A New Descriptor of Amino Acids‐SVGER and its Applications in Peptide QSAR. Issue 5 (14th October 2016)

• Record Type: Journal Article
• Authors: Tong, Jianbo; Li, Lingxiao; Bai, Min; Li, Kangnan
• Is Part Of: Molecular informatics. Volume 36:Issue 5/6(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-10-14
• Subjects: Descriptor -- Multiple linear regression -- Partial least square regression -- Peptide drugs -- QSAR; Cheminformatics -- Periodicals; QSAR (Biochemistry) -- Periodicals; Structure-activity relationships (Biochemistry) -- Periodicals; Drugs -- Structure-activity relationships -- Periodicals; 615.19
• DOI: 10.1002/minf.201501023
• Languages: English
• ISSNs: 1868-1743

Abstract

Abstract: In the study of peptide quantitative structure activity relationship (QSAR), a new descriptor of amino acids (SVGER) was calculated. It was applied in two peptides which are angiotensin converting enzyme inhibitors and bitter tasting threshold of di‐peptide. QSAR models were built by stepwise multiple regression‐multiple linear regression (SMR‐MLR) and stepwise multiple regression‐partial least square regression (SMR‐PLS). In the SMR‐MLR models for angiotensin converting enzyme inhibitors, the squared cross‐validation correlation coefficient ( Q LOO 2 ) was 0.907, squared correlation coefficient between predicted and observed activities ( R cum 2 ) was 0.977 and external multiple correlation coefficient ( Q ext 2 ) was 0.867. The corresponding data for the bitter tasting threshold of di‐peptide were 0.802, 0.966, 0.719. While in the SMR‐PLS model, Q LOO 2, R cum 2 and Q ext 2 were 0.804, 0.915, 0.858 for angiotensin converting enzyme inhibitors and 0.782, 0.881, 0.747 for bitter tasting threshold of di‐peptide. Our results showed that descriptor SVGER can afford good account of relationships between activity and structure of peptide drugs. Abstract :