Three-dimensional Complex Research Articles

Equivariant Line Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Binding affinity prediction of three-dimensional (3D) protein-ligand complexes is critical for drug repositioning and virtual drug screening. Existing approaches usually transform a 3D protein-ligand complex to a two-dimensional (2D) graph, and then use graph neural networks (GNNs) to predict its binding affinity. However, the node and edge features of the 2D graph are extracted based on invariant local coordinate systems of the 3D complex. As a result, these approaches can not fully learn the global information of the complex, such as the physical symmetry and the topological information of bonds. To address these issues, we propose a novel Equivariant Line Graph Network (ELGN) for binding affinity prediction of 3D protein-ligand complexes. The proposed ELGN firstly adds a super node to the 3D complex, and then builds a line graph based on the 3D complex. After that, ELGN uses a new E(3)-equivariant network layer to pass the messages between nodes and edges based on the global coordinate system of the 3D complex. Experimental results on two real datasets demonstrate the effectiveness of ELGN over several state-of-the-art baselines.

Fabrication of Microstructure Arrays via Localized Electrochemical Deposition

Localized electrochemical deposition microadditive manufacturing (AM) (LECD-µAM) technology represents a nontraditional manufacturing method applied for the layer-by-layer fabrication of metal microstructures via a fully automatic feedback mechanism. In terms of material utilization and complex structure formation, the proposed technology exhibits great potential for microstructure fabrication. The LECD-µAM technology introduced in this study involves the reduction of metal cations in the electrolyte to form metal microstructures. This study showed the flow simulation of an electrolyte in the cantilever probe and pressure distribution at the probe tip. In addition, the effect of extrusion pressure on the deposition structure was investigated experimentally. Combined with the experimental results, we discussed the effects of LECD-µAM technology on deposition outcomes and optimized parameters and designed a printing route for the deposition of complex metal microstructure arrays with smooth surfaces. The proposed technology attained a deposition rate and a microstructural copper content of 0.961 µm/s and 99.5%. In addition, LECD-µAM technology can be performed at room temperature, has low environmental requirements and cost, provides a good deposition surface, and holds great potential for the manufacture of three-dimensional and other complex microstructure arrays.

Characterization of deep-sea sponge ground (Asconema setubalense) using structure from motion methodology.

The hexactinellid sponge Asconema setubalenseKent, 1870 is a deep-sea species characterized by its expansive cup-shaped morphology, which contributes significantly to the three-dimensional complexity of the marine ecosystems. This sponge forms grounds that offer protection to pelagic organisms and juvenile stages. Despite its ecological relevance, there is a lack of information on the ecology, behavior and population structure of this species. The research aimed to conduct a multitemporal analysis of this sponge in the Aviles Canyon System over a ten-year period, focusing on spatial distribution and abundance. Changes in fishing pressure were estimated using the presence of fishing gears as a proxy. Additionally, the study sought to provide a detailed morphometric description through 3D photogrammetric reconstructions based on the latest data. The multi-temporal analysis revealed a subtle increase in sponge density, particularly at depths ranging from 320 to 390 m, exhibiting an irregular spatial distribution in 2022, with maximal values of 0.08 individuals/m2. Despite a small decrease on the loss of fishing gears in the overlapping area between samplings in 2012 and 2022, there was not a clear indication of a decline in fishing pressure over the years. Notably, more sightings of fishing gears were found in transect IC222TV_16 (0.07 gears/m2) than in IC222_TV02 (0.04 gears/m2) in 2022, suggesting potential spatial preferences for fishing activities. Visual analysis of temporal populations revealed an increase of 7% in specimen perturbations over ten years, with the population in IC222_TV16 being healthier (9% of the individuals presenting severe deformations) than in IC222_TV02 (40%). High-density fishing gear locations coincided with areas inhabited by sponges displaying the highest perturbation levels in both transects. Morphometric analysis using data from 2022 indicated a prevalence of individuals with heights concentrated between 0.18 and 0.38 m, osculum and flounce diameters reaching 0.4 and 0.56 m and osculum and flounce surfaces of 0.02–0.04 and 0.06–0.19 m2 respectively. Over 80% of measured specimens exhibited a high degree of asymmetry. Strong correlations were observed between heights and osculum and flounce surfaces, but external factors may be included for explaining wall deformities. These findings contribute valuable insights into the characterization of A. setubalense, serving as a foundation for future research in the area. Moreover, this work highlights the promising potential of photogrammetry as an efficient tool for monitoring of vulnerable marine ecosystems (VME) and marine protected areas.

Morphological insights into the three-dimensional complexity of rhodolith beds

The ecological importance of rhodolith beds stems from their role as structurally complex three-dimensional habitat formed by free-living red calcareous algae. Their structural singularity is due to the great variety of complex and branching morphologies exhibited by rhodoliths that create interstitial spaces and increase their surface area. This increases the ecological niches for cryptofauna and provide refuge for a high number of organisms, which is why rhodolith beds are considered biodiversity hotspots. In this work, we studied a rhodolith bed located in the Menorca Channel, formed by several species of red calcareous algae that exhibit a great variety of morphologies and form an extensive and heterogeneous habitat. This study explored the morphological diversity of the rhodolith bed, comparing the ‘Core Habitat’ (within the center of the bed with the highest densities of rhodoliths) with the boundaries or ‘Adjacent Habitat’ where rhodolith density was lower. Our results show that all rhodolith growth forms (branched, pralines and boxwork) in the Core Habitat had higher interstitial space and were larger than the ones from adjacent zones. Moreover, we explored the three-dimensional techniques to study the morphological characteristics that have historically been studied in two dimensions. This study contributes to the knowledge of morphological diversity in well-preserved rhodolith beds from continental shelves in the western Mediterranean Sea and reinforces the use of three-dimensional measurements, specifically the interstitial space of branched rhodoliths, to provide more accurate data on habitat complexity.

Peritectic solidification patterns in the Zn–Ag system captured in three- and four-dimensions

Microstructure selection in two-phase peritectic alloys has been a long-standing topic of fundamental importance. The bicontinuous microstructures arising from peritectic solidification have presented significant challenges for analysis due (in part) to our reliance on two-dimensional (2D) sections, which limits our ability to interpret the full three-dimensional (3D) complexity. Additionally, understanding growth mechanisms based solely on postmortem data has proven to be challenging because the extent of the solid-state peritectic transformation is unknown. Here, we employed X-ray imaging techniques to acquire detailed 3D data and visualize in real-time the dynamics of peritectic solidification in a model system of composition Zn-9.53 wt.% Ag. This paper offers a detailed examination of the origin of two-phase (Zn) + AgZn3 microstructures during directional solidification: specifically, our work investigates the influence of velocity, thermal gradient, and sample size on microstructure selection, namely, rod-like, singly-banded, and multiply-banded structures. Importantly, we find at low velocities V (0.07–0.1 μm/s) and a low thermal gradient G (3 K/mm) the emergence of peritectic (Zn) channels, interwoven within and between primary AgZn3 columnar grains. While these microstructures are suggestive of coupled growth morphologies, real-time imaging proves that the two solids are instead decoupled at the growth front. Meanwhile, at thermal gradients 10× higher, we observe a partially dendritic and partially banded structure that has not been reported before, to the best of our knowledge. We initiate a discussion on the formation of such structures, with broad implications to a wide range of metallic, semi-metallic, and organic peritectic alloys.

Microfluidic chips for microbially induced calcium carbonate precipitation: Advantages, challenges, and insights

Microbially induced calcium carbonate precipitation (MICP) has garnered significant attention as a biomineralization process with diverse applications spanning from construction to environmental remediation. To propel MICP research and deepen our comprehension of MICP mechanisms, microfluidic chips have emerged as potent tools offering precise control over environmental parameters and real-time observations. Herein, we explore the benefits and challenges associated with employing microfluidic chips as a platform for investigating MICP. The advantages of microfluidic chips lie in their capacity to create controlled microenvironments conducive to emulating specific conditions crucial for MICP. The high-throughput nature of these devices accelerates experimentation by facilitating simultaneous testing of various microbial strains and nutrient compositions. Throughout the MICP process, observations were made on the behaviors of both bacterial cells and CaCO3 cementation. The inherent reduction in reagent consumption offered by microfluidics is both cost-effective and environmentally friendly. However, scaling up from microscale findings to practical applications necessitates careful consideration. Fully replicating the three-dimensional complexity and heterogeneous structures of the soil matrix, which influence microbial behavior, mineral distribution, and overall precipitation dynamics, using microfluidic chips remains challenging. Additionally, certain environmental complexities, including macroscopic soil components such as organic matter and various particle types, which significantly affect microbial activities and mineral precipitation patterns, may be difficult to replicate in microfluidic setups. However, microfluidic chips stand as invaluable tools for advancing MICP research. By addressing the advantages and disadvantages outlined here, researchers can harness the capabilities of microfluidic systems to unravel the intricacies of MICP, ultimately bridging the gap between fundamental understanding and real-world applications.

Mechanical characterization of lining under three-dimensional complex load during shield posture adjustment

The shield tunneling method is widely used in urban underpass construction. However, research on the mechanical characteristics of segments during construction is insufficient. Throughout the shield tunneling construction process, segments undergo a diverse range of loads, and their modes become complex. During the adjustment of the posture of the shield machine along a curved path, segments must withstand three-dimensional uneven loads from the shield tail brush and extrusion of the shield shell, in addition to conventional loads. Thus, this study delves into the mechanical characterization of the lining during shield posture adjustment. First, three-dimensional refined models of the longitudinal and circumferential joints were established to investigate their bending and shear mechanical properties. Using the joint and shield tail brush stiffness models, a nonlinear spring-connector-shell model was developed for the mechanical analysis of segments during posture adjustment. Subsequently, a three-dimensional segment load model was formulated for the construction period. The segment response under the influence of different posture adjustments was examined using a numerical model of a tunnel subjected to a complex three-dimensional load. Furthermore, a multistage model of the segment response under various posture adjustments was established. This model serves as a valuable reference for engineering applications.

A serendipity fully discrete div-div complex on polygonal meshes

In this work we address the reduction of face degrees of freedom (DOFs) for discrete elasticity complexes. Specifically, using serendipity techniques, we develop a reduced version of a recently introduced two-dimensional complex arising from traces of the three-dimensional elasticity complex. The keystone of the reduction process is a new estimate of symmetric tensor-valued polynomial fields in terms of boundary values, completed with suitable projections of internal values for higher degrees. We prove an extensive set of new results for the original complex and show that the reduced complex has the same homological and analytical properties as the original one. This paper also contains an appendix with proofs of general Poincaré–Korn-type inequalities for hybrid fields.

Nonlinear ray tracing in focused fields, part 2. Tracing the flux: tutorial

In this three-part paper series, we develop a method to trace the lines of flux through a three-dimensional wavefield by following a direction that is governed by the derivative of the phase at each point, a process that is best described as flux tracing but which we interchangeably name “nonlinear ray tracing.” In the first part we focused on the high-speed calculation of focused three-dimensional complex wavefields in the paraxial approximation for TEM00 and TEM01 laser modes. The algorithms developed in the first paper are first used to generate the three-dimensional grid of samples of the complex wavefield in the focal region. In this second part, we focus on tracing a flux through this three-dimensional point cloud. For a given “ray” at an arbitrary position in the 3D volume, interpolation of the three-dimensional samples is applied to determine the derivative of the phase (normal to the direction of propagation) at the ray position, which is then used to direct the ray as it “propagates” forward in a straight line over a short distance to a subsequent plane; the process is repeated between consecutive planes. The initial origin of the ray can be chosen arbitrarily at any point, and the ray can then be traced through the volume with appropriate interpolation. Results are demonstrated for focused wavefields in the absence of aberrations, corresponding to the cases highlighted in the first paper. Some of the most interesting results relate to focused Laguerre-Gaussian beams, for which the rays are found to spiral at different rates of curvature. In the third paper we extend the application of this algorithm to the investigation of lens aberration.

Nonlinear ray tracing in focused fields, part 1. Calculation of 3D focused wavefields: tutorial

In this three-part paper series, we develop a method to trace the lines of flux through a three-dimensional wavefield by following a direction that is governed by the derivative of the phase at each point, a process that is best described as flux tracing but which we interchangeably name “nonlinear ray tracing.” In this first part, we provide a tutorial on the high-speed calculation of three-dimensional complex wavefields, which is a necessary precursor to flux tracing. The basis of this calculation is the angular spectrum method, a well-known numerical algorithm that can be used to efficiently and accurately calculate diffracted fields for numerical apertures <0.7. It is known that this approach yields identical predictions to the first Rayleigh–Sommerfeld solution. We employ the angular spectrum method to develop two algorithms that generate the 3D complex wavefield in the region of focus of a lens. The first algorithm is based on the thin lens approximation, and the second is based on the concept of an ideal lens, which can be modeled using an optical Fourier transform. We review how these algorithms can be used to calculate focused laser beams with TEM00 and TEM01 laser profiles. The three-dimensional sampling requirements of the focused field are explained in detail, and expressions for the computational and memory efficiency of the two algorithms are developed. These two algorithms generate the 3D scaffold for the flux tracing method developed in the second paper, and in the third paper we highlight the application of the method to understanding monochromatic lens aberration. Disregarding the second and third papers, this first paper will serve as a practical tutorial for anyone seeking to compute focused fields in three dimensions.

Bending, Twisting, and Propulsion of Photoreactive Crystals by Controlled Gas Release.

The rapid release of gas by a chemical reaction to generate momentum is one of the most fundamental ways to elicit motion that could be used to sustain and control the motility of objects. We report that hollow crystals of a three-dimensional supramolecular metal complex that releases gas by photolysis can propel themselves or other objects and advance in space when suspended in mother solution. In needle-like regular crystals, the reaction occurs mainly on the surface and results in the formation of cracks that evolve due to internal pressure; the expansion on the cracked surface of the crystal results in bending, twisting, or coiling of the crystal. In hollow crystals, gas accumulates inside their cavities and emanates preferentially from the recess at the crystal terminus, propelling the crystals to undergo directional photomechanical motion through the mother solution. The motility of the object which can be controlled externally to perform work delineates the concept of "crystal microbots", realized by photoreactive organic crystals capable of prolonged directional motion for actuation or delivery. Within the prospects, we envisage the development of a plethora of light-weight, efficient, autonomously operating robots based on organic crystals with high work capacity where motion over large distances can be attained due to the large volume of latent gas generated from a small volume of the crystalline solid.

Recent advances in polymers, preparation techniques, applications and future perspectives of hydrogels

Drug delivery via hydrogel is one of the most effective methods. Hydrogels have been described as polymeric water-swollen materials and retain water in distinctive three-dimensional complex. These are classified as pH sensitive hydrogels, temperature sensitive hydrogels, homo-polymer hydrogels, co-polymer hydrogels and Interpenetrating Network (IP-N) hydrogel. Hydrogels can be prepared via various techniques, including physical crosslinking, chemical crosslinking, free radical polymerization, photo-initiator’s and hydrogen bonding. Various polymers in manufacturing includes pectin, chitosan, cyclodextrin and carrageenan, etc. This review aims to describes hydrogels for drug delivery, classifications, preparation techniques, various polymers in hydrogel preparation and highlights novel applications of hydrogels in medicine.

Characterization and Quantitative Assessment of Shale Fracture Characteristics and Fracability Based on a Three-Dimensional Digital Core

At present, assessment techniques for the fracability of shale reservoirs, which rely on the formation of an effective fracture network, are scarce. Hence, in order to assess the fracability, it is critical to establish a quantitative correlation between the pattern of fracture distribution after fracture and fracability. The present investigation utilizes three-dimensional digital core technology and triaxial compression experiments to simulate the fracturing process in typical domestic shale reservoir cores. In addition to utilizing the maximum ball algorithm to extract fracture images, a number of other techniques are employed to compute the spatial quantitative parameters of the fractures, including least squares fitting, image tracking algorithms, and three-dimensional image topology algorithms. The introduction of the notion of three-dimensional fracture complexity serves to delineate the degree of successful fracture network formation subsequent to fracturing. A quantitative fracability characterization model is developed by integrating the constraints of fracture network formation potential and fragmentation potential. The results of this study show that the quantitative characterization of the characteristic parameters of cracks can be achieved by establishing a method for extracting crack information as well as parameters after core compression and completing the construction of a three-dimensional complexity characterization model. Meanwhile, the three-dimensional post-compression fracture image validation shows that the core fracturability index can better reflect the actual fracturing situation, which is in line with the microseismic monitoring results, and significantly improves the accuracy of fracturability characterization, which is an important guideline for the fracturing design of shale gas reservoirs.

Revolutionizing Dental Implant Research: A Systematic Review on Three-Dimensional In Vitro Models.

Dental implants have been clinically used for almost five decades with high success rates. In vitro research models used in implant dentistry are limited to two-dimensional experiments, which are reproducible and well adapted to evaluate a single parameter but do not reproduce the complexity of clinical settings. On the contrary, the invivo research models using animals offer similar histological and anatomical features to humans, and tissue healing can be close to a clinical situation, but those models are usually accompanied with ethical concerns, and their outcomes could not be extrapolated to humans because of interspecies variabilities. This makes the development of novel in vitro models that recapitulate physiological events occurring during dental implant placement of particular interest for current research in dentistry. Also, such models could be challenged by setting a pathological environment (peri-implantitis) to better understand the disease and eventually serve as a platform to evaluate novel treatment modalities. The aim of this systematic literature review was to cover all the in vitro three-dimensional (3D) complex models available for research in implant dentistry. To accomplish this, a comprehensive search of the literature present on Scopus and PubMed databases was done using specific keywords, as well as inclusion/exclusion criteria. Out of 1334 articles found, we have finally included 27 articles in this review with publication dates between 2001 and 2022. In those articles, the 3D models were designed to study tissue-implant interface behavior in bone or gingival tissue. The articles focused on simulating implant integration, evaluating the effect of different conditions on implant integration, or developing an infection model for the implant integration process. The methods used involved implant material and cells organized in a specific 3D structure. The 3D models developed were able to simulate the process of dental implant osseo- and soft tissue integration and lead to results comparable with conventional in vitro and invivo models. A relatively limited number of articles were obtained, which indicates that this is an emerging field, highly dependent on progresses made in biotechnologies and tissue engineering, and that further investigation is needed to enhance these 3D in vitro models.

Green processing and characterization of Novel HETERO-ligand Co(II) complexes with cyanopyridine derivatives: Quantitative structure, Computational assessment, and Biological activity relationship

Novel hetero-ligand Co(II) complexes prepared from mixed ligand of ammonium metavanadate and cyanopyridine derivatives as a polydentate ligands by an easy and green ball milling technique to limit the use of hazardous compounds in the preparation process. The isolated solid chelates were demonstrated via various spectroscopic techniques including (13C NMR, 1H NMR, UV-visible, IR, SEM, XRD, and EXD), thermal analyses (TG, DTG), and elemental analyses. Also, the optimized structure for the isolated solid compounds were supported by applying DFT theory along with the calculations of altered energetic parameters for instance EHOMO and ELUMO. Moreover, the optimized target isolated solid compounds were proposed to be used for docking and were ordered using the defaulting methodology of the Ligprep software in Schrödinger's suite. Whereas, the three-dimensional complex structures of E. coli (PDB code: 1 xk6), S. aureus (PDB code: 6 gyw), C. albicans (PDB code: 3 ppc) and Covid 19 virus (PDB code: 7 jpy) were regained from the Protein Data Bank. Lastly, Bleomycin dependent DNA damage, antioxidant, and anti-microbia were performed for all isolated solid compounds to invistigate the impact of complexation on the biological activity of cyanopyridine derivatives.

Enhancing Generalizability in Protein-Ligand Binding Affinity Prediction with Multimodal Contrastive Learning.

Improving the generalization ability of scoring functions remains a major challenge in protein-ligand binding affinity prediction. Many machine learning methods are limited by their reliance on single-modal representations, hindering a comprehensive understanding of protein-ligand interactions. We introduce a graph-neural-network-based scoring function that utilizes a triplet contrastive learning loss to improve protein-ligand representations. In this model, three-dimensional complex representations and the fusion of two-dimensional ligand and coarse-grained pocket representations converge while distancing from decoy representations in latent space. After rigorous validation on multiple external data sets, our model exhibits commendable generalization capabilities compared to those of other deep learning-based scoring functions, marking it as a promising tool in the realm of drug discovery. In the future, our training framework can be extended to other biophysical- and biochemical-related problems such as protein-protein interaction and protein mutation prediction.

Seasonal variations in the mechanisms of understory herb diversity in a temperate forest in Northeast China

Herbaceous plants contribute greatly to plant diversity and play an important role in regulating the structure and functioning of forest ecosystems. Comparing with woody species, herbs exhibit higher sensitivity to seasonal changes from spring-growth to autumn-mortality. Despite extensive research on understory herb diversity (e.g., abundance and richness) in forests, how the underlying mechanisms change across seasons remain unclear, especially in temperate forests. We explored the seasonal dynamics of herb diversity (here abundance and richness) by surveying herbs of 174 quadrats (1 m × 1 m) in a 25-ha (500 m × 500 m) temperate forest in spring, summer, and autumn of 2022, respectively. We examined the effects of overstory trees (diversity, composition, and three-dimensional (3D) structural complexity detected by LiDAR), topography (elevation, slope, and aspect), and microsite conditions (light availability, soil nutrients, and soil water content) on herb diversity in different seasons. We found a similar seasonal pattern for herb abundance and richness, i.e., both decreased from spring to summer and then to autumn, but the driving mechanisms differed remarkably across seasons. Specifically, the importance of overstory trees, topography, and microsite conditions on herb abundance vs. richness varied inversely across seasons. For herb abundance, the importance of overstory trees (primarily 3D structural complexity) increased from spring to autumn, while the importance of topography decreased. Conversely, for herb richness, the importance of overstory trees decreased from spring to autumn, while the importance of topography increased. Microsite conditions governed spatial variations of herb abundance in all seasons but only in autumn for herb richness, with importance of soil nutrients remaining relatively constant while that of soil water content and light availability changed greatly across seasons. Our results demonstrate substantial seasonal variations in driving mechanisms of herb diversity in the temperate forest. These differentiated responses of herb abundance and richness to different drivers across seasons further highlight the significance of considering seasonal variations of the mechanisms underlying understory plant diversity in forest biodiversity conservation.

Time-varying dynamic modeling of micro-milling considering tool wear and the process parameter identification

Micro-milling technology is widely used in the manufacturing of micro three-dimensional complex parts in aerospace, mechanical equipment, biomedical devices, electronic components, and other fields due to its advantages of high machining accuracy, small size, and complex surface. Consequently, understanding its machining process is essential. This study proposes a time-varying dynamic micro-milling process model with the effects of tool runout, tool wear, and cutting status and explores the stable cutting domain of real-time machining. Considering the time-varying characteristics of the cutting process, combined with measured data and particle filtering method, the cutting force coefficients and tool wear parameters in the dynamic model at different times are identified. The dynamic equation of micro-milling is derived using a discrete method, and the stability of the cutting process is evaluated. Multiple cutting experiments are conducted on the Al6061, and the test data are compared with simulated values. The comparison results show that the accuracy of the proposed model in predicting the cutting state can reach 100%, and the average error of cutting force prediction is 7.72%. The research results can provide theoretical guidance for the safety evaluation of micro-milling and the selection of machining conditions.

Biocatalytic strategy for the construction of sp3-rich polycyclic compounds from directed evolution and computational modelling.

Catalysis with engineered enzymes has provided more efficient routes for the production of active pharmaceutical agents. However, the potential of biocatalysis to assist in early-stage drug discovery campaigns remains largely untapped. In this study, we have developed a biocatalytic strategy for the construction of sp3-rich polycyclic compounds via the intramolecular cyclopropanation of benzothiophenes and related heterocycles. Two carbene transferases with complementary regioisomer selectivity were evolved to catalyse the stereoselective cyclization of benzothiophene substrates bearing diazo ester groups at the C2 or C3 position of the heterocycle. The detailed mechanisms of these reactions were elucidated by a combination of crystallographic and computational analyses. Leveraging these insights, the substrate scope of one of the biocatalysts could be expanded to include previously unreactive substrates, highlighting the value of integrating evolutionary and rational strategies to develop enzymes for new-to-nature transformations. The molecular scaffolds accessed here feature a combination of three-dimensional and stereochemical complexity with 'rule-of-three' properties, which should make them highly valuable for fragment-based drug discovery campaigns.

A Physics-Based Seismic Risk Assessment of the Qujiang Fault: From Dynamic Rupture to Disaster Estimation

This study achieved the construction of earthquake disaster scenarios based on physics-based methods—from fault dynamic rupture to seismic wave propagation—and then population and economic loss estimations. The physics-based dynamic rupture and strong ground motion simulations can fully consider the three-dimensional complexity of physical parameters such as fault geometry, stress field, rock properties, and terrain. Quantitative analysis of multiple seismic disaster scenarios along the Qujiang Fault in western Yunnan Province in southwestern China based on different nucleation locations was achieved. The results indicate that the northwestern segment of the Qujiang Fault is expected to experience significantly higher levels of damage compared to the southeastern segment. Additionally, there are significant variations in human losses, even though the economic losses are similar across different scenarios. Dali Bai Autonomous Prefecture, Chuxiong Yi Autonomous Prefecture, Yuxi City, Honghe Hani and Yi Autonomous Prefecture, and Wenshan Zhuang and Miao Autonomous Prefecture were identified as at medium to high seismic risks, with Yuxi and Honghe being particularly vulnerable. Implementing targeted earthquake prevention measures in Yuxi and Honghe will significantly mitigate the potential risks posed by the Qujiang Fault. Notably, although the fault is within Yuxi, Honghe is likely to suffer the most severe damage. These findings emphasize the importance of considering rupture directivity and its influence on ground motion distribution when assessing seismic risk.