immediately after an unanticipated government-mandated COVID-19 shutdown forced 3 years of schoolwork into 2 years, escalating academic pressures. RESULTS: Participants (N = 1,252; 48.72% female) were allocated to: growth (n = 249), gratitude (n = 237), values (n = 265), Shamiri (n = 250), and study skills (n = 251) conditions. Longitudinal multilevel models showed that, across all conditions, anxiety scores significantly improved at midpoint (B = -0.847), end point (B = -2.948), 1-month (B = -1.587), 3-month (B = -2.374), and 8-month (B = -1.917) follow-ups. Depression scores also improved significantly at midpoint (B = -0.796), end point (B = -3.126), 1-month (B = -2.382), 3-month (B = -2.521), and 8-month (B = -2.237) follow-ups. Well-being scores improved significantly at midpoint (B = 1.73), end point (B = 3.44), 1-month (B = 2.21), 3-month (B = 1.78), and 8-month (B = 1.59) follow-ups. Symptom reduction with Shamiri matched that of pre-COVID-19 trials, but symptom reduction with study skills far outpaced that of trials before the COVID-19-related school shutdown (31% greater anxiety reduction and 60% greater depression reduction). Thus, in contrast to previous RCTs, this COVID-19-era trial showed no significant differences between outcomes in any intervention and active control groups. CONCLUSION: Our RCT conducted during a post-COVID-19 period of heightened academic pressure produced unexpected results. Improvements in youth-reported anxiety and depression were consistent with previous trials for Shamiri, but markedly larger than in previous trials for study skills. Control interventions teaching life skills may produce mental health benefits when they convey skills of particular contextual relevance. PLAIN LANGUAGE SUMMARY: A large five-group randomized controlled trial involved comparing the Shamiri Intervention to its component interventions (growth mindset, gratitude, and values affirmation) and a study-skills control. In contrast to previous studies of Shamiri, similar effects were observed across all groups (p<.05). This trial was conducted right after an unanticipated government-mandated COVID shutdown forced three years of schoolwork into two. Benchmarking analyses against previous trials showed approximately equal effects of Shamiri over time, but a 31% greater anxiety reduction and 60% greater depression reduction for the study-skills condition; this highlights the potential of interventions teaching highly relevant life-skills for improving mental health. CLINICAL TRIAL REGISTRATION: Five-Arm Shamiri Trial; https://pactr.samrc.ac.za/; PACTR202104716135752.

Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge.

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein-nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Enhancing anaerobic digestion of lignocellulosic biomass by mechanical cotreatment.

BACKGROUND: The aim of this study was to increase the accessibility and accelerate the breakdown of lignocellulosic biomass to methane in an anaerobic fermentation system by mechanical cotreatment: milling during fermentation, as an alternative to conventional pretreatment prior to biological deconstruction. Effluent from a mesophilic anaerobic digester running with unpretreated senescent switchgrass as the predominant carbon source was collected and subjected to ball milling for 0.5, 2, 5 and 10 min. Following this, a batch fermentation test was conducted with this material in triplicate for an additional 18 days with unmilled effluent as the 'status quo' control. RESULTS: The results indicate 0.5 - 10 min of cotreatment increased sugar solubilization by 5- 13% when compared to the unmilled control, with greater solubilization correlated with increased milling duration. Biogas concentrations ranged from 44% to 55.5% methane with the balance carbon dioxide. The total biogas production was statistically higher than the unmilled control for all treatments with 2 or more minutes of milling (α = 0.1). Cotreatment also decreased mean particle size. Energy consumption measurements of a lab-scale mill indicate that longer durations of milling offer diminishing benefits with respect to additional methane production. CONCLUSIONS: Cotreatment in anaerobic digestion systems, as demonstrated in this study, provides an alternative approach to conventional pretreatments to increase biogas production from lignocellulosic grassy material.

Frameless image-guided linear accelerator (LINAC) stereotactic radiosurgery for medically refractory trigeminal neuralgia: Clinical outcomes in 116 patients.

Background: Frameless image-guided radiosurgery (IGRS) is an effective and non-invasive method of treating patients who are unresponsive to medical management for trigeminal neuralgia (TN). This study evaluated the use of frameless IGRS to treat patients with medically refractory TN. Methods: We performed a retrospective review of records of 116 patients diagnosed with TN who underwent frameless IGRS using a linear accelerator (LINAC) over 10 years (March 2012-February 2023). All patients had failed medical management for TN. Facial pain was graded using the Barrow Neurological Institute (BNI) scoring system. Each patient received a BNI score before frameless IGRS and following treatment. Failure was defined as a BNI score IV-V at the last follow-up and/or undergoing a salvage procedure following IGRS. Results: All patients had a BNI score of either IV or V before the frameless IGRS. The mean follow-up duration for all 116 patients following IGRS was 44.1 months. Most patients (81 [69.8%]) had not undergone surgery (microvascular decompression [MVD] or rhizotomy) or stereotactic radiosurgery (SRS) for TN before frameless IGRS. A total of 41 (35.3%) patients underwent a salvage procedure (MVD, rhizotomy, or an additional IGRS) following frameless IGRS. The mean duration between the initial frameless IGRS and salvage procedure was 20.1 months. At the last follow-up, a total of 110 (94.8%) patients had a BNI score of I-III. No complications were reported after the frameless IGRS. The BNI score at the last follow-up was lower compared to the initial BNI for patients regardless of prior intervention (P < 0.001). Patients who failed IGRS had a higher BNI score at the last follow-up compared to those who did not fail IGRS (2.8 vs. 2.5, P = 0.05). Patients with pain relief had a shorter follow-up compared to those with pain refractory to SRS (38.0 vs. 55.1, P = 0.005). Conclusion: In this large cohort of patients with medically refractory TN, frameless IGRS resulted in durable pain control in the majority of patients without any toxicity.

A Fragment-Based Competitive 19F†LB-NMR Platform For Hotspot-Directed Ligand Profiling.

Ligand binding hotspots are regions of protein surfaces that form particularly favourable interactions with small molecule pharmacophores. Targeting interactions with these hotspots maximises the efficiency of ligand binding. Existing methods are capable of identifying hotspots but often lack assays to quantify ligand binding and direct elaboration at these sites. Herein, we describe a fragment-based competitive 19F Ligand Based NMR (LB-NMR) screening platform that enables routine, quantitative ligand profiling focused at ligand-binding hotspots. As a proof of concept, the method was applied to 4'-phosphopantetheine adenylyltransferase (PPAT) from Mycobacterium abscessus (Mabs). X-ray crystallographic characterisation of the hits from a 960-member fragment screen identified three ligand-binding hotspots across the PPAT active site. From the fragment hits a collection of 19F reporter candidates were designed and synthesised. By rigorous prioritisation and use of optimisation workflows, a single 19F reporter molecule was generated for each hotspot. Profiling the binding of a set of structurally characterised ligands by competitive 19F LB-NMR with this suite of 19F reporters recapitulated the binding affinity and site ID assignments made by ITC and X-ray crystallography. This quantitative mapping of ligand binding events at hotspot level resolution establishes the utility of the fragment-based competitive 19F LB-NMR screening platform for hotspot-directed ligand profiling.

Methods and associations of suicidality in Kenyan high school students: clinical and public health implications.

BACKGROUND: Most evidence on suicidal thoughts, plans and attempts comes from Western countries; prevalence rates may differ in other parts of the world. AIMS: This study determined the prevalence of suicidal thoughts, plans and attempts in high school students in three different regional settings in Kenya. METHOD: This was a cross-sectional study of 2652 high school students. We asked structured questions to determine the prevalence of various types of suicidality, the methods planned or effected, and participants' gender, age and form (grade level). We provided descriptive statistics, testing significant differences by chi-squared and Fisher's exact tests, and used logistic regression to identify relationships among different variables and their associations with suicidality. RESULTS: The prevalence rates of suicidal thoughts, plans and attempts were 26.8, 14.9 and 15.7%, respectively. These rates are higher than those reported for Western countries. Some 6.7% of suicide attempts were not associated with plans. The most common method used in suicide attempts was drinking chemicals/poison (18.8%). Rates of suicidal thoughts and plans were higher for older students and students in urban rather than rural locations, and attempts were associated with female gender and higher grade level - especially the final year of high school, when exam performance affects future education and career prospects. CONCLUSION: Suicidal thoughts, plans and attempts are prevalent in Kenyan high school students. There is a need for future studies to determine the different starting points to suicidal attempts, particularly for the significant number whose attempts are not preceded by thoughts and plans.

Flavone Cocrystals: A Comprehensive Approach Integrating Experimental and Virtual Methods.

The dapsone/flavone cocrystal system served as a benchmark for both experimental and virtual screening methods. Expanding beyond this, two additional active pharmaceutical ingredients (APIs), sulfanilamide and sulfaguanidine, structurally related to dapsone were chosen to investigate the impact of substituents on cocrystal formation. The experimental screening involved mechanochemical methods, slurry experiments, hot-melt extrusion, and the contact preparation method. The virtual screening focused on crystal structure prediction (CSP), molecular complementarity, hydrogen-bond propensity, and molecular electrostatic potentials. The CSP studies not only indicated that each of the three APIs should form cocrystals with flavone but also reproduced the known single- and multicomponent phases. Experimentally, dapsone/flavone cocrystals ACC, BCC, CCC, and DCC were reproduced, CCC was identified as a nonstoichiometric hydrate, and a fifth cocrystal (ECC), a t-butanol solvate, was discovered. The cocrystal polymorphs ACC and BCC are enantiotripically related, and DCC, exhibiting a different stoichiometric ratio, is enthalpically stabilized over the other cocrystals. For the sulfaguanidine/flavone system, two novel, enantiotripically related cocrystals were identified. The crystal structures of two cocrystals and a flavone polymorph were solved from powder X-ray diffraction data, and the stability of all cocrystals was assessed through differential scanning calorimetry and lattice energy calculations. Despite computational indications, a diverse array of cocrystallization techniques did not result in a sulfanilamide/flavone cocrystal. The driving force behind dapsone's tendency to cocrystallize with flavone can be attributed to the overall strength of flavone interactions in the cocrystals. For sulfaguanidine, the potential to form strong API···API and API···coformer interactions in the cocrystal is a contributing factor. Furthermore, flavone was found to be trimorphic.

Correction: Proteomic profiling of cereal aphid saliva reveals both ubiquitous and adaptive secreted proteins.

[This corrects the article DOI: 10.1371/journal.pone.0057413.].

Lipoarabinomannan modification as a source of phenotypic heterogeneity in host-adapted Mycobacterium abscessus isolates.

Mycobacterium abscessus is increasingly recognized as the causative agent of chronic pulmonary infections in humans. One of the genes found to be under strong evolutionary pressure during adaptation of M. abscessus to the human lung is embC which encodes an arabinosyltransferase required for the biosynthesis of the cell envelope lipoglycan, lipoarabinomannan (LAM). To assess the impact of patient-derived embC mutations on the physiology and virulence of M. abscessus, mutations were introduced in the isogenic background of M. abscessus ATCC 19977 and the resulting strains probed for phenotypic changes in a variety of in vitro and host cell-based assays relevant to infection. We show that patient-derived mutational variations in EmbC result in an unexpectedly large number of changes in the physiology of M. abscessus, and its interactions with innate immune cells. Not only did the mutants produce previously unknown forms of LAM with a truncated arabinan domain and 3-linked oligomannoside chains, they also displayed significantly altered cording, sliding motility, and biofilm-forming capacities. The mutants further differed from wild-type M. abscessus in their ability to replicate and induce inflammatory responses in human monocyte-derived macrophages and epithelial cells. The fact that different embC mutations were associated with distinct physiologic and pathogenic outcomes indicates that structural alterations in LAM caused by nonsynonymous nucleotide polymorphisms in embC may be a rapid, one-step, way for M. abscessus to generate broad-spectrum diversity beneficial to survival within the heterogeneous and constantly evolving environment of the infected human airway.

Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation.

Accurate modeling of cerebral hemodynamics is crucial for better understanding the hemodynamics of stroke, for which computational fluid dynamics (CFD) modeling is a viable tool to obtain information. However, a comprehensive study on the accuracy of cerebrovascular CFD models including both transient arterial pressures and flows does not exist. This study systematically assessed the accuracy of different outlet boundary conditions (BCs) comparing CFD modeling and an in-vitro experiment. The experimental setup consisted of an anatomical cerebrovascular phantom and high-resolution flow and pressure data acquisition. The CFD model of the same cerebrovascular geometry comprised five sets of stationary and transient BCs including established techniques and a novel BC, the phase modulation approach. The experiment produced physiological hemodynamics consistent with reported clinical results for total cerebral blood flow, inlet pressure, flow distribution, and flow pulsatility indices (PI). The in-silico model instead yielded time-dependent deviations between 19-66% for flows and 6-26% for pressures. For cerebrovascular CFD modeling, it is recommended to avoid stationary outlet pressure BCs, which caused the highest deviations. The Windkessel and the phase modulation BCs provided realistic flow PI values and cerebrovascular pressures, respectively. However, this study shows that the accuracy of current cerebrovascular CFD models is limited.

Face-to-face bullying in and outside of schools and cyberbullying are associated with suicidality in Kenyan high school students: a public health issue.

BACKGROUND: Childhood bullying has been classified as a major public health concern by WHO, with negative effects on the health education and social outcomes of both bullies and victims. There is no current Kenyan data on the prevalence of face-to-face bullying and cyberbullying co-occurring in the same cohort of youth and how they are associated with different aspects of suicidality and socio-demographic characteristics. This study aims to fill these gaps in the Kenyan situation so as to inform current policy and practice. METHODOLOGY: This cross-sectional study involved 2,652 students from ten secondary schools in Kenya, selected from three regions representing different levels of public funded schools and socioeconomic spaces. The outcome variable was derived from the questionnaire which asked students questions related to self-harm, suicide thoughts, plans, and attempts. Predictor variables were based on response on experience of bullying in school, out of school, at home, and cyberbullying. Other variables such as gender, age, family background, and class were also collected from the self-reported questions. Data were analyzed using SPSS version 25, with descriptive summary statistics and chi-square tests used to examine variables, and logistic regression analysis used to determine the associations between suicidality and experience of bullying. RESULTS: The mean age was 16.13 years. More than half of the participants were male, with the largest proportion living in rural areas. Face-to-face bullying was more prevalent than cyberbullying, with 82% of participants experiencing bullying and 68% experiencing it almost daily in the past six months. Both face-to-face bullying and cyberbullying were associated with suicidal thoughts, plans, and attempts. Predictors of suicidal attempts included being bullied outside of school and being a victim of group bullying, while being bullied every day and being bullied by adult men were predictors of suicidal attempts in cyberbullying. CONCLUSION: There is a high prevalence of face-to-face bullying both in and outside schools. There is also a high prevalence of cyberbullying. Both face-to-face and cyberbullying are associated with suicidality in Kenyan high school students.

Computational analyses of drug resistance mutations in katG and emb complexes in Mycobacterium tuberculosis.

The number of antibiotic resistant pathogens is increasing rapidly, and with this comes a substantial socioeconomic cost that threatens much of the world. To alleviate this problem, we must use antibiotics in a more responsible and informed way, further our understanding of the molecular basis of drug resistance, and design new antibiotics. Here, we focus on a key drug-resistant pathogen, Mycobacterium tuberculosis, and computationally analyze trends in drug-resistant mutations in genes of the proteins embA, embB, embC, and katG, which play essential roles in the action of the first-line drugs ethambutol and isoniazid. We use docking to predict binding modes of isoniazid to katG that agree with suggested binding sites found in our laboratory using cryo-EM. Using mutant stability predictions, we recapitulate the idea that resistance occurs when katG's heme cofactor is destabilized rather than due to a decrease in affinity to isoniazid. Conversely, we have identified resistance mutations that affect the affinity of ethambutol more drastically than the affinity of the natural substrate of embB. With this, we illustrate that we can distinguish between the two types of drug resistance-cofactor destabilization and drug affinity reduction-suggesting potential uses in the prediction of novel drug-resistant mutations.

Rare, long-distance dispersal underpins genetic connectivity in the pink sea fan, Eunicella verrucosa.

Characterizing patterns of genetic connectivity in marine species is of critical importance given the anthropogenic pressures placed on the marine environment. For sessile species, population connectivity can be shaped by many processes, such as pelagic larval duration, oceanographic boundaries and currents. This study combines restriction-site associated DNA sequencing (RADseq) and passive particle dispersal modelling to delineate patterns of population connectivity in the pink sea fan, Eunicella verrucosa, a temperate octocoral. Individuals were sampled from 20 sites covering most of the species' northeast Atlantic range, and a site in the northwest Mediterranean Sea to inform on connectivity across the Atlantic-Mediterranean transition. Using 7510 neutral SNPs, a geographic cline of genetic clusters was detected, partitioning into Ireland, Britain, France, Spain (Atlantic), and Portugal and Spain (Mediterranean). Evidence of significant inbreeding was detected at all sites, a finding not detected in a previous study of this species based on microsatellite loci. Genetic connectivity was characterized by an isolation by distance pattern (IBD) (r 2 = 0.78, p < 0.001), which persisted across the Mediterranean-Atlantic boundary. In contrast, exploration of ancestral population assignment using the program ADMIXTURE indicated genetic partitioning across the Bay of Biscay, which we suggest represents a natural break in the species' range, possibly linked to a lack of suitable habitat. As the pelagic larval duration (PLD) is unknown, passive particle dispersal simulations were run for 14 and 21 days. For both modelled PLDs, inter-annual variations in particle trajectories suggested that in a long-lived, sessile species, range-wide IBD is driven by rare, longer dispersal events that act to maintain gene flow. These results suggest that oceanographic patterns may facilitate range-wide stepping-stone genetic connectivity in E. verrucosa and highlight that both oceanography and natural breaks in a species' range should be considered in the designation of ecologically coherent MPA networks.

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge.

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.