Junchao Xia

Bio: Junchao Xia is an academic researcher from Temple University. The author has contributed to research in topics: Magnetic field & Replica. The author has an hindex of 19, co-authored 42 publications receiving 805 citations. Previous affiliations of Junchao Xia include Clark University & University of Iowa.

How Does Water Affect the Dynamics of the Room-Temperature Ionic Liquid 1-Hexyl-3-methylimidazolium Hexafluorophosphate and the Fluorescence Spectroscopy of Coumarin-153 When Dissolved in It?

Abstract: Molecular dynamics simulations of mixtures of 1-hexyl-3-methylimidazolium hexafluorophosphate ([HMIM+][PF6-]) and water have been performed in order to investigate how small amounts of water affect the translational and rotational dynamics of this ionic liquid (IL). We find that water is closely associated with the anions and that its presence enhances both the translational and rotational dynamics of the IL. In agreement with experiments, we find that the fluorescence spectra of Coumarin-153 is red-shifted because of the presence of water. Small amounts of water enhance the speed of relaxation of the solvent surrounding the solute probe after photoexcitation, but only at a “local environment” level. Interconversion between environments still occurs on a long time scale compared with the fluorescence lifetime of the probe. Excitation wavelength-dependent emission is observed both in the neat IL and in the IL+water mixture.

The cooling rate dependence of crystallization for liquid copper: A molecular dynamics study

Abstract: The constant-pressure molecular dynamics simulations based on the second-moment approximation of tight-binding scheme have been performed to study the relationship between the resulting crystallization microstructure of the liquid copper and the cooling rate. Below the glass-forming critical cooling rate, the metastable hcp phase and the stable fcc phase can coexist in the resulting configuration with all sorts of proportion and various forms such as layering and phase separation. The sizes and the distributions of the two crystalline phases depend on the cooling rate: the faster the cooling rate the larger percents of the metastable hcp phase and the more easily the layering take place. From the split of peaks of the angular distribution function, for both hcp and fcc phase the faster the cooling rate is the more imperfect they are, which may be considered as the precursor of glass-forming.

Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands.

Abstract: Accurately predicting absolute binding free energies of protein-ligand complexes is important as a fundamental problem in both computational biophysics and pharmaceutical discovery. Calculating binding free energies for charged ligands is generally considered to be challenging because of the strong electrostatic interactions between the ligand and its environment in aqueous solution. In this work, we compare the performance of the potential of mean force (PMF) method and the double decoupling method (DDM) for computing absolute binding free energies for charged ligands. We first clarify an unresolved issue concerning the explicit use of the binding site volume to define the complexed state in DDM together with the use of harmonic restraints. We also provide an alternative derivation for the formula for absolute binding free energy using the PMF approach. We use these formulas to compute the binding free energy of charged ligands at an allosteric site of HIV-1 integrase, which has emerged in recent years as a promising target for developing antiviral therapy. As compared with the experimental results, the absolute binding free energies obtained by using the PMF approach show unsigned errors of 1.5-3.4 kcal mol-1, which are somewhat better than the results from DDM (unsigned errors of 1.6-4.3 kcal mol-1) using the same amount of CPU time. According to the DDM decomposition of the binding free energy, the ligand binding appears to be dominated by nonpolar interactions despite the presence of very large and favorable intermolecular ligand-receptor electrostatic interactions, which are almost completely cancelled out by the equally large free energy cost of desolvation of the charged moiety of the ligands in solution. We discuss the relative strengths of computing absolute binding free energies using the alchemical and physical pathway methods.

Simulating Replica Exchange: Markov State Models, Proposal Schemes, and the Infinite Swapping Limit.

Abstract: Replica exchange molecular dynamics is a multicanonical simulation technique commonly used to enhance the sampling of solvated biomolecules on rugged free energy landscapes. While replica exchange is relatively easy to implement, there are many unanswered questions about how to use this technique most efficiently, especially because it is frequently the case in practice that replica exchange simulations are not fully converged. A replica exchange cycle consists of a series of molecular dynamics steps of a set of replicas moving under different Hamiltonians or at different thermodynamic states followed by one or more replica exchange attempts to swap replicas among the different states. How the replica exchange cycle is constructed affects how rapidly the system equilibrates. We have constructed a Markov state model of replica exchange (MSMRE) using long molecular dynamics simulations of a host–guest binding system as an example, in order to study how different implementations of the replica exchange cycle...

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models.

Abstract: Markov (state) models (MSMs) and related models of molecular kinetics have recently received a surge of interest as they can systematically reconcile simulation data from either a few long or many short simulations and allow us to analyze the essential metastable structures, thermodynamics, and kinetics of the molecular system under investigation. However, the estimation, validation, and analysis of such models is far from trivial and involves sophisticated and often numerically sensitive methods. In this work we present the open-source Python package PyEMMA (http://pyemma.org) that provides accurate and efficient algorithms for kinetic model construction. PyEMMA can read all common molecular dynamics data formats, helps in the selection of input features, provides easy access to dimension reduction algorithms such as principal component analysis (PCA) and time-lagged independent component analysis (TICA) and clustering algorithms such as k-means, and contains estimators for MSMs, hidden Markov models, an...

Interenzyme Substrate Diffusion for an Enzyme Cascade Organized on Spatially Addressable DNA Nanostructures

Abstract: Spatially addressable DNA nanostructures facilitate the self-assembly of heterogeneous elements with precisely controlled patterns. Here we organized discrete glucose oxidase (GOx)/horseradish peroxidase (HRP) enzyme pairs on specific DNA origami tiles with controlled interenzyme spacing and position. The distance between enzymes was systematically varied from 10 to 65 nm, and the corresponding activities were evaluated. The study revealed two different distance-dependent kinetic processes associated with the assembled enzyme pairs. Strongly enhanced activity was observed for those assemblies in which the enzymes were closely spaced, while the activity dropped dramatically for enzymes as little as 20 nm apart. Increasing the spacing further resulted in a much weaker distance dependence. Combined with diffusion modeling, the results suggest that Brownian diffusion of intermediates in solution governed the variations in activity for more distant enzyme pairs, while dimensionally limited diffusion of interme...

Statistical physics approach to understanding the multiscale dynamics of earthquake fault systems

Abstract: [1] Earthquakes and the faults upon which they occur interact over a wide range of spatial and temporal scales. In addition, many aspects of regional seismicity appear to be stochastic both in space and time. However, within this complexity, there is considerable self-organization. We argue that the occurrence of earthquakes is a problem that can be attacked using the fundamentals of statistical physics. Concepts of statistical physics associated with phase changes and critical points have been successfully applied to a variety of cellular automata models. Examples include sandpile models, forest fire models, and, particularly, slider block models. These models exhibit avalanche behavior very similar to observed seismicity. A fundamental question is whether variations in seismicity can be used to successfully forecast the occurrence of earthquakes. Several attempts have been made to utilize precursory seismic activation and quiescence to make earthquake forecasts, some of which show promise.