The binding pose and affinity between a ligand and enzyme are very important pieces of information for computer-aided drug design. In the initial stage of a drug discovery project, this information is often obtained by using molecular docking methods. Autodock4 and Autodock Vina are two commonly used open-source and free software tools to perform this task, and each has been cited more than 6000 times in the last ten years. It is of great interest to compare the success rate of the two docking software programs for a large and diverse set of protein–ligand complexes. In this study, we selected 800 protein–ligand complexes for which both PDB structures and experimental binding affinity are available. Docking calculations were performed for these complexes using both Autodock4 and Autodock Vina with different docking options related to computing resource consumption and accuracy. Our calculation results are in good agreement with a previous study that the Vina approach converges much faster than AD4 one. However, interestingly, AD4 shows a better performance than Vina over 21 considered targets, whereas the Vina protocol is better than the AD4 package for 10 other targets. There are 16 complexes for which both the AD4 and Vina protocols fail to produce a reasonable correlation with respected experiments so both are not suitable to use to estimate binding free energies for these cases. In addition, the best docking option for performing the AD4 approach is the long option. However, the short option is the best solution for carrying out Vina docking. The obtained results probably will be useful for future docking studies in deciding which program to use.

Familial Alzheimer's disease (FAD) is passed down in family, which account for 2-3% of about 40 million AD cases worldwide. The Flemish (A21G) mutant of amyloid β (Aβ) exhibits unique properties among all hereditary mutants of FAD, including the lowest aggregation rate. Recent studies showed that Aβ oligomers play a key role in Alzheimer's disease (AD) pathogenesis. They could insert themselves in brain cell membrane, disrupting the membrane integrity and ion homeostasis. However, experimental studies of transmembrane Aβ oligomers have been limited due to their intrinsic heterogeneity. In this work, we extensively studied the A21G mutant of the transmembrane 3Aβ (A21G 3Aβ) using temperature replica exchange molecular dynamics (REMD) simulations. Results provide detailed information on the conformational distribution and dynamics of transmembrane A21G 3Aβ. Minimal local change from A to G leads to significant conformational changes and wider free energy holes on the free energy surface as well as altered surface charges that lead to weaker affinity to the dipalmitoylphosphatidylcholine (DPPC) lipid bilayers. These results are consistent with experimental data that showed that A21G mutants of Aβ peptides have lower aggregation rates and membrane binding rates.

Understanding the interactions between nanoparticles (NPs) and human immune cells is necessary for justifying their utilization in consumer products and biomedical applications. However, conventional assays may be insufficient in describing the complexity and heterogeneity of cell–NP interactions. Herein, mass cytometry and single‐cell RNA‐sequencing (scRNA‐seq) are complementarily used to investigate the heterogeneous interactions between silver nanoparticles (AgNPs) and primary immune cells. Mass cytometry reveals the heterogeneous biodistribution of the positively charged polyethylenimine‐coated AgNPs in various cell types and finds that monocytes and B cells have higher association with the AgNPs than other populations. scRNA‐seq data of these two cell types demonstrate that each type has distinct responses to AgNP treatment: NRF2‐mediated oxidative stress is confined to B cells, whereas monocytes show Fcγ‐mediated phagocytosis. Besides the between‐population heterogeneity, analysis of single‐cell dose–response relationships further reveals within‐population diversity for the B cells and naïve CD4+ T cells. Distinct subsets having different levels of cellular responses with respect to their cellular AgNP doses are found. This study demonstrates that the complementary use of mass cytometry and scRNA‐seq is helpful for gaining in‐depth knowledge on the heterogeneous interactions between immune cells and NPs and can be incorporated into future toxicity assessments of nanomaterials.

Oligomerization of amyloid beta (Aβ) peptides has been considered as the crucially causative agent in the development of Alzheimer's disease. Etersalate, a nonsteroidal anti-inflammatory oral drug (United State Food and Drug Administration—Unique Ingredient Identifier: 653GN04T2G) was previously suggested to bind well to proto-fibrils of Aβ peptides in silico. Here, the effect of etersalate on the oligomerization of soluble Aβ16–22 hexamer (6Aβ16–22) were extensively investigated using temperature replica exchange molecular dynamics (REMD) simulations over ~16.8 μs in total for 48 replicas (350 ns per replica). The results reveal that etersalate can enter the inner space or bind on the surface of 6Aβ16–22 conformations, which destabilizes the hexamer. Etersalate was predicted to able to cross the blood brain barrier using prediction of absorption, distribution, metabolism, and excretion—toxicity (preADMET) tools. Overall, although the investigation was performed with the low concentration of trial inhibitor, the obtained results indicate that etersalate is a potential drug candidate for AD through inhibiting formation of Aβ oligomers with the average binding free energy of -11.7 kcal/mol.