Molecular Structure, Substituent Effect and Physical-Chemistry Property Relationship of Indole Derivatives

Harkati, Dalal; Belaidi, Salah; Kerassa, Aicha; Gherraf, Noureddine

doi:10.1166/qm.2016.1252

Cited by 5 publications

(6 citation statements)

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“…Quantitative structure–activity relationship (QSAR) is a general concept for computational models, which is proposed based on the presumption that similar chemical structures give birth to similar bioactivities ( Harkati et al., 2016) . Conventionally, the computational model can be divided into two consecutive but independent steps: chemical representation and structure–bioactivity association ( Butler et al., 2018) .…”

Section: Introductionmentioning

confidence: 99%

On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme

et al. 2023

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Introduction: Given the direct association with malignant ventricular arrhythmias, cardiotoxicity is a major concern in drug design. In the past decades, computational models based on the quantitative structure–activity relationship have been proposed to screen out cardiotoxic compounds and have shown promising results. The combination of molecular fingerprint and the machine learning model shows stable performance for a wide spectrum of problems; however, not long after the advent of the graph neural network (GNN) deep learning model and its variant (e.g., graph transformer), it has become the principal way of quantitative structure–activity relationship-based modeling for its high flexibility in feature extraction and decision rule generation. Despite all these progresses, the expressiveness (the ability of a program to identify non-isomorphic graph structures) of the GNN model is bounded by the WL isomorphism test, and a suitable thresholding scheme that relates directly to the sensitivity and credibility of a model is still an open question.Methods: In this research, we further improved the expressiveness of the GNN model by introducing the substructure-aware bias by the graph subgraph transformer network model. Moreover, to propose the most appropriate thresholding scheme, a comprehensive comparison of the thresholding schemes was conducted.Results: Based on these improvements, the best model attains performance with 90.4% precision, 90.4% recall, and 90.5% F1-score with a dual-threshold scheme (active: <1μM; non-active: >30μM). The improved pipeline (graph subgraph transformer network model and thresholding scheme) also shows its advantages in terms of the activity cliff problem and model interpretability.

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Section: Introductionmentioning

confidence: 99%

On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme

et al. 2023

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“…Some chemotherapeutic drugs are organic compounds either of natural or synthetic origin. Synthetic heteroaromatic organic compounds that are cyclic compounds with at least two or more different heteroatoms such as N, O, and S have attracted numerous attention due to their wide applications in medicinal chemistry research [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ], which among the major pharmaceutical natural products and synthetic drugs have a distinct place because of their remarkable biological activities and established application in medicinal chemistry [ 4 ]. The sulfur atoms in these molecules provide great stability in the form of sulfide or disulfide linkages [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…The discovery and design of new therapeutic chemicals or biochemicals and their development into useful medicine is the science of drug design [ 3 ]. The first step in the study of drug design and drug discovery is to perform computational electronic structure calculations.…”

Section: Introductionmentioning

confidence: 99%

A Computational QSAR, Molecular Docking and In Vitro Cytotoxicity Study of Novel Thiouracil-Based Drugs with Anticancer Activity against Human-DNA Topoisomerase II

Khaled

Elshakre

Noamaan

et al. 2022

IJMS

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Computational chemistry, molecular docking, and drug design approaches, combined with the biochemical evaluation of the antitumor activity of selected derivatives of the thiouracil-based dihydroindeno pyrido pyrimidines against topoisomerase I and II. The IC50 of other cell lines including the normal human lung cell line W138, lung cancer cell line, A549, breast cancer cell line, MCF-7, cervical cancer, HeLa, and liver cancer cell line HepG2 was evaluated using biochemical methods. The global reactivity descriptors and physicochemical parameters were computed, showing good agreement with the Lipinski and Veber’s rules of the drug criteria. The molecular docking study of the ligands with the topoisomerase protein provides the binding sites, binding energies, and deactivation constant for the inhibition pocket. Various biochemical methods were used to evaluate the IC50 of the cell lines. The QSAR model was developed for colorectal cell line HCT as a case study. Four QSAR statistical models were predicted between the IC50 of the colorectal cell line HCT to correlate the anticancer activity and the computed physicochemical and quantum chemical global reactivity descriptors. The predictive power of the models indicates a good correlation between the observed and the predicted activity.

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“…Molecular modeling [1] is used in many fields, particularly drug design [2,3]. Drug design is a science that focuses on the discovery and design of new therapeutic chemicals or biochemical and their development into useful medicines [4]. There has been a growing interest in the study of the chemical and biological aspects of heterocyclic compounds in the medicinal chemistry field in the past decades.…”

Section: Introductionmentioning

confidence: 99%

“…Heterocyclic compounds are cyclic organic compounds with at least two different elements, including nitrogen, oxygen and sulfur, as ring member atoms [1]. Among the major pharmaceutical natural products and synthetic drugs, heterocyclic compounds [4][5][6][7][8][9] have a distinct place, because of their remarkable biological activities and established application in medicinal chemistry [5]. The importance of the sulfur atom in drugs in the form of sulfide or disulfide linkages provides great stability for the three dimensional structure of the molecule [10].…”

Section: Introductionmentioning

confidence: 99%

Density Functional Theory, Chemical Reactivity, Pharmacological Potential and Molecular Docking of Dihydrothiouracil-Indenopyridopyrimidines with Human-DNA Topoisomerase II

Elshakre

Noamaan

Moustafa

et al. 2020

IJMS

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In this work, three computational methods (Hatree-Fock (HF), Møller–Plesset 2 (MP2), and Density Functional Theory (DFT)) using a variety of basis sets are used to determine the atomic and molecular properties of dihydrothiouracil-based indenopyridopyrimidine (TUDHIPP) derivatives. Reactivity descriptors of this system, including chemical potential (µ), chemical hardness (η), electrophilicity (ω), condensed Fukui function and dual descriptors are calculated at B3LYP/6-311++ G (d,p) to identify reactivity changes of these molecules in both gas and aqueous phases. We determined the molecular electrostatic surface potential (MESP) to determine the most active site in these molecules. Molecular docking study of TUDHIPP with topoisomerase II α and β is performed, predicting binding sites and binding energies with amino acids of both proteins. Docking studies of TUDHIPP versus etoposide suggest their potential as antitumor candidates. We have applied Lipinski, Veber’s rules and analysis of the Golden triangle and structure activity/property relationship for a series of TUDHIPP derivatives indicate that the proposed compounds exhibit good oral bioavailability. The comparison of the drug likeness descriptors of TUDHIPP with those of etoposide, which is known to be an antitumor drug, indicates that TUDHIPP can be considered as an antitumor drug. The overall study indicates that TUDHIPP has comparable and even better descriptors than etoposide proposing that it can be as effective antitumor drug, especially 2H, 6H and 7H compounds.

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Molecular Structure, Substituent Effect and Physical-Chemistry Property Relationship of Indole Derivatives

Cited by 5 publications

References 0 publications

On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme

On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme

A Computational QSAR, Molecular Docking and In Vitro Cytotoxicity Study of Novel Thiouracil-Based Drugs with Anticancer Activity against Human-DNA Topoisomerase II

Density Functional Theory, Chemical Reactivity, Pharmacological Potential and Molecular Docking of Dihydrothiouracil-Indenopyridopyrimidines with Human-DNA Topoisomerase II

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