Molecular Simulations Research Articles

High-affinity host-guest systems, such as Cucurbit[n]uril (CBn) macrocycles, are vital across various scientific and technological fields-such as targeted drug delivery, smart (self-healing) materials, sensitive biosensors, and molecular diagnostics-due to their exceptional molecular recognition capabilities. Molecular simulation (MS)-based predictions of ligands' binding poses and affinities on the macrocycles would greatly help optimize such host-guest systems. Yet, the poor accuracy of force fields (FFs) for these synthetic receptors has limited the applicability of MS thus far. Here, we demonstrate that incorporating electron density-derived Lennard-Jones parameters and charges into FFs can drastically improve the accuracy of free-energy calculations for these systems. As a test case, we focus on five adamantane derivatives and two diamantane derivatives in complex with one of the macrocycles, CB7. Our free energies of binding, calculated via multiple-walker well-tempered funnel metadynamics, turned out to be in fair agreement with the experiment for all the adamantane molecules. For the larger diamantane molecules, we still observe a discrepancy with experiments, which calls for deeper investigation. Overall, the calculations also provide insights into the binding mechanism and the role of the solvent. In particular, the chemical structures of the ligands and the ion strength play an important role in the binding process.

Introduction: The objective of this research is to experimentally demonstrate desensitization of thin filaments to Ca 2+ due to troponin I (TnI) phosphorylation and (-)-epigallocatechin-3-gallate (EGCG) binding and to explain the molecular mechanisms via computational modeling. While TnI inhibitory function regulates myocardial contraction via systolic Ca 2+ -dependent activation of thin filaments, its function can be modulated via phosphorylation of Ser23/24 at the N-terminal region of TnI, leading to an apparent Ca 2+ - desensitization. Similarly, EGCG found to be abundant in green tea desensitizes the troponin complex via mechanisms to be determined. The hypothesis is that TnI phosphorylation and EGCG binding desensitize thin filaments via enhanced stabilization of protein-protein interactions within the troponin complex. Methods: In vitro motility assays quantified Ca 2+ -dependent sliding velocities in phosphorylated TnI bound to thin filaments. AlphaFold3 recreated de novo structural models of phosphorylated TnI bound to the troponin (Tn) complex. Molecular docking simulations employed PyRx to model EGCG binding to Tn. Results: TnI phosphorylation and 20 µM ECGC treatments significantly reduced the maximum sliding velocity of thin filaments (-49±7%, p = 7x10 -6 ; and -58±8%, p =5x10 -5 respectively) and decreased the pCa 50 sensitivity (-3±2%, p = 1x10 -3 ; and -8±4%, p =4x10 -3 respectively) relative to controls. AlphaFold3 revealed that TnI phosphorylation led to the formation of an α-helix at the Ser23/24 phosphorylation sites across Tn complex isoforms four mammalian species including human. Molecular docking simulations localized the ECGC binding site onto the Tn complex that resulted from hydrogen-bonds between EGCG and the troponin C (TnC) C-lobe (residues 120-161) as well at the beginning of the TnI IT arm directly downstream from the TnI Ser 23/24 phosphorylation sites (residues 34-71). Conclusions: The results suggest that EGCG and TnI Ser23/24 phosphorylation desensitization mechanisms are allosteric, with phosphorylation modifying interactions between TnI and TnC N-terminal domains and EGCG between TnI and TnC C-terminal domain. The results of this wok could inform the development of more targeted therapies to treat diastolic heart diseases such as HFpEF and cardiomyopathies derived from over-sensitization of thin filaments to Ca 2+ .

Ischemic stroke (IS) is a complex cerebrovascular disease with a high global incidence, recurrence rate, and disability. Despite the limited availability of clinical therapies for IS, further research is essential to develop traditional Chinese medicine (TCM)-based neuroprotective treatments. This study aims to investigate the neuroprotective properties of mirificin against neuronal damage and uncover the pharmacological mechanisms involved.Mirificin levels in rat cerebrospinal fluid (CSF) and plasma following oral administration of Naomaitong (NMT) were analyzed using ultra high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Middle cserebral artery occlusion (MCAO) models were utilized to assess the effects of mirificin, with cerebral infarction size determined using TTC staining and neurobehavioral evaluation. Oxygen-glucose deprivation/reperfusion (OGD/R) experiments were conducted on PC12 cells to evaluate cell viability through CCK-8 and LDH assays. The predictive analysis of mirificin's potential therapeutic targets and pharmacological mechanisms was conducted employing advanced computational strategies such as Network Pharmacology (NP) and molecular docking simulations, which were further verified by corresponding antagonists.Mirificin was present in drug-containing plasma and CSF. Mirificin reduced infarct size, improved neurological function in vivo, and exerted dose-dependent neuroprotective effects towards OGD/R-injured PC12 cells. Moreover, the core targets of mirificin were predicted to be VEGFR2, CAT, MMP9, and HSP1A1. Antagonists of VEGFR2 and HSP1A1 inhibited the neuroprotective effects of mirificin.The neuroprotective effect of mirificin against OGD/R-induced neuronal injury appears to be mediated, at least in part, by targeting VEGFR2 and HSP1A1.

This paper proposes and implements a method to efficiently parallelize constraint solving in rigid body simulation using GPUs. Rigid body simulation is widely used in robot development, computer games, movies, and other fields, and there is a growing need for faster computation. As current computers are reaching their limits in terms of scale-up, such as clock frequency improvements, performance improvements are being sought through scale-out, which increases parallelism. However, rigid body simulation is difficult to parallelize efficiently due to its characteristics. This is because, unlike fluid or molecular physics simulations, where each particle or lattice can be independently extracted and processed, rigid bodies can interact with a large number of distant objects depending on the instance. This characteristic causes significant load imbalance, making it difficult to evenly distribute computational resources using simple methods such as spatial partitioning. Therefore, this paper proposes and implements a computational method that enables high-speed computation of large-scale scenes by hierarchically clustering rigid bodies based on their number and associating the hierarchy with the hardware structure of GPUs. In addition, to effectively utilize parallel computing resources, we considered a more relaxed parallelization condition for the conventional Gauss–Seidel block parallelization method and demonstrated that convergence is guaranteed. We investigated how speed and convergence performance change depending on how much computational cost is allocated to each hierarchy and discussed the desirable parameter settings. By conducting experiments comparing our method with several widely used software packages, we demonstrated that our approach enables calculations at speeds previously unattainable with existing techniques, while leveraging GPU computational resources to handle multiple rigid bodies simultaneously without significantly compromising accuracy.

MMP1 (matrix metallopeptidase 1) plays a significant role in the degradation of collagen fibres within the extracellular matrix, and has been linked to a multitude of biological processes, including rheumatoid arthritis, osteoarthritis, periodontal disease, and tumor invasion. In order to discover inhibitors of MMP1 that originate from the phytochemicals of the dandelion (Taraxacum mongolicum Hand.-Mazz.). The herbal constituents of the dandelion were retrieved from the HERB database. A multifaceted approach including molecular docking, MMP1 enzyme assays, and molecular dynamics simulations was used to identify potential MMP1 inhibitors among the chemical compounds present in the dandelion. A total of 61 chemical constituents of the dandelion were collated from the HERB database. A potential MMP1 inhibitor was identified through a combination of molecular docking and an MMP1 enzyme bioactivity assay. Cichoric acid demonstrated pronounced inhibitory activity against MMP1, with an IC50 value of 7.81 ± 2.60 µM. Molecular dynamics simulations and binding free energy calculations indicated that the nonpolar interaction energies of LEU181, ARG214, VAL215, HIS218, GLU219, HIS228, PRO238, and SER239 played a primary role in the binding of cichoric acid to MMP1. The integration of molecular modeling and bioactivity testing proved an effective method for the rapid discovery of targeted small molecule inhibitors. Cichoric acid demonstrated potent MMP1 inhibitory activity and thus represented a promising candidate for further development.

Surface chemistry-driven lipase activation: insights from spectroscopy and molecular simulations.

Identification of novel umami peptides from Pleurotus ostreatus and their umami-enhancing effects through virtual screening, sensory evaluation, and molecular simulation.

Inhibition of xanthine oxidase by two aldehydes: Inhibitory kinetics, molecular simulation, inhibition mechanism, and cellular insights.

Sequential grafting of PEI on PDA-anchored graphene oxide for enhanced xylose dehydrogenase Catalysis: Positively charged surface interfaces and mechanistic insights via molecular simulation

Molecular insights in outstanding performance of Ca2+ bridging MXene/Sodium alginate composite membranes.

Competitive and inhibitive mechanism of carbon dioxide in sulfur dissolution in natural gas through a combined approach of machine learning and molecular simulation

Molybdenum disulfide quantum dots inhibit catalase activity via conformational alteration: Insights from multispectral analysis and molecular simulations

Insights into the synergistic cross-linking effect of EGCG and TGase on surimi gels.

Study on the influence of surfactants on the wetting of bituminous coal by halogen salt inhibitors: Molecular simulation and experimental characterization

Predicting binding strength and dissociation kinetics of HIV-1 protease inhibitors Ritonavir, XK-263, and AHA-001 by molecular simulations.

Towards reproducible wetting studies: Automated contact angle determination by molecular simulations

Mechanisms of Al2O3 nanofluids affecting coal wettability and gas adsorption-desorption under different pH conditions: Molecular simulation and experimental study

Investigation on the micro-mechanism of borehole instability in coalbed methane reservoirs by molecular simulation

Functional valorization of oil shale waste for sustainable pavement materials: Component regulation mechanisms based on molecular simulation and experimental validation

Force-electric response of conductive elastomer composites reinforced with double-charged layer spider webs: experiments and molecular simulations