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Malaria Journal
Published in: Malaria Journal 1/2020

Open Access 01-12-2020 | Malaria | Research

Characterisation of plasmodial transketolases and identification of potential inhibitors: an in silico study

Authors: Rita Afriyie Boateng, Özlem Tastan Bishop, Thommas Mutemi Musyoka

Published in: Malaria Journal | Issue 1/2020

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Abstract

Background

Plasmodial transketolase (PTKT) enzyme is one of the novel pharmacological targets being explored as potential anti-malarial drug target due to its functional role and low sequence identity to the human enzyme. Despite this, features contributing to such have not been exploited for anti-malarial drug design. Additionally, there are no anti-malarial drugs targeting PTKTs whereas the broad activity of these inhibitors against PTKTs from other Plasmodium spp. is yet to be reported. This study characterises different PTKTs [Plasmodium falciparum (PfTKT), Plasmodium vivax (PvTKT), Plasmodium ovale (PoTKT), Plasmodium malariae (PmTKT) and Plasmodium knowlesi (PkTKT) and the human homolog (HsTKT)] to identify key sequence and structural based differences as well as the identification of selective potential inhibitors against PTKTs.

Methods

A sequence-based study was carried out using multiple sequence alignment, phylogenetic tree calculations and motif discovery analysis. Additionally, TKT models of PfTKT, PmTKT, PoTKT, PmTKT and PkTKT were modelled using the Saccharomyces cerevisiae TKT structure as template. Based on the modelled structures, molecular docking using 623 South African natural compounds was done. The stability, conformational changes and detailed interactions of selected compounds were accessed viz all-atom molecular dynamics (MD) simulations and binding free energy (BFE) calculations.

Results

Sequence alignment, evolutionary and motif analyses revealed key differences between plasmodial and the human TKTs. High quality homodimeric three-dimensional PTKTs structures were constructed. Molecular docking results identified three compounds (SANC00107, SANC00411 and SANC00620) which selectively bind in the active site of all PTKTs with the lowest (better) binding affinity ≤ − 8.5 kcal/mol. MD simulations of ligand-bound systems showed stable fluctuations upon ligand binding. In all systems, ligands bind stably throughout the simulation and form crucial interactions with key active site residues. Simulations of selected compounds in complex with human TKT showed that ligands exited their binding sites at different time steps. BFE of protein–ligand complexes showed key residues involved in binding.

Conclusions

This study highlights significant differences between plasmodial and human TKTs and may provide valuable information for the development of novel anti-malarial inhibitors. Identified compounds may provide a starting point in the rational design of PTKT inhibitors and analogues based on these scaffolds.
Appendix
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Literature
1.
2.
Joshi S, Singh AR, Kumar A, Misra PC, Siddiqi MI, Saxena JK. Molecular cloning and characterization of Plasmodium falciparum transketolase. Mol Biochem Parasitol. 2008;160:32–41.PubMed
3.
Schenk G, Duggleby RG, Nixon PF. Properties and functions of the thiamin diphosphate dependent enzyme transketolase. Int J Biochem Cell Biol. 1998;30:1297–318.PubMed
4.
Mitschke L, Parthier C, Schröder-Tittmann K, Coy J, Lüdtke S, Tittmann K. The crystal structure of human transketolase and new insights into its mode of action. J Biol Chem. 2010;285:31559–70.PubMedPubMedCentral
5.
Heinrich PC, Steffen H, Janser P, Wiss O. Studies on the reconstitution of apotransketolase with thiamine pyrophosphate and analogs of the coenzyme. Eur J Biochem. 1972;30:533–41.PubMed
6.
Muller YA, Lindqvist Y, Furey W, Schulz GE, Jordan F, Schneider G. A thiamin diphosphate binding fold revealed by comparison of the crystal structures of transketolase, pyruvate oxidase and pyruvate decarboxylase. Structure. 1993;1:95–103.PubMed
7.
Wille G, Meyer D, Steinmetz A, Hinze E, Golbik R, Tittmann K. The catalytic cycle of a thiamin diphosphate enzyme examined by cryocrystallography. Nat Chem Biol. 2006;2:324–8.PubMed
8.
Lindqvist Y, Schneider G, Ermler U, Sundström M. Three-dimensional structure of transketolase, a thiamine diphosphate dependent enzyme, at 2.5 Å resolution. Embo J. 1992;11:2373–9.PubMedPubMedCentral
9.
Kochetov G, Sevostyanova IA. Binding of the coenzyme and formation of the transketolase active center. IUBMB Life. 2005;57:491–7.PubMed
10.
Tittmann K. Sweet siblings with different faces: the mechanisms of FBP and F6P aldolase, transaldolase, transketolase and phosphoketolase revisited in light of recent structural data. Bioorg Chem. 2014;57:263–80.PubMed
11.
Nikkola M, Lindqvist Y, Schneider G. Refined structure of transketolase from Saccharomyces cerevisiae at 2·0 Å resolution. J Mol Biol. 1994;238:387–404.PubMed
12.
Liu H, Huang D, McArthur DL, Boros LG, Nissen N, Heaney AP. Fructose induces transketolase flux to promote pancreatic cancer growth. Cancer Res. 2010;70:6368–76.PubMed
13.
Atamna H, Ginsburg H. Origin of reactive oxygen species in erythrocytes infected with Plasmodium falciparum. Mol Biochem Parasitol. 1993;61:231–41.PubMed
14.
Nilsson U, Lindqvist Y, Kluger R, Schneider G. Crystal structure of transketolase in complex with thiamine thiazolone diphosphate, an analogue of the reaction intermediate, at 2.3 Å resolution. FEBS Lett. 1993;326:145–8.PubMed
15.
Nilsson U, Meshalkina L, Lindqvist Y, Schneider G. Examination of substrate binding in thiamin diphosphate-dependent transketolase by protein crystallography and site-directed mutagenesis. J Biol Chem. 1997;272:1864–9.PubMed
16.
Solovjeva ON, Kochetov GA. Inhibition of transketolase by p-hydroxyphenylpyruvate. FEBS Lett. 1999;462:246–8.PubMed
17.
Sharma M, Chauhan K, Chauhan SS, Kumar A, Singh SV, Saxena JK, et al. Synthesis of hybrid 4-anilinoquinoline triazines as potent antimalarial agents, their in silico modeling and bioevaluation as Plasmodium falciparum transketolase and β-hematin inhibitors. Med Chem Commun. 2012;3:71–9.
18.
Kotra L, Meza-Avina M, Wei L, Buhendwa M, Poduch E, Bello A, et al. Inhibition of orotidine 5-monophosphate decarboxylase and its therapeutic potential: mini-reviews. Med Chem. 2008;8:239–47.
19.
Pavadai E, El Mazouni F, Wittlin S, de Kock C, Phillips MA, Chibale K. Identification of new human malaria parasite Plasmodium falciparum dihydroorotate dehydrogenase inhibitors by pharmacophore and structure-based virtual screening. J Chem Inf Model. 2016;56:548–62.PubMedPubMedCentral
20.
Wadood A, Ghufran M, Hassan SF, Khan H, Azam SS, Rashid U. In silico identification of promiscuous scaffolds as potential inhibitors of 1-deoxy-d-xylulose 5-phosphate reductoisomerase for treatment of falciparum malaria. Pharm Biol. 2017;55:19–32.PubMed
21.
Hatherley R, Brown DK, Musyoka TM, Penkler DL, Faya N, Lobb KA, et al. SANCDB: a South African natural compound database. J Cheminform. 2015;7:29.PubMedPubMedCentral
22.
Aurrecoechea C, Brestelli J, Brunk BP, Dommer J, Fischer S, Gajria B, et al. PlasmoDB: a functional genomic database for malaria parasites. Nucleic Acids Res. 2009;37:D539–43.PubMed
23.
Coordinators NR. Database resources of the national center for biotechnology information. Nucleic Acids Res. 2017;45:D12–7.
24.
Pei J, Grishin NV. PROMALS3D: multiple protein sequence alignment enhanced with evolutionary and three-dimensional structural information. Methods Mol Biol. 2014;1079:263–71.PubMedPubMedCentral
25.
Katoh K, Standley DM. MAFFT: iterative refinement and additional methods. Methods Mol Biol. 2014;1079:131–46.PubMed
26.
Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview version 2: a multiple sequence alignment and analysis workbench. Bioinformatics. 2009;25:1189–91.PubMedPubMedCentral
27.
Hatherley R, Clitheroe C-L, Faya N, Tastan BÖ. Plasmodium falciparum Hop: detailed analysis on complex formation with Hsp70 and Hsp90. Biochem Biophys Res Commun. 2015;456:440–5.PubMed
28.
Le SQ, Lartillot N, Gascuel O. Phylogenetic mixture models for proteins. Philos Trans R Soc B Biol Sci. 2008;363:3965–76.
29.
Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870–4.PubMedPubMedCentral
30.
Fiser A, Šali A. Modeller: generation and refinement of homology-based protein structure models. Methods Enzymol. 2003;374:461–91.PubMed
31.
Hatherley R, Brown DK, Glenister M, Tastan BÖ. PRIMO: an interactive homology modeling pipeline. PLoS ONE. 2016;11:e0166698.PubMedPubMedCentral
32.
Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr. 1993;26:283–91.
33.
Eisenberg D, Lüthy R, Bowie JU. VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol. 1997;277:396–404.PubMed
34.
Benkert P, Tosatto SCE, Schomburg D. QMEAN: a comprehensive scoring function for model quality assessment. Proteins Struct Funct Bioinform. 2008;71:261–77.
35.
Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35:W407–10.PubMedPubMedCentral
36.
Burley SK, Berman HM, Kleywegt GJ, Markley JL, Nakamura H, Velankar S. Protein Data Bank (PDB): the single global macromolecular structure archive. Methods Mol Biol. 2017;1607:627–41.PubMedPubMedCentral
37.
Shen M, Sali A. Statistical potential for assessment and prediction of protein structures. Protein Sci. 2006;15:2507–24.PubMedPubMedCentral
38.
39.
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31:455–61.PubMedPubMedCentral
40.
San Diego: Accelrys Software Inc. Discovery studio modeling environment, release 3.5. Accelrys Softw. Inc. 2012.
41.
El-Hachem N, Haibe-Kains B, Khalil A, Kobeissy FH, Nemer G. AutoDock and AutoDockTools for protein–ligand docking: beta-site amyloid precursor protein cleaving enzyme 1(BACE1) as a case study. Methods Mol Biol. 2017;1598:391–403.PubMed
42.
Lipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol. 2004;1:337–41.PubMed
43.
Jayaram B, Singh T, Mukherjee G, Mathur A, Shekhar S, Shekhar V. Sanjeevini: a freely accessible web-server for target directed lead molecule discovery. BMC Bioinform. 2012;13:S7.
44.
Baell JB, Holloway GA. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J Med Chem. 2010;53:2719–40.PubMed
45.
Baell JB, Nissink JWM. Seven year itch: pan-assay interference compounds (PAINS) in 2017—utility and limitations. ACS Chem Biol. 2018;13:36–44.PubMed
46.
Laskowski RA, Swindells MB. LigPlot+: multiple ligand–protein interaction diagrams for drug discovery. J Chem Inf Model. 2011;51:2778–86.PubMed
47.
Abraham M, Hess B, van der Spoel D, Lindahl E. User manual. Berlin: Springer; 2015. p. 1–259.
48.
Kollman P, Dixon R, Cornell W, Fox T, Chipot C, Pohorille A. The development/application of a ‘minimalist’ organic/biochemical molecular mechanic force field using a combination of ab initio calculations and experimental data. In: Van Gunsteren WF, Weiner PK, Wilkinson AJ, editors. Computer simulation of biomolecular systems. Dordrecht: Springer; 1997. p. 83–96.
49.
SousadaSilva AW, Vranken WF. ACPYPE—antechamber python parser interface. BMC Res Notes. 2012;5:367.
50.
Parrinello M, Rahman A. Polymorphic transitions in single crystals: a new molecular dynamics method. J Appl Phys. 1981;52:7182–90.
51.
Salentin S, Schreiber S, Haupt VJ, Adasme MF, Schroeder M. PLIP: fully automated protein–ligand interaction profiler. Nucleic Acids Res. 2015;43:W443–7.PubMedPubMedCentral
52.
Humphrey W, Dalke A, Schulten KVMD. Visual molecular dynamics. J Mol Graph. 1996;14:33–8.PubMed
53.
Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, et al. Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res. 2000;33:889–97.PubMed
54.
Musyoka TM, Kanzi AM, Lobb KA, Tastan BÖ. Analysis of non-peptidic compounds as potential malarial inhibitors against plasmodial cysteine proteases via integrated virtual screening workflow. J Biomol Struct Dyn. 2016;34:2084–101.PubMedPubMedCentral
55.
Wang C, Greene D, Xiao L, Qi R, Luo R. Recent developments and applications of the MMPBSA method. Front Mol Biosci. 2018;4:87.PubMedPubMedCentral
56.
Schenk G, Layfield R, Candy JM, Duggleby RG, Nixon PF. Molecular evolutionary analysis of the thiamine-diphosphate-dependent enzyme, transketolase. J Mol Evol. 1997;44:552–72.PubMed
57.
Faya N, Penkler DL, Tastan BÖ. Human, vector and parasite Hsp90 proteins: a comparative bioinformatics analysis. FEBS Open Bio. 2015;5:916–27.PubMedPubMedCentral
58.
Nyamai DW, Tastan BÖ. Aminoacyl tRNA synthetases as malarial drug targets: a comparative bioinformatics study. Malar J. 2019;18:34.PubMedPubMedCentral
59.
Gnémé A, Guelbéogo WM, Riehle MM, Tiono AB, Diarra A, Kabré GB, et al. Plasmodium species occurrence, temporal distribution and interaction in a child-aged population in rural Burkina Faso. Malar J. 2013;12:67.PubMedPubMedCentral
60.
Otto TD, Böhme U, Jackson AP, Hunt M, Franke-Fayard B, Hoeijmakers WAM, et al. A comprehensive evaluation of rodent malaria parasite genomes and gene expression. BMC Biol. 2014;12:86.PubMedPubMedCentral
61.
Schwarz R, Dayhoff M. Matrices for detecting distant relationships. In: Dayhoff M, editor. Atlas of protein sequences. Washington: National Biomedical Research Foundation; 1979. p. 353–8.
62.
Fidler DR, Murphy SE, Courtis K, Antonoudiou P, El-Tohamy R, Ient J, et al. Using HHsearch to tackle proteins of unknown function: a pilot study with PH domains. Traffic. 2016;17:1214–26.PubMedPubMedCentral
63.
64.
Ross C, Knox C, Tastan BÖ. Interacting motif networks located in hotspots associated with RNA release are conserved in Enterovirus capsids. FEBS Lett. 2017;591:1687–701.PubMed
65.
Davey NE, Van Roey K, Weatheritt RJ, Toedt G, Uyar B, Altenberg B, et al. Attributes of short linear motifs. Mol BioSyst. 2012;8:268–81.PubMed
66.
Costelloe SJ, Ward JM, Dalby PA. Evolutionary analysis of the TPP-dependent enzyme family. J Mol Evol. 2008;66:36–49.PubMed
67.
Hulo N. The PROSITE database. Nucleic Acids Res. 2006;34:D227–30.PubMed
68.
Hawkins CF, Borges A, Perham RN. A common structural motif in thiamin pyrophosphate-binding enzymes. FEBS Lett. 1989;255:77–82.PubMed
69.
Dell’Agli M, Giavarini F, Ferraboschi P, Galli G, Bosisio E. Determination of aloesin and aloeresin A for the detection of aloe in beverages. J Agric Food Chem. 2007;55:3363–7.PubMed
70.
Rout S, Mahapatra RK. In silico study of M18 aspartyl amino peptidase (M18AAP) of Plasmodium vivax as an antimalarial drug target. Bioorg Med Chem. 2019;27:2553–71.PubMed
71.
Ríos-Soto L, Avitia-Domínguez C, Sierra-Campos E, Valdez-Solana M, Cisneros-Martínez J, Palacio-Gastellum MG, et al. Virtual screening, molecular dynamics and ADME-Tox tools for finding potential inhibitors of phosphoglycerate mutase 1 from Plasmodium falciparum. Curr Top Med Chem. 2018;18:1610–7.PubMed
72.
Mysinger MM, Carchia M, Irwin JJ, Shoichet BK. Directory of useful decoys, enhanced (DUD-E). Better ligands and decoys for better benchmarking. J Med Chem. 2012;55:6582–94.PubMedPubMedCentral
73.
74.
75.
76.
Musyoka T, Bishop ÖT. South African Abietane diterpenoids and their analogs as potential antimalarials: novel insights from hybrid computational approaches. Molecules. 2019;24:4036.PubMedCentral
77.
Roche O, Schneider P, Zuegge J, Guba W, Kansy M, Alanine A, et al. Development of a virtual screening method for identification of “frequent hitters” in compound libraries. J Med Chem. 2002;45:137–42.PubMed
78.
Eloff JN, Jäger AK, Van Staden J. The stability and the relationship between anti-inflammatory activity and antibacterial properties of southern African Combretum species. S Afr J Sci. 2001;97:291–3.
79.
80.
van Heerden FR, Viljoen AM, van Wyk B-E. 6′-O-Coumaroylaloesin from Aloe castanea—a taxonomic marker for Aloe section Anguialoe. Phytochemistry. 2000;55:117–20.PubMed
81.
Asres K, Girma B, Bisrat D. Antimalarial evaluation of the leaf latex of Aloe citrina and its major constituent. Anc Sci Life. 2015;34:142.PubMedPubMedCentral
82.
Zhao H, Caflisch A. Molecular dynamics in drug design. Eur J Med Chem. 2015;91:4–14.PubMed
83.
84.
Malabanan MM, Amyes TL, Richard JP. A role for flexible loops in enzyme catalysis. Curr Opin Struct Biol. 2010;20:702–10.PubMedPubMedCentral
85.
Yu H, Yan Y, Zhang C, Dalby PA. Two strategies to engineer flexible loops for improved enzyme thermostability. Sci Rep. 2017;7:41212.PubMedPubMedCentral
86.
Hasan MA, Mazumder MHH, Chowdhury AS, Datta A, Khan MA. Molecular-docking study of malaria drug target enzyme transketolase in Plasmodium falciparum 3D7 portends the novel approach to its treatment. Source Code Biol Med. 2015;10:7.PubMedPubMedCentral
87.
Fitch CA, Platzer G, Okon M, Garcia-Moreno EB, McIntosh LP. Arginine: Its pK a value revisited. Protein Sci. 2015;24:752–61.PubMedPubMedCentral
Metadata
Title
Characterisation of plasmodial transketolases and identification of potential inhibitors: an in silico study
Authors
Rita Afriyie Boateng
Özlem Tastan Bishop
Thommas Mutemi Musyoka
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Malaria Journal / Issue 1/2020
Electronic ISSN: 1475-2875
DOI
https://doi.org/10.1186/s12936-020-03512-1

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