Traditional high-throughput screening requires conducting biological activity screening of a large number of compounds in the laboratory, which involves tedious experimental procedures and equipment operations, and incurs high costs. In contrast, virtual screening uses computer simulation and prediction methods to select compounds with potential biological activity from large compound databases. This greatly accelerates the drug development process, reduces experimental costs and development cycles. Virtual screening involves Computer-Aided Drug Design (CADD) technologies, including molecular docking, drug property prediction, and drug interaction prediction.

Developing new drugs is a time-consuming and costly process. Compared to new drug development, drug repositioning (also known as 'old drugs for new uses') has many advantages. Firstly, drug development based on known active compounds can lower the risk of drug development failure. Additionally, most compounds in the MCE Bioactive compounds library have undergone explicit activity research or are in clinical trial stages, thus screening from this source can shorten the development cycle and reduce development costs.

In recent years, an increasing number of cases of 'old drugs for new uses' have entered clinical research. For instance, Minoxidil initially entered the clinic as a drug for treating high blood pressure, and was later found to have excellent therapeutic effects in stimulating hair growth, it is now widely used in the treatment of hair loss. Moreover, Aspirin , once widely known as an antipyretic analgesic, was confirmed by the U.S. Preventive Services Task Force (USPSTF) in September 2015 to have a preventive effect on cardiovascular diseases and colorectal cancer. Approved drugs have good bioactivity, pharmacokinetic properties, and safety, making them particularly suitable for repositioning research.

Generally speaking, drug repositioning strategies need to go through three steps: (1) Identifying candidate molecules with therapeutic effects on diseases; (2) Investigating the mechanisms of candidate drugs in preclinical models; (3) Evaluating the efficacy of clinical trials^[3]. Preliminary identification of candidate molecules with therapeutic potential through computational and experimental methods has become an important step in drug repositioning research. Structure-based molecular docking techniques have been widely used to predict the binding affinity between ligands (drugs) and therapeutic targets (usually proteins) (Figure 4).

We've just introduced the applications and advantages of virtual screening techniques and drug repositioning strategies. So how do we validate the candidate compounds obtained from virtual screening? Let's take a look with MCE!

Molecular Dynamics Simulation

Molecular Dynamics (MD) simulation is a computer simulation method based on Newtonian mechanics that integrates various disciplines such as physics, mathematics, and chemistry. It is used to study the motion and interactions of molecular systems, and to predict the behavior and structural properties of molecular systems. Through computer molecular simulation, researchers can understand the motion of biological macromolecules and their biological functions, as well as the interaction mechanisms between proteins and small molecules at the molecular level. Currently, MD is widely used in the fields of biomedicine, physics, chemistry, and materials science, serving as a powerful supplement to theoretical calculations and experiments.

Affinity Mass Spectrometry Screening

The 'precise' targeted drug molecule design strategy is based on the theory of precise interactions between disease-related drug targets and ligands. This strategy discovers small molecule ligands that have strong affinity and specificity for target proteins through the interaction of drug active ingredients with specific biological targets related to diseases. Affinity Selection Mass Spectrometry (ASMS) as a method for indirect screening of small molecule ligands, has been successfully applied to the ligand screening of many receptors, enzymes and other target proteins, and has been widely used.

SPR Detection

Surface Plasmon Resonance (SPR) is a bio-sensing analytical technique that takes advantage of traditional optical phenomena to generate resonance between evanescent waves produced by light in different mediums and plasmonic waves, thereby constructing interactions among biomolecules. It is used to detect the interactions between the ligand on the biosensor chip and the analyte. In simple terms, SPR measures the degree of change in resonance angle based on whether the ligands coupled to the metal surface bind with the analyte. By monitoring the changes in the resonance angle, one can infer information about the affinity, association constants, and binding kinetics of biomolecular interactions.

SPR technology has extensive applications and significant value in fields such as drug screening, protein-protein interaction studies, and antibody-antigen binding.

Case 1

The team led by Zhang Wenlong from Nanjing University Gulou Hospital discovered that Wedelolactone from the MCE active compound library has potential GPD1 agonistic activity, achieving drug repositioning^[5].

Published journal: Journal of Hematology & Oncology (IF= 28.5)

In this study, the authors obtained the GPD1 conformational activator Wedelolactone from the MCE active compound library through virtual screening. They demonstrated its ability to inhibit bladder tumor growth in vitro and in vivo: The GPD1 enzymatic activity analysis system determined the compound's activating effect on GPD1 enzymatic activity (Figure G-H). Choosing Wedelolactone , which displayed the strongest activity in the selected enzyme activity experiment, they used an MST method to prove that it has good binding affinity with GPD1 (K_d=505 nM) (Figure F). Treating 5637 and T24 cells with 10 µM of Wedelolactone, they found that Wedelolactone can significantly increase intracellular G3P and NAD+. Wedelolactone activated the catalytic activity of endogenous GPD1 in bladder cancer cells.

Case 2

The team led by Wang Yifei from the Chinese University of Hong Kong successfully identified inhibitors targeting MCM6 from the MCE active compound library^[6].

Published journal: Theranostics (IF=12.4)

In this study, the authors first screened YAP downstream targets through RNA sequencing (RNA-seq) and gene chip screening. They further confirmed MCM6 as a potential YAP downstream target in GC through ChIP PCR and luciferase reporter gene detection. Since there are currently no known available MCM6 inhibitors, the authors conducted a virtual screening of the MCE active compound library and identified Purpureaside C as a new MCM6 inhibitor. They performed activity validation on it and confirmed the interaction between them.

Case 3

A joint study by Hunan Provincial People's Hospital and Fudan University Children's Hospital identified Pentagalloylglucose , a PALB2-BRCA2 PPI inhibitor, from the MCE active compound library^[7].

Published journal: Cancer Letters (IF= 9.756)

In this study, the authors conducted structure-based virtual screening and nanobit-based screening of approximately 2 million small molecules from the HTS Compound Library and MCE Bioactive Compound Library Plus. Through Surface Plasmon Resonance (SPR) experiments, they identified Pentagalloylglucose (PGG) as a compound that can disrupt the protein-protein interaction between PALB2 and BRCA2: PGG can bind in the pocket where the BRCA2 peptide binds to PALB2, reducing the recruitment of BRCA2 to DNA damage sites, inhibiting the formation of RAD51 foci, and suppressing homologous recombination repair.

Additionally, PGG can inhibit the proliferation and survival of a variety of cancer cell lines, including breast cancer and medulloblastoma cells. It also suppresses the in vivo growth of tumor xenografts. This implies potential value in cancer treatment, enhancing the sensitivity of tumors to PARP inhibitors and radiation therapy.