admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties

Cheng, Feixiong; Li, Weihua; Zhou, Yadi; Shen, Jie; Wu, Zengrui; Liu, Guixia; Lee, Philip W.; Tang, Yun

doi:10.1021/ci300367a

Cited by 1,705 publications

(1,079 citation statements)

References 46 publications

Supporting

Mentioning

1,008

Contrasting

Unclassified

Order By: Relevance

“…Lipinski's rule of five (RO5) was used to evaluate drug-likeness to determine if the herbal derivatives have certain pharmacological or biological activity that would make them an orally active drug-like moiety for humans [41,42].…”

Section: Prediction Of Molecular Propertiesmentioning

confidence: 99%

Molecular Docking and Pharmacokinetic Prediction of Herbal Derivatives as Maltase-Glucoamylase Inhibitor

Ochieng

Sumaryada

Okun

2017

Asian J Pharm Clin Res

View full text Add to dashboard Cite

Objective: To perform molecular docking and pharmacokinetic prediction of momordicoside F2, beta-sitosterol, and cis-N-feruloyltyramine herbal derivatives as maltase-glucoamylase (MGAM) inhibitors for the treatment of diabetes. Methods:The herbal derivatives and standard drug miglitol were docked differently onto MGAM receptor using AutoDock Vina software. In addition, Lipinski's rule, drug-likeness, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were analyzed using Molinspiration, ADMET structure-activity relationship, and prediction of activity spectra for substances online tools.Results: Docking studies reveal that momordicoside F2, beta-sitosterol, and cis-N-feruloyltyramine derivatives have high binding affinity to the MGAM receptor (−7.8, −6.8, and −6.5 Kcal/Mol, respectively) as compared to standard drug miglitol (−5.3 Kcal/Mol). In addition, all the herbal derivatives indicate good bioavailability (topological polar surface area <140 Ȧ and N rot <10) without toxicity or mutagenic effects. Conclusion:The molecular docking and pharmacokinetic information of herbal derivatives obtained in this study can be utilized to develop novel MGAM inhibitors having antidiabetic potential with better pharmacokinetic and pharmacodynamics profile.

show abstract

Section: Prediction Of Molecular Propertiesmentioning

confidence: 99%

Molecular Docking and Pharmacokinetic Prediction of Herbal Derivatives as Maltase-Glucoamylase Inhibitor

Ochieng

Sumaryada

Okun

2017

Asian J Pharm Clin Res

View full text Add to dashboard Cite

show abstract

“…In this study absorption, distribution, metabolism, excretion and toxicity (ADMET) of the selected compounds were predicted using the ADMET SAR database (Cheng et al, 2012). This database is known as a knowledge based tool that used for Insilico screening of the ADMET properties for all types of compounds.…”

Section: Absorption Distribution Metabolism Excretion and Toxicitymentioning

confidence: 99%

In-silico Virtual Screening and ADMET Study to Find Novel Neuraminidase N1 Inhibitors Extended to the 150-Cavity

2017

J App Pharm Sci

View full text Add to dashboard Cite

Neuraminidase (NA) is the major surface protein of the influenza virus. It extracellularly acts by cleaving the terminal neuraminic acid from cellular receptors recognized by the Hemagglutinin. Then, it facilitates the release of newly formed visions from the host cell surface to the neighboring cells, thereby facilitating the spread of the virus. A 150-cavity adjacent to the active conservative site is possessed by the group-1 neuraminidase, thereby rendering conformational change from open to close form when the ligand binds to the enzyme. In the present study, author reported an in silico virtual screening and docking analysis for potential neuraminidase inhibitors of various ligands obtained from the ZINC database using Autodock Vina against the 3TI6 protein. Analysis of 850 screened ligands reveal that five compounds with free binding energies of -11.2, -10.9, -10.4, -10.4, and -10.1 kcal/mol (ZINC03260201, ZINC09153352, ZINC09460395, ZINC13128611, and ZINC20605436, respectively) showed interaction with the protein at the known active site, as well as with the 150-cavity creating a stronger interaction between the ligand and the protein. Furthermore, lower binding energy is exhibited compared with the co-crystallized drug oseltamivir. In silico absorption, distribution, metabolism, and excretion (ADMET) prediction revealed that best compounds show comparative results with oseltamivir. Novel compounds interacting with the 150-cavity were successfully identified using this approach; such compounds could serve as a potential lead compound for developing a new anti-neuraminidase drug.

show abstract

“…The complete ADMET properties were calculated using admetSAR (Cheng et al, 2012) DOI:http://dx.doi.org/10.7314/APJCP.2015.16.18…”

Section: Admet and Bioactivity Prediction Of Compoundsmentioning

confidence: 99%

Identification and Pharmacological Analysis of High Efficacy Small Molecule Inhibitors of EGF-EGFR Interactions in Clinical Treatment of Non-Small Cell Lung Carcinoma: a Computational Approach

Gudala¹,

Khan²,

Kanungo³

et al. 2016

Asian Pacific Journal of Cancer Prevention

View full text Add to dashboard Cite

Inhibition of EGFR-EGF interactions forms an important therapeutic rationale in treatment of non-small cell lung carcinoma. Established inhibitors have been successful in reducing proliferative processes observed in NSCLC, however patients suffer serious side effects. Considering the narrow therapeutic window of present EGFR inhibitors, the present study centred on identifying high efficacy EGFR inhibitors through structure based virtual screening strategies. Established inhibitors -Afatinib, Dacomitinib, Erlotinib, Lapatinib, Rociletinib formed parent compounds to retrieve similar compounds by linear fingerprint based tanimoto search with a threshold of 90%. The compounds (parents and respective similars) were docked at the EGF binding cleft of EGFR. Patch dock supervised protein-protein interactions were established between EGF and ligand (query and similar) bound and free states of EGFR. Compounds ADS103317, AKOS024836912, AGN-PC-0MXVWT, GNF-Pf-3539, SCHEMBL15205939 were retrieved respectively similar to Afatinib, Dacomitinib, Erlotinib, Lapatinib, Rociletinib. Compound-AGN-PC-0MXVWT akin to Erlotinib showed highest affinity against EGFR amongst all the compounds (parent and similar) assessed in the study. Further, AGN-PC-0MXVWT brought about significant blocking of EGFR-EGF interactions in addition showed appreciable ADMET properties and pharmacophoric features. In the study, we report AGN-PC-0MXVWT to be an efficient and high efficacy inhibitor of EGFR-EGF interactions identified through computational approaches.

show abstract

admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties

Cited by 1,705 publications

References 46 publications

Molecular Docking and Pharmacokinetic Prediction of Herbal Derivatives as Maltase-Glucoamylase Inhibitor

Molecular Docking and Pharmacokinetic Prediction of Herbal Derivatives as Maltase-Glucoamylase Inhibitor

In-silico Virtual Screening and ADMET Study to Find Novel Neuraminidase N1 Inhibitors Extended to the 150-Cavity

Identification and Pharmacological Analysis of High Efficacy Small Molecule Inhibitors of EGF-EGFR Interactions in Clinical Treatment of Non-Small Cell Lung Carcinoma: a Computational Approach

Contact Info

Product

Resources

About