| Literature DB >> 34523908 |
Barbara Forte1, Sabine Ottilie2, Andrew Plater1, Brice Campo3, Koen J Dechering4, Francisco Javier Gamo5, Daniel E Goldberg6, Eva S Istvan6, Marcus Lee7, Amanda K Lukens8,9, Case W McNamara10, Jacquin C Niles11, John Okombo12, Charisse Flerida A Pasaje11, Miles G Siegel13, Dyann Wirth8,9, Susan Wyllie1, David A Fidock12,14, Beatriz Baragaña1, Elizabeth A Winzeler2, Ian H Gilbert1.
Abstract
There is a shift in antimalarial drug discovery from phenotypic screening toward target-based approaches, as more potential drug targets are being validated in Plasmodium species. Given the high attrition rate and high cost of drug discovery, it is important to select the targets most likely to deliver progressible drug candidates. In this paper, we describe the criteria that we consider important for selecting targets for antimalarial drug discovery. We describe the analysis of a number of drug targets in the Malaria Drug Accelerator (MalDA) pipeline, which has allowed us to prioritize targets that are ready to enter the drug discovery process. This selection process has also highlighted where additional data are required to inform target progression or deprioritization of other targets. Finally, we comment on how additional drug targets may be identified.Entities:
Keywords: Plasmodium; drug discovery; malaria; molecular targets
Mesh:
Substances:
Year: 2021 PMID: 34523908 PMCID: PMC8608365 DOI: 10.1021/acsinfecdis.1c00322
Source DB: PubMed Journal: ACS Infect Dis ISSN: 2373-8227 Impact factor: 5.084
Target Candidate Profile (TCP) definitions
| TCP | Goal | Definition |
|---|---|---|
| TCP-1 | Treatment of disease (both severe and uncomplicated) and chemoprophylaxis (protecting vulnerable populations) | Compounds active
against the asexual blood stage of the |
| TCP-3 | Anti-relapse (treatment for recurrent malaria) | Compounds active against liver stage hypnozoites |
| TCP-4 | Prophylaxis (for migratory population or outbreak prevention) | Compounds active against liver stages (ideally providing protection for at least a month) |
| TCP-5 | Transmission blockers (prevention strategies, e.g., treatment of asymptomatic infection) | Compounds active against parasite gametocytes |
| TCP-6 | Transmission blockers | Compounds that block transmission by targeting the insect vector (mosquitocides / endectocides) |
Target Product Profile (TPP) definitions
| TPP | Goal | Definition |
|---|---|---|
| TPP-1 | Treating active disease | Ideally, a combination of TCP-1 with TCP-5 or TCP-3 in order to cure acute or uncomplicated malaria in both adults and children, ideally given as a single oral dose. A fast-killing TCP-1 compound with parenteral administration is essential for severe malaria. |
| TPP-2 | Chemoprotection | Ideally a combination of TCP-4 and TCP-1 (for emerging infection) with the goal to treat migratory populations or prevent outbreaks. |
Figure 1Geographical location of MalDA consortium members. MalDA, with its state-of-the-art Plasmodium-adapted technology platforms in bioinformatics, chemo-informatics, chemo-proteomics, genetic manipulation, metabolomics, in vivo resistance evaluation, and medicinal chemistry expertise, is at the forefront of the antimalarial drug discovery process by providing tools to accelerate the finding of new starting points for drug discovery (www.malariaDA.org).[15]
Criteria for Target Prioritization
| tier 1 target assessment | ranking | |
|---|---|---|
| Genetic validation | Conditional knockout. Target vulnerability upon conditional knock-down | high |
| Essential in
genome-wide saturation mutagenesis in | medium | |
| Chemical validation | Compound-target pair established rigorously | high |
| Good correlation between enzyme and cell activity over 3 log units for a compound series | medium | |
| Resistance potential | Irresistible—no resistance found in selections | high |
| MIR 8–9 and no cross resistance with any drug in clinical use or development | medium | |
| 6 < MIR < 8 and no cross resistance with any drug in clinical use or development | low | |
| MIR ≤ 6 and an EC50 shift > 10-fold; or evidence
of high-grade resistance-conferring SNPs in field isolates; or enzyme
not conserved across | STOP | |
Examples of Deprioritized Targets for MalDA
| target name (abbreviation) | Pf gene ID | reason for deprioritization |
|---|---|---|
| PF3D7_1412800 | slow killer, challenges with selectivity compared to the human enzyme | |
| P-type ATPase 4 (ATP4) | PF3D7_1211900 | multiple series under investigation in the drug discovery pipeline |
| plasmepsin X | PF3D7_0808200 | multiple series under investigation in the drug discovery pipeline |
| Niemann–Pick type C1-related protein (NCR1) | PF3D7_0107500 | resistance risk, slow rate of kill and single-stage efficacy |
| dihydrofolate reductase (DHFR) | PF3D7_0417200 | clinically approved inhibitor; resistant parasites widespread in the field |
| dihydroorotate dehydrogenase (DHODH) | PF3D7_0603300 | multiple chemotypes have been developed, and resistance can arise readily |
| phosphatidyl inositol 4-kinase (PI4K) | PF3D7_0509800 | multiple chemotypes have been developed, and resistance can arise readily |
Figure 2Current MalDA target portfolio
Targets Ranked As High Priority
| target name (abbreviation) | Pf gene ID | key questions | next steps |
|---|---|---|---|
| serine/threonine protein kinase, putative[ | PF3D7_1114700 | can target be structurally enabled? | optimization of hits; more chemical starting points |
| cGMP-dependent protein kinase (PKG) | PF3D7_1436600 | rate of kill with selective inhibitor | Rate of kill (PRR assay); optimize chemical starting points |
| geranylgeranyl pyrophosphate synthase (F/GGPPS) | Pf3D7_1128400 | small molecule inhibitors | generate additional chemical matter |
| phenylalanine tRNA synthetase–alpha subunit (PheRS) | PF3D7_0109800 | resistance risk | more screening/scaffold hopping to identify more start points |
| prolyl tRNA synthetase, putative (ProRS) | PF3D7_0925300 | is selectivity versus human orthologues possible? | additional screens |
| acetyl CoA synthetase, putative (AcAS) | PF3D7_0627800 | resistance risk; can the target be structurally enabled? | proof of concept from MMV693183 first-in-human study; establish alternate lead series from existing hits/new screens and H2L; crystal structure to guide chemistry program |
| isoleucine—tRNA ligase, putative (cIRS) | PF3D7_1332900 | rate of kill, resistance risk | generate additional chemical matter |
Targets Ranked As Under Consideration and in Assay Development and Screening Stages
| target name (abbreviation) | Pf gene ID | key questions |
|---|---|---|
| cytosolic seryl-tRNA synthetase (SerRS) | PF3D7_0717700.1 | chemical starting points; TCP fit |
| V-Type H+ ATPase | includes PF3D7_0406100, PF3D7_0806800, PF3D7_1311900 | generate chemical matter; understand resistance profile, druggability, and TCP fit |
| heat shock protein 90 (HSP90) | PF3D7_0708400 | selectivity; more chemical starting points |
| adenylyl cyclase beta (AC beta) | PF3D7_0802600 | TCP fit; more potent inhibitors; selectivity |
| histone acetyltransferase GCN5 (GCN5) | PF3D7_0823300 | rate of kill; chemical starting points |
| phosphodiesterase beta (PDEβ) | PF3D7_1321500 | resistance potential TCP fit; More chemical starting points; chemical tools for validation |
| aminopeptidase P (APP) | PF3D7_1454400 | TCP fit; selectivity; chemical tools |
| cysteine tRNA synthetase (CysRS) | PF3D7_1015200.1 | protein expressed; development of assay; selectivity |
| hexose transporter (HT) | PF3D7_0204700 | is selectivity versus human orthologues possible? TCP fit; activity against various life cycle stages |
Figure 3Structures of tool compounds (see text for references to each structure)
Figure 4(A) Analysis of the P. falciparum genome categorizing targets according to their predicted essentiality, druggability, and the presence of mammalian orthologs. The number of proteins in each category is shown in parentheses. (B) Analysis of high value targets, according to tool compounds, the presence of mammalian orthologs, and proof of concept in humans. The number of proteins in each category is shown in parentheses. Where there is only one protein in a category, it is stated explicitly. Most MalDA targets fall into the light blue or violet regions.