Vet informatics and the future of drug discovery in veterinary medicine

The objective of this study was to investigate the molecular interaction and complex stability of four major cow's milk (CM) proteins (α-LA, β-LG, αs1 -CA, and β-CA) with cyanidin-3-O-glucoside (C3G) using computational methods. The results of molecular docking analysis revealed that hydrogen bond and hydrophobic interaction were the main binding forces to maintain the stability of the C3G-CM protein complexes. Molecular dynamics simulation results showed that all complexes except for C3G-αs1 -CA were found to reach equilibrium within 50 ns of simulation. αs1 -CA and β-CA switched to a more compact conformation after binding with C3G. Additionally, the radius of gyration, number of hydrogen bond, radial distribution function, and interaction energy showed that β-CA is the best C3G carrier protein among the four CM proteins. This study can provide valuable information for CM proteins to serve as C3G delivery carriers. PRACTICAL APPLICATIONS: Anthocyanins (ACNs) are flavonoid-based pigments that play an important functional role in regulating human's health. Cow's milk (CM) proteins are the most representative protein-based carriers that can improve the short-term bioavailability and stability of ACNs. Thus, it is important to study the interactions between ACNs and CM proteins at the molecular level for the development of effective ACNs delivery carriers. Our study showed that caseins (αs1 -CA and β-CA) had more hydrophobic and hydrogen-bonding sites with cyanidin-3-O-glucoside (C3G) than whey proteins using computational methods. Among the four CM proteins, β-CA was the best C3G carrier protein showing the best interaction stability with C3G. Thus, it is helpful for us to screen effective ACNs carriers from multiple protein sources by computational methods. Show more

Abstract Animal-ImputeDB (http://gong_lab.hzau.edu.cn/Animal_ImputeDB/) is a public database with genomic reference panels of 13 animal species for online genotype imputation, genetic variant search, and free download. Genotype imputation is a process of estimating missing genotypes in terms of the haplotypes and genotypes in a reference panel. It can effectively increase the density of single nucleotide polymorphisms (SNPs) and thus can be widely used in large-scale genome-wide association studies (GWASs) using relatively inexpensive and low-density SNP arrays. However, most animals except humans lack high-quality reference panels, which greatly limits the application of genotype imputation in animals. To overcome this limitation, we developed Animal-ImputeDB, which is dedicated to collecting genotype data and whole-genome resequencing data of nonhuman animals from various studies and databases. A computational pipeline was developed to process different types of raw data to construct reference panels. Finally, 13 high-quality reference panels including ∼400 million SNPs from 2265 samples were constructed. In Animal-ImputeDB, an easy-to-use online tool consisting of two popular imputation tools was designed for the purpose of genotype imputation. Collectively, Animal-ImputeDB serves as an important resource for animal genotype imputation and will greatly facilitate research on animal genomic selection and genetic improvement. Show more

Background The use of swine in biomedical research has increased dramatically in the last decade. Diverse genomic- and proteomic databases have been developed to facilitate research using human and rodent models. Current porcine gene databases, however, lack the robust annotation to study pig models that are relevant to human studies and for comparative evaluation with rodent models. Furthermore, they contain a significant number of errors due to their primary reliance on machine-based annotation. To address these deficiencies, a comprehensive literature-based survey was conducted to identify certain selected genes that have demonstrated function in humans, mice or pigs. Results The process identified 13,054 candidate human, bovine, mouse or rat genes/proteins used to select potential porcine homologs by searching multiple online sources of porcine gene information. The data in the Porcine Translational Research Database ((http://www.ars.usda.gov/Services/docs.htm?docid=6065) is supported by >5800 references, and contains 65 data fields for each entry, including >9700 full length (5′ and 3′) unambiguous pig sequences, >2400 real time PCR assays and reactivity information on >1700 antibodies. It also contains gene and/or protein expression data for >2200 genes and identifies and corrects 8187 errors (gene duplications artifacts, mis-assemblies, mis-annotations, and incorrect species assignments) for 5337 porcine genes. Conclusions This database is the largest manually curated database for any single veterinary species and is unique among porcine gene databases in regard to linking gene expression to gene function, identifying related gene pathways, and connecting data with other porcine gene databases. This database provides the first comprehensive description of three major Super-families or functionally related groups of proteins (Cluster of Differentiation (CD) Marker genes, Solute Carrier Superfamily, ATP binding Cassette Superfamily), and a comparative description of porcine microRNAs. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4009-7) contains supplementary material, which is available to authorized users. Show more