Biomedical subjects

Qing-You Zhang

Publications and source records attributed to Qing-You Zhang.

5 recordsLinked to original sources

PubMed2005

Automatic assignment of absolute configuration from 1D NMR data.

[reaction: see text] Opposite enantiomers exhibit different NMR properties in the presence of an external common chiral element, and a chiral molecule exhibits different NMR properties in the presence of external enantiomeric chiral elements. Automatic prediction of such differences, and comparison with experimental values, leads to the assignment of the absolute configuration. Here two cases are reported, one using a dataset of 80 chiral secondary alcohols esterified with (R)-MTPA and the corresponding (1)H NMR chemical shifts and the other with 94 (13)C NMR chemical shifts of chiral secondary alcohols in two enantiomeric chiral solvents. For the first application, counterpropagation neural networks were trained to predict the sign of the difference between chemical shifts of opposite stereoisomers. The neural networks were trained to process the chirality code of the alcohol as the input, and to give the NMR property as the output. In the second application, similar neural networks were employed, but the property to predict was the difference of chemical shifts in the two enantiomeric solvents. For independent test sets of 20 objects, 100% correct predictions were obtained in both applications concerning the sign of the chemical shifts differences. Additionally, with the second dataset, the difference of chemical shifts in the two enantiomeric solvents was quantitatively predicted, yielding r(2) 0.936 for the test set between the predicted and experimental values.

Alcohols↗

PubMed2004

[Interaction between endogenous nitric oxide and hydrogen sulfide in pathogenesis of hypoxic pulmonary hypertension].

OBJECTIVE: To investigate the interaction between nitric (NO) / nitric oxygenase (NOS) and hydrogen sulfide (H(2)S)/ cystathionine-gamma-lyase (CSE) system in the pathogenesis of hypoxic pulmonary hypertension. METHODS: 25 rats were randomly divided into four groups: hypoxic group (n=7 ), hypoxic + L-NAME group (n=6 ), hypoxic + PPG group (n=6) and control group (n=6 ). After 21 days, pulmonary artery mean pressure (mPAP) of each rat was evaluated, and the plasma concentration of H(2)S and NO was measured. Meanwhile, the activities of CSE in pulmonary tissue in hypoxic, hypoxic + L-NAME and control groups were detected, respectively, and expressions of NOS in pulmonary arteries in hypoxic, hypoxic + PPG and control groups were also detected by immunohistochemistry technique. RESULTS: mPAP was significantly increased in hypoxic rats as compared with normal controls. Meanwhile, compared with controls, the production of NO and H(2)S in plasma, the activity of CSE in pulmonary tissue and expression of NOS in pulmonary arteries were markedly decreased in hypoxic rats. However, mPAP was significantly increased in hyopxic + L-NAME group as compared with hypoxic groups, and at the same time, the plasma concentration of NO was markedly decreased. However, the plasma concentration of H(2)S and the activity of CSE in pulmonary tissue in hyopxic+L-NAME group were increased significantly as compared with those of hypoxic group. PPG also worsened pulmonary hypertension of hypoxic rats, however,it increased endogenous production of NO and the expression of NOS of pulmonary arteries obviously. CONCLUSION: There is a negative feed back effect between NO/NOS system and H(2)S/CSE system in development of hypoxic pulmonary hypertension. They might interact with each other and therefore play an important regulating role in hypoxic pulmonary hypertension.

Animals↗

PubMedDate not supplied

Correlation analysis of the structures and stability constants of gadolinium(III) complexes.

To simplify the abstraction of descriptors, for the correlation analysis of the stability constants of gadolinium(III) complexes and their ligand structures, aiming at gadolinium(III) complexes, we only considered the ligands and ignored the common parts of the structures, i.e., the metal ions. Quantum-chemical descriptors and topological indices were calculated to describe the structures of the ligands. Multiple regression analysis and neural networks were applied to construct the models between the ligands and the stability constants of gadolinium(III) complexes and satisfactory results were obtained.

Contrast Media↗

PubMedDate not supplied

Structure-based classification of chemical reactions without assignment of reaction centers.

The automatic classification of chemical reactions is of high importance for the analysis of reaction databases, reaction retrieval, reaction prediction, or synthesis planning. In this work, the classification of photochemical reactions was investigated with no explicit assignment of the reacting centers. Classifications were explored with Random Forests or Kohonen neural networks in three different situations, using different levels of information: (a) pairs of reactants were classified according to the type of reaction they produce, (b) products were classified according to the type of reaction from which they can be synthesized, and (c) reactions were classified from the difference between the descriptors of the product and the descriptors of the reactants. In all cases molecular maps of atom-level properties (MOLMAPs) were used as descriptors. They are generated by a self-organizing map and encode physicochemical properties of the bonds available in a molecule. Correct classification could be achieved for approximately 90% of the 78 reactions in an independent test set.

Journal Article↗

PubMedDate not supplied

Physicochemical stereodescriptors of atomic chiral centers.

Physicochemical atomic stereodescriptors (PAS) were implemented that represent the chirality of an atomic chiral center on the basis of empirical physicochemical properties of the ligands. The ligands are ranked according to a specific property, and the chiral center takes an S/R-like descriptor relative to that property. The procedure is performed for a series of properties, yielding a chirality profile. Application of the PAS descriptors to the prediction of enantioselectivity in chemical reactions, from the molecular structures, is illustrated here. The relationship between the molecular structures, represented by the PAS descriptors, and the enantioselectivity was learned by neural networks, decision trees, or random forests. In a first application, a data set was employed with chiral amino alcohols that enantioselectively catalyze the addition of diethylzinc to benzaldehyde. Prediction of the major enantiomer obtained in the reaction, from the molecular structure of the catalyst, was achieved with accuracy up to 90%. The second application investigated the enantiopreference of Pseudomonas cepacia lipase (PCL) toward primary alcohols. The learned models could make correct predictions about the preferred enantiomer, from the molecular structure of the substrate, in up to 93% of the cases. These included substrates with and without O-atoms bonded to the chiral center. The properties automatically selected to build the models can give indications on the relevant factors guiding the observed chemical behavior.

Alcohols↗