Biomedical subjects

Mingyue Zheng

Publications and source records attributed to Mingyue Zheng.

6 recordsLinked to original sources

PubMed2006

QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR.

The recent wide spreading of the H5N1 avian influenza virus (AIV) in Asia, Europe and Africa and its ability to cause fatal infections in human has raised serious concerns about a pending global flu pandemic. Neuraminidase (NA) inhibitors are currently the only option for treatment or prophylaxis in humans infected with this strain. However, drugs currently on the market often meet with rapidly emerging resistant mutants and only have limited application as inadequate supply of synthetic material. To dig out helpful information for designing potent inhibitors with novel structures against the NA, we used automated docking, CoMFA, CoMSIA, and HQSAR methods to investigate the quantitative structure-activity relationship for 126 NA inhibitors (NIs) with great structural diversities and wide range of bioactivities against influenza A virus. Based on the binding conformations discovered via molecular docking into the crystal structure of NA, CoMFA and CoMSIA models were successfully built with the cross-validated q (2) of 0.813 and 0.771, respectively. HQSAR was also carried out as a complementary study in that HQSAR technique does not require 3D information of these compounds and could provide a detailed molecular fragment contribution to the inhibitory activity. These models also show clearly how steric, electrostatic, hydrophobicity, and individual fragments affect the potency of NA inhibitors. In addition, CoMFA and CoMSIA field distributions are found to be in well agreement with the structural characteristics of the corresponding binding sites. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction should be useful in developing novel potent NA inhibitors.

Amino Acid Sequence↗

PubMed2006

Towards discovering dual functional inhibitors against both wild type and K103N mutant HIV-1 reverse transcriptases: molecular docking and QSAR studies on 4,1-benzoxazepinone analogues.

To find useful information for discovering dual functional inhibitors against both wild type (WT) and K103N mutant reverse transcriptases (RTs) of HIV-1, molecular docking and 3D-QSAR approaches were applied to a set of twenty-five 4,1-benzoxazepinone analogues of efavirenz (SUSTIVA), some of them are active against the two RTs. 3D-QSAR models were constructed, based on their binding conformations determined by molecular docking, with r(2)(cv) values ranging from 0.656 to 0.834 for CoMFA and CoMSIA, respectively. The models were then validated to be highly predictive and extrapolative by inhibitors in two test sets with different molecular skeletons. Furthermore, CoMFA models were found to be well matched with the binding sites of both WT and K103N RTs. Finally, a reasonable pharmacophore model of 4,1-benzoxazepinones were established. The application of the model not only successfully differentiated the experimentally determined inhibitors from non-inhibitors, but also discovered two potent inhibitors from the compound database SPECS. On the basis of both the 3D-QSAR and pharmacophore models, new clues for discovering and designing potent dual functional drug leads against HIV-1 were proposed: (i) adopting positively charged aliphatic group at the cis-substituent of C3; (ii) reducing the electronic density at the position of O4; (iii) positioning a small branched aliphatic group at position of C5; (iv) using the negatively charged bulky substituents at position of C7.

Drug Design↗

PubMed2006

Syntheses of triazole-modified zanamivir analogues via click chemistry and anti-AIV activities.

Sixteen novel 4-triazole-modified zanamivir (1) analogues were synthesized using the click reactions, and their inhibitory activities against avian influenza virus (AIV, H5N1) were determined. Compound 3b exerts promising inhibitory activity with EC(50) of 6.4 microM, which is very close to that of zanamivir (EC(50) = 2.8 microM). Molecular modeling provided the information about the binding model between inhibitors and neuraminidase, which are in good agreement with inhibitory activities.

Antiviral Agents↗

PubMed2006

Mutagenic probability estimation of chemical compounds by a novel molecular electrophilicity vector and support vector machine.

MOTIVATION: Mutagenicity is among the toxicological end points that pose the highest concern. The accelerated pace of drug discovery has heightened the need for efficient prediction methods. Currently, most available tools fall short of the desired degree of accuracy, and can only provide a binary classification. It is of significance to develop a discriminative and informative model for the mutagenicity prediction. RESULTS: Here we developed a mutagenic probability prediction model addressing the problem, based on datasets covering a large chemical space. A novel molecular electrophilicity vector (MEV) is first devised to represent the structure profile of chemical compounds. An extended support vector machine (SVM) method is then used to derive the posterior probabilistic estimation of mutagenicity from the MEVs of the training set. The results show that our model gives a better performance than TOPKAT (http://www.accelrys.com) and other previously published methods. In addition, a confidence level related to the prediction can be provided, which may help people make more flexible decisions on chemical ordering or synthesis. AVAILABILITY: The binary program (ZGTOX_1.1) based on our model and samples of input datasets on Windows PC are available at http://dddc.ac.cn/adme upon request from the authors.

Algorithms↗

PubMed2006

Essential structural profile of a dual functional inhibitor against cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX): molecular docking and 3D-QSAR analyses on DHDMBF analogues.

It is recently proposed that compounds with equal capabilities of inhibiting COX and 5-LOX, both are key enzymes involved in the arachidonic acid (AA) cascade, are expected to be safer non-steroidal anti-inflammatory drugs (NSAIDs). To dig out helpful information in designing dual functional inhibitors against the two enzymes, homology modeling, molecular dynamics (MD) simulations, automated docking, and 3D-QSAR analyses were performed in this study on 21 COX-2/5-LOX dual inhibitors, namely, 7-tert-butyl-2,3-dihydro-3,3-dimethylbenzofuran (DHDMBF) analogues. A 3D-model of 5-LOX was built based on the high-resolution X-ray structure of rabbit reticulocyte 15-lipoxygenase. Molecular docking was then applied to locate the binding orientations and conformations of DHDMBF analogues with COX-2 and 5-LOX, respectively, leading to highly predictive CoMFA models constructed on the basis of the binding conformations with q2 values of 0.782 and 0.634 for COX-2 and 5-LOX, respectively. In addition, CoMFA field distributions were found in good agreement with the structural characteristics of the corresponding binding sites. Both the docking simulations and QSAR analyses suggest that new potent dual inhibitors should share a structural feature with a moderately bulky group at R2 position and a rather negatively charged group around the position of the carbonyl group of DHDMBFs. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction should be useful in developing new NSAIDs as anti-inflammation drugs with favorable safety profile.

Amino Acid Sequence↗

PubMedDate not supplied

Focused combinatorial library design based on structural diversity, druglikeness and binding affinity score.

The advent of focused library and virtual screening has reduced the disadvantage of combinatorial chemistry and changed it to a realizable and cost-effective tool in drug discovery. Usually, genetic algorithms (GAs) are used to quickly finding high-scoring molecules by sampling a small subset of the total combinatorial space. Therefore, scoring functions play essential roles in focused library design. Reported here is our initial attempt to establish a new approach for generating a target-focused library using the combination of the scores of structural diversity and binding affinity with our newly improved drug-likeness scoring functions. Meanwhile, a software package, named LD1.0, was developed on the basis of the new approach. One test on a cyclooxygenase (COX)2-focused library successfully reproduced the structures that have been experimentally studied as COX2-selective inhibitors. Another test is on a peroxisome proliferator-activated receptors gamma-focused library design, which not only reproduces the key fragments in the approved (thiazolidinedione) TZD drugs, but also generates some new structures that are more active than the approved drugs or published ligands. Both of the two tests took approximately 15% of the running time of the ordinary molecular docking method. Thus, our new approach is an effective, reliable, and practical way for building up a properly sized focused library with a high hit rate, novel structure, and good ADME/T profile.

Algorithms↗