GSScore: a novel Graphormer-based shell-like scoring method for protein-ligand docking.

Protein-ligand interactions (PLIs) are essential for cellular activities and drug discovery. But due to the complexity and high cost of experimental methods, there is a great demand for computational approaches to recognize PLI patterns, such as protein-ligand docking. In recent years, more and more models based on machine learning have been developed to directly predict the root mean square deviation (RMSD) of a ligand docking pose with reference to its native binding pose. However, new scoring methods are pressingly needed in methodology for more accurate RMSD prediction. We present a new deep learning-based scoring method for RMSD prediction of protein-ligand docking poses based on a Graphormer method and Shell-like graph architecture, named GSScore. To recognize near-native conformations from a set of poses, GSScore takes atoms as nodes and then establishes the docking interface of protein-ligand into multiple bipartite graphs within different shell ranges. Benefiting from the Graphormer and Shell-like graph architecture, GSScore can effectively capture the subtle differences between energetically favorable near-native conformations and unfavorable non-native poses without extra information. GSScore was extensively evaluated on diverse test sets including a subset of PDBBind version 2019, CASF2016 as well as DUD-E, and obtained significant improvements over existing methods in terms of RMSE, $R$ (Pearson correlation coefficient), Spearman correlation coefficient and Docking power.

Distribution patterns and drivers of urban green space and plant diversity in Haikou, China.

Investigating historical and ongoing changes in urban green space (UGS) and urban plant diversity (UPD) provides critical insights into urban ecology and urban planning development. The present study illuminates some of the transformations which can occur in rapidly developing urban landscapes. In this work, we used 30 m resolution images from the Landsat 5 satellite from 2015 to investigate UGS patterns in Haikou City, China. Metrics of UPD were obtained using field surveys, allowing the proportion of UGS and UPD to be determined in each urban functional unit (UFU) of Haikou. The results revealed that leisure and entertainment areas (such as parks) had the highest diversity, whereas roads and transportation hubs had the lowest. More frequent anthropogenic maintenance had a positive effect on the total number of species, including cultivated, tree, and herb species. Similarly, increased watering frequency had a positive impact on the diversity of cultivated and shrub species. By providing demonstrating a crucial link between UGS and UPD, the results provide valuable information for planning sustainable urban development in Haikou City and other tropical regions. They highlight the important role of UGS in maintaining biodiversity and providing a range of ecosystem services. This research will inform policymakers and urban planners about the need to consider UGS and UPD in urban planning and management process, in order to promote sustainability and conservation of biodiversity.

ViTScore: A Novel Three-Dimensional Vision Transformer Method for Accurate Prediction of Protein-Ligand Docking Poses.

Protein-ligand interactions (PLIs) are essential for cellular activities and drug discovery, and due to the complexity and high cost of experimental methods, there is a great demand for computational approaches, such as protein-ligand docking, to decipher PLI patterns. One of the most challenging aspects of protein-ligand docking is to identify near-native conformations from a set of poses, but traditional scoring functions still have limited accuracy. Therefore, new scoring methods are urgently needed for methodological and/or practical implications. We present a novel deep learning-based scoring function for ranking protein-ligand docking poses based on Vision Transformer (ViT), named ViTScore. To recognize near-native poses from a set of poses, ViTScore voxelizes the protein-ligand interactional pocket into a 3D grid labeled by the occupancy contribution of atoms in different physicochemical classes. This allows ViTScore to capture the subtle differences between spatially and energetically favorable near-native poses and unfavorable non-native poses without needing extra information. After that, ViTScore will output the prediction of the root mean square deviation (rmsd) of a docking pose with reference to the native binding pose. ViTScore is extensively evaluated on diverse test sets including PDBbind2019 and CASF2016, and obtains significant improvements over existing methods in terms of RMSE, R and docking power. Moreover, the results demonstrate that ViTScore is a promising scoring function for protein-ligand docking, and it can be used to accurately identify near-native poses from a set of poses. Furthermore, the results suggest that ViTScore is a powerful tool for protein-ligand docking, and it can be used to accurately identify near-native poses from a set of poses. Additionally, ViTScore can be used to identify potential drug targets and to design new drugs with improved efficacy and safety.

Spatiotemporal Variation of Urban Plant Diversity and above Ground Biomass in Haikou, China.

Understanding the drivers of urban plant diversity (UPD) and above ground biomass (AGB) in urbanized areas is critical for urban ecosystem services and biodiversity protection. The relationships between UPD and AGB have been investigated simultaneously. However, the drivers of UPD and AGB have been explored independently in tropical coastal areas at different time points. To fill this gap, we conducted a remote sensing interpretation, field plant plot surveys, and compiled socioeconomic and urban greening management survey data. We conducted spatial analyses to investigate the relationships among UPD and socioeconomic variables across different primary and secondary urban functional units (UFUs) in the tropical urban ecosystems of the coastal city of Haikou, China. The primary UFUs with the highest AGB were the recreation and leisure districts in 2015 and 2021. In 2015, AGB was mainly correlated with the number of herb species in undeveloped land and the districts of industry, business, recreation, and leisure. In 2021, AGB was affected primarily by the frequency of fertilizing, maintenance, and watering. Our study found that the relationship between UPD and AGB varied across time and space in Haikou. The plant diversity and AGB's response to human activities and socioeconomics appear to have a time-lag effect. These results provide new insights in understanding how management decisions affect urban vegetation and could be used to guide future urban green space planning in Haikou.

TRScore: a 3D RepVGG-based scoring method for ranking protein docking models.

MOTIVATION: Protein-protein interactions (PPI) play important roles in cellular activities. Due to the technical difficulty and high cost of experimental methods, there are considerable interests towards the development of computational approaches, such as protein docking, to decipher PPI patterns. One of the important and difficult aspects in protein docking is recognizing near-native conformations from a set of decoys, but unfortunately, traditional scoring functions still suffer from limited accuracy. Therefore, new scoring methods are pressingly needed in methodological and/or practical implications. RESULTS: We present a new deep learning-based scoring method for ranking protein-protein docking models based on a 3D RepVGG network, named TRScore. To recognize near-native conformations from a set of decoys, TRScore voxelizes the protein-protein interface into a 3D grid labeled by the number of atoms in different physicochemical classes. Benefiting from the deep convolutional RepVGG architecture, TRScore can effectively capture the subtle differences between energetically favorable near-native models and unfavorable non-native decoys without needing extra information. TRScore was extensively evaluated on diverse test sets including protein-protein docking benchmark 5.0 update set, DockGround decoy set, as well as realistic CAPRI decoy set and overall obtained a significant improvement over existing methods in cross-validation and independent evaluations. AVAILABILITY AND IMPLEMENTATION: Codes available at: https://github.com/BioinformaticsCSU/TRScore.

Complete plastome sequence of Balakata baccata (Roxb.) Esser (Euphorbiaceae).

Balakata baccata belongs to the family Euphorbiaceae and is distributed in Yunnan province, China, and other southeast Asian countries, e.g., Bangladesh, Cambodia, India, Indonesia, etc. Here, we report and characterize the complete plastome of B. baccata. The complete plastome is 163,988 bp in length and contains a typical quadripartite structure and gene content found in angiosperms, including two inverted repeat (IR) regions of 27,274 bp, a large single-copy (LSC) region of 90,946 bp and a small single-copy (SSC) region of 18,494 bp. The plastome contains 129 genes, consisting of 84 protein-coding genes, 37 tRNA genes, and eight rRNA genes. The overall G/C content in the plastome of B. baccata is 35.6%. Phylogenetic results show that B. baccata is the earliest diverging lineage of Euphorbioideae. Euphorbia helioscopia + E. esula, E. tirucalli + E. milii and B. baccata have a closer phylogenetic relationship than other taxa within Euphorbiaceae. The complete plastome sequence of B. baccata will provide a useful resource for the conservation genetics of this species as well as for phylogenetic studies in Euphorbiaceae.

MHC2SKpan: a novel kernel based approach for pan-specific MHC class II peptide binding prediction.

BACKGROUND: Computational methods for the prediction of Major Histocompatibility Complex (MHC) class II binding peptides play an important role in facilitating the understanding of immune recognition and the process of epitope discovery. To develop an effective computational method, we need to consider two important characteristics of the problem: (1) the length of binding peptides is highly flexible; and (2) MHC molecules are extremely polymorphic and for the vast majority of them there are no sufficient training data. METHODS: We develop a novel string kernel MHC2SK (MHC-II String Kernel) method to measure the similarities among peptides with variable lengths. By considering the distinct features of MHC-II peptide binding prediction problem, MHC2SK differs significantly from the recently developed kernel based method, GS (Generic String) kernel, in the way of computing similarities. Furthermore, we extend MHC2SK to MHC2SKpan for pan-specific MHC-II peptide binding prediction by leveraging the binding data of various MHC molecules. RESULTS: MHC2SK outperformed GS in allele specific prediction using a benchmark dataset, which demonstrates the effectiveness of MHC2SK. Furthermore, we evaluated the performance of MHC2SKpan using various benckmark data sets from several different perspectives: Leave-one-allele-out (LOO), 5-fold cross validation as well as independent data testing. MHC2SKpan has achieved comparable performance with NetMHCIIpan-2.0 and outperformed NetMHCIIpan-1.0, TEPITOPEpan and MultiRTA, being statistically significant. MHC2SKpan can be freely accessed at http://datamining-iip.fudan.edu.cn/service/MHC2SKpan/index.html.

Molecularly imprinted matrix solid-phase dispersion for extraction of chloramphenicol in fish tissues coupled with high-performance liquid chromatography determination.

The synthesis and evaluation of a molecularly imprinted polymer (MIP) as a selective matrix solid-phase dispersion (MSPD) sorbent, coupled with high-performance liquid chromatography for the efficient determination of chloramphenicol (CAP) in fish tissues are studied. The polymer was prepared using CAP as the template molecule, vinylpyridine as the functional monomer and ethylene glycol dimethacrylate as the cross-linking monomer, and sodium dodecyl sulfate as the surfactant in the presence of water as a solvent by miniemulsion polymerization. The CAP-imprinted polymers and nonimprinted polymers (NIPs) were characterized by Fourier transform IR spectroscopy, scanning electron microscopy, and static adsorption experiments. The CAP-imprinted material prepared showed high adsorption capacity, significant selectivity, and good site accessibility. The maximum static adsorption capacity of the CAP-imprinted and the NIP material for CAP was 78.4 and 59.9 mg g(-1), respectively. The relative selectivity factors of this CAP-imprinted material were larger than 1.9. Several parameters influencing the MSPD process were optimized. Finally, the CAP-imprinted polymers were used as the sorbent in MSPD to determine CAP in three kinds of fishes and resulted in satisfactory recovery in the range 89.8-101.43%. CAP-imprinted polymer as a sorbent in MSPD is better than C18 and attapulgite in terms of both recovery and percent relative standard deviation. The baseline noise was measured from a chromatogram of a blank fish sample which was treated after the MSPD procedure using CAP-imprinted polymer as a sorbent. Signal values of 3 times the noise (signal-to-noise ratio of 3) and 10 times the noise (signal-to-noise ratio of 10) were used to calculate the limit of detection and the limit of quantitation of the calibration curve. The limit of detection for CAP was 1.2 ng g(-1) and the limit of quantitation was 3.9 ng g(-1).

Analysis of sulfamerazine in pond water and several fishes by high-performance liquid chromatography using molecularly imprinted solid-phase extraction.

The synthesis and evaluation of a molecularly imprinted polymer (MIP) used as a selective solid-phase extraction sorbent and coupled to high-performance liquid chromatography (HPLC) for the efficient determination of sulfamerazine (SMR) in pond water and three fishes are reported. The polymer was prepared using SMR as the template molecule, methacrylic acid as the functional monomer and ethylene glycol dimethacrylate as the crosslinking monomer in the presence of tetrahydrofuran as the solvent. The SMR-imprinted polymers and nonimprinted polymers were characterized by FT-IR and static adsorption experiments. The prepared SMR-imprinted material showed a high adsorption capacity, significant selectivity and good site accessibility. The maximum static adsorption capacities of the SMR-imprinted and nonimprinted materials for SMR were 108.8 and 79.6 mg g(-1), respectively. The relative selectivity factor of this SMR-imprinted material was 1.6. Several parameters influencing the solid-phase extraction process were optimized. Finally, the SMR-imprinted polymers were used as the sorbent in solid-phase extraction to determine SMR in pond water and three fishes with satisfactory recovery. The average recoveries of the MIP-SPE method were 94.0% in ultrapure water and 95.8% in pond water. Relative standard deviations ranging from 0.3% to 5.2% in MIP were acquired. The results for the SMR concentrations in crucian, carp and wuchang fish were 66.0, 127.1 and 51.5 ng g(-1), respectively. The RSDs (n = 5) were 3.51%, 0.53% and 5.08%, respectively. The limit of detection (LOD) for SMR was 1 ng g(-1) and the limit of quantitation (LOQ) was 3.5 ng g(-1).

Analysis of free amino acids in islets of Langerhans by high-performance liquid chromatography using pre-column derivatization with 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole.

A simple high-performance liquid chromatographic method with pre-column derivatization and fluorescence detection was developed and used for the analysis of free amino acids in islets of Langerhans; 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole (NBD-Cl) served as pre-column derivatization reagent. Islets of Langerhans were separated from the pancreas of normal and obese rats, treated with pre-cooling methanol-water (80:20, v/v), and ultrasonicated to fragmentize the islets and effect deproteination. Several parameters influencing the derivatization reaction and chromatographic separation were optimized. Amino acid derivatives obtained under optimal conditions were separated on a C18 column with acetonitrile-acetate buffer as mobile phase and detected at 470 nm/540 nm (Ex/Em). Matrix effects were investigated and good linearities with correlation coefficients better than 0.9972 were obtained over a wide range of 0.42-42.11 microM for most of the amino acids. The detection limits (S/N = 3) were within the range of 6.1-51 nM. The precision of the method and recoveries were in the ranges of 1.43-10.76% (RSD%) and 85.07-108.82%, respectively. The analytical results showed that the serine content was markedly higher in normal rats than in obese rats, whereas methionine was of relatively lower content in both normal and obese rats.

Determination of tetrandrine and fangchinoline in plasma samples using hollow fiber liquid-phase microextraction combined with high-performance liquid chromatography.

Tetrandrine (TET) and fangchinoline (FAN) are basic and highly hydrophobic drugs with logP>5.7. In this work, a simple, inexpensive and efficient liquid-phase microextraction (LPME) technology combined with high-performance liquid chromatography (HPLC) was developed for the simultaneous analysis of tetrandrine and fangchinoline in plasma samples. Tetrahydropalmatine was used as internal standard. Several parameters influencing the efficiency of LPME were investigated and optimized including organic solvent, stirring rate, extraction time, salt concentration, organic modifier and pH. Under the optimal conditions, extraction recoveries from plasma samples were 46% for tetrandrine and 50% for fangchinoline, corresponding to the drugs enriched by a factor of 23 and 25 by LPME, respectively. Excellent sample clean-up was observed and good linearities with correlation coefficients (r) of 0.9979 (FAN) and 0.9995 (TET) were obtained in the range of 15-1000 ngmL(-1). The limits of detection (LOD, S/N=3) were 3.0 ngmL(-1) for FAN and 2.0 ngmL(-1) for TET.