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Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

ABSTRACT: CONTEXT:Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. AIMS:To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. MATERIALS AND METHODS:In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. STATISTICAL ANALYSIS USED:Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. RESULTS:From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. CONCLUSIONS:Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

SUBMITTER: Satpathy R

PROVIDER: S-EPMC4333623 | biostudies-literature | 2015 Jan-Mar

REPOSITORIES: biostudies-literature

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Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

Satpathy Raghunath R Guru R K RK Behera R R Nayak B B

Journal of pharmacy & bioallied sciences 20150101 1

<h4>Context</h4>Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here.<h4>Aims</h4>To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches.<h4>Materials and methods</h4>In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the s ...[more]

PMID: 25709332

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Project description:Xanthone derivatives have a wide range of pharmacological activities, such as those involving antibacterial, antiviral, antimalarial, anthelmintic, anti-inflammatory, antiprotozoal, and anticancer properties. Among these, we investigated the anticancer properties of xanthone. This research aimed to analyze the biological activity of ten novel xanthone derivatives, to investigate the most contributing-descriptors for their cytotoxic activities, and to examine the possible mechanism of actions of xanthone compound through molecular docking.The cytotoxic tests were carried out on WiDR and Vero cell lines, by a 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) assay method. The structural features required for xanthone's anticancer activity were conducted by using the semi-empirical Austin Model-1 method, and continued with quantitative structure-activity relationship (QSAR) analysis using BuildQSAR program. The study of the possible mechanism of actions of the selected xanthone compound was done through molecular docking with PLANTS.The three novel xanthone derivatives (compounds 5, 7, and 8) exhibited cytotoxic activity with compound 5 showed the highest degree of cytotoxicity at concentration 9.23 µg/mL (37.8 µM). The following best equation model was obtained from the BuildQSAR calculation: log 1/IC50 = -8.124 qC1 -35.088 qC2 -6.008 qC3 + 1.831 u + 0.540 logP -9.115 (n = 10, r = 0.976, s = 0.144, F = 15.920, Q2 = 0.651, SPRESS = 0.390). This equation model generated 15 proposed new xanthone compounds with better-predicted anticancer activities. A molecular docking study of compound 5 showed that xanthone formed binding interactions with some receptors involved in cancer pathology, including telomerase, tumor-promoting inflammation (COX-2), and cyclin-dependent kinase-2 (CDK2) inhibitor.The results suggested that compound 5 showed the best cytotoxic activity among the xanthone derivatives tested. QSAR analysis showed that the descriptors contributed to xanthone's cytotoxic activity were the net atomic charge at qC1, qC2, and qC3 positions, also dipole moment and logP. Compound 5 was suspected to be cytotoxic by its inhibition of telomerase, COX-2, and CDK2 receptors.

Project description:Heavy-atom-free sensitizers forming long-living triplet excited states via the spin-orbit charge transfer intersystem crossing (SOCT-ISC) process have recently attracted attention due to their potential to replace costly transition metal complexes in photonic applications. The efficiency of SOCT-ISC in BODIPY donor-acceptor dyads, so far the most thoroughly investigated class of such sensitizers, can be finely tuned by structural modification. However, predicting the triplet state yields and reactive oxygen species (ROS) generation quantum yields for such compounds in a particular solvent is still very challenging due to a lack of established quantitative structure-property relationship (QSPR) models. In this work, the available data on singlet oxygen generation quantum yields (ΦΔ ) for a dataset containing >70 heavy-atom-free BODIPY in three different solvents (toluene, acetonitrile, and tetrahydrofuran) were analyzed. In order to build reliable QSPR model, a series of new BODIPYs were synthesized that bear different electron donating aryl groups in the meso position, their optical and structural properties were studied along with the solvent dependence of singlet oxygen generation, which confirmed the formation of triplet states via the SOCT-ISC mechanism. For the combined dataset of BODIPY structures, a total of more than 5000 quantum-chemical descriptors was calculated including quantum-chemical descriptors using density functional theory (DFT), namely M06-2X functional. QSPR models predicting ΦΔ values were developed using multiple linear regression (MLR), which perform significantly better than other machine learning methods and show sufficient statistical parameters (R=0.88-0.91 and q2 =0.62-0.69) for all three solvents. A small root mean squared error of 8.2 % was obtained for ΦΔ values predicted using MLR model in toluene. As a result, we proved that QSPR and machine learning techniques can be useful for predicting ΦΔ values in different media and virtual screening of new heavy-atom-free BODIPYs with improved photosensitizing ability.

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Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

Publications

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

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