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Protein Structure Prediction:Challenges,Advances,and the Shift of Research Paradigms

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Genomics, Proteomics & Bioinformatics 2023年第5期21卷 913-925页

作者： Bin Huang Lupeng Kong Chao Wang Fusong Ju Qi Zhang Jianwei Zhu Tiansu Gong Haicang Zhang Chungong Yu wei-mou zheng Dongbo Bu Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Changping Laboratory Beijing 102206China Microsoft Research AI4Science Beijing 100080China Huawei Noah’s Ark Lab Wuhan 430206China Zhongke Big Data Academy Zhengzhou 450046China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China

Protein structure prediction is an interdisciplinary research topic that has attracted researchers from multiple fields,including biochemistry,medicine,physics,mathematics,and computer *** researchers adopt various research paradigms to attack the same structure prediction problem:biochemists and physicists attempt to reveal the principles governing protein folding;mathematicians,especially statisticians,usually start from assuming a probability distribution of protein structures given a target sequence and then find the most likely structure,while computer scientists formulate protein structure prediction as an optimization problem-finding the structural conformation with the lowest energy or minimizing the difference between predicted structure and native *** research paradigms fall into the two statistical modeling cultures proposed by Leo Breiman,namely,data modeling and algorithmic ***,we have also witnessed the great success of deep learning in protein structure *** this review,we present a survey of the efforts for protein structure *** compare the research paradigms adopted by researchers from different fields,with an emphasis on the shift of research paradigms in the era of deep *** short,the algorithmic modeling techniques,especially deep neural networks,have considerably improved the accuracy of protein structure prediction;however,theories interpreting the neural networks and knowledge on protein folding are still highly desired.

关键词： Protein folding Protein structure prediction Deep learning Transformer Language model

Research progress in tumor angiogenesis and drug resistance in breast cancer

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Cancer Biology & Medicine 2024年第7期21卷 571-585页

作者： Jiancheng mou Chenhong Li Qinghui zheng Xuli Meng Hongchao Tang The Second Clinical Medical College Zhejiang Chinese Medical UniversityHangzhou 310053China Department of Breast Surgery General SurgeryCancer CenterZhejiang Provincial People's Hospital(Affiliated People's Hospital)Hangzhou Medical CollegeHangzhou 310053China Key Laboratory for Diagnosis and Treatment of Upper Limb Edema and Stasis of Breast Cancer Hangzhou310053China

Angiogenesis is considered a hallmark pathophysiological process in tumor development. Aberrant vasculature resulting from tumor angiogenesis plays a critical role in the development of resistance to breast cancer treatments, via exacerbation of tumor hypoxia, decreased effective drug concentrations within tumors, and immune-related mechanisms. Antiangiogenic therapy can counteract these breast cancer resistance factors by promoting tumor vascular normalization. The combination of antiangiogenic therapy with chemotherapy, targeted therapy, or immunotherapy has emerged as a promising approach for overcoming drug resistance in breast cancer. This review examines the mechanisms associated with angiogenesis and the interactions among tumor angiogenesis, the hypoxic tumor microenvironment, drug distribution, and immune mechanisms in breast cancer. Furthermore, this review provides a comprehensive summary of specific antiangiogenic drugs, and relevant studies assessing the reversal of drug resistance in breast cancer. The potential mechanisms underlying these interventions are discussed, and prospects for the clinical application of antiangiogenic therapy to overcome breast cancer treatment resistance are highlighted.

关键词： Angiogenesis breast cancer chemotherapy drug resistance vascular normalization immunologic therapy tumor microenvironment(TME)

Synthesis of uniform two-dimensional MoS_(2) films via thermal evaporation

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Nano Research 2024年第4期17卷 3217-3223页

作者： Xue-wei Lu Zhewei Li Chen-Kai Yang weijia mou Liying Jiao Key Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education Department of ChemistryTsinghua UniversityBeijing 100084China

Two-dimensional(2D)molybdenum disulfide(MoS_(2))holds great potential for various applications such as electronic devices,catalysis,lubrication,anti-corrosion and so *** evaporation is a versatile thin film deposition technique,however,the conventional thermal evaporation techniques face challenges in producing uniform thin films of MoS_(2) due to its high melting temperature of 1375℃.As a result,only thick and rough MoS_(2) films can be obtained using these *** address this issue,we have designed a vacuum thermal evaporation system specifically for large-scale preparation of MoS_(2) thin *** using K2MoS4 as the precursor,we achieved reliable deposition of uniform polycrystalline MoS_(2) thin films with a size of 50 mm×50 mm and controllable thickness ranging from 0.8 to 2.4 *** approach also allows for patterned deposition of MoS_(2) using shadow masks and sequential deposition of MoS_(2) and tungsten disulfide(WS_(2)),similar to conventional thermal evaporation ***,we have demonstrated the potential applications of the obtained MoS_(2) thin films in field effect transistors(FETs),memristors and electrocatalysts for hydrogen evolution reaction(HER).

关键词： thermal evaporation molybdenum disulfide two-dimensional memristors hydrogen evolution reaction

On-surface synthesis and characterization of polyynic carbon chains

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National Science Review 2024年第3期11卷 192-199页

作者： Wenze Gao wei zheng Luye Sun Faming Kang zheng Zhou wei Xu Interdisciplinary Materials Research Center School of Materials Science and Engineering Tongji University

Carbyne, an elusive sp-hybridized linear carbon allotrope, has fascinated chemists and physicists for decades. Due to its high chemical reactivity and extreme instability, carbyne was much less explored in contrast to the sp2-hybridized carbon allotropes such as graphene. Herein, we report the on-surface synthesis of polyynic carbon chains by demetallization of organometallic polyynes on the Au（111） surface;the longest one observed consists of ～60 alkyne units（120 carbon atoms）. The polyynic structure of carbon chains with alternating triple and single bonds was unambiguously revealed by bond-resolved atomic force microscopy. Moreover, an atomically precise polyyne, C14, was successfully produced via tip-induced dehalogenation and ring-opening of the decachloroanthracene molecule(C14Cl10) on a bilayer NaCl/Au（111） surface at 4.7 K, and a band gap of 5.8 eV was measured by scanning tunnelling spectroscopy,in a good agreement with the theoretical HOMO–LUMO gap（5.48 eV）.

关键词： polyyne scanning probe microscopy carbon allotrope on-surface synthesis organometallic polyyne

Accurately tracking hypersonic gliding vehicles via an LEO mega-constellation in relay tracking mode

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Journal of Systems Engineering and Electronics 2024年第1期35卷 211-221页

作者： LI Zhao WANG Yidi zheng wei College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China

In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based *** benefited by the developing megaconstellations in low-Earth orbit,this paper proposes a relay tracking mode to track HGVs to overcome the above *** whole tracking mission is composed of several tracking intervals with the same *** each tracking interval,several appropriate satellites are dispatched to track the *** that are planned to take part in the tracking mission are selected by a new derived observability *** tracking performances of the proposed tracking mode and the other two traditional tracking modes,including the stare and track-rate modes,are compared by *** results show that the relay tracking mode can track the whole trajectory of a HGV,while the stare mode can only provide a very short tracking ***,the relay tracking mode achieve higher tracking accuracy with fewer attitude controls than the track-rate mode.

关键词： target tracking mega-constellation hypersonic gliding vehicle(HGV) sensor selection observability analysis

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

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Defence Technology（防务技术） 2024年第2期32卷 271-284页

作者： Yiwen Zhang wei zheng Zongqiang Liu Qian Xuesen Laboratory of Space Technology China Academy of Space TechnologyBeijing 100094China China Academy of Aerospace Science and Innovation Beijing 100176China State Key Laboratory of Space-Ground Integrated Information Technology Beijing Institute of Satellite Information EngineeringBeijing 100194China

Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater *** present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically ***,GNSS-R satellite constellations that meet the global altimetry needs to be ***,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric ***,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is ***,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is ***,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

关键词： GNSS-R satellite constellations Sea surface altimetric precision Underwater navigation Multilayer feedforward neural network

High-Order Decoupled and Bound Preserving Local Discontinuous Galerkin Methods for a Class of Chemotaxis Models

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Communications on Applied Mathematics and Computation 2024年第1期6卷 372-398页

作者： wei zheng Yan Xu School of Mathematical Sciences University of Science and Technology of ChinaHefei230026AnhuiChina

In this paper,we explore bound preserving and high-order accurate local discontinuous Galerkin(LDG)schemes to solve a class of chemotaxis models,including the classical Keller-Segel(KS)model and two other density-dependent *** use the convex splitting method,the variant energy quadratization method,and the scalar auxiliary variable method coupled with the LDG method to construct first-order temporal accurate schemes based on the gradient flow structure of the *** semi-implicit schemes are decoupled,energy stable,and can be extended to high accuracy schemes using the semi-implicit spectral deferred correction *** bound preserving DG discretizations are only worked on explicit time integration methods and are difficult to get high-order *** overcome these difficulties,we use the Lagrange multipliers to enforce the implicit or semi-implicit LDG schemes to satisfy the bound constraints at each time *** bound preserving limiter results in the Karush-Kuhn-Tucker condition,which can be solved by an efficient active set semi-smooth Newton *** numerical experiments illustrate the high-order accuracy and the effect of bound preserving.

关键词： Chemotaxis models Local discontinuous Galerkin(LDG)scheme Convex splitting method Variant energy quadratization method Scalar auxiliary variable method Spectral deferred correction method

A Transformer-Based Ensemble Framework for the Prediction of Protein-Protein Interaction Sites

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Research 2024年第2期2023卷 703-718页

作者： Minjie mou Ziqi Pan Zhimeng Zhou Lingyan zheng Hanyu Zhang Shuiyang Shi Fengcheng Li Xiuna Sun Feng Zhu College of Pharmaceutical Sciences The Second Affliated HospitalZhejiang University School of MedicineNational Key Laboratory of Advanced Drug Delivery and Release SystemsZhejiang UniversityHangzhou 310058China Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University Alibaba-Zhejiang University Joint Research Center of Future Digital HealthcareHangzhou 330110China

The identification of protein-protein interaction (PPI) sites is essential in the research of protein function and the discovery of new drugs. So far, a variety of computational tools based on machine learning have been developed to accelerate the identification of PPI sites. However, existing methods suffer from the low predictive accuracy or the limited scope of application. Specifically, some methods learned only global or local sequential features, leading to low predictive accuracy, while others achieved improved performance by extracting residue interactions from structures but were limited in their application scope for the serious dependence on precise structure information. There is an urgent need to develop a method that integrates comprehensive information to realize proteome-wide accurate profiling of PPI sites. Herein, a novel ensemble framework for PPI sites prediction, EnsemPPIS, was therefore proposed based on transformer and gated convolutional networks. EnsemPPIS can effectively capture not only global and local patterns but also residue interactions. Specifically, EnsemPPIS was unique in (a) extracting residue interactions from protein sequences with transformer and (b) further integrating global and local sequential features with the ensemble learning strategy. Compared with various existing methods, EnsemPPIS exhibited either superior performance or broader applicability on multiple PPI sites prediction tasks. Moreover, pattern analysis based on the interpretability of EnsemPPIS demonstrated that EnsemPPIS was fully capable of learning residue interactions within the local structure of PPI sites using only sequence information. The web server of EnsemPPIS is freely available at http://***/ensemppis.

关键词： residue extracting ensemble

Joint Sample Position Based Noise Filtering and Mean Shift Clustering for Imbalanced Classification Learning

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Tsinghua Science and Technology 2024年第1期29卷 216-231页

作者： Lilong Duan wei Xue Jun Huang Xiao zheng School of Computer Science and Technology Anhui University of TechnologyMaanshan 243032China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China

The problem of imbalanced data classification learning has received much *** classification algorithms are susceptible to data skew to favor majority samples and ignore minority *** weighted minority oversampling technique(MWMOTE)is an effective approach to solve this problem,however,it may suffer from the shortcomings of inadequate noise filtering and synthesizing the same samples as the original minority *** this end,we propose an improved MWMOTE method named joint sample position based noise filtering and mean shift clustering(SPMSC)to solve these ***,in order to effectively eliminate the effect of noisy samples,SPMsC uses a new noise filtering mechanism to determine whether a minority sample is noisy or not based on its position and distribution relative to the majority *** that MWMOTE may generate duplicate samples,we then employ the mean shift algorithm to cluster minority samples to reduce synthetic replicate ***,data cleaning is performed on the processed data to further eliminate class *** on extensive benchmark datasets demonstrate the effectiveness of SPMsC compared with other sampling methods.

关键词： imbalanced data classification oversampling noise filtering clustering