Quantitative Sequence-Activity Model (QSAM): Applying QSAR Strategy to Model and Predict Bioactivity and Function of Peptides, Proteins and Nucleic Acids

Title: Quantitative Sequence-Activity Model (QSAM): Applying QSAR Strategy to Model and Predict Bioactivity and Function of Peptides, Proteins and Nucleic Acids

Volume: 4 Issue: 4

Author(s): Peng Zhou, Feifei Tian, Yuqian Wu, Zhiliang Li and Zhicai Shang

Affiliation:

Keywords: QSAM, QSAR, biosequence, structural characterization, statistical modeling

Abstract: Traditional quantitative structure-activity relationship (QSAR) is a term describing a variety of approaches that are of substantial interest for chemistry. Quantitative sequence-activity model (QSAM), applying QSAR strategy to explore sequence-activity/function relationship for biosystems, is greatly meaningful but meanwhile extremely difficult. For biomolecules, high molecular weight, diverse structural morphology and intricate interaction network all bring in traditional QSAR methodologies unprecedented challenges. This article comprehensively reviewed developing process, current state and future perspective of QSAM, concerning its applications into fields of pharmacy, food science, immunology and molecular biology. Besides, discipline-crossing and amalgamation of QSAM with QSAR, bioinformatics and computational biology were also discussed.

Cite this article as:

Zhou Peng, Tian Feifei, Wu Yuqian, Li Zhiliang and Shang Zhicai, Quantitative Sequence-Activity Model (QSAM): Applying QSAR Strategy to Model and Predict Bioactivity and Function of Peptides, Proteins and Nucleic Acids, Current Computer-Aided Drug Design 2008; 4 (4) . https://dx.doi.org/10.2174/157340908786785994