Large-scale cross-species chemogenomic platform proposes a new drug discovery strategy of veterinary drug from herbal medicines

Abstract

Veterinary Herbal Medicine (VHM) is a comprehensive, current, and informative discipline on the utilization of herbs in veterinary practice. Driven by chemistry but progressively directed by pharmacology and the clinical sciences, drug research has contributed more to address the needs for innovative veterinary medicine for curing animal diseases. However, research into veterinary medicine of vegetal origin in the pharmaceutical industry has reduced, owing to questions such as the short of compatibility of traditional natural-product extract libraries with high-throughput screening. Here, we present a cross-species chemogenomic screening platform to dissect the genetic basis of multifactorial diseases and to determine the most suitable points of attack for future veterinary medicines, thereby increasing the number of treatment options. First, based on critically examined pharmacology and text mining, we build a cross-species drug-likeness evaluation approach to screen the lead compounds in veterinary medicines. Second, a specific cross-species target prediction model is developed to infer drug-target connections, with the purpose of understanding how drugs work on the specific targets. Third, we focus on exploring the multiple targets interference effects of veterinary medicines by heterogeneous network convergence and modularization analysis. Finally, we manually integrate a disease pathway to test whether the cross-species chemogenomic platform could uncover the active mechanism of veterinary medicine, which is exemplified by a specific network module. We believe the proposed cross-species chemogenomic platform allows for the systematization of current and traditional knowledge of veterinary medicine and, importantly, for the application of this emerging body of knowledge to the development of new drugs for animal diseases.

Decoding Hippophae rhamnoides’ action of mechanism in Sjögren’s syndrome: A network pharmacology and molecular docking study

“…This database comprises 499 Chinese medicinal species and provides data about the absorption, distribution, metabolism, and excretion (ADME) properties of various ingredients (Ru et al, 2014). Oral bioavailability (OB) and drug-like (DL) properties are the foremost pharmacokinetic indicators (Huang et al, 2017). Oral bioavailability (OB) and drug-like (DL) properties are the foremost pharmacokinetic indicators (Huang et al, 2017).…”

“…Oral bioavailability (OB) and drug-like (DL) properties are the foremost pharmacokinetic indicators (Huang et al, 2017). Oral bioavailability (OB) and drug-like (DL) properties are the foremost pharmacokinetic indicators (Huang et al, 2017). In this study, compounds with OB ndicatorinal speciesfrom Hippophae rhamnoides were selected as candidate components, and their corresponding target proteins were predicted by searching the HERB (Highthroughput Experiment-and Reference-guided database of TCM; http://herb.ac.cn) database (Fang et al, 2021).…”

Bioinformatical and Biochemical Analyses on the Protective Role of Traditional Chinese Medicine against Age-Related Macular Degeneration

“…php; https://old.tcmsp-e.com/load_intro.php?id=40) to identify all the active ingredients. 11 At the same time, with oral bioavailability (OB)!30% and drug likeness (DL)!0.18 as the filter conditions, 12 the active ingredients of anti-AMD decoction were screened.…”

Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products

“…Currently, artificial intelligence algorithms (Wolfe et al, 2018 ; Lima et al, 2020 ; Stokes et al, 2020 ) and omics-based technologies (Floros et al, 2016 ; Huang et al, 2017 ; Jones and Bunnage, 2017 ; Merwin et al, 2020 ) have emerged as approaches to characterize and select interesting chemo-structures with appropriate physicochemical properties and biological activities as well as to prioritize the isolation of natural compounds from biological sources (Chen et al, 2018 ; Wolfender et al, 2019 ), which open up new opportunities to explore their industrial applications. Combined with other in silico analyses, artificial intelligence and cheminformatics methods can screen a high diversity of chemo-structures isolated from natural sources or deposited in public databases (Chen and Kirchmair, 2020 ), analyzing their bioactivity, pharmacodynamics, and their pharmacokinetic properties, thus reducing the financial efforts involved in research programs that aim to find new chemical agents (Chen et al, 2018 ; Al Sharie et al, 2020 ; Medina-Franco and Saldívar-González, 2020 ).…”