Beijing Science and Technology Project and Beijing Nova Program.

Molecular descriptors represent structural and physicochemical features of compounds. They have been extensively used for developing statistical models, such as quantitative structure activity relationship (QSAR) and artificial neural networks (NN), for computer prediction of the pharmacodynamic, pharmacokinetic, or toxicological properties of compounds from their structure. While computer programs have been developed for computing molecular descriptors, there is a lack of a freely accessible one. We have developed a web-based server, MODEL (Molecular Descriptor Lab), for computing a comprehensive set of 3,778 molecular descriptors, which is significantly more than the approximately 1,600 molecular descriptors computed by other software. Our computational algorithms have been extensively tested and the computed molecular descriptors have been used in a number of published works of statistical models for predicting variety of pharmacodynamic, pharmacokinetic, and toxicological properties of compounds. Several testing studies on the computed molecular descriptors are discussed. MODEL is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/model/model.cgi free of charge for academic use.

Objective: To explore the clinical efficacy and safety of Qigong in reducing the self-rating depression scale (SDS) and self-rating anxiety scale (SAS) scores of patients with chronic obstructive pulmonary disease (COPD). Methods: We searched CNKI, Wan fang, Chongqing VIP, China Biology Medicine disc, PubMed, Cochrane Library, and EMBASE for studies published as of Dec 31, 2018. All randomized controlled trials of Qigong in COPD patients, which met the inclusion criteria were included. The Cochrane bias risk assessment tool was used for literature evaluation. RevMan 5.3 software was used for meta-analysis. Results: Six studies (combined n = 415 patients) met the inclusion criteria. Compared with conventional therapy alone, Qigong in combination with conventional therapy significantly improved the following outcome measures: SDS score [mean difference (MD) −3.99, 95% CI (−6.17, −1.82), P < .001, I 2 = 69%]; SAS score[MD −4.57, 95% CI (−5.67, −3.48), P < .001, I 2 = 15%]; forced expiratory volume in one second/prediction (FEV 1 % pred) [MD 3.77, 95% CI (0.97,6.58), P < .01, I 2 = 0]; forced expiratory volume in one second (FEV 1 ) [MD 0.21, 95% CI (0.13, 0.30), P < .001, I 2 = 0%]; forced vital capacity (FVC) [MD 0.28, 95% CI (0.16, 0.40), P < .001, I 2 = 0]; 6-minute walk test (6MWT) distance [MD 39.31, 95% CI (18.27, 60.34), P < .001, I 2 = 32%]; and St. George's Respiratory Questionnaire (SGRQ) total score [MD −11.42, 95% CI (−21.80, −1.03), P < .05, I 2 = 72%]. Conclusion: Qigong can improve the SDS and SAS scores of COPD patients, and has auxiliary effects on improving lung function, 6MWT distance, and SGRQ score.

Abstract:The metabotropic glutamate subtype 1 (mGluR1), a member of the metabotropic glutamate receptors, is a therapeutic target for neurological disorders. However, due to the lower subtype selectivity of mGluR1 orthosteric compounds, a new targeted strategy, known as allosteric modulators research, is needed for the treatment of mGluR1-related diseases. Recently, the structure of the seven-transmembrane domain (7TMD) of mGluR1 has been solved, which reveals the binding site of allosteric modulators and provides an opportunity for future subtype-selectivity drug design. In this study, a series of computer-aided drug design methods were utilized to discover potential mGluR1 negative allosteric modulators (NAMs). Pharmacophore models were constructed based on three different structure types of mGluR1 NAMs. After validation using the built-in parameters and test set, the optimal pharmacophore model of each structure type was selected and utilized as a query to screen the Traditional Chinese Medicine Database (TCMD). Then, three different hit lists of compounds were obtained. Molecular docking was used based on the latest crystal structure of mGluR1-7TMD to further filter these hits. As a compound with high QFIT and LibDock Score was preferred, a total of 30 compounds were retained. MD simulation was utilized to confirm the stability of potential compounds binding. From the computational results, OPEN ACCESSMolecules 2015, 20 12770 thesinine-4ʹ-O-β-D-glucoside, nigrolineaxanthone-P and nodakenin might exhibit negative allosteric moderating effects on mGluR1. This paper indicates the applicability of molecular simulation technologies for discovering potential natural mGluR1 NAMs from Chinese herbs.