Ubiquitous D-alanylation of lipoteichoic acids modulates the surface charge and ligand binding of the gram-positive cell wall. Disruption of the bacterial DltABCD gene involved in teichoic acid alanylation, as well as inhibition of the DltA protein, has been shown to increase a gram-positive bacterium's susceptibility to antibiotics. The DltA D-alanyl carrier protein ligase promotes a two-step process starting with adenylation of D-alanine. We have determined the 2.0 A resolution crystal structure of a DltA protein from Bacillus cereus in complex with the D-alanine adenylate intermediate of the first reaction. Despite the low level of sequence similarity, the DltA structure resembles known structures of adenylation domains such as the acetyl-CoA synthetase. The enantiomer selection appears to be enhanced by the medium-sized side chain of Cys-269. The Ala-269 mutant protein shows marked loss of such selection. The network of noncovalent interactions between the D-alanine adenylate and DltA provides structure-based rationale for aiding the design of tight-binding DltA inhibitors for combating infectious gram-positive bacteria such as the notorious methicillin-resistant Staphylococcus aureus.

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A new drug design method, the multiple field three-dimensional quantitative structure-activity relationship (MF-3D-QSAR), is proposed. It is a combination and development of classical 2D-QSAR and traditional 3D-QSAR. In addition to the electrostatic and van der Waals potentials, more potential fields (such as lipophilic potential, hydrogen bonding potential, and nonthermodynamic factors) are integrated in the MF-3D-QSAR. Meanwhile, a principal component analysis (PCA) and iterative double least square (IDLS) technique is developed for predicting the bioactivity of query drug candidates. As an example, the MF-3D-QSAR is applied to the design of neuraminidase inhibitor and to prove its predictive power, and some useful findings are obtained for developing drugs against influenza virus.

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus.

Barley contains hydroxycinnamic acids, mainly ferulic acid (FA; 3-methoxy-4-hydroxycinnamic acid) and p-coumaric acid (PCA; 4-hydroxycinnamic acid). Ferulic acid is produced via the phenylpropanoid biosynthetic pathway and covalently cross-linked to polysaccharides by ester bonds and to components of lignin mainly by ether bonds. Various studies have consistently indicated that FA is among the factors most inhibitory to the biodegradability of cell wall polysaccharides. p-Coumaric acid is also covalently linked to polysaccharides (minor) and lignin (major), but does not form the inhibitory cross-linkages as FA does and is considered to represent cell wall lignification. The objectives in this study were to (1) determine genotypic differences in physicochemical characteristics in terms of (a) two major low molecular weight hydroxycinnamic acid profiles (FA, PCA, PCA-to-FA ratio, which are associated with digestion and lignification), (b) particle size distributions (mean, median), (c) hull content, and (d) digestion-resistant fiber fractions and (2) determine genotypic differences in in situ solubilization kinetics of FA and PCA. The barley varieties grown during three consecutive years (2003, 2004, and 2005) included AC Metcalfe, CDC Dolly, McLeod, CDC Helgason, CDC Trey, and CDC Cowboy. These barleys were grown at the Kernen Crop Research Farm (KCRF, University of Saskatchewan) and managed using standard agronomic production practices. Results showed that there were significant differences in hull content (P < 0.05) among the barley varieties, with Mcleod having the highest (11% DM) and CDC Dolly and CDC Helgason the lowest hull content (9% DM). Ferulic acid ranged from 555 to 663 microg/g of DM (P < 0.05). p-Coumaric acid ranged (P < 0.05) from 283 to 345 microg/g of DM. PCA-to-FA ratios ranged (P < 0.05) from 0.49 to 0.56. Mean particle size ranged (P < 0.05) from 3.06 to 3.66 mm, and median particle size ranged (P < 0.05) from 2.71 to 3.04 mm. In situ DM degradability ranged from 44 to 49%. In situ solubilized FA fractions ranged (P < 0.05) from 60 to 72% and of PCA ranged (P < 0.05) from 71 to 81%. In conclusion, CDC Dolly was best and McLeod barley was poorest as feed barley in terms of hull and FA contents. There were significant genotypic differences in FA, PCA and their ratio, hull content, particle size distribution, and in situ solubilization of FA and PCA among the barley varieties.