Megacities serve as crucial catalysts for national economic and social development, and Shanghai, one of China’s most prominent metropolitan areas, exemplifies this transformative urbanization. To ...study Shanghai’s urban expansion, we extracted urban land cover data from 1985 to 2020 using impervious area products and simulated urban expansion dynamics from 2021 to 2035 by employing the cellular automata model. Leveraging these data, we analyzed a 50-year period of urban expansion and investigated the drivers, including economic factors, population growth, and transportation infrastructure. Our findings indicate that the size of Shanghai’s urban area in 2035 will be nearly 13 times that of 1985. Over these five decades, Shanghai’s urban centroid shifted from the northeast to the southwest, with early urban expansion concentrated in the northeast and later expansion in the southwest. New urban patches primarily emerged at the edges of the initial urban area. As time progressed, areas with higher urban expansion intensity moved outward from the city center, mirroring the trend of urban expansion hotspots. Landscape indicators also demonstrated a trend of urban patches initially spreading and subsequently clustering. Overall, the development of Shanghai’s metropolitan area exhibits substantial spatiotemporal heterogeneity. By integrating correlation analysis and generalized additive models, we quantified the impact of urban expansion drivers. The results show that economic and population factors had high correlation coefficients (over 0.97) with urban area, and proximity to the city center and road network greatly contributed to urban expansion. Our research amalgamates various theories and methods to analyze the spatiotemporal dynamics of urban expansion in metropolitan areas. This work provides a valuable data foundation to aid policymakers in designing effective metropolitan development policies.
Spatial simulation and projection of ecosystem services value (ESV) changes caused by urban growth are important for sustainable development in arid regions. We developed a new model of cellular ...automata based grasshopper optimization algorithm (named GOA-CA) for simulating urban growth patterns and assessing the impacts of urban growth on ESV changes under climate change scenarios. The results show that GOA-CA yielded overall accuracy exceeding 98%, and FOM for 2010 and 2020 were 43.2% and 38.1%, respectively, indicating the effectiveness of the model. The prairie lost the highest economic ESVs (192 million USD) and the coniferous yielded the largest economic ESV increase (292 million USD) during 2000-2020. Using climate change scenarios as urban future land use demands, we projected three scenarios of the urban growth of Urumqi for 2050 and their impacts on ESV. Our model can be easily applied to simulating urban development, analyzing its impact on ESV and projecting future scenarios in global arid regions.
This study proposes a spatial evaluation method for urban growth simulation based on moving windows, where the metrics measured within each window are considered to be those of the central cell. We ...also applied the generalized additive model to identify the quantitative relationship between the urban growth drivers and the spatial assessment metrics. A case study in Jiaxing city shows that the single-number overall accuracies (OAs) are above 94% and the figure-of-merits (FOMs) are above 27% in both 2010 and 2015. Most regions of the study area yield very high OAs and low FOMs while the regions around the administration centres yield low OAs and high FOMs. The spatial method can well indicate the model's effects on the urban simulations in different regions. The spatial assessment can report the assessment metrics of each cell to produce assessment maps as well as quantify the relationship between drivers and assessment metrics.
Detection of cytosolic dsDNA by cyclic GMP-AMP synthase (cGAS) is critical for the immune system to sense and fight against infection, but chronic activation of cGAS by self-DNA leads to autoimmune ...diseases without effective treatment yet. It was found that acetylation on either Lys384, Lys394, or Lys414 could inhibit the catalytic production of cGAMP by cGAS, and further suppressed self-DNA-induced autoimmunity. However, the implied mechanism remains unclear. Here, extensive molecular dynamics simulations combined with multiple analytical approaches were employed to uncover the allosteric inhibition mechanisms by using the K-to-Q mutations to mimic acetylation. Results suggested that the exterior loops contributed most to the conformational dynamics of cGAS, and two concerted intrinsic motions were observed: the inward/outward or twisting movement for the outer appendage of lobe 1 and the open/closed swing of the active-site loops. Mutations slightly affected the binding of dsDNA and cGAMP. The shift of the conformational sampling of the active-site loops or residues around cGAMP upon mutation might potentially explain the inhibition of cGAS activity. Moreover, the intra- and inter-molecular coupling was weakened upon mutations more or less but
via
distinct pathways. Hence, conformational dynamics play a vital role in the allosteric inhibition of cGAS upon the studied acetyl-mimic mutations. As the studied acetyl-mimic mutations are located at either the inter-lobe or inter-molecular interfaces, hence except for acetylation, our findings might help the development of new therapeutics against autoimmune diseases due to abnormal cGAS activation by designing inter-lobe or intermolecular allosteric inhibitors.
In the present study, the allosteric inhibition mechanism of cGAS upon acetyl-mimic mutations was investigated, and conformational dynamics was found to be especially critical.
Phthalate esters (PAEs) are a ubiquitous kind of environmental endocrine that disrupt chemicals, causing environmental and health issues. EstJ6 is an effective phthalate-degrading hydrolase, and its ...mutant with a combination of three non-conservative distal mutations has an improved activity against PAEs with unknown molecular mechanisms. Herein, we attempt to fill the significant gap between distal mutations and the activity of this enzyme using computational approaches. We found that mutations resulted in a redistribution of the enzyme's preexisting conformational states and dynamic changes of key functional regions, especially the lid over the active site. The outward motion of the lid upon the mutations made it easier for substrates or products to enter or exit. Additionally, a stronger substrate binding affinity and conformational rearrangements of catalytic reaction-associated residues in the mutant, accompanied by the strengthened communication within the protein, could synergistically contribute to the elevated catalytic efficiency. Finally, an attempt was made to improve the thermostability of EstJ6 upon introducing a distal disulfide bond between residues A23 and A29, and the simulation results were as expected. Together, our work explored the allosteric effects caused by distal mutations, which could provide insights into the rational design of esterases for industrial applications in the future.
The parathyroid hormone type 1 receptor (PTH1R) acts as a canonical class B G protein-coupled receptor, regulating crucial functions including calcium homeostasis and bone formation. The ...identification and development of PTH1R non-peptide allosteric modulators have obtained widespread attention. It has been found that a negative allosteric modulator (NAM) could inhibit the activation of PTH1R, but the implied mechanism remains unclear. Herein, extensive molecular dynamics simulations together with multiple analytical approaches are utilized to unravel the mechanism of PTH1R allosteric inhibition. The results suggest that the binding of NAM destabilizes the structure of the PTH1R-PTH-spep/qpep (the C terminus of Gs/Gq proteins) complexes. Moreover, the presence of NAM weakens the binding of PTH/peps (spep and qpep) and PTH1R. The intra- and inter-molecular couplings are also weakened in PTH1R upon NAM binding. Interestingly, compared with our previous study of the positive allosteric effects induced by extracellular Ca
, the enhanced correlation between the PTH and G-protein binding sites is significantly reduced by the replacement of this negative allosteric regulator. Our findings might contribute to the development of new therapeutic agents for diseases caused by the abnormal activation of PTH1R.
Abstract
Biological membranes (biomembranes) are one of the most complicated structures that allow life to exist. Investigating their structure, dynamics, and function is crucial for advancing our ...knowledge of cellular mechanisms and developing novel therapeutic strategies. However, experimental investigation of many biomembrane phenomena is challenging due to their compositional and structural complexity, as well as the inherently multi‐scalar features. Computational approaches, particularly molecular dynamics (MD) simulations, have emerged as powerful tools for addressing the atomic details of biomembrane systems, driving breakthroughs in our understanding of biomembranes and their roles in cellular function. This review presents an overview of the latest advancements in related computational approaches, from force fields and model construction to MD simulations and trajectory analysis. We also discussed current hot research topics and challenges. Finally, we outline future directions, emphasizing the integration of force field development, enhanced sampling techniques, and data‐driven approaches to accelerate the growth of this field in the years to come. We aim to equip readers with an understanding of the promise and limitations of emerging computational technologies in biomembrane systems and offer valuable recommendations for future research endeavors.
This article is categorized under:
Structure and Mechanism > Computational Biochemistry and Biophysics
Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods
