OPTIMIZING STRUCTURE-BASED VIRTUAL SCREENING PROTOCOL TO IDENTIFY PHYTOCHEMICALS AS CYCLOOXYGENASE-2 INHIBITORS

By employing Databases of Useful Decoys (DUD) and its enhanced version (DUD-E), several attempts to construct validated Structure-based Virtual Screening (SBVS) protocols to identify cyclooxygenase-2 (COX-2) inhibitors have been performed. Both databases tagged active COX-2 inhibitors for compounds with IC50 values < 1mM. In the search for phytochemicals as natural COX-2 inhibitors, however, most of their IC50 values are in the micromolar range, which will likely be identified as non-inhibitors for COX-2 by the available SBVS protocols. In this article, validation of an SBVS protocol by adding marginal active COX-2 inhibitors from DUD-E as active compounds is presented. Binary quantitative-structure activity relationship analysis by using recursive partition and regression tree method was performed subsequently to optimize the predictive ability of the protocol. The enrichment factor and the F-measure values of the optimized protocol could reach 44.78 and 0.47, respectively. The optimized protocol could identify 1 out of 9 phytochemicals as COX-2 inhibitors

EMPLOYING RECURSIVE PARTITION AND REGRESSION TREE METHOD TO INCREASE THE QUALITY OF STRUCTURE-BASED VIRTUAL SCREENING IN THE ESTROGEN RECEPTOR ALPHA LIGANDS IDENTIFICATION

Objective: Increase the predictive quality of the structure-based virtual screening (SBVS) protocol to identify potent ligands for estrogen receptoralpha (ERα).Methods: Employing recursive partition and regression tree (RPART) method to identify potent ligands for ERα among their decoys by using moleculardocking scores and the protein-ligand interaction fingerprint bitstrings as the predictors. These predictors were obtained from previously publishedSBVS campaign to identify potent ligands for ERα. The quality of the protocol by using RPART method was assessed by examining the enrichmentfactors and the accuracy in 95% level of confidence compared to the reference protocol.Results: The decision tree resulted from analysis using RPART method increased the enrichment factor and the accuracy values of the SBVS protocolfrom 18.5 to 247.9 and from 0.975 to 0.989, respectively. Notably, the accuracy value of the protocol using the decision tree was statistically significantin 95% level of confidence while the reference protocol was not.Conclusion: RPART method could lead to a significant increase of the SBVS quality to identify potent ligands for ERα.Keywords: Recursive partition and regression tree, Molecular docking, Interaction fingerprint, Estrogen receptor alpha.Â

VIRTUAL SCREENING CAMPAIGNS ON ISOFLAVONES TO DISCOVER POTENT CYCLOOXYGENASE-2 INHIBITORS

By employing recently published structure-based virtual screening (SBVS) to identify potent cyclooxygenase-2 (COX-2) inhibitors, all isoflavones collected by ZINC15 database were virtually screened. There were 3371 isoflavones in ZINC15 database and 1356 compounds out of them met the Lipinskis rule of 5. Notably, only 3 isoflavones out of those 1356 compounds were identified as potent COX-2 inhibitors

DOCKING STUDIES OF CURCUMIN AS A POTENTIAL LEAD COMPOUND TO DEVELOP NOVEL DIPEPTYDYL PEPTIDASE-4 INHIBITORS

ABSTRACT Interaction of curcumin to dipeptydyl peptidase-4 (DPP-4) has been studied by employing docking method using Molecular Operating Environment (MOE) and AutoDock as the docking software applications. Although MOE can sample more conformational spaces that represent the original interaction poses than AutoDock, both softwares serve as valid and acceptable docking applications to study the interactions of small compound to DPP-4. The calculatedfree energy of binding (AGblndlnsJ results from MOEand AutoDockshows that curcuminis neededto be optimizedto reachsimilaror betterAGbind/ng compareto the referencecompound.Curcumincan be consideredas a good lead compound in the development of new DPP-4 inhibitor. The results of these studies can serve as an initial effort of the further study

Molecular Dynamics Simulation of Serotonin Transport Protein Complex with 6-Hydroxy-1-Methyl-1,2,3,4-Tetrahydro-β-Carboline Ligand from Chocolate (Theobroma cacao L.) Isolate

6-hydroxy-1-methyl1,2,3,4-tetrahydro-β-carboline (6OHMTHβC) is a chocolate derivate that has antidepressant potency. It can increase dopamine and serotonin secretion, which leads to mood improvement. This method was carried out using computational molecular docking simulations (in silico). The research design was computational-based exploratory descriptive. The results of molecular docking showed the lowest energy score and the backbone RMSD value ≤2Å. The procedure performed was 6AWP receptor docking without ligand, with native ligand (6OHMTHβC), and with reference ligand (fluvoxamine). This study also performed molecular docking simulations of 6OHMTHβC towards 6AWP to find compounds in the receptor binding pocket. This study also performed dynamics simulations and identified the molecular determinants using PyPLIF-HIPPOS and YASARA Structure software 20.1.24.10 with the Windows 10 operating system. This study succeeded in determining the stability of the dynamics simulation of the serotonin transport protein complex with the reference ligand 6OHMTHβC for 50 ns, and this result corresponds to the RMSD value and binding energy. The determination of binding energy (BE) was calculated from the BE calculation available at YASARA and Ubuntu. The binding energy value of the original ligand was -11.6590 kJ/mol, and the reference ligand was -83880 kJ/mol. The highest RMSD value of the original ligand was 1.39292Å, while the RMSD value of the reference ligand was 1.71072Å. The essential amino acid carried out was 438Ser with hydrogen bond interactions, so 6OHMTHβC was considered a competent antidepressant candidate

UJI IN SILICO SENYAWA EMODIN SEBAGAI LIGAN PADA RESEPTOR ESTROGEN ALFA

Breast cancer is a disease with abnormal cell proliferation at breast tissue that can invade the surrounding tissue and spread to another organ. Based on WHO (2014) at 2012, there are 48,998 breast cancer cases on women in Indonesia with 19,730 death cases. In breast cancer, overexpression estrogen receptor alpha (ER-?) usually observed. Hence ER-? became the focus of prevention and therapy for breast cancer. In vitro study of emodin shows IC50 2.7 M and Ki 0.77 M on ER-?. In silico research using docking protocol and post docking analysis protocol shown that emodin was not an active ligand on ER-?. The outcome shown as ChemPLP score with average -75.292 and PLIF bitstring. Emodin binds with LEU346, LEU387, and ARG394 residue. Currently, the protocol that used in this research has yet identified marginal compound like emodin as an active ligand on ER-?

Quantitative Structure-Activity Relationship Analysis Of Curcumin And Its Derivatives As GST Inhibitors Based On Computational Chemistry Calculation = Analisis Hubungan Kuantitatif Struktur-Aktivitas Kurkumin dan...

ABSTRACT The Quantitative Structure-Activity Relationship (QSAR) study was established on curcumin and its derivatives as glutathione S-transferase(s) (GSTs) inhibitors using atomic net charges as the descriptors. The charges were resulted by semiempirical AM1 and PM3 quantum-chemical calculations using computational chemistry approach. The inhibition activity was expressed as the concentration that gave 50% inhibition of GSTs activity (IC50). The selection of the best QSAR equation models was determined by multiple linear regression analysis. This research was related to the nature of GSTs as multifunctional enzymes, which play an important role in the detoxification of electrophilic compounds, the process of inflammation and the effectivity of anticancer compounds. The result showed that AM1 semiempirical method gave better descriptor for the construction of QSAR equation model than PM3 did. The best QSAR equation model was described by : log 1/1050= -2,238 â 17,326 qC2⢠+ 1,876 gar + 9,200 qCs⢠The equation was significant at 95% level with statistical parameters : n = 10, m = 3, r = 0,839, SE = 0,254, F = 4,764, F/Frable = 1,001. Keywords: QSAR analysis, curcumin, glutathione S-transferase(s) (GSTs), atomic net charg