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QSAR×Uundaji wa Farmakofori×
NyanjaBioinformatikiBioinformatiki
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili19641977
MwanzilishiCorwin HanschPeter Gund
AinaRegression-based predictive modeling pipelinePattern-based virtual screening pipeline
Chanzo asiliaHansch, C. & Fujita, T. (1964). Rho-sigma-pi analysis. A method for the correlation of biological activity and chemical structure. Journal of the American Chemical Society, 86(8), 1616-1626. DOI ↗Wermuth, C. G., Ganellin, C. R., Lindberg, P., & Mitscher, L. A. (1998). Glossary of terms used in medicinal chemistry. Pure and Applied Chemistry, 70(5), 1129-1143. DOI ↗
Majina mbadalaQSAR model, quantitative structure-activity relationshippharmacophore pattern recognition, 3D pharmacophore
Zinazohusiana33
MuhtasariQuantitative Structure-Activity Relationship (QSAR) modeling predicts biological activity from molecular structure using statistical or machine learning models. Pioneered by Hansch in 1964, QSAR correlates numerical molecular descriptors with measured bioactivity, enabling prediction of activity for untested compounds and rational lead optimization.Pharmacophore modeling identifies the spatial arrangement of molecular features (hydrogen bond donors, acceptors, aromatic rings) that are essential for biological activity. Introduced by Gund in 1977, this ligand-based method creates a three-dimensional pattern that can screen chemical libraries and design new active compounds without requiring receptor structure.
ScholarGateSeti ya data
  1. v1
  2. 3 Vyanzo
  3. PUBLISHED
  1. v1
  2. 3 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: QSAR · Pharmacophore Modeling. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare