The accuracy of the CHARMM22/CMAP and AMBER ff99SB force fields for modelling the antimicrobial peptide cecropin P1

MERTK activation drives osimertinib resistance in EGFR-mutant non-small cell lung cancer

Acquired resistance is inevitable in non-small cell lung cancers (NSCLCs) treated with osimertinib (OSI), and the mechanisms are not well defined. The MERTK ligand GAS6 promoted downstream oncogenic signaling in EGFR-mutated (EGFRMT) NSCLC cells treated with OSI, suggesting a role for MERTK activation in OSI resistance. Indeed, treatment with MRX-2843, a first-in-class MERTK kinase inhibitor, resensitized GAS6-treated NSCLC cells to OSI. Both GAS6 and EGF stimulated downstream PI3K/AKT and MAPK/ERK signaling in parental cells, but only GAS6 activated these pathways in OSI-resistant (OSIR) derivative cell lines. Functionally, OSIR cells were more sensitive to MRX-2843 than parental cells, suggesting acquired dependence on MERTK signaling. Furthermore, MERTK and/or its ligands were dramatically upregulated in EGFRMT tumors after treatment with OSI in both xenograft models and patient samples, consistent with induction of autocrine/paracrine MERTK activation. Moreover, treatment with MRX-2843 in combination with OSI, but not OSI alone, provided durable suppression of tumor growth in vivo, even after treatment was stopped. These data identify MERTK as a driver of bypass signaling in treatment-naive and EGFRMT-OSIR NSCLC cells and predict that MRX-2843 and OSI combination therapy will provide clinical benefit in patients with EGFRMT NSCLC.

Off-Pocket Activity Cliffs: A Puzzling Facet of Molecular Recognition

While accurate quantitative prediction of ligand-protein binding affinity remains an elusive goal, high-affinity ligands to therapeutic targets are being designed through heuristic optimization of ligand-protein contacts. However, herein, through large-scale data mining and analyses, we demonstrate that a ligand's binding can also be strongly affected through modifying its solvent-exposed portion that does not make contacts with the protein, thus resulting in "off-pocket activity cliffs" (OAC). We then exposed the roots of the OAC phenomenon by means of molecular dynamics (MD) simulations and MD data analyses. We expect OAC to extend our knowledge of molecular recognition and enhance the drug designer's toolkit.

Effects of Tyr555 and Trp678 on the processivity of cellobiohydrolase A from Ruminiclostridium thermocellum: A simulation study

Cellobiohydrolase A from Ruminiclostridium thermocellum (Cbh9A) is a processive exoglucanase from family 9 and is an important cellobiohydrolase that hydrolyzes cello-oligosaccharide into cellobiose. Residues Tyr555 and Trp678 considerably affect catalytic activity, but their mechanisms are still unknown. To investigate how the Tyr555 and Trp678 affect the processivity of Cbh9A, conventional molecular dynamics, steered molecular dynamics, and free energy calculation were performed to simulate the processive process of wild type (WT)-Cbh9A, Y555S mutant, and W678G mutant. Analysis of simulation results suggests that the binding free energies between the substrate and WT-Cbh9A are lower than those of Y555S and W678G mutants. The pull forces and energy barrier in Y555S and W678G mutants also reduced significantly during the steered molecular dynamics (SMD) simulation compared with that of the WT-Cbh9A. And the potential mean force calculations showed that the pulling energy barrier of Y555S and W678G mutants is much lower than that of WT-Cbh9A.

Stability of amyloid oligomers

Molecular simulations are now commonly used to complement experimental techniques in investigating amyloids and their role in human diseases. In this chapter, we will summarize techniques and approaches often used in amyloid simulations and will present recent success stories. Our examples will be focused on lessons learned from molecular dynamics simulations in aqueous environments that start from preformed aggregates. These studies explore the limitations that arise from the choice of force field, the role of mutations in the growth of amyloid aggregates, segmental polymorphism, and the importance of cross-seeding. Furthermore, they give evidence for potential toxicity mechanisms. We finally discuss the role of molecular simulations in the search for aggregation inhibitors.