- Leveraging the known structures of both the ligand and the protein target to enable efficient structure-based drug design. - Computational methods, such as QSAR (Quantitative Structure-Activity Relationships) modeling, are commonly used to predict novel active molecular structures at the initial stages of a drug discovery project. These models analyze relationships between chemical structures and biological activity by using basic molecular features such as charge distribution, hydrophobicity, and stereochemistry of known ligands. - The structures of the ligand-protein complexes enable the construction of a pharmacophore model. Pharmacophore modeling uses essential 3D features to map interactions between a known compound and a target protein, including the arrangement of ligand-binding atomic groups (side chain and main chain atoms) and the distribution of charged and hydrophobic groups within the binding site. The model can subsequently guide the design of new active molecules. - Both QSAR and pharmacophore modeling are used in virtual screening of fragment or drug-like compound libraries to improve the efficiency and accuracy of the method. An advantage of virtual screening is its ability to handle much larger compound libraries and a higher screening speed. - Biophysical screening techniques such as NMR spectroscopy, X-ray crystallography, and our proprietary weak-affinity chromatography (WAC™) play a central role in compound library screening and identification of new active compounds. - Recent developments in synchrotron radiation technologies have enabled the use of X-ray crystallography for fragment screening. The advantage of the crystallographic fragment screening method is that it provides direct insights into the binding mode of fragment hits. NMR spectroscopy is highly efficient for detecting low-affinity ligands (Kd > 10−6 M) or for studying the protein in a non-ideal conformation for ligand binding using crystal soaking.
