3D CoMFA, CoMSIA, topomer CoMFA and HQSAR studies on aromatic acid esters for carbonic anhydrase inhibitory activity

Nilewar, Shrikant; Kathiravan, Muthu K.

doi:10.1002/cem.2574

Cited by 17 publications

(6 citation statements)

References 20 publications

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“…Somehow considered as a development of COMFA, Comparative Molecular Similarity Index Analysis (COMSIA) extends to more spatial descriptors, such as hydrophobicity, hydrogen bond acceptors and donors. It also does not involve cut-off values, which makes the calculations outside the molecular surface possible, thus making COMSIA a more reliable technique (Nilewar & Kathiravan, 2014). This review does not aim to provide an exhaustive explanation on the modeling technique and procedures performed in various experiments.…”

Section: Sar Analysesmentioning

confidence: 95%

Flavonoid interactions during digestion, absorption, distribution and metabolism: a sequential structure–activity/property relationship-based approach in the study of bioavailability and bioactivity

Gonzales

Smagghe

Grootaert

et al. 2015

Drug Metabolism Reviews

205

133

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Flavonoids are a group of polyphenols that provide health-promoting benefits upon consumption. However, poor bioavailability has been a major hurdle in their use as drugs or nutraceuticals. Low bioavailability has been associated with flavonoid interactions at various stages of the digestion, absorption and distribution process, which is strongly affected by their molecular structure. In this review, we use structure-activity/property relationship to discuss various flavonoid interactions with food matrices, digestive enzymes, intestinal transporters and blood proteins. This approach reveals specific bioactive properties of flavonoids in the gastrointestinal tract as well as various barriers for their bioavailability. In the last part of this review, we use these insights to determine the effect of different structural characteristics on the overall bioavailability of flavonoids. Such information is crucial when flavonoid or flavonoid derivatives are used as active ingredients in foods or drugs.

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Section: Sar Analysesmentioning

confidence: 95%

Flavonoid interactions during digestion, absorption, distribution and metabolism: a sequential structure–activity/property relationship-based approach in the study of bioavailability and bioactivity

Gonzales

Smagghe

Grootaert

et al. 2015

Drug Metabolism Reviews

205

133

View full text Add to dashboard Cite

show abstract

“…Molecular docking is a computational program identifying possible interactions between the ligand and the target active site. 63,64 The hit compounds from the Pharmacophore model were then subjected to additional screening utilizing MOE® 2022 molecular docking on CDK6 as a target. The rigid receptor docking method was used to accomplish molecular docking, with the ligands set as flexible and the CDK6 set as rigid.…”

Section: Methodsmentioning

confidence: 99%

Exploring cyclin-dependent kinase inhibitors: a comprehensive study in search of CDK-6 inhibitors using a pharmacophore modelling and dynamics approach

Chagaleti,

Saravanan,

Vellapandian

et al. 2023

RSC Adv.

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“…The partial least squares (PLS) regression method was employed to build the Topomer CoMFA model, and the leave-one-out (LOO) cross-validation was used to evaluate the model. Additional details regarding the Topomer CoMFA can be found in the references [ 23 , 24 , 25 ].…”

Section: Methodsmentioning

confidence: 99%

Discovery of MAO-B Inhibitor with Machine Learning, Topomer CoMFA, Molecular Docking and Multi-Spectroscopy Approaches

Zheng

Qin²,

Wang³

et al. 2022

Biomolecules

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Alzheimer’s disease (AD) is the most common type of dementia and is a serious disruption to normal life. Monoamine oxidase-B (MAO-B) is an important target for the treatment of AD. In this study, machine learning approaches were applied to investigate the identification model of MAO-B inhibitors. The results showed that the identification model for MAO-B inhibitors with　K-nearest neighbor(KNN) algorithm had a prediction accuracy of 94.1% and 88.0% for the 10-fold cross-validation test and the independent test set, respectively. Secondly, a quantitative activity prediction model for MAO-B was investigated with the Topomer CoMFA model. Two separate cutting mode approaches were used to predict the activity of MAO-B inhibitors. The results showed that the cut model with q2 = 0.612 (cross-validated correlation coefficient) and r2 = 0.824 (non-cross-validated correlation coefficient) were determined for the training and test sets, respectively. In addition, molecular docking was employed to analyze the interaction between MAO-B and inhibitors. Finally, based on our proposed prediction model, 1-(4-hydroxyphenyl)-3-(2,4,6-trimethoxyphenyl)propan-1-one (LB) was predicted as a potential MAO-B inhibitor and was validated by a multi-spectroscopic approach including fluorescence spectra and ultraviolet spectrophotometry.

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3D CoMFA, CoMSIA, topomer CoMFA and HQSAR studies on aromatic acid esters for carbonic anhydrase inhibitory activity

Cited by 17 publications

References 20 publications

Flavonoid interactions during digestion, absorption, distribution and metabolism: a sequential structure–activity/property relationship-based approach in the study of bioavailability and bioactivity

Flavonoid interactions during digestion, absorption, distribution and metabolism: a sequential structure–activity/property relationship-based approach in the study of bioavailability and bioactivity

Exploring cyclin-dependent kinase inhibitors: a comprehensive study in search of CDK-6 inhibitors using a pharmacophore modelling and dynamics approach

Discovery of MAO-B Inhibitor with Machine Learning, Topomer CoMFA, Molecular Docking and Multi-Spectroscopy Approaches

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