Repurposing of FDA approved drugs and their validation against potential drug targets for <i>Salmonella enterica</i> through molecular dynamics simulation

Kesharwani, Akanksha; Chaurasia, Dheeraj Kumar; Katara, Pramod

doi:10.1080/07391102.2021.1880482

Cited by 8 publications

(4 citation statements)

References 42 publications

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“…The radius of gyration yields quantitative measures such as folding, compactness, and shape of the protein in a biological system along with the MD simulation [ 35 ]. The assessment of protein collapse dynamics for the peramivir-free neuraminidase and the peramivir–(wild-type and R292K) neuraminidase complexes was performed as a function of time, as shown in Figure 5 .…”

Section: Resultsmentioning

confidence: 99%

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Impact of the R292K Mutation on Influenza A (H7N9) Virus Resistance towards Peramivir: A Molecular Dynamics Perspective

2022

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In March 2013, a novel avian influenza A (H7N9) virus emerged in China. By March 2021, it had infected more than 1500 people, raising concerns regarding its epidemic potential. Similar to the highly pathogenic H5N1 virus, the H7N9 virus causes severe pneumonia and acute respiratory distress syndrome in most patients. Moreover, genetic analysis showed that this avian H7N9 virus carries human adaptation markers in the hemagglutinin and polymerase basic 2 (PB2) genes associated with cross-species transmissibility. Clinical studies showed that a single mutation, neuraminidase (NA) R292K (N2 numbering), induces resistance to peramivir in the highly pathogenic H7N9 influenza A viruses. Therefore, to evaluate the risk for human public health and understand the possible source of drug resistance, we assessed the impact of the NA-R292K mutation on avian H7N9 virus resistance towards peramivir using various molecular dynamics approaches. We observed that the single point mutation led to a distorted peramivir orientation in the enzyme active site which, in turn, perturbed the inhibitor’s binding. The R292K mutation induced a decrease in the interaction among neighboring amino acid residues when compared to its wild-type counterpart, as shown by the high degree of fluctuations in the radius of gyration. MM/GBSA calculations revealed that the mutation caused a decrease in the drug binding affinity by 17.28 kcal/mol when compared to the that for the wild-type enzyme. The mutation caused a distortion of hydrogen bond-mediated interactions with peramivir and increased the accessibility of water molecules around the K292 mutated residue.

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Section: Resultsmentioning

confidence: 99%

“…The radius of gyration yields quantitative measures such as folding, compactness, and shape of the protein in a biological system along with the MD simulation [35]. The…”

Section: Radius Of Gyration (Rog)mentioning

confidence: 99%

Impact of the R292K Mutation on Influenza A (H7N9) Virus Resistance towards Peramivir: A Molecular Dynamics Perspective

2022

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“…The process entails docking, subsequently scoring the various poses and applying them to determine and calculate binding free energies [ 112 ]. This docking technique has been pivotal in computational drug discovery and modelling, such as designing HSP90 selective inhibition [ 113 , 114 ]. Molecular docking extends to methods used to decipher the binding mechanism of small receptor ligands (macromolecules) [ 105 , 115 ].…”

Section: Molecular Reactivity Allosteric Dynamics and Allosteric Designmentioning

confidence: 99%

Heat Shock Protein 90 (HSP90) Inhibitors as Anticancer Medicines: A Review on the Computer-Aided Drug Discovery Approaches over the Past Five Years

Magwenyane

Ugbaja

Amoako

et al. 2022

Computational and Mathematical Methods in Medicine

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Cancer is a disease caused by the uncontrolled, abnormal growth of cells in different anatomic sites. In 2018, it was predicted that the worldwide cancer burden would rise to 18.1 million new cases and 9.6 million deaths. Anticancer compounds, often known as chemotherapeutic medicines, have gained much interest in recent cancer research. These medicines work through various biological processes in targeting cells at various stages of the cell’s life cycle. One of the most significant roadblocks to developing anticancer drugs is that traditional chemotherapy affects normal cells and cancer cells, resulting in substantial side effects. Recently, advancements in new drug development methodologies and the prediction of the targeted interatomic and intermolecular ligand interaction sites have been beneficial. This has prompted further research into developing and discovering novel chemical species as preferred therapeutic compounds against specific cancer types. Identifying new drug molecules with high selectivity and specificity for cancer is a prerequisite in the treatment and management of the disease. The overexpression of HSP90 occurs in patients with cancer, and the HSP90 triggers unstable harmful kinase functions, which enhance carcinogenesis. Therefore, the development of potent HSP90 inhibitors with high selectivity and specificity becomes very imperative. The activities of HSP90 as chaperones and cochaperones are complex due to the conformational dynamism, and this could be one of the reasons why no HSP90 drugs have made it beyond the clinical trials. Nevertheless, HSP90 modulations appear to be preferred due to the competitive inhibition of the targeted N-terminal adenosine triphosphate pocket. This study, therefore, presents an overview of the various computational models implored in the development of HSP90 inhibitors as anticancer medicines. We hereby suggest an extensive investigation of advanced computational modelling of the three different domains of HSP90 for potent, effective inhibitor design with minimal off-target effects.

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“…In the earlier 2008, Jedinak et al demonstrated that P. ostreatus have inhibition property against human colon and cancer (Jedinak et al, 2008); later P. ostreatus extract has also been studied for its carcinogenic potential in other cancers and found to be effective on erythroleukemia and human breast and gastric cancer (Tong et al, 2009; Ebrahimi et al, 2017; Facchini et al, 2014; Cao et al, 2015). Since the last decade, several structure based insilico approaches such as molecular docking, homology modeling and MD simulation, are already exist as potential tools for screening compounds against receptor having substantial accuracy (Katara, 2013; Kesharwani et al, 2021). As 3-D structure of BUB1B (PDB: 2WVI) is available (fig.…”

Section: Introductionmentioning

confidence: 99%

In Silico insight to identify Potential Inhibitors of BUB1B from Mushroom bioactive compounds to Prevent Breast cancer metastasis

Mishra

Singh

2022

Preprint

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BUB1B (BUB1 Mitotic Checkpoint Serine/Threonine Kinase B) gene belongs to the spindle assembly checkpoint protein family, proven to be associated with many kinds of cancers. Protein kinases are crucial in metaphase to anaphase cellular transition. It is a primary element of spindle assembly checkpoint (SAC). This SAC is responsible for guarding the proper chromosomal segregation while any chromosomal instability hinders its normal functioning. The chromosomal instability may lead to cancer progression. And it occurs mainly due to overexpression of BUB1B in many cancer types especially in breast cancer metastasis. This could be controlled by designing proper inhibitor of this gene. For this purpose, there are proved existence of various mushroom compounds possessing some important medicinal properties with proven anti-cancerous effects. Proper screening and identification of molecules having these anti-cancerous effects and showing affinity against BUB1B with inhibition properties could be obtained from these compounds. So this study has incorporated 70 bioactive compounds (handpicked through literature mining) of distinct mushrooms that were considered and explored for identifying a suitable drug candidate. Their ADME/T properties were obtained to predict the drug-likeness of these 70 mushroom compounds based on Lipinskis rule of 5 (RO5). The screening of these bioactive compounds and subsequent molecular docking against BUB1B provided compounds with the best conformation-based binding affinity. The best 2 complexes, i.e., BUB1B-Lepiotaprocerin D and BUB1B-Peptidoglycan, were subjected to the molecular dynamics simulation. Both the complexes were observed for their affinity, stability, and flexibility in protein-ligand complex systems. The MD simulation study revealed that Lepiotaprocerin D has an energetically favorable binding affinity with BUB1B. Results showed that the formation of a hydrogen bond between ASN123, SER157 residue and Lepiotaprocerin D has strengthened the affinity of Lepiotaprocerin D with BUB1B. Hence, this study identified Lepiotaprocerin D as a potential and novel inhibitor for BUB1B that could be a plausible drug candidate for checking and controlling the spread of breast cancer metastasis.

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Repurposing of FDA approved drugs and their validation against potential drug targets for Salmonella enterica through molecular dynamics simulation

Cited by 8 publications

References 42 publications

Impact of the R292K Mutation on Influenza A (H7N9) Virus Resistance towards Peramivir: A Molecular Dynamics Perspective

Impact of the R292K Mutation on Influenza A (H7N9) Virus Resistance towards Peramivir: A Molecular Dynamics Perspective

Heat Shock Protein 90 (HSP90) Inhibitors as Anticancer Medicines: A Review on the Computer-Aided Drug Discovery Approaches over the Past Five Years

In Silico insight to identify Potential Inhibitors of BUB1B from Mushroom bioactive compounds to Prevent Breast cancer metastasis

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