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A Review of 3D-QSAR in Drug Design
Madhavan, Thirumurthy The Basic Science Institute Chosun University 2012 조선자연과학논문집 Vol.5 No.1
Quantitative structure-activity relationship (QSAR) methodologies have been applied for many years, to correlate the relationship between physicochemical properties of chemical substances and their biological activities to generate a statistical model for prediction of the activities of new chemical entities. The basic principle behind the QSAR models is that, how structural variation is responsible for the difference in biological activities of the compounds. 3D-QSAR has emerged as a natural extension to the classical Hansch and Free-Wilson approaches, which develops the 3D properties of the ligands to predict their biological activities using various chemometric techniques (PLS, G/PLS, ANN etc). It has served as a valuable predictive tool in the design of pharmaceuticals and agrochemicals. This review seeks to provide different 3D-QSAR approaches involved in drug designing process to develop structure-activity relationships and also discussed the fundamental limitations, as well as those that might be overcome with the improved methodologies.
3D-QSAR Studies of 3,5-disubstituted Quinolines Inhibitors of c-Jun N-terminal Kinase-3
Madhavan, Thirumurthy The Basic Science Institute Chosun University 2011 조선자연과학논문집 Vol.4 No.3
c-Jun N-terminal kinase-3 (JNK-3) has been shown to mediate neuronal apoptosis and make the promising therapeutic target for neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and other CNS disorders. In order to better understand the structural and chemical features of JNK-3, comparative molecular field analysis (CoMFA) was performed on a series of 3,5-disubstituted quinolines derivatives. The best predictions were obtained CoMFA model ($q^2$=0.707, $r^2$=0.972) and the statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The resulting contour map from 3D-QSAR models might be helpful to design novel and more potent JNK3 derivatives.
A Docking Study of Newly Found Natural Neuraminidase Inhibitor: Erystagallin A
Madhavan, Thirumurthy The Basic Science Institute Chosun University 2011 조선자연과학논문집 Vol.4 No.4
It's a threat for the public health that H1N1 (Influenza virus A) causes disease and transmits among humans. WHO (world health organization) declared that the infections caused by the new strain had reached pandemic proportions. The approved neuraminidase inhibitors (Zanamivir and Oseltamivir) and related investigative drug (BCX-1812) are potent, specific inhibitors of influenza A and B viruses. These drugs are highly effective to prevent influenza A and B infections. Early therapeutic use reduces illness duration and respiratory complications. Recently, we found one of the potent inhibitor of erystagallin A ($IC_{50}$ of 2.04 ${\mu}M$) for neuraminidase target, this inhibitor shows most similar structure to its natural substrate, sialic acid. Therefore, we chose 1l7f to get the receptor structure for docking study among many crystal structures. A docking study has been performed in Surflex-Dock module in SYBYL 8.1. In the present study, we attempt to compare the docking studies of pterocarpin and erystagallin A with neuraminidase receptor structure. In the previous report, the methoxy group of pterocarpin had H-bonding with Arg residues. The present docking results for erystagallin A showed the backbone of hydroxyl group shows significant H-bonding interactions with Arg152 and Arg292. The results showed that erystagallin A interacts more favorably with distinctive binding site rather than original active site. Therefore, we tried to reveal plausible binding mode and important amino acid for this inhibitor using docking and site id search calculations of Sybyl. The results obtained from this work may be utilized to design novel inhibitors for neuraminidase.
Modeling Aided Lead Design of FAK Inhibitors
Madhavan, Thirumurthy The Basic Science Institute Chosun University 2011 조선자연과학논문집 Vol.4 No.4
Focal adhesion kinase (FAK) is a potential target for the treatment of primary cancers as well as prevention of tumor metastasis. To understand the structural and chemical features of FAK inhibitors, we report comparative molecular field analysis (CoMFA) for the series of 7H-pyrrolo(2,3-d)pyrimidines. The CoMFA models showed good correlation between the actual and predicted values for training set molecules. Our results indicated the ligand-based alignment has produced better statistical results for CoMFA ($q^2$ = 0.505, $r^2$ = 0.950). Both models were validated using test set compounds, and gave good predictive values of 0.537. The statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The contour map from 3D-QSAR models explains nicely the structure-activity relationships of FAK inhibitors and our results would give proper guidelines to further enhance the activity of novel inhibitors.
Molecular Docking Analysis of Protein Phosphatase 1D (PPM1D) Receptor with SL-175, SL-176 and CDC5L
Madhavan, Thirumurthy The Basic Science Institute Chosun University 2018 조선자연과학논문집 Vol.11 No.1
Protein phosphatase manganese dependent 1D (PPM1D), a Ser/Thr protein phosphatise, play major role in the cancer tumorigenesis of various tumors including neuroblastoma, pancreatic adenocarcinoma, medulloblastoma, breast cancer, prostate cancer and ovarian cancer. Hence, analysis on the structural features required for the formation of PPM1D-inhibitor complex becomes essential. In this study, we have performed molecular docking of SL-175 and -176 and protein-protein docking of CDC5L with PPM1D. On analysing the docked complexes, we have identified the important residues involved in the formation of protein-ligand complex. Research concentrating on these residues could be helpful in understanding the pathophysiology of various tumors related to PPM1D.