New drug target identification in Vibrio vulnificus by subtractive genome analysis and their inhibitors through molecular docking and molecular dynamics simulations

Alotaibi, Bader S.; Ajmal, Amar; Hakami, Mohammed Ageeli; Mahmood, Arif; Wadood, Abdul; Hu, Junjie

doi:10.1016/j.heliyon.2023.e17650

Cited by 13 publications

(3 citation statements)

References 36 publications

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“…The preparation module of UCSF Chimera ( https://www.cgl.ucsf.edu/chimera/ ) was used to resolve the missing residues and non-sense mutation was inserted using the mutagenesis tool PyMOL, followed by energy minimization with MMFF94 force field implemented in a molecular operating environment (MOE) ( https://www.chemcomp.com/Products.htm ). The mutation was induced in the structure using the mutagenesis tool implemented in PyMOL ( https://pymol.org/2/ ) as described by Alotaibi et al ( 33 ).…”

Section: Methodsmentioning

confidence: 99%

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Truncated DNM1 variant underlines developmental delay and epileptic encephalopathy

Afsar,

Huang,

Shah

et al. 2023

Front. Pediatr.

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BackgroundDevelopmental and epileptic encephalopathies (DEEs) signify a group of heterogeneous neurodevelopmental disorder associated with early-onset seizures accompanied by developmental delay, hypotonia, mild to severe intellectual disability, and developmental regression. Variants in the DNM1 gene have been associated with autosomal dominant DEE type 31A and autosomal recessive DEE type 31B.MethodsIn the current study, a consanguineous Pakistani family consisting of a proband (IV-2) was clinically evaluated and genetically analyzed manifesting in severe neurodevelopmental phenotypes. WES followed by Sanger sequencing was performed to identify the disease-causing variant. Furthermore, 3D protein modeling and dynamic simulation of wild-type and mutant proteins along with reverse transcriptase (RT)–based mRNA expression were checked using standard methods.ResultsData analysis of WES revealed a novel homozygous non-sense variant (c.1402G>T; p. Glu468*) in exon 11 of the DNM1 gene that was predicted as pathogenic class I. Variants in the DNM1 gene have been associated with DEE types 31A and B. Different bioinformatics prediction tools and American College of Medical Genetics guidelines were used to verify the identified variant. Sanger sequencing was used to validate the disease-causing variant. Our approach validated the pathogenesis of the variant as a cause of heterogeneous neurodevelopmental disorders. In addition, 3D protein modeling showed that the mutant protein would lose most of the amino acids and might not perform the proper function if the surveillance non-sense-mediated decay mechanism was skipped. Molecular dynamics analysis showed varied trajectories of wild-type and mutant DNM1 proteins in terms of root mean square deviation, root mean square fluctuation and radius of gyration. Similarly, RT-qPCR revealed a substantial reduction of the DNM1 gene in the index patient.ConclusionOur finding further confirms the association of homozygous, loss-of-function variants in DNM1 associated with DEE type 31B. The study expands the genotypic and phenotypic spectrum of pathogenic DNM1 variants related to DNM1-associated pathogenesis.

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Section: Methodsmentioning

confidence: 99%

“…The temperature was kept constant at 300 K using the Langevin thermostat. Moreover, a 200 ns molecular dynamics (MD) was run after equilibration ( 33 ). For electrostatic interactions, the particle Mesh Ewald (PME) method was used.…”

Section: Methodsmentioning

confidence: 99%

Truncated DNM1 variant underlines developmental delay and epileptic encephalopathy

Afsar,

Huang,

Shah

et al. 2023

Front. Pediatr.

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“…The model that revealed high accuracy and MCC values was used for the virtual screening of the 20,000 drug-like compounds of the ZINC database [47]. The hits obtained from the RF model were docked against the KRAS G12D mutant.…”

Section: Virtual Screening and Molecular Docking Studymentioning

confidence: 99%

In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches

Ajmal,

Danial,

Zulfat

et al. 2024

Pharmaceuticals

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Single-point mutations in the Kirsten rat sarcoma (KRAS) viral proto-oncogene are the most common cause of human cancer. In humans, oncogenic KRAS mutations are responsible for about 30% of lung, pancreatic, and colon cancers. One of the predominant mutant KRAS G12D variants is responsible for pancreatic cancer and is an attractive drug target. At the time of writing, no Food and Drug Administration (FDA) approved drugs are available for the KRAS G12D mutant. So, there is a need to develop an effective drug for KRAS G12D. The process of finding new drugs is expensive and time-consuming. On the other hand, in silico drug designing methodologies are cost-effective and less time-consuming. Herein, we employed machine learning algorithms such as K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF) for the identification of new inhibitors against the KRAS G12D mutant. A total of 82 hits were predicted as active against the KRAS G12D mutant. The active hits were docked into the active site of the KRAS G12D mutant. Furthermore, to evaluate the stability of the compounds with a good docking score, the top two complexes and the standard complex (MRTX-1133) were subjected to 200 ns MD simulation. The top two hits revealed high stability as compared to the standard compound. The binding energy of the top two hits was good as compared to the standard compound. Our identified hits have the potential to inhibit the KRAS G12D mutation and can help combat cancer. To the best of our knowledge, this is the first study in which machine-learning-based virtual screening, molecular docking, and molecular dynamics simulation were carried out for the identification of new promising inhibitors for the KRAS G12D mutant.

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Experimental and computational insights of Albizia amara phytoconstituents targeting anthranilate phosphoribosyltransferase from Malassezia globosa

Subhashini,

Jebastin,

Khasamwala

et al. 2024

Acta Tropica

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New drug target identification in Vibrio vulnificus by subtractive genome analysis and their inhibitors through molecular docking and molecular dynamics simulations

Cited by 13 publications

References 36 publications

Truncated DNM1 variant underlines developmental delay and epileptic encephalopathy

Truncated DNM1 variant underlines developmental delay and epileptic encephalopathy

In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches

Experimental and computational insights of Albizia amara phytoconstituents targeting anthranilate phosphoribosyltransferase from Malassezia globosa

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