high throughput virtual screening

PD-1/PD-L1 are key immune checkpoint targets that suppress T-cell-mediated anti-tumor immunity, representing a major focus in cancer immunotherapy. While antibody drugs dominate the clinic, they are limited by administration challenges and immune-related side effects. Small-molecule PD-1/PD-L1 inhibitors, with oral availability, good tissue penetration and low cost, have emerged as a promising next-generation strategy.

A PD-1/PD-L1 lead-like library was built via a five-step virtual screening process. After collecting 8,947 inhibitors from BindingDB and PubChem and filtering by activity and duplicates, AI similarity screening was performed using GeminiMol. Key pharmacophores were extracted from the PPI interface of co-crystal structures, and molecular was screened via a pharmacophore model, effectively enhancing target activity.

Containing 10,000 structurally diverse and drug-like molecules well-matched to the PD-L1 pocket, the library supports virtual docking, high-throughput screening and hit discovery, enabling efficient and rapid development of small-molecule immunotherapies.

COVID-19 poses a serious threat to people's health, and it is urgent to develop drugs to treat COVID-19 quickly. The screening of anti-COVID-19 drugs by using the clinical and approved compounds can greatly shorten the research and development cycle. In addition, the virtual screening technology can effectively narrow the scope of screening and improve the screening efficiency in the pre-screening of new drugs.

Taking advantage of our virtual screening, we conduct virtual screening of approved compound library and clinical compound library based on the 3CL protease (PDB ID: 6LU7), Spike Glycoprotein (PDB ID: 6VSB), NSP15 (PDB ID: 6VWW), RDRP, PLPro and ACE2 (Angiotensin Converting Enzyme 2) structure. We design a unique collection of 1,381 compounds which may have anti-COVID-19 activity. Anti-COVID-19 Compound Library will be a powerful tool for screening new anti-COVID-19 activity drugs.

On May 15, 2024, "Dimerization and antidepressant recognition at noradrenaline transporter" was published online by Nature. The research findings were an effort from Shanghai Institute of Materia Medica, Chinese Academy of Sciences. This study unraveled the important neural system target - the noradrenaline transporter (NET), obtaining the binding modes of human NET homodimers with the natural substrate norepinephrine (NE) and six selective antidepressants. It laid an important theoretical foundation for understanding the physiological regulation mechanisms of NET and other monoamine transporters.

The Norepinephrine Transporter (NET) Compound Library is obtained by computer-aided virtual screening based on the HY-L901 compound library . The specific screening process includes molecular docking screening, key pharmacophore screening, and CNS-MPO screening, which can be used for new drug discovery targeting the noradrenaline transporter.