Publications

351.

Wang, M., Mei, Y., and Ryde, U. Host-guest relative binding affinities at density-functional theory level from semiempirical molecular dynamics simulations. J. Chem. Theory Comput. 15, 2659-2671 (2019)

352.

Han, Y., Liu, J., Huang, L., He, X., and Li, J. Predicting the phase diagram of solid carbon dioxide at high pressure from first principles. npj Quantum Materials. 4, 10 (2019)

353.

Verma, P., Janesko, B. G., Wang, Y., He, X., Scalmani, G., Frisch, M. J., and Truhlar, D. G. M11plus: A range-separated hybrid meta functional with both local and rung-3.5 correlation terms and high across-the-board accuracy for chemical applications. J. Chem. Theory Comput. 15, 4804-4815 (2019)

354.

Liu, J., Sun, H., Glover, W. J., and He, X. Prediction of excited-state properties of oligoacene crystals using fragment-based quantum mechanical method. J. Phys. Chem. A. 123, 5407-5417 (2019)

355.

Lu, Q., He, X., Hu, W., Chen, X., and Liu, J. Stability, vibrations, and diffusion of hydrogen gas in clathrate hydrates: Insights from ab initio calculations on condensed-phase crystalline structures. J. Phys. Chem. C. 123, 12052-12061 (2019)

356.

Verma, P., Wang, Y., Ghosh, S., He, X., and Truhlar, D. G. Revised M11 exchange-correlation functional for electronic excitation energies and ground-state properties. J. Phys. Chem. A. 123, 2966-2990 (2019)

357.

Luo, H., Hao, X., Gong, Y., Zhou, J., He, X., and Li, J. Rational crystal polymorph design of olanzapine. Cryst. Growth Des. 19, 2388-2395 (2019)

358.

Tuckerman, M. E. Machine learning transforms how microstates are sampled. Science. 365, 982-983 (2019)

359.

Zelovich, T., Vogt-Maranto, L., Hickner, M. A., Paddison, S. J., Bae, C., Dekel, D. R., and Tuckerman, M. E. Hydroxide ion diffusion in anion-exchange membranes at low hydration: Insights from ab initio molecular dynamics. Chem. Mater. 31, 5778-5787 (2019)

360.

Shtukenberg, A. G., Tan, M., Vogt-Maranto, L., Chan, E. J., Xu, W., Yang, J., Tuckerman, M. E., Hu, C. T., and Kahr, B. Melt crystallization for paracetamol polymorphism. Cryst. Growth Des. 19, 4070-4080 (2019)

361.

Zhang, Z., Liu, X., Yan, K., Tuckerman, M. E., and Liu, J. Unified efficient thermostat scheme for the canonical ensemble with holonomic or isokinetic constraints via molecular dynamics. J. Phys. Chem. A. 123, 6056-6079 (2019)

362.

Zhang, Y., Xia, K., Cao, Z., Gräter, F., and Xia, F. A new method for the construction of coarse-grained models of large biomolecules from low-resolution cryo-electron microscopy data. Phys. Chem. Chem. Phys. 21, 9720-9727 (2019)

363.

Zhang, L., Mei, D., Wu, Y., Shen, C., Hu, W., Zhang, L., Li, J., Wu, Y., and He, X. Syntheses, structures, optical properties, and electronic structures of Ba6Cu2GSn4S16 (G= Fe, Ni) and Sr6D2FeSn4S16 (D= Cu, Ag). J. Solid State Chem. 272, 69-77 (2019)

364.

He, L., Bao, J., Yang, Y., Dong, S., Zhang, L., Qi, Y., and Zhang, J. Z. H. Study of SHMT2 inhibitors and their binding mechanism by computational alanine scanning. J. Chem. Inf. Model. 59, 3871-3878 (2019)

365.

Lu, J., Wang, C., and Zhang, Y. Predicting molecular energy using force-field optimized geometries and atomic vector representations learned from an improved deep tensor neural network. J. Chem. Theory Comput. 15, 4113-4121 (2019)

366.

Li, K., Hou, X., Li, R., Bi, W., Yang, F., Chen, X., Xiao, P., Liu, T., Lu, T., Zhou, Y., Tian, Z., Shen, Y., Zhang, Y., Wang, J., Fang, H., Sun, J., and Yu, X. Identification and structure-function analyses of an allosteric inhibitor of the tyrosine phosphatase PTPN22. J. Biol. Chem. 294, 8653-8663 (2019)

367.

Sun, X. Hybrid equilibrium-nonequilibrium molecular dynamics approach for two-dimensional solute-pump/solvent-probe spectroscopyJ. Chem. Phys. 151, 194507 (2019)

368.

Wang, T., Su, X., Zhang, X., Nie, X., Huang, L., Zhang, X., Sun, X., Luo, Y., and Zhang, G. Aggregation-induced dual-phosphorescence from organic molecules for non-doped light-emitting diodesAdv. Mater. 31, 1904273 (2019)

369.

Glover, W. J., Paz, A. S. P., Thongyod, W., and Punwong, C. Analytical gradients and derivative couplings for dynamically weighted complete active space self-consistent fieldJ. Chem. Phys. 151, 201101 (2019)

370.

Yang, Y., Lu, J., Yang, C., and Zhang, Y. Exploring fragment-based target specific ranking protocol with machine learning on cathepsin S. J. Comput. Aided Mol. Des. 33, 1095-1105 (2019)

371.

Lu, J., Hou, X., Wang, C., and Zhang Y. Incorporating explicit water molecules and ligand conformation stability in machine-learning scoring functions. J. Chem. Inf. Model. 59, 4540-4549 (2019)

372.

Marsiglia, W., Katigbak, J., Zheng, S., Mohammadi, M., Zhang, Y., and Traaseth N. A conserved allosteric pathway in tyrosine kinase regulation. Structure. 27, 1308-1315.e3 (2019)

373.

Rogal, J., Schneider, E., and Tuckerman, M. E. Neural-network-based path collective variables for enhanced sampling of phase transformationsPhys. Rev. Lett. 123, 245701 (2019)

374.

Wu, Z., Zhang, Y., Zhang, J. Z., Xia, K., and Xia, F. Determining optimal coarse-grained representation for biomolecules using internal cluster validation indexesJ. Comput. Chem. 41, 14-20 (2019)

375.

Shao, Y., Mei, Y., Sundholm, D., and Kaila, V. R. I. Benchmarking the performance of time-dependent density functional theory methods on biochromophoresJ. Chem. Theory Comput. 16, 587-600 (2019)

376.

Mao, J., Aladin, V., Jin, X., Leeder, A. J., Brown, L. J., Brown, R. C. D., He, X., Corzilius, B., and Glaubitz, C. Exploring protein structures by DNP-enhanced methyl solid-state NMR spectroscopy. J. Am. Chem. Soc. 141, 19888-19901 (2019)

377.

Petkov, B. K., Gellen, T. A., Farfan, C. A., Carbery, W. P., Hetzler, B. E., Trauner, D., Li, X., Glover, W. J., Ulness, D. J., and Turner, D. B. Two-dimensional electronic spectroscopy reveals the spectral dynamics of Förster resonance energy transferChem. 5, 1928-1929 (2019)

378.

Yang, H., Zhang, F., Huang, C.-J., Liao, J., Han, Y., Hao, P., Chu, Y., Lu, X., Li, W., Yu, H., and Kang, J. Mps1 regulates spindle morphology through MCRS1 to promote chromosome alignment. Mol. Biol. Cell. 30, 1051-1128 (2019)

379.

Chin, C.-H., Zhu, T., and Zhang, J. Z. H. Formation mechanism and spectroscopy of C6H radicals in extreme environments: a theoretical study. Phys. Chem. Chem. Phys. 21, 23044-23055 (2019)

380.

Tian, S., Zeng, J., Liu, X., Chen, J., Zhang, J. Z. H., and Zhu, T. Understanding the selectivity of inhibitors toward PI4KIIIα and PI4KIIIβ based molecular modeling. Phys. Chem. Chem. Phys. 21, 22103-22112 (2019)

381.

Luo, H., Liu, J., He, X., and Li, J. Low-temperature polymorphic transformation of β-lactam antibiotics. Crystals. 9, 460 (2019)

382.

Hagras, M. A. and Glover, W. J. Polarizable embedding for excited-state reactions: Dynamically weighted polarizable QM/MM. J. Chem. Theory Comput. 14, 2137-2144 (2018)

383.

Glover, W. J., Mori, T., Schuurman, M. S., Boguslavskiy, A. E., Schalk, O., Stolow, A., and Martínez, T. J. Excited state non-adiabatic dynamics of the smallest polyene, trans 1,3-butadiene. II. Ab initio multiple spawning simulations. J. Chem. Phys. 148, 164303 (2018)

384.

Song, J., Qiu, L., and Zhang, J. Z. H. An efficient method for computing excess free energy of liquidScience China Chemistry, 61, 135-140 (2018)  

385.

Liu, J., He, X., Zhang, J. Z. H., and Qi, L.-W. Hydrogen-bond structure dynamics in bulk water: Insights from ab initio simulations with coupled cluster theory. Chem. Sci. 9, 2065-2073 (2018)

386.

Chen, P.-Y., and Tuckerman, M. E. Molecular dynamics based enhanced sampling of collective variables with very large time stepsJ. Chem. Phys. 148, 024106 (2018)

387.

Cendagorta, J. R., Bačić, Z., and Tuckerman, M. E. An open-chain imaginary-time path-integral sampling approach to the calculation of approximate symmetrized quantum time correlation functionsJ. Chem. Phys. 148, 102340 (2018)

388.

Tuckerman M. and Ceperley, D. Preface: Special topic on nuclear quantum effectsJ. Chem. Phys. 148, 102001 (2018) 

389.

Powers, A., Scribano, Y., Lauvergnat, D., Mebe, E., Benoit, D. M., and Bačić, Z. The effect of the condensed-phase environment on the vibrational frequency shift of a hydrogen molecule inside clathrate hydrates. J. Chem. Phys. 148, 144304 (2018)

390.

Bačić, Z., Xu, M., and Felker, P. M. Coupled translation-rotation dynamics of H2 and H2O inside C60: Rigorous quantum treatment. Adv. Chem. Phys. 163, 195-216 (2018)

391.

Jin, X., Zhu, T., Zhang, J. Z. H., and He, X. Automated fragmentation QM/MM calculation of NMR chemical shifts for protein-ligand complexes. Front. Chem. 6, 150 (2018)

392.

Wang, P., Liu, L., Luo, Z., Zhou, Q., Lu, Y., Xia, F., and Liu, Y. Combination of transition metal Rh-catalysis and tautomeric catalysis through a bi-functional ligand for one-pot tandem methoxycarbonylation-aminolysis of olefins towards primary amides. J. Catal. 361, 230-237 (2018)

393.

Wang, J., Cao, H., Zhang, J. Z. H., and Qi, Y. Computational protein design with deep learning neural networks. Sci. Rep. 8, 6349 (2018)

394.

Li, Y., Zhang, Y., Großerüschkamp, F., Stephan, S., Cui, Q., Kötting, C., Xia, F., and Gerwert, K. Specific substates of Ras to interact with GAPs and effectors: Revealed by theoretical simulations and FTIR experiments. J. Phys. Chem. Lett. 9, 1312-1317 (2018)

395.

Liu, X., Peng, L., Zhou, Y., Zhang, Y, and Zhang, J. Z. H. Computational alanine scanning with interaction entropy for protein–ligand binding free energies. J. Chem. Theory Comput. 14, 1772-1780 (2018)

396.

Qiu, L., Yan, Y., Sun, Z., Song, J., and Zhang, J. Z. H. Interaction entropy for computational alanine scanning in protein–protein binding. Wiley Interdiscip. Rev. Comput. Mol. Sci. 8, e1342 (2018)

397.

Liu, J., Swails, J., Zhang, J. Z. H., He, X., and Roitberg, A. E. A coupled ionization-conformational equilibrium is required to understand the properties of ionizable residues in the hydrophobic interior of staphylococcal nuclease. J. Am. Chem. Soc. 140, 1639–1648 (2018)

398.

Ji, L., Luo, Z., Zhang, Y., Wang, R., Ji, Y., Xia, F., Gao, G. Imidazolium ionic liquids/organic bases: Efficient intermolecular synergistic catalysts for the cycloaddition of  CO and epoxides under atmospheric pressure. Molecular Catalysis. 446, 124-130 (2018)

399.

Wang, X., Tu, X., Zhang, J. Z. H., and Sun, Z. BAR-based optimum adaptive sampling regime for variance minimization in alchemical transformation: the nonequilibrium stratification. Phys. Chem. Chem. Phys. 20, 2009-2021 (2018)

400.

Gao, B., Jiang, S., Wang, L., Zhang, L., Wei, D. Energy and conformation determine the enantioselectivity of enzyme. Biochem. Eng. J. 129, 106-112 (2018)

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