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Mycobacterium tuberculosis (Mtb) relies on a specialized set of metabolic pathways to support growth in macrophages. By conducting an extensive, unbiased chemical screen to identify small molecules that inhibit Mtb metabolism within macrophages, we identified a significant number of novel compounds that limit Mtb growth in macrophages and in medium containing cholesterol as the principle carbon source. Based on this observation, we developed a chemical-rescue strategy to identify compounds that target metabolic enzymes involved in cholesterol metabolism. This approach identified two compounds that inhibit the HsaAB enzyme complex, which is required for complete degradation of the cholesterol A/B rings. The strategy also identified an inhibitor of PrpC, the 2-methylcitrate synthase, which is required for assimilation of cholesterol-derived propionyl-CoA into the TCA cycle. These chemical probes represent new classes of inhibitors with novel modes of action, and target metabolic pathways required to support growth of Mtb in its host cell. The screen also revealed a structurally-diverse set of compounds that target additional stage(s) of cholesterol utilization. Mutants resistant to this class of compounds are defective in the bacterial adenylate cyclase Rv1625/Cya. These data implicate cyclic-AMP (cAMP) in regulating cholesterol utilization in Mtb, and are consistent with published reports indicating that propionate metabolism is regulated by cAMP levels. Intriguingly, reversal of the cholesterol-dependent growth inhibition caused by this subset of compounds could be achieved by supplementing the media with acetate, but not with glucose, indicating that Mtb is subject to a unique form of metabolic constraint induced by the presence of cholesterol.

The serine/threonine kinase 17B (STK17B) is involved in setting the threshold for T cell activation and its absence sensitizes T cells to suboptimal stimuli. Consequently, STK17B represents an attractive potential target for cancer immunotherapy. To assess the potential of STK17B as an immuno-oncology target, we developed potent and selective tool compounds from starting points in Blueprint Medicines Corporation's proprietary kinase inhibitor library. To characterize these molecules, enzyme and cellular assays for STK17A and STK17B were established to drive chemistry optimization. Mass spectrometry-based phosphoproteomics profiling with tool inhibitors led to the identification of Ser19 on myosin light chain 2 as STK17B substrate, which is then developed into a flow cytometry-based pharmacodynamic readout of STK17B inhibition both and . In a mouse T cell activation assay, STK17B inhibitors demonstrated the ability to enhance interleukin-2 (IL-2) production. Similarly, treatment with STK17B inhibitors resulted in stronger cytokine secretion in human T cells activated using a T cell bispecific antibody. Subsequent chemistry optimization led to the identification of a highly selective and orally bioavailable tool compound, BLU7482. , STK17B inhibition led to dose-dependent modulation of myosin light chain 2 phosphorylation and enhanced priming of naïve T cells, as determined by upregulation of CD69, IL-2 and interferon-γ secretion. In line with increased T cell activation, treatment with STK17B inhibitor enhanced antitumor activity of anti-PD-L1 antibody in the MCA205 model. In summary, we successfully identified and optimized STK17B kinase inhibitors which led to increased T cell responses and . This allowed us to evaluate the potential of STK17B inhibition as an approach for cancer immunotherapy.

Mycobacterium tuberculosis (Mtb) relies on a specialized set of metabolic pathways to support growth in macrophages. By conducting an extensive, unbiased chemical screen to identify small molecules that inhibit Mtb metabolism within macrophages, we identified a significant number of novel compounds that limit Mtb growth in macrophages and in medium containing cholesterol as the principle carbon source. Based on this observation, we developed a chemical-rescue strategy to identify compounds that target metabolic enzymes involved in cholesterol metabolism. This approach identified two compounds that inhibit the HsaAB enzyme complex, which is required for complete degradation of the cholesterol A/B rings. The strategy also identified an inhibitor of PrpC, the 2-methylcitrate synthase, which is required for assimilation of cholesterol-derived propionyl-CoA into the TCA cycle. These chemical probes represent new classes of inhibitors with novel modes of action, and target metabolic pathways required to support growth of Mtb in its host cell. The screen also revealed a structurally-diverse set of compounds that target additional stage(s) of cholesterol utilization. Mutants resistant to this class of compounds are defective in the bacterial adenylate cyclase Rv1625/Cya. These data implicate cyclic-AMP (cAMP) in regulating cholesterol utilization in Mtb, and are consistent with published reports indicating that propionate metabolism is regulated by cAMP levels. Intriguingly, reversal of the cholesterol-dependent growth inhibition caused by this subset of compounds could be achieved by supplementing the media with acetate, but not with glucose, indicating that Mtb is subject to a unique form of metabolic constraint induced by the presence of cholesterol.

A high-quality NMR solution structure of the chimeric hybrid duplex r(gcaguggc).r(gcca)d(CTGC) was determined using the program DYANA with its recently implemented new module FOUND, which performs exhaustive conformational grid searches for dinucleotides. To ensure conservative data interpretation, the use of 1H-1H lower distance limit constraints was avoided. The duplex comprises the tRNA-DNA junction formed during the initiation of HIV-1 reverse transcription. It forms an A-type double helix that exhibits distinct structural deviations from a standard A-conformation. In particular, the minor groove is remarkably narrow, and its width decreases from about 7.5 A in the RNA/RNA stem to about 4.5 A in the RNA/DNA segment. This is unexpected, since minor groove widths for A-RNA and RNA/DNA hybrid duplexes of approximately 11 A and approximately 8.5 A, respectively, were previously reported. The present, new structure supports that reverse transcriptase-associated RNaseH specificity is related primarily to conformational adaptability of the nucleic acid in 'induced-fit'-type interactions, rather than the minor groove width of a predominantly static nucleic acid duplex.

Farnesyltransferase (FT) inhibitors can repress tumor cell proliferation without substantially interfering with normal cell growth and are thus promising in cancer treatment. A detailed knowledge of how substrates and inhibitors bind to FT at the atomic level can expedite screening and rational design of improved FT inhibitors. Here we report theoretical models of the FT complexed with FPP and the potent nonpeptidic inhibitor SCH 56580 and other inhibitor-FPP-FT ternary complexes derived from the docking studies prior to any crystal structures of the FT liganded with nonpeptidic inhibitors. On the basis of these models we evaluate the roles of FPP, Zn2+ and the zinc-coordinated water molecule in inhibitor binding, and propose the structural determinants of binding of nonpeptidic FT inhibitors. Furthermore, we suggest the use of the FPP-FT binary complex as a novel and effective drug target structure for screening and rational design of improved FT inhibitors.

Cholesteryl ester transfer protein (CETP) inhibition reduces vascular event risk, but confusion surrounds its effects on low-density lipoprotein (LDL) cholesterol. Here, we clarify associations of genetic inhibition of CETP on detailed lipoprotein measures and compare those to genetic inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). We used an allele associated with lower CETP expression (rs247617) to mimic CETP inhibition and an allele associated with lower HMGCR expression (rs12916) to mimic the well-known effects of statins for comparison. The study consists of 65,427 participants of European ancestries with detailed lipoprotein subclass profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% reduction in relative risk of coronary heart disease (CHD). We also examined observational associations of the lipoprotein subclass measures with risk of incident CHD in 3 population-based cohorts totalling 616 incident cases and 13,564 controls during 8-year follow-up. Genetic inhibition of CETP and HMGCR resulted in near-identical associations with LDL cholesterol concentration estimated by the Friedewald equation. Inhibition of HMGCR had relatively consistent associations on lower cholesterol concentrations across all apolipoprotein B-containing lipoproteins. In contrast, the associations of the inhibition of CETP were stronger on lower remnant and very-low-density lipoprotein (VLDL) cholesterol, but there were no associations on cholesterol concentrations in LDL defined by particle size (diameter 18-26 nm) (-0.02 SD LDL defined by particle size; 95% CI: -0.10 to 0.05 for CETP versus -0.24 SD, 95% CI -0.30 to -0.18 for HMGCR). Inhibition of CETP was strongly associated with lower proportion of triglycerides in all high-density lipoprotein (HDL) particles. In observational analyses, a higher triglyceride composition within HDL subclasses was associated with higher risk of CHD, independently of total cholesterol and triglycerides (strongest hazard ratio per 1 SD higher triglyceride composition in very large HDL 1.35; 95% CI: 1.18-1.54). In conclusion, CETP inhibition does not appear to affect size-specific LDL cholesterol but is likely to lower CHD risk by lowering concentrations of other atherogenic, apolipoprotein B-containing lipoproteins (such as remnant and VLDLs). Inhibition of CETP also lowers triglyceride composition in HDL particles, a phenomenon reflecting combined effects of circulating HDL, triglycerides, and apolipoprotein B-containing particles and is associated with a lower CHD risk in observational analyses. Our results reveal that conventional composite lipid assays may mask heterogeneous effects of emerging lipid-altering therapies.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10−8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10−8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10−3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.

Restless legs syndrome is a prevalent chronic neurological disorder with potentially severe mental and physical health consequences. Clearer understanding of the underlying pathophysiology is needed to improve treatment options. We did a meta-analysis of genome-wide association studies (GWASs) to identify potential molecular targets. In the discovery stage, we combined three GWAS datasets (EU-RLS GENE, INTERVAL, and 23andMe) with diagnosis data collected from 2003 to 2017, in face-to-face interviews or via questionnaires, and involving 15 126 cases and 95 725 controls of European ancestry. We identified common variants by fixed-effect inverse-variance meta-analysis. Significant genome-wide signals (p≤5 × 10−8) were tested for replication in an independent GWAS of 30 770 cases and 286 913 controls, followed by a joint analysis of the discovery and replication stages. We did gene annotation, pathway, and gene-set-enrichment analyses and studied the genetic correlations between restless legs syndrome and traits of interest. We identified and replicated 13 new risk loci for restless legs syndrome and confirmed the previously identified six risk loci. MEIS1 was confirmed as the strongest genetic risk factor for restless legs syndrome (odds ratio 1·92, 95% CI 1·85–1·99). Gene prioritisation, enrichment, and genetic correlation analyses showed that identified pathways were related to neurodevelopment and highlighted genes linked to axon guidance (associated with SEMA6D), synapse formation (NTNG1), and neuronal specification (HOXB cluster family and MYT1). Identification of new candidate genes and associated pathways will inform future functional research. Advances in understanding of the molecular mechanisms that underlie restless legs syndrome could lead to new treatment options. We focused on common variants; thus, additional studies are needed to dissect the roles of rare and structural variations. Deutsche Forschungsgemeinschaft, Helmholtz Zentrum München–Deutsches Forschungszentrum für Gesundheit und Umwelt, National Research Institutions, NHS Blood and Transplant, National Institute for Health Research, British Heart Foundation, European Commission, European Research Council, National Institutes of Health, National Institute of Neurological Disorders and Stroke, NIH Research Cambridge Biomedical Research Centre, and UK Medical Research Council.

Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes ( r g  = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82–0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction. Pooled and sex-specific genome-wide association analyses identify new risk loci for restless legs syndrome and candidates for drug repurposing. Machine learning models combining genetic and other information show improved risk prediction performance.

[This corrects the article DOI: 10.1371/journal.pbio.3000572.].