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Publication Metadata only Synthesis, anticancer activity and QSAR study of 1,4-naphthoquinone derivatives(2014-09-12) Veda Prachayasittikul; Ratchanok Pingaew; Apilak Worachartcheewan; Chanin Nantasenamat; Supaluk Prachayasittikul; Somsak Ruchirawat; Virapong Prachayasittikul; Mahidol University; Srinakharinwirot University; Chulabhorn Research Institute; Chulabhorn Graduate Institute; Ministry of Educationthe HepG2, HuCCA-1 and A549 cell lines was found to be m-acetylphenylamino-1,4-naphthoquinone (8) affording IC50values of 4.758, 2.364 and 12.279 μM, respectively. On the other hand, p-acetylphenylamino-1,4-naphthoquinone (9) exhibited the most potent....1881. The effects of substituents at the 2-amino position on the naphthoquinone core structure and its corresponding influence on the cytotoxic activity were investigated by virtually constructing additional 1,4-naphthoquinone compounds (13-36) for which cytotoxicPublication Open Access Discovery of novel 1,2,3-triazole derivatives as anticancer agents using QSAR and in silico structural modification(2015-10-05) Veda Prachayasittikul; Ratchanok Pingaew; Nuttapat Anuwongcharoen; Apilak Worachartcheewan; Chanin Nantasenamat; Supaluk Prachayasittikul; Somsak Ruchirawat; Virapong Prachayasittikul; Mahidol University. Faculty of Medical Technology. Department of Clinical Microbiology and Applied Technology; Mahidol University. Faculty of Medical Technology. Center of Data Mining and Biomedical InformaticsConsiderable attention has been given on the search for novel anticancer drugs with respect to the disease sequelae on human health and well-being. Triazole is considered to be an attractive scaffold possessing diverse biological activities. Structural modification on the privileged structures is noted as an effective strategy towards successful design and development of novel drugs. The quantitative structure–activity relationships (QSAR) is well-known as a powerful computational tool to facilitate the discovery of potential compounds. In this study, a series of thirty-two 1,2,3-triazole derivatives (1–32) together with their experimentally measured cytotoxic activities against four cancer cell lines i.e., HuCCA-1, HepG2, A549 and MOLT-3 were used for QSAR analysis. Four QSAR models were successfully constructed with acceptable predictive performance affording RCV ranging from 0.5958 to 0.8957 and RMSE CV ranging from 0.2070 to 0.4526. An additional set of 64 structurally modified triazole compounds (1A–1R, 2A–2R, 7A–7R and 8A–8R) were constructed in silico and their predicted cytotoxic activities were obtained using the constructed QSAR models. The study suggested crucial moieties and certain properties essential for potent anticancer activity and highlighted a series of promising compounds (21, 28, 32, 1P, 8G, 8N and 8Q) for further development as novel triazole-based anticancer agents.Publication Open Access Classification of P-glycoprotein-interacting compounds using machine-learning methods(2015-07) Watshara Shoombuatong; Apilak Worachartcheewan; Veda Prachayasittikul; Chanin Nantasenamat; Virapong Prachayasittikul; Mahidol University. Faculty of Medical Technology. Center of Data Mining and Biomedical Informaticsfunction of their physicochemical properties. The models provided good predictive performance, producing MCC values in the range of 0.739-1 for internal cross-validation and 0.665-1 for external validation. The study provided simple and interpretable modelsPublication Open Access Copper Complexes of Nicotinic-Aromatic Carboxylic Acids as Superoxide Dismutase Mimetics(Mahidol University, 2008) Thummaruk Suksrichavalit; Supaluk Prachayasittikul; Theeraphon Piacham; Chartchalerm Isarankura-Na-Ayudhya; Chanin Nantasenamat; Virapong Prachayasittikul) at the B3LYP/LANL2DZ level of theory. Interestingly, the SOD activity of the copper complex CuNA/Ph was positively correlated with the electron affinity (EA) value. The two quantum chemical parameters, highest occupied molecular orbital (HOMO) and lowest... shown to possess the lowest HOMO energy. These findings demonstrate a great potential for the development of value-added metallovitamin-based therapeutics.Publication Open Access Modeling the LPS neutralization activity of anti-endotoxins(2009) Chadinee Thippakorn; Thummaruk Suksrichavalit; Chanin Nantasenamat; Tanawut Tantimongcolwat; Chartchalerm Isarankura-Na-Ayudhya; Thanakorn Naenna; Virapong Prachayasittikul-out crossvalidation were well correlated with the experimental values as observed from the correlation coefficient and root mean square error of 0.930 and 0.162, respectively. Similarly, the external testing set also yielded good predictivityPublication Open Access Origin of aromatase inhibitory activity via proteochemometric modeling(2016-04) Saw Simeon; Ola Spjuth; Maris Lapins; Chanin Nantasenamat; Jarl ES Wikberg; Virapong Prachayasittikul; Mahidol University. Faculty of Medical Technology. Center of Data Mining and Biomedical InformaticsAromatase, the rate-limiting enzyme that catalyzes the conversion of androgen to estrogen, plays an essential role in the development of estrogen-dependent breast cancer. Side effects due to aromatase inhibitors (AIs) necessitate the pursuit of novel inhibitor candidates with high selectivity, lower toxicity and increased potency. Designing a novel therapeutic agent against aromatase could be achieved computationally by means of ligand-based and structure-based methods. For over a decade, we have utilized both approaches to design potential AIs for which quantitative structure-activity relationships and molecular docking were used to explore inhibitory mechanisms of AIs towards aromatase. However, such approaches do not consider the effects that aromatase variants have on different AIs. In this study, proteochemometrics modeling was applied to analyze the interaction space between AIs and aromatase variants as a function of their substructural and amino acid features. Good predictive performance was achieved, as rigorously verified by 10-fold cross-validation, external validation, leave-one-compound-out cross-validation, leave-one-protein-out cross-validation and Y-scrambling tests. The investigations presented herein provide important insights into the mechanisms of aromatase inhibitory activity that could aid in the design of novel potent AIs as breast cancer therapeutic agents.Publication Open Access Computational identification of miRNAs that modulate the differentiation of mesenchymal stem cells to osteoblasts(2016-04) Kanokwan Seenprachawong; Pornlada Nuchnoi; Chanin Nantasenamat; Aungkura Supokawej; Mahidol University. Faculty of Medical Technology. Center of Data Mining and Biomedical Informatics; Mahidol University. Faculty of Medical Technology. Department of Clinical MicroscopymiRNAs were then selected based on their free energy values, followed by assessing the probability of target accessibility. The results showed that miRNAs 23b, 23a, 30b, 143, 203, 217, and 221 could regulate the RUNX2 gene during the differentiation