Ray Luo

University of California, Irvine, Irvine, California, United States

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Publications (59)170.78 Total impact

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    ABSTRACT: A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier–Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design.
    Chemical Physics Letters 11/2014; 616. · 2.15 Impact Factor
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    ABSTRACT: The KH3 domain of Nova-2 protein can precisely recognize the sequence-specific target RNA of human glycine receptor α2. However, the recognition mechanism between the protein and its target RNA is still hotly debated. In this study molecular dynamic simulations in explicit solvent were utilized to understand the recognition mechanism. The structural analysis and the Kolmogorov-Smirnov P-test statistics reveal that the KH3 domain might obey a conformational selection mechanism upon RNA binding. However, the induced fit mechanism could not be completely ruled out. Unfolding kinetics indicates that the folding of RNA and KH3 happens first, then the binding between RNA and KH3 follows. Principle component analysis shows that the invariant Gly-Lys-Gly-Gly loop moves towards to the RNA molecule but the C-terminal domain moves away from the RNA molecule upon binding. These specific dominant motions were hypothesized to stabilize the complex structure. The hydrophobic and hydrogen bonding interactions were found to be the driving forces for the specific recognition, in contrast to the dominant electrostatic interactions for non-specific recognition.
    The journal of physical chemistry. B. 10/2014;
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    ABSTRACT: Continuum electrostatics modeling of solvation based on the Poisson–Boltzmann (PB) equation has gained wide acceptance in biomolecular applications such as energetic analysis and structural visualization. Successful application of the PB solvent models requires careful calibration of the solvation parameters. Extensive testing and validation is also important to ensure accuracy in their applications. Limitation in the continuum modeling of solvation is also a known issue in certain biomolecular applications. Growing interest in membrane systems has further spurred developmental efforts to allow inclusion of membrane in the PB solvent models. Despite their past successes due to careful parameterization, algorithm development and parallel implementation, there is still much to be done to improve their transferability from the small molecular systems upon which they were developed and validated to complex macromolecular systems as advances in technology continue to push forward, providing ever greater computational resources to researchers to study more interesting biological systems of higher complexity.
    Journal of Theoretical and Computational Chemistry 05/2014; 13(03). · 0.52 Impact Factor
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    ABSTRACT: Electrostatic solvation modeling based upon the Poisson–Boltzmann equation is widely used in studies of biomolecular structures and functions. This manuscript provides a thorough review of published efforts to adapt the numerical Poisson–Boltzmann methods to molecular simulations so that these methods can be extended to biomolecular studies involving conformational fluctuation and/or dynamics. We first review the fundamental works on how to define the electrostatic free energy and the Maxwell stress tensor. These topics are followed by three different strategies in developing algorithms to compute electrostatic forces and how to improve their numerical performance. Finally procedures are also presented in detail on how to discretize these algorithms for numerical calculations. Given the pioneer works reviewed here, further developmental efforts will be on how to balance efficiency and accuracy in these theoretical sound approaches — two important issues in applying any numerical algorithms for routine biomolecular applications. Even if not reviewed here, more advanced numerical solvers are certainly necessary to achieve higher accuracy than the widely used classical methods to improve the overall performance of the numerical Poisson–Boltzmann methods.
    Journal of Theoretical and Computational Chemistry 05/2014; 13(03). · 0.52 Impact Factor
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    ABSTRACT: Intrinsically disordered proteins (IDPs) or intrinsically disordered protein regions comprise a large portion of eukaryotic proteomes (between 35% and 51%). These IDPs were found to link with cancer and various other diseases. However, widely used additive force field parameter sets are insufficient in quantifying the structural properties of IDPs. Therefore, we explored to a systematic correction of a base additive force field parameter set (chosen as Amber ff99SBildn) to correct the biases that was first demonstrated in simulations with the base parameter set. Specifically the φ/ψ distributions of disorder-promoting residues were systematically corrected with the CMAP method. Our simulations show that the CMAP corrected Amber parameter set, termed ff99IDPs, improves the φ/ψ distributions of the disorder-promoting residues with respect to the benchmark data of IDP structures, with root mean squared percentage deviation less than 0.15% between the simulation and the benchmark. Our further validation shows that the chemical shifts from the ff99IDPs simulations are in quantitative agreement with those from reported NMR measurements for two tested IDPs, MeV NTAIL and p53. The predicted residue dipolar couplings also show high correlation with experimental data. Interestingly, our simulations show that ff99IDPs can still be used to model the ordered state when the IDPs are in complex, in contrast to ff99SBildn that can be applied well only to the ordered complex structures. These findings confirm that the newly proposed Amber ff99IDPs parameter set provides a reasonable tool in further studies of intrinsically disordered protein structures. In addition, our study also shows the importance of considering IDP structures in general-purpose force field developments for both additive and nonadditive models. This article is protected by copyright. All rights reserved.
    Chemical Biology &amp Drug Design 03/2014; · 2.47 Impact Factor
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    ABSTRACT: Accurate and efficient treatment of electrostatics is a crucial step in computational analyses of biomolecular structures and dynamics. In this study, we have explored a second-order finite-difference numerical method to solve the widely used Poisson-Boltzmann equation for electrostatic analyses of realistic bio-molecules. The so-called immersed interface method was first validated and found to be consistent with the classical weighted harmonic averaging method for a diversified set of test biomolecules. The numerical accuracy and convergence behaviors of the new method were next analyzed in its computation of numerical reaction field grid potentials, energies, and atomic solvation forces. Overall similar convergence behaviors were observed as those by the classical method. Interestingly, the new method was found to deliver more accurate and better-converged grid potentials than the classical method on or nearby the molecular surface, though the numerical advantage of the new method is reduced when grid potentials are extrapolated to the molecular surface. Our exploratory study indicates the need for further improving interpolation/extrapolation schemes in addition to the developments of higher-order numerical methods that have attracted most attention in the field.
    Computational and Theoretical Chemistry 11/2013; 1024:34-44. · 1.14 Impact Factor
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    ABSTRACT: The kink-turn sRNA motif in archaea, whose combination with protein L7Ae initializes the assembly of small ribonucleoprotein particles (sRNPs), plays a key role in ribosome maturation and the translation process. Although many studies have been reported on this motif, the mechanism of sRNA folding coupled with protein binding is still poorly understood. Here, room and high temperature molecular dynamics (MD) simulations were performed on the complex of 25-nt kink-turn sRNA and L7Ae. The average RMSD values between the bound and corresponding apo structures and Kolmogorov-Smirnov P test analysis indicate that sRNA may follow an induced fit mechanism upon binding with L7Ae, both locally and globally. These conclusions are further supported by high-temperature unfolding kinetic analysis. Principal component analysis (PCA) found both closing and opening motions of the kink-turn sRNA. This might play a key role in the sRNP assembly and methylation catalysis. These combined computational methods can be used to study the specific recognition of other sRNAs and proteins.
    Physical Chemistry Chemical Physics 09/2013; · 4.20 Impact Factor
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    ABSTRACT: Continuum modeling of electrostatic interactions based upon numerical solutions of the Poisson-Boltzmann equation has been widely used in structural and functional analyses of biomolecules. A limitation of the numerical strategies is that it is conceptually difficult to incorporate these types of models into molecular mechanics simulations, mainly because of the issue in assigning atomic forces. In this theoretical study, we first derived the Maxwell stress tensor for molecular systems obeying the full nonlinear Poisson-Boltzmann equation. We further derived formulations of analytical electrostatic forces given the Maxwell stress tensor and discussed the relations of the formulations with those published in the literature. We showed that the formulations derived from the Maxwell stress tensor require a weaker condition for its validity, applicable to nonlinear Poisson-Boltzmann systems with a finite number of singularities such as atomic point charges and the existence of discontinuous dielectric as in the widely used classical piece-wise constant dielectric models.
    The Journal of Chemical Physics 09/2013; 139(9):094106. · 3.12 Impact Factor
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    ABSTRACT: Antibody-antigen specific recognition is essential in autoimmunity. In this study, antibody SPE7 binding to protein antigens and to hapten molecules were carefully analyzed in order to gain insight into their binding mechanisms. X-ray crystal structures show that SPE7 can adopt at least four different conformations, as in the two observed free isomers (Ab1 and Ab2) and the two observed bound conformers (Ab3 and Ab4). Multidimensional scaling analysis reveals that antibody SPE7 may obey a global conformational selection mechanism upon its binding to an antigen. The conformations of key residue at the binding site (Trp93L) further reveals that bound isomer Ab3 may come from free isomer Ab2, and bound isomer Ab4 from free isomer Ab1. The average RMSD values between the bound isomers and the corresponding free isomers and Kolmogorov-Smimov P test analysis indicate that the antibody may also follow a local induced fit mechanism at the binding interface. Quantitative analysis indicates that the magnitude of the local induced fit interaction at the binding site is more pronounced than that of the global conformational selection interaction. These conclusions are further supported by high-temperature unbinding kinetics analysis. The computational methods proposed here can also be used to study the specific recognitions between other antibody and antigen systems.
    The Journal of Physical Chemistry B 04/2013; · 3.61 Impact Factor
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    ABSTRACT: Membrane protein systems are important computational research topics due to their roles in rational drug design. In this study, we developed a continuum membrane model utilizing a level set formulation under the numerical Poisson-Boltzmann framework within the AMBER molecular mechanics suite for applications such as protein-ligand binding affinity and docking pose predictions. Two numerical solvers were adapted for periodic systems to alleviate possible edge effects. Validation on systems ranging from organic molecules to membrane proteins up to 200 residues, demonstrated good numerical properties. This lays foundations for sophisticated models with variable dielectric treatments and second-order accurate modeling of solvation interactions.
    Chemical Physics Letters 01/2013; 555:274-281. · 2.15 Impact Factor
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    ABSTRACT: Continuum solvent treatments based on the Poisson-Boltzmann equation have been widely accepted for energetic analysis of biomolecular systems. In these approaches, the molecular solute is treated as a low dielectric region and the solvent is treated as a high dielectric continuum. The existence of a sharp dielectric jump at the solute-solvent interface poses a challenge to model the solvation energetics accurately with such a simple mathematical model. In this study, we explored and evaluated a strategy based on the "induced surface charge" to eliminate the dielectric jump within the finite-difference discretization scheme. In addition to the use of the induced surface charges in solving the equation, the second-order accurate immersed interface method is also incorporated to discretize the equation. The resultant linear system is solved with the GMRES algorithm to explicitly impose the flux conservation condition across the solvent-solute interface. The new strategy was evaluated on both analytical and realistic biomolecular systems. The numerical tests demonstrate the feasibility of utilizing induced surface charge in the finite-difference solution of the Poisson-Boltzmann equation. The analysis data further show that the strategy is consistent with theory and the classical finite-difference method on the tested systems. Limitations of the current implementations and further improvements are also analyzed and discussed to fully bring out its potential of achieving higher numerical accuracy.
    Physical Chemistry Chemical Physics 11/2012; · 4.20 Impact Factor
  • Qin Cai, Xiang Ye, Ray Luo
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    ABSTRACT: Continuum solvation representations based on the Poisson-Boltzmann equation have become widely accepted in biomolecular applications after years of basic research and development. Since analytical solution of the differential equation can be achieved only in a few specific cases with simple solute geometry, only numerical solution is possible for biomolecular applications. However, it is conceptually difficult to assign solvation forces in the numerical methods, limiting their applications into direct simulations of energy minimization and molecular dynamics. In this study a dielectric pressure formulation was derived from the general Maxwell stress tensor for continuum solvation of biomolecules modeled with the widely used abrupt-transitioned dielectrics. A charge-central strategy was then proposed to improve the numerical behavior of the computed pressure. An interesting observation is the highly similar charge-central formulations between the smooth-transition dielectric and the abrupt-transition dielectric models utilized in the biomolecular solvation treatments. The connections of the new formulation with both the Davis-McCammon and Gilson et al. approaches were further presented after applying the normal field approximation. The consistency was verified with the numerical tests on a realistic biomolecule. The numerical experiments on the tested biomolecule further indicate that the charge-central strategy combined with the normal field approximation not only improves the accuracy of the dielectric boundary force but also reduces its grid dependence for biomolecular applications.
    Physical Chemistry Chemical Physics 10/2012; · 4.20 Impact Factor
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    ABSTRACT: Grid dependence in numerical reaction field energies and solvation forces is a well-known limitation in the finite-difference Poisson-Boltzmann methods. In this study we have investigated several numerical strategies to overcome the limitation. Specifically, we have included trimer arc dots during analytical molecular surface generation to improve the convergence of numerical reaction field energies and solvation forces. We have also utilized the level set function to trace the molecular surface implicitly to simplify the numerical mapping of the grid-independent solvent excluded surface. We have further explored to combine the weighted harmonic averaging of boundary dielectrics with a charge-based approach to improve the convergence and stability of numerical reaction field energies and solvation forces. Our test data show that the convergence and stability in both numerical energies and forces can be improved significantly when the combined strategy is applied to either the Poisson equation or the full Poisson-Boltzmann equation.
    Journal of Chemical Theory and Computation 08/2012; 8(8):2741-2751. · 5.39 Impact Factor
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    ABSTRACT: As an integrated step toward a coherent polarizable force field for biomolecular modeling, we analyzed four polarizable water models to evaluate their consistencies with the Thole polarization screening schemes utilized in our latest Amber polarizable force field. Specifically, we studied the performance of both the Thole linear and exponential schemes in these water models to assess their abilities to reproduce experimental water properties. The analysis shows that the tested water models reproduce most of the room-temperature properties of liquid water reasonably well but fall short of reproducing the dynamic properties and temperature-dependent properties. This study demonstrates the necessity to further fine-tune water polarizable potentials for more robust polarizable force fields for biomolecular simulations.
    The Journal of Physical Chemistry B 06/2012; · 3.61 Impact Factor
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    ABSTRACT: In the previous publications of this series, we presented a set of Thole induced dipole interaction models using four types of screening functions. In this work, we document our effort to refine the van der Waals parameters for the Thole polarizable models. Following the philosophy of AMBER force field development, the van der Waals (vdW) parameters were tuned for the Thole model with linear screening function to reproduce both the ab initio interaction energies and the experimental densities of pure liquids. An in-house genetic algorithm was applied to maximize the fitness of "chromosomes" which is a function of the root-mean-square errors (RMSE) of interaction energy and liquid density. To efficiently explore the vdW parameter space, a novel approach was developed to estimate the liquid densities for a given vdW parameter set using the mean residue-residue interaction energies through interpolation/extrapolation. This approach allowed the costly molecular dynamics simulations be performed at the end of each optimization cycle only and eliminated the simulations during the cycle. Test results show notable improvements over the original AMBER FF99 vdW parameter set, as indicated by the reduction in errors of the calculated pure liquid densities (d), heats of vaporization (H(vap)), and hydration energies. The average percent error (APE) of the densities of 59 pure liquids was reduced from 5.33 to 2.97%; the RMSE of H(vap) was reduced from 1.98 to 1.38 kcal/mol; the RMSE of solvation free energies of 15 compounds was reduced from 1.56 to 1.38 kcal/mol. For the interaction energies of 1639 dimers, the overall performance of the optimized vdW set is slightly better than the original FF99 vdW set (RMSE of 1.56 versus 1.63 kcal/mol). The optimized vdW parameter set was also evaluated for the exponential screening function used in the Amoeba force field to assess its applicability for different types of screening functions. Encouragingly, comparable performance was observed when the optimized vdW set was combined with the Thole Amoeba-like polarizable model, particularly for the interaction energy and liquid density calculations. Thus, the optimized vdW set is applicable to both types of Thole models with either linear or Amoeba-like screening functions.
    The Journal of Physical Chemistry B 05/2012; 116(24):7088-101. · 3.61 Impact Factor
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    ABSTRACT: MicroRNAs are endogenous 23-25 nt RNAs that play important gene-regulatory roles in animals and plants. Recently, miR369-3 was found to upregulate translation of TNFα mRNA in quiescent (G0) mammalian cell lines. Knock down and immunofluorescence experiments suggest that microRNA-protein complexes (with FXR1 and AGO2) are necessary for the translation upregulation. However the molecular mechanism of microRNA translation activation is poorly understood. In this study we constructed the microRNA-mRNA-AGO2-FXR1 quadruple complex by bioinformatics and molecular modeling, followed with all atom molecular dynamics simulations in explicit solvent to investigate the interaction mechanisms for the complex. A combined analysis of experimental and computational data suggests that AGO2-FXR1 complex relocalize microRNA:mRNA duplex to polysomes in G0. The two strands of dsRNA are then separated upon binding of AGO2 and FXR1. Finally, polysomes may improve the translation efficiency of mRNA. The mutation research confirms the stability of microRNA-mRNA-FXR1 and illustrates importance of key residue of Ile304. This possible mechanism can shed more light on the microRNA-dependent upregulation of translation.
    PLoS ONE 01/2012; 7(8):e43788. · 3.53 Impact Factor
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    ABSTRACT: Most implicit solvation models require the definition of a molecular surface as the interface that separates the solute in atomic detail from the solvent approximated as a continuous medium. Commonly used surface definitions include the solvent accessible surface (SAS), the solvent excluded surface (SES), and the van der Waals surface. In this study, we present an efficient numerical algorithm to compute the SES and SAS areas to facilitate the applications of finite-difference Poisson-Boltzmann methods in biomolecular simulations. Different from previous numerical approaches, our algorithm is physics-inspired and intimately coupled to the finite-difference Poisson-Boltzmann methods to fully take advantage of its existing data structures. Our analysis shows that the algorithm can achieve very good agreement with the analytical method in the calculation of the SES and SAS areas. Specifically, in our comprehensive test of 1,555 molecules, the average unsigned relative error is 0.27% in the SES area calculations and 1.05% in the SAS area calculations at the grid spacing of 1/2Å. In addition, a systematic correction analysis can be used to improve the accuracy for the coarse-grid SES area calculations, with the average unsigned relative error in the SES areas reduced to 0.13%. These validation studies indicate that the proposed algorithm can be applied to biomolecules over a broad range of sizes and structures. Finally, the numerical algorithm can also be adapted to evaluate the surface integral of either a vector field or a scalar field defined on the molecular surface for additional solvation energetics and force calculations.
    Journal of Chemical Theory and Computation 11/2011; 7(11):3608-3619. · 5.39 Impact Factor
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    ABSTRACT: Continuum modeling of electrostatic interactions based upon the numerical solutions of the Poisson-Boltzmann equation has been widely adopted in biomolecular applications. To extend their applications to molecular dynamics and energy minimization, robust and efficient methodologies to compute solvation forces must be developed. In this study, we have first reviewed the theory for the computation of dielectric boundary forces based on the definition of the Maxwell stress tensor. This is followed by a new formulation of the dielectric boundary force suitable for the finite-difference Poisson-Boltzmann methods. We have validated the new formulation with idealized analytical systems and realistic molecular systems.
    Chemical Physics Letters 10/2011; 514(4-6):368-373. · 2.15 Impact Factor
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    ABSTRACT: In this work, four types of polarizable models have been developed for calculating interactions between atomic charges and induced point dipoles. These include the Applequist, Thole linear, Thole exponential model, and the Thole Tinker-like. The polarizability models have been optimized to reproduce the experimental static molecular polarizabilities obtained from the molecular refraction measurements on a set of 420 molecules reported by Bosque and Sales. We grouped the models into five sets depending on the interaction types, that is, whether the interactions of two atoms that form the bond, bond angle, and dihedral angle are turned off or scaled down. When 1-2 (bonded) and 1-3 (separated by two bonds) interactions are turned off, 1-4 (separated by three bonds) interactions are scaled down, or both, all models including the Applequist model achieved similar performance: the average percentage error (APE) ranges from 1.15 to 1.23%, and the average unsigned error (AUE) ranges from 0.143 to 0.158 Å(3). When the short-range 1-2, 1-3, and full 1-4 terms are taken into account (set D models), the APE ranges from 1.30 to 1.58% for the three Thole models, whereas the Applequist model (DA) has a significantly larger APE (3.82%). The AUE ranges from 0.166 to 0.196 Å(3) for the three Thole models, compared with 0.446 Å(3) for the Applequist model. Further assessment using the 70-molecule van Duijnen and Swart data set clearly showed that the developed models are both accurate and highly transferable and are in fact have smaller errors than the models developed using this particular data set (set E models). The fact that A, B, and C model sets are notably more accurate than both D and E model sets strongly suggests that the inclusion of 1-2 and 1-3 interactions reduces the transferability and accuracy.
    The Journal of Physical Chemistry B 03/2011; 115(12):3091-9. · 3.61 Impact Factor
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    ABSTRACT: In the companion paper, we presented a set of induced dipole interaction models using four types of screening functions, which include the Applequist (no screening), the Thole linear, the Thole exponential model, and the Thole Tinker-like (another form of exponential screening function) functions. In this work, we evaluate the performance of polarizability models using a large set of amino acid analog pairs in conformations that are frequently observed in protein structures as a benchmark. For each amino acid pair, we calculated quantum mechanical interaction energies at the MP2/aug-cc-pVTZ//MP2/6-311++G(d,p) level with the basis set superposition error (BSSE) correction and compared them with molecular mechanics results. Encouragingly, all polarizable models significantly outperform the additive F94 and F03 models (mimicking AMBER ff94/ff99 and ff03 force fields, respectively) in reproducing the BSSE-corrected quantum mechanical interaction energies. In particular, the root-mean-square errors (RMSEs) for three Thole models in Set A (where the 1-2 and 1-3 interactions are turned off and all 1-4 interactions are included) are 1.456, 1.417, and 1.406 kcal/mol for model AL (Thole Linear), model AE (Thole exponential), and model AT (Thole Tinker-like), respectively. In contrast, the RMSEs are 3.729 and 3.433 kcal/mol for F94 and F03 models, respectively. A similar trend was observed for the average unsigned errors (AUEs), which are 1.057, 1.025, 1.011, 2.219, and 2.070 kcal/mol for AL, AE, AT, F94/ff99, and F03, respectively. Analyses based on the trend line slopes indicate that the two fixed charge models substantially underestimate the relative strengths of noncharge-charge interactions by 24 (F03) and 35% (F94), respectively, whereas the four polarizable models overestimate the relative strengths by 5 (AT), 3 (AL, AE), and 13% (AA), respectively. Agreement was further improved by adjusting the van der Waals parameters. Judging from the notably improved accuracy in comparison with the fixed charge models, the polarizable models are expected to form the foundation for the development of high quality polarizable force fields for protein and nucleic acid simulations.
    The Journal of Physical Chemistry B 03/2011; 115(12):3100-11. · 3.61 Impact Factor

Publication Stats

4k Citations
170.78 Total Impact Points

Institutions

  • 2003–2014
    • University of California, Irvine
      • • Department of Molecular Biology and Biochemistry
      • • Department of Biomedical Engineering
      Irvine, California, United States
  • 2012–2013
    • Shanghai University
      Shanghai, Shanghai Shi, China
  • 2009–2013
    • CSU Mentor
      Long Beach, California, United States
  • 2011–2012
    • University of Texas Southwestern Medical Center
      • Department of Pharmacology
      Dallas, TX, United States
    • Shanghai Normal University
      Shanghai, Shanghai Shi, China
  • 2004
    • University of California, San Francisco
      • Department of Pharmaceutical Chemistry
      San Francisco, CA, United States