Identification Of Novel Drug Targets Research Articles

Potential Drug Target Identification in Porphyromonas gingivalis using In-silico Subtractive Metabolic Pathway Analysis

Introduction: Porphyromonas Gingivalis (P. gingivalis) a primary periodontal disease pathogen. This bacterium affects sub-gingival tissue and leads to loss of teeth and alveolar bone destruction in the acute stage. In recent years, P. gingivalis is often connected with other diseases such as rheumatoid arthritis, diabetes, Alzheimer’s, and heart disease, though the aetiology is still unclear.
 Objective: The use of commonly available drugs to treat periodontitis results in various side effects, in particular multi-drug resistant strains. As the development of multidrugresistant strains frequently urges the identification of novel drug targets, the aim of this study is to identify specific targets in the narrow spectrum to combat oral pathogens.
 Methodology: This study used a comparative and subtractive pathway analysis approach to identify potential drug targets specific to P. gingivalis.
 Results: The in-silico comparison of the P. gingivalis and Homo sapiens (H. sapiens) metabolic pathways resulted in 13 unique pathogen pathways. A homology search of the 67 enzymes in the unique bacterial pathway using the BLASTp program against the Homo sapiens proteome resulted in fifteen possible targets that are non-homologous to the human proteome. Thirteen genes among 15 potent target encoders are key DEG genes indispensable for P. gingivalis’s survival. A comprehensive analysis of the literature identified three potential therapeutic drug targets.
 Conclusions: The three most relevant drug targets are Arabinose-5-phosphate isomerase, UDP-2,3-diacylglucosamine hydrolase, and Undecaprenyl diphosphatase. Upon corroboration, these targets may give rise to narrow-spectrum antibiotics that can specificallytreat thedental infection.
 Bangladesh Journal of Medical Science Vol.20(4) 2021 p.887-896

Improving Prediction of Helminth Aminoacyl‐tRNA Synthetases through Manual Analysis of Genomic Data

Helminth is a generic term for the parasitic worms that negatively impact health outcomes for a roughly a quarter of the global population. Although more than 150 helminth genomes have now been sequenced, protein sequence predictions available in compiled genomes and public databases are often incorrect. These errors hinder identification of novel drug targets in helminth genomes. We have focused on identifying and correcting predictions for aminoacyl-tRNA synthetase genes. These enzymes are targets of effective antiparasitic therapies in in other organisms. Using published genomic information available in WormBase from a set of twelve human-infecting helminths, we initially corrected exon boundary predictions using RNAseq data. The proposed protein sequences were then validated using multiple-sequence alignments of enzymes from helminths and other organisms, allowing us to identify helminth-specific features. We confirmed a high error rate in predictions of the studied genes, with 60% requiring at least one correction and an average of 4.3 corrections made per gene. Our analysis also identified several unique features of helminth aminoacyl-tRNA synthetases, particularly among trematode (fluke) and platyhelminth (flatworm) proteins and in mitochondrially-targeted enzymes.

Effects of Antidepressant Treatment on Peripheral Biomarkers in Patients with Major Depressive Disorder (MDD).

Major depressive disorder (MDD) is one of the most prevalent mental illness and a leading cause of disability worldwide. Despite a range of effective treatments, more than 30% of patients do not achieve remission as a result of conventional therapy. In these circumstances the identification of novel drug targets and pathogenic factors becomes essential for selecting more efficacious and personalized treatment. Increasing evidence has implicated the role of inflammation in the pathophysiology of depression, revealing potential new pathways and treatment options. Moreover, convergent evidence indicates that MDD is related to disturbed neurogenesis and suggests a possible role of neurotrophic factors in recovery of function in patients. Although the influence of antidepressants on inflammatory cytokines balance was widely reported in various studies, the exact correlation between drugs used and specific cytokines and neurotrophins serum levels often remains inconsistent. Available data suggest anti-inflammatory properties of selective serotonin reuptake inhibitors (SSRIs), selective serotonin and noradrenaline inhibitors (SNRIs), and tricyclic antidepressants (TCAs) as a possible additional mechanism of reduction of depressive symptoms. In this review, we outline emerging data regarding the influence of different antidepressant drugs on a wide array of peripheral biomarkers such as interleukin (IL)-1ß, IL-2, IL-5, IL-6, IL-8, IL-10, C-reactive protein (CRP), or interferon (IFN)-γ. Presented results indicate anti-inflammatory effect for selected drugs or lack of such effect. Research in this field is insufficient to define the role of inflammatory markers as a predictor of treatment response in MDD.

Metabolic Diseases and Down Syndrome: How Are They Linked Together?

Down syndrome is a genetic disorder caused by the presence of a third copy of chromosome 21, associated with intellectual disabilities. Down syndrome is associated with anomalies of both the nervous and endocrine systems. Over the past decades, dramatic advances in Down syndrome research and treatment have helped to extend the life expectancy of these patients. Improved life expectancy is obviously a positive outcome, but it is accompanied with the need to address previously overlooked complications and comorbidities of Down syndrome, including obesity and diabetes, in order to improve the quality of life of Down syndrome patients. In this focused review, we describe the associations between Down syndrome and comorbidities, obesity and diabetes, and we discuss the understanding of proposed mechanisms for the association of Down syndrome with metabolic disorders. Drawing molecular mechanisms through which Type 1 diabetes and Type 2 diabetes could be linked to Down syndrome could allow identification of novel drug targets and provide therapeutic solutions to limit the development of metabolic and cognitive disorders.

Cell Surface Biosynthesis and Remodeling Pathways in Mycobacteria Reveal New Drug Targets.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), remains the leading cause of death from an infectious bacterium and is responsible for 1.8 million deaths annually. The emergence of drug resistance, together with the need for a shorter more effective regimen, has prompted the drive to identify novel therapeutics with the bacterial cell surface emerging as a tractable area for drug development. Mtb assembles a unique, waxy, and complex cell envelope comprised of the mycolyl-arabinogalactan-peptidoglycan complex and an outer capsule like layer, which are collectively essential for growth and pathogenicity while serving as an inherent barrier against antibiotics. A detailed understanding of the biosynthetic pathways required to assemble the polymers that comprise the cell surface will enable the identification of novel drug targets as these structures provide a diversity of biochemical reactions that can be targeted. Herein, we provide an overview of recently described mycobacterial cell wall targeting compounds, novel drug combinations and their modes of action. We anticipate that this summary will enable prioritization of the best pathways to target and triage of the most promising molecules to progress for clinical assessment.

Identification of novel non-homologous drug targets against Acinetobacter baumannii using subtractive genomics and comparative metabolic pathway analysis

Lack of effective antibiotics and the development of multidrug resistance in clinical isolates of nosocomial pathogen Acinetobacter baumanni has necessitated the identification of novel drug targets. The study is divided into three phases, in phase I, four different sets of proteins were subjected to a chokepoint, plasmid, resistance genes, and virulence factors analysis. After phase 1 analysis we obtained two hundred twenty-two proteins which were analyzed further in the phase II for essentiality and homology. Fifty-eight proteins identified as target candidates were studied for qualitative characteristics. Among them, 32 were identified as cytoplasmic membrane, 17 as cytoplasmic, one as periplasmic, one as outer membrane, two as extracellular, and location of 5 was not known. Druggability analysis revealed that 18 proteins were druggable, and 40 were novel. Drug targets obtained in the present study can be utilized for the identification of novel antimicrobials for the treatment of infections caused by multidrug-resistant A. baumannii. Predicted drug targets can be evaluated for their binding affinity by molecular docking studies and thus accelerating the process of drug discovery.

Identification of Novel SARS-CoV-2 Drug Targets by Host MicroRNAs and Transcription Factors Co-regulatory Interaction Network Analysis.

Understanding the host regulatory mechanisms opposing virus infection and virulence can provide actionable insights to identify novel therapeutics against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have used a network biology approach to elucidate the crucial factors involved in host responses involving host–microRNA (miRNA) interactions with host and virus genes using recently published experimentally verified protein–protein interaction data. We were able to identify 311 host genes to be potentially targetable by 2,197 human miRNAs. These miRNAs are known to be involved in various biological processes, such as T-cell differentiation and activation, virus replication, and immune system. Among these, the anti-viral activity of 38 miRNAs to target 148 host genes is experimentally validated. Six anti-viral miRNAs, namely, hsa-miR-1-3p, hsa-miR-17-5p, hsa-miR-199a-3p, hsa-miR-429, hsa-miR-15a-5p, and hsa-miR-20a-5p, are previously reported to be anti-viral in respiratory diseases and were found to be downregulated. The interaction network of the 2,197 human miRNAs and interacting transcription factors (TFs) enabled the identification of 51 miRNAs to interact with 77 TFs inducing activation or repression and affecting gene expression of linked genes. Further, from the gene regulatory network analysis, the top five hub genes HMOX1, DNMT1, PLAT, GDF1, and ITGB1 are found to be involved in interferon (IFN)-α2b induction, epigenetic modification, and modulation of anti-viral activity. The comparative miRNAs target identification analysis in other respiratory viruses revealed the presence of 98 unique host miRNAs targeting SARS-CoV-2 genome. Our findings identify prioritized key regulatory interactions that include miRNAs and TFs that provide opportunities for the identification of novel drug targets and development of anti-viral drugs.

Modeling Novel Putative Drugs and Vaccine Candidates against Tick-Borne Pathogens: A Subtractive Proteomics Approach.

Ticks and tick-borne pathogens (TBPs) continuously causing substantial losses to the public and veterinary health sectors. The identification of putative drug targets and vaccine candidates is crucial to control TBPs. No information has been recorded on designing novel drug targets and vaccine candidates based on proteins. Subtractive proteomics is an in silico approach that utilizes extensive screening for the identification of novel drug targets or vaccine candidates based on the determination of potential target proteins available in a pathogen proteome that may be used effectively to control diseases caused by these infectious agents. The present study aimed to investigate novel drug targets and vaccine candidates by utilizing subtractive proteomics to scan the available proteomes of TBPs and predict essential and non-host homologous proteins required for the survival of these diseases causing agents. Subtractive proteome analysis revealed a list of fifteen essential, non-host homologous, and unique metabolic proteins in the complete proteome of selected pathogens. Among these therapeutic target proteins, three were excluded due to the presence in host gut metagenome, eleven were found to be highly potential drug targets, while only one was found as a potential vaccine candidate against TBPs. The present study may provide a foundation to design potential drug targets and vaccine candidates for the effective control of infections caused by TBPs.

Synthesis, Anticancer Activity on Prostate Cancer Cell Lines and Molecular Modeling Studies of Flurbiprofen-Thioether Derivatives as Potential Target of MetAP (Type II).

Prostate cancer is still one of the serious causes of mortality and morbidity in men. Despite recent advances in anticancer therapy, there is a still need of novel agents with more efficacy and specificity in the treatment of prostate cancer. Because of its function on angiogenesis and overexpression in the prostate cancer, methionine aminopeptidase-2 (MetAP-2) has been a potential target for novel drug design recently. A novel series of Flurbiprofen derivatives N-(substituted)-2-(2-(2-fluoro-[1,1'- biphenyl]-4-il)propanoyl)hydrazinocarbothioamide (3a-c), 4-substituted-3-(1-(2-fluoro-[1,1'-biphenyl]- 4-yl)ethyl)-1H-1,2,4-triazole-5(4H)-thione (4a-d), 3-(substitutedthio)-4-(substituted-phenyl)- 5-(1-(2-fluoro-[1,1'-biphenyl]-4-yl)ethyl)-4H-1,2,4-triazole (5a-y) were synthesized. The purpose of the research was to evaluate these derivatives against MetAP-2 in vitro and in silico to obtain novel specific and effective anticancer agents against prostate cancer. The chemical structures and purities of the compounds were defined by spectral methods (1H-NMR, 13C-NMR, HR-MS and FT-IR) and elemental analysis. Anticancer activities of the compounds were evaluated in vitro by using MTS method against PC-3 and DU-143 (androgenindependent human prostate cancer cell lines) and LNCaP (androgen-sensitive human prostate adenocarcinoma) prostate cancer cell lines. Cisplatin was used as a positive sensitivity reference standard. Compounds 5b and 5u; 3c, 5b and 5y; 4d and 5o showed the most potent biological activity against PC3 cancer cell line (IC50= 27.1 μM, and 5.12 μM, respectively), DU-145 cancer cell line (IC50= 11.55 μM, 6.9 μM and 9.54 μM, respectively) and LNCaP cancer cell line (IC50= 11.45 μM and 26.91 μM, respectively). Some compounds were evaluated for their apoptotic caspases protein expression (EGFR/PI3K/AKT pathway) by Western blot analysis in androgen independent- PC3 cells. BAX, caspase 9, caspsase 3 and anti-apoptotic BcL-2 mRNA levels of some compounds were also investigated. In addition, molecular modeling studies of the compounds on MetAP-2 enzyme active site were evaluated in order to get insight into binding mode and energy. A series of Flurbiprofen-thioether derivatives were synthesized. This study presented that some of the synthesized compounds have remarkable anticancer and apoptotic activities against prostate cancer cells. Also, molecular modeling studies exhibited that there is a correlation between molecular modeling and anticancer activity results.

PND25 Identification of NOVEL Drug Targets and Exploring Drug Repurposing Avenues for Amyotrophic Lateral Sclerosis

PND25 Identification of NOVEL Drug Targets and Exploring Drug Repurposing Avenues for Amyotrophic Lateral Sclerosis

Metabolic fitness of Candida albicans is indispensable for functional drug efflux, ergosterol, and chitin biosynthesis.

Background and Purpose: The increment in fungal infections, particularly due to Candida species, is alarming due to the emergence of multidrug resistance (MDR). Hence, the identification of novel drug targets to circumvent the problem of MDR requires immediate attention. The metabolic pathway, such as glyoxylate cycle (GC), which utilizes key enzymes (isocitrate lyase [ICL] and malate synthase [MLS]), enables C. albicans to adapt under glucose-deficient conditions. This study uncovers the effect of GC disruption on the major MDR mechanisms of C. albicans as a human pathogenic fungus.Materials and Methods: For the purpose of the study, efflux pump activity was assessed by phenotypic susceptibilities in the presence of substrates rhodamine 6G (R6G) and Nile red, along with R6G extracellular concentration (527 nm). In addition, ergosterol content was estimated by the alcoholic potassium hydroxide hydrolysis method. The estimation of chitin was also accomplished by the absorbance (520 nm) of glucosamine released by acid hydrolysis.Results: The results revealed that the disruption of ICL enzyme gene (Δicl1) led to the impairment of the efflux activity of multidrug transporters belonging to the ATP - binding cassette superfamily. It was further shown that Δicl1 mutant exhibited diminished ergosterol and chitin contents. In addition, all abrogated phenotypes could be rescued in the reverting strain of Δicl1 mutant.Conclusion: Based on the findings, the disruption of GC affected efflux activity and the synthesis of ergosterol and chitin. The present study for the first time revealed that metabolic fitness was associated with functional drug efflux, ergosterol and chitin biosynthesis and validated GC as an antifungal target. However, further studies are needed to comprehend and exploit this therapeutic opportunity.

Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets.

The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia-present in many filariae-which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.

Personal Medicine and Bone Metastases: Biomarkers, Micro-RNAs and Bone Metastases

Bone metastasis is a major cause of morbidity within solid tumours of the breast, prostate, lung and kidney. Metastasis to the skeleton is associated with a wide range of complications including bone fractures, spinal cord compression, hypercalcaemia and increased bone pain. Improved treatments for bone metastasis, such as the use of anti-bone resorptive bisphosphonate agents, within post-menopausal women have improved disease-free survival; however, these treatments are not without side effects. There is thus a need for biomarkers, which will predict the risk of developing the spread to bone within these cancers. The application of molecular profiling techniques, together with animal model systems and engineered cell-lines has enabled the identification of a series of potential bone-metastasis biomarker molecules predictive of bone metastasis risk. Some of these biomarker candidates have been validated within patient-derived samples providing a step towards clinical utility. Recent developments in multiplex biomarker quantification now enable the simultaneous measurement of up to 96 micro-RNA/protein molecules in a spatially defined manner with single-cell resolution, thus enabling the characterisation of the key molecules active at the sites of pre-metastatic niche formation as well as tumour-stroma signalling. These technologies have considerable potential to inform biomarker discovery. Additionally, a potential future extension of these discoveries could also be the identification of novel drug targets within cancer spread to bone. This chapter summarises recent findings in biomarker discovery within the key bone metastatic cancers (breast, prostate, lung and renal cell carcinoma). Tissue-based and circulating blood-based biomarkers are discussed from the fields of genomics, epigenetic regulation (micro-RNAs) and protein/cell-signalling together with a discussion of the potential future development of these markers towards clinical development.

Intervening along the spectrum of tuberculosis: meeting report from the World TB Day nanosymposium in the Institute of Infectious Disease and Molecular Medicine at the University of Cape Town.

Tuberculosis (TB), caused by the highly infectious Mycobacterium tuberculosis, remains a leading cause of death worldwide, with an estimated 1.6 million associated deaths reported in 2017. In South Africa, an estimated 322,000 (range 230,000-428,000) people were infected with TB in 2017, and a quarter of them lost their lives due to the disease. Bacille Calmette-Guérin (BCG) remains the only effective vaccine against disseminated TB, but its inability to confer complete protection against pulmonary TB in adolescents and adults calls for an urgent need to develop new and better vaccines. There is also a need to identify markers of disease protection and develop novel drugs. It is within this backdrop that we convened a nanosymposium at the Institute of Infectious Disease and Molecular Medicine at the University of Cape Town to commemorate World TB Day and showcase recent findings generated by early career scientists in the institute. The speakers spoke on four broad topics: identification of novel drug targets, development of host-directed drug therapies, transmission of TB and immunology of TB/HIV co-infections.

From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases.

Genome-wide association studies (GWAS) have successfully mapped thousands of loci associated with complex traits. These associations could reveal the molecular mechanisms altered in common complex diseases and result in the identification of novel drug targets. However, GWAS have also left a number of outstanding questions. In particular, the majority of disease-associated loci lie in non-coding regions of the genome and, even though they are thought to play a role in gene expression regulation, it is unclear which genes they regulate and in which cell types or physiological contexts this regulation occurs. This has hindered the translation of GWAS findings into clinical interventions. In this review we summarize how these challenges have been addressed over the last decade, with a particular focus on the integration of GWAS results with functional genomics datasets. Firstly, we investigate how the tissues and cell types involved in diseases can be identified using methods that test for enrichment of GWAS variants in genomic annotations. Secondly, we explore how to find the genes regulated by GWAS loci using methods that test for colocalization of GWAS signals with molecular phenotypes such as quantitative trait loci (QTLs). Finally, we highlight potential future research avenues such as integrating GWAS results with single-cell sequencing read-outs, designing functionally informed polygenic risk scores (PRS), and validating disease associated genes using genetic engineering. These tools will be crucial to identify new drug targets for common complex diseases.

Genome Subtraction and Comparison for the Identification of Novel Drug Targets against Mycobacterium avium subsp. hominissuis.

Mycobacterium avium complex (MAC) is a major cause of non-tuberculous pulmonary and disseminated diseases worldwide, inducing bronchiectasis, and affects HIV and immunocompromised patients. In MAC, Mycobacterium avium subsp. hominissuis is a pathogen that infects humans and mammals, and that is why it is a focus of this study. It is crucial to find essential drug targets to eradicate the infections caused by these virulent microorganisms. The application of bioinformatics and proteomics has made a significant impact on discovering unique drug targets against the deadly pathogens. One successful bioinformatics methodology is the use of in silico subtractive genomics. In this study, the aim was to identify the unique, non-host and essential protein-based drug targets of Mycobacterium avium subsp. hominissuis via in silico a subtractive genomics approach. Therefore, an in silico subtractive genomics approach was applied in which complete proteome is subtracted systematically to shortlist potential drug targets. For this, the complete dataset of proteins of Mycobacterium avium subsp. hominissuis was retrieved. The applied subtractive genomics method, which involves the homology search between the host and the pathogen to subtract the non-druggable proteins, resulted in the identification of a few prioritized potential drug targets against the three strains of M. avium subsp. Hominissuis, i.e., MAH-TH135, OCU466 and A5. In conclusion, the current study resulted in the prioritization of vital drug targets, which opens future avenues to perform structural as well as biochemical studies on predicted drug targets against M. avium subsp. hominissuis.

A computational subtractive genome analysis for the characterization of novel drug targets in Klebsiella pneumonia strain PittNDM01

The emergence of carbapenem-resistant Klebsiella Pneumoniae had been reported previously, which needs rapid attention. Currently, Pittsburgh University Hospital reported a new strain of carbapenem-resistant Klebsiella pneumoniae that was co-producing OXA-232 and NDM-1 named as PittNDM01. This strain is resistant to almost all beta-lactam antibiotics such as Carbapenem as well as to fluoroquinolones and aminoglycosides. Globally, failure to the wide-spread pathogenic strains had been observed due to the increased and antibiotic resistance, which leads to less antimicrobial drug efficacy. Since last decades, computational genomic approaches have been introduced to fight against resistant pathogens, which is an advanced approach for novel drug targets investigation. The current study emphasizes the utilization of the available genomic and proteomic data of Klebsiella pneumoniae PittNDM01 for the identification of novel drug targets for future drug developments. Comparative genomic analysis and molecular biological tools were applied, results in observing 582 non-human homologous-essential proteins of Klebsiella pneumoniae. Among the total 582 proteins, 66 were closely related to the pathogen-specific pathway. Out of all 66-targeted proteins, ten non-homologous essential proteins were found to have druggability potential. The subcellular localization of these proteins revealed; 6 proteins in the cytoplasm, 2 in the inner membrane, and one each in periplasmic space and outer membrane. All the above 10 proteins were compared to the proteins sequences of gut flora to eliminate the homologous proteins. In total, 6-novel non-human and non-gut flora essential drug targets of Klebsiella pneumoniae PittNDM01 strain were identified. Further, the 3D structures of the identified drug target proteins were developed, and protein-protein interaction network analysis was performed to know the functional annotation of the desire proteins. Therefore, these non-homologous essential targets ensure the survival of the pathogen and hence can be targeted for drug discovery.

GammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning

The biology of bacterial cells is, in general, based on information encoded on circular chromosomes. Regulation of chromosome replication is an essential process that mostly takes place at the origin of replication (oriC), a locus unique per chromosome. Identification of high numbers of oriC is a prerequisite for systematic studies that could lead to insights into oriC functioning as well as the identification of novel drug targets for antibiotic development. Current methods for identifying oriC sequences rely on chromosome-wide nucleotide disparities and are therefore limited to fully sequenced genomes, leaving a large number of genomic fragments unstudied. Here, we present gammaBOriS (Gammaproteobacterial oriCSearcher), which identifies oriC sequences on gammaproteobacterial chromosomal fragments. It does so by employing motif-based machine learning methods. Using gammaBOriS, we created BOriS DB, which currently contains 25,827 gammaproteobacterial oriC sequences from 1,217 species, thus making it the largest available database for oriC sequences to date. Furthermore, we present gammaBOriTax, a machine-learning based approach for taxonomic classification of oriC sequences, which was trained on the sequences in BOriS DB. Finally, we extracted the motifs relevant for identification and classification decisions of the models. Our results suggest that machine learning sequence classification approaches can offer great support in functional motif identification.

Combined siRNA and Small-Molecule Phenotypic Screening Identifies Targets Regulating Rhinovirus Replication in Primary Human Bronchial Epithelial Cells

Human rhinovirus (RV) is the most common cause of acute upper respiratory tract infections and has recently been shown to play a significant role in exacerbations of asthma and chronic obstructive pulmonary disease (COPD). There is a significant unmet medical need for agents for the prevention and/or treatment of exacerbations triggered by human RV infection. Phenotypic drug discovery programs using different perturbation modalities, for example, siRNA, small-molecule compounds, and CRISPR, hold significant value for identifying novel drug targets. We have previously reported the identification of lanosterol synthase as a novel regulator of RV2 replication through a phenotypic screen of a library of siRNAs against druggable genes in normal human bronchial epithelial (NHBE) cells. Here, we describe a follow-up phenotypic screen of small-molecule compounds that are annotated to be pharmacological regulators of target genes that were identified to significantly affect RV2 replication in the siRNA primary screen of 10,500 druggable genes. Two hundred seventy small-molecule compounds selected for interacting with 122 target gene hits were screened in the primary RV2 assay in NHBE cells by quantifying viral replication via in situ hybridization followed by secondary quantitative PCR-based assays for RV2, RV14, and RV16. The described follow-up phenotypic screening allowed us to identify Fms-related tyrosine kinase 4 (FLT4) as a novel target regulating RV replication. We demonstrate that a combination of siRNA and small-molecule compound screening models is a useful phenotypic drug discovery approach for the identification of novel drug targets.

Peptidoglycan Hydrolases RipA and Ami1 Are Critical for Replication and Persistence of Mycobacterium tuberculosis in the Host.

Synthesis and cleavage of the cell wall polymer peptidoglycan (PG) are carefully orchestrated processes and are essential for the growth and survival of bacteria. Yet, the function and importance of many enzymes that act on PG in Mycobacterium tuberculosis remain to be elucidated. We demonstrate that the activity of the N-acetylmuramyl-l-alanine amidase Ami1 is dispensable for cell division in M. tuberculosisin vitro yet contributes to the bacterium's ability to persist during chronic infection in mice. Furthermore, the d,l-endopeptidase RipA, a predicted essential enzyme, is dispensable for the viability of M. tuberculosis but required for efficient cell division in vitro and in vivo. Depletion of RipA sensitizes M. tuberculosis to rifampin and to cell envelope-targeting antibiotics. Ami1 helps sustain residual cell division in cells lacking RipA, but the partial redundancy provided by Ami1 is not sufficient during infection, as depletion of RipA prevents M. tuberculosis from replicating in macrophages and leads to dramatic killing of the bacteria in mice. Notably, RipA is essential for persistence of M. tuberculosis in mice, suggesting that cell division is required during chronic mouse infection. Despite the multiplicity of enzymes acting on PG with redundant functions, we have identified two PG hydrolases that are important for M. tuberculosis to replicate and persist in the host.IMPORTANCE Tuberculosis (TB) is a major global heath burden, with 1.6 million people succumbing to the disease every year. The search for new drugs to improve the current chemotherapeutic regimen is crucial to reducing this global health burden. The cell wall polymer peptidoglycan (PG) has emerged as a very successful drug target in bacterial pathogens, as many currently used antibiotics target the synthesis of this macromolecule. However, the multitude of genes encoding PG-synthesizing and PG-modifying enzymes with apparent redundant functions has hindered the identification of novel drug targets in PG synthesis in Mycobacterium tuberculosis Here, we demonstrate that two PG-cleaving enzymes are important for virulence of M. tuberculosis In particular, the d,l-endopeptidase RipA represents a potentially attractive drug target, as its depletion results in the clearance of M. tuberculosis from the host and renders the bacteria hypersusceptible to rifampin, a frontline TB drug, and to several cell wall-targeting antibiotics.