Rational Computational Design of Fourth-Generation EGFR Inhibitors to Combat Drug-Resistant Non-Small Cell Lung Cancer

Abstract

Although the inhibitors of singly mutated epidermal growth factor receptor (EGFR) kinase are effective for the treatment of non-small cell lung cancer (NSCLC), their clinical efficacy has been limited due to the emergence of various double and triple EGFR mutants with drug resistance. It has thus become urgent to identify potent and selective inhibitors of triple mutant EGFRs resistant to first-, second-, and third-generation EGFR inhibitors. Herein, we report the discovery of potent and highly selective inhibitors of EGFR exon 19 p.E746_A750del/EGFR exon 20 p.T790M/EGFR exon 20 p.C797S (d746-750/T790M/C797S) mutant, which were derived via two-track virtual screening and de novo design. This two-track approach was performed so as to maximize and minimize the inhibitory activity against the triple mutant and the wild type, respectively. Extensive chemical modifications of the initial hit compounds led to the identification of several low-nanomolar inhibitors of the d746-750/T790M/C797S mutant. Among them, two compounds exhibited more than 104-fold selectivity in the inhibition of EGFRd746-750/T790M/C797S over the wild type. The formations of a hydrogen bond with the mutated residue Ser797 and the van der Waals contact with the mutated residue Met790 were found to be a common feature in the interactions between EGFRd746-750/T790M/C797S and the fourth-generation inhibitors. Such an exceptionally high selectivity could also be attributed to the formation of the hydrophobic contact with a Gly loop residue or the hydrogen bond with Asp855 in the activation loop. The discovery of the potent and selective EGFRd746-750/T790M/C797S inhibitors were actually made possible by virtue of the modified protein–ligand binding free energy function involving a new hydration free energy term with enhanced accuracy. The fourth-generation EGFR inhibitors found in this work are anticipated to serve as a new starting point for the discovery of anti-NSCLC medicines to overcome the problematic drug resistance.

Structure-Based Virtual Screening and De Novo Design of PIM1 Inhibitors with Anticancer Activity from Natural Products

“…Despite a significant contribution to the protein-ligand association, it was difficult to reflect the ligand hydration effects explicitly in docking simulations because the scoring function of the original AutoDock program contained a crude dehydration energy term involving only six atom types for varying solute molecules. Therefore, the modified version of AutoDock program was used in this work because the outperformance of its scoring function was demonstrated in various target proteins [37,38]. This modified scoring function (∆G aq bind ) differs from the original one in the inclusion of a sophisticated dehydration free energy term, which can be expressed in the following mathematical form.…”

“…In particular, the underestimation of ligand dehydration in protein-ligand binding has been invoked to elucidate the poor correlation between computational estimations of biochemical potency and the corresponding experimental measurements [36]. Accordingly, the potential-based scoring function including a sophisticated molecular hydration energy term showed the outperformance in virtual screening for various target proteins by alleviating overestimation of the biochemical potency of a ligand with hydrophilic moieties [37,38]. It is further exemplified in this work that even low-nanomolar PIM1 inhibitors with anticancer activity can be identified from natural products using the modified scoring function.…”

Recent Advances in Kinase Drug Discovery Part I: The Editors’ Take

“… Recent advances in kinase drug discovery span the drug discovery pipeline from target identification through to pharmacovigilance. These advances are illustrated in six primary research articles covering kinome array profiling [ 4 ], structure-guided drug development [ 5 , 6 ], rational computational design [ 7 ], targeting the protein/peptide substrate binding site [ 8 ] and combinatorial drug treatment [ 9 ]; and nine topical reviews on TAO kinases [ 10 ], liver disease [ 11 ], AMPK [ 3 ], pancreatic cancer [ 12 ], urothelial carcinoma [ 13 ], Flaviviridae infections [ 14 ], squamous cell carcinoma [ 15 ], thyroid cancer [ 16 ] and adverse reactions to JAK inhibitors [ 17 ]. The indicated figures from special issue papers have been re-used with permission from the authors.…”

“…Park and colleagues [ 7 ] apply a dual-track virtual screening approach to identify novel inhibitors of the clinically relevant, drug-resistant EGFR mutant, EGFR [DelE746-A750 T790M C797S], with selectivity over wild-type EGFR. They implement an improved scoring function, which takes better account of ligand hydration effects, to improve their hit selection process, and screen in parallel against a homology model of the EGFR mutant and a crystal structure of the wild-type protein.…”

“…Limitations of space and time mean that many exciting advances, including the application of biophysical techniques to larger and more complex systems, novel cellular target engagement assays and the burgeoning area of protein degraders, as well as the therapeutic targeting of lipid, nucleotide and small molecule kinases, are missing from this special issue. Several articles in this special issue highlight the use of computational methods to tackle current challenges in target validation and compound design [ 4 , 7 , 8 ]. The increasing application of artificial intelligence within the drug discovery pipeline has the potential to further enhance our ability to ‘drug’ those kinases currently considered ‘difficult’, for example, due to a lack of structural information.…”