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...
Saved in:
Main Author: | |
---|---|
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 |