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学者姓名：李春华
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Abstract ：
We propose an improved transfer entropy approach called the dynamic version of the force constant fitted Gaussian network model based on molecular dynamics ensemble (dfcfGNMMD) to explore the allosteric mechanism of human mitochondrial phenylalanyl-tRNA synthetase (hmPheRS), one of the aminoacyl-tRNA synthetases that play a crucial role in translation of the genetic code. The dfcfGNMMD method can provide reliable estimates of the transfer entropy and give new insights into the role of the anticodon binding domain in driving the catalytic domain in aminoacylation activity and into the effects of tRNA binding and residue mutation on the enzyme activity, revealing the causal mechanism of the allosteric communication in hmPheRS. In addition, we incorporate the residue dynamic and co-evolutionary information to further investigate the key residues in hmPheRS allostery. This study sheds light on the mechanisms of hmPheRS allostery and can provide important information for related drug design.
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| GB/T 7714 | Han, Zhongjie , Wang, Xiaoli , Wu, Zhixiang et al. Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses [J]. | JOURNAL OF PHYSICAL CHEMISTRY LETTERS , 2023 , 14 (14) : 3452-3460 . |
| MLA | Han, Zhongjie et al. "Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses" . | JOURNAL OF PHYSICAL CHEMISTRY LETTERS 14 . 14 (2023) : 3452-3460 . |
| APA | Han, Zhongjie , Wang, Xiaoli , Wu, Zhixiang , Li, Chunhua . Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses . | JOURNAL OF PHYSICAL CHEMISTRY LETTERS , 2023 , 14 (14) , 3452-3460 . |
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Abstract ：
目的 构建CK2天然产物类抑制剂的定量构效关系(quantitative structure-activity relationship,QSAR)模型,揭示影响该类抑制剂活性的结构因素,为新型CK2抑制剂的开发提供理论基础和实验依据.方法 基于文献报道的115个多骨架CK2天然产物类抑制剂,采用遗传算法(genetic algorithm,GA)联合多元线性回归(multiple linear regression,MLR)方法,建立了基于优选的Dragon描述符的QSAR模型,以留一法交叉验证系数Q2LOO以及相关系数R2作为模型内部验证的评价指标;通过Q2ext和R2ext评估模型的外部预测能力.结果 最优2D-QSAR模型由8个描述符组成,基于训练集内部验证的统计学参数为Q2Loo=0.7914、R2=0.8220;基于测试集外部验证的统计学参数为Q2ext=0.7921、R2ext=0.7998,表明该模型具有较高的可靠性和预测能力.结论 影响CK2天然产物类抑制剂活性的分子描述符包括IVDE、CATS2D_08_DA、nArX、IC1、Chi_D/Dt、SdssC、F08[C-O]以及C-006.本研究可为新型CK2抗癌抑制剂的发现提供实验指导.
Keyword ：
定量结构-活性关系 定量结构-活性关系 天然产物类抑制剂 天然产物类抑制剂 遗传算法 遗传算法 多元线性回归 多元线性回归 蛋白激酶CK2 蛋白激酶CK2
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| GB/T 7714 | 张雪文 , 张娜 , 李春华 et al. 蛋白激酶CK2天然产物类抑制剂的定量构效关系研究 [J]. | 北京生物医学工程 , 2023 , 42 (1) : 81-87 . |
| MLA | 张雪文 et al. "蛋白激酶CK2天然产物类抑制剂的定量构效关系研究" . | 北京生物医学工程 42 . 1 (2023) : 81-87 . |
| APA | 张雪文 , 张娜 , 李春华 , 孙国辉 , 赵丽娇 , 钟儒刚 . 蛋白激酶CK2天然产物类抑制剂的定量构效关系研究 . | 北京生物医学工程 , 2023 , 42 (1) , 81-87 . |
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Protein-deoxyribonucleic acid (DNA) interactions are important in a variety of biological processes. Accurately predicting protein DNA binding affinity has been one of the most attractive and challenging issues in computational biology. However, the existing approaches still have much room for improvement. In this work, we propose an ensemble model for Protein-DNA Binding Affinity prediction (emPDBA), which combines six base models with one meta-model. The complexes are classified into four types based on the DNA structure (double-stranded or other forms) and the percentage of interface residues. For each type, emPDBA is trained with the sequence-based, structure-based and energy features from binding partners and complex structures. Through feature selection by the sequential forward selection method, it is found that there do exist considerable differences in the key factors contributing to intermolecular binding affinity. The complex classification is beneficial for the important feature extraction for binding affinity prediction. The performance comparison of our method with other peer ones on the independent testing dataset shows that emPDBA outperforms the state-of-the-art methods with the Pearson correlation coefficient of 0.53 and the mean absolute error of 1.11 kcal/mol. The comprehensive results demonstrate that our method has a good performance for protein-DNA binding affinity prediction.Availability and implementation: The source code is available at https://github.com/ChunhuaLiLab/emPDBA/.
Keyword ：
protein-DNA binding affinity protein-DNA binding affinity pairwise potential pairwise potential complex classification complex classification ensemble model ensemble model
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| GB/T 7714 | Yang, Shuang , Gong, Weikang , Zhou, Tong et al. emPDBA: protein-DNA binding affinity prediction by combining features from binding partners and interface learned with ensemble regression model [J]. | BRIEFINGS IN BIOINFORMATICS , 2023 , 24 (4) . |
| MLA | Yang, Shuang et al. "emPDBA: protein-DNA binding affinity prediction by combining features from binding partners and interface learned with ensemble regression model" . | BRIEFINGS IN BIOINFORMATICS 24 . 4 (2023) . |
| APA | Yang, Shuang , Gong, Weikang , Zhou, Tong , Sun, Xiaohan , Chen, Lei , Zhou, Wenxue et al. emPDBA: protein-DNA binding affinity prediction by combining features from binding partners and interface learned with ensemble regression model . | BRIEFINGS IN BIOINFORMATICS , 2023 , 24 (4) . |
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Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5'-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 mu s Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor.
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| GB/T 7714 | Wu, Zhixiang , Han, Zhongjie , Tao, Lianci et al. Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G-Protein-Coupled Receptor GPR52 [J]. | JOURNAL OF CHEMICAL INFORMATION AND MODELING , 2023 , 63 (18) : 5847-5862 . |
| MLA | Wu, Zhixiang et al. "Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G-Protein-Coupled Receptor GPR52" . | JOURNAL OF CHEMICAL INFORMATION AND MODELING 63 . 18 (2023) : 5847-5862 . |
| APA | Wu, Zhixiang , Han, Zhongjie , Tao, Lianci , Sun, Xiaohan , Su, Jingjie , Hu, Jianping et al. Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G-Protein-Coupled Receptor GPR52 . | JOURNAL OF CHEMICAL INFORMATION AND MODELING , 2023 , 63 (18) , 5847-5862 . |
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Abstract ：
Metal ion is an indispensable factor for the proper folding, structural stability and functioning of RNA molecules. However, it is very difficult for experimental methods to detect them in RNAs. With the increase of experimentally resolved RNA structures, it becomes possible to identify the metal ion-binding sites in RNA structures through in-silico methods. Here, we propose an approach called Metal3DRNA to identify the binding sites of the most common metal ions (Mg2+, Na+ and K+) in RNA structures by using a three-dimensional convolutional neural network model. The negative samples, screened out based on the analysis for binding surroundings of metal ions, are more like positive ones than the randomly selected ones, which are beneficial to a powerful predictor construction. The microenvironments of the spatial distributions of C, O, N and P atoms around a sample are extracted as features. Metal3DRNA shows a promising prediction power, generally surpassing the state-of-the-art methods FEATURE and MetalionRNA. Finally, utilizing the visualization method, we inspect the contributions of nucleotide atoms to the classification in several cases, which provides a visualization that helps to comprehend the model. The method will be helpful for RNA structure prediction and dynamics simulation study.
Keyword ：
deep learning method deep learning method RNA structure RNA structure visualization visualization metal ion-binding site metal ion-binding site microenvironment microenvironment
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| GB/T 7714 | Zhao, Yanpeng , Wang, Jingjing , Chang, Fubin et al. Identification of metal ion-binding sites in RNA structures using deep learning method [J]. | BRIEFINGS IN BIOINFORMATICS , 2023 , 24 (2) . |
| MLA | Zhao, Yanpeng et al. "Identification of metal ion-binding sites in RNA structures using deep learning method" . | BRIEFINGS IN BIOINFORMATICS 24 . 2 (2023) . |
| APA | Zhao, Yanpeng , Wang, Jingjing , Chang, Fubin , Gong, Weikang , Liu, Yang , Li, Chunhua . Identification of metal ion-binding sites in RNA structures using deep learning method . | BRIEFINGS IN BIOINFORMATICS , 2023 , 24 (2) . |
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Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma
Keyword ：
mRNA vaccine mRNA vaccine monkeypox monkeypox multi-epitope vaccine construct multi-epitope vaccine construct > > Reverse vaccinology Reverse vaccinology immunoinformatics immunoinformatics
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| GB/T 7714 | Aiman, Sara , Ali, Yasir , Malik, Abdul et al. Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus [J]. | JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS , 2023 . |
| MLA | Aiman, Sara et al. "Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus" . | JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2023) . |
| APA | Aiman, Sara , Ali, Yasir , Malik, Abdul , Alkholief, Musaed , Ahmad, Abbas , Akhtar, Suhail et al. Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus . | JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS , 2023 . |
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Abstract ：
ObjectiveOpioid receptor,a kind of G protein-coupled receptors(GPCRs),mainly mediates ananalgesic responseviaallosterically transducing the signal of endogenous ligand binding in the extracellulardomain to couple to effector proteins in the intracellular domain.delta opioid receptor(DOP)is associated withemotional control besides pain control,which makes it an attractive therapeutic target.However,its allostericmechanism and key residues responsible for structural stability and signal transmission are not completely clear.This paper aims to analyze the structural dynamics and allosteric effects of DOP.MethodsFirstly,therelationships between DOP structure dynamics and function were explored by means of residue fluctuations inslow motion mode and fast motion mode from the anisotropic network model(ANM).Then,perturbationresponse scanning(PRS)was used to identify key residues related to allosteric communication in DOP.ResultsThe DOP segments and functional sodium-binding sites can be well identified by the slowest motionmodes,and the key residues that play a crucial role in protein structural stability can be identified by the fastestmotion modes.Correlation analysis of residue motions reveals positive correlations between extracellular/intracellular transmembrane helices and loops,which promote the DOP structural stability and the binding ofDOP with ligands.Key residues with high sensitivity and high effectiveness in PRS analysis play an importantrole in the allosteric communication of DOP.ConclusionThis work sheds light on the allosteric communicationmechanism of delta opioid receptor and provides valuable information for drug design
Keyword ：
?opioid receptor(DOP) ?opioid receptor(DOP) anisotropic network model anisotropic network model allosteric mechanism allosteric mechanism dynamics dynamics perturbation-response scanning perturbation-response scanning
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| GB/T 7714 | Chen Lei , Gong Wei-Kang , Li Chun-Hua . Dynamics and Key Residues of?Opioid Receptor Investigated by AnisotropicNetwork Model br [J]. | PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS , 2022 , 49 (6) : 1146-1154 . |
| MLA | Chen Lei et al. "Dynamics and Key Residues of?Opioid Receptor Investigated by AnisotropicNetwork Model br" . | PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS 49 . 6 (2022) : 1146-1154 . |
| APA | Chen Lei , Gong Wei-Kang , Li Chun-Hua . Dynamics and Key Residues of?Opioid Receptor Investigated by AnisotropicNetwork Model br . | PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS , 2022 , 49 (6) , 1146-1154 . |
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The three-dimensional (3D) chromosomal structure plays an essential role in all DNA-templated processes, including gene transcription, DNA replication and other cellular processes. Although developing chromosome conformation capture (3C) methods, such as Hi-C, which can generate chromosomal contact data characterized genome-wide chromosomal structural properties, understanding 3D genomic nature-based on Hi-C data remains lacking. Here, we propose a persistent spectral simplicial complex (PerSpectSC) model to describe Hi-C data for the first time. Specifically, a filtration process is introduced to generate a series of nested simplicial complexes at different scales. For each of these simplicial complexes, its spectral information can be calculated from the corresponding Hodge Laplacian matrix. PerSpectSC model describes the persistence and variation of the spectral information of the nested simplicial complexes during the filtration process. Different from all previous models, our PerSpectSC-based features provide a quantitative global-scale characterization of chromosome structures and topology. Our descriptors can successfully classify cell types and also cellular differentiation stages for all the 24 types of chromosomes simultaneously. In particular, persistent minimum best characterizes cell types and Dim (1) persistent multiplicity best characterizes cellular differentiation. These results demonstrate the great potential of our PerSpectSC-based models in polymeric data analysis.
Keyword ：
machine learning machine learning Hi-C data Hi-C data Hodge Laplacian Hodge Laplacian persistent spectral simplicial complex persistent spectral simplicial complex chromosomal featurization chromosomal featurization
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| GB/T 7714 | Gong, Weikang , Wee, JunJie , Wu, Min-Chun et al. Persistent spectral simplicial complex-based machine learning for chromosomal structural analysis in cellular differentiation [J]. | BRIEFINGS IN BIOINFORMATICS , 2022 , 23 (4) . |
| MLA | Gong, Weikang et al. "Persistent spectral simplicial complex-based machine learning for chromosomal structural analysis in cellular differentiation" . | BRIEFINGS IN BIOINFORMATICS 23 . 4 (2022) . |
| APA | Gong, Weikang , Wee, JunJie , Wu, Min-Chun , Sun, Xiaohan , Li, Chunhua , Xia, Kelin . Persistent spectral simplicial complex-based machine learning for chromosomal structural analysis in cellular differentiation . | BRIEFINGS IN BIOINFORMATICS , 2022 , 23 (4) . |
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Abstract ：
Motivation: The identification of binding hotspots in protein-RNA interactions is crucial for understanding their potential recognition mechanisms and drug design. The experimental methods have many limitations, since they are usually time-consuming and labor-intensive. Thus, developing an effective and efficient theoretical method is urgently needed. Results: Here, we present SREPRHot, a method to predict hotspots, defined as the residues whose mutation to alanine generate a binding free energy change >= 2.0 kcal/mol, while others use a cutoff of 1.0 kcal/mol to obtain balanced datasets. To deal with the dataset imbalance, Synthetic Minority Over-sampling Technique (SMOTE) is utilized to generate minority samples to achieve a dataset balance. Additionally, besides conventional features, we use two types of new features, residue interface propensity previously developed by us, and topological features obtained using node-weighted networks, and propose an effective Random Grouping feature selection strategy combined with a two-step method to determine an optimal feature set. Finally, a stacking ensemble classifier is adopted to build our model. The results show SREPRHot achieves a good performance with SEN, MCC and AUC of 0.900, 0.557 and 0.829 on the independent testing dataset. The comparison study indicates SREPRHot shows a promising performance.
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| GB/T 7714 | Zhou, Tong , Rong, Jie , Liu, Yang et al. An ensemble approach to predict binding hotspots in protein-RNA interactions based on SMOTE data balancing and Random Grouping feature selection strategies [J]. | BIOINFORMATICS , 2022 , 38 (9) : 2452-2458 . |
| MLA | Zhou, Tong et al. "An ensemble approach to predict binding hotspots in protein-RNA interactions based on SMOTE data balancing and Random Grouping feature selection strategies" . | BIOINFORMATICS 38 . 9 (2022) : 2452-2458 . |
| APA | Zhou, Tong , Rong, Jie , Liu, Yang , Gong, Weikang , Li, Chunhua . An ensemble approach to predict binding hotspots in protein-RNA interactions based on SMOTE data balancing and Random Grouping feature selection strategies . | BIOINFORMATICS , 2022 , 38 (9) , 2452-2458 . |
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The human equilibrative nucleoside transporter 1 (hENT1) is an effective controller of adenosine signaling by regulating its extracellular and intracellular concentration, and has become a solid drug target of clinical used adenosine reuptake inhibitors (AdoRIs). Currently, the mechanisms of adenosine transport and inhibition for hENT1 remain unclear, which greatly limits the in-depth understanding of its inner workings as well as the development of novel inhibitors. In this work, the dynamic details of hENT1 underlie adenosine transport and the inhibition mechanism of the non-nucleoside AdoRIs dilazep both were investigated by comparative long-time unbiased molecular dynamics simulations. The calculation results show that the conformational transitions of hENT1 from the outward open to metastable occluded state are mainly driven by TM1, TM2, TM7 and TM9. One of the trimethoxyphenyl rings in dilazep serves as the adenosyl moiety of the endogenous adenosine substrate to competitively occupy the orthosteric site of hENT1. Due to extensive and various VDW interactions with N30, M33, M84, P308 and F334, the other trimethoxyphenyl ring is stuck in the opportunistic site near the extracellular side preventing the complete occlusion of thin gate simultaneously. Obviously, dilazep shows significant inhibitory activity by disrupting the local induce-fit action in substrate binding cavity and blocking the transport cycle of whole protein. This study not only reveals the nucleoside transport mechanism by hENT1 at atomic level, but also provides structural guidance for the subsequent design of novel non-nucleoside AdoRIs with enhanced pharmacologic properties.
Keyword ：
Nucleoside transport Nucleoside transport hENT1 hENT1 Inhibition mechanism Inhibition mechanism Adenosine Adenosine Dilazep Dilazep
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| GB/T 7714 | Wu, Zhixiang , Han, Zhongjie , Zhou, Wenxue et al. Insight into the nucleoside transport and inhibition of human ENT1 [J]. | CURRENT RESEARCH IN STRUCTURAL BIOLOGY , 2022 , 4 : 192-205 . |
| MLA | Wu, Zhixiang et al. "Insight into the nucleoside transport and inhibition of human ENT1" . | CURRENT RESEARCH IN STRUCTURAL BIOLOGY 4 (2022) : 192-205 . |
| APA | Wu, Zhixiang , Han, Zhongjie , Zhou, Wenxue , Sun, Xiaohan , Chen, Lei , Yang, Shuang et al. Insight into the nucleoside transport and inhibition of human ENT1 . | CURRENT RESEARCH IN STRUCTURAL BIOLOGY , 2022 , 4 , 192-205 . |
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