HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL

Cancer is a disease that can cause high mortality in the world. One of them is colorectal cancer that is the third most common cancer that cause a death in the world. Some alkaloid derivative ®??????¸ ??-carboline) has been fought and confirmed that have good activity again colorectal cancer cell...

Full description

Saved in:
Bibliographic Details
Main Author: Wijaya, Grady
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/44322
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:44322
spelling id-itb.:443222019-10-10T10:20:02ZHUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL Wijaya, Grady Indonesia Final Project Colorectal cancer, QSAR, carboline, derivatives, Bcl-2 receptor INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/44322 Cancer is a disease that can cause high mortality in the world. One of them is colorectal cancer that is the third most common cancer that cause a death in the world. Some alkaloid derivative ®??????¸ ??-carboline) has been fought and confirmed that have good activity again colorectal cancer cell with apoptotic mechanism. The purpose of this research was to obtain a new ¸±?ð? ?ð?±?®??????¸ ?» ?-carboline with a lower IC50 prediction and good binding afinity with apoptotic induction receptor (Bcl-2) based on mathematic equation Quantitative Structure- Activity Relationship (QSAR) on in silico studies. A training set compounds of QSAR were designed using GaussView 5.0.8 and were optimized with Gauss 09W. A descriptor value of optimized compounds were computed by MOE 2014.09. The data of descriptor value were analyzed using statistic and validated based on their correlation coeficient, Fischer criteria, and Leave One Out (LOO) method with SPSS Statistics 22.0 to obtain the best QSAR equation. The best QSAR equation ?» ?-carboline derivatives is Log 1/IC50 (µM) = ?5,865(±0,994) ?0,156(±0,143) x LogP(o/w) + 0,074(±0,067) x AM1_dipole + 3,233(±2,119) x glob + 0,513(±0,104) x mr. The new derivatives compound were design using Topliss scheme or Craig plot and has been obtain 7 compound that have IC50 prediction lower than the parent compound (Methyl-9-(3,4,5-trimethoxybenzyl)-9Hpyrido[2,3-b]indole-3-carboxylate). Docking studies of natural ligand, parent compound, and new derivatives compound to Bcl-2 receptor using Autodock 4.2.6, shown that 11 new derivatives compounds had more negative binding energy and higher affinity to Bcl-2 receptor. Compound 11_2, 11_7, and 11_8 have the lower IC50 prediction and higher affinity to Bcl-2 receptor than parent compound. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Cancer is a disease that can cause high mortality in the world. One of them is colorectal cancer that is the third most common cancer that cause a death in the world. Some alkaloid derivative ®??????¸ ??-carboline) has been fought and confirmed that have good activity again colorectal cancer cell with apoptotic mechanism. The purpose of this research was to obtain a new ¸±?ð? ?ð?±?®??????¸ ?» ?-carboline with a lower IC50 prediction and good binding afinity with apoptotic induction receptor (Bcl-2) based on mathematic equation Quantitative Structure- Activity Relationship (QSAR) on in silico studies. A training set compounds of QSAR were designed using GaussView 5.0.8 and were optimized with Gauss 09W. A descriptor value of optimized compounds were computed by MOE 2014.09. The data of descriptor value were analyzed using statistic and validated based on their correlation coeficient, Fischer criteria, and Leave One Out (LOO) method with SPSS Statistics 22.0 to obtain the best QSAR equation. The best QSAR equation ?» ?-carboline derivatives is Log 1/IC50 (µM) = ?5,865(±0,994) ?0,156(±0,143) x LogP(o/w) + 0,074(±0,067) x AM1_dipole + 3,233(±2,119) x glob + 0,513(±0,104) x mr. The new derivatives compound were design using Topliss scheme or Craig plot and has been obtain 7 compound that have IC50 prediction lower than the parent compound (Methyl-9-(3,4,5-trimethoxybenzyl)-9Hpyrido[2,3-b]indole-3-carboxylate). Docking studies of natural ligand, parent compound, and new derivatives compound to Bcl-2 receptor using Autodock 4.2.6, shown that 11 new derivatives compounds had more negative binding energy and higher affinity to Bcl-2 receptor. Compound 11_2, 11_7, and 11_8 have the lower IC50 prediction and higher affinity to Bcl-2 receptor than parent compound.
format Final Project
author Wijaya, Grady
spellingShingle Wijaya, Grady
HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL
author_facet Wijaya, Grady
author_sort Wijaya, Grady
title HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL
title_short HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL
title_full HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL
title_fullStr HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL
title_full_unstemmed HUBUNGAN KUANTITATIF STRUKTUR-AKTIVITAS (HKSA) TURUNAN ?-KARBOLIN SEBAGAI KANDIDAT SENYAWA ANTIKANKER KOLOREKTAL
title_sort hubungan kuantitatif struktur-aktivitas (hksa) turunan ?-karbolin sebagai kandidat senyawa antikanker kolorektal
url https://digilib.itb.ac.id/gdl/view/44322
_version_ 1821999125381513216