Center for Computational Chemistry

Shanghai, China

Center for Computational Chemistry

Shanghai, China
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Ozer G.,New York University | Luque A.,New York University | Luque A.,San Diego State University | Schlick T.,New York University | And 2 more authors.
Current Opinion in Structural Biology | Year: 2015

The structure of chromatin, affected by many factors from DNA linker lengths to posttranslational modifications, is crucial to the regulation of eukaryotic cells. Combined experimental and computational methods have led to new insights into its structural and dynamical features, from interactions due to the flexible core histone tails or linker histones to the physical mechanism driving the formation of chromosomal domains. Here we present a perspective of recent advances in chromatin modeling techniques at the atomic, mesoscopic, and chromosomal scales with a view toward developing multiscale computational strategies to integrate such findings. Innovative modeling methods that connect molecular to chromosomal scales are crucial for interpreting experiments and eventually deciphering the complex dynamic organization and function of chromatin in the cell. © 2015 Elsevier Ltd.


Brkljaca Z.,Institute for Theoretical Physics | Klimczak M.,Crystallography and Structural Physics | Milicevic Z.,Institute for Theoretical Physics | Weisser M.,Crystallography and Structural Physics | And 7 more authors.
Journal of Physical Chemistry Letters | Year: 2015

Understanding the molecular-level behavior of ionic liquids (ILs) at IL-solid interfaces is of fundamental importance with respect to their application in, for example, electrochemical systems and electronic devices. Using a model system, consisting of an imidazolium-based IL ([C2Mim][NTf2]) in contact with a sapphire substrate, we have approached this problem using a complementary combination of high-resolution X-ray reflectivity measurements and atomistic molecular dynamics (MD) simulations. Our strategy enabled us to compare experimental and theoretically calculated reflectivities in a direct manner, thereby critically assessing the applicability of several force-field variants. On the other hand, using the best-matching MD description, we are able to describe the nature of the model IL-solid interface in appreciable detail. More speci fically, we find that characteristic interactions between the surface hydroxyl groups and donor and acceptor sites on the IL constituents have a dominant role in inducing a multidimensional layering profile of the cations and anions. (Graph Presented). © 2015 American Chemical Society.


Konig G.,U.S. National Institutes of Health | Mei Y.,East China Normal University | Mei Y.,Center for Computational Chemistry | Pickard F.C.,U.S. National Institutes of Health | And 6 more authors.
Journal of Chemical Theory and Computation | Year: 2016

A recently developed MESS-E-QM/MM method (multiple-environment single-system quantum mechanical molecular/mechanical calculations with a Roothaan-step extrapolation) is applied to the computation of hydration free energies for the blind SAMPL4 test set and for 12 small molecules. First, free energy simulations are performed with a classical molecular mechanics force field using fixed-geometry solute molecules and explicit TIP3P solvent, and then the non-Boltzmann-Bennett method is employed to compute the QM/MM correction (QM/MM-NBB) to the molecular mechanical hydration free energies. For the SAMPL4 set, MESS-E-QM/MM-NBB corrections to the hydration free energy can be obtained 2 or 3 orders of magnitude faster than fully converged QM/MM-NBB corrections, and, on average, the hydration free energies predicted with MESS-E-QM/MM-NBB fall within 0.10-0.20 kcal/mol of full-converged QM/MM-NBB results. Out of five density functionals (BLYP, B3LYP, PBE0, M06-2X, and ωB97X-D), the BLYP functional is found to be most compatible with the TIP3P solvent model and yields the most accurate hydration free energies against experimental values for solute molecules included in this study. © 2015 American Chemical Society.


Zhou Y.,Nanjing University | Xie D.,Nanjing University | Zhang Y.,New York University | Zhang Y.,Center for Computational Chemistry
Journal of Physical Chemistry Letters | Year: 2016

Cystine-knot peptides have remarkable stability against protease degradation and are attractive scaffolds for peptide-based therapeutic and diagnostic agents. In this work, by studying the hydrolysis reaction of a cystine-knot inhibitor MCTI-A and its variants with ab initio QM/MM molecular dynamics simulations, we have elucidated an amide rotation hindrance mechanism for proteolysis resistance: The proteolysis of MCTI-A is retarded due to the higher free energy cost during the rotation of NH group around scissile peptide bond at the tetrahedral intermediate of acylation, and covalent constraint provided by disulfide bonds is the key factor to hinder this rotation. A nearly linear correlation has been revealed between free energy barriers of the peptide hydrolysis reaction and the amide rotation free energy changes at the protease-peptide Michaelis complex state. This suggests that amide rotation hindrance could be one useful feature to estimate peptide proteolysis stability. © 2016 American Chemical Society.


Li M.,East China Normal University | Zhang J.Z.,East China Normal University | Zhang J.Z.,Center for Computational Chemistry | Xia F.,East China Normal University | Xia F.,Center for Computational Chemistry
Journal of Chemical Theory and Computation | Year: 2016

Coarse-grained (CG) models are valuable tools for the study of functions of large biomolecules on large length and time scales. The definition of CG representations for huge biomolecules is always a formidable challenge. In this work, we propose a new method called fluctuation maximization coarse-graining (FM-CG) to construct the CG sites of biomolecules. The defined residual in FM-CG converges to a maximal value as the number of CG sites increases, allowing an optimal CG model to be rigorously defined on the basis of the maximum. More importantly, we developed a robust algorithm called stepwise local iterative optimization (SLIO) to accelerate the process of coarse-graining large biomolecules. By means of the efficient SLIO algorithm, the computational cost of coarse-graining large biomolecules is reduced to within the time scale of seconds, which is far lower than that of conventional simulated annealing. The coarse-graining of two huge systems, chaperonin GroEL and lengsin, indicates that our new methods can coarse-grain huge biomolecular systems with up to 10 000 residues within the time scale of minutes. The further parametrization of CG sites derived from FM-CG allows us to construct the corresponding CG models for studies of the functions of huge biomolecular systems. © 2016 American Chemical Society.


He X.,East China Normal University | He X.,Center for Computational Chemistry | Zhu T.,East China Normal University | Wang X.,East China Normal University | And 3 more authors.
Accounts of Chemical Research | Year: 2014

ConspectusThe desire to study molecular systems that are much larger than what the current state-of-the-art ab initio or density functional theory methods could handle has naturally led to the development of novel approximate methods, including semiempirical approaches, reduced-scaling methods, and fragmentation methods. The major computational limitation of ab initio methods is the scaling problem, because the cost of ab initio calculation scales nth power or worse with system size. In the past decade, the fragmentation approach based on chemical locality has opened a new door for developing linear-scaling quantum mechanical (QM) methods for large systems and for applications to large molecular systems such as biomolecules. The fragmentation approach is highly attractive from a computational standpoint. First, the ab initio calculation of individual fragments can be conducted almost independently, which makes it suitable for massively parallel computations. Second, the electron properties, such as density and energy, are typically combined in a linear fashion to reproduce those for the entire molecular system, which makes the overall computation scale linearly with the size of the system.In this Account, two fragmentation methods and their applications to macromolecules are described. They are the electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method and the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach. The EE-GMFCC method is developed from the MFCC approach, which was initially used to obtain accurate protein-ligand QM interaction energies. The main idea of the MFCC approach is that a pair of conjugate caps (concaps) is inserted at the location where the subsystem is divided by cutting the chemical bond. In addition, the pair of concaps is fused to form molecular species such that the overcounted effect from added concaps can be properly removed. By introducing the electrostatic embedding field in each fragment calculation and two-body interaction energy correction on top of the MFCC approach, the EE-GMFCC method is capable of accurately reproducing the QM molecular properties (such as the dipole moment, electron density, and electrostatic potential), the total energy, and the electrostatic solvation energy from full system calculations for proteins.On the other hand, the AF-QM/MM method was used for the efficient QM calculation of protein nuclear magnetic resonance (NMR) parameters, including the chemical shift, chemical shift anisotropy tensor, and spin-spin coupling constant. In the AF-QM/MM approach, each amino acid and all the residues in its vicinity are automatically assigned as the QM region through a distance cutoff for each residue-centric QM/MM calculation. Local chemical properties of the central residue can be obtained from individual QM/MM calculations. The AF-QM/MM approach precisely reproduces the NMR chemical shifts of proteins in the gas phase from full system QM calculations. Furthermore, via the incorporation of implicit and explicit solvent models, the protein NMR chemical shifts calculated by the AF-QM/MM method are in excellent agreement with experimental values. The applications of the AF-QM/MM method may also be extended to more general biological systems such as DNA/RNA and protein-ligand complexes. © 2014 American Chemical Society.


Ji C.,East China Normal University | Ji C.,Center for Computational Chemistry | Mei Y.,East China Normal University | Mei Y.,Center for Computational Chemistry
Accounts of Chemical Research | Year: 2014

ConspectusElectrostatic interaction plays a significant role in determining many properties of biomolecules, which exist and function in aqueous solution, a highly polar environment. For example, proteins are composed of amino acids with charged, polar, and nonpolar side chains and their specific electrostatic properties are fundamental to the structure and function of proteins. An important issue that arises in computational study of biomolecular interaction and dynamics based on classical force field is lack of polarization. Polarization is a phenomenon in which the charge distribution of an isolated molecule will be distorted when interacting with another molecule or presented in an external electric field. The distortion of charge distribution is intended to lower the overall energy of the molecular system, which is counter balanced by the increased internal energy of individual molecules due to the distorted charge distributions. The amount of the charge redistribution, which characterizes the polarizability of a molecule, is determined by the level of the charge distortion.Polarization is inherently quantum mechanical, and therefore classical force fields with fixed atomic charges are incapable of capturing this important effect. As a result, simulation studies based on popular force fields, AMBER, CHARMM, etc., lack the polarization effect, which is a widely known deficiency in most computational studies of biomolecules today. Many efforts have been devoted to remedy this deficiency, such as adding additional movable charge on the atom, allowing atomic charges to fluctuate, or including induced multipoles. Although various successes have been achieved and progress at various levels has been reported over the past decades, the issue of lacking polarization in force field based simulations is far from over. For example, some of these methods do not always give converged results, and other methods require huge computational cost.This Account reviews recent work on developing polarized and polarizable force fields based on fragment quantum mechanical calculations for proteins. The methods described here are based on quantum mechanical calculations of proteins in solution, but with a different level of rigor and different computational efficiency for the molecular dynamics applications. In the general approach, a fragment quantum mechanical calculation for protein with implicit solvation is carried out to derive a polarized protein-specific charge (PPC) for any given protein structure. The PPC correctly reflects the polarization state of the protein in a given conformation, and it can also be dynamically changed as the protein changes conformation in dynamics simulations. Another approach that is computationally more efficient is the effective polarizable bond method in which only polar bonds or groups can be polarized and their polarizabilities are predetermined from quantum mechanical calculations of these groups in external electric fields. Both methods can be employed for applications in various situations by taking advantage of their unique features. © 2014 American Chemical Society.


Mu H.,New York University | Geacintov N.E.,New York University | Zhang Y.,New York University | Zhang Y.,Center for Computational Chemistry | Broyde S.,New York University
Biochemistry | Year: 2015

Mammalian global genomic nucleotide excision repair requires lesion recognition by XPC, whose detailed binding mechanism remains to be elucidated. Here we have delineated the dynamic molecular pathway and energetics of lesion-specific and productive binding by the Rad4/yeast XPC lesion recognition factor, as it forms the open complex [Min, J. H., and Pavletich, N. P. (2007) Nature 449, 570-575; Chen, X., et al. (2015) Nat. Commun. 6, 5849] that is required for excision. We investigated extensively a cis-syn cyclobutane pyrimidine dimer in mismatched duplex DNA, using high-level computational approaches. Our results delineate a preferred correlated motion mechanism, which provides for the first time an atomistic description of the sequence of events as Rad4 productively binds to the damaged DNA. (Figure Presented). © 2015 American Chemical Society.


Xiao X.,New York University | Kallenbach N.,New York University | Zhang Y.,New York University | Zhang Y.,Center for Computational Chemistry
Journal of Chemical Theory and Computation | Year: 2014

Unlike native proteins that are amenable to structural analysis at atomic resolution, unfolded proteins occupy a manifold of dynamically interconverting structures. Defining the conformations of unfolded proteins is of significant interest and importance, for folding studies and for understanding the properties of intrinsically disordered proteins. Short chain protein fragments, i.e., oligopeptides, provide an excellent test-bed in efforts to define the conformational ensemble of unfolded chains. Oligomers of alanine in particular have been extensively studied as minimalist models of the intrinsic conformational preferences of the peptide backbone. Even short alanine peptides occupy an ensemble of substates that are distinguished by small free energy differences, so that the problem of quantifying the conformational preferences of the backbone remains a fundamental challenge in protein biophysics. Here, we demonstrate an integrated computational-experimental-Bayesian approach to quantify the conformational ensembles of the model trialanine peptide in water. In this approach, peptide conformational substates are first determined objectively by clustering molecular dynamics snapshots based on both structural and dynamic information. Next, a set of spectroscopic data for each conformational substate is computed. Finally, a Bayesian statistical analysis of both experimentally measured spectroscopic data and computational results is carried out to provide a current best estimate of the substate population ensemble together with corresponding confidence intervals. This distribution of substates can be further systematically refined with additional high-quality experimental data and more accurate computational modeling. Using an experimental data set of NMR coupling constants, we have also applied this approach to characterize the conformation ensemble of trivaline in water. © 2014 American Chemical Society.


Xu M.,New York University | Ye S.,New York University | Bacic Z.,New York University | Bacic Z.,Center for Computational Chemistry
Journal of Physical Chemistry Letters | Year: 2015

Knowledge of the relevant selection rules is crucial for the accurate interpretation of experimental spectra in general. There has been a consensus for a long time that the incoherent inelastic neutron scattering (INS) spectroscopy of the vibrations of discrete molecular compunds is free from any selection rules. We contradict this widely held view by presenting an analytical derivation of the general selection rule for the INS spectroscopy of a hydrogen molecule inside a near-spherical nanocavity. It defines all forbidden transitions, originating in a range of initial translation-rotation (TR) states, ground and excited, of the caged para- and ortho-H2, as well as HD, that are unobservable in the INS spectra. These predictions are amenable to experimental verification. In addition, we demonstrate that the general selection rule applies to the INS spectroscopy of any diatomic molecule in a nanocavity with near-spherical symmetry, which exhibits strong TR coupling. Its existence strongly suggests that similar selection rules apply to the INS spectra of other molecular and supramolecular systems, and need to be identified. © 2015 American Chemical Society.

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