Some charmonium-like resonances such as X（3872） can be interpreted as possible D （＊） （＊） molecular states.Within the quark model,we study the structure of such molecular states and the similar B （＊） （＊...Some charmonium-like resonances such as X（3872） can be interpreted as possible D （＊） （＊） molecular states.Within the quark model,we study the structure of such molecular states and the similar B （＊） （＊） molecular states by taking into account the light meson exchange （π,η,ρ,ω and σ） between two light quarks from different mesons.展开更多
In the framework of the one-boson-exchange model, we have performed an extensive study of the possible B＊B, B B＊ D＇D, D＇D＊ molecular states with various quantum numbers after considering the S-wave and D-wave m...In the framework of the one-boson-exchange model, we have performed an extensive study of the possible B＊B, B B＊ D＇D, D＇D＊ molecular states with various quantum numbers after considering the S-wave and D-wave mixing. We also discuss the possible experimental research of these interesting states.展开更多
Molecular kinetics underlies all biological phenomena and, like many other biological processes, may best be understood in terms of networks. These networks, called Markov state models （MSMs）, are typically built fr...Molecular kinetics underlies all biological phenomena and, like many other biological processes, may best be understood in terms of networks. These networks, called Markov state models （MSMs）, are typically built from physical simulations. Thus, they are capable of quantitative prediction of experiments and can also provide an intuition for complex couformational changes. Their primary application has been to protein folding; however, these technologies and the insights they yield are transferable. For example, MSMs have already proved useful in understanding human diseases, such as protein misfolding and aggregation in Alzheimer＇s disease.展开更多
The recently observed X（3872） resonance, which is difficult to assign a conventional cc charmonium state in the quark model, may be interpreted as a molecular state. Such a molecular state is a hidden flavor four qu...The recently observed X（3872） resonance, which is difficult to assign a conventional cc charmonium state in the quark model, may be interpreted as a molecular state. Such a molecular state is a hidden flavor four quark state because of its charmonium-like quantum numbers. The s-channel one gluon exchange is an interaction which only acts in the hidden flavor multi-quark system. In this paper, we will study the X（3872） and other similiar hidden flavor molecular states in a quark model by taking into account the s-channel one gluon exchange interaction.展开更多
An understanding of protein folding/unfolding processes has important implications for all biological processes, in- eluding protein degradation, protein translocation, aging, and diseases. All-atom molecular dynamics...An understanding of protein folding/unfolding processes has important implications for all biological processes, in- eluding protein degradation, protein translocation, aging, and diseases. All-atom molecular dynamics （MD） simulations are uniquely suitable for it because of their atomic level resolution and accuracy. However, limited by computational ca- pabilities, nowadays even for small and fast-folding proteins, all-atom MD simulations of protein folding still presents a great challenge. An alternative way is to study unfolding process using MD simulations at high temperature. High temper- ature provides more energy to overcome energetic barriers to unfolding, and information obtained from studying unfolding can shed light on the mechanism of folding. In the present study, a 1000-ns MD simulation at high temperature （500 K） was performed to investigate the unfolding process of a small protein, chicken villin headpiece （HP-35）. To infer the folding mechanism, a Markov state model was also built from our simulation, which maps out six macrostates during the folding/unfolding process as well as critical transitions between them, revealing the folding mechanism unambiguously.展开更多
Molecular dynamics （MD） simulation has become a powerful tool to investigate the structure- function relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timesc...Molecular dynamics （MD） simulation has become a powerful tool to investigate the structure- function relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timescales. MD simulations often produce massive datasets con- taining millions of snapshots describing proteins in motion. Therefore, clustering algorithms have been in high demand to be developed and applied to classify these MD snapshots and gain biological insights. There mainly exist two categories of clustering algorithms that aim to group protein conformations into clusters based on the similarity of their shape （geometric clustering） and kinetics （kinetic clustering）. In this paper, we review a series of frequently used clustering algorithms applied in MD simulations, including divisive algorithms, ag- glomerative algorithms （single-linkage, complete-linkage, average-linkage, centroid-linkage and ward-linkage）, center-based algorithms （K-Means, K-Medoids, K-Centers, and APM）, density-based algorithms （neighbor-based, DBSCAN, density-peaks, and Robust-DB）, and spectral-based algorithms （PCCA and PCCA＋）. In particular, differences between geomet- ric and kinetic clustering metrics will be discussed along with the performances of diflhrent clustering algorithms. We note that there does not exist a one-size-fits-all algorithm in the classification of MD datasets. For a specific application, the right choice of clustering algo- rithm should be based on the purpose of clustering, and the intrinsic properties of the MD conformational ensembles. Therefore, a main focus of our review is to describe the merits and limitations of each clustering algorithm. We expect that this review would be helpful to guide researchers to choose appropriate clustering algorithms for their own MD datasets.展开更多
A novel variational approach is proposed to calculate the ground-state （GS） properties of the two-site Holstein model. By the linear superposition of two coherent states, which simulate the behaviour of the weak and...A novel variational approach is proposed to calculate the ground-state （GS） properties of the two-site Holstein model. By the linear superposition of two coherent states, which simulate the behaviour of the weak and strong coupling limits, we can obtain very accurate GS energy for arbitrary electron-phonon coupling constant. Other GS properties are also discussed. Moreover, the present concise approach is hopefully generalized to many other Holstein models.展开更多
文摘Some charmonium-like resonances such as X（3872） can be interpreted as possible D （＊） （＊） molecular states.Within the quark model,we study the structure of such molecular states and the similar B （＊） （＊） molecular states by taking into account the light meson exchange （π,η,ρ,ω and σ） between two light quarks from different mesons.
基金Supported by National Natural Science Foundation of China (11175073, 11021092, 11035006, 11047606, 10805048)Ministry of Science and Technology of China (2009CB825200)+1 种基金Ministry of Education of China (FANEDD 200924, DPFIHE 20090211120029, NCET-10-0442)Fundamental Research Funds for the Central Universities
文摘In the framework of the one-boson-exchange model, we have performed an extensive study of the possible B＊B, B B＊ D＇D, D＇D＊ molecular states with various quantum numbers after considering the S-wave and D-wave mixing. We also discuss the possible experimental research of these interesting states.
文摘Molecular kinetics underlies all biological phenomena and, like many other biological processes, may best be understood in terms of networks. These networks, called Markov state models （MSMs）, are typically built from physical simulations. Thus, they are capable of quantitative prediction of experiments and can also provide an intuition for complex couformational changes. Their primary application has been to protein folding; however, these technologies and the insights they yield are transferable. For example, MSMs have already proved useful in understanding human diseases, such as protein misfolding and aggregation in Alzheimer＇s disease.
文摘The recently observed X（3872） resonance, which is difficult to assign a conventional cc charmonium state in the quark model, may be interpreted as a molecular state. Such a molecular state is a hidden flavor four quark state because of its charmonium-like quantum numbers. The s-channel one gluon exchange is an interaction which only acts in the hidden flavor multi-quark system. In this paper, we will study the X（3872） and other similiar hidden flavor molecular states in a quark model by taking into account the s-channel one gluon exchange interaction.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11175068 and 11474117)the Self-determined Research Funds of CCNU from the Colleges Basic Research and Operation of MOE,China(Grant No.230-20205170054)
文摘An understanding of protein folding/unfolding processes has important implications for all biological processes, in- eluding protein degradation, protein translocation, aging, and diseases. All-atom molecular dynamics （MD） simulations are uniquely suitable for it because of their atomic level resolution and accuracy. However, limited by computational ca- pabilities, nowadays even for small and fast-folding proteins, all-atom MD simulations of protein folding still presents a great challenge. An alternative way is to study unfolding process using MD simulations at high temperature. High temper- ature provides more energy to overcome energetic barriers to unfolding, and information obtained from studying unfolding can shed light on the mechanism of folding. In the present study, a 1000-ns MD simulation at high temperature （500 K） was performed to investigate the unfolding process of a small protein, chicken villin headpiece （HP-35）. To infer the folding mechanism, a Markov state model was also built from our simulation, which maps out six macrostates during the folding/unfolding process as well as critical transitions between them, revealing the folding mechanism unambiguously.
基金supported by Shenzhen Science and Technology Innovation Committee(JCYJ20170413173837121)the Hong Kong Research Grant Council(HKUST C6009-15G,14203915,16302214,16304215,16318816,and AoE/P-705/16)+2 种基金King Abdullah University of Science and Technology(KAUST) Office of Sponsored Research(OSR)(OSR-2016-CRG5-3007)Guangzhou Science Technology and Innovation Commission(201704030116)Innovation and Technology Commission(ITCPD/17-9and ITC-CNERC14SC01)
文摘Molecular dynamics （MD） simulation has become a powerful tool to investigate the structure- function relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timescales. MD simulations often produce massive datasets con- taining millions of snapshots describing proteins in motion. Therefore, clustering algorithms have been in high demand to be developed and applied to classify these MD snapshots and gain biological insights. There mainly exist two categories of clustering algorithms that aim to group protein conformations into clusters based on the similarity of their shape （geometric clustering） and kinetics （kinetic clustering）. In this paper, we review a series of frequently used clustering algorithms applied in MD simulations, including divisive algorithms, ag- glomerative algorithms （single-linkage, complete-linkage, average-linkage, centroid-linkage and ward-linkage）, center-based algorithms （K-Means, K-Medoids, K-Centers, and APM）, density-based algorithms （neighbor-based, DBSCAN, density-peaks, and Robust-DB）, and spectral-based algorithms （PCCA and PCCA＋）. In particular, differences between geomet- ric and kinetic clustering metrics will be discussed along with the performances of diflhrent clustering algorithms. We note that there does not exist a one-size-fits-all algorithm in the classification of MD datasets. For a specific application, the right choice of clustering algo- rithm should be based on the purpose of clustering, and the intrinsic properties of the MD conformational ensembles. Therefore, a main focus of our review is to describe the merits and limitations of each clustering algorithm. We expect that this review would be helpful to guide researchers to choose appropriate clustering algorithms for their own MD datasets.
基金Supported by the National Natural Science Foundation of China under Grant Nos 19804009 and 10274067.
文摘A novel variational approach is proposed to calculate the ground-state （GS） properties of the two-site Holstein model. By the linear superposition of two coherent states, which simulate the behaviour of the weak and strong coupling limits, we can obtain very accurate GS energy for arbitrary electron-phonon coupling constant. Other GS properties are also discussed. Moreover, the present concise approach is hopefully generalized to many other Holstein models.
