Skip to content

Advertisement

  • Research note
  • Open Access

Homology modelling, molecular docking, and molecular dynamics simulations reveal the inhibition of Leishmania donovani dihydrofolate reductase-thymidylate synthase enzyme by Withaferin-A

BMC Research Notes201811:246

https://doi.org/10.1186/s13104-018-3354-1

  • Received: 13 December 2017
  • Accepted: 11 April 2018
  • Published:

Abstract

Objective

Present in silico study was carried out to explore the mode of inhibition of Leishmania donovani dihydrofolate reductase-thymidylate synthase (Ld DHFR-TS) enzyme by Withaferin-A, a withanolide isolated from Withania somnifera. Withaferin-A (WA) is known for its profound multifaceted properties, but its antileishmanial activity is not well understood. The parasite’s DHFR-TS enzyme is diverse from its mammalian host and could be a potential drug target in parasites.

Results

A 3D model of Ld DHFR-TS enzyme was built and verified using Ramachandran plot and SAVES tools. The protein was docked with WA-the ligand, methotrexate (MTX)-competitive inhibitor of DHFR, and dihydrofolic acid (DHFA)-substrate for DHFR-TS. Molecular docking studies reveal that WA competes for active sites of both Hu DHFR and TS enzymes whereas it binds to a site other than active site in Ld DHFR-TS. Moreover, Lys 173 residue of DHFR-TS forms a H-bond with WA and has higher binding affinity to Ld DHFR-TS than Hu DHFR and Hu TS. The MD simulations confirmed the H-bonding interactions were stable. The binding energies of WA with Ld DHFR-TS were calculated using MM-PBSA. Homology modelling, molecular docking and MD simulations of Ld DHFR-TS revealed that WA could be a potential anti-leishmanial drug.

Keywords

  • Leishmania donovani
  • DHFR-TS
  • Withania somnifera
  • Ashwagandha
  • Molecular docking
  • Withaferin-A
  • Methotrexate
  • Dihydrofolicacid
  • Antileishmanial drug

Introduction

Withaferin-A (WA) is among the most effective withanolide isolated from W. somnifera and has various effects like anti-bacterial, anti-inflammatory, anti-proliferative and potent anti-cancer properties [14]. Recently we demonstrated in vitro, that withanolides show potent anti-leishmanial activity [5] and a drastic reduction in parasite load in vivo [6].

Availability of complete genome sequence of Leishmania opens new windows to identify a potential drug target [7]. Many enzymes of Leishmania are extensively explored as drug targets as they are diverse from mammalian hosts [8, 9]. Trypanosomatids including Leishmania are pteridine auxotrophs and require an exogenous source of folate/biopterin [10, 11]. Folate and biopterin are served as cofactors only in their fully reduced forms, H4-folate and H4-biopterin, respectively (Fig. 1a). In Leishmania DHFR along with TS forms DHFR-TS complex and occurs as a bifunctional enzyme [1217]. However, as de novo biopterin synthetic pathway is absent, DHFR-TS shows no activity with biopterin [1821]. Parasite obtains folates from the host and uses its DHFR-TS and PTR1 enzymes to reduce folates to active H4 forms [2224].
Fig. 1
Fig. 1

Folate biosynthesis pathway, homology modelling and molecular docking: a DHFR-TS synthesizes dTMP while converting methylene THF to DHF which is converted back to THF by DHFR-TS. PTR1 converts H2 biopterin to H4 biopterin. PTR1 can reduce both pterins and folates. WA inhibits both PTR1 and DHFR-TS enzymes. b Superimposed image of the template T. cruzi DHFR-TS chain A (PDB ID: 3INV) shown in blue and modeled Ld DHFR-TS shown in green. c Substrate DHFA (red) binds to two active sites of Ld DHFR-TS where an electrostatic channel is formed and substrate channeling between both the active sites is observed. Competitive inhibitor MTX (blue) competes with DHFA (red) and binds to two active sites of Ld DHFR-TS. Inhibitor WA (yellow) is binding to Ld DHFR-TS enzyme by blocking the electrostatic channel. d Substrate DHFA (red), Competitive inhibitor MTX (blue) and inhibitor WA (yellow) binding to Hu DHFR enzyme. e Substrate dUMP (red), inhibitors MTX (blue) and WA (yellow) binding to Hu TS enzyme

Hence, folate biosynthesis enzymes can be potential drug targets and molecules which inhibit any enzyme of these pathways can be a safe antileishmanial drug. Our in silico study shows that WA inhibits multiple enzymes in folate biosynthesis pathway of Leishmania parasites.

Main text

Methods

Homology modeling

Amino acid sequences of Ld DHFR-TS, (accession no. CBZ31672.1, Homo sapiens or Human DHFR (Hu DHFR) (AAH71996.1) and Homo sapiens or Human TS (Hu TS) (NP_001062.1) were obtained from NCBI (http://www.ncbi.nlm.nih.gov). The similarity in sequences between host and parasite enzymes was identified using Clustal omega (https://www.ebi.ac.uk/Tools/msa/clustalo/). Template for structural modeling was identified using PDB-BLAST. Protein model was developed using SWISS-Model (https://swissmodel.expasy.org/) [2528] and verified with Ramachandran plot, PROCHECK analysis, global model quality estimation (GMQE) score and qualitative model energy analysis (QMEAN) values [29].

Enzyme-ligand docking

The structures of WA, MTX and DHFA (PubChem CID 265237, 126941, 98792, respectively) were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/) (Additional file 1: Fig. S1). Open Babel (http://openbabel.org/wiki/Main_Page) was used to obtain. pdbqt files. Molecular docking studies were carried out in Auto Dock Vina [30]. Initially, blind docking, was performed, followed by docking within restricted search space around the probable binding sites. Docking conformations were selected based on binding affinity. Pymol (https://www.pymol.org/) was used for visualization and graphical representations.

Drug-likeness prediction

Drug-likeness of WA [31, 32] was calculated using molsoft server (http://molsoft.com/mprop/). A drug-likeness plot and score were obtained. Swiss target was used to predict drug target class for Withaferin A. The server, using a combination of 2D and 3D similarity measures, compares the query molecule to a library of 280,000 compounds active on more than 2000 targets of five different organisms [33].

Molecular dynamic simulation

MD simulation of Ld DHFR-TS, Hu DHFR and Hu TS, and their WA complexes were performed in Gromacs 5.0. (http://www.gromacs.org/) [34]. The topological parameter of the ligand was obtained from ATB server (https://atb.uq.edu.au/) [35]. Initially, protein or its complex was kept in a cubic box filled with water using SPC/E water models. The system was energy minimized using GROMOS54a7 force field [36] and equilibrated at 300 K using V-rescale for 200 ps as NVT ensemble followed by equilibration at 1 atm pressure using Parrinello–Rahman algorithm as NPT ensemble for 200 ps. The equilibrated conformation was further extended for production simulation for 25 ns. LINCS algorithm was applied for bond constraints with distance cut-off using Verlet during simulation. Root mean square deviations of atomic coordinates during the simulation from their respective initial coordinates were calculated using the gmx_rms tool in Gromacs and binding energies were calculated using MM-PBSA [37].

Results

Sequence alignment and homology modeling

The sequence similarity between Hu DHFR and Ld DHFR-TS was found to be 25.13%, and between Hu TS and Ld DHFR-TS, it was 54.63% suggesting that Ld DHFR-TS could be a valid drug target (Additional file 1: Figs. S2, S3). The amino acid sequence of Ld DHFR-TS was blasted against PDB-BLAST database for identifying an appropriate template for homology modeling. T.cruzi DHFR-TS showed 67.32% identity with the target protein and was selected as a template (Additional file 1: Fig. S4). Quality of the model generated by Swiss-model was verified using different tools (Fig. 1b) (Additional file 1: Table S1). The selected model showed 0.2% of residues in disallowed regions of Ramachandran plot (Additional file 1: Fig. S5, Table S2) with GMQE score of 0.82 and QMEAN score of − 2.25 (Additional file 1: Fig. S6).

The generated model is a homo-dimer protein of α + β class. The protein consists of 4β-sheets, 3βαβ units, 5β-hairpins, 19β-strands, 21α-helices (Additional file 1: Fig. S7). Similar numbers of secondary structural elements were found in T. cruzi DHFR-TS and RMSD between the template and generated model was calculated to be 0.625 Å.

Drug-likeness of Withaferin A

A compound to be considered as a drug should have ≤ 5 H-bond donors (HBD), ≤ 10 H-bond acceptors (HBA), molecular weight (MW) ≤ 500 Daltons, octanol–water partition coefficient (Log P) value between − 0.4 to + 5.6, and polar surface area (PSA) ≤ 140 Ǻ2 [38]. WA has 2HBDs, 6HBAs, MW of 470.27, Log P of 3.21, and PSA of 75.66 A2. The drug-likeness model score was 0.36 (Additional file 1: Table S3). Further, the frequency of drug target class as predicted by Swiss target prediction for WA is enzymes (40%) and kinases (33%).

Molecular docking studies

To know the active site of Ld DHFR-TS, it was first docked with its substrate DHFA and found that it has two active sites, one in DHFR and other in TS domain. TS active site is located 40 Å away from DHFR active site [3840]. Asp 52, Arg 97 and Thr 180 of DHFR domain form H-bonds with DHFA and binding energy is − 29.3 kJ/mol. Arg 283, His 401, Gln 421, and Asn 433 of TS domain form H-bonds with DHFA and binding energy is − 31.8 kJ/mol.

MTX is a known competitive inhibitor of DHFR, hence Ld DHFR-TS was also docked with MTX. The results show that MTX binds at active sites (Fig. 1c). Ser 86 of DHFR domain forms H-bond with MTX and binding energy is − 33.1 kJ/mol. Arg 283, Glu 292, His 401, Gln 421 and Asn 433 of TS domain form H-bonds with MTX and binding energy is − 31.8 kJ/mol. The Binding site for MTX was compared with a 3D crystal structure of bifunctional Tc DHFR-TS in complex with MTX (3CL9) by superimposing on Ld DHFR-TS docked with MTX and RMSD of the ligand was found to be 0.625 Å. Likewise, crystal structure of mouse TS in ternary complex with N(4)-hydroxy-2′-deoxycytidine-5′-monophosphate and cofactor product, dihydrofolate (4EZ8), crystal structure of Hu TS, ternary complex with dUMP and tomudex (1i00) and Hu TS in complex with dUMP and MTX (5 × 66) were also used for superimposing and confirming the respective positions of ligands. RMSD values were 0.768, 0.806 and 0.669 Å respectively. Further, Ld DHFR-TS was docked with WA and Lys 173 forms an H-bond with WA. The binding energy of WA is − 42.7 kJ/mol and it binds in between both the active sites. It blocks the electrostatic channel of the enzyme (Fig. 1c).

Crystal structure of Hu DHFR (4m6k) was docked with WA and was superimposed with Hu DHFR ternary crystal complex of MTX and NADPH (1u72) and crystal structure of Hu DHFR complex of NADP+ and folate (4m6k). The results showed all three ligands viz. WA, DHFA, and MTX are binding in the same pocket. The ligand WA also competes for the active site and might be acting as a competitive inhibitor. The binding energy of WA is − 41.4 kJ/mol (Fig. 1d).

Crystal structure of Hu TS (1hzw) was docked with WA and later superimposed with Hu TS complex of dUMP and MTX (5x66). We observed that WA is binding at the same site like MTX. The residues Phe 80, His 196, Leu 221 and Asn 226 were forming H-bonds with WA and binding energy of WA was − 39.8 kJ/mol. The ligand WA was again competing for the active site and might be acting as a competitive inhibitor (Fig. 1e). Lys 173 forms an H-bond with WA. No H-bonding with WA was observed in Hu DHFR and Phe 80, His 196, Leu 221 and Asn 226 form H-bonds with WA in Hu TS. Although, WA is not binding in the active site of Ld DHFR-TS, it binds to human enzymes due to differences in the interacting residues.

The docking results of Hu DHFR and TS with WA suggest that WA competes for substrate binding sites of both human enzymes and act as competitive inhibitor. In case of Ld DHFR-TS, WA act as an uncompetitive inhibitor. The binding energy of Ld DHFR-TS with WA is higher than Hu DHFR and TS. Moreover, WA could be a better drug than MTX because of its high binding energy.

Molecular dynamic simulations of enzyme-inhibitor complexes

To characterize the stabilizing interactions and to evaluate binding energies of WA with Ld DHFR-TS, Hu DHFR and Hu TS, MD simulation of proteins and protein-WA complexes were carried out. The analysis of root mean square deviations (RMSD) showed all proteins attained almost stable conformations (Fig. 2a–c) with comparable RMSD values. Addition of WA did not show much change in RMSD of Hu DHFR whereas RMSD of Ld DHFR-TS slightly increased. RMSD of ligand alone was around 0.15 nm in all proteins suggesting that bound conformation was stable. Further, root mean square fluctuations (RMSF) of individual residues were calculated by considering their Cα atoms as a reference (Fig. 2d–f). RMSF of β5-loop in DHFR domain and β1′ and β4′ loops in TS domain were found to increase slightly in the ligand-bound state of Ld DHFR-TS. The RMSF of β4 and β6 loops of DHFR domain reduced. In WA bound Hu DHFR, the fluctuations around β2, β3, and β6 loops reduced. In case of WA bound Hu TS protein, RMSF of β1 loop reduced whereas β3 increased. In all three proteins, changes in fluctuations were observed largely at sites away from ligand binding sites. Moreover, during binding of WA with Ld DHFR-TS, it was observed that WA formed H-bonding interactions with a backbone of F483 and side chains of Arg275, Asn199, and Asn231. Similarly, H-bonding interactions were identified between WA and backbone of Gly7 and side chain of Gln48 in Hu DHFR. WA formed H-bonding interactions with Arg163 and I1e 78 of Hu TS.
Fig. 2
Fig. 2

Molecular dynamics simulation: root mean square deviations (RMSD) of the proteins Ld DHFR-TS (black), Hu DHFR (red) and Hu TS (blue) a in the absence and b in the presence of WA. c Presents the RMSD of WA bound in different proteins. Root mean square fluctuations (RMSF) of Cα atoms of the residues of proteins: d Ld DHFR-TS, e Hu DHFR and f Hu TS in the absence and the presence of WA. The color codes are presented in the labels

For further quantitative binding, energies of ligand were calculated by MM-PBSA using the last 10 ns of simulation data where RMSD of proteins were found to be more stable (Table 1). The analysis indicates that binding affinity of WA is more towards Ld DHFR-TS than Hu DHFR or Hu TS.
Table 1

Binding energy contributions of different interactions calculated using MM-PBSA

Types of energy (kJ/mol)

Ld DHFR-TS

Hu DHFR (kJ/mol)

Hu TS

Van der Waal energy

− 240.828 ± 14.111

− 152.257 ± 20.412

− 130.454 ± 11.349

Electrostatic energy

− 29.298 ± 9.846

− 24.299 ± 13.315

− 49.324 ± 14.361

Polar solvation energy

161.597 ± 20.010

95.665 ± 23.352

122.969 ± 30.393

Non-polar solvation energy

− 23.375 ± 1.019

− 16.934 ± 2.120

− 15.405 ± 2.536

Binding energy

− 131.904 ± 15.686

− 97.826 ± 24.200

− 72.214 ± 18.570

Discussion

Interestingly, Leishmania dhfrts− mutants are unable to survive in mammalian host [41]. Deletion of PTR1 gene is lethal in promastigotes, indicating an essential role for unconjugated pteridines [2023, 42]. PTR1 expression provides a potential ‘metabolic by-pass’ of DHFR-TS inhibition and allows a partial or complete reversal of anti-pteridine inhibition in the promastigote stage of parasites [20, 21]. PTR1 activity in L. major promastigotes is lower than in L. donovani and L. mexicana. L. major is more sensitive to MTX suggesting the role of PTR1 as a metabolic-bypass in L. donovani and L. mexicana [18, 19]. 3D structures of DHFR-TS and PTR1 of parasite and Hu DHFR have provided a strong base to design new inhibitors which are selective for parasite alone [43, 44].

Recently, we reported that WA inhibits Ld PTR1 enzyme activity and molecular docking studies of WA showed high binding affinity with PTR1. Enzyme assay with purified PTR-1 revealed that WA inhibits enzyme activity through uncompetitive mode [45]. The present molecular docking study reveals that the binding energy of WA with Ld DHFR-TS is higher than Hu DHFR, Hu TS enzymes and WA inhibits Ld DHFR-TS same as the PTR-1 enzyme. Thus it could be concluded that binding affinity of WA with multiple enzymes (DHFR-TS and PTR1) of folate biosynthesis pathway of parasites could make WA an effective anti-leishmanial drug.

Limitation

Due to the lack of purified DHFR-TS enzyme, the current study could not include enzyme assay. However, enzyme assayed from parasite lysate with WA has shown the inhibition activity reported earlier [45].

Abbreviations

2D: 

two dimensional

3D: 

three dimensional

Å: 

Angstrom

ATB: 

automated topology builder

atm: 

atmosphere

DHFA: 

dihydrofolic acid

GMQE: 

global model quality estimation

HBA: 

hydrogen bond acceptors

HBD: 

hydrogen bond donors

Hu DHFR: 

human dihydrofolate reductase

Hu TS: 

human thymidylate synthase

K: 

Kelvin

Ld DHFR-TS: 

Leishmania donovani dihydrofolate reductase-thymidylate synthase

LINCS: 

LINear constraint solver

Log P: 

octanol–water partition coefficient

MDS: 

molecular dynamic simulations

MM-PBSA: 

molecular mechanics-Poisson–Boltzmann surface area

MTX: 

methotrexate

MW: 

molecular weight

nm: 

nano meters

ns: 

nano seconds

NCBI: 

National Center for Biotechnology Information

NPT ensemble: 

isothermal (constant temperature T)-isobaric (constant pressure P) ensemble

NVT ensemble: 

number of particles (N), absolute temperature (T) and volume (V) ensemble

PDB-BLAST: 

Protein Data Bank-Basic Local Alignment Search Tool

ps: 

pico seconds

PSA: 

polar surface area

PTR: 

pteridine reductase

QMEAN: 

qualitative model energy analysis

RMSD: 

root mean square deviation

RMSF: 

root mean square fluctuations

SAVES: 

structure analysis and verification server

SPC/E water models: 

extended simple point charge model

Tc DHFR-TS: 

Trypanosoma cruzi dihydrofolate reductase-thymidylate synthase

V-rescale: 

velocity rescale

WA: 

Withaferin A

Declarations

Authors’ contributions

RM and BV conceived the idea and designed the experiments. BV and AKS performed the in silico experiments. BV, AKS, PP, and RM analyzed and interpreted data. PP and RM corrected and edited the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We sincerely acknowledged the bioinformatics facilities DBT-BINC, DST-PURSE, DBT-CREB and BBL fellowship to Mr. Bharadwaja Vadloori from University of Hyderabad.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The PDB file of the Ld DHFR-TS enzyme model (PMDB ID: PM0081119) generated by homology modelling has been deposited in the protein model database repository. (https://bioinformatics.cineca.it/PMDB/user/graph_model_bar.php?page=1&target=6344&inizio=1&fine=509).

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

Not applicable.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Animal Biology, School of Life Sciences, University of Hyderabad, Prof. C.R. Rao Road, Gachibowli, Hyderabad, 500046, India
(2)
Department of Biotechnology and Bioinformatics, University of Hyderabad, Hyderabad, India

References

  1. Kulkarni SK, Dhir A. Withania somnifera: an Indian ginseng. Prog Neuro-Psychopharmacol Biol Psychiatry. 2008;32:1093–105.View ArticleGoogle Scholar
  2. Dar NJ, Hamid A, Ahmad M. Pharmacologic overview of Withania somnifera, the Indian Ginseng. Cell Mol Life Sci. 2015;72:4445–60.View ArticlePubMedGoogle Scholar
  3. Singh G, Sharma PK, Dudhe R, Singh S. Biological activities of Withania somnifera. Ann Biol Res. 2010;1:56–63.Google Scholar
  4. Uddin Q, Samiulla L, Singh VK, Jamil SS. Phytochemical and pharmacological profile of Withania somnifera dunal: a review. J Appl Pharm Sci. 2012;2:170–5.Google Scholar
  5. Chandrasekaran S, Dayakar A, Veronica J, Sundar S, Maurya R. An in vitro study of apoptotic like death in Leishmania donovani promastigotes by withanolides. Parasitol Int. 2013;62:253–61. https://doi.org/10.1016/j.parint.2013.01.007.View ArticlePubMedGoogle Scholar
  6. Chandrasekaran S, Veronica J, Sundar S, Maurya R. Alcoholic fractions F5 and F6 from Withania somnifera leaves show a potent antileishmanial and immunomodulatory activities to control experimental visceral Leishmaniasis. Front Med. 2017;4:55.View ArticleGoogle Scholar
  7. Ivens AC, Peacock CS, Worthey EA, Murphy L, Aggarwal G, Berriman M, et al. The genome of the kinetoplastid parasite, Leishmania major. Science. 2005;309:436–42.View ArticlePubMedPubMed CentralGoogle Scholar
  8. Singh N, Kumar M, Singh RK. Leishmaniasis: current status of available drugs and new potential drug targets. Asian Pac J Trop Med. 2012;5:485–97.View ArticlePubMedGoogle Scholar
  9. Chawla B, Madhubala R. Drug targets in Leishmania. J Parasit Dis. 2010;34:1–13.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Lemley C, Yan S, Dole VS, Madhubala R, Cunningham ML, Beverley SM, et al. The Leishmania donovani LD1 locus gene ORFG encodes a biopterin transporter (BT1). Mol Biochem Parasitol. 1999;104:93–105.View ArticlePubMedGoogle Scholar
  11. Beck JT, Ullman B. Nutritional requirements of wild-type and folate transport-deficient Leishmania donovani for pterins and folates. Mol Biochem Parasitol. 1990;43:221–30.View ArticlePubMedGoogle Scholar
  12. Blakley RLBS. Chemistry and biochemistry of folates. In: Blakley RL, Benkovic SJ, editors. Folates and Pterins. New York: Wiley; 1984.Google Scholar
  13. Wang J, Leblanc E, Chang CF, Papadopoulou B, Bray T, Whiteley JM, et al. Pterin and folate reduction by the Leishmania tarentolae H locus short-chain dehydrogenase/reductase PTR1. Arch Biochem Biophys. 1997;342:197–202.View ArticlePubMedGoogle Scholar
  14. Whiteley JM, Xuong NHVK. Is dihydropteridine reductase an anomalous dihydrofolate reductase, a flavin-like enzyme, or a short-chain dehydrogenase? Adv Exp Med Biol. 1993;338:115–21.View ArticlePubMedGoogle Scholar
  15. Beverley SM, Ellenberger TE, Cordingley JS. Primary structure of the gene encoding the bifunctional dihydrofolate reductase-thymidylate synthase of Leishmania major. Proc Natl Acad Sci USA. 1986;83:2584–8.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Ferone R, Roland S. Dihydrofolate reductase: thymidylate synthase, a bifunctional polypeptide from Crithidia fasciculata. Proc Natl Acad Sci USA. 1980;77:5802–6.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Ivanetich KM, Santi DV. Thymidylate synthase-dihydrofolate reductase in protozoa. Exp Parasitol. 1990;70:367–71.View ArticlePubMedGoogle Scholar
  18. Cruz A, Beverley SM. Gene replacement in parasitic protozoa. Nature. 1990;348:171–3.View ArticlePubMedGoogle Scholar
  19. Scott DA, Coombs GH, Sanderson BE. Folate utilisation by Leishmania species and the identification of intracellular derivatives and folate-metabolising enzymes. Mol Biochem Parasitol. 1987;23:139–49.View ArticlePubMedGoogle Scholar
  20. Kaur K, Coons T, Emmett K, Ullman B. Methotrexate-resistant Leishmania donovani genetically deficient in the folate–methotrexate transporter. J Biol Chem. 1988;263:7020–8.PubMedGoogle Scholar
  21. Thöny B, Auerbach G, Blau N. Tetrahydrobiopterin biosynthesis, regeneration and functions. Biochem J. 2000;347(Pt 1):1–16.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Nare B, Hardy LW, Beverley SM. The roles of pteridine reductase 1 and dihydrofolate reductase-thymidylate synthase in pteridine metabolism in the protozoan parasite Leishmania major. J Biol Chem. 1997;272:13883–91.View ArticlePubMedGoogle Scholar
  23. Bello AR, Nare B, Freedman D, Hardy L, Beverley SM. PTR1: a reductase mediating salvage of oxidized pteridines and methotrexate resistance in the protozoan parasite Leishmania major. Proc Natl Acad Sci USA. 1994;91:11442–6.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Luba J, Nare B, Liang PH, Anderson KS, Beverley SM, Hardy LW. Leishmania major pteridine reductase 1 belongs to the short chain dehydrogenase family: stereochemical and kinetic evidence. Biochemistry. 1998;37:4093–104.View ArticlePubMedGoogle Scholar
  25. Arnold K, Bordoli L, Kopp J, Schwede T. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics. 2006;22:195–201.View ArticlePubMedGoogle Scholar
  26. Guex N, Peitsch MC. SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis. 1997;18:2714–23.View ArticlePubMedGoogle Scholar
  27. Schwede T, Kopp J, Guex N, Peitsch MC. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res. 2003;31:3381–5.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Bordoli L, Kiefer F, Arnold K, Benkert P, Battey J, Schwede T. Protein structure homology modeling using SWISS-MODEL workspace. Nat Protoc. 2008;4:1–13.View ArticleGoogle Scholar
  29. Benkert P, Tosatto SC, Schomburg D. QMEAN: a comprehensive scoring function for model quality assessment. Proteins. 2008;71:261–77.View ArticlePubMedGoogle Scholar
  30. 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.PubMedPubMed CentralGoogle Scholar
  31. Lipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol. 2004;1:337–41.View ArticlePubMedGoogle Scholar
  32. Leeson PD, Springthorpe B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov. 2007;6:881–90.View ArticlePubMedGoogle Scholar
  33. Gfeller D, Grosdidier A, Wirth M, Daina A, Michielin O, Zoete V. SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Nucleic Acids Res. 2014;42:W32–8.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. Gromacs: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1–2:19–25.View ArticleGoogle Scholar
  35. Malde AK, Zuo L, Breeze M, Stroet M, Poger D, Nair PC, et al. An automated force field topology builder (ATB) and repository: version 1.0. J Chem Theory Comput. 2011;7:4026–37.View ArticlePubMedGoogle Scholar
  36. Huang W, Lin Z, Van Gunsteren WF. Validation of the GROMOS 54A7 force field with respect to β-peptide folding. J Chem Theory Comput. 2011;7:1237–43.View ArticlePubMedGoogle Scholar
  37. Genheden S, Ryde U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin Drug Discov. 2015;10:449–61. https://doi.org/10.1517/17460441.2015.1032936.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Grumont R, Washtien WL, Caputtt D, Santi DV. Bifunctional thymidylate synthase-dihydrofolate reductase from Leishmania tropica: sequence homology with the corresponding monofunctional proteins (cDNA cloning/gene structure and evolution/protozoan parasite). Biochemistry. 1986;83:5387–91.Google Scholar
  39. Elcock AH, Potter MJ, Matthews DA, Knighton DR, McCammon JA. Electrostatic channeling in the bifunctional enzyme dihydrofolate reductase-thymidylate synthase. J Mol Biol. 1996;262:370–4.View ArticlePubMedGoogle Scholar
  40. Liang PH, Anderson KS. Substrate channeling and domain–domain interactions in bifunctional thymidylate synthase-dihydrofolate reductase. Biochemistry. 1998;37:12195–205.View ArticlePubMedGoogle Scholar
  41. Veras PST, Brodskyn CI, Balestieri FMP, De Freitas LAR, Ramos APS, Queiroz ARP, et al. A dhfr-ts-Leishmania major knockout mutant cross-protects against Leishmania amazonensis. Mem Inst Oswaldo Cruz. 1999;94:491–6.View ArticlePubMedGoogle Scholar
  42. Cunningham ML, Beverley SM. Pteridine salvage throughout the Leishmania infectious cycle: implications for antifolate chemotherapy. Mol Biochem Parasitol. 2001;113:199–213.View ArticlePubMedGoogle Scholar
  43. Gourley DG, Luba J, Hardy LW, Beverley SM, Hunter WN. Crystallization of recombinant Leishmania major pteridine reductase 1 (PTR1). Acta Crystallogr Sect D: Biol Crystallogr. 1999;55:1608–10.View ArticleGoogle Scholar
  44. Knighton DR, Kan C-C, Howland E, Janson CA, Hostomska Z, Welsh KM, et al. Structure of and kinetic channelling in bifunctional dihydrofolate reductase-thymidylate synthase. Nat Struct Biol. 1994;1:186–94.View ArticlePubMedGoogle Scholar
  45. Chandrasekaran S, Veronica J, Gundampati RK, Sundar S, Maurya R. Exploring the inhibitory activity of Withaferin-A against pteridine reductase-1 of L. major. J Enzyme Inhib Med Chem. 2016;31:1029–37.View ArticlePubMedGoogle Scholar

Copyright

Advertisement