Related Experiment Video
Updated: Sep 2, 2025

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
Published on: May 20, 2020
Modeling receptor flexibility in the structure-based design of KRASG12C inhibitors
Kai Zhu1, Cui Li2, Kingsley Y Wu3
1Department of Molecular Engineering, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA, 91320, USA. kzhu@amgen.com.
Abstract:
KRAS has long been referred to as an 'undruggable' target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRASG12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRASG12C-sometimes referred to as the 'switch-II pocket'-holds great potential in the design of direct inhibitors of KRASG12C. In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRASG12C, we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRASG12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.
More Related Videos
07:08Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein
Published on: January 16, 2020
09:19Strategic Screening and Characterization of the Visual GPCR-mini-G Protein Signaling Complex for Successful Crystallization
Published on: March 16, 2020
Related Concept Videos
G Protein-coupled Receptors
GPCRs are also called heptahelical, 7TM, or serpentine receptors, and consist of seven (H1-H7) transmembrane alpha-helices that span the bilayer to form a cylindrical core. The transmembrane helices are connected by three extracellular loops and three...
Structure-Activity Relationships and Drug Design
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
Ligand Binding and Linkage
The Two-State Receptor Model
The binding affinity of a drug determines its interaction with...
Adrenergic Agonists: Chemistry and Structure-Activity Relationship
Aromatic ring substitutions: Substituting the aromatic ring with –OH groups at positions 3 and 4 yields catecholamines (e.g., epinephrine), which have a high affinity for adrenoceptors. Hydrogen bonding between –OH groups and receptors enhances adrenergic activity.
Separation of...