They designed and synthesized a series of nine enmein-type ent-kaurane diterpenoid and furoxan-based nitric oxide (NO) donor hybrids from commercially available oridonin. Wei Xiao, Huiming Hua, Jinyi Xu, and their coworkers wrote an article with the title “NO-Releasing Enmein-Type Diterpenoid Derivatives with Selective Antiproliferative Activity and Effects on Apoptosis-Related Proteins”. This approach will significantly reduce the lead time, risk, cost, and resources required to determine efficacious therapies against future Ebola virus disease outbreaks. They found that integrating computational docking predictions on a proteomic scale with results from in vitro screening studies may be used to select and prioritize compounds for further in vivo and clinical testing. They used the CANDO platform to generate top ranking drug candidates for Ebola virus disease treatment, which were compared to those identified from in vitro studies. In the article entitled “Combating Ebola with Repurposed Therapeutic Using the CANDO Platform”, Gaurav Chopra, Ram Samudrala, and coauthors have developed a Computational Analysis of Novel Drug Opportunities (CANDO) platform based on the hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for rapid therapeutic repurposing and discovery. The request for novel drug development, finding efficient drug discovery pathways is going to be crucial in the fight against future outbreaks. The 2014 Ebola epidemic in West Africa is believed to have caused more than 11,000 fatalities. It covered seventeen research articles and one communication contributed from experts all around the world, as briefed below. This Special Issue “Drug Design and Discovery: Principles and Applications” was focused on the basic principles of modern drug design and discovery and the potential applications. Once a compound that fulfills all of these requirements has been identified, it will begin the process of drug development prior to clinical trials. Modern drug discovery involves the identification of screening hits, medicinal chemistry and optimization of those hits to increase the affinity, selectivity (to reduce the potential of side effects), efficacy/potency, metabolic stability (to increase the half-life), and oral bioavailability. Drug development and discovery includes preclinical research on cell-based and animal models and clinical trials on humans, and finally move forward to the step of obtaining regulatory approval in order to market the drug.
In addition to small molecules, biopharmaceuticals and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also gained great advances. Drug design frequently but not necessarily relies on computer modeling techniques and bioinformatics approaches in the big data era. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the molecular target with which they interact and bind. Drug design is the inventive process of finding new medications based on the knowledge of a biological target.
Despite advances in biotechnology and understanding of biological systems, drug discovery is still a lengthy, costly, difficult, and inefficient process with a high attrition rate of new therapeutic discovery.
Drug discovery is the process through which potential new therapeutic entities are identified, using a combination of computational, experimental, translational, and clinical models (see, e.g., ).