The major preclinical phases of peptide drug discovery encompass initial target identification and validation, hit identification, high throughput screening, lead optimization, etc. Among them, hit identification is one of the most critical steps in identifying peptides that can interact with well-validated targets.
Hit identification (HI) follows the process of target validation, in which the compound screening assays are developed. The main goal of the HI process is to apply the most suitable hit finding approaches to finally identify validated hit series with the best chance of developing into druggable compounds. A successful hit identification campaign relies on the use of a high-quality, diverse library of potential compounds to be screened, but also on capitalizing on other complementary techniques, such as structure-based virtual screening (SBVS) and fragment-based screening. This has to be coupled with the deployment of a battery of the most relevant and accurate assays for the specific target and disease state.
There is a variety of well-established strategies available to identify good hits, devoted to maximizing the number of initial hits and hit series. These methods include medium- or high-throughput screening, virtual screening, knowledge-based screening, nuclear magnetic resonance (NMR) screening, and so forth. Depending upon the characteristics of the project and the resources available, these different methods can be applied in parallel or individually.
- Medium- or High-Throughput Screening
Medium-or high-throughput screening (M-HTS) is an efficient and widely-used means to rapidly identify promising compounds, with the help of robotics and automation. Scientists use M-HTS to quickly test thousands of samples with biological activities at the model organism, cell, pathway, or molecular levels. Large compound libraries therefore can be screened in a cost-effective way which helps to accelerate target analysis.
Virtual screening is a computer-based technology used to analyze the presence or absence of specific substructures, match certain calculated molecular properties, as well as fit potential ligand molecules into the target receptor site. Structure- and ligand-based virtual screening technologies are the most popular tools for hit-to-lead compound discovery. As a standalone activity, this computational screening focus on the compounds that are most likely to be successful resulting in shorter screen times and reduced costs in hit identification.
- Knowledge-based Screening
Knowledge-based screening refers to selecting smaller subsets of molecules from chemical libraries that are likely to be active against the target protein based on knowledge of the target protein and literature or patent precedents for the chemical class that may be active against the drug target. More recently, this type of knowledge has led to early discovery paradigms that use pharmacophore and molecular modeling to virtually screen compound databases.
- Nuclear Magnetic Resonance (NMR) screening
Hits identified by NMR screening is a powerful method in the early hit development of peptide drug discovery. NMR can guide SAR by determining the structural tendency through atomic resolution and offer insights into the way the peptide interacts with its target from the binding site to the binding mode by the use of chemical shift maps and saturation shift difference (STD) experiments.
Whatever the screening paradigm, the output of the hit discovery phase of a lead identification program is a so-called hit molecule, typically with a potency of 100 nM–5 µM at the drug target. To find more good hits, many pharmaceutical companies have built large organizations and been equipped with the advanced facility to screen those compounds to identify initially hit molecules from HTS or other screening paradigms and to optimize those screening hits into clinical candidates.