Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five

Chagas, Caroline Manto; Moss, Sara; Alisaraie, Laleh

doi:10.1016/j.ijpharm.2018.07.046

Cited by 166 publications

(102 citation statements)

References 138 publications

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“…Rofecoxib is an orally administered drug and in consonance, its properties did not violate the rule of Lipinski (RO5). Thus, this result predicts similarity to biological activity designed for oral administration [ 37 , 46 ].…”

Section: Resultsmentioning

confidence: 55%

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

et al. 2020

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The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = −11.0 kcal/mol), LMQC36 (∆G = −10.6 kcal/mol), and LMQC50 (∆G = −10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = −10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = −45.31 kcal/mol; LMQC72: ΔGbind = −38.58 kcal/mol; LMQC36: ΔGbind = −36.10 kcal/mol; and LMQC50: ΔGbind = −39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.

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Section: Resultsmentioning

confidence: 55%

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

et al. 2020

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“…1,and many factors should be considered,such as half-life, indicating the continuous effect of the drug,and oral bioavailability to prove the biological activity of the smolecule [29].The blood-brain barrier should be considered rst in brain diseases treatments [30]. According to Lipinski's ve-point ruleto determine the choice of drugs [31],the recommended choice for oral drugs was molecular weight < 500, Logp < 5.The number of hydrogen-bonded donors and acceptors was less than 5 and 10,respectively (Table 1).Among the drugs we selected, paeoni orin'Hacc values > 10,but other parameters meet the pharmacokinetics of oral drugs.Therefore, we still consider paeoni orin as a new drug option and a new target need to be explored deeply.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Paeoniflorin Treatment of Cancer Based on Bioinformatic Network and Potential Target Prediction

yongan¹,

Yu²,

Li³

et al. 2020

Preprint

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In the synthesis of chemical drugs used to treat various cancers and tumors,more and more scientists are now focusing on the development of natural extracts.Paeoniflorin,as an important compounds of the total glucosides of peony,,had therapeutic effects on a variety of cancers in vivo and in vitro experiments.The purpose of this study was to use biological information analysis to reveal the basic mechanism and potential molecular mechanism of paeoniflorin treatment.We evaluated the efficacy of paeoniflorin through Traditional Chinese Medicine Systems Pharmacology Database(TCMSP).The potential targets of paeoniflorin were identified and summarized by Comparative Toxicogenomics Database (CTD),and GeneMANIA protein interaction analysis was performed online.Also.We used WebGestalt for Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis and functional annotation.Finally,cytoscape was used to construct the paeoniflorin-target-pathway network to predict the results.

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“…Referring to LRO5, a compound will adequate to drug-like molecule if it has a molecular weight less than 500 g/mol, a logP value no more than 5 which represents hydrophobicity characters, number of Hbond donor less than 5, and H-bond acceptor less than 10 sites. Further, the number of rotatable bonds less than 10 will provide molecule flexibility, while TPSA value less than or equal to 140 Å provides good permeability and bioavailability (Chagas et al, 2018). Regarding those rules, all of the analyzed compounds from Ginger have acceptable to perform respectable drug-likeness properties.…”

Section: Ligand Potency As Inhibitor Of Mpromentioning

confidence: 99%

Virtual prediction of antiviral potential of ginger (Zingiber officinale) bioactive compounds against spike and MPro of SARS-CoV2 protein

Ahkam

Hermanto

Alamsyah

et al. 2020

Berkala Penelitian Hayati

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Coronavirus disease 2019 (COVID-19) is a human disease caused by SARS-CoV2 becomes a serious health threat after infected more than 6 million people globally. The virus enters the host cell through an S protein on its surface and begins its life cycle with the help of a key protein, MPro. On the other hand, several bioactive from Ginger have been reported for their antiviral properties, but few studies related to COVID-19. This study aims to pursue the potential of a few bioactive compounds from Ginger as anti-SARS-CoV 2 from their interaction to spike and Mpro protein. Gingerenone A, gingerol, geraniol, shogaol, zingiberene, zingiberenol, and zingerone were used as ligand to be docked with S protein and MPro. Drug-likeness properties also evaluated using SwissADME. Gingerenone A constantly gave the lowest binding energy compared to others both with S or MPro. However, gingerol, geraniol, shogaol, zingiberene, zingiberenol, and zingerone could interact with key residues responsible for MPro catalytic domain, while geraniol, shogaol, zingiberene, zingiberenol, and zingerone could interfere S-ACE2 binding shape and increase its binding energy. The drug-likeness analysis also revealed that all of the analyzed compounds have no violation of Lipinski's Rule of 5. In conclusion, gingerol, geraniol, shogaol, zingiberene, zingiberenol, and zingerone from Ginger have good potential as antiviral agents with good oral bioavailability and flexibility.

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Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five

Cited by 166 publications

References 138 publications

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

Analysis of Paeoniflorin Treatment of Cancer Based on Bioinformatic Network and Potential Target Prediction

Virtual prediction of antiviral potential of ginger (Zingiber officinale) bioactive compounds against spike and MPro of SARS-CoV2 protein

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