Binding Mode and Potency of <i>N</i>‑Indolyloxopyridinyl-4-aminopropanyl-Based Inhibitors Targeting <i>Trypanosoma cruzi</i> CYP51

Chagas disease is a chronic infection in humans caused by <i>Trypanosoma cruzi</i> and manifested in progressive cardiomyopathy and/or gastrointestinal dysfunction. Limited therapeutic options to prevent and treat Chagas disease put 8 million people infected with <i>T. cruzi</i> worldwide at risk. CYP51, involved in the biosynthesis of the membrane sterol component in eukaryotes, is a promising drug target in <i>T. cruzi</i>. We report the structure–activity relationships (SAR) of an <i>N</i>-arylpiperazine series of <i>N</i>-indolyloxopyridinyl-4-aminopropanyl-based inhibitors designed to probe the impact of substituents in the terminal N-phenyl ring on binding mode, selectivity and potency. Depending on the substituents at C-4, two distinct ring binding modes, buried and solvent-exposed, have been observed by X-ray structure analysis (resolution of 1.95–2.48 Å). The 5-chloro-substituted analogs <b>9</b> and <b>10</b> with no substituent at C-4 demonstrated improved selectivity and potency, suppressing ≥99.8% parasitemia in mice when administered orally at 25 mg/kg, b.i.d., for 4 days

Targeting Ergosterol Biosynthesis in <i>Leishmania donovani</i>: Essentiality of Sterol 14alpha-demethylase

<div><p><i>Leishmania</i> protozoan parasites (Trypanosomatidae family) are the causative agents of cutaneous, mucocutaneous and visceral leishmaniasis worldwide. While these diseases are associated with significant morbidity and mortality, there are few adequate treatments available. Sterol 14alpha-demethylase (CYP51) in the parasite sterol biosynthesis pathway has been the focus of considerable interest as a novel drug target in <i>Leishmania</i>. However, its essentiality in <i>Leishmania donovani</i> has yet to be determined. Here, we use a dual biological and pharmacological approach to demonstrate that CYP51 is indispensable in <i>L</i>. <i>donovani</i>. We show via a facilitated knockout approach that chromosomal <i>CYP51</i> genes can only be knocked out in the presence of episomal complementation and that this episome cannot be lost from the parasite even under negative selection. In addition, we treated wild-type <i>L</i>. <i>donovani</i> and CYP51-deficient strains with 4-aminopyridyl-based inhibitors designed specifically for <i>Trypanosoma cruzi</i> CYP51. While potency was lower than in <i>T</i>. <i>cruzi</i>, these inhibitors had increased efficacy in parasites lacking a <i>CYP51</i> allele compared to complemented parasites, indicating inhibition of parasite growth via a CYP51-specific mechanism and confirming essentiality of CYP51 in <i>L</i>. <i>donovani</i>. Overall, these results provide support for further development of CYP51 inhibitors for the treatment of visceral leishmaniasis.</p></div

Machine Learning Models and Pathway Genome Data Base for <i>Trypanosoma cruzi</i> Drug Discovery

<div><p>Background</p><p>Chagas disease is a neglected tropical disease (NTD) caused by the eukaryotic parasite <i>Trypanosoma cruzi</i>. The current clinical and preclinical pipeline for <i>T</i>. <i>cruzi</i> is extremely sparse and lacks drug target diversity.</p><p>Methodology/Principal Findings</p><p>In the present study we developed a computational approach that utilized data from several public whole-cell, phenotypic high throughput screens that have been completed for <i>T</i>. <i>cruzi</i> by the Broad Institute, including a single screen of over 300,000 molecules in the search for chemical probes as part of the NIH Molecular Libraries program. We have also compiled and curated relevant biological and chemical compound screening data including (i) compounds and biological activity data from the literature, (ii) high throughput screening datasets, and (iii) predicted metabolites of <i>T</i>. <i>cruzi</i> metabolic pathways. This information was used to help us identify compounds and their potential targets. We have constructed a Pathway Genome Data Base for <i>T</i>. <i>cruzi</i>. In addition, we have developed Bayesian machine learning models that were used to virtually screen libraries of compounds. Ninety-seven compounds were selected for <i>in vitro</i> testing, and 11 of these were found to have EC₅₀ < 10μM. We progressed five compounds to an <i>in vivo</i> mouse efficacy model of Chagas disease and validated that the machine learning model could identify <i>in vitro</i> active compounds not in the training set, as well as known positive controls. The antimalarial pyronaridine possessed 85.2% efficacy in the acute Chagas mouse model. We have also proposed potential targets (for future verification) for this compound based on structural similarity to known compounds with targets in <i>T</i>. <i>cruzi</i>.</p><p>Conclusions/ Significance</p><p>We have demonstrated how combining chemoinformatics and bioinformatics for <i>T</i>. <i>cruzi</i> drug discovery can bring interesting <i>in vivo</i> active molecules to light that may have been overlooked. The approach we have taken is broadly applicable to other NTDs.</p></div

4‑Aminopyridyl-Based CYP51 Inhibitors as Anti-Trypanosoma cruzi Drug Leads with Improved Pharmacokinetic Profile and in Vivo Potency

CYP51 is a P450 enzyme involved in the biosynthesis of the sterol components of eukaryotic cell membranes. CYP51 inhibitors have been developed to treat infections caused by fungi, and more recently the protozoan parasite Trypanosoma cruzi, the causative agent of Chagas disease. To specifically optimize drug candidates for T. cruzi CYP51 (<i>Tc</i>CYP51), we explored the structure–activity relationship (SAR) of a <i>N</i>-indolyl-oxopyridinyl-4-aminopropanyl-based scaffold originally identified in a target-based screen. This scaffold evolved via medicinal chemistry to yield orally bioavailable leads with potent anti-T. cruzi activity in vivo. Using an animal model of infection with a transgenic T. cruzi Y luc strain expressing firefly luciferase, we prioritized the biaryl and <i>N</i>-arylpiperazine analogues by oral bioavailability and potency. The drug–target complexes for both scaffold variants were characterized by X-ray structure analysis. Optimization of both binding mode and pharmacokinetic properties of these compounds led to potent inhibitors against experimental T. cruzi infection

Leave-out cross validation data for <i>T</i>.<i>cruzi</i> Bayesian models.

<p>Leave-out cross validation data for <i>T</i>.<i>cruzi</i> Bayesian models.</p

Modulation of CYP51 levels in <i>L</i>. <i>donovani</i>.

<p><b>A</b>, Replacement of a <i>CYP51</i> allele by homologous recombination. Correct targeting of the knockout cassettes was verified by PCR using one primer within the knockout cassette and one upstream of <i>CYP51</i> (primers 7 and 8 (hygromycin), top or 7 and 9 (puromycin), bottom). <b>B</b>, qPCR quantification of chromosomal <i>CYP51</i> levels, normalized to SAT or to CBS and to wild-type levels. <b>C</b>, CYP51 protein levels in half knockout and complemented strains. CYP51 and GAPDH were detected by Western blot (top) and quantified by densitometry (bottom) <b>D</b>, <i>In vitro</i> infectivity of half knockout and complemented strains. THP1 macrophages were infected at a 10:1 parasite to macrophage ratio. Cells were fixed and stained with DAPI 24, 48 and 72 h post-infection, and macrophage infection levels were determined by automated high-throughput imaging and parasite detection. <b>E</b>, <i>In vivo</i> infectivity of half knockout and complemented strains. BALB/c mice were infected intravenously. Liver parasite burden (Leishman-Donovan Units, LDU) was determined 28 days post-infection by counting stained liver impressions. <b>F</b>, Sterol profiling by GC-MS.</p

Susceptibility of half knockout strains to CYP51 inhibitors (EC50, μM): compounds with no significant differences between HKO + C and HKO + CYP strains.

<p>Values ± standard error are shown. ^a p-values are for comparison between HKO+C and HKO+CYP.</p

<i>In vivo</i> efficacy of test compounds (50mg/kg b.i.d.) in a 4-day mouse model of infection by transgenic <i>T</i>.<i>cruzi</i> Brazil luc strain35 expressing firefly luciferase.

<p><i>In vivo</i> efficacy of test compounds (50mg/kg b.i.d.) in a 4-day mouse model of infection by transgenic <i>T</i>.<i>cruzi</i> Brazil luc strain35 expressing firefly luciferase.</p

A typical metabolic cellular overview of TCruCyc provided by the Pathway Tools web server.

<p>This view of the TCruCyc PGDB shows the (almost entirely) inferred set of metabolic pathways from gene sequence data. Canonical pathways such as “Amino Acids Biosynthesis”, “Amino Acids Degradation”, “Nucleosides and Nucleotides Biosynthesis”, “Fatty Acids and Lipids Biosynthesis” and “Respiration” are partially inferred as well as a large set of single reaction steps (right side) that Pathway Tools could integrate into larger pathways. This is an expected level of derivable connectivity that would be available from annotated genome and proteome sequence data. We expect that a significant number of unassigned protein functions can be assigned by extending Pathway Tools with (high threshold) automated sequence similarity analysis that is currently done via manual curation.</p

<i>In vitro</i> and <i>in vivo</i> data for compounds selected in this study.

<p>* Used hydroxymethylnitrofurazone for <i>in vivo</i> study (nitrofural pro-drug)</p><p><i>In vitro</i> and <i>in vivo</i> data for compounds selected in this study.</p