Computational Chemistry

Compound solubility is a crucial factor in medicinal chemistry and drug discovery, as it greatly influences the ADMET profile of potential drug candidates. Computational, methods are an important tool for predicting and calculating compound solubility in silico.

Transcription factors are involved in various diseases, including cancer, diabetes, neurological, autoimmune, inflammatory disorders, cardiovascular disease, and parasitic infections. To promote the transcription-related drug discovery, Life Chemicals presents distinctive collections of drug-like screening compounds competent for TF modulation research.

Given the complementary benefits and capabilities of the two screening methods, Life Chemicals considers both approaches for creating the most diverse and balanced collection of screening compound libraries for HTS efforts in drug discovery.

Rapidly developing structure-based drug design (SBDD) is mainly based on various computational techniques, which allow for the automation and acceleration of the drug design workflow. Life Chemicals offers its proprietary collection of 3D-shaped and Fsp3-enriched screening compounds for efficient drug discovery.

Research efforts that seek to prioritize the selection of screening compound libraries or sub-libraries for experimental evaluation can take advantage of chemical diversity to increase the probability of finding new scaffolds.