Drug Target Discovery Methods In Targeting Neurotropic Parasitic

Dec 11, 2017 - development of drug resistance by the neurotropic parasites like Naegleria fowleri, Balamuthia mandrillaris, and Acanthamoeba spp has m...
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Drug Target Discovery Methods In Targeting Neurotropic Parasitic Amoebae Abdul Mannan Baig,*,† Nuzair Waliani,‡ and Saiqa Karim‡ †

The Aga Khan University, Stadium Road, Karachi 74800, Pakistan Dow University of Health Sciences, Karachi 74200, Pakistan

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ABSTRACT: Neurotropic parasitic amoebal infections have imposed an enormous challenge to chemotherapy in patients who fall victims to the infections caused by them. Conventional antibiotics that are given to treat these infections have a low patient compliance because of the serious adverse effects that are associated with their use. Additionally, the growing incidence of the development of drug resistance by the neurotropic parasites like Naegleria fowleri, Balamuthia mandrillaris, and Acanthamoeba spp has made the drug therapy more challenging. Recent studies have reported some cellular targets in the neurotropic parasitic Acanthamoeba that are used as receptors by human neurotransmitters like acetylcholine. This Viewpoint attempts to highlight the novel methodologies that use drug assays and structural modeling to uncover cellular targets of diverse groups of drugs and the safety issues of the drugs proposed for their use in brain infections caused by the neurotropic parasitic amoebae. KEYWORDS: Neurochemical receptors, receptor discovery methods, drug safety, brain-eating amoeba, Acanthamoeba spp, structural homology, 3D modeling

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INTRODUCTION Targeting of vital receptors and protein in the free-living neurotropic amoeba (FLNA) has been done in the past to treat the diseases caused by them in humans. Identification of novel cellular targets is essentially needed as drug resistance has been seen to be emerging in the FLNA that include the Naegleria fowleri, Balamuthia mandrillaris, and Acanthamoeba spp. Selection of drug targets has been facilitated by using bioinformatic computational tools, expermientations, and methods like single cell analysis. Recently, identification of a diverse group of receptors and ion channels followed by in vitro experimentations to antagonize them has proven to be amoebicidal for FLNA. As FLNA are unicellular eukaryotes, proteins and ion channels expressed by human cells have been explored for their presence in the FLNA. Such comparative homology has faced difficulties when amino-acid sequence homology of the compared proteins turns out to be dissimilar between these two species. Using structural homology and docking predictions instead of amino acid sequence matching has proved to be more accurate in the determination of the drug targets in FLNA that are similar to proteins in humans. Here we discuss the methodologies used in the recent past and provide details of the structural bioinformatics and experimental approach that has helped in targeting the proteins identified by this methodology.

antagonist) effect or search for the target in the databases of FLNA. A. Target Identification Based on Drug Effects. This approach is based on selection of drugs used in humans in diverse noninfectious clinical conditions, that affect a single or multiple evolutionary conserved protein in the FLNA. This approach has been seen to be adopted in several studies done in the past.1 Recently based upon the above rationale a diverse group of drugs have shown to produce amoebicidal and cysticidal3 effects. Drugs targeting FLNA could behave as agonists or antagonist at the target proteins3,4 and/or act on a unique amoebal enzyme.2 In the former group, as the drugs selected have established and well-known effects on human cellular receptors and proteins, their effects in FLNA could therefore be inferred.3 Calmodulin, calcium channels, Na−K ATPase, and K- and Na-channels are few examples of the proteins that have remained conserved from unicellular eukaryotes (FLNA) to humans. It is therefore possible to select drugs already in use for human diseases that target these proteins and predict their effects. Studies done by using the above rationale have shown to be effective in in vitro experiments.3 At other times, there are examples of studies where drugs have produced effects on FLNA on targets that are unique to them.2 The effectiveness of drug target discovery by drug assays can be gauged by the fact that the effects of the above-described drugs have led to the discovery of muscarinic receptor subtype in FLNA, like Naegleria fowleri and Acanthamoeba.4 There are examples where the drugs have shown an amoebistatic and amoebicidal effect, but their target cellular proteins cannot be ascribed with certainty in the FLNA.

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IDENTIFICATION OF PROTEIN TARGETS IN FLNA There have been reports of two methodologies adopted to provide evidence of protein targets in FLNA: (A) Drug effect based target identification1 and (B) drug target discovery based on the use of bioinformatics tools.2 These two methods have the advantage that they could follow each other to establish the evidence of the expression of target proteins. In both of these approaches, a druggable target has to be inferred at first, followed by either observing a drug (agonist/ © XXXX American Chemical Society

Received: December 9, 2017 Accepted: December 11, 2017

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DOI: 10.1021/acschemneuro.7b00492 ACS Chem. Neurosci. XXXX, XXX, XXX−XXX

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ACS Chemical Neuroscience

Figure 1. Recently discovered receptors and ion channels in Acanthamoeba castellanii by the use of bioinformatic computational tools like 3D structural homology and modeling. A mAChR1 like receptor (1) that docks acetylcholine is shown (refs 4−6, see text). The calcium (3) and potassium channels (4) have been reported in recent studies in Acanthamoeba castellanii with capability to synthesize acetylcholine. (ref 6, see text).

Apomorphine can be cited as one example of such drugs.3 Speculating drug targets on FLNA by performing growth and cytotoxicity assays is comparatively easy when the drug has a single established cellular target in human. Pirenzepine on human muscarinic M1-receptors (mAChR1) is one example of such drug.4 For drugs like chlorpromazine that are known agonist and antagonists at multiple receptors and proteins, an inference of their targets can be problematic if the targets have not been established in FLNA.1 Another obstacle in inferring the drug effects in FLNA is the consideration of parameters like pH alterations caused by the drugs used. Such a possibility can be ruled out by measuring the pH before and after exposure to the drug in experimental assays. A1. Validation of Target Proteins in FLNA. Though agonistic and antagonistic effects of drugs that are wellknown to produce their action at human cellular targets hint toward the presence of a homologous protein in FLNA, these drug targets could be validated by additional experiments like single cell microarray, gene knockout, and fluorophore tagging of the drug and receptors in FLNA. An additional method to evidence their expression is by the use of the antireceptor-fluorescent antibodies. Bioinformatic tools using the data-banks (detailed below) that have complete genome deposited in them, can be useful tools to check for the protein/receptor expression. Of the FLNA, the genome of Acanthamoeba deposited at amoebaDB.org and NCBI has served as a very helpful repository for receptor discovery4 and amoebal enzymes in recent years.2 A2. Significance of Drug Assays Based Drug Target Discovery in FLNA. Observation of the effects of a receptor binding drug in FLNA opens an additional portal of research into exploration of the source of the ligand in the FLNA. This approach has recently led to the discovery of acetylcholine in Acanthamoeba, that was reported to express human mAChR1

like AMB receptors.4 In several other instances, protein binding molecules like glucose and choline have led to the discovery of GLUT and choline transporters of CLT-family proteins (data not shown). B. Bioinformatics Computation Tools and Docking Prediction in Drug Target Validation. The genome and proteins expressed by the FLNA that have been discovered and deposited in various data banks are enormous resources that are of help in drug target discovery in the neurotropic unicellular microbes. Excellent scientific contributions5 have resulted in deposition of extended genomic and proteomic data of the FLNA in amoebaDB.org, NCBI and UniprotKB databases. Additionally, template based model building databases and 3D protein structural homology predictions have been made possible with Web sites like SWISS MODEL and Phyre2 databases. Figure 1 shows the receptors and ion channels recently reported by the use of the above-mentioned databases and protein modeling softwares.

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TRANSLATIONAL SIGNIFICANCE OF DRUG-TARGET DISCOVERY We proposed the rationale of targeting vital cellular receptors and ion channels that are expressed by the FLNA like N. fowleri, Balamuthia mandrillaris, and Acanthamoeba spp. with the use of drug assays and bioinformatic tools. The combination of these two methodologies has enabled the discovery of novel receptors, Ca2+/K+/Na+ ion channels and neurochemicals like acetylcholine in FLNA.6 As the drug target discovered in our studies are shared between FLNA and humans, their use in humans is expected to have adverse effects. In other instances, the targets are unique to the FLNA,2 but even then the side effect can occur. In vivo animal trials and studies to determine the margin of safety of the drugs like procyclidine, loperamide, amlodipine, and prochlorpromazine B

DOI: 10.1021/acschemneuro.7b00492 ACS Chem. Neurosci. XXXX, XXX, XXX−XXX

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ACS Chemical Neuroscience remain mandatory before they are approved for their use in human diseases caused by FLNA. The only advantage expected to be seen with the use of the above mentioned drugs in FLNA related human diseases, is that being approved by the United States Food and Drug Administration for their use in noninfectious human diseases,3 their pharmacokinetics and side effects would be predictable. For example, the drug chlorpromazine that has been proven to be amoebicidal to the trophozoites of N. fowleri1 has a margin of safety of ∼200, which makes it ideally safe for animal and human trials. Anticholinergic drugs with amoebicidal effects are expected to produce CNS side effects, but agents like procyclidine is already prescribed for Parkinsonism and its adverse effects and margin of safety is known and predictable.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Telephone: +923332644246. ORCID

Abdul Mannan Baig: 0000-0003-0626-216X Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This project was funded by AKU seed money grant awarded to Dr. Baig AM for the year 2016-17. REFERENCES

(1) Schuster, F. L., and Mandel, N. (1984) Phenothiazine compounds inhibit in vitro growth f pathogenic free-living amoebae. Antimicrob. Agents Chemother. 25 (1), 109−12. (2) Thomson, S., Rice, C. A., Zhang, T., Edrada-Ebel, R., Henriquez, F. L., and Roberts, C. W. (2017) Characterisation of sterol biosynthesis and validation of 14α-demethylase as a drug target in Acanthamoeba. Sci. Rep. 7 (1), 8247. (3) Baig, A. M., Iqbal, J., and Khan, N. A. (2013) In vitro efficacy of clinically available drugs against the growth and viability of Acanthamoeba castellanii keratitis isolate T4. Antimicrob. Agents Chemother. 57, 3561. (4) Baig, A. M., and Ahmad, H. R. (2017) Evidence of an M (1)muscarinic GPCR homolog in unicellular eukaryotes: featuring Acanthamoeba spp. Bioinformatics 3D-modelling and experimentations. J. Recept. Signal Transduction Res. 37 (3), 267−275. (5) Clarke, M., Lohan, A. J., Liu, B., Lagkouvardos, I., Roy, S., and Zafar, N. (2013) Genome of Acanthamoeba castellanii highlights extensive lateral gene transfer and Early evolution of tyrosine kinase signaling. Genome Biol. 14 (2), R11. (6) Baig, A. M., Rana, Z., Tariq, S., Lalani, S., and Ahmad, H. R. (2017) Traced on the Timeline: Discovery of Acetylcholine and the Components of the Human Cholinergic System in a Primitive Unicellular Eukaryote Acanthamoeba spp. ACS Chem. Neurosci., DOI: 10.1021/acschemneuro.7b00254.

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DOI: 10.1021/acschemneuro.7b00492 ACS Chem. Neurosci. XXXX, XXX, XXX−XXX