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Pharmacophore Mapping and Virtual Screening for SIRT1 Activators
Sugunadevi Sakkiah,Navaneethakrishnan Krishnamoorthy,Poornima Gajendrarao,Sundarapandian Thangapandian,이윤호,Songmi Kim,Keun Woo Lee,서정근,Hyong-Ha Kim 대한화학회 2009 Bulletin of the Korean Chemical Society Vol.30 No.5
Silent information regulator 2 (Sir2) or sirtuins are NAD(+)-dependent deacetylases, which hydrolyze the acetyllysine residues. In mammals, sirtuins are classified into seven different classes (SIRT1-7). SIRT1 was reported to be involved in age related disorders like obesity, metabolic syndrome, type II diabetes mellitus and Parkinson’s disease. Activation of SIRT1 is one of the promising approaches to treat these age related diseases. In this study, we have used HipHop module of CATALYST to identify a series of pharmacophore models to screen SIRT1 enhancing molecules. Three molecules from Sirtris Pharmaceuticals were selected as training set and 607 sirtuin activator molecules were used as test set. Five different hypotheses were developed and then validated using the training set and the test set. The results showed that the best pharmacophore model has four features, ring aromatic, positive ionization and two hydrogen-bond acceptors. The best hypothesis from our study, Hypo2, screened high number of active molecules from the test set. Thus, we suggest that this four feature pharmacophore model could be helpful to screen novel SIRT1 activator molecules. Hypo2-virtual screening against Maybridge database reveals seven molecules, which contains all the critical features. Moreover, two new scaffolds were identified from this study. These scaffolds may be a potent lead for the SIRT1 activation.
Sundarapandian Thangapandian,Navaneethakrishnan Krishnamoorthy,Shalini John,Sugunadevi Sakkiah,Prettina Lazar,이윤호,이근우 대한화학회 2010 Bulletin of the Korean Chemical Society Vol.31 No.1
Human histamine H1 receptor (HHR1) is a G protein-coupled receptor and a primary target for antiallergic therapy. Here, the ligand-based three-dimensional pharmacophore models were built from a set of known HHR1 inverse agonists using HypoGen module of CATALYST software. All ten generated pharmacophore models consist of five essential features: hydrogen bond acceptor, ring aromatic, positive ionizable and two hydrophobic functions. Best model had a correlation coefficient of 0.854 for training set compounds and it was validated with an external test set with a high correlation value of 0.925. Using this model Maybridge database containing 60,000 compounds was screened for potential leads. A rigorous screening for drug-like compounds unveiled RH01692 and SPB00834, two novel molecules for HHR1 with good CATALYST fit and estimated activity values. The new lead molecules were docked into the active site of constructed HHR1 homology model based on recently crystallized squid rhodopsin as template. Both the hit compounds were found to have critical interactions with Glu177, Phe432 and other important amino acids. The interpretations of this study may effectively be deployed in designing of novel HHR1 inverse agonists
Sridevi, R.,Navaneethakrishnan, S.,Nagarajan, A.,Nagarajan, K. The Korean Society for Computational and Applied M 2012 Journal of applied mathematics & informatics Vol.30 No.5
The Odd-Even graceful labeling of a graph G with $q$ edges means that there is an injection $f:V (G)$ to $\{1,3,5,{\cdots},2q+1\}$ such that, when each edge $uv$ is assigned the label ${\mid}f(u)-f(v){\mid}$, the resulting edge labels are $\{2,4,6,{\cdots},2q\}$. A graph which admits an odd-even graceful labeling is called an odd-even graceful graph. In this paper, we prove that some well known graphs namely $P_n$, $P_n^+$, $K_{1,n}$, $K_{1,2,n}$, $K_{m,n}$, $B_{m,n}$ are Odd-Even graceful.
Thangapandian, Sundarapandian,Krishnamoorthy, Navaneethakrishnan,John, Shalini,Sakkiah, Sugunadevi,Lazar, Prettina,Lee, Yu-No,Lee, Keun-Woo Korean Chemical Society 2010 Bulletin of the Korean Chemical Society Vol.31 No.1
Human histamine H1 receptor (HHR1) is a G protein-coupled receptor and a primary target for antiallergic therapy. Here, the ligand-based three-dimensional pharmacophore models were built from a set of known HHR1 inverse agonists using HypoGen module of CATALYST software. All ten generated pharmacophore models consist of five essential features: hydrogen bond acceptor, ring aromatic, positive ionizable and two hydrophobic functions. Best model had a correlation coefficient of 0.854 for training set compounds and it was validated with an external test set with a high correlation value of 0.925. Using this model Maybridge database containing 60,000 compounds was screened for potential leads. A rigorous screening for drug-like compounds unveiled RH01692 and SPB00834, two novel molecules for HHR1 with good CATALYST fit and estimated activity values. The new lead molecules were docked into the active site of constructed HHR1 homology model based on recently crystallized squid rhodopsin as template. Both the hit compounds were found to have critical interactions with Glu177, Phe432 and other important amino acids. The interpretations of this study may effectively be deployed in designing of novel HHR1 inverse agonists.
R. Sridevi,S. Navaneethakrishnan,A. Nagarajan,K. Nagarajan 한국전산응용수학회 2012 Journal of applied mathematics & informatics Vol.30 No.5
The Odd-Even graceful labeling of a graph G with q edges means that there is an injection f : V (G) to {1, 3, 5, ... , 2q +1} such that,when each edge uv is assigned the label| f(u) - f(v)|, the resulting edge labels are {2, 4, 6, ..., 2q}. A graph which admits an odd-even graceful labeling is called an odd-even graceful graph. In this paper, we prove that some well known graphs namely Pn, P+n , K1,n, K1,2,n, Km,n, Bm,n are Odd-Even graceful.
Pharmacophore Mapping and Virtual Screening for SIRT1 Activators
Sakkiah, Sugunadevi,Krishnamoorthy, Navaneethakrishnan,Gajendrarao, Poornima,Thangapandian, Sundarapandian,Lee, Yun-O,Kim, Song-Mi,Suh, Jung-Keun,Kim, Hyong-Ha,Lee, Keun-Woo Korean Chemical Society 2009 Bulletin of the Korean Chemical Society Vol.30 No.5
Silent information regulator 2 (Sir2) or sirtuins are NAD(+)-dependent deacetylases, which hydrolyze the acetyllysine residues. In mammals, sirtuins are classified into seven different classes (SIRT1-7). SIRT1 was reported to be involved in age related disorders like obesity, metabolic syndrome, type II diabetes mellitus and Parkinson’s disease. Activation of SIRT1 is one of the promising approaches to treat these age related diseases. In this study, we have used HipHop module of CATALYST to identify a series of pharmacophore models to screen SIRT1 enhancing molecules. Three molecules from Sirtris Pharmaceuticals were selected as training set and 607 sirtuin activator molecules were used as test set. Five different hypotheses were developed and then validated using the training set and the test set. The results showed that the best pharmacophore model has four features, ring aromatic, positive ionization and two hydrogen-bond acceptors. The best hypothesis from our study, Hypo2, screened high number of active molecules from the test set. Thus, we suggest that this four feature pharmacophore model could be helpful to screen novel SIRT1 activator molecules. Hypo2-virtual screening against Maybridge database reveals seven molecules, which contains all the critical features. Moreover, two new scaffolds were identified from this study. These scaffolds may be a potent lead for the SIRT1 activation.
Effect of Nanographene Oxide on the Mechanical Properties of EPDM/SBRNano-composites
P. C. Prakash,G. Gurumoorthi,V. Navaneethakrishnan,S. Vishvanathperumal 한국고분자학회 2023 폴리머 Vol.47 No.4
The curing (optimum cure (t90) and scorch time (ts2), cure rate index (CRI), torque difference (ΔM), maximum torque (Mh) and minimum torque (Ml)), physical (hardness, rebound resilience, compression set and abrasion resistance), and mechanical properties (tensile strength, tensile modulus, tear strength and elongation at break) of ethylene-propylene-diene monomer terpolymer (EPDM)/styrene-butadiene copolymer rubber (SBR) nano-composites with additions of modified nano-graphene oxide (mGO) for possible usage as flexible and durable materials were examined in this study. Nano-graphene oxide (GO) was treated with two types of surfactants, 3-aminopropyltriethoxysilane (KH550) coupling agent and 4,4'-diphenylmethane diisocyanate (MDI), and then incorporated into an EPDM/SBR rubber matrix at a varying loading (2-10 phr), mixed by an open mill mixer, and vulcanized by hydraulic press. The particle size altered after modification, and the modified GO diffused efficiently in the EPDM/SBR rubber matrix, according to the FESEM. The MDI modified GO nano-composites have better mechanical properties than the KH550 modified GO nano-composites. The findings suggest that the produced nano-composites could be employed in a diversity of outdoor uses, including window seals, door seals and cooling system hoses.
V. Aravinth,G. Gurumoorthi,S. Vishvanathperumal,V. Navaneethakrishnan 한국고분자학회 2023 폴리머 Vol.47 No.3
Nanocomposites were created by using nanographene oxide (GO) as a reinforcing filler into silicone rubber and evaluating the materials' mechanical and abrasion resistance properties. GO was treated with 4,4'-diphenylmethane diisocyanate (MDI), then mixed with phenyl silicone rubber (PSR) at different concentrations (2-10 phr) and vulcanised. It was investigated the impact of MDI modified GO concentration on the morphology of PSR nanocomposites. The swelling properties of silicone rubber/MDI modified GO nanocomposites were also investigated in relation to penetrants (aromatic, aliphatic, and chlorinated solvents) and nanofiller concentrations (0-10 phr). Due to greater dispersion and reinforcing impact, mechanical parameters (tensile strength and modulus), and swelling resistance of silicone nanocomposites improve with MDI-GO concentration. The rate of rise is constant up to a concentration of 6 phr MDI-GO, after which it drops, confirming the formation of agglomeration. The MDI modification of GO improves the dispersion of MDI-GO in silicone rubber considerably, according to FESEM analysis. Because of its strong contact with the polymer matrix, GO serves as reinforcement. This research expands the range of applications for GO in the silicone rubber sector.