Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Riset Ilmu Kesehatan Umum dan Farmasi
Nurul Sulistia Azzahra
Unknown Affiliation
Health Professions Public Health

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Literatur Review: Strategi dan Perkembangan Computer-Aided Drug Design (Cadd) untuk Identifikasi Lead Compound Antikanker dalam Konteks Kimia Medisinal dan Farmasi Nurul Sulistia Azzahra; Saeful Amin
Jurnal Riset Ilmu Kesehatan Umum dan Farmasi (JRIKUF) Vol. 3 No. 4 (2025): Oktober : Jurnal Riset Ilmu Kesehatan Umum dan Farmasi (JRIKUF)
Publisher : LPPM STIKES KESETIAKAWANAN SOSIAL INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57213/jrikuf.v3i4.875

Abstract

Cancer remains the second leading cause of death worldwide, while conventional therapies are often limited by toxicity, resistance, and high costs. Advances in bioinformatics and artificial intelligence have established Computer-Aided Drug Design (CADD) as an efficient tool for modern drug discovery. Integrating medicinal chemistry, structural biology, and computational modeling, CADD accelerates the identification and optimization of anticancer candidates through in silico approaches such as molecular docking, molecular dynamics, QSAR, and pharmacophore modeling. This review systematically analyzed literature from PubMed, ScienceDirect, ResearchGate, and Google Scholar (2015–2025) focusing on in silico studies related to anticancer drug design. Selected articles were evaluated based on molecular targets, compound types, CADD techniques, and major findings.The results reveal that CADD effectively identifies natural and synthetic compounds targeting key cancer proteins including EGFR, CDK2, PI3K/Akt/mTOR, and p53. Integration with artificial intelligence enhances screening efficiency, prediction accuracy, and ADMET assessment. Overall, CADD represents a crucial strategy to accelerate the discovery of selective and clinically promising anticancer drugs.
Co-Authors Saeful Amin