Xuhui Huang

The Hong Kong University of Science and Technology, Chiu-lung, Kowloon City, Hong Kong

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Publications (49)346.61 Total impact

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    ABSTRACT: Protein-ligand recognition plays key roles in many biological processes. One of the most fascinating questions about protein-ligand recognition is to understand its underlying mechanism, which often results from a combination of induced fit and conformational selection. In this study, we have developed a three-pronged approach of Markov State Models, Molecular Dynamics simulations, and flux analysis to determine the contribution of each model. Using this approach, we have quantified the recognition mechanism of the choline binding protein (ChoX) to be ∼90% conformational selection dominant under experimental conditions. This is achieved by recovering all the necessary parameters for the flux analysis in combination with available experimental data. Our results also suggest that ChoX has several metastable conformational states, of which an apo-closed state is dominant, consistent with previous experimental findings. Our methodology holds great potential to be widely applied to understand recognition mechanisms underlining many fundamental biological processes.
    PLoS Computational Biology 08/2014; 10(8):e1003767. · 4.87 Impact Factor
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    ABSTRACT: Nonenzymatic RNA polymerization in early life is likely to introduce backbone heterogeneity with a mixture of 2'-5' and 3'-5' linkages. On the other hand, modern nucleic acids are dominantly composed of 3'-5' linkages. RNA polymerase II (pol II) is a key modern enzyme responsible for synthesizing 3'-5'-linked RNA with high fidelity. It is not clear how modern enzymes, such as pol II, selectively recognize 3'-5' linkages over 2'-5' linkages of nucleic acids. In this work, we systematically investigated how phosphodiester linkages of nucleic acids govern pol II transcriptional efficiency and fidelity. Through dissecting the impacts of 2'-5' linkage mutants in the pol II catalytic site, we revealed that the presence of 2'-5' linkage in RNA primer only modestly reduces pol II transcriptional efficiency without affecting pol II transcriptional fidelity. In sharp contrast, the presence of 2'-5' linkage in DNA template leads to dramatic decreases in both transcriptional efficiency and fidelity. These distinct effects reveal that pol II has an asymmetric (strand-specific) recognition of phosphodiester linkage. Our results provided important insights into pol II transcriptional fidelity, suggesting essential contributions of phosphodiester linkage to pol II transcription. Finally, our results also provided important understanding on the molecular basis of nucleic acid recognition and genetic information transfer during molecular evolution. We suggest that the asymmetric recognition of phosphodiester linkage by modern nucleic acid enzymes likely stems from the distinct evolutionary pressures of template and primer strand in genetic information transfer during molecular evolution.
    Proceedings of the National Academy of Sciences of the United States of America. 07/2014;
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    ABSTRACT: Alzheimer's disease (AD), characterized by cognitive decline, has emerged as a disease of synaptic failure. The present study reveals an unanticipated role of erythropoietin-producing hepatocellular A4 (EphA4) in mediating hippocampal synaptic dysfunctions in AD and demonstrates that blockade of the ligand-binding domain of EphA4 reverses synaptic impairment in AD mouse models. Enhanced EphA4 signaling was observed in the hippocampus of amyloid precursor protein (APP)/presenilin 1 (PS1) transgenic mouse model of AD, whereas soluble amyloid-β oligomers (Aβ), which contribute to synaptic loss in AD, induced EphA4 activation in rat hippocampal slices. EphA4 depletion in the CA1 region or interference with EphA4 function reversed the suppression of hippocampal long-term potentiation in APP/PS1 transgenic mice, suggesting that the postsynaptic EphA4 is responsible for mediating synaptic plasticity impairment in AD. Importantly, we identified a small-molecule rhynchophylline as a novel EphA4 inhibitor based on molecular docking studies. Rhynchophylline effectively blocked the EphA4-dependent signaling in hippocampal neurons, and oral administration of rhynchophylline reduced the EphA4 activity effectively in the hippocampus of APP/PS1 transgenic mice. More importantly, rhynchophylline administration restored the impaired long-term potentiation in transgenic mouse models of AD. These findings reveal a previously unidentified role of EphA4 in mediating AD-associated synaptic dysfunctions, suggesting that it is a new therapeutic target for this disease.
    Proceedings of the National Academy of Sciences of the United States of America. 06/2014;
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    ABSTRACT: Transcription is a central step in gene expression, in which the DNA template is processively read by RNA polymerase II (Pol II), synthesizing a complementary messenger RNA transcript. At each cycle, Pol II moves exactly one register along the DNA, a process known as translocation. Although X-ray crystal structures have greatly enhanced our understanding of the transcription process, the underlying molecular mechanisms of translocation remain unclear. Here we use sophisticated simulation techniques to observe Pol II translocation on a millisecond timescale and at atomistic resolution. We observe multiple cycles of forward and backward translocation and identify two previously unidentified intermediate states. We show that the bridge helix (BH) plays a key role accelerating the translocation of both the RNA:DNA hybrid and transition nucleotide by directly interacting with them. The conserved BH residues, Thr831 and Tyr836, mediate these interactions. To date, this study delivers the most detailed picture of the mechanism of Pol II translocation at atomic level.
    Proceedings of the National Academy of Sciences 04/2014; · 9.81 Impact Factor
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    ABSTRACT: Conformational changes of proteins are an*Author contributed equally with all other contributors. essential part of many biological processes such as: protein folding, ligand binding, signal transduction, allostery, and enzymatic catalysis. Molecular dynamics (MD) simulations can describe the dynamics of molecules at atomic detail, therefore providing a much higher temporal and spatial resolution than most experimental techniques. Although MD simulations have been widely applied to study protein dynamics, the timescales accessible by conventional MD methods are usually limited to timescales that are orders of magnitude shorter than the conformational changes relevant for most biological functions. During the past decades great effort has been devoted to the development of theoretical methods that may enhance the conformational sampling. In recent years, it has been shown that the statistical mechanics framework provided by discrete-state and -time Markov State Models (MSMs) can predict long timescale dynamics from a pool of short MD simulations. In this chapter we provide the readers an account of the basic theory and selected applications of MSMs. We will first introduce the general concepts behind MSMs, and then describe the existing procedures for the construction of MSMs. This will be followed by the discussions of the challenges of constructing and validating MSMs, Finally, we will employ two biologically-relevant systems, the RNA polymerase and the LAO-protein, to illustrate the application of Markov State Models to elucidate the molecular mechanisms of complex conformational changes at biologically relevant timescales.
    Advances in experimental medicine and biology 01/2014; 805:29-66. · 1.83 Impact Factor
  • Xuhui Huang, Gianni De Fabritiis
    Advances in experimental medicine and biology 01/2014; 797:107-14. · 1.83 Impact Factor
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    ABSTRACT: One longstanding puzzle concerning photosystem II, a core component of photosynthesis, is that only one of the two symmetric branches in its reaction centre is active in electron transfer. To investigate the effect of the photosystem II environment on the preferential selection of the energy transfer pathway (a prerequisite for electron transfer), we have constructed an exciton model via extensive molecular dynamics simulations and quantum mechanics/molecular mechanics calculations based on a recent X-ray structure. Our results suggest that it is essential to take into account an ensemble of protein conformations to accurately compute the site energies. We identify the cofactor CLA606 of active chain as the most probable site for the energy excitation. We further pinpoint a number of charged protein residues that collectively lower the CLA606 site energy. Our work provides insights into the understanding of molecular mechanisms of the core machinery of the green-plant photosynthesis.
    Nature Communications 01/2014; 5:4170. · 10.74 Impact Factor
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    ABSTRACT: Markov models and master equations are a powerful means of modeling dynamic processes like protein conformational changes. However, these models are often difficult to understand because of the enormous number of components and connections between them. Therefore, a variety of methods have been developed to facilitate understanding by coarse-graining these complex models. Here, we employ Bayesian model comparison to determine which of these coarse-graining methods provides the models that are most faithful to the original set of states. We find that the Bayesian agglomerative clustering engine and the hierarchical Nyström expansion graph (HNEG) typically provide the best performance. Surprisingly, the original Perron cluster cluster analysis (PCCA) method often provides the next best results, outperforming the newer PCCA+ method and the most probable paths algorithm. We also show that the differences between the models are qualitatively significant, rather than being minor shifts in the boundaries between states. The performance of the methods correlates well with the entropy of the resulting coarse-grainings, suggesting that finding states with more similar populations (i.e., avoiding low population states that may just be noise) gives better results.
    The Journal of Chemical Physics 09/2013; 139(12):121905. · 3.12 Impact Factor
  • Qin Qiao, Gregory R Bowman, Xuhui Huang
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    ABSTRACT: Amyloid fibril deposits of the intrinsically disordered hIAPP peptide are found in 95% of type II diabetes patients, and the aggregation of this peptide is suggested to induce apoptotic cell-death in insulin-producing β cells. Understanding the structure and dynamics of the hIAPP monomer in solution is thus important for understanding the nucleation of aggregation and the formation of oligomers. In this study, we identify the metastable conformational states of the hIAPP monomer and the dynamics of transitioning between them using Markov State Models (MSMs) constructed from extensive Molecular Dynamics (MD) simulations. We show that the overall structure of the hIAPP peptide is random coil-like and lacks a dominant folded structure. Despite this fact, our model reveals a large number of reasonably well-populated metastable conformational states (or local free energy minima) having populations of a few percent or less. The timescales for transitioning between these states range from several microseconds to milliseconds. In contrast to folded proteins, there is no kinetic hub. More strikingly, a few states contain significant amounts of β-hairpin secondary structure and extended hydrophobic surfaces that are exposed to the solvent. We propose that these states may facilitate the nucleation of hIAPP aggregation through a significant component of the conformational selection mechanism, because they may increase their populations upon aggregation by promoting hydrophobic interactions and at the same time provide a flat geometry to seed the ordered β-strand packing of the fibrils.
    Journal of the American Chemical Society 09/2013; · 10.68 Impact Factor
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    ABSTRACT: Markov state models (MSMs) have become a popular approach for investigating the conformational dynamics of proteins and other biomolecules. MSMs are typically built from numerous molecular dynamics simulations by dividing the sampled configurations into a large number of microstates based on geometric criteria. The resulting microstate model can then be coarse-grained into a more understandable macrostate model by lumping together rapidly mixing microstates into larger, metastable aggregates. However, finite sampling often results in the creation of many poorly sampled microstates. During coarse-graining, these states are mistakenly identified as being kinetically important because transitions to/from them appear to be slow. In this paper, we propose a formalism based on an algebraic principle for matrix approximation, i.e., the Nyström method, to deal with such poorly sampled microstates. Our scheme builds a hierarchy of microstates from high to low populations and progressively applies spectral clustering on sets of microstates within each level of the hierarchy. It helps spectral clustering identify metastable aggregates with highly populated microstates rather than being distracted by lowly populated states. We demonstrate the ability of this algorithm to discover the major metastable states on two model systems, the alanine dipeptide and trpzip2 peptide.
    The Journal of Chemical Physics 05/2013; 138(17):174106. · 3.12 Impact Factor
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    ABSTRACT: The dynamics of the PPi release during the transcription elongation of bacterial RNA polymerase and its effects on the Trigger Loop (TL) opening motion are still elusive. Here, we built a Markov State Model (MSM) from extensive all-atom molecular dynamics (MD) simulations to investigate the mechanism of the PPi release. Our MSM has identified a simple two-state mechanism for the PPi release instead of a more complex four-state mechanism observed in RNA polymerase II (Pol II). We observed that the PPi release in bacterial RNA polymerase occurs at sub-microsecond timescale, which is ∼3-fold faster than that in Pol II. After escaping from the active site, the (Mg-PPi)(2-) group passes through a single elongated metastable region where several positively charged residues on the secondary channel provide favorable interactions. Surprisingly, we found that the PPi release is not coupled with the TL unfolding but correlates tightly with the side-chain rotation of the TL residue R1239. Our work sheds light on the dynamics underlying the transcription elongation of the bacterial RNA polymerase.
    PLoS Computational Biology 04/2013; 9(4):e1003020. · 4.87 Impact Factor
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    ABSTRACT: We implemented a GPU-powered parallel k-centers algorithm to perform clustering on the conformations of molecular dynamics (MD) simulations. The algorithm is up to two orders of magnitude faster than the CPU implementation. We tested our algorithm on four protein MD simulation datasets ranging from the small Alanine Dipeptide to a 370-residue Maltose Binding Protein (MBP). It is capable of grouping 250,000 conformations of the MBP into 4000 clusters within 40 s. To achieve this, we effectively parallelized the code on the GPU and utilize the triangle inequality of metric spaces. Furthermore, the algorithm's running time is linear with respect to the number of cluster centers. In addition, we found the triangle inequality to be less effective in higher dimensions and provide a mathematical rationale. Finally, using Alanine Dipeptide as an example, we show a strong correlation between cluster populations resulting from the k-centers algorithm and the underlying density. © 2012 Wiley Periodicals, Inc.
    Journal of Computational Chemistry 09/2012; · 3.84 Impact Factor
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    ABSTRACT: Vibrationally resolved fluorescence spectra of the β-hairpin trpzip2 peptide at two temperatures as well as during a T-jump unfolding process are simulated on the basis of a combination of Markov state models and quantum chemistry schemes. The broad asymmetric spectral line shape feature is reproduced by considering the exciton-phonon couplings. The temperature dependent red shift observed in the experiment has been attributed to the state population changes of specific chromophores. Through further theoretical study, it is found that both the environment's electric field and the chromophores' geometry distortions are responsible for tryptophan fluorescence shift.
    The Journal of Physical Chemistry B 09/2012; 116(42):12669-76. · 3.61 Impact Factor
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    ABSTRACT: In this contribution, we conceptually present a new avenue to construction of molecular functional materials with high performance of circularly polarised luminescence (CPL) in the condensed phase. A molecule (1) containing luminogenic silole and chiral sugar moieties was synthesized and thoroughly characterized. In a solution of 1, no circular dichroism (CD) and fluorescence emission are observed, but upon molecular aggregation, both the CD and fluorescence are simultaneously turned on, showing aggregation-induced CD (AICD) and emission (AIE) effects. The AICD effect is supported by the fact that the molecules readily assemble into right-handed helical nanoribbons and superhelical ropes when aggregated. The AIE effect boosts the fluorescence quantum efficiency (ΦF) by 136 fold (ΦF, 0.6% in the solution versus 81.3% in the solid state), which surmounts the serious limitations of aggregation-caused quenching effect encountered by conventional luminescent materials. Time-resolved fluorescence study and theoretical calculation from first principles conclude that restriction of the low-frequency intramolecular motions is responsible for the AIE effect. The helical assemblies of 1 prefer to emit right-handed circularly polarised light and display large CPL dissymmetry factors (gem), whose absolute values are in the range of 0.08–0.32 and are two orders of magnitude higher than those of commonly reported organic materials. We demonstrate for the first time the use of a Teflon-based microfluidic technique for fabrication of the fluorescent pattern. This shows the highest gem of −0.32 possibly due to the enhanced assembling order in the confined microchannel environment. The CPL performance was preserved after more than half year storage under ambient conditions, revealing the excellent spectral stability. Computational simulation was performed to interpret how the molecules in the aggregates interact with each other at the molecular level. Our designed molecule represents the desired molecular functional material for generating efficient CPL in the solid state, and the current study shows the best results among the reported organic conjugated molecular systems in terms of emission efficiency, dissymmetry factor, and spectral stability.
    Chemical Science 07/2012; 3(9):2737-2747. · 8.31 Impact Factor
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    ABSTRACT: We present a set of force field (FF) parameters compatible with the AMBER03 FF to describe five cofactors in photosystem II (PSII) of oxygenic photosynthetic organisms: plastoquinone-9 (three redox forms), chlorophyll-a, pheophytin-a, heme-b, and β-carotene. The development of a reliable FF for these cofactors is an essential step for performing molecular dynamics simulations of PSII. Such simulations are important for the calculation of absorption spectrum and the further investigation of the electron and energy transfer processes. We have derived parameters for partial charges, bonds, angles, and dihedral-angles from solid theoretical models using systematic quantum mechanics (QM) calculations. We have shown that the developed FF parameters are in good agreement with both ab initio QM and experimental structural data in small molecule crystals as well as protein complexes.
    Journal of Computational Chemistry 06/2012; 33(25):1969-80. · 3.84 Impact Factor
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    ABSTRACT: In this article, we review the recent progress in multiresolution modeling of structure and dynamics of protein, RNA and their complexes. Many approaches using both physics-based and knowledge-based potentials have been developed at multiple granularities to model both protein and RNA. Coarse graining can be achieved not only in the length, but also in the time domain using discrete time and discrete state kinetic network models. Models with different resolutions can be combined either in a sequential or parallel fashion. Similarly, the modeling of assemblies is also often achieved using multiple granularities. The progress shows that a multiresolution approach has considerable potential to continue extending the length and time scales of macromolecular modeling.
    Briefings in Bioinformatics 01/2012; 13(4):395-405. · 5.30 Impact Factor
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    Lin-Tai Da, Dong Wang, Xuhui Huang
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    ABSTRACT: Pyrophosphate ion (PP(i)) release after nucleotide incorporation is a necessary step for RNA polymerase II (pol II) to enter the next nucleotide addition cycle during transcription elongation. However, the role of pol II residues in PP(i) release and the mechanistic relationship between PP(i) release and the conformational change of the trigger loop remain unclear. In this study, we constructed a Markov state model (MSM) from extensive all-atom molecular dynamics (MD) simulations in the explicit solvent to simulate the PP(i) release process along the pol II secondary channel. Our results show that the trigger loop has significantly larger intrinsic motion after catalysis and formation of PP(i), which in turn aids PP(i) release mainly through the hydrogen bonding between the trigger loop residue H1085 and the (Mg-PP(i))(2-) group. Once PP(i) leaves the active site, it adopts a hopping model through several highly conserved positively charged residues such as K752 and K619 to release from the pol II pore region of the secondary channel. These positive hopping sites form favorable interactions with PP(i) and generate four kinetically metastable states as identified by our MSM. Furthermore, our single-mutant simulations suggest that H1085 and K752 aid PP(i) exit from the active site after catalysis, whereas K619 facilitates its passage through the secondary channel. Finally, we suggest that PP(i) release could help the opening motion of the trigger loop, even though PP(i) release precedes full opening of the trigger loop due to faster PP(i) dynamics. Our simulations provide predictions to guide future experimental tests.
    Journal of the American Chemical Society 12/2011; 134(4):2399-406. · 10.68 Impact Factor
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    ABSTRACT: Amyloid fibrillation of proteins is associated with a great variety of pathologic conditions. Development of new molecules that can monitor amyloidosis kinetics and inhibit fibril formation is of great diagnostic and therapeutic value. In this work, we have developed a biocompatible molecule that functions as an ex situ monitor and an in situ inhibitor for protein fibrillation, using insulin as a model protein. 1,2-Bis[4-(3-sulfonatopropoxyl)phenyl]-1,2-diphenylethene salt (BSPOTPE) is nonemissive when it is dissolved with native insulin in an incubation buffer but starts to fluoresce when it is mixed with preformed insulin fibril, enabling ex situ monitoring of amyloidogenesis kinetics and high-contrast fluorescence imaging of protein fibrils. Premixing BSPOTPE with insulin, on the other hand, inhibits the nucleation process and impedes the protofibril formation. Increasing the dose of BSPOTPE boosts its inhibitory potency. Theoretical modeling using molecular dynamics simulations and docking reveals that BSPOTPE is prone to binding to partially unfolded insulin through hydrophobic interaction of the phenyl rings of BSPOTPE with the exposed hydrophobic residues of insulin. Such binding is assumed to have stabilized the partially unfolded insulin and obstructed the formation of the critical oligomeric species in the protein fibrillogenesis process.
    Journal of the American Chemical Society 12/2011; 134(3):1680-9. · 10.68 Impact Factor
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    ABSTRACT: The initiation of transcription by RNA polymerase II is a multistage process. X-ray crystal structures of transcription complexes containing short RNAs reveal three structural states: one with 2- and 3-nucleotide RNAs, in which only the 3'-end of the RNA is detectable; a second state with 4- and 5-nucleotide RNAs, with an RNA-DNA hybrid in a grossly distorted conformation; and a third state with RNAs of 6 nucleotides and longer, essentially the same as a stable elongating complex. The transition from the first to the second state correlates with a markedly reduced frequency of abortive initiation. The transition from the second to the third state correlates with partial "bubble collapse" and promoter escape. Polymerase structure is permissive for abortive initiation, thereby setting a lower limit on polymerase-promoter complex lifetime and allowing the dissociation of nonspecific complexes. Abortive initiation may be viewed as promoter proofreading, and the structural transitions as checkpoints for promoter control.
    Science 07/2011; 333(6042):633-7. · 31.20 Impact Factor
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    ABSTRACT: RNA molecules play integral roles in gene regulation, and understanding their structures gives us important insights into their biological functions. Despite recent developments in template-based and parameterized energy functions, the structure of RNA--in particular the nonhelical regions--is still difficult to predict. Knowledge-based potentials have proven efficient in protein structure prediction. In this work, we describe two differentiable knowledge-based potentials derived from a curated data set of RNA structures, with all-atom or coarse-grained representation, respectively. We focus on one aspect of the prediction problem: the identification of native-like RNA conformations from a set of near-native models. Using a variety of near-native RNA models generated from three independent methods, we show that our potential is able to distinguish the native structure and identify native-like conformations, even at the coarse-grained level. The all-atom version of our knowledge-based potential performs better and appears to be more effective at discriminating near-native RNA conformations than one of the most highly regarded parameterized potential. The fully differentiable form of our potentials will additionally likely be useful for structure refinement and/or molecular dynamics simulations.
    RNA 06/2011; 17(6):1066-75. · 5.09 Impact Factor

Publication Stats

1k Citations
346.61 Total Impact Points


  • 2010–2014
    • The Hong Kong University of Science and Technology
      • Department of Chemistry
      Chiu-lung, Kowloon City, Hong Kong
  • 2013
    • Peking University
      • School of Mathematical Sciences
      Beijing, Beijing Shi, China
    • University of California, Berkeley
      Berkeley, California, United States
  • 2011
    • Dalian Institute of Chemical Physics
      Lü-ta-shih, Liaoning, China
  • 2008–2010
    • Stanford University
      • Department of Chemistry
      Palo Alto, CA, United States
  • 2004–2010
    • Columbia University
      • Department of Chemistry
      New York City, NY, United States
    • IBM
      • Computational Biology Center
      Armonk, NY, United States
  • 2009
    • Stanford Medicine
      • Department of Structural Biology
      Stanford, California, United States