38 results
Search Results
Now showing 1 - 10 of 38
Publication Metadata only Elucidating the structure-activity relationship of curcumin and its biological activities(2014-07-01) Chanin Nantasenamat; Saw Simeon; Abdul Hafeez; Veda Prachayasittikul; Apilak Worachartcheewan; Napat Songtawee; Kakanand Srungboonmee; Chartchalerm Isarankura-Na-Ayudhya; Supaluk Prachayasittikul; Virapong Prachayasittikul; Mahidol Universityusage. This chapter discusses the origins of curcumin's biological activities in light of its structure-activity relationship. The structure of curcumin iscomprised of the central 1,6-heptadiene-3,5-dione bearing two terminal phenolic rings. Structural... modification of this compound alters its biological activities either by affecting its selectivity, specificity or potency. Understanding of such structure-activity relationship may provide the impetus for further expanding its biological activity repertoirePublication Metadata only Synthesis and structure-activity relationship of 2-thiopyrimidine-4-one analogs as antimicrobial and anticancer agents(2011-02-01) Supaluk Prachayasittikul; Apilak Worachartcheewan; Chanin Nantasenamat; Maneekarn Chinworrungsee; Nirun Sornsongkhram; Somsak Ruchirawat; Virapong Prachayasittikul; Srinakharinwirot University; Mahidol University; Chulabhorn Research Instituteas antifungal action against Candida albicans. Significantly, the 1-adamantylthiopyrimidine (5e) was shown to be the most potent cytotoxic compound against multidrug-resistant small cell lung cancer (H69AR). Their structure-activity relationships were discussedPublication Metadata only Quantitative structure-activity relationship study of betulinic acid derivatives against HIV using SMILES-based descriptors(2018-01-01) Apilak Worachartcheewan; Alla P. Toropova; Andrey A. Toropov; Suphakit Siriwong; Jatupat Prapojanasomboon; Virapong Prachayasittikul; Chanin Nantasenamat; Istituto di Ricerche Farmacologiche Mario Negri; Mahidol Universityand development. Objective: To construct Quantitative-structure Activity Relationship (QSAR) models of betulinic acid derivatives with anti-HIV activity using Simplified Molecular-Input Line-Entry System (SMILES)-based descriptors. Methods: A data set of 107Publication Metadata only Quantitative population-health relationship (QPHR) for assessing metabolic syndrome(2013-06-26) Apilak Worachartcheewan; Chanin Nantasenamat; Chartchalerm Isarankura-Na-Ayudhya; Virapong Prachayasittikul; Mahidol University. This study explores the utility of quantitative population-health relationship (QPHR) for predicting MS status as well as discovers variables that frequently occur together. The former was achieved by decision tree (DT) analysis, artificial neural networkPublication Metadata only Large-scale structure-activity relationship study of hepatitis C virus NS5B polymerase inhibition using SMILES-based descriptors(2015-11-01) Apilak Worachartcheewan; Virapong Prachayasittikul; Alla P. Toropova; Andrey A. Toropov; Chanin Nantasenamat; Mahidol University; Istituto di Ricerche Farmacologiche Mario Negritranscription and genome replication and is a target for designing anti-viral agents. In this study, classification and quantitative structure-activity relationship (QSAR) models of HCV NS5B inhibitors were constructed using the Correlation and Logic softwarePublication Metadata only Elucidating the Structure-Activity relationships of the vasorelaxation and antioxidation properties of thionicotinic acid derivatives(2010-01-01) Supaluk Prachayasittikul; Orapin Wongsawatkul; Apilak Worachartcheewan; Chanin Nantasenamat; Somsak Ruchirawat; Virapong Prachayasittikul; Srinakharinwirot University; Mahidol University; Chulabhorn Research InstituteNicotinic acid, known as vitamin B3, is an effective lipid lowering drug and intense cutaneous vasodilator. This study reports the effect of 2-(1-adamantylthio)nicotinic acid (6) and its amide 7 and nitrile analog 8 on phenylephrine-induced contraction of rat thoracic aorta as well as antioxidative activity. It was found that the tested thionicotinic acid analogs 6-8 exerted maximal vasorelaxation in a dose-dependent manner, but their effects were less than acetylcholine (ACh)-induced nitric oxide (NO) vasorelaxation. The vasorelaxations were reduced, apparently, in both NG-nitro-L- arginine methyl ester (L-NAME) and indomethacin (INDO). Synergistic effects were observed in the presence of L-NAME plus INDO, leading to loss of vasorelaxation of both the ACh and the tested nicotinic acids. Complete loss of the vasorelaxation was noted under removal of endothelial cells. This infers that the vasorelaxations are mediated partially by endothelium-induced NO and prostacyclin. The thionicotinic acid analogs all exhibited antioxidant properties in both 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and superoxide dismutase (SOD) assays. Significantly, the thionicotinic acid 6 is the most potent vasorelaxant with ED50 of 21.3 nM and is the most potent antioxidant (as discerned from DPPH assay). Molecular modeling was also used to provide mechanistic insights into the vasorelaxant and antioxidative activities. The findings reveal that the thionicotinic acid analogs are a novel class of vasorelaxant and antioxidant compounds which have potential to be further developed as promising therapeutics.Publication Metadata only Machine learning approaches for discerning intercorrelation of hematological parameters and glucose level for identification of diabetes mellitus(2013-10-21) Apilak Worachartcheewan; Chanin Nantasenamat; Pisit Prasertsrithong; Jakraphob Amranan; Teerawat Monnor; Tassaneya Chaisatit; Wilairat Nuchpramool; Virapong Prachayasittikul; Mahidol UniversityBackground: The aim of this study is to explore the relationship between hematological parameters and glycemic status in the establishment of quantitative population-health relationship (QPHR) model for identifying individuals with or without...) and artificial neural network (ANN) are machine learning approaches that were employed for identifying the glycemic status while association analysis (AA) was utilized in discovery of health parameters that frequently occur together. Results: Relationship amongstPublication Metadata only Data mining for the identification of metabolic syndrome status(2018-01-10) Apilak Worachartcheewan; Nalini Schaduangrat; Virapong Prachayasittikul; Chanin Nantasenamat; Mahidol University, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucida-tion/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data miningPublication Metadata only Towards the design of 3-aminopyrazole pharmacophore of pyrazolopyridine derivatives as novel antioxidants(2017-11-01) Apilak Worachartcheewan; Chanin Nantasenamat; Supaluk Prachayasittikul; Anyaporn Aiemsaard; Virapong Prachayasittikul; Mahidol Universityactivity were utilized for constructing a quantitative structure–activity relationship model as to unravel the origins of the antioxidant activity. Quantum chemical and molecular descriptors were used to quantitate the physicochemical properties... of investigated compounds. Significant descriptors as identified by stepwise regression analysis consisted of Mor11m, Mor25v, JGI5, H8p, GATS5p, and GVWAI-50. Statistical parameters suggested that the constructed quantitative structure–activity relationship modelsPublication Metadata only Novel 1,4-naphthoquinone-based sulfonamides: Synthesis, QSAR, anticancer and antimalarial studies(2015-10-20) Ratchanok Pingaew; Veda Prachayasittikul; Apilak Worachartcheewan; Chanin Nantasenamat; Supaluk Prachayasittikul; Somsak Ruchirawat; Virapong Prachayasittikul; Srinakharinwirot University; Mahidol University; Chulabhorn Research Institute; Ministry of Education-activity relationships (QSAR) study was performed to reveal important chemical features governing the biological activities. Five constructed QSAR models provided acceptable predictive performance (Rcv 0.5647-0.9317 and RMSEcv 0.1231-0... relationships was made and a set of promising compounds (i.e., 33, 36, 38, 42, 36d, 36f, 42e, 42g and 42f) was suggested for further development as anticancer and antimalarial agents.