Human LC3 and GABARAP subfamily members achieve functional specificity via specific structural modulations

Autophagy is a conserved adaptive cellular pathway essential to maintain a variety of physiological functions. Core components of this machinery are the six human Atg8 orthologs that initiate formation of appropriate protein complexes. While these proteins are routinely used as indicators of autophagic flux, it is presently not possible to discern their individual biological functions due to our inability to predict specific binding partners. In our attempts towards determining downstream effector functions, we developed a computational pipeline to define structural determinants of human Atg8 family members that dictate functional diversity. We found a clear evolutionary separation between human LC3 and GABARAP subfamilies and also defined a novel sequence motif responsible for their specificity. By analyzing known protein structures, we observed that functional modules or microclusters reveal a pattern of intramolecular network, including distinct hydrogen bonding of key residues (F52/Y49; a subset of HP2) that may directly modulate their interaction preferences. Multiple molecular dynamics simulations were performed to characterize how these proteins interact with a common protein binding partner, PLEKHM1. Our analysis showed remarkable differences in binding modes via intrinsic protein dynamics, with PLEKHM1-bound GABARAP complexes showing less fluctuations and higher number of contacts. We further mapped 373 genomic variations and demonstrated that distinct cancer-related mutations are likely to lead to significant structural changes. Our findings present a quantitative framework to establish factors underlying exquisite specificity of human Atg8 proteins, and thus facilitate the design of precise modulators.Abbreviations: Atg: autophagy-related; ECs: evolutionary constraints; GABARAP: GABA type A receptor-associated protein; HsAtg8: human Atg8; HP: hydrophobic pocket; KBTBD6: kelch repeat and BTB domain containing 6; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; HIV-1 Nef: human immunodeficiency virus type 1 negative regulatory factor; PLEKHM1: pleckstrin homology and RUN domain containing M1; RMSD: root mean square deviation; SQSTM1/p62: sequestosome 1; WDFY3/ALFY: WD repeat and FYVE domain containing 3.

A 30 kDa polyethylene glycol-enfuvirtide complex enhances the exposure of enfuvirtide in lymphatic viral reservoirs in rats

HIV therapy with anti-retroviral drugs is limited by the poor exposure of viral reservoirs, such as lymphoid tissue, to these small molecule drugs. We therefore investigated the effect of PEGylation on the anti-retroviral activity and subcutaneous lymphatic pharmacokinetics of the peptide-based fusion inhibitor enfuvirtide in thoracic lymph duct cannulated rats. Both the peptide and the PEG were quantified in plasma and lymph via ELISA. Conjugation to a single 5 kDa linear PEG decreased anti-HIV activity three-fold compared to enfuvirtide. Whilst plasma and lymphatic exposure to peptide mass was moderately increased, the loss of anti-viral activity led to an overall decrease in exposure to enfuvirtide activity. A 20 kDa 4-arm branched PEG conjugated with an average of two enfuvirtide peptides decreased peptide activity by six-fold. Plasma and lymph exposure to enfuvirtide, however, increased significantly such that anti-viral activity was increased two- and six-fold respectively. The results suggest that a multi-enfuvirtide-PEG complex may optimally enhance the anti-retroviral activity of the peptide in plasma and lymph.

Exploring Protein Supersecondary Structure Through Changes in Protein Folding, Stability, and Flexibility

The ability to predict how mutations affect protein structure, folding, and flexibility can elucidate the molecular mechanisms leading to disruption of supersecondary structures, the emergence of phenotypes, as well guiding rational protein engineering. The advent of fast and accurate computational tools has enabled us to comprehensively explore the landscape of mutation effects on protein structures, prioritizing mutations for rational experimental validation.Here we describe the use of two complementary web-based in silico methods, DUET and DynaMut, developed to infer the effects of mutations on folding, stability, and flexibility and how they can be used to explore and interpret these effects on protein supersecondary structures.

Understanding molecular consequences of putative drug resistant mutations in Mycobacterium tuberculosis

Genomic studies of Mycobacterium tuberculosis bacteria have revealed loci associated with resistance to anti-tuberculosis drugs. However, the molecular consequences of polymorphism within these candidate loci remain poorly understood. To address this, we have used computational tools to quantify the effects of point mutations conferring resistance to three major anti-tuberculosis drugs, isoniazid (n = 189), rifampicin (n = 201) and D-cycloserine (n = 48), within their primary targets, katG, rpoB, and alr. Notably, mild biophysical effects brought about by high incidence mutations were considered more tolerable, while different structural effects brought about by haplotype combinations reflected differences in their functional importance. Additionally, highly destabilising mutations such as alr Y388, highlighted a functional importance of the wildtype residue. Our qualitative analysis enabled us to relate resistance mutations onto a theoretical landscape linking enthalpic changes with phenotype. Such insights will aid the development of new resistance-resistant drugs and, via an integration into predictive tools, in pathogen surveillance.

Structural and Biochemical Insights into the Function and Evolution of Sulfoquinovosidases

An estimated 10 billion tonnes of sulfoquinovose (SQ) are produced and degraded each year. Prokaryotic sulfoglycolytic pathways catabolize sulfoquinovose (SQ) liberated from plant sulfolipid, or its delipidated form α-d-sulfoquinovosyl glycerol (SQGro), through the action of a sulfoquinovosidase (SQase), but little is known about the capacity of SQ glycosides to support growth. Structural studies of the first reported SQase (Escherichia coli YihQ) have identified three conserved residues that are essential for substrate recognition, but crossover mutations exploring active-site residues of predicted SQases from other organisms have yielded inactive mutants casting doubt on bioinformatic functional assignment. Here, we show that SQGro can support the growth of E. coli on par with d-glucose, and that the E. coli SQase prefers the naturally occurring diastereomer of SQGro. A predicted, but divergent, SQase from Agrobacterium tumefaciens proved to have highly specific activity toward SQ glycosides, and structural, mutagenic, and bioinformatic analyses revealed the molecular coevolution of catalytically important amino acid pairs directly involved in substrate recognition, as well as structurally important pairs distal to the active site. Understanding the defining features of SQases empowers bioinformatic approaches for mapping sulfur metabolism in diverse microbial communities and sheds light on this poorly understood arm of the biosulfur cycle.

DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability

Proteins are highly dynamic molecules, whose function is intrinsically linked to their molecular motions. Despite the pivotal role of protein dynamics, their computational simulation cost has led to most structure-based approaches for assessing the impact of mutations on protein structure and function relying upon static structures. Here we present DynaMut, a web server implementing two distinct, well established normal mode approaches, which can be used to analyze and visualize protein dynamics by sampling conformations and assess the impact of mutations on protein dynamics and stability resulting from vibrational entropy changes. DynaMut integrates our graph-based signatures along with normal mode dynamics to generate a consensus prediction of the impact of a mutation on protein stability. We demonstrate our approach outperforms alternative approaches to predict the effects of mutations on protein stability and flexibility (P-value < 0.001), achieving a correlation of up to 0.70 on blind tests. DynaMut also provides a comprehensive suite for protein motion and flexibility analysis and visualization via a freely available, user friendly web server at http://biosig.unimelb.edu.au/dynamut/.

Kinact: a computational approach for predicting activating missense mutations in protein kinases

Protein phosphorylation is tightly regulated due to its vital role in many cellular processes. While gain of function mutations leading to constitutive activation of protein kinases are known to be driver events of many cancers, the identification of these mutations has proven challenging. Here we present Kinact, a novel machine learning approach for predicting kinase activating missense mutations using information from sequence and structure. By adapting our graph-based signatures, Kinact represents both structural and sequence information, which are used as evidence to train predictive models. We show the combination of structural and sequence features significantly improved the overall accuracy compared to considering either primary or tertiary structure alone, highlighting their complementarity. Kinact achieved a precision of 87% and 94% and Area Under ROC Curve of 0.89 and 0.92 on 10-fold cross-validation, and on blind tests, respectively, outperforming well established tools (P < 0.01). We further show that Kinact performs equally well on homology models built using templates with sequence identity as low as 33%. Kinact is freely available as a user-friendly web server at http://biosig.unimelb.edu.au/kinact/.

Frequent transmission of the Mycobacterium tuberculosis Beijing lineage and positive selection for the EsxW Beijing variant in Vietnam

To examine the transmission dynamics of Mycobacterium tuberculosis (Mtb) isolated from tuberculosis patients in Ho Chi Minh City, Vietnam, we sequenced the whole genomes of 1,635 isolates and compared these with 3,144 isolates from elsewhere. The data identify an underlying burden of disease caused by the endemic Mtb lineage 1 associated with the activation of long-term latent infection, and a threefold higher burden associated with the more recently introduced Beijing lineage and lineage 4 Mtb strains. We find that Beijing lineage Mtb is frequently transferred between Vietnam and other countries, and detect higher levels of transmission of Beijing lineage strains within this host population than the endemic lineage 1 Mtb. Screening for parallel evolution of Beijing lineage-associated SNPs in other Mtb lineages as a signal of positive selection, we identify an alteration in the ESX-5 type VII-secreted protein EsxW, which could potentially contribute to the enhanced transmission of Beijing lineage Mtb in Vietnamese and other host populations.

Tumour risks and genotype-phenotype correlations associated with germline variants in succinate dehydrogenase subunit genes SDHB, SDHC and SDHD

BACKGROUND

Germline pathogenic variants in SDHB/SDHC/SDHD are the most frequent causes of inherited phaeochromocytomas/paragangliomas. Insufficient information regarding penetrance and phenotypic variability hinders optimum management of mutation carriers. We estimate penetrance for symptomatic tumours and elucidate genotype-phenotype correlations in a large cohort of SDHB/SDHC/SDHD mutation carriers.

METHODS

A retrospective survey of 1832 individuals referred for genetic testing due to a personal or family history of phaeochromocytoma/paraganglioma. 876 patients (401 previously reported) had a germline mutation in SDHB/SDHC/SDHD (n=673/43/160). Tumour risks were correlated with in silico structural prediction analyses.

RESULTS

Tumour risks analysis provided novel penetrance estimates and genotype-phenotype correlations. In addition to tumour type susceptibility differences for individual genes, we confirmed that the SDHD:p.Pro81Leu mutation has a distinct phenotype and identified increased age-related tumour risks with highly destabilising SDHB missense mutations. By Kaplan-Meier analysis, the penetrance (cumulative risk of clinically apparent tumours) in SDHB and (paternally inherited) SDHD mutation-positive non-probands (n=371/67 with detailed clinical information) by age 60 years was 21.8% (95% CI 15.2% to 27.9%) and 43.2% (95% CI 25.4% to 56.7%), respectively. Risk of malignant disease at age 60 years in non-proband SDHB mutation carriers was 4.2%(95% CI 1.1% to 7.2%). With retrospective cohort analysis to adjust for ascertainment, cumulative tumour risks for SDHB mutation carriers at ages 60 years and 80 years were 23.9% (95% CI 20.9% to 27.4%) and 30.6% (95% CI 26.8% to 34.7%).

CONCLUSIONS

Overall risks of clinically apparent tumours for SDHB mutation carriers are substantially lower than initially estimated and will improve counselling of affected families. Specific genotype-tumour risk associations provides a basis for novel investigative strategies into succinate dehydrogenase-related mechanisms of tumourigenesis and the development of personalised management for SDHB/SDHC/SDHD mutation carriers.

Publisher Correction: Structural Implications of Mutations Conferring Rifampin Resistance in Mycobacterium leprae

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Fragment-Based Approach to Targeting Inosine-5'-monophosphate Dehydrogenase (IMPDH) from Mycobacterium tuberculosis

Tuberculosis (TB) remains a major cause of mortality worldwide, and improved treatments are needed to combat emergence of drug resistance. Inosine 5′-monophosphate dehydrogenase (IMPDH), a crucial enzyme required for de novo synthesis of guanine nucleotides, is an attractive TB drug target. Herein, we describe the identification of potent IMPDH inhibitors using fragment-based screening and structure-based design techniques. Screening of a fragment library for Mycobacterium thermoresistible (Mth) IMPDH ΔCBS inhibitors identified a low affinity phenylimidazole derivative. X-ray crystallography of the Mth IMPDH ΔCBS–IMP–inhibitor complex revealed that two molecules of the fragment were bound in the NAD binding pocket of IMPDH. Linking the two molecules of the fragment afforded compounds with more than 1000-fold improvement in IMPDH affinity over the initial fragment hit.

Structural Implications of Mutations Conferring Rifampin Resistance in Mycobacterium leprae

The rpoB gene encodes the β subunit of RNA polymerase holoenzyme in Mycobacterium leprae (M. leprae). Missense mutations in the rpoB gene were identified as etiological factors for rifampin resistance in leprosy. In the present study, we identified mutations corresponding to rifampin resistance in relapsed leprosy cases from three hospitals in southern India which treat leprosy patients. DNA was extracted from skin biopsies of 35 relapse/multidrug therapy non-respondent leprosy cases, and PCR was performed to amplify the 276 bp rifampin resistance-determining region of the rpoB gene. PCR products were sequenced, and mutations were identified in four out of the 35 cases at codon positions D441Y, D441V, S437L and H476R. The structural and functional effects of these mutations were assessed in the context of three-dimensional comparative models of wild-type and mutant M. leprae RNA polymerase holoenzyme (RNAP), based on the recently solved crystal structures of RNAP of Mycobacterium tuberculosis, containing a synthetic nucleic acid scaffold and rifampin. The resistance mutations were observed to alter the hydrogen-bonding and hydrophobic interactions of rifampin and the 5' ribonucleotide of the growing RNA transcript. This study demonstrates that rifampin-resistant strains of M. leprae among leprosy patients in southern India are likely to arise from mutations that affect the drug-binding site and stability of RNAP.

Evolution of carbapenem resistance in Acinetobacter baumannii during a prolonged infection

Acinetobacter baumannii is a common causative agent of hospital-acquired infections and a leading cause of infection in burns patients. Carbapenem-resistant A. baumannii is considered a major public-health threat and has been identified by the World Health Organization as the top priority organism requiring new antimicrobials. The most common mechanism for carbapenem resistance in A. baumannii is via horizontal acquisition of carbapenemase genes. In this study, we sampled 20 A. baumannii isolates from a patient with extensive burns, and characterized the evolution of carbapenem resistance over a 45 day period via Illumina and Oxford Nanopore sequencing. All isolates were multidrug resistant, carrying two genomic islands that harboured several antibiotic-resistance genes. Most isolates were genetically identical and represented a single founder genotype. We identified three novel non-synonymous substitutions associated with meropenem resistance: F136L and G288S in AdeB (part of the AdeABC efflux pump) associated with an increase in meropenem MIC to ≥8 µg ml⁻¹; and A515V in FtsI (PBP3, a penicillin-binding protein) associated with a further increase in MIC to 32 µg ml⁻¹. Structural modelling of AdeB and FtsI showed that these mutations affected their drug-binding sites and revealed mechanisms for meropenem resistance. Notably, one of the adeB mutations arose prior to meropenem therapy but following ciprofloxacin therapy, suggesting exposure to one drug whose resistance is mediated by the efflux pump can induce collateral resistance to other drugs to which the bacterium has not yet been exposed.

Relapsed acute lymphoblastic leukemia-specific mutations in NT5C2 cluster into hotspots driving intersubunit stimulation

Activating mutations in NT5C2, a gene encoding cytosolic purine 5'-nucleotidase (cN-II), confer chemoresistance in relapsed acute lymphoblastic leukemia. Here we show that all mutants became independent of allosteric effects of ATP and thus constitutively active. Structural mapping of mutations described in patients demonstrates that 90% of leukemia-specific allelles directly affect two regulatory hotspots within the cN-II molecule-the helix A region: residues 355-365, and the intersubunit interface: helix B (232-242) and flexible interhelical loop L (400-418). Furthermore, analysis of hetero-oligomeric complexes combining wild-type (WT) and mutant subunits showed that the activation is transmitted from the mutated to the WT subunit. This intersubunit interaction forms structural basis of hyperactive NT5C2 in drug-resistant leukemia in which heterozygous NT5C2 mutation gave rise to hetero-tetramer mutant and WT proteins. This enabled us to define criteria to aid the prediction of NT5C2 drug resistance mutations in leukemia.

Huntingtin Inclusions Trigger Cellular Quiescence, Deactivate Apoptosis, and Lead to Delayed Necrosis

Competing models exist in the literature for the relationship between mutant Huntingtin exon 1 (Httex1) inclusion formation and toxicity. In one, inclusions are adaptive by sequestering the proteotoxicity of soluble Httex1. In the other, inclusions compromise cellular activity as a result of proteome co-aggregation. Using a biosensor of Httex1 conformation in mammalian cell models, we discovered a mechanism that reconciles these competing models. Newly formed inclusions were composed of disordered Httex1 and ribonucleoproteins. As inclusions matured, Httex1 reconfigured into amyloid, and other glutamine-rich and prion domain-containing proteins were recruited. Soluble Httex1 caused a hyperpolarized mitochondrial membrane potential, increased reactive oxygen species, and promoted apoptosis. Inclusion formation triggered a collapsed mitochondrial potential, cellular quiescence, and deactivated apoptosis. We propose a revised model where sequestration of soluble Httex1 inclusions can remove the trigger for apoptosis but also co-aggregate other proteins, which curtails cellular metabolism and leads to a slow death by necrosis.

Prediction and Optimization of Pharmacokinetic and Toxicity Properties of the Ligand

A crucial factor for the approval and success of any drug is how it behaves in the body. Many drugs, however, do not reach the market due to poor efficacy or unacceptable side effects. It is therefore important to take these into consideration early in the drug development process, both in the prioritization of potential hits, and optimization of lead compounds. In silico approaches offer a cost and time-effective approach to rapidly screen and optimize pharmacokinetic and toxicity properties. Here we demonstrate the use of the comprehensive analysis system pkCSM, to allow early identification of potential problems, prioritization of hits, and optimization of leads.

A Computational Approach From Gene to Structure Analysis of the Human ABCA4 Transporter Involved in Genetic Retinal Diseases

Purpose

The aim of this article is to report the investigation of the structural features of ABCA4, a protein associated with a genetic retinal disease. A new database collecting knowledge of ABCA4 structure may facilitate predictions about the possible functional consequences of gene mutations observed in clinical practice.

Methods

In order to correlate structural and functional effects of the observed mutations, the structure of mouse P-glycoprotein was used as a template for homology modeling. The obtained structural information and genetic data are the basis of our relational database (ABCA4Database).

Results

Sequence variability among all ABCA4-deposited entries was calculated and reported as Shannon entropy score at the residue level. The three-dimensional model of ABCA4 structure was used to locate the spatial distribution of the observed variable regions. Our predictions from structural in silico tools were able to accurately link the functional effects of mutations to phenotype. The development of the ABCA4Database gathers all the available genetic and structural information, yielding a global view of the molecular basis of some retinal diseases.

Conclusions

ABCA4 modeled structure provides a molecular basis on which to analyze protein sequence mutations related to genetic retinal disease in order to predict the risk of retinal disease across all possible ABCA4 mutations. Additionally, our ABCA4 predicted structure is a good starting point for the creation of a new data analysis model, appropriate for precision medicine, in order to develop a deeper knowledge network of the disease and to improve the management of patients.

Optimizing genomic medicine in epilepsy through a gene-customized approach to missense variant interpretation

Gene panel and exome sequencing have revealed a high rate of molecular diagnoses among diseases where the genetic architecture has proven suitable for sequencing approaches, with a large number of distinct and highly penetrant causal variants identified among a growing list of disease genes. The challenge is, given the DNA sequence of a new patient, to distinguish disease-causing from benign variants. Large samples of human standing variation data highlight regional variation in the tolerance to missense variation within the protein-coding sequence of genes. This information is not well captured by existing bioinformatic tools, but is effective in improving variant interpretation. To address this limitation in existing tools, we introduce the missense tolerance ratio (MTR), which summarizes available human standing variation data within genes to encapsulate population level genetic variation. We find that patient-ascertained pathogenic variants preferentially cluster in low MTR regions (P < 0.005) of well-informed genes. By evaluating 20 publicly available predictive tools across genes linked to epilepsy, we also highlight the importance of understanding the empirical null distribution of existing prediction tools, as these vary across genes. Subsequently integrating the MTR with the empirically selected bioinformatic tools in a gene-specific approach demonstrates a clear improvement in the ability to predict pathogenic missense variants from background missense variation in disease genes. Among an independent test sample of case and control missense variants, case variants (0.83 median score) consistently achieve higher pathogenicity prediction probabilities than control variants (0.02 median score; Mann-Whitney U test, P < 1 × 10⁻¹⁶). We focus on the application to epilepsy genes; however, the framework is applicable to disease genes beyond epilepsy.

Combating mutations in genetic disease and drug resistance: understanding molecular mechanisms to guide drug design

INTRODUCTION

Mutations introduce diversity into genomes, leading to selective changes and driving evolution. These changes have contributed to the emergence of many of the current major health concerns of the 21st century, from the development of genetic diseases and cancers to the rise and spread of drug resistance. The experimental systematic testing of all mutations in a system of interest is impractical and not cost-effective, which has created interest in the development of computational tools to understand the molecular consequences of mutations to aid and guide rational experimentation. Areas covered: Here, the authors discuss the recent development of computational methods to understand the effects of coding mutations to protein function and interactions, particularly in the context of the 3D structure of the protein. Expert opinion: While significant progress has been made in terms of innovative tools to understand and quantify the different range of effects in which a mutation or a set of mutations can give rise to a phenotype, a great gap still exists when integrating these predictions and drawing causality conclusions linking variants. This often requires a detailed understanding of the system being perturbed. However, as part of the drug development process it can be used preemptively in a similar fashion to pharmacokinetics predictions, to guide development of therapeutics to help guide the design and analysis of clinical trials, patient treatment and public health policy strategies.

DNA-PKcs, Allostery, and DNA Double-Strand Break Repair: Defining the Structure and Setting the Stage

DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is central to the regulation of the DNA damage response and repair through nonhomologous end joining. The structure has proved challenging due to its large size and multiple HEAT repeats. We have recently reported crystals of selenomethionine-labeled DNA-PKcs complexed with native KU80ct₁₉₄ (KU80 residues 539-732) diffracting to 4.3Å resolution. The novel use of crystals of selenomethionine-labeled protein expressed in HeLa cells has facilitated the use of single anomalous X-ray scattering of this 4128 amino acid, multiple HEAT-repeat structure. The monitoring of the selenomethionines in the anomalous-difference density map has allowed the checking of the amino acid residue registration in the electron density, and the labeling of the Ku-C-terminal moiety with selenomethionine has further allowed its identification in the structure of the complex with DNA-PKcs. The crystal structure defines a stage on which many of the components assemble and regulate the kinase activity through modulating the conformation and allosteric regulation of kinase activity.

SDHA related tumorigenesis: a new case series and literature review for variant interpretation and pathogenicity

PURPOSE

To evaluate the role of germline SDHA mutation analysis by (1) comprehensive literature review, (2) description of novel germline SDHA mutations and (3) in silico structural prediction analysis of missense substitutions in SDHA.

PATIENTS AND METHODS

A systematic literature review and a retrospective review of the molecular and clinical features of patients identified with putative germline variants in UK molecular genetic laboratories was performed. To evaluate the molecular consequences of SDHA missense variants, a novel model of the SDHA/B/C/D complex was generated and the structural effects of missense substitutions identified in the literature, our UK novel cohort and a further 32 "control missense variants" were predicted by the mCSM computational platform. These structural predictions were correlated with the results of tumor studies and other bioinformatic predictions.

RESULTS

Literature review revealed reports of 17 different germline SDHA variants in 47 affected individuals from 45 kindreds. A further 10 different variants in 15 previously unreported cases (seven novel variants in eight patients) were added from our UK series. In silico structural prediction studies of 11 candidate missense germline mutations suggested that most (63.7%) would destabilize the SDHA protomer, and that most (78.1%) rare SDHA missense variants present in a control data set (ESP6500) were also associated with impaired protein stability.

CONCLUSION

The clinical spectrum of SDHA-associated neoplasia differs from that of germline mutations in other SDH-subunits. The interpretation of the significance of novel SDHA missense substitutions is challenging. We recommend that multiple investigations (e.g. tumor studies, metabolomic profiling) should be performed to aid classification of rare missense variants before genetic testing results are used to influence clinical management.

The Inosine Monophosphate Dehydrogenase, GuaB2, Is a Vulnerable New Bactericidal Drug Target for Tuberculosis

VCC234718, a molecule with growth inhibitory activity against Mycobacterium tuberculosis (Mtb), was identified by phenotypic screening of a 15344-compound library. Sequencing of a VCC234718-resistant mutant identified a Y487C substitution in the inosine monophosphate dehydrogenase, GuaB2, which was subsequently validated to be the primary molecular target of VCC234718 in Mtb. VCC234718 inhibits Mtb GuaB2 with a Ki of 100 nM and is uncompetitive with respect to IMP and NAD+. This compound binds at the NAD+ site, after IMP has bound, and makes direct interactions with IMP; therefore, the inhibitor is by definition uncompetitive. VCC234718 forms strong pi interactions with the Y487 residue side chain from the adjacent protomer in the tetramer, explaining the resistance-conferring mutation. In addition to sensitizing Mtb to VCC234718, depletion of GuaB2 was bactericidal in Mtb in vitro and in macrophages. When supplied at a high concentration (≥125 μM), guanine alleviated the toxicity of VCC234718 treatment or GuaB2 depletion via purine salvage. However, transcriptional silencing of guaB2 prevented Mtb from establishing an infection in mice, confirming that Mtb has limited access to guanine in this animal model. Together, these data provide compelling validation of GuaB2 as a new tuberculosis drug target.

Essential but Not Vulnerable: Indazole Sulfonamides Targeting Inosine Monophosphate Dehydrogenase as Potential Leads against Mycobacterium tuberculosis

A potent, noncytotoxic indazole sulfonamide was identified by high-throughput screening of >100,000 synthetic compounds for activity against Mycobacterium tuberculosis (Mtb). This noncytotoxic compound did not directly inhibit cell wall biogenesis but triggered a slow lysis of Mtb cells as measured by release of intracellular green fluorescent protein (GFP). Isolation of resistant mutants followed by whole-genome sequencing showed an unusual gene amplification of a 40 gene region spanning from Rv3371 to Rv3411c and in one case a potential promoter mutation upstream of guaB2 (Rv3411c) encoding inosine monophosphate dehydrogenase (IMPDH). Subsequent biochemical validation confirmed direct inhibition of IMPDH by an uncompetitive mode of inhibition, and growth inhibition could be rescued by supplementation with guanine, a bypass mechanism for the IMPDH pathway. Beads containing immobilized indazole sulfonamides specifically interacted with IMPDH in cell lysates. X-ray crystallography of the IMPDH-IMP-inhibitor complex revealed that the primary interactions of these compounds with IMPDH were direct pi-pi interactions with the IMP substrate. Advanced lead compounds in this series with acceptable pharmacokinetic properties failed to show efficacy in acute or chronic murine models of tuberculosis (TB). Time-kill experiments in vitro suggest that sustained exposure to drug concentrations above the minimum inhibitory concentration (MIC) for 24 h were required for a cidal effect, levels that have been difficult to achieve in vivo. Direct measurement of guanine levels in resected lung tissue from tuberculosis-infected animals and patients revealed 0.5-2 mM concentrations in caseum and normal lung tissue. The high lesional levels of guanine and the slow lytic, growth-rate-dependent effect of IMPDH inhibition pose challenges to developing drugs against this target for use in treating TB.