High throughput virtual screening and validation of Plant-Based EGFR L858R kinase inhibitors against Non-Small cell lung Cancer: An integrated approach Utilizing GC-MS, network Pharmacology, Docking, and molecular dynamics.

Lung cancer ranks as the 2nd most common cancer globally. It's the most prevalent cancer in men and the 2nd most common in women. The prominent events in EGFR-mutated non-small-cell lung cancer (NSCLC) include the emergence of the L858R mutation within EGFR exon 21. Despite the promising efficacy of EGFR inhibitors in managing lung cancer, the development of acquired resistance poses a significant hurdle. In the current investigation, we focused on the screening of two phytochemicals, namely Dehydrocostus lactone and Mokkolactone, derived from the Saussurea lappa plant, as potential inhibitors targeting EGFR L858R mutant lung cancer. The chloroform and ethanol extract of the plant demonstrated anti-proliferative activity through the Resazurin chemosensitivity assay, exhibiting an IC50 value of 37.90 ± 0.29 µg/ml with selectivity index 2.4. Through a GC-MS study, we identified 11 phytochemicals for further insilico analysis. These compounds underwent ADMET assessment followed by drug likeliness analysis before being subjected to molecular docking against EGFR L858R, identified through protein-protein interaction network analysis. All phytochemicals exhibited binding energy scores ranging from -6.9 to -8.1 kcal/mol. Dehydrocostus lactone and Mokkolactone were specifically identified for their binding profile. Findings from 100 ns molecular dynamics simulations demonstrated their enhanced stability compared to the reference ligand DJK. This was evident in the root mean square deviation (RMSD) values, ranging from 0.23 ± 0.01 nm to 0.30 ± 0.05 nm, the radius of gyration values, from 1.71 ± 0.01 nm to 1.72 ± 0.01 nm, and the solvent accessible surface area values, from 155.39 ± 2.40 nm2 to 159.32 ± 2.14 nm2. Additionally, favourable characteristics were observed in terms of hydrogen bonding, principal component analysis, and free energy landscape analysis. Examination of their electronic structure via density functional theory revealed efficient properties, with the highest occupied molecular orbital-least unoccupied molecular orbital energy gap values ranging from -3.984 eV to -6.547 eV. Further, in vivo analysis is required to gain a more comprehensive understanding and efficacy of these identified phytochemicals against lung cancer.

A study on the spatial distribution characteristics and driving factors of traditional villages in the southeast coast of China: A case study of Puxian, Fujian.

Traditional villages are the common historical and cultural heritage of all mankind. With the intensification of urbanization, the continuation of traditional villages and the inheritance of historical and cultural heritage are facing risks. The research on the driving factors affecting the spatial distribution characteristics, heterogeneity and human land interaction of traditional villages provides a new idea for the protection of traditional villages. This study takes 137 traditional villages in Puxian area, a typical cultural area in the southeast coast, as the research object, analyzes the spatial distribution pattern of traditional villages by using spatial analysis method, and selects 13 factors to analyze the main driving forces and interaction mechanisms through geographical detectors. The results show that: (1) Puxian traditional villages are clustered and distributed, and the distribution among counties is uneven, mainly in the state of "one cluster and many scattered points" with more coastal areas and less mountainous areas. (2) Puxian traditional villages are mainly affected by many factors such as nature, space, society and culture. They are more densely distributed in areas with rich cultural heritage, fertile land, flat terrain, suitable climate, close to water systems, developed transportation, backward economy and dense population. (3) Cultural factors are the primary factors affecting the spatial distribution of traditional villages, the order of driving factors' explanatory power is: intangible cultural heritage (0.5160) > protected cultural relic units (0.3591) > distance from railway (0.3255) > night light remote sensing (0.3179) > elevation (0.3012) > population density (0.2671) > slope (0.2032) > soil type (0.1804) > precipitation (0.1750) > temperature (0.1744) > land use (0.1492) > distance from river (0.0691)>distance from highway (0.0530). The interaction of intangible cultural heritage, protected cultural relic units and distance from the railway is the dominant factor for the spatial differentiation of traditional villages. Among them, the interaction of intangible cultural heritage∩distance from the railway is the strongest, and the q-value is 0.79, which proves that the interpretation ability of the two factor model is much higher than that of the single factor model. The results of this study reflect that traditional villages and nature, space, society and culture are interdependent, so the protection of traditional villages should be adapted to local conditions.