Lung cancer is the most frequent cause of cancer-related deaths worldwide, and mutations in the kinase domain of the epidermal growth factor receptor (EGFR) are a common cause of non-small-cell lung cancers, which is a major subtype of lung cancers. Recently, a series of 5-methylpyrimidine-pyridinone derivatives have been designed and synthesized as novel selective inhibitors of EGFR and EGFR mutants. However, the binding-based inhibition mechanism has not yet been determined. In this study, we carried out molecular dynamic simulations and free-energy calculations for EGFR derivatives to fill this gap. Based on the investigation, the three factors that influence the inhibitory effect of inhibitors are as follows: (1) The substitution site of the Cl atom is the main factor influencing the activity through steric effect; (2) The secondary factors are repulsion between the F atom (present in the inhibitor) and Glu762, and the blocking effect of Lys745 on the phenyl ring of the inhibitor. (3) The two factors function synergistically to influence the inhibitory capacity of the inhibitor. The theoretical results of this study can provide further insights that will aid the design of oncogenic EGFR inhibitors with high selectivity.

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.

Monoacylglycerol lipase (MAGL) can regulate the endocannabinoid system and thus becomes a target of antidepressant drugs. In this paper, molecular docking and molecular dynamics simulations, combined with binding free energy calculation, were employed to investigate the inhibitory mechanism and binding modes of four aryl formyl piperidine derivative inhibitors with different 1-substituents to MAGL. The results showed that in the four systems, the main four regions where the enzyme bound to the inhibitor included around the head aromatic ring, the head carbonyl oxygen, the tail amide bond, and the tail benzene ring. The significant conformational changes in the more flexible lid domain of the enzyme were caused by 1-substituted group differences of inhibitors and resulted in different degrees of flipping in the tail of the inhibitor. The flipping led to a different direction of the tail amide bond and made a greater variation in its interaction with some of the charged residues in the enzyme, which further contributed to a different swing of the tail benzene ring. If the swing is large enough, it can weaken the binding strength of the head carbonyl oxygen to its nearby residues, and even the whole inhibitor with the enzyme so that the inhibition decreases.

No abstract

E. coli thioesterase ‘TesA is an important enzyme in fatty acid production. Medium-chain fatty acids (MCFAs, C6-C10) are of great interest due to their similar physicochemical properties to petroleum-based oleo-chemicals. It has been shown that wild-type ‘TesA had better selectivity for long-chain acyl substrates (≥C16), while the two mutants ‘TesAE142D/Y145G and ‘TesAM141L/E142D/Y145G had better selectivity for medium-chain acyl substrates. However, it is difficult to obtain the selectivity mechanism of substrates for proteins by traditional experimental methods. In this study, in order to obtain more MCFAs, we analyzed the binding mode of proteins (‘TesA, ‘TesAE142D/Y145G and ‘TesAM141L/E142D/Y145G) and substrates (C16/C8-N-acetylcysteamine analogs, C16/C8-SNAC), the key residues and catalytic mechanisms through molecular docking, molecular dynamics simulations and the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA). The results showed that several main residues related to catalysis, including Ser10, Asn73 and His157, had a strong hydrogen bond interaction with the substrates. The mutant region (Met141-Tyr146) and loop107–113 were mainly dominated by Van der Waals contributions to the substrates. For C16-SNAC, except for ‘TesAM141L/E142D/Y145G with large conformational changes, there were strong interactions at both head and tail ends that distorted the substrate into a more favorable high-energy conformation for the catalytic reaction. For C8-SNAC, the head and tail found it difficult to bind to the enzyme at the same time due to insufficient chain length, which made the substrate binding sites more variable, so ‘TesAM141L/E142D/Y145G with better binding sites had the strongest activity, and ‘TesA had the weakest activity, conversely. In short, the matching substrate chain and binding pocket length are the key factors affecting selectivity. This will be helpful for the further improvement of thioesterases.