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• W2070290569 abstract "The reemergence of dengue outbreak demands an effective and efficient treatment especially for antiviral agent since neither vaccine nor drug is available to overcome this disease. This study designed the new model for Dengue Type-2 (DENV2) NS2B/NS3 protease inhibitor from quinoline scaffold by combining QSAR modeling with molecular docking. Genetic Function Approximation (GFA) method was used to construct the QSAR model showing good correlation coefficient (r 2 = 0.8996). The model was validated using Partial Least Square (PLS) analysis (r 2 = 0.861), Leave One Out - Cross Validation (LOO-CV with q 2 = 0.677) and external validation (r 2 = 0.854). The model was then used to design more quinoline derivatives by attaching more electron withdrawing group such as halogen and aldehyde. Ssearching for more diverse structure of protease inhibitors was carried out by screening out NCI database. Results showed that the QSAR model was able to predict the new protease inhibitor model with a nanomolar inhibition. The molecular docking was then performed to predict the binding mode of all protease inhibitor models and revealed that most of essential amino acid residues such as Ile36, His51, Ser135, Asp129, Tyr150, Gly151, Gly153 and Val154 significantly interact with the ligands. Based on the agreement between QSAR modeling and molecular docking results, the designed molecules were reported gaining insight activities as DENV2 NS2B/NS3 protease inhibitor." @default.
• W2070290569 created "2016-06-24" @default.
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• W2070290569 date "2015-01-01" @default.
• W2070290569 modified "2023-09-24" @default.
• W2070290569 title "Computational Design of Dengue Type-2 NS2B/NS3 Protease Inhibitor: 2D/3D QSAR of Quinoline and Its Molecular Docking" @default.
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• W2070290569 doi "https://doi.org/10.2991/iccst-15.2015.13" @default.
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