Pharmacokinetic profiling of anticancer phytocompounds using computational approach

Abstract

We have created an interactive database (ADMETCan), which provides access to predicted ADMET of these anticancer phytomolecules. The ease of availability of this dataset is expected to minimise failure rate of these compounds and thus is expected to be beneficial to the scientific community involved in anticancer identification and development.

Expanding the Chemical Space of Withaferin A by Incorporating Silicon To Improve Its Clinical Potential on Human Ovarian Carcinoma Cells

“…Understanding pharmacokinetic properties (ADME, absorption, distribution, metabolism, and excretion molecular properties) is an important step in drug discovery to select new lead/drug candidates, since potent in vitro activity along with enhanced ADME profiles increases the probability of clinical success. 32 Moreover, despite a great deal of research conducted on the potential anticancer properties of WA-related withanolides, there are only two reports of ADME studies. 33,34 The QikProp module of Schrodinger software 35 was used for analyzing physicochemical and pharmacokinetic descriptors (ADME properties) of selected compounds (IC 50 values ≤1 μm on A2780 and A2780/CP70 cell lines) with the aim of increasing the success rate of compounds reaching further stages of development.…”

“…Understanding pharmacokinetic properties (ADME, absorption, distribution, metabolism, and excretion molecular properties) is an important step in drug discovery to select new lead/drug candidates, since potent in vitro activity along with enhanced ADME profiles increases the probability of clinical success . Moreover, despite a great deal of research conducted on the potential anticancer properties of WA-related withanolides, there are only two reports of ADME studies. , …”

Computational identification of natural product inhibitors against EGFR double mutant (T790M/L858R) by integrating ADMET, machine learning, molecular docking and a dynamics approach

“…As poor pharmacokinetics oen results in failure in later stages of drug discovery, screening libraries for their ADMET properties before taking them for virtual screening studies is considered necessary. 16,17,29 In the last few years, various in silico rules to evaluate the pharmacological properties and identify optimal molecules have been designed. 30 The routinely used approach to screen for drug-like molecules is by estimating Lipinski's "Rule of Five" (Ro5).…”

“…However, it is essential to identify inhibitors that exhibit high affinity with the target binding site and have suitable ADMET properties to reduce the chances of attrition during the drug development phase. 16,17 So, a novel computational approach has been employed wherein the rule for constrained-based docking was developed based on reported TMLR X-ray crystal structures so that the screened inhibitors mimic interactions similar to that of co-crystallized ligands. Additionally, prior to docking the NP library was screened using a machine learning based binary classication model (NPred) which categorizes molecules based on their anticancer potential.…”

Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds

“…Pharmacokinetic descriptors such as absorption, distribution, metabolism, and excretion (ADME), and toxicity (T) are commonly used properties for profiling or predicting the fate of many drug candidates after clinical administration [ 85 ]. The concept of investigating the ADMET is of interest in early drug discovery given that over 70% of clinical failures have been connected to these properties [ 86 , 87 ]. In addition to potency, a successful drug candidate is expected to have favorable ADMET properties [ 85 , 87 ].…”