Pemodelan dan Analisis Hubungan kuantitatif struktur dan aktivitas (QSAR/HKSA) dan Desain Senyawa Baru

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Authors: Rahadian Zainul, Yaktinafi Salavia, Iffat Syafiqoh Afif
Cited by: 0

Abstract

QSAR modeling is a computational chemistry approach that quantitatively links molecular structure to biological activity or physicochemical properties, enabling rational design of new compounds. By utilizing molecular descriptors that represent topological, electronic, geometric, and physicochemical features, QSAR models can identify key structural factors influencing activity. The modeling process involves data preprocessing, statistical or machine-learning analysis, and rigorous validation to ensure predictive reliability. Validated QSAR models allow efficient prediction and optimization of new compounds while reducing experimental cost and time. Consequently, QSAR plays a crucial role in modern drug discovery, agrochemical development, and chemical risk assessment.

Fields of Study & Subjects

Computational Drug Discovery Methods Machine Learning in Materials Science Advanced Chemical Physics Studies

Publication details

Journal / source
OSF Preprints (OSF Preprints)
Publication date
1 January 2026
Document type
Preprint