# Computer-Aided Drug Design Boosts RAS Inhibitor Discovery
## 3 Application of CADD Methods in the Development of RAS Inhibitors
### Virtual Screening
In the second round, on LigandScout software, hybrid virtual screening strategy was used to build a pharmacophore model by extracting basic interaction parameters involving hydrogen bonds, salt bridges, aromatic rings, and hydrophobic regions from the existing co-crystal complexes of active inhibitors binding to the SOS1-KRAS interface. Finally, nine hit compounds were screened out of 250,000 compounds in the National Cancer Institution (NCI) database for subsequent molecular docking and molecular dynamics simulation screening. In search of more effective inhibitors, the nine candidates were then used to generate new ligand sets to repeat the process in the PubChem database. Auriculasin (\(-9.8\) kcal/mol) was finally identified with a higher affinity than the reported inhibitor DCAI (\(-5.2\) kcal/mol) for inhibiting the SOS1-KRAS\({}^{\rm G12D}\) interaction [77]. Due to RAS's undruggability, the post-translational modification (PTM) of RAS is considered a drug target, such as farnesyltransferase. As a potential inhibitor, theflavin (Vina score = \(-12.2\) kcal/mol) is identified as an alliance of virtual screening with Autodock Vina based on the Lamarckian genetic algorithm, molecular docking, and molecular dynamics [78]. After PTM, RAS localization and transport regulated by the preynl-binding protein PDE\(\delta\) is also promising for drug intervention [79]. NHTD targeting the hydrophobic premyl pocket of PDE\(\delta\) (Glide XP score = \(-12.77\) kcal/mol) was discovered by [PERSON] et al. [80], who applied an extra precision (XP) docking scoring to 1.3 million compounds with Glide [81]. Aiming at the interface of the KRAS4B-PDE6\(\delta\) crystal complex as a binding pocket, VS in collaboration with MOE Dock was also performed to search for compounds that prevent the mutant KRAS from being released from the stable complex and are candidates for the treatment of pancreatic ductal adenocarcinoma [82]. MEK1 inhibitors targeting the RAS downstream pathway were identified by a cooperation of GOLD and CDOCKER and finally adopted by Glide XP in collaboration with HypoSen pharmacophore modeling as a scoring method with a low root mean square deviation (RMSD) to improve screening reliability and efficiency. After screening the SPECS library of more than 200,000 compounds, the candidate MEK1 inhibitor was validated by biochemical and cellular assays (IC\({}_{50}\) = 3.5 \(\upmu\)M) [83]. Multiple approaches, including Fischer's randomization, test set prediction, and decoy set confirmation, have been used in many studies to assess the quality of pharmacophore modeling and analyze costs. Glide XP scoring was also used to identify catechin (Glide XP score = 10.98 kcal/mol) as another potential MEK1 inhibitor for the treatment of melanoma [84]. In this study, the known MEK1 inhibitory ligands in Ligand.Info were screened for analogue compounds to build a drug library for molecular docking in SB-VS rather than LB-VS. Due to flexibility in ligand selection, low computational cost, and methodological versatility, LB-VS has been extensively used despite the known target protein structure in most cases. VS is considered to be advantageously compatible with multiple CADD screening strategies in the search for RAS inhibitors.