Ligand-Based Virtual Screening
Binary star can build a 3D model of the target by exploiting the collective information contained in sets of ligands. Multiple similar ligand atoms in a spatially consistent location result in a strong pharmacophore feature. This model can be generated from one or more high-affinity scaffolds such as hydrogen bond donors and acceptors.
Structure-Based Virtual Screening
Our structure-based virtual screening technique is a combination of high-throughput docking engines with estimating the affinity likelihood that the ligand binding to targets. Our fast and accurate ligand docking and scoring procedures lead to efficient virtual screening.
Peptide-Based Virtual Screening
Binary star employs an in-house pipeline to search for far more potent peptide ligands. Our computational docking techniques predict all possible binding modes in the translational and rotational space between a protein receptor and its peptide binding partner, starting from random conformations and positions of the peptide. We further comprehend our established protocol to improve the binding affinity of the selected peptide by many folds through different modification methods. Our peptide-based VS approach will facilitate the rational design of potentially therapeutic peptides.
Fragment-Based Virtual Screening
Fragment-based screening has proven to be a viable complementary approach to high throughput screening, and it has shown profound significance in drug discovery. Binary star has built well-established protocols for the screening of low-molecular weight compounds against macromolecular targets of clinical relevance.
Drug Repurposing
New drug discovery and development are accompanied by high costs and prolonged timelines, which are major roadblocks for creating therapies for emerging infectious diseases. To discover economically viable new treatments against various diseases, Binary star employs a repurposing approach for drug discovery. Our in silico drug repurposing platform represents an alternative and complementary approach to drug discovery.
ADMET Prediction
The journey of an oral drug candidate depicts the quantitative structure-activity relationship of physicochemical properties with absorption, distribution, metabolism, excretion, and toxicity (ADMET). The poor ADMET is closely related to their structure. The ultimate goal of the in silico prediction of ADMET properties is to accurately mimic the in vivo pharmacokinetics of a potential drug molecule in the body whilst it exists as only a virtual structure. Binary star has a well-established in-house protocol to search for more drug-like molecules by eliminating unfavoured structures.
