Structure of the 40S ribosomal subunit of Plasmodium falciparum by homology and de novo modeling

Mwangi, Harrison Ndung'u; Wagacha, Peter Waiganjo; Mathenge, Peterson Gitonga; Sijenyi, Fredrick; Mulaa, Francis

doi:10.1016/j.apsb.2016.10.003

Cited by 5 publications

(13 citation statements)

References 41 publications

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“…Moreover, we could isolate the GltC T99A and GltC P88L variants with enhanced activator function that were described previously (Belitsky and Sonenshein, 1995). Based on a model of the tetramer structure of the CbnR LysR-type regulator from Cupriavidus necator (PDBid: 1lZ1) (Muraoka et al, 2003), we generated a model for a full-length GltC protomer using the SWISS-MODEL server for homology modeling of protein structures (Waterhouse et al, 2018). As shown in Figure 3C, many amino acid exchanges enhancing the activator function of GltC are located between the linker and the effector domain.…”

Section: Resultsmentioning

confidence: 99%

“…Coloring of the GltC monomer model corresponds to that used for illustrating the domain organization of the regulator in (A) . The model was generated using the SWISS-MODEL server for homology modeling of protein structures (Waterhouse et al, 2018) and a model of the tetramer structure of the CbnR LysR-type regulator from Cupriavidus necator (PDBid: 1lZ1) (Muraoka et al, 2003). The overall amino acid sequence identity between GltC and CbnR is 28%.…”

Section: Resultsmentioning

confidence: 99%

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Variants of the Bacillus subtilis LysR-Type Regulator GltC With Altered Activator and Repressor Function

et al. 2019

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The Gram-positive soil bacterium Bacillus subtilis relies on the glutamine synthetase and the glutamate synthase for glutamate biosynthesis from ammonium and 2-oxoglutarate. During growth with the carbon source glucose, the LysR-type transcriptional regulator GltC activates the expression of the gltAB glutamate synthase genes. With excess of intracellular glutamate, the gltAB genes are not transcribed because the glutamate-degrading glutamate dehydrogenases (GDHs) inhibit GltC. Previous in vitro studies revealed that 2-oxoglutarate and glutamate stimulate the activator and repressor function, respectively, of GltC. Here, we have isolated GltC variants with enhanced activator or repressor function. The majority of the GltC variants with enhanced activator function differentially responded to the GDHs and to glutamate. The GltC variants with enhanced repressor function were still capable of activating the PgltA promoter in the absence of a GDH. Using PgltA promoter variants (PgltA∗) that are active independent of GltC, we show that the wild type GltC and the GltC variants with enhanced repressor function inactivate PgltA∗ promoters in the presence of the native GDHs. These findings suggest that GltC may also act as a repressor of the gltAB genes in vivo. We discuss a model combining previous models that were derived from in vivo and in vitro experiments.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Variants of the Bacillus subtilis LysR-Type Regulator GltC With Altered Activator and Repressor Function

et al. 2019

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“…RNA123 was able to predict the secondary and tertiary structure of the three kinetoplastids ribosomal RNA. RNA123 took three steps; Preprocessing, Alignment, and Modeling [ 18 ].…”

Section: Methodsmentioning

confidence: 99%

“…The purpose of molecular modeling is to provide functional insight in biological molecules, not to achieve some arbitrary precision in the atomic coordinates. Therefore, we seek to improve our abilities to construct 3D models for molecules for which we do not yet have experimental atomic-resolution structures and carefully identify the predicted features that yield important insights [ 10 , 18 ].…”

Section: Rna As a Drug Targetmentioning

confidence: 99%

Methods for Identifying Microbial Natural Product Compounds that Target Kinetoplastid RNA Structural Motifs by Homology and De Novo Modeled 18S rRNA

Mwangi

Muge

Wagacha

et al. 2021

IJMS

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The development of novel anti-infectives against Kinetoplastids pathogens targeting proteins is a big problem occasioned by the antigenic variation in these parasites. This is also a global concern due to the zoonosis of these parasites, as they infect both humans and animals. Therefore, we need not only to create novel antibiotics, but also to speed up the development pipeline for these antibiotics. This may be achieved by using novel drug targets for Kinetoplastids drug discovery. In this study, we focused our attention on motifs of rRNA molecules that have been created using homology modeling. The RNA is the most ambiguous biopolymer in the kinetoplatid, which carries many different functions. For instance, tRNAs, rRNAs, and mRNAs are essential for gene expression both in the pro-and eukaryotes. However, all these types of RNAs have sequences with unique 3D structures that are specific for kinetoplastids only and can be used to shut down essential biochemical processes in kinetoplastids only. All these features make RNA very potent targets for antibacterial drug development. Here, we combine in silico methods combined with both computational biology and structure prediction tools to address our hypothesis. In this study, we outline a systematic approach for identifying kinetoplastid rRNA-ligand interactions and, more specifically, techniques that can be used to identify small molecules that target particular RNA. The high-resolution optimized model structures of these kineoplastids were generated using RNA 123, where all the stereochemical conflicts were solved and energies minimized to attain the best biological qualities. The high-resolution optimized model’s structures of these kinetoplastids were generated using RNA 123 where all the stereochemical conflicts were solved and energies minimized to attain the best biological qualities. These models were further analyzed to give their docking assessment reliability. Docking strategies, virtual screening, and fishing approaches successfully recognized novel and myriad macromolecular targets for the myxobacterial natural products with high binding affinities to exploit the unmet therapeutic needs. We demonstrate a sensible exploitation of virtual screening strategies to 18S rRNA using natural products interfaced with classical maximization of their efficacy in phamacognosy strategies that are well established. Integration of these virtual screening strategies in natural products chemistry and biochemistry research will spur the development of potential interventions to these tropical neglected diseases.

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“…Internal evaluation is done to check whether the model satisfied the restraints used in its calculation. It is then evaluated through assessment of the stereochemistry of the model which includes bond angles, dihedral angles, non-bonded atom-atom distances and bonds [11][12][13][14][15].…”

Section: Model Validation -mentioning

confidence: 99%

Virtual Screening and Validation of Potential Lead Compound from the Malaria Box against Plasmodium Falciparum S7 and S19 Proteins

Mulaa¹

2018

OAJPR

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Molecular docking is a computer based tool used in drug design, where predominant binding modes of a ligand with known three dimensional protein structures are predicted. This study addresses the possible ways of coming up with antimalarial drugs using computational chemistry methods. This approach which utilizes virtual screening is more advantageous as it is effective, affordable and less tedious as compared to the normal laboratory experimental biological assays and spectroscopic techniques for characterization of the compounds. Treatment of malaria has become complex due to the high rate of emergence of resistance exhibited by Plasmodium falciparum and mutations resulting from the parasite. To test the reliability of this model for future tests, compounds for this study were sourced from the Malaria Box containing compounds proven to have interesting activities against the malaria causing parasite, P. faliciparum. In the current study, three dimensional structures of twenty compounds fetched from the Malaria Box and of the ribosomal 40S proteins S7 and S19 were generated using structure predicting software. The potential of the selected compounds to dock and bind onto the ribosomal 40S proteins S7 and S19 proteins was accessed by calculating pose complex RMSD as well as its geometric shape complementarity score, approximate interface area, atomic contact energy, the 3d transformation, 3 rotational angles and 3 translational parameters applied on the ligand molecule, to test authenticity of the docking experiments. The compounds that showed best pose were considered active lead compounds. Using this model three out of several compounds from the Malaria Box confirmed the results that were obtained using laboratory experiments as evidenced from the low energy pose of the complex. The objectives of the experiment were accomplished as the Plasmodium falciparum proteins S7 and S19 models were generated, validated and the docked structures of the two proteins with the Research ArticleVolume 2 Issue 2

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Structure of the 40S ribosomal subunit of Plasmodium falciparum by homology and de novo modeling

Cited by 5 publications

References 41 publications

Variants of the Bacillus subtilis LysR-Type Regulator GltC With Altered Activator and Repressor Function

Variants of the Bacillus subtilis LysR-Type Regulator GltC With Altered Activator and Repressor Function

Methods for Identifying Microbial Natural Product Compounds that Target Kinetoplastid RNA Structural Motifs by Homology and De Novo Modeled 18S rRNA

Virtual Screening and Validation of Potential Lead Compound from the Malaria Box against Plasmodium Falciparum S7 and S19 Proteins

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