Anti-infective Drug Discovery Research Articles

Application of machine learning based genome sequence analysis in pathogen identification.

Infectious diseases caused by pathogenic microorganisms pose a serious threat to human health. Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious diseases remain a significant public health concern. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance requires concerted interdisciplinary efforts. With the development of computer technology and the continuous exploration of artificial intelligence(AI)applications in the biomedical field, the automatic morphological recognition and image processing of microbial images under microscopes have advanced rapidly. The research team of Institute of Microbiology, Chinese Academy of Sciences has developed a single cell microbial identification technology combining Raman spectroscopy and artificial intelligence. Through laser Raman acquisition system and convolutional neural network analysis, the average accuracy rate of 95.64% has been achieved, and the identification can be completed in only 5 min. These technologies have shown substantial advantages in the visible morphological detection of pathogenic microorganisms, expanding anti-infective drug discovery, enhancing our understanding of infection biology, and accelerating the development of diagnostics. In this review, we discuss the application of AI-based machine learning in image analysis, genome sequencing data analysis, and natural language processing (NLP) for pathogen identification, highlighting the significant role of artificial intelligence in pathogen diagnosis. AI can improve the accuracy and efficiency of diagnosis, promote early detection and personalized treatment, and enhance public health safety.

ARTIFICIAL INTELLIGENCE IN CLINICAL APPLICATIONS FOR INFECTIOUS DISEASES: DIAGNOSIS, TREATMENT AND IMMUNIZATION

Despite scientific and technological advances in recent years, infectious diseases continue to pose a significant threat to public health. These diseases can cause serious health problems as they have the potential to spread rapidly. In addition, they occur in the form of epidemics and affect populations. The difficulty of rapid and accurate diagnosis and increasing antimicrobial resistance create difficulties in the treatment of infectious diseases. Artificial intelligence technology has developed useful applications in many areas such as the development of diagnosis and treatment methods, anti-infective drug and vaccine discovery, and prevention of increasing anti-infective drug resistance. In particular, AI-assisted clinical decision support systems can help predict disease outbreaks, support diagnosis of diseases, optimise treatment options and monitor epidemiological trends by analysing large datasets. It can also provide more accurate and faster results in analysing diagnostic images and identifying diseases. Advances in this field need to be supported by multidisciplinary studies and a strong ethical framework. In this review, we outline approaches to the application and use of artificial intelligence in infectious diseases, highlight the progress supported by artificial intelligence, and discuss how it can be used. We outline the applications and benefits of AI in infectious diseases. In this way, more effective intervention strategies can be developed to control infectious diseases and protect public health.

Molecular docking, molecular dynamics simulation, and MM/PBSA analysis of ginger phytocompounds as a potential inhibitor of AcrB for treating multidrug-resistant Klebsiella pneumoniae infections

The emergence of Multidrug resistance (MDR) in human pathogens has defected the existing antibiotics and compelled us to understand more about the basic science behind alternate anti-infective drug discovery. Soon, proteome analysis identified AcrB efflux pump protein as a promising drug target using plant-driven phytocompounds used in traditional medicine systems with lesser side effects. Thus, the present study aims to explore the novel, less toxic, and natural inhibitors of Klebsiella pneumoniae AcrB pump protein from 69 Zingiber officinale phyto-molecules available in the SpiceRx database through computational-biology approaches. AcrB protein’s homology-modelling was carried out to get a 3D structure. The multistep-docking (HTVS, SP, and XP) were employed to eliminate less-suitable compounds in each step based on the docking score. The chosen hit-compounds underwent induced-fit docking (IFD). Based on the XP GScore, the top three compounds, epicatechin (−10.78), 6-gingerol (−9.71), and quercetin (−9.09) kcal/mol, were selected for further calculation of binding free energy (MM/GBSA). Furthermore, the short-listed compounds were assessed for their drug-like properties based on in silico ADMET properties and Pa, Pi values. In addition, the molecular dynamics simulation (MDS) studies for 250 ns elucidated the binding mechanism of epicatechin, 6-gingerol, and quercetin to AcrB. From the dynamic binding free energy calculations using MM/PBSA, 6-gingerol exhibited a strong binding affinity towards AcrB. Further, the 6-gingerol complex’s energy fluctuation was observed from the free energy landscape. In conclusion, 6-gingerol has a promising inhibiting potential against the AcrB efflux pump and thus necessitates further validation through in vitro and in vivo experiments. Communicated by Ramaswamy H. Sarma

Leveraging artificial intelligence in the fight against infectious diseases.

Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious disease remains an ominous threat to public health. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance will require concerted interdisciplinary efforts. In conjunction with systems and synthetic biology, artificial intelligence (AI) is now leading to rapid progress, expanding anti-infective drug discovery, enhancing our understanding of infection biology, and accelerating the development of diagnostics. In this Review, we discuss approaches for detecting, treating, and understanding infectious diseases, underscoring the progress supported by AI in each case. We suggest future applications of AI and how it might be harnessed to help control infectious disease outbreaks and pandemics.

Neutropenic Rat Thigh Infection Model for Evaluation of the Pharmacokinetics/Pharmacodynamics of Anti-Infectives.

The neutropenic mouse infection model is extensively used to characterize the pharmacokinetics/pharmacodynamics (PK/PD) of anti-infective agents. However, it is difficult to evaluate agents following intravenous (i.v.) infusions using this model. Furthermore, in many drug discovery programs, lead identification and optimization is performed in rats, and pharmacology is performed in mice. Alternative models of infection are needed for robust predictions of PK/PD in humans. The rat is an alternative model of infection which can overcome the shortcomings of the mouse model. However, the rat neutropenic thigh infection (NTI) model has not been adequately characterized for evaluation of the PK/PD of anti-infectives. The aim of this study was to characterize the PK/PD of ciprofloxacin against bacterial pathogens in a rat NTI model. We studied the PK/PD relationships of ciprofloxacin against wild-type Escherichia coli, Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae in neutropenic Wistar rats following administration of 10, 30, and 100 mg/kg as single intravenous boluses and 30- and 60-min infusions. The PK/PD of ciprofloxacin against all four pathogens was AUC/MIC dependent and independent of the duration of administration at 10, 30, and 100 mg/kg. At human-equivalent rat doses, the PK/PD targets of ciprofloxacin achieved in rats for microbiological cure were similar to those reported in human patients. The neutropenic rat thigh infection model can be used to evaluate anti-infective agents intended to be administered as infusions in the clinic, and it complements the mouse model, increasing the robustness of PK/PD predictions in humans. IMPORTANCE Many antibiotics are administered as intravenous infusions in the clinic, especially in intensive care units. Anti-infective drug discovery companies develop clinical candidates that are intended to be administered as i.v. infusions in the clinic. However, there are no well-characterized models with which they can evaluate the PK/PD of the candidates following i.v. infusions. The neutropenic rat thigh infection model reported in this study helps in evaluating anti-infective agents that are intended to be administered as i.v. infusions in the clinic. The rat model is useful for simulating the clinical conditions for i.v. infusions for treatment of infections, such as acute bacterial skin and skin structure, lung, and urinary tract infections. This model is predictive of efficacy in humans and can serve as an additional confirmatory model, along with the mouse model, for determining the proof of concept and for making robust predictions of efficacy in humans.

The AcrAB efflux pump confers self-resistance to stilbenes in Photorhabdus laumondii

The Resistance-nodulation-division (RND)-type AcrAB-TolC efflux pump contributes to multidrug resistance in Gram-negative bacteria. Recently, the bacterium Photorhabdus laumondii TT01 has emerged as a goldmine for novel anti-infective drug discovery. Outside plants, Photorhabdus is the only Gram-negative known to produce stilbene-derivatives including 3,5-dihydroxy-4-ethyl-trans-stilbene and 3,5-dihydroxy-4-isopropyl-trans-stilbene (IPS). IPS is a bioactive polyketide which received considerable attention, mainly because of its antimicrobial properties, and is currently in late-stage clinical development as a topical treatment for psoriasis and dermatitis. To date, little is known about how Photorhabdus survives in the presence of stilbenes. We combined genetic and biochemical approaches to assess whether AcrAB efflux pump exports stilbenes in P. laumondii. We demonstrated that the wild-type (WT) exerts an antagonistic activity against its derivative ΔacrA mutant, and that is able to outcompete it in a dual-strain co-culture assay. The ΔacrA mutant also showed high sensitivity to 3,5-dihydroxy-4-ethyl-trans-stilbene and IPS as well as decreased IPS concentrations in its supernatant comparing to the WT. We report here a mechanism of self-resistance against stilbene derivatives of P. laumondii TT01, which enables these bacteria to survive under high concentrations of stilbenes by extruding them out via the AcrAB efflux pump.

Artificial intelligence for antiviral drug discovery in low resourced settings: A perspective

Current antiviral drug discovery efforts face many challenges, including development of new drugs during an outbreak and coping with drug resistance due to rapidly accumulating viral mutations. Emerging artificial intelligence and machine learning (AI/ML) methods can accelerate anti-infective drug discovery and have the potential to reduce overall development costs in Low and Middle-Income Countries (LMIC), which in turn may help to develop new and/or accessible therapies against communicable diseases within these countries. While the marketplace currently offers a plethora of data-driven AI/ML tools, most to date have been developed within the context of non-communicable diseases like cancer, and several barriers have limited the translation of existing tools to the discovery of drugs against infectious diseases. Here, we provide a perspective on the benefits, limitations, and pitfalls of AI/ML tools in the discovery of novel therapeutics with a focus on antivirals. We also discuss available and emerging data sharing models including intellectual property-preserving AI/ML. In addition, we review available data sources and platforms and provide examples for low-cost and accessible screening methods and other virus-based bioassays suitable for implementation of AI/ML-based programs in LMICs. Finally, we introduce an emerging AI/ML-based Center in Cameroon (Central Africa) which is currently developing methods and tools to promote local, independent drug discovery and represents a model that could be replicated among LMIC globally.

Multitargeted anti-infective drugs: resilience to resistance in the antimicrobial resistanceera.

The standard drug discovery paradigm of single molecule – single biological target – single biological effect is perhaps particularly unsuitable for anti-infective drug discovery. This is due to the rapid evolution of resistance likely to be observed with single target drugs. Multitargeted anti-infective drugs are likely to be superior due to their lower susceptibility to target-related resistance mechanisms. Strathclyde minor groove binders are a class of compounds which have been developed by adopting the multitargeted anti-infective drugs paradigm, and their effectiveness against a wide range of pathogenic organisms is discussed. The renaming of this class to Strathclyde nucleic acid binders is also presented due to their likely targets including both DNA and RNA.

In Vitro Profiling of Antitubercular Compounds by Rapid, Efficient, and Nondestructive Assays Using Autoluminescent Mycobacterium tuberculosis.

ABSTRACTAnti-infective drug discovery is greatly facilitated by the availability of in vitro assays that are more proficient at predicting the preclinical success of screening hits. Tuberculosis (TB) drug discovery is hindered by the relatively slow growth rate of Mycobacterium tuberculosis and the use of whole-cell-based in vitro assays that are inherently time-consuming, and for these reasons, rapid, noninvasive bioluminescence-based assays have been widely used in anti-TB drug discovery and development. In this study, in vitro assays that employ autoluminescent M. tuberculosis were optimized to determine MIC, minimum bactericidal concentration (MBC), time-kill curves, activity against macrophage internalized M. tuberculosis (90% effective concentration [EC90]), and postantibiotic effect (PAE) to provide rapid and dynamic biological information. Standardization of the luminescence-based MIC, MBC, time-kill, EC90, and PAE assays was accomplished by comparing results of established TB drugs and two ClpC1-targeting TB leads, ecumicin and rufomycin, to those obtained from conventional assays and/or to previous studies. Cumulatively, the use of the various streamlined luminescence-based in vitro assays has reduced the time for comprehensive in vitro profiling (MIC, MBC, time-kill, EC90, and PAE) by 2 months. The luminescence-based in vitro MBC and EC90 assays yield time and concentration-dependent kill information that can be used for pharmacokinetic-pharmacodynamic (PK-PD) modeling. The MBC and EC90 time-kill graphs revealed a significantly more rapid bactericidal activity for ecumicin than rufomycin. The PAEs of both ecumicin and rufomycin were comparable to that of the first-line TB drug rifampin. The optimization of several nondestructive, luminescence-based TB assays facilitates the in vitro profiling of TB drug leads in an efficient manner.

Screening of compound library identifies novel inhibitors against the MurA enzyme of Escherichia coli.

Bacterial cell has always been an attractive target for anti-infective drug discovery. MurA (UDP-N-acetylglucosamine enolpyruvyl transferase) enzyme of Escherichia coli (E.coli) is crucial for peptidoglycan biosynthetic pathway, as it is involved in the early stages of bacterial cell wall biosynthesis. In the present study we aim to identify novel chemical structures targeting the MurA enzyme. For screening purpose, we used in silico approach (pharmacophore based strategy) for 52,026 library compounds (Chembridge, Chemdiv and in house synthetics) which resulted in identification of 50 compounds. These compounds were screened in vitro against MurA enzyme and release of inorganic phosphate (Pi) was estimated. Two compounds (IN00152 and IN00156) were found to inhibit MurA enzyme > 70% in primary screening and IC50 of 14.03 to 32.30 μM respectively. These two hits were further evaluated for their mode of inhibition studies and whole-cell activity where we observed 2-4 folds increase in activity in presence of Permeabilizer EDTA (Ethylenediaminetetraacetic acid). Combination studies were also performed with known antibiotics in presence of EDTA. Hits are reported for the first time against this target and our report also support the use of OM permeabilizer in combination with antibacterial compounds to address the permeability and efficacy issue. These lead hits can be further optimized for drug discovery. KEY POINTS: • Emerging Gram negative resistant strains is a matter of concern. • Need for new screening strategies to cope with drying up antibiotics pipeline. • Outer membrane permeabilizers could be useful to improve potency of molecules to reach its target.

β-Lactamase Inhibitors To Restore the Efficacy of Antibiotics against Superbugs.

Infections caused by resistant bacteria are nowadays too common, and some pathogens have even become resistant to multiple types of antibiotics, in which case few or even no treatments are available. In recent years, the most successful strategy in anti-infective drug discovery for the treatment of such problematic infections is the combination therapy "antibiotic + inhibitor of resistance". These inhibitors allow the repurposing of antibiotics that have already proven to be safe and effective for clinical use. Three main types of compounds have been developed to block the principal bacterial resistance mechanisms: (i) β-lactamase inhibitors; (ii) outer membrane permeabilizers; (iii) efflux pump inhibitors. This Perspective is focused on β-lactamase inhibitors that disable the most prevalent cause of antibiotic resistance in Gram-negative bacteria, i.e., the deactivation of the most widely used antibiotics, β-lactams (penicillins, cephalosporines, carbapenems, and monobactams), by the production of β-lactamases. An overview of the most recently identified β-lactamase inhibitors and of combination therapy is provided. The article also covers the mechanism of action of the different types of β-lactamase enzymes as a basis for inhibitor design and target inactivation.

Pathway-Centric Structure-Based Multi-Target Compound Screening for Anti-Virulence Drug Repurposing.

The emergence of superbugs that are resistant to last-resort antibiotics poses a serious threat to human health, and we are in a “race against time to develop new antibiotics.” New approaches are urgently needed to control drug-resistant pathogens, and to reduce the emergence of new drug-resistant microbes. Targeting bacterial virulence has emerged as an important strategy for combating drug-resistant pathogens. It has been shown that pyocyanin, which is produced by the phenazine biosynthesis pathway, plays a key role in the virulence of Pseudomonas aeruginosa infection, making it an attractive target for anti-infective drug discovery. In order to discover efficient therapeutics that inhibit the phenazine biosynthesis in a timely fashion, we screen 2004 clinical and pre-clinical drugs to target multiple enzymes in the phenazine biosynthesis pathway, using a novel procedure of protein–ligand docking. Our detailed analysis suggests that kinase inhibitors, notably Lifirafenib, are promising lead compounds for inhibiting aroQ, phzG, and phzS enzymes that are involved in the phenazine biosynthesis, and merit further experimental validations. In principle, inhibiting multiple targets in a pathway will be more effective and have less chance of the emergence of drug resistance than targeting a single protein. Our multi-target structure-based drug design strategy can be applied to other pathways, as well as provide a systematic approach to polypharmacological drug repositioning.

Cell wall peptidoglycan in Mycobacterium tuberculosis: An Achilles' heel for the TB-causing pathogen.

ABSTRACTTuberculosis (TB), caused by the intracellular pathogen Mycobacterium tuberculosis, remains one of the leading causes of mortality across the world. There is an urgent requirement to build a robust arsenal of effective antimicrobials, targeting novel molecular mechanisms to overcome the challenges posed by the increase of antibiotic resistance in TB. Mycobacterium tuberculosis has a unique cell envelope structure and composition, containing a peptidoglycan layer that is essential for maintaining cellular integrity and for virulence. The enzymes involved in the biosynthesis, degradation, remodelling and recycling of peptidoglycan have resurfaced as attractive targets for anti-infective drug discovery. Here, we review the importance of peptidoglycan, including the structure, function and regulation of key enzymes involved in its metabolism. We also discuss known inhibitors of ATP-dependent Mur ligases, and discuss the potential for the development of pan-enzyme inhibitors targeting multiple Mur ligases.

In Silico and in Vitro-Guided Identification of Inhibitors of Alkylquinolone-Dependent Quorum Sensing in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a major opportunistic pathogen in cystic fibrosis, wound and nosocomial infections, posing a serious burden to public health, due to its antibiotic resistance. The P. aeruginosa Pseudomonas Quinolone System (pqs) quorum sensing system, driven by the activation of the transcriptional regulator, PqsR (MvfR) by alkylquinolone (AQ) signal molecules, is a key player in the regulation of virulence and a potential target for the development of novel antibacterial agents. In this study, we performed in silico docking analysis, coupled with screening using a P. aeruginosa mCTX::PpqsA-lux chromosomal promoter fusion, to identify a series of new PqsR antagonists. The hit compounds inhibited pyocyanin and alkylquinolone signal molecule production in P. aeruginosa PAO1-L and PA14 strains. The inhibitor Ia, which showed the highest activity in PA14, reduced biofilm formation in PAO1-L and PA14, increasing their sensitivity to tobramycin. Furthermore, the hepatic and plasma stabilities for these compounds were determined in both rat and human in vitro microsomal assays, to gain a further understanding of their therapeutic potential. This work has uncovered a new class of P. aeruginosa PqsR antagonists with potential for hit to lead optimisation in the search for quorum sensing inhibitors for future anti-infective drug discovery programs.

Editorial: Anti-Infective Drug Discovery Based on Diversified Plant Natural Compounds

Editorial: Anti-Infective Drug Discovery Based on Diversified Plant Natural Compounds

Isolation of metabolites from epigenetically modified mangrove fungi for anti-infective drug discovery

Isolation of metabolites from epigenetically modified mangrove fungi for anti-infective drug discovery

The bacterial cell envelope as delimiter of anti-infective bioavailability – An in vitro permeation model of the Gram-negative bacterial inner membrane

Gram-negative bacteria possess a unique and complex cell envelope, composed of an inner and outer membrane separated by an intermediate cell wall-containing periplasm. This tripartite structure acts intrinsically as a significant biological barrier, often limiting the permeation of anti-infectives, and so preventing such drugs from reaching their target. Furthermore, identification of the specific permeation-limiting envelope component proves difficult in the case of many anti-infectives, due to the challenges associated with isolation of individual cell envelope structures in bacterial culture. The development of an in vitro permeation model of the Gram-negative inner membrane, prepared by repeated coating of physiologically-relevant phospholipids on Transwell® filter inserts, is therefore reported, as a first step in the development of an overall cell envelope model. Characterization and permeability investigations of model compounds as well as anti-infectives confirmed the suitability of the model for quantitative and kinetically-resolved permeability assessment, and additionally confirmed the importance of employing bacteria-specific base materials for more accurate mimicking of the inner membrane lipid composition - both advantages compared to the majority of existing in vitro approaches. Additional incorporation of further elements of the Gram-negative bacterial cell envelope could ultimately facilitate model application as a screening tool in anti-infective drug discovery or formulation development.

Repositioning of DHFR Inhibitors

Development of new drugs is a time-consuming, hugely expensive and an uncertain endeavor. The pharmaceutical industry is looking for cost-effective alternatives with reduced risks of drug failure. Validated target machinery along with established inhibitors indicates usefulness in drug design, discovery and further development. Folate metabolism, found in both prokaryotes and eukaryotes, represents an essential druggable target for chemotherapy. Numerous enzymes in the cell replication cycle use folate either as a cofactor or as a substrate. DHFR, an enzyme of the folate biosynthesis pathway is an established chemotherapeutic target, initially explored for anti-cancer drug discovery. Diaminopteridines e.g. methotrexate and aminopterin, primarily used as anti-cancer agents, are folic acid analogues, first reported in late 1940's, used to produce temporary remission of acute leukaemia in children. However, due to the toxicity of these drugs, they could not be used for other therapeutic implications such as in the treatment of infectious diseases. Development of newer diaminopteridine derivatives has helped in repositioning their therapeutic usefulness. These analogues have now been proven as anti-parasitic, immuno-suppressants, anti-bacterial agents, to enlist a few therapeutic applications. Likewise, diaminopyrimidine, diaminoquinazoline and diaminodihydrotriazines are being explored for structural modifications by which they can be repurposed from their originally developed medicinal applicability and exploited for various other infectious disease conditions. In this review, we encompass the study of DHFR inhibitors potentially to be repurposed for different infectious disease case scenario and also highlight the novel anti-infective drug discovery benefits therein.

In Vitro Anti-Infective Screening Of Selected West African Medicinal Plants

Individual or whole parts of Persea Americana, Caesalpinia bonduc and Caesalpinia pulcherrima have been traditionally used for the treatment of various infectious diseases in West Africa. Methanolic extracts and fractions of these plants were screened for in vitro activity against L. donovani (promastigotes, axenic amastigotes and intracellular amastigotes in THP1 cells), T. brucei, Plasmodium falciparum (chloroquine sensitive and chloroquine resistant strains) and selected pathogenic microbes. With IC50 values less than 10 µg/mL, the extracts exhibited selective antileishmanial activity against, L. donovani Amastigote, and less potent effects against L. donovani Promastigote, L. donovani Amastigote + THP, and T. brucei blood stage trypamastigotes. Fractions of P. Americana and C. pulcherrima showed strong activities against both chloroquine-sensitive and chloroquine-resistant strains of P. falciparum. With IC50 values ranging from 3.6 to 12 µg/mL, all fractions of C. pulcherrima exhibited significant antimicrobial activity especially against C. glabrata, C. krusei, S. aureus and P. aeruginosa (IC50 < 8 – 81 µg/mL). Crude extracts of P. Americana showed activity against C. glabrata, S. aureus and P. aeruginosa (IC50 22 – 86 µg/mL). These findings are important scientific support for traditional uses of these plants in infectious diseases and provide a strong basis for further studies towards anti-infective drug discovery from the plants. Acknowledgements: This work was in part supported by USAID/HED grant 153 – 6200BF A-15 – 01 to Prof A. Falodun, University of Benin.

Nanomolar Inhibitors of Trypanosoma brucei RNA Triphosphatase.

ABSTRACTEukaryal taxa differ with respect to the structure and mechanism of the RNA triphosphatase (RTPase) component of the mRNA capping apparatus. Protozoa, fungi, and certain DNA viruses have a metal-dependent RTPase that belongs to the triphosphate tunnel metalloenzyme (TTM) superfamily. Because the structures, active sites, and chemical mechanisms of the TTM-type RTPases differ from those of mammalian RTPases, the TTM RTPases are potential targets for antiprotozoal, antifungal, and antiviral drug discovery. Here, we employed RNA interference (RNAi) knockdown methods to show that Trypanosoma brucei RTPase Cet1 (TbCet1) is necessary for proliferation of procyclic cells in culture. We then conducted a high-throughput biochemical screen for small-molecule inhibitors of the phosphohydrolase activity of TbCet1. We identified several classes of chemicals—including chlorogenic acids, phenolic glycopyranosides, flavonoids, and other phenolics—that inhibit TbCet1 with nanomolar to low-micromolar 50% inhibitory concentrations (IC50s). We confirmed the activity of these compounds, and tested various analogs thereof, by direct manual assays of TbCet1 phosphohydrolase activity. The most potent nanomolar inhibitors included tetracaffeoylquinic acid, 5-galloylgalloylquinic acid, pentagalloylglucose, rosmarinic acid, and miquelianin. TbCet1 inhibitors were less active (or inactive) against the orthologous TTM-type RTPases of mimivirus, baculovirus, and budding yeast (Saccharomyces cerevisiae). Our results affirm that a TTM RTPase is subject to potent inhibition by small molecules, with the caveat that parallel screens against TTM RTPases from multiple different pathogens may be required to fully probe the chemical space of TTM inhibition.