Identification and Validation of Compounds Targeting Leishmania major Leucyl-Aminopeptidase M17

. 2024 Jun 14 ; 10 (6) : 2002-2017. [epub] 20240516

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid38753953

Grantová podpora
Wellcome Trust - United Kingdom

Leishmaniasis is a neglected tropical disease; there is currently no vaccine and treatment is reliant upon a handful of drugs suffering from multiple issues including toxicity and resistance. There is a critical need for development of new fit-for-purpose therapeutics, with reduced toxicity and targeting new mechanisms to overcome resistance. One enzyme meriting investigation as a potential drug target in Leishmania is M17 leucyl-aminopeptidase (LAP). Here, we aimed to chemically validate LAP as a drug target in L. major through identification of potent and selective inhibitors. Using RapidFire mass spectrometry, the compounds DDD00057570 and DDD00097924 were identified as selective inhibitors of recombinant Leishmania major LAP activity. Both compounds inhibited in vitro growth of L. major and L. donovani intracellular amastigotes, and overexpression of LmLAP in L. major led to reduced susceptibility to DDD00057570 and DDD00097924, suggesting that these compounds specifically target LmLAP. Thermal proteome profiling revealed that these inhibitors thermally stabilized two M17 LAPs, indicating that these compounds selectively bind to enzymes of this class. Additionally, the selectivity of the inhibitors to act on LmLAP and not against the human ortholog was demonstrated, despite the high sequence similarities LAPs of this family share. Collectively, these data confirm LmLAP as a promising therapeutic target for Leishmania spp. that can be selectively inhibited by drug-like small molecules.

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Burza S.; Croft S. L.; Boelaert M. Leishmaniasis. Lancet. 2018, 392 (10151), 951–970. 10.1016/S0140-6736(18)31204-2. PubMed DOI

World Health Organization. Leishmaniasis. 2023, Retrieved from https://apps.who.int/neglected_diseases/ntddata/leishmaniasis/leishmaniasis.html.

Desjeux P. The increase in risk factors for leishmaniasis worldwide. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2001, 95 (3), 239–243. 10.1016/S0035-9203(01)90223-8. PubMed DOI

World Health Organization. Leishmaniasis. 2023, Retrieved from https://www.who.int/news-room/fact-sheets/detail/leishmaniasis.

Boelaert M.; Sundar S.. Leishmaniasis. In Manson’s Tropical Diseases, 23rd ed.; Farrar J.; Hotez P. J.; Junghanss T.; Kang G.; Lalloo D.; White N., Eds.; Elsevier Inc.: Philadelphia, 2014; pp 631–651.http://lib.itg.be/pdf/itg/2013/2013mtdi0631.pdf.

Mann S.; Frasca K.; Scherrer S.; Henao-Martínez A. F.; Newman S.; Ramanan P.; Suarez J. A. A Review of Leishmaniasis: Current Knowledge and Future Directions. Curr. Trop Med. Rep. 2021, 8 (2), 121–132. 10.1007/s40475-021-00232-7. PubMed DOI PMC

Lupi O.; Bartlett B. L.; Haugen R. N.; Dy L. C.; Sethi A.; Klaus S. N.; Machado Pinto J.; Bravo F.; Tyring S. K. Tropical dermatology: Tropical diseases caused by protozoa. J. Am. Acad. Dermatol. 2009, 60 (6), 897–925. quiz 926–92810.1016/j.jaad.2009.03.004. PubMed DOI

World Health Organization. Neglected tropical diseases. 2021, Retrieved from https://www.who.int/health-topics/neglected-tropical-diseases/#tab=tab_1.

Alvar J.; Vélez I. D.; Bern C.; Herrero M.; Desjeux P.; Cano J.; Jannin J.; den Boer M. WHO leishmaniasis control team Leishmaniasis worldwide and global estimates of its incidence. PLoS One 2012, 7 (5), e3567110.1371/journal.pone.0035671. PubMed DOI PMC

Mohapatra S. Drug resistance in leishmaniasis: Newer developments. Trop Parasitol. 2014, 4 (1), 4–9. 10.4103/2229-5070.129142. PubMed DOI PMC

Kedzierski L.; Sakthianandeswaren A.; Curtis J. M.; Andrews P. C.; Junk P. C.; Kedzierska K. (2009) Leishmaniasis: current treatment and prospects for new drugs and vaccines. Curr. Med. Chem. 2009, 16 (5), 599–614. 10.2174/092986709787458489. PubMed DOI

De Almeida Nogueira N. P.; Morgado-Díaz J. A.; Menna-Barreto R. F.; Paes M. C.; da Silva-López R. E. Effects of a marine serine protease inhibitor on viability and morphology of Trypanosoma cruzi, the agent of Chagas disease. Acta Trop. 2013, 128 (1), 27–35. 10.1016/j.actatropica.2013.05.013. PubMed DOI

Matsui M.; Fowler J. H.; Walling L. L. Leucine aminopeptidases: diversity in structure and function. Biol. Chem. 2006, 387 (12), 1535–1544. 10.1515/BC.2006.191. PubMed DOI

Cadavid-Restrepo G.; Gastardelo T. S.; Faudry E.; de Almeida H.; Bastos I. M.; Negreiros R. S.; Lima M. M.; Assumpção T. C.; Almeida K. C.; Ragno M.; Ebel C.; Ribeiro B. M.; Felix C. R.; Santana J. M. The major leucyl aminopeptidase of Trypanosoma cruzi (LAPTc) assembles into a homohexamer and belongs to the M17 family of metallopeptidases. BMC Biochem. 2011, 12, 46.10.1186/1471-2091-12-46. PubMed DOI PMC

Harbut M. B.; Velmourougane G.; Dalal S.; Reiss G.; Whisstock J. C.; Onder O.; Brisson D.; McGowan S.; Klemba M.; Greenbaum D. C. Bestatin-based chemical biology strategy reveals distinct roles for malaria M1- and M17-family aminopeptidases. Proc. Natl. Acad. Sci. U. S. A. 2011, 108 (34), E52610.1073/pnas.1105601108. PubMed DOI PMC

Aguado M. E.; Izquierdo M.; González-Matos M.; Varela A. C.; Méndez Y.; Del Rivero M. A.; Rivera D. G.; González-Bacerio J. Parasite Metalo-aminopeptidases as Targets in Human Infectious Diseases. Curr. Drug Targets. 2023, 24 (5), 416–461. 10.2174/1389450124666230224140724. PubMed DOI

Edgar R. C. S.; Siddiqui G.; Hjerrild K.; Malcolm T. R.; Vinh N. B.; Webb C. T.; Holmes C.; MacRaild C. A.; Chernih H. C.; Suen W. W.; Counihan N. A.; Creek D. J.; Scammells P. J.; McGowan S.; de Koning-Ward T. F. Genetic and chemical validation of Plasmodium falciparum aminopeptidase PfA-M17 as a drug target in the hemoglobin digestion pathway. Elife. 2022, 11, e8081310.7554/eLife.80813. PubMed DOI PMC

Timm J.; Valente M.; García-Caballero D.; Wilson K. S.; González-Pacanowska D. Structural Characterization of Acidic M17 Leucine Aminopeptidases from the TriTryps and Evaluation of Their Role in Nutrient Starvation in Trypanosoma brucei. mSphere 2017, 2 (4), e00226-1710.1128/mSphere.00226-17. PubMed DOI PMC

Morty R. E.; Morehead J. Cloning and characterization of a leucyl aminopeptidase from three pathogenic Leishmania species. J. Biol. Chem. 2002, 277 (29), 26057–26065. 10.1074/jbc.M202779200. PubMed DOI

Gu Y. Q.; Walling L. L. Identification of Residues Critical for Activity of the Wound-Induced Leucine Aminopeptidase (LAP-A) of Tomato. European Journal of Biochemistry/FEBS. 2002, 269, 1630–1640. 10.1046/j.1432-1327.2002.02795.x. PubMed DOI

Schneider P.; Glaser T. A. Characterisation of two soluble metalloexopeptidases in the protozoan parasite Leishmania major. Mol. Biochem. Parasitol. 1993, 62 (2), 223–231. 10.1016/0166-6851(93)90111-A. PubMed DOI

Ginger M. L.; Prescott M. C.; Reynolds D. G.; Chance M. L.; Goad L. J. Utilization of leucine and acetate as carbon sources for sterol and fatty acid biosynthesis by Old and New World Leishmania species, Endotrypanum monterogeii and Trypanosoma cruzi. Eur. J. Biochem. 2000, 267 (9), 2555–66. 10.1046/j.1432-1327.2000.01261.x. PubMed DOI

Aguado M. E.; González-Matos M.; Izquierdo M.; Quintana J.; Field M. C.; González-Bacerio J. Expression in Escherichia coli, purification and kinetic characterization of LAPLm, a Leishmania major M17-aminopeptidase. Protein Expr Purif. 2021, 183, 105877.10.1016/j.pep.2021.105877. PubMed DOI

Izquierdo M.; Lin D.; O’Neill S.; Zoltner M.; Webster L.; Hope A.; Gray D. W.; Field M. C.; González-Bacerio J. Development of a high-throughput screening assay to identify inhibitors of the major M17-leucyl aminopeptidase from Trypanosoma cruzi using RapidFire mass spectrometry. SLAS Discovery 2020, 25 (9), 1064–1071. 10.1177/2472555220923367. PubMed DOI

Izquierdo M.; Lin D.; O’Neill S.; Webster L. A.; Paterson C.; Thomas J.; Aguado M. E.; Colina Araújo E.; Alpízar-Pedraza D.; Joji H.; MacLean L.; Hope A.; Gray D. W.; Zoltner M.; Field M. C.; González-Bacerio J.; De Rycker M. Identification of a potent and selective LAPTc inhibitor by RapidFire-Mass Spectrometry, with antichagasic activity. PLoS Negl. Trop. Dis. 2024, 18 (2), e001195610.1371/journal.pntd.0011956. PubMed DOI PMC

Copeland R. A.Enzymes, A Practical Introduction to Structure, Mechanism, and Data Analysis, 2nd ed.; Wiley-VCH, Inc.: New York, 2000.

Taylor M.; Ho J. MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn. J. Comput. Aided Mol. Des. 2023, 37 (4), 167–182. 10.1007/s10822-023-00499-0. PubMed DOI PMC

Corpas-Lopez V.; Wyllie S. Utilizing thermal proteome profiling to identify the molecular targets of anti-leishmanial compounds. STAR Protoc. 2021, 2 (3), 100704.10.1016/j.xpro.2021.100704. PubMed DOI PMC

Milne R.; Wiedemar N.; Corpas-Lopez V.; Moynihan E.; Wall R. J.; Dawson A.; Robinson D. A.; Shepherd S. M.; Smith R. J.; Hallyburton I.; Post J. M.; Dowers K.; Torrie L. S.; Gilbert I. H.; Baragaña B.; Patterson S.; Wyllie S. Toolkit of Approaches To Support Target-Focused Drug Discovery for Plasmodium falciparum Lysyl tRNA Synthetase. ACS Infect Dis. 2022, 8 (9), 1962–1974. 10.1021/acsinfecdis.2c00364. PubMed DOI PMC

Ambit A.; Woods K. L.; Cull B.; Coombs G. H.; Mottram J. C. Morphological events during the cell cycle of Leishmania major. Eukaryot Cell. 2011, 10 (11), 1429–1438. 10.1128/EC.05118-11. PubMed DOI PMC

Sajid M.; Robertson S. A.; Brinen L. S.; McKerrow J. H. Cruzain: the path from target validation to the clinic. Adv. Exp. Med. Biol. 2011, 712, 100–115. 10.1007/978-1-4419-8414-2_7. PubMed DOI

González-Bacerio J.; Varela A. C.; Aguado M. E.; Izquierdo M.; Méndez Y.; Del Rivero M. A.; Rivera D. G. Bacterial Metalo-Aminopeptidases as Targets in Human Infectious Diseases. Curr. Drug Targets. 2022, 23 (12), 1155–1190. 10.2174/1389450123666220316085859. PubMed DOI

Arastu-Kapur S.; Ponder E. L.; Fonović U. P.; Yeoh S.; Yuan F.; Fonović M.; Grainger M.; Phillips C. I.; Powers J. C.; Bogyo M. Identification of proteases that regulate erythrocyte rupture by the malaria parasite Plasmodium falciparum. Nat. Chem. Biol. 2008, 4 (3), 203–13. 10.1038/nchembio.70. PubMed DOI

Benz C.; Clucas C.; Mottram J. C.; Hammarton T. C. Cytokinesis in bloodstream stage Trypanosoma brucei requires a family of katanins and spastin. PLoS One 2012, 7 (1), e30367-1210.1371/journal.pone.0030367. PubMed DOI PMC

Peña-Diaz P.; Vancová M.; Resl C.; Field M. C.; Lukeš J. A leucine aminopeptidase is involved in kinetoplast DNA segregation in Trypanosoma brucei. PLoS Pathog. 2017, 13 (4), e100631010.1371/journal.ppat.1006310. PubMed DOI PMC

Billington K.; Halliday C.; Madden R.; Dyer P.; Barker A. R.; Moreira-Leite F. F.; Carrington M.; Vaughan S.; Hertz-Fowler C.; Dean S.; Sunter J. D.; Wheeler R. J.; Gull K. Genome-wide subcellular protein map for the flagellate parasite Trypanosoma brucei. Nat. Microbiol. 2023, 8 (3), 533–547. 10.1038/s41564-022-01295-6. PubMed DOI PMC

Flipo M.; Beghyn T.; Leroux V.; Florent I.; Deprez B. P.; Deprez-Poulain R. F. Novel selective inhibitors of the zinc plasmodial aminopeptidase PfA-M1 as potential antimalarial agents. J. Med. Chem. 2007, 50 (6), 1322–1334. 10.1021/jm061169b. PubMed DOI

Drinkwater N.; Malcolm T. R.; McGowan S. M17 aminopeptidases diversify function by moderating their macromolecular assemblies and active site environment. Biochimie. 2019, 166, 38–51. 10.1016/j.biochi.2019.01.007. PubMed DOI

Machado P. A.; Carneiro M. P. D.; Sousa-Batista A. J.; Lopes F. J. P.; Lima A. P. C. A.; Chaves S. P.; Sodero A. C. R.; de Matos Guedes H. L. Leishmanicidal therapy targeted to parasite proteases. Life Sci. 2019, 219, 163–181. 10.1016/j.lfs.2019.01.015. PubMed DOI

Van Bocxlaer K.; Caridha D.; Black C.; Vesely B.; Leed S.; Sciotti R. J.; Wijnant G. J.; Yardley V.; Braillard S.; Mowbray C. E.; Ioset J. R.; Croft S. L. Novel benzoxaborole, nitroimidazole and aminopyrazoles with activity against experimental cutaneous leishmaniasis. Int. J. Parasitol Drugs Drug Resist. 2019, 11, 129–138. 10.1016/j.ijpddr.2019.02.002. PubMed DOI PMC

Wyllie S.; Brand S.; Thomas M.; De Rycker M.; Chung C. W.; Pena I.; Bingham R. P.; Bueren-Calabuig J. A.; Cantizani J.; Cebrian D.; Craggs P. D.; Ferguson L.; Goswami P.; Hobrath J.; Howe J.; Jeacock L.; Ko E. J.; Korczynska J.; MacLean L.; Manthri S.; Wyatt P. G.; et al. Preclinical candidate for the treatment of visceral leishmaniasis that acts through proteasome inhibition. Proc. Nat. Acad. Sci. U. S. A. 2019, 116 (19), 9318–9323. 10.1073/pnas.1820175116. PubMed DOI PMC

Mowbray C. E.; Braillard S.; Glossop P. A.; Whitlock G. A.; Jacobs R. T.; Speake J.; Pandi B.; Nare B.; Maes L.; Yardley V.; Freund Y.; Wall R. J.; Carvalho S.; Bello D.; Van den Kerkhof M.; Caljon G.; Gilbert I. H.; Corpas-Lopez V.; Lukac I.; Patterson S.; Zuccotto F.; Wyllie S. DNDI-6148: A Novel Benzoxaborole Preclinical Candidate for the Treatment of Visceral Leishmaniasis. J. Med. Chem. 2021, 64 (21), 16159–16176. 10.1021/acs.jmedchem.1c01437. PubMed DOI PMC

Valiallahi A.; Vazifeh Z.; Gatabi Z. R.; Davoudi M.; Gatabi I. R. (2023). PLGA Nanoparticles as New Drug Delivery Systems in Leishmaniasis Chemotherapy: A Review of Current Practices. Current medicinal chemistry. 2023, 10.2174/0929867331666230823094737. PubMed DOI

Braillard S.; Keenan M.; Breese K. J.; Heppell J.; Abbott M.; Islam R.; Shackleford D. M.; Katneni K.; Crighton E.; Chen G.; Patil R.; Lee G.; White K. L.; Carvalho S.; Wall R. J.; Chemi G.; Zuccotto F.; González S.; Marco M.; Deakyne J.; Standing D.; Brunori G.; Lyon J. J.; Castañeda-Casado P.; Camino I.; Martinez Martinez M. S.; Zulfiqar B.; Avery V. M.; Feijens P. B.; Van Pelt N.; Matheeussen A.; Hendrickx S.; Maes L.; Caljon G.; Yardley V.; Wyllie S.; Charman S. A.; Chatelain E. DNDI-6174 is a preclinical candidate for visceral leishmaniasis that targets the cytochrome bc1. Sci. Transl Med. 2023, 15 (726), eadh990210.1126/scitranslmed.adh9902. PubMed DOI PMC

Kao C. C.; Wedes S. H.; Hsu J. W.; Bohren K. M.; Comhair S. A.; Jahoor F.; Erzurum S. C. Arginine metabolic endotypes in pulmonary arterial hypertension. Pulm Circ. 2015, 5 (1), 124–34. 10.1086/679720. PubMed DOI PMC

Mirdita M.; Steinegger M.; Söding J. MMseqs2 desktop and local web server app for fast, interactive sequence searches. Bioinformatics. 2019, 35 (16), 2856–2858. 10.1093/bioinformatics/bty1057. PubMed DOI PMC

Steinegger M.; Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 2017, 35 (11), 1026–1028. 10.1038/nbt.3988. PubMed DOI

Jumper J.; Evans R.; Pritzel A.; Green T.; Figurnov M.; Ronneberger O.; Tunyasuvunakool K.; Bates R.; Žídek A.; Potapenko A.; Bridgland A.; Meyer C.; Kohl S. A. A.; Ballard A. J.; Cowie A.; Romera-Paredes B.; Nikolov S.; Jain R.; Adler J.; Back T.; Bodenstein S.; Silver D.; Vinyals O.; Senior A. W.; Kavukcuoglu K.; Kohli P.; Hassabis D.; et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021, 596 (7873), 583–589. 10.1038/s41586-021-03819-2. PubMed DOI PMC

Fiser A.; Do R. K.; Sali A. Modeling of loops in protein structures. Protein Sci. 2000, 9 (9), 1753–1773. 10.1110/ps.9.9.1753. PubMed DOI PMC

Fiser A.; Sali A. ModLoop: automated modeling of loops in protein structures. Bioinformatics. 2003, 19 (18), 2500–2501. 10.1093/bioinformatics/btg362. PubMed DOI

Hanwell M. D.; Curtis D. E.; Lonie D. C.; Vandermeersch T.; Zurek E.; Hutchison G. R. Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. J. Cheminform. 2012, 4 (1), 17.10.1186/1758-2946-4-17. PubMed DOI PMC

Santos-Martins D.; Forli S.; Ramos M. J.; Olson A. J. AutoDock4(Zn): an improved AutoDock force field for small-molecule docking to zinc metalloproteins. J. Chem. Inf Model. 2014, 54 (8), 2371–2379. 10.1021/ci500209e. PubMed DOI PMC

Valdés-Tresanco M. S.; Valdés-Tresanco M. E.; Valiente P. A.; Moreno E. AMDock: a versatile graphical tool for assisting molecular docking with Autodock Vina and Autodock4. Biol. Direct. 2020, 15 (1), 12.10.1186/s13062-020-00267-2. PubMed DOI PMC

Morris G. M.; Huey R.; Lindstrom W.; Sanner M. F.; Belew R. K.; Goodsell D. S.; Olson A. J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem. 2009, 30 (16), 2785–2791. 10.1002/jcc.21256. PubMed DOI PMC

Abraham M. J.; Murtola T.; Schulz R.; Páll S.; Smith J. C.; Hess B.; Lindahl E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015, 1-2, 19.10.1016/j.softx.2015.06.001. DOI

Maier J. A.; Martinez C.; Kasavajhala K.; Wickstrom L.; Hauser K. E.; Simmerling C. ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J. Chem. Theory Comput. 2015, 11 (8), 3696–3713. 10.1021/acs.jctc.5b00255. PubMed DOI PMC

He X.; Man V. H.; Yang W.; Lee T. S.; Wang J. A fast and high-quality charge model for the next generation general AMBER force field. J. Chem. Phys. 2020, 153 (11), 114502.10.1063/5.0019056. PubMed DOI PMC

Jakalian A.; Bush B. L.; Jack D. B.; Bayly C. I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method. J. Comput. Chem. 2000, 21, 132–146. 10.1002/(SICI)1096-987X(20000130)21:2<132::AID-JCC5>3.0.CO;2-P. PubMed DOI

Jakalian A.; Jack D. B.; Bayly C. I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J. Comput. Chem. 2002, 23 (16), 1623–1641. 10.1002/jcc.10128. PubMed DOI

Jorgensen W. L.; Chandrasekhar J.; Madura J. D.; Impey W. R.; Klein M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79 (2), 926–935. 10.1063/1.445869. DOI

Yang W.; Riley B. T.; Lei X.; Porebski B. T.; Kass I.; Buckle A. M.; McGowan S. Generation of AMBER force field parameters for zinc centres of M1 and M17 family aminopeptidases. J. Biomol Struct Dyn. 2018, 36 (10), 2595–2604. 10.1080/07391102.2017.1364669. PubMed DOI

Hess B. P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation. J. Chem. Theory Comput. 2008, 4 (1), 116–122. 10.1021/ct700200b. PubMed DOI

Miyamoto S.; Kollman P. A. Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 1992, 13, 952–962. 10.1002/jcc.540130805. DOI

Nguyen H.; Roe D. R.; Simmerling C. Improved Generalized Born Solvent Model Parameters for Protein Simulations. J. Chem. Theory Comput. 2013, 9 (4), 2020–2034. 10.1021/ct3010485. PubMed DOI PMC

Valdés-Tresanco M. E.; Valdés-Tresanco M. S.; Moreno E.; Valiente P. A. Assessment of Different Parameters on the Accuracy of Computational Alanine Scanning of Protein-Protein Complexes with the Molecular Mechanics/Generalized Born Surface Area Method. J. Phys. Chem. B 2023, 127 (4), 944–954. 10.1021/acs.jpcb.2c07079. PubMed DOI

Park E. K.; Jung H. S.; Yang H. I.; Yoo M. C.; Kim C.; Kim K. S. Optimized THP-1 differentiation is required for the detection of responses to weak stimuli. Inflamm Res. 2007, 56 (1), 45–50. 10.1007/s00011-007-6115-5. PubMed DOI

Daigneault M.; Preston J. A.; Marriott H. M.; Whyte M. K.; Dockrell D. H. The identification of markers of macrophage differentiation in PMA-stimulated THP-1 cells and monocyte-derived macrophages. PLoS One. 2010, 5 (1), e866810.1371/journal.pone.0008668. PubMed DOI PMC

Paradela L. S.; Wall R. J.; Carvalho S.; Chemi G.; Corpas-Lopez V.; Moynihan E.; Bello D.; Patterson S.; Güther M. L. S.; Fairlamb A. H.; Ferguson M. A. J.; Zuccotto F.; Martin J.; Gilbert I. H.; Wyllie S. Multiple unbiased approaches identify oxidosqualene cyclase as the molecular target of a promising anti-leishmanial. Cell Chem. Biol. 2021, 28 (5), 711–721. 10.1016/j.chembiol.2021.02.008. PubMed DOI PMC

Perez-Riverol Y.; Csordas A.; Bai J.; Bernal-Llinares M.; Hewapathirana S.; Kundu D. J.; Inuganti A.; Griss J.; Mayer G.; Eisenacher M.; Pérez E.; Uszkoreit J.; Pfeuffer J.; Sachsenberg T.; Yilmaz S.; Tiwary S.; Cox J.; Audain E.; Walzer M.; Jarnuczak A. F.; Ternent T.; Brazma A.; Vizcaíno J. A. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 2019, 47 (D1), D442–D450. 10.1093/nar/gky1106. PubMed DOI PMC

Tyanova S.; Temu T.; Sinitcyn P.; Carlson A.; Hein M. Y.; Geiger T.; Mann M.; Cox J. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods. 2016, 13 (9), 731–40. 10.1038/nmeth.3901. PubMed DOI

Allan C.; Burel J. M.; Moore J.; Blackburn C.; Linkert M.; Loynton S.; Macdonald D.; Moore W. J.; Neves C.; Patterson A.; Porter M.; Tarkowska A.; Loranger B.; Avondo J.; Lagerstedt I.; Lianas L.; Leo S.; Hands K.; Hay R. T.; Patwardhan A.; Best C.; Kleywegt G. J.; Zanetti G.; Swedlow J. R. OMERO: flexible, model-driven data management for experimental biology. Nat. Methods. 2012, 9 (3), 245–53. 10.1038/nmeth.1896. PubMed DOI PMC

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