In silico 3-D structure prediction and molecular docking studies of inosine monophosphate dehydrogenase from Plasmodium falciparum

Raza, Muslim; Khan, Zahid; Ahmad, Aftab; Raza, Saleem; Khan, Abad; Mohammadzai, Imdad Ullah; Zada, Shah

doi:10.1016/j.compbiolchem.2017.09.002

Cited by 10 publications

(16 citation statements)

References 32 publications

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“…The published in silico models were mostly applied for lead identification/optimization (13 articles) of the known Plasmodium targets (13 targets). Most articles are specific for P. falciparum targets (Campbell et al, 2014;Kumari et al, 2016;LaMonte et al, 2017;Lhouvum et al, 2013;MacDonald and Boyd, 2015;Raza et al, 2017;Ren et al, 2016;Sharma et al, 2016); 3 articles involved target for P. vivax (MacDonald et al, 2015;Rout et al, 2016;Bouillon et al, 2013) and 1 article involved target for liver stage of Plasmodium (Sullivan et al, 2015). Five articles were applied in silico modeling for target identification/validation (Lhouvum et al, 2013;Mehra et al, 2015;Paul et al, 2015;Rout et al, 2015;Pandey et al, 2014).…”

Section: Study Selectionmentioning

confidence: 99%

“…Five articles were applied in silico modeling for target identification/validation (Lhouvum et al, 2013;Mehra et al, 2015;Paul et al, 2015;Rout et al, 2015;Pandey et al, 2014). Both structure-based (Bouillon et al, 2013;LaMonte et al, 2017;MacDonald and Boyd, 2015;Raza et al, 2017;Ren et al, 2016;Rout and Mahapatra, 2016;Sullivan et al, 2015) and ligandbased (Villalobos et al, 2013;Kumari et al, 2016;Ren et al, 2016;Sharma et al, 2016) approaches were applied to obtain lead antimalarial candidates. Two articles also assessed ADMET properties (Ren et al, 2016;Rout and Mahapatra, 2016).…”

Section: Study Selectionmentioning

confidence: 99%

“…Inosine monophosphate dehydrogenase (IMPDH) is an important enzyme in the purine biosynthesis of P. falciparum. A 3D homology model for this parasite enzyme was made using human IMPDH (PDB code 1NF7) as a template (Raza et al, 2017). The in silico combinatorial library of 1,347 ribavirin derivatives was designed and virtually screened.…”

Section: Lead Identification/optimizationmentioning

confidence: 99%

“…Lead identification/optimization involved identification of potent antimalarial candidate molecules which are inhibitors of known specific Plasmodium targets (13 targets) encoded by the malaria parasite genome. These included: inosine monophosphate dehydrogenase (IMPDH) (Raza et al, 2017), proteasome (LaMonte et al, 2017), lipid kinase PI(4)K (phosphatidylinositol-4-OH kinase) (Ren et al, 2016), heat shock regulated A (HrA or DegP) (Sharma et al, 2016), P. falciparum M18 (Kumari et al, 2016), P. falciparum aspartyl aminopeptidase (PfM18AAP) (Kumari et al, 2016), leucine amino peptidase (M17 LAP) (Rout and Mahapatra, 2016), P. falciparum glycogen synthase kinase-3 (PfGSK-3), P. falciparum CTP synthetase (PfCTPS), choline kinase (PfCK), and glutathione S-transferase (PfGST) (Verma et al, 2015), Plasmodium peptidyl-prolyl cis/trans isomerase (MacDonald and Boyd, 2015), Plasmodium phosphatases, cytochrome bc1 (Jimenez et al, 2013), and P. vivax subtilin-like serine protease (PvSUB1) (Bouillon et al, 2013). Application of the modeling for target identification/validation included Nmyristoyltransferase (NMT) (Paul et al, 2015), Plasmodium phosphatases (Campbell et al, 2014;Pandey et al, 2014), and PFI1625c metalloprotease (Lhouvum et al, 2013).…”

Section: Study Characteristicsmentioning

confidence: 99%

“…For antimalarial protein targets, the databases applied included PlasmoDB 9.2 (Lhouvum et al, 2013;Pandey et al, 2014;Rout et al, 2015;Sharma et al, 2016), PFAM (Pandey et al, 2014;Rout et al, 2015), CDD [29], ZINC (Lhouvum et al, 2013;Pandey et al, 2014), and InterPro (Campbell et al, 2014;Rout et al, 2015). Protein structures were downloaded from these databases and validated using RAMPAGE (Paul et al, 2015;Sharma et al, 2016), PROCHECK (Bouillon et al, 2013;Campbell et al, 2014;Kruggel and Lemcke, 2009;Lhouvum et al, 2013;Mehra et al, 2015;Paul et al, 2015;Raza et al, 2017;Rout et al, 2015;Rout and Mahapatra, 2016), Verify-3D (Campbell et al, 2014;Lhouvum et al, 2013;Rout et al, 2015;Rout and Mahapatra, 2016;Sharma et al, 2016), ERRAT (Campbell et al, 2014;Lhouvum et al, 2013;Rout et al, 2015;Rout and Mahapatra, 2016;Sharma et al, 2016), CHIMERA (Paul et al, 2015), and PROSA (Rout et al, 2015;Rout and Mahapatra, 2016;Sharma et al, 2016;Verma et al, 2015). Stability check was performed using Gromacs (Lhouvum et...…”

Section: Study Characteristicsmentioning

confidence: 99%

See 4 more Smart Citations

A systematic review: Application of in silico models for antimalarial drug discovery

Cheoymang¹,

Na‐Bangchang²

2018

Afr. J. Pharm. Pharmacol.

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Malaria remains the global public health problem due to the reemergence of drug resistance. There is an urgent need for development of new antimalarial candidates which are effective against resistant malaria parasite. This systematic review evaluates the published research studies that applied in silico modeling during the discovery process of antimalarial drugs. Literature searches were conducted using PubMed, EBSCO, EMBASE, and Web of Science to identify the relevant articles using the search terms "Malaria" "In silico model", "Computer-based drug design", "Antimalarial drug", and "Drug discovery". Only the articles published in English between 2008 and May 2015 were included in the analysis. A total of 17 relevant articles met the search criteria. Most articles are studies specific to Plasmodium falciparum targets; 3 and 1 articles, respectively involve target for P. vivax and liver stage of Plasmodium. Both structure-based and ligand-based approaches were applied to obtain lead antimalarial candidates. Two articles also assessed absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Confirmation of activity of the candidate leads by in vitro and/or in vivo assays were reported in some studies. Homology modelling, molecular docking, 2D-or 3D-QSAR and pharmacophore modeling are commonly applied methods. One study used de novo synthesis for lead identification and one study applied phylogenetic analysis for target identification/validation.

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Section: Study Selectionmentioning

confidence: 99%

Section: Study Selectionmentioning

confidence: 99%

Section: Lead Identification/optimizationmentioning

confidence: 99%

Section: Study Characteristicsmentioning

confidence: 99%

Section: Study Characteristicsmentioning

confidence: 99%

See 3 more Smart Citations

A systematic review: Application of in silico models for antimalarial drug discovery

Cheoymang¹,

Na‐Bangchang²

2018

Afr. J. Pharm. Pharmacol.

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Engineering an efficient mutant of Eupenicillium terrenum fructosyl peptide oxidase for the specific determination of hemoglobin A1c

Shahbazmohammadi

Sardari

Lari

et al. 2019

Appl Microbiol Biotechnol

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Fructosyl peptide oxidase (FPOX, EC 1.5.3) belongs to the family of oxidoreductases, which is used as a diagnostic enzyme for diabetes mellitus. FPOX has activities toward Fru-ValHis and Fru-Lys as model compounds for hemoglobin A1c (HbA1c) and glycated albumin, respectively. However, when the concentration of HbA1c is measured, the activity toward Fru-Lys will cause interference. In this study, we focused on the substrate specificity engineering of FPOX from Eupenicillium terrenum through computational and experimental methods with characteristics more suitable for HbA1c measurement in the blood. Based on structural knowledge of E. terrenum FPOX (PDB ID 4RSL) and molecular modeling results, residues His-377, Arg-62, Lys-380, and Tyr-261 were selected as mutagenesis sites. The best mutant with lower binding energy, stronger hydrophobic interactions, and more hydrogen bonds with Fru-ValHis and higher binding energy toward Fru-Lys was selected for experimental studies. To investigate the conformational changes in FPOX due to the mutation, molecular dynamics simulation was also performed. The genes encoding of native and engineered variants were cloned into pET-22b(+) and produced in Escherichia coli strain BL21 (DE3). The expressed recombinant enzymes were purified and their kinetic properties were studied. Substitution of Tyr261 with Trp resulted in a mutant enzyme with improved specificity for Fru-ValHis, a model compound of HbA1c. The specific activity of mutant FPOX increased by 5.1-fold to 145.2 ± 3.2 U/mg for Fru-ValHis and decreased by 13.7-fold to 1.3 U/mg ± 0.9 for Fru-Lys compared to the native variant. Kinetics analysis indicated that Tyr261Trp FPOX mutant had 11.7-fold increase in K cat /K m for Fru-ValHis compared to the wild-type enzyme, while the K cat /K m for Fru-Lys diminished by 22.4-fold. In summary, our computational and experimental results suggested that the engineered FPOX is a good candidate to efficient determination of HbA1c.

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In silico structure prediction and inhibition mechanism studies of AtHDA14 as revealed by homology modeling, docking, molecular dynamics simulation

Zhao

Wang

Nie

et al. 2018

Computational Biology and Chemistry

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In silico 3-D structure prediction and molecular docking studies of inosine monophosphate dehydrogenase from Plasmodium falciparum

Cited by 10 publications

References 32 publications

A systematic review: Application of in silico models for antimalarial drug discovery

A systematic review: Application of in silico models for antimalarial drug discovery

Engineering an efficient mutant of Eupenicillium terrenum fructosyl peptide oxidase for the specific determination of hemoglobin A1c

In silico structure prediction and inhibition mechanism studies of AtHDA14 as revealed by homology modeling, docking, molecular dynamics simulation

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