Article
Biology
Jixue Sun, Fei Liu, Longxiao Yuan, Ning-Ning Pang, Bing Zhu, Na Yang
Summary: This study elucidates the activation mechanism of DNMT1 using various sampling methods. The results show that the binding of H3Ub2 to the RFTS domain of DNMT1 leads to conformational changes, activating DNMT1.
SCIENCE CHINA-LIFE SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Yong Xiao Yang, Peng Li, Pan Wang, Bao Ting Zhu
Summary: The insulin receptor plays a crucial role in energy metabolism regulation and dysfunction can lead to diseases like diabetes. Molecular modeling has been used to study the dynamic structures of IR in different states and the mechanism of activation, providing insights into signaling pathways and drug design for diabetes treatment.
ACTA BIOCHIMICA ET BIOPHYSICA SINICA
(2021)
Article
Biochemistry & Molecular Biology
Peng Xie, Junjie Zhang, Baiyu Chen, Xinwei Li, Wenbo Zhang, Mengdan Zhu, Wei Li, Jianqi Li, Wei Fu
Summary: Opioid receptors are effective targets for treating severe pain. This study investigated the activation mechanisms of opioid receptors and identified key structural determinants using aminomethyl tetrahydronaphthalene compounds.
Article
Biophysics
Hannes Schihada, Maria Kowalski-Jahn, Ainoleena Turku, Gunnar Schulte
Summary: This study developed fluorescence-based biosensors that detect WNT-induced FZD conformational changes in living cells, revealing the selectivity of WNTs to their receptors and distinct ligand-induced receptor conformations.
BIOSENSORS & BIOELECTRONICS
(2021)
Article
Biology
Suhaila Rajab, Leah Bismin, Simone Schwarze, Alexandra Pinggera, Ingo H. Greger, Hannes Neuweiler
Summary: This study reveals the dynamics of closure of ligand-binding domains (LBDs) of the three major ionotropic glutamate receptor subtypes, showing pronounced sub-millisecond fluctuations in the apo state of LBDs from all three subtypes and uncovering a pathway of allosteric communication in LBD dynamics across the dimerization interface.
COMMUNICATIONS BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Ada Y. Chen, Bernard R. Brooks, Ana Damjanovic
Summary: In bacterial voltage-gated sodium channels, the passage of ions through the pore is controlled by a selectivity filter (SF) composed of four glutamate residues. This study proposes an alternative mechanism for selectivity, based on ion-triggered shifts in pKa values of SF glutamates. The mechanism suggests that selectivity is achieved through ion-triggered shifts in the protonation state, favoring more conductive states for Na+ ions and less conductive states for K+ ions.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Biochemistry & Molecular Biology
Zahra Musavizadeh, Alessandro Grottesi, Giulia Guarguaglini, Alessandro Paiardini
Summary: The study reveals the impact of phosphorylation on the stability of the A-loop and the effect of conformation disrupting inhibitors on the dynamics of Aurora-A. The presence of a phosphate moiety induces Aurora-A to sample two distinct energy minima, indicating a significant difference in conformational distributions compared to the unphosphorylated state.
Article
Chemistry, Multidisciplinary
Wei Peng, Shengheng Yan, Xuan Zhang, Langxing Liao, Jinyan Zhang, Sason Shaik, Binju Wang
Summary: Nature has employed intrinsic electric fields (IEFs) in electrostatic catalysis of enzymes, but how do IEFs target their functions in enzymes involving multiple reaction steps? In this study, molecular dynamics and quantum-mechanical/molecular-mechanical (QM/MM) simulations on tyrosine hydroxylase (TyrH) were performed to decipher the impact of IEFs on the catalytic cycle. The results show that IEFs in TyrH are optimized to promote the O-O bond heterolysis that generates the active species of the enzyme, Cpd I, but slow down the subsequent aromatic hydroxylation.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Multidisciplinary Sciences
Linlin Wang, Zhihui Jiang, Jiahe Zhang, Kuan Chen, Meng Zhang, Zilong Wang, Binju Wang, Min Ye, Xue Qiao
Summary: This article reports a saponin acetyltransferase, AmAT7-3, discovered from Astragalus membranaceus, which plays a key role in the acetylation of astragaloside IV. The authors studied the catalytic mechanism through crystal structures and computational analysis, and constructed a mutant library. The results expand the understanding of saponin acetyltransferases and provide efficient catalytic tools.
NATURE COMMUNICATIONS
(2023)
Article
Engineering, Chemical
G. De Luca, J. Luque Di Salvo, A. Cipollina, G. L. Luque, A. Fuoco, E. P. M. Leiva, G. Micale
Summary: The confinement effect on ion hydration in narrow pores is investigated in this study, and it is found that it can provide a membrane with high selectivity for Na+ compared to traditional ion exchange membranes. This selectivity is mainly based on thermodynamics rather than size exclusion mechanisms. However, Cl- is completely excluded within the range of investigated CNT diameters.
Article
Biochemical Research Methods
Wesley B. Asher, Peter Geggier, Michael D. Holsey, Grant T. Gilmore, Avik K. Pati, Jozsef Meszaros, Daniel S. Terry, Signe Mathiasen, Megan J. Kaliszewski, Mitchell D. McCauley, Alekhya Govindaraju, Zhou Zhou, Kaleeckal G. Harikumar, Khuloud Jaqaman, Laurence J. Miller, Adam W. Smith, Scott C. Blanchard, Jonathan A. Javitch
Summary: This study presents a generally applicable method for using single-molecule fluorescence resonance energy transfer (smFRET) to detect and track transmembrane proteins diffusing within the plasma membrane of mammalian cells. The in-cell smFRET approach reveals agonist-induced structural dynamics within individual metabotropic glutamate receptor dimers. Evidence for receptor monomers, density-dependent dimers, and constitutive dimers in representative class A, B, and C receptors were observed using these methods.
Article
Chemistry, Analytical
Helisa H. Wippel, Juan D. Chavez, Andrew D. Keller, James E. Bruce
Summary: The XL-MS technique provides insight into protein conformations and interactions within their cellular environment, while the iqPIR strategy allows for comparative interactome studies using isotope encoded chemical cross-linkers. Multiplexed iqPIR enables quantitative interactome analysis of up to six biological samples in a single LC-MS acquisition, revealing specific protein conformational and interaction changes in response to different inhibitors.
ANALYTICAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Chenyi Liao, Jacob M. Remington, Victor May, Jianing Li
Summary: Through the study of structural information and advanced simulation techniques, important features in the interactions between PACAP and VIP with different receptors were revealed, providing theoretical basis for the design of selective ligands.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Biology
Sabab Hasan Khan, Sean M. Braet, Stephen John Koehler, Elizabeth Elacqua, Ganesh Srinivasan Anand, C. Denise Okafor
Summary: This study investigates ligand-induced conformational changes in a reconstructed ancestral nuclear receptor and generates receptor variants with altered ligand specificities. Cellular and biophysical experiments, as well as atomistic molecular dynamics simulations, are used to characterize these conformational changes and understand their impact on ligand responses.
Article
Biochemistry & Molecular Biology
Gaspar Pandy-Szekeres, Luis P. Taracena Herrera, Jimmy Caroli, Ali A. Kermani, Yashraj Kulkarni, Gyorgy M. Keseru, David E. Gloriam
Summary: GproteinDb is a database that provides data and tools related to G proteins for analysis, visualization and experiment design. The major update includes the expansion of coupling data and structural templates, and the improvement of interactive analysis tools for coupling selectivity.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Wenyi Bian, Xueli Shen, Huang Tan, Xing Fan, Yunxia Liu, Haiping Lin, Youyong Li
Summary: The intrinsic coordinating effect of Fe single-atom catalysts in propane dehydrogenation was systematically studied using density functional theory (DFT) calculations. The Fe-N3P-C dual-coordinated site exhibited superior catalytic activity and selectivity at industrial temperatures due to its in-plane configuration that promotes C-H bond scission and offers an appropriate H diffusion rate, ensuring high propylene selectivity and catalyst regeneration.
CHINESE CHEMICAL LETTERS
(2023)
Article
Pharmacology & Pharmacy
Lingjie Bao, Zhe Wang, Zhenxing Wu, Hao Luo, Jiahui Yu, Yu Kang, Dongsheng Cao, Tingjun Hou
Summary: In this study, a model called AMGU was developed to predict the inhibitory activities of small molecules against various kinases. The AMGU model outperformed other models on both internal and external test sets, demonstrating its enhanced generalizability. Additionally, a method called edges masking was devised to explain the predictive mechanisms, and a web server called KIP was developed for predicting the polypharmacology effects of small molecules on the kinome.
ACTA PHARMACEUTICA SINICA B
(2023)
Article
Biochemical Research Methods
Lei Wang, Shao-Hua Shi, Hui Li, Xiang-Xiang Zeng, Su-You Liu, Zhao-Qian Liu, Ya-Feng Deng, Ai-Ping Lu, Ting-Jun Hou, Dong-Sheng Cao
Summary: Machine learning-based scoring functions (MLSFs) have gained popularity due to their potential superior screening performance compared to classical scoring functions. However, little is known about the information of negative data used in constructing MLSFs, and existing databases often contain biased putative inactive molecules. In this study, we propose an easy-to-use method called AMLSF that combines active learning and MLSF to improve the quality of inactive sets and reduce false positive rate. Our results demonstrate that AMLSF outperforms the control models in terms of identifying active molecules and reducing false positives.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Kai-Yue Ji, Chong Liu, Zhao-Qian Liu, Ya-Feng Deng, Ting-Jun Hou, Dong-Sheng Cao
Summary: Identification of potential targets for known bioactive compounds and novel synthetic analogs is crucial. In silico target fishing has emerged as an alternative strategy due to the challenges of wet-lab experiments and the rapid growth of bioactivity data. This study evaluated nine popular ligand-based target fishing methods and found that SwissTargetPrediction produced the most reliable predictions with a larger target pool. Additionally, the high-recall similarity ensemble approach showed promise in identifying real targets for more compounds. The study also proposed a novel ensemble method based on consensus voting for improved prediction performance.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Dong Wang, Zhenxing Wu, Chao Shen, Lingjie Bao, Hao Luo, Zhe Wang, Hucheng Yao, De-Xin Kong, Cheng Luo, Tingjun Hou
Summary: This study explores the utility and effectiveness of evidential uncertainty in compound screening. The results demonstrate that evidential uncertainties help reduce false positives and improve experimental validation rates. The study highlights the importance of understanding the uncertainty in model predictions.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Lingling Wang, Lei Xu, Zhe Wang, Tingjun Hou, Haiping Hao, Huiyong Sun
Summary: Understanding the mechanism of drug selectivity is crucial for designing drugs with high specificity. Designing drugs targeting cyclin-dependent kinases (CDKs) is challenging due to their conserved binding pockets. By analyzing a representative CDK12 inhibitor from both thermal dynamics and kinetics perspectives, we propose to use kinetic residue energy analysis (KREA) and community network analysis (CNA) to reveal the cooperation between individual residues and protein motifs in the drug-target recognition process. The general mechanism of drug selectivity in CDKs is determined by the difference in structural cooperation between the ligand and protein motifs, resulting in different energetic contributions from key residues. These proposed mechanisms may be prevalent in drug selectivity and could aid in the design of strategies to overcome or attenuate selectivity issues.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Shukai Gu, Chao Shen, Jiahui Yu, Hong Zhao, Huanxiang Liu, Liwei Liu, Rong Sheng, Lei Xu, Zhe Wang, Tingjun Hou, Yu Kang
Summary: This study evaluated the impact of structural dynamic information on binding affinity prediction and found that the optimized molecular dynamics protocol improved the predictive performance for the TAF1-BD2 target with high structural flexibility, but not for the less flexible JAK1 and DDR1 targets.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Chemistry, Medicinal
Ziyi Yang, Shaohua Shi, Li Fu, Aiping Lu, Tingjun Hou, Dongsheng Cao
Summary: Matched molecular pair analysis (MMPA) is a tool that extracts medicinal chemistry knowledge from experimental data by identifying relationships between changes in activities or properties and specific structural changes. It has been recently applied in multi-objective optimization and de novo drug design. This Perspective discusses the concept, techniques, and case studies of MMPA, providing an overview of its current development and highlighting successes and opportunities for further advances.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Jie Feng, Zhihao Dong, Yujin Ji, Youyong Li
Summary: By introducing a dynamic embedding layer, we propose a universal graph neural network called CrystalGNN, which can automatically update atomic inputs during the training process. We train a model based on this framework to accurately predict the formation energies of 10,500 IrO2 configurations and discover 8 unreported metastable phases. Among them, C2/m-IrO2 and P62-IrO2 are identified as excellent electrocatalysts that can reach the theoretical OER overpotential limit at their most stable surfaces. Our self-learning-input CrystalGNN framework exhibits reliable accuracy, generalization, and transferring ability and successfully accelerates the bottom-up catalyst design to boost the OER activity.
Article
Chemistry, Physical
Zhihao Dong, Jie Feng, Yujin Ji, Youyong Li
Summary: We propose a self-learning-input graph neural network framework, called SLI-GNN, to predict the properties of both crystals and molecules. By using a dynamic embedding layer and the Infomax mechanism, the input features are dynamically updated and the average mutual information between local and global features is maximized. Experimental results show that our SLI-GNN achieves comparable performance to other GNNs in material property prediction, indicating promising potential for accelerating new material discovery.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
Article
Chemistry, Multidisciplinary
Chao Shen, Xujun Zhang, Chang-Yu Hsieh, Yafeng Deng, Dong Wang, Lei Xu, Jian Wu, Dan Li, Yu Kang, Tingjun Hou, Peichen Pan
Summary: Applying machine learning algorithms to protein-ligand scoring functions has gained attention due to its high predictive accuracy and affordable computational cost. However, most machine learning-based scoring functions are limited to specific tasks, making it challenging to develop a scoring function with balanced performance across critical tasks. In this study, we propose a novel parameterization strategy that introduces an adjustable binding affinity term into the training of a mixture density network. The resulting scoring framework achieves superior docking and screening power, as well as remarkable improvements in scoring and ranking performance. Our study highlights the potential utility of this innovative parameterization strategy and scoring framework in future structure-based drug design.
Article
Chemistry, Physical
Wenzhen Xu, Yunpeng Shu, Mengmeng Xu, Juan Xie, Youyong Li, Huilong Dong
Summary: In this study, the effect of strain engineering on the electrocatalysis of CO reduction reaction (CORR) by 2D transition metal embedded polyphthalocyanines (MPPcs) was computationally explored. It was found that only CrPPc under biaxial strain had the potential to significantly enhance the catalytic performance. The free energy diagrams showed that the optimal reaction pathway and rate-determining step were changed under specific biaxial strains, and applying 5% compressive strain on CrPPc resulted in unexpected electrocatalytic activity.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Biochemistry & Molecular Biology
Wentao Qi, Dong Zhai, Danna Song, Chengcheng Liu, Junxia Yang, Lei Sun, Youyong Li, Xingwei Li, Weiqiao Deng
Summary: Considering the global challenge of low-cost and efficient anti-COVID-19 drug production, we developed a low-cost and efficient synthesis route for favipiravir using improved retrosynthesis software. This route involves only 3 steps under safe and near-ambient air conditions, achieving a yield of 32% and cost of $1.54 per g. We also applied the same strategy to optimize the synthesis of sabizabulin. These synthetic routes are expected to contribute to the prevention and treatment of COVID-19.
RSC MEDICINAL CHEMISTRY
(2023)
Article
Chemistry, Medicinal
Sutong Xiang, Zhe Wang, Rongfan Tang, Lingling Wang, Qinghua Wang, Yang Yu, Qirui Deng, Tingjun Hou, Haiping Hao, Huiyong Sun
Summary: This study investigates the binding and dissociation process of nuclear receptor drugs and reveals the main dissociation pathways of FXR ligands using computational methods. Furthermore, key residues involved in the dissociation pathways are identified through kinetic residue energy analysis. The results suggest that RAMD simulations are suitable for large-scale exploration of binding pathways in ligands with obscure binding tunnels to the target.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Multidisciplinary
Piao Wang, Changle Zhang, Jiabao Ding, Yujin Ji, Youyong Li, Weifeng Zhang
Summary: Combining iridium dopants with highly active iridium atoms, Ir-SMO exhibits excellent performance for water oxidation in acidic conditions, making it an efficient and stable electrocatalyst.