Toward an improved discrimination of outer membrane proteins using a sequence-based approach.

This article offers a novel sequence-based approach to discriminate outer membrane proteins (OMPs). The first step is to use a new representation approach, factor analysis scales of generalized amino acid information (FASGAI) representing hydrophobicity, alpha and turn propensities, bulky properties, compositional characteristics, local flexibility and electronic properties, etc., to characterize sequences of OMPs and non-OMPs.

Structure-activity relationship of flavonoids active against lard oil oxidation based on quantum chemical analysis.

In this study, the antioxidant activities of 15 flavonoids against lard oil oxidation were determined by using the Rancimat test. Quercetin, dihydromyricetin, luteolin and kaempferol showed the strongest antioxidant activity, with protection factor values (PF) of 11.50, 11.

Three-dimensional holographic vector of atomic interaction field for quantitative structure-activity relationship of Aza-bioisosteres of anthrapyrazoles (Aza-APs).

A newly developed descriptor, three-dimensional holographic vector of atomic interaction field (3D-HoVAIF), is used to describe the chemical structures of Aza-bioisosteres of anthrapyrazoles (Aza-APs). 3D-HoVAIF contains three non-bonded (electrostatic, van der Waals and hydrophobic) factors, which are directly related to bioactivities and utilized to express intramolecular potential energies, employed to several different models on 35 anticancer agents Aza-APs. After variable screening by stepwise multiple regression (SMR) technique, a partial least square (PLS) regression model is built with 3D-HoVAIF.

Recognition for avian influenza virus proteins based on support vector machine and linear discriminant analysis.

Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influenza virus (AIV) were developed using support vector machine (SVM) and linear discriminant analysis (LDA). The results obtained from LDA are as follows: the identification accuracy ( ) for training samples is 99.

[Quantitative structure-activity relationship study of tetrahydroimidazobenzodiazepinone anti-HIV drug using three-dimensional holographic vector of atomic interaction field].

Aim: To study the quantitative structure-activity relationship ( QSAR) of 23 tetrahydroimidazobenzodiazepinone (TIBO) as anti-HIV drug.

Methods: A newly developed three-dimensional holographic vector of atomic interaction field (3D-HoVAIF) was used to describe the chemical structure of anti-HIV drug-23 TIBO, a partial least square regression (PLS) model was built.

Results: The obtained model with the cumulative multiple correlation coefficient (Rcum(2)), cumulative cross-validated (Qcum(2)) and standard error of estimation (SD) were Rcum(2) = 0.