Predicting ADME properties in silico: methods and models

Butina, Darko; Segall, Matthew D.; Frankcombe, Katrina E.

doi:10.1016/s1359-6446(02)02288-2

Cited by 233 publications

(148 citation statements)

References 40 publications

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“…Moreover, in silico prediction of ADME can be used to identify individual molecules or chemical libraries by evaluating their suitability as potential drug molecules. The determination of the attempted lead optimization before synthesizing the compounds causes less redesign-synthesize-test cycles [46]. Thus, predictions of ADME properties of the all synthesized compounds ( a-s) were performed by QikProp 4.8 software [35].…”

Section: Cytotoxicity Testmentioning

confidence: 99%

Synthesis, Molecular Docking Studies, and Antifungal Activity Evaluation of New Benzimidazole-Triazoles as Potential Lanosterol 14α-Demethylase Inhibitors

Can

Çevik

Sağlık

et al. 2017

Journal of Chemistry

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Due to anticandidal importance of azole compounds, a new series of benzimidazole-triazole derivatives ( a-s) were designed and synthesized as ergosterol inhibitors. The chemical structures of the target compounds were characterized by spectroscopic methods. The final compounds were screened for antifungal activity against Candida glabrata (ATCC 90030), Candida krusei (ATCC 6258), Candida parapsilosis (ATCC 22019), and Candida albicans (ATCC 24433). Compounds i and s exhibited significant inhibitory activity against Candida strains with MIC 50 values ranging from 0.78 to 1.56 g/mL. Cytotoxicity results revealed that IC 50 values of compounds i and s against NIH/3T3 are significantly higher than their MIC 50 values. Effect of the compounds i and s against ergosterol biosynthesis was determined by LC-MS-MS analysis. Both compounds caused a significant decrease in the ergosterol level. The molecular docking studies were performed to investigate the interaction modes between the compounds and active site of lanosterol 14--demethylase (CYP51), which is as a target enzyme for anticandidal azoles. Theoretical ADME predictions were also calculated for final compounds.

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Section: Cytotoxicity Testmentioning

confidence: 99%

Synthesis, Molecular Docking Studies, and Antifungal Activity Evaluation of New Benzimidazole-Triazoles as Potential Lanosterol 14α-Demethylase Inhibitors

Can

Çevik

Sağlık

et al. 2017

Journal of Chemistry

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“…In this context, structure-activity relationship (SAR) analysis is commonly used to build predictive models for the property of interest from a description of the molecules, using statistical procedures to build these models from the analysis of molecules with known properties (2).…”

Section: Introductionmentioning

confidence: 99%

The Pharmacophore Kernel for Virtual Screening with Support Vector Machines

Mahé

Ralaivola

Stoven

et al. 2006

J. Chem. Inf. Model.

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We introduce a family of positive definite kernels specifically optimized for the manipulation of 3D structures of molecules with kernel methods. The kernels are based on the comparison of the three-points pharmacophores present in the 3D structures of molecules, a set of molecular features known to be particularly relevant for virtual screening applications. We present a computationally demanding exact implementation of these kernels, as well as fast approximations related to the classical fingerprint-based approaches. Experimental results suggest that this new approach outperforms state-of-the-art algorithms based on the 2D structure of molecules for the detection of inhibitors of several drug targets.

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“…However, this is a subject matter for clinical verification. In silico predictions on administration, distribution, metabolism and elimination (ADME) of drugs in modern day research has the advantage of limiting time and reducing the cost of searching for NCEs with drug-like potentials (Butina et al, 2002;Kapetanovic, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…There are commercially available softwares (Boobis et al, 2002) that predict and simulate the fate of drug components as they interact with different compartments of the body notably, the administration, distribution, metabolism, elimination and toxic (ADMETox) outcomes of NCEs. In silico models built around the quantitative structure activity relationship (QSAR) concepts for example, have helped describe physicochemical properties of molecules by reliable laboratory data parameterization and development of molecular descriptors (Butina et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

In silico physico-chemical evaluation, anti-inflammatory and mcf-7 breast cancer cell line growth inhibition effects of trolline isolated from Mirabilis jalapa

Sadiq¹,

Inuwa²,

Rehman³

et al. 2016

J. Med. Plants Res.

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The in silico simulations and predictions approach in evaluation of pharmacokinetic properties of new chemical entities (NCEs) is fast becoming an acceptable trend in natural products research and drug discovery. This paper focuses on the properties of trolline with respect to its anti-inflammatory and MCF-7 breast cancer cell line growth inhibition effects and an attempt to predict physico-chemical druglike properties in silico. The compound was isolated for the first time from aerial parts of Mirabilis jalapa and the structure was elucidated by 1D and 2D NMR, FTIR and mass spectroscopic analyses. The compound was screened for anti-inflammatory and anti-MCF-7 cell lines proliferation using chemoluminiscence oxidative burst and MTT assays respectively. Predictions on physico-chemical properties central to oral route drug administration were done using commercial software Admet predictor. Results show anti-inflammatory effects at IC 50 concentration of 53.8 µg/ml and 48% mortality of breast cancer cell lines at 50 µM concentration. Predictions suggest moderate solubility of 1.72 to 2.92 mg/ml across pH range of 1.6 to 6.8 in simulated solvent systems and effective jejunal permeability of 5.61 x 10 -4 cm/s. The compound was also predicted to be 60% unbound to plasma proteins and an LD 50 of 950 mg/kg in rats. The compound, trolline had clinically important bioactive effects, probably possess promising drug-like properties suitable for further high throughput screening.

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Predicting ADME properties in silico: methods and models

Cited by 233 publications

References 40 publications

Synthesis, Molecular Docking Studies, and Antifungal Activity Evaluation of New Benzimidazole-Triazoles as Potential Lanosterol 14α-Demethylase Inhibitors

Synthesis, Molecular Docking Studies, and Antifungal Activity Evaluation of New Benzimidazole-Triazoles as Potential Lanosterol 14α-Demethylase Inhibitors

The Pharmacophore Kernel for Virtual Screening with Support Vector Machines

In silico physico-chemical evaluation, anti-inflammatory and mcf-7 breast cancer cell line growth inhibition effects of trolline isolated from Mirabilis jalapa

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