Template-based de novo design for type II kinase inhibitors and its extented application to acetylcholinesterase inhibitors

Hypothalamic and ovarian transcriptome profiling reveals potential candidate genes in low and high egg production of white Muscovy ducks (Cairina moschata)

In China, the low egg production rate is a major challenge to Muscovy duck farmers. Hypothalamus and ovary play essential role in egg production of birds. However, there are little or no reports from these tissues to identify potential candidate genes responsible for egg production in White Muscovy ducks. A total of 1,537 laying ducks were raised; the egg production traits which include age at first egg (days), number of eggs at 300 d, and number of eggs at 59 wk were recorded. Moreover, 4 lowest (LP) and 4 highest producing (HP) were selected at 59 wk of age, respectively. To understand the mechanism of egg laying regulation, we sequenced the hypothalamus and ovary transcriptome profiles in LP and HP using RNA-Seq. The results showed that the number of eggs at 300 d and number of eggs at 59 wk in the HP were significantly more (P < 0.001) than the LP ducks. In total, 106.98G clean bases were generated from 16 libraries with an average of 6.68G clean bases for each library. Further analysis showed 569 and 2,259 differentially expressed genes (DEGs) were identified in the hypothalamus and ovary between LP and HP, respectively. The KEGG pathway enrichment analysis revealed 114 and 139 pathways in the hypothalamus and ovary, respectively which includes Calcium signaling pathway, ECM-receptor interaction, Focal adhesion, MAPK signaling pathway, Apoptosis and Apelin signaling pathways that are involved in egg production. Based on the GO terms and KEGG pathways results, 10 potential candidate genes (P2RX1, LPAR2, ADORA1, FN1, AKT3, ADCY5, ADCY8, MAP3K8, PXN, and PTTG1) were identified to be responsible for egg production. Further, protein-protein interaction was analyzed to show the relationship between these candidate genes. Therefore, this study provides useful information on transcriptome of hypothalamus and ovary of LP and HP Muscovy ducks.

MoleGear: A Java-Based Platform for Evolutionary De Novo Molecular Design

A Java-based platform, MoleGear, is developed for de novo molecular design based on the chemistry development kit (CDK) and other Java packages. MoleGear uses evolutionary algorithm (EA) to explore chemical space, and a suite of fragment-based operators of growing, crossover, and mutation for assembling novel molecules that can be scored by prediction of binding free energy or a weighted-sum multi-objective fitness function. The EA can be conducted in parallel over multiple nodes to support large-scale molecular optimizations. Some complementary utilities such as fragment library design, chemical space analysis, and graphical user interface are also integrated into MoleGear. The candidate molecules as inhibitors for the human immunodeficiency virus 1 (HIV-1) protease were designed by MoleGear, which validates the potential capability for de novo molecular design.