High-Throughput Covalent Modifier Screening with Acoustic Ejection Mass Spectrometry.

Interests in covalent drugs have grown in modern drug discovery as they could tackle challenging targets traditionally considered "undruggable". The identification of covalent binders to target proteins typically involves directly measuring protein covalent modifications using high-resolution mass spectrometry. With a continually expanding library of compounds, conventional mass spectrometry platforms such as LC-MS and SPE-MS have become limiting factors for high-throughput screening. Here, we introduce a prototype high-resolution acoustic ejection mass spectrometry (AEMS) system for the rapid screening of a covalent modifier library comprising ∼10,000 compounds against a 50 kDa-sized target protein─Werner syndrome helicase. The screening samples were arranged in a 1536-well format. The sample buffer containing high-concentration salts was directly analyzed without any cleanup steps, minimizing sample preparation efforts and ensuring protein stability. The entire AEMS analysis process could be completed within a mere 17 h. An automated data analysis tool facilitated batch processing of the sample data and quantitation of the formation of various covalent protein-ligand adducts. The screening results displayed a high degree of fidelity, with a Z' factor of 0.8 and a hit rate of 2.3%. The identified hits underwent orthogonal testing in a biochemical activity assay, revealing that 75% were functional antagonists of the target protein. Notably, a comparative analysis with LC-MS showcased the AEMS platform's low risk of false positives or false negatives. This innovative platform has enabled robust high-throughput covalent modifier screening, featuring a 10-fold increase in library size and a 10- to 100-fold increase in throughput when compared with similar reports in the existing literature.

Nanoscale synthesis and affinity ranking.

Most drugs are developed through iterative rounds of chemical synthesis and biochemical testing to optimize the affinity of a particular compound for a protein target of therapeutic interest. This process is challenging because candidate molecules must be selected from a chemical space of more than 1060 drug-like possibilities 1 , and a single reaction used to synthesize each molecule has more than 107 plausible permutations of catalysts, ligands, additives and other parameters 2 . The merger of a method for high-throughput chemical synthesis with a biochemical assay would facilitate the exploration of this enormous search space and streamline the hunt for new drugs and chemical probes. Miniaturized high-throughput chemical synthesis3-7 has enabled rapid evaluation of reaction space, but so far the merger of such syntheses with bioassays has been achieved with only low-density reaction arrays, which analyse only a handful of analogues prepared under a single reaction condition8-13. High-density chemical synthesis approaches that have been coupled to bioassays, including on-bead 14 , on-surface 15 , on-DNA 16 and mass-encoding technologies 17 , greatly reduce material requirements, but they require the covalent linkage of substrates to a potentially reactive support, must be performed under high dilution and must operate in a mixture format. These reaction attributes limit the application of transition-metal catalysts, which are easily poisoned by the many functional groups present in a complex mixture, and of transformations for which the kinetics require a high concentration of reactant. Here we couple high-throughput nanomole-scale synthesis with a label-free affinity-selection mass spectrometry bioassay. Each reaction is performed at a 0.1-molar concentration in a discrete well to enable transition-metal catalysis while consuming less than 0.05 milligrams of substrate per reaction. The affinity-selection mass spectrometry bioassay is then used to rank the affinity of the reaction products to target proteins, removing the need for time-intensive reaction purification. This method enables the primary synthesis and testing steps that are critical to the invention of protein inhibitors to be performed rapidly and with minimal consumption of starting materials.

Intolerance of uncertainty and psychological flexibility as predictors of mental health from adolescence to old age.

PURPOSE: The COVID-19 pandemic brought with it significant social, economic and health uncertainties. These were proposed to impact young people more compared to adults, leading adolescents to report more mental health problems during the pandemic. The current study examined whether differences in cognitive risk (tolerance of uncertainty) and protective (psychological flexibility) factors accounted for age-related differences in depression and anxiety. METHODS: These associations were investigated in the COVID-19 Risks Across the Lifespan (CORAL) cohort (N = 2280, 11-89 years). RESULTS: The results showed that adolescents experienced greater intolerance of uncertainty and lower psychological flexibility compared to adults and older adults. Tolerance of uncertainty did not account for age-related differences in depression or anxiety. However, psychological flexibility conferred more protective advantage for anxiety in adults compared to adolescents. CONCLUSION: The observed age-related differences in risk and protective factors advance our understanding of developmental vulnerabilities to depression and anxiety. Implications for mental health interventions in the context of future pandemics are discussed.

Characterising variability in youth mental health service populations: A detailed and scalable approach using digital technology.

OBJECTIVE: This study utilised digital technology to assess the clinical needs of young people presenting for care at headspace centres across Australia. METHOD: 1490 young people (12-25 years) who presented to one of 11 headspace services from four geographical locations (urban New South Wales, urban South Australia, regional New South Wales, and regional Queensland) completed a digital multidimensional assessment at initial presentation. Characteristics were compared between services and geographical locations. RESULTS: We identified major variation in the demographics, and the type and severity of needs across different services. Individuals from regional services were more likely to be younger, of Aboriginal and Torres Strait Islander origin, and present with psychotic-like symptoms and suicidality, while those in urban areas were more likely to have previously sought help and have problematic alcohol use. Further differences in age, distress, depressive symptoms, psychotic-like experiences, trauma, family history, alcohol use, education/employment engagement, and days out of role were identified between different urban sites. CONCLUSIONS: The variability between services provides insight into the heterogeneity of youth mental health populations which has implications for appropriate early intervention and prevention service provisions. We propose that integrating digital technologies has the potential to provide insights for smarter service planning and evaluation.

SAR towards indoline and 3-azaindoline classes of IDO1 inhibitors.

A novel series of IDO1 inhibitors have been identified with good IDO1 Hela cell and human whole blood activity. These inhibitors contain an indoline or a 3-azaindoline scaffold. Their structure-activity-relationship studies have been explored. Compounds 37 and 41 stood out as leads due to their good potency in IDO1 Hela assay, good IDO1 unbound hWB IC50s, reasonable unbound clearance, and good MRT in rat and dog PK studies.

A multivariate prognostic model for pain and activity limitation in people undergoing lumbar discectomy.

Purpose: The purpose of this study was to identify a multivariate predictive model for 6-month outcomes on overall pain, leg pain and activity limitation in patients undergoing lumbar discectomy. Identification of predictors of outcome for lumbar discectomy has the potential to assist identifying treatment targets, clinical decision making and disease understanding.Materials and methods: Prospective cohort design. Ninety-seven patients deemed by study surgeons to be suitable for lumbar discectomy completed a comprehensive clinical and radiological baseline assessment. At 6-months post surgery outcome measures of overall and leg pain (visual analogue scale) as well as activity limitation (Oswestry Disability Index) were completed. Univariate and multivariate analyses were conducted to determine the best multivariate predictive model of outcome.Results: In the multivariate model, presence of a compensation claim, longer duration of injury and presence of below knee pain and/or parasthesia were negative prognostic indicators for at least two of the outcomes. Peripheralization in response to mechanical loading strategies was a positive prognostic indicator for overall pain and leg pain. A range of other prognostic indicators for one outcome were also identified. The prognostic model explained up to 32% of the variance in outcome.Conclusions: An 11-factor prognostic model was identified from a range of clinically and radiologically assessed variables in accordance with a biopsychosocial model. The multivariate model has potential implications for researchers and practitioners in the field. Further high quality research is required to externally validate the prognostic model, evaluate effect of the identified prognostic factors on treatment effectiveness and explore potential mechanisms of effect.

ProbAnnoWeb and ProbAnnoPy: probabilistic annotation and gap-filling of metabolic reconstructions.

Summary: Gap-filling is a necessary step to produce quality genome-scale metabolic reconstructions capable of flux-balance simulation. Most available gap-filling tools use an organism-agnostic approach, where reactions are selected from a database to fill gaps without consideration of the target organism. Conversely, our likelihood based gap-filling with probabilistic annotations selects candidate reactions based on a likelihood score derived specifically from the target organism's genome. Here, we present two new implementations of probabilistic annotation and likelihood based gap-filling: a web service called ProbAnnoWeb, and a standalone python package called ProbAnnoPy. Availability and implementation: Our tools are available as a web service with no installation needed (ProbAnnoWeb) at probannoweb.systemsbiology.net, and as a local python package implementation (ProbAnnoPy) at github.com/PriceLab/probannopy. Contact: evangelos.simeonidis@systemsbiology.org or nathan.price@systemsbiology.org. Supplementary information: Supplementary data are available at Bioinformatics online.

Exploring Hydrogenotrophic Methanogenesis: a Genome Scale Metabolic Reconstruction of Methanococcus maripaludis.

Hydrogenotrophic methanogenesis occurs in multiple environments, ranging from the intestinal tracts of animals to anaerobic sediments and hot springs. Energy conservation in hydrogenotrophic methanogens was long a mystery; only within the last decade was it reported that net energy conservation for growth depends on electron bifurcation. In this work, we focus on Methanococcus maripaludis, a well-studied hydrogenotrophic marine methanogen. To better understand hydrogenotrophic methanogenesis and compare it with methylotrophic methanogenesis that utilizes oxidative phosphorylation rather than electron bifurcation, we have built iMR539, a genome scale metabolic reconstruction that accounts for 539 of the 1,722 protein-coding genes of M. maripaludis strain S2. Our reconstructed metabolic network uses recent literature to not only represent the central electron bifurcation reaction but also incorporate vital biosynthesis and assimilation pathways, including unique cofactor and coenzyme syntheses. We show that our model accurately predicts experimental growth and gene knockout data, with 93% accuracy and a Matthews correlation coefficient of 0.78. Furthermore, we use our metabolic network reconstruction to probe the implications of electron bifurcation by showing its essentiality, as well as investigating the infeasibility of aceticlastic methanogenesis in the network. Additionally, we demonstrate a method of applying thermodynamic constraints to a metabolic model to quickly estimate overall free-energy changes between what comes in and out of the cell. Finally, we describe a novel reconstruction-specific computational toolbox we created to improve usability. Together, our results provide a computational network for exploring hydrogenotrophic methanogenesis and confirm the importance of electron bifurcation in this process. IMPORTANCE: Understanding and applying hydrogenotrophic methanogenesis is a promising avenue for developing new bioenergy technologies around methane gas. Although a significant portion of biological methane is generated through this environmentally ubiquitous pathway, existing methanogen models portray the more traditional energy conservation mechanisms that are found in other methanogens. We have constructed a genome scale metabolic network of Methanococcus maripaludis that explicitly accounts for all major reactions involved in hydrogenotrophic methanogenesis. Our reconstruction demonstrates the importance of electron bifurcation in central metabolism, providing both a window into hydrogenotrophic methanogenesis and a hypothesis-generating platform to fuel metabolic engineering efforts.

Individualised physiotherapy as an adjunct to guideline-based advice for low back disorders in primary care: a randomised controlled trial.

BACKGROUND: Many patients with low-back disorders persisting beyond 6 weeks do not recover. This study investigates whether individualised physiotherapy plus guideline-based advice results in superior outcomes to advice alone in participants with low-back disorders. METHODS: This prospective parallel group multicentre randomised controlled trial was set in 16 primary care physiotherapy practices in Melbourne, Australia. Random assignment resulted in 156 participants receiving 10 sessions of physiotherapy that was individualised based on pathoanatomical, psychosocial and neurophysiological barriers to recovery combined with guideline-based advice, and 144 participants receiving 2 sessions of physiotherapist-delivered advice alone. Primary outcomes were activity limitation (Oswestry Disability Index) and numerical rating scales for back and leg pain at 5, 10, 26 and 52 weeks postbaseline. Analyses were by intention-to-treat using linear mixed models. RESULTS: Between-group differences showed significant effects favouring individualised physiotherapy for back and leg pain at 10 weeks (back: 1.3, 95% CI 0.8 to 1.8; leg: 1.1, 95% CI 0.5 to 1.7) and 26 weeks (back: 0.9, 95% CI 0.4 to 1.4; leg: 1.0, 95% CI 0.4 to 1.6). Oswestry favoured individualised physiotherapy at 10 weeks (4.7; 95% CI 2.0 to 7.5), 26 weeks (5.4; 95% CI 2.6 to 8.2) and 52 weeks (4.3; 95% CI 1.4 to 7.1). Responder analysis at 52 weeks showed participants receiving individualised physiotherapy were more likely to improve by a clinically important amount of 50% from baseline for Oswestry (relative risk (RR=1.3) 1.5; 95% CI 1.2 to 1.8) and back pain (RR 1.3; 95% CI 1.2 to 1.8) than participants receiving advice alone. CONCLUSIONS: 10 sessions of individualised physiotherapy was more effective than 2 sessions of advice alone in participants with low-back disorders of ≥6 weeks and ≤6 months duration. Between-group changes were sustained at 12 months for activity limitation and 6 months for back and leg pain and were likely to be clinically significant. CLINICAL TRIAL REGISTRATION: ACTRN12609000834257.

The epidemiology of enterococci in a tertiary hospital and primary healthcare facilities in Fiji (2019-2022).

OBJECTIVES: We analysed 4 y of laboratory data to characterise the species and determine the antimicrobial susceptibility profiles of enterococci as human pathogens in Fiji. The study also investigated the molecular epidemiology amongst the subset of vancomycin-resistant enterococci (VRE). METHODS: This retrospective study reviewed bacteriological data from Colonial War Memorial Hospital (CWMH) and other healthcare facilities in the Central and Eastern divisions of Fiji. Phenotypic, antimicrobial susceptibility and vanA and vanB PCR testing were performed using locally approved protocols. The first clinical isolates per patient with antimicrobial susceptibility testing results in a single year were included in the analysis. Data was analysed using WHONET software and Microsoft Excel. RESULTS: A total of 1817 enterococcal isolates were reported, 1415 from CWMH and 402 from other healthcare facilities. The majority of isolates, 75% (n = 1362) were reported as undifferentiated Enterococcus spp., 17.8% (n = 324) were specifically identified as Enterococcus faecalis and 6.7% (n = 122) as E. faecium. Overall, 10% of the enterococci isolates were from blood cultures. Among isolates from CWMH, <15% of E. faecium were susceptible to ampicillin, and 17.2% were vancomycin resistant. Overall, 874 enterococcal isolates (including the undifferentiated species) were tested against vancomycin, of which 4.8% (n = 42) were resistance. All of the VRE isolates tested (n = 15) expressed vanA genes. CONCLUSIONS: This study demonstrates the clinical importance of VRE, particularly van A E. faecium in the national referral hospital in Fiji. Enhanced phenotypic and molecular surveillance data are needed to better understand enterococci epidemiology and help guide specific infection prevention and control measures and antibiotic prescribing guidelines.

Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology.

Mental fitness is a construct that goes beyond a simple focus on subjective emotional wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we want in our daily lives. The measurement and monitoring of multiple (often interacting) domains is crucial to gain a holistic and complete insight into an individual's mental fitness. We aimed to demonstrate the capability of a new mobile app to characterise the mental fitness of a general population of Australians and to quantify the interrelationships among different domains of mental fitness. Cross-sectional data were collected from 4901 adults from the general population of Australians engaged in work or education who used a mobile app (Innowell) between September 2021 and November 2022. Individuals completed a baseline questionnaire comprised of 26 questions across seven domains of mental fitness (i.e., physical activity, sleep and circadian rhythms, nutrition, substance use, daily activities, social connection, psychological distress). Network analysis was applied at both a domain-level (e.g., 7 nodes representing each cluster of items) and an individual item-level (i.e., 26 nodes representing all questionnaire items). Only 612 people (12%) were functioning well across all domains. One quarter (n = 1204, 25%) had only one problem domain and most (n = 3085, 63%) had multiple problem domains. The two most problematic domains were physical activity (n = 2631, 54%) and social connection (n = 2151, 44%), followed closely by daily activity (n = 1914, 39%). At the domain-level, the strongest association emerged between psychological distress and daily activity (r = 0.301). Psychological distress was the most central node in the network (as measured by strength and expected influence), followed closely by daily activity, sleep and circadian rhythms and then social connection. The item-level network revealed that the nodes with the highest centrality in the network were: hopelessness, depression, functional impairment, effortfulness, subjective energy, worthlessness, and social connectedness. Social connection, sleep and circadian rhythms, and daily activities may be critical targets for intervention due to their widespread associations in the overall network. While psychological distress was not among the most common problems, its centrality may indicate its importance for indicated prevention and early intervention. We showcase the capability of a new mobile app to monitor mental fitness and identify the interrelationships among multiple domains, which may help people develop more personalised insights and approaches.

The changing epidemiology of antimicrobial resistance in Fiji: a descriptive analysis of antimicrobial susceptibility and trends of endemic and emerging pathogens, 2019-2022.

Background: There is a paucity of data on antimicrobial resistance in Fiji. The aim of this study was to determine the antimicrobial susceptibility profile of bacterial isolates from clinical samples at Colonial War Memorial Hospital in Fiji. Methods: This retrospective study reviewed four-year of data from January 1, 2019, through December 31, 2022. Laboratory testing was carried out using locally approved protocols. Selective antimicrobial susceptibility testing was performed whereby only isolates resistant to first line antimicrobials were tested against second line antimicrobials. Only the first isolate of a given species per patient in a single year were included in the analysis. WHONET software and Microsoft Excel were used for analysis. Findings: A total of 29,222 bacterial isolates were included, 62% (n = 18,084) were Gram-negative bacteria. K. pneumoniae was the most common (n = 5363), followed by E. coli (n = 4321). Extended spectrum beta lactamase (ESBL) production increased from 30% in 2019 to 43% in 2022 amongst K. pneumoniae, and 10%-23% in E coli. There were 733 carbapenem-resistant isolates identified from clinical samples, 61% (n = 445) were A. baumannii, 15% (n = 110) E. coli and 14% (n = 101) P. aeruginosa. Amongst the E. coli isolates tested, susceptibility to meropenem declined from 99% (272/274) in 2019 to 79% (255/325) in 2022. The rate of methicillin resistance amongst Staphylococcus aureus was steady, remaining between 11% and 13%. Interpretation: This study demonstrated a high rate of MDR amongst Gram-negative bacteria, especially ESBL producing K. pneumoniae and E. coli and carbapenem-resistant A. baumannii. The emergence and rapid spread of carbapenemase producing E. coli in Fiji's largest hospital is of particular concern. There is an urgent need to allocate resources to improve existing capacity and to develop effective multimodal strategies to detect, manage and control the spread of MDR organisms. Funding: This study was supported by the Medical Research Future Fund through the Australian government (grant number APP 1200970).

Structure-based design and optimization of 2-aminothiazole-4-carboxamide as a new class of CHK1 inhibitors.

Drug design efforts in the emerging 2-aminothiazole-4-carboxamide class of CHK1 inhibitors have uncovered specific combinations of key substructures within the molecule; resulting in significant improvements in cell-based activity while retaining a greater than one hundred-fold selectivity against CDK2. The X-ray crystal structure of a complex between compound 39 and the CHK1 protein detailing a 'U-shaped' topology and key interactions with the protein surface at the ATP site is also reported.

Patterns of emergency department presentations for a youth mental health cohort: data-linkage cohort study.

BACKGROUND: Primary youth mental health services in Australia have increased access to care for young people, yet the longer-term outcomes and utilisation of other health services among these populations is unclear. AIMS: To describe the emergency department presentation patterns of a help-seeking youth mental health cohort. METHOD: Data linkage was performed to extract Emergency Department Data Collection registry data (i.e. emergency department presentations, pattern of re-presentations) for a transdiagnostic cohort of 7024 youths (aged 12-30 years) who presented to mental health services. Outcome measures were pattern of presentations and reason for presentations (i.e. mental illness; suicidal behaviours and self-harm; alcohol and substance use; accident and injury; physical illness; and other). RESULTS: During the follow-up period, 5372 (76.5%) had at least one emergency department presentation. The presentation rate was lower for males (IRR = 0.87, 95% CI 0.86-0.89) and highest among those aged 18 to 24 (IRR = 1.117, 95% CI 1.086-1.148). Almost one-third (31.12%) had an emergency department presentation that was directly associated with mental illness or substance use, and the most common reasons for presentation were for physical illness and accident or injury. Index visits for mental illness or substance use were associated with a higher rate of re-presentation. CONCLUSIONS: Most young people presenting to primary mental health services also utilised emergency services. The preventable and repeated nature of many presentations suggests that reducing the ongoing secondary risks of mental disorders (i.e. substance misuse, suicidality, physical illness) could substantially improve the mental and physical health outcomes of young people.

Correction: Reproducible big data science: A case study in continuous FAIRness.

[This corrects the article DOI: 10.1371/journal.pone.0213013.].

Specific treatment of problems of the spine (STOPS): design of a randomised controlled trial comparing specific physiotherapy versus advice for people with subacute low back disorders.

BACKGROUND: Low back disorders are a common and costly cause of pain and activity limitation in adults. Few treatment options have demonstrated clinically meaningful benefits apart from advice which is recommended in all international guidelines. Clinical heterogeneity of participants in clinical trials is hypothesised as reducing the likelihood of demonstrating treatment effects, and sampling of more homogenous subgroups is recommended. We propose five subgroups that allow the delivery of specific physiotherapy treatment targeting the pathoanatomical, neurophysiological and psychosocial components of low back disorders. The aim of this article is to describe the methodology of a randomised controlled trial comparing specific physiotherapy treatment to advice for people classified into five subacute low back disorder subgroups. METHODS/DESIGN: A multi-centre parallel group randomised controlled trial is proposed. A minimum of 250 participants with subacute (6 weeks to 6 months) low back pain and/or referred leg pain will be classified into one of five subgroups and then randomly allocated to receive either physiotherapy advice (2 sessions over 10 weeks) or specific physiotherapy treatment (10 sessions over 10 weeks) tailored according to the subgroup of the participant. Outcomes will be assessed at 5 weeks, 10 weeks, 6 months and 12 months following randomisation. Primary outcomes will be activity limitation measured with a modified Oswestry Disability Index as well as leg and back pain intensity measured on separate 0-10 Numerical Rating Scales. Secondary outcomes will include a 7-point global rating of change scale, satisfaction with physiotherapy treatment, satisfaction with treatment results, the Sciatica Frequency and Bothersomeness Scale, quality of life (EuroQol-5D), interference with work, and psychosocial risk factors (Orebro Musculoskeletal Pain Questionnaire). Adverse events and co-interventions will also be measured. Data will be analysed according to intention to treat principles, using linear mixed models for continuous outcomes, Mann Whitney U tests for ordinal outcomes, and Chi-square, risk ratios and risk differences for dichotomous outcomes. DISCUSSION: This trial will determine the difference in outcomes between specific physiotherapy treatment tailored to each of the five subgroups versus advice which is recommended in guidelines as a suitable treatment for most people with a low back disorder. TRIAL REGISTRATION: Australia and New Zealand Clinical Trials Register (ANZCTR): ACTRN12609000834257.

Carbamate and N-Pyrimidine Mitigate Amide Hydrolysis: Structure-Based Drug Design of Tetrahydroquinoline IDO1 Inhibitors.

Indoleamine-2,3-dioxygenase-1 (IDO1) has emerged as an attractive target for cancer immunotherapy. An automated ligand identification system screen afforded the tetrahydroquinoline class of novel IDO1 inhibitors. Potency and pharmacokinetic (PK) were key issues with this class of compounds. Structure-based drug design and strategic incorporation of polarity enabled the rapid improvement on potency, solubility, and oxidative metabolic stability. Metabolite identification studies revealed that amide hydrolysis in the D-pocket was the key clearance mechanism for this class. Strategic survey of amide isosteres revealed that carbamates and N-pyrimidines, which maintained exquisite potencies, mitigated the amide hydrolysis issue and led to an improved rat PK profile. The lead compound 28 is a potent IDO1 inhibitor, with clean off-target profiles and the potential for quaque die dosing in humans.

Targeting RNA with Small Molecules: Identification of Selective, RNA-Binding Small Molecules Occupying Drug-Like Chemical Space.

Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA-small molecule interactions that was generated was compared with that for protein-small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts.

Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types.

Characterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking. Here, we develop a scalable footprinting workflow using two state-of-the-art algorithms: Wellington and HINT. We apply our workflow to detect footprints in 192 ENCODE DNase-seq experiments and predict the genomic occupancy of 1,515 human TFs in 27 human tissues. We validate that these footprints overlap true-positive TF binding sites from ChIP-seq. We demonstrate that the locations, depth, and tissue specificity of footprints predict effects of genetic variants on gene expression and capture a substantial proportion of genetic risk for complex traits.