
- SECS: Stochastic Exploration of Chemical Space
- Traditional virtual screening in drug discovery relies on a pre-compiled compound library (~10E9 compounds) which only covers the fraction of the chemical space (10E60 compounds).
- Previous library-free virtual screening methods (genetic algorithem, AI) still rely on a pre-compiled fragment library or pre-trained models.
- SECS sequentially applies the structure perturbation to sample the chemical space, analogous to trajectories in molecular dynamics, and generate novel chemical structures to be used for virtual screening.
- Preliminary implementation can be found at https://github.com/wryu94/stochastic_exploration_of_chemical_space

- Molecular dynamics and enhanced sampling simulation of protein-ligand complexes
- Molecular dynamics and enhanced sampling are valuable tools to study atomistic details of pharmaceutical systems of interest:
- many cases in which the atomistic mechanism of action for approved drugs are not known
- or specific binding site
- computational characterization of these protein-ligand systems can be used for lead optimization / catalyze further drug discovery work
- Systems we are interested in:
- HIV capsid + lenacapavir:
- Ligand conformational space
- Lead optimization for mutation resistance
- HCMV terminase + letermovir:
- Binding site identification
- Structural modeling
- HCMV terminase + tomeglovir:
- Binding/unbinding free energy surface and pathway
- Mechanism of action
- HIV capsid + lenacapavir:
- Molecular dynamics and enhanced sampling are valuable tools to study atomistic details of pharmaceutical systems of interest:

- CADD (computer aided drug discovery) collaborations
- The Ryu Lab welcomes collaboration with medicinal chemistry, organic chemistry, and biology research groups on drug discovery projects.
- We bring expertise in CADD methods such as:
- Virtual screening
- Structure prediction
- Alchemical free energy calculations
- Cheminformatics
- Molecular dynamics and enhanced sampling simulation
- At various contexts in pre-clinical drug discovery campaign such as:
- Hit identification and generation
- Target identification
- Lead optimization
- With technical proficiency in:
- Molecular modeling software
- Python programming