Zhe Wu

Bio: Zhe Wu is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Lipid bilayer & Peripheral membrane protein. The author has an hindex of 13, co-authored 16 publications receiving 960 citations. Previous affiliations of Zhe Wu include University of Wisconsin-Madison.

A new coarse-grained model for water: the importance of electrostatic interactions.

Abstract: A new coarse-grained (CG) model is developed for water. Each CG unit consists of three charged sites, and there is an additional nonelectrostatic soft interaction between central sites on different units. The interactions are chosen to mimic the properties of 4-water clusters in atomistic simulations: the nonelectrostatic component is modeled using a modified Born−Mayer−Huggins potential, and the charges are chosen to reproduce the dipole moment and quadrupole moment tensor of 4-water clusters from atomistic simulations. The parameters are optimized to reproduce experimental data for the compressibility, density, and permittivity of bulk water and the surface tension and interface potential for the air−water interface. This big multipole water (BMW) model represents a qualitative improvement over existing CG water models; for example, it reproduces the dipole potential in membrane−water interface when compared to experiment, with modest additional computational cost as compared to the popular MARTINI CG m...

Self-diffusion and viscosity in electrolyte solutions.

Abstract: The effect of salt on the dynamics of water molecules follows the Hofmeister series. For some “structure-making” salts, the self-diffusion coefficient of the water molecules, D, decreases with increasing salt concentration. For other “structure-breaking” salts, D increases with increasing salt concentration. In this work, the concentration and temperature dependence of the self-diffusion of water in electrolyte solutions is studied using molecular dynamics simulations and pulsed-field-gradient NMR experiments; temperature-dependent viscosities are also independently measured. Simulations of rigid, nonpolarizable models at room temperature show that none of the many models tested can reproduce the experimentally observed trend for the concentration dependence of D; that is, the models predict that D decreases with increasing salt concentration for both structure-breaking and structure-making salts. Predictions of polarizable models are not in agreement with experiment either. These results suggest that man...

A New Coarse-Grained Force Field for Membrane-Peptide Simulations.

Abstract: We present a new coarse-grained (CG) model for simulations of lipids and peptides. The model follows the same topology and parametrization strategy as the MARTINI force field but is based on our recently developed big multipole water (BMW) model for water (J. Phys. Chem. B2010, 114, 10524–10529). The new BMW-MARTINI force field reproduces many fundamental membrane properties and also yields improved energetics (when compared to the original MARTINI force-field) for the interactions between charged amino acids with lipid membranes, especially at the membrane–water interface. A stable attachment of cationic peptides (e.g., Arg8) to the membrane surface is predicted, consistent with experiment and in contrast to the MARTINI model. The model predicts electroporation when there is a charge imbalance across the lipid bilayer, an improvement over the original MARTINI. Moreover, the pore formed during electroporation is toroidal in nature, similar to the prediction of atomistic simulations but distinct from resul...

Why do arginine and lysine organize lipids differently? Insights from coarse-grained and atomistic simulations.

Abstract: An important puzzle in membrane biophysics is the difference in the behaviors of lysine (Lys) and arginine (Arg) based peptides at the membrane. For example, the translocation of poly-Arg is orders of magnitude faster than that of poly-Lys. Recent experimental work suggests that much of the difference can be inferred from the phase behavior of peptide/lipid mixtures. At similar concentrations, mixtures of phosphatidylethanolamine (PE) and phosphatidylserine (PS) lipids display different phases in the presence of these polypeptides, with a bicontinuous phase observed with poly-Arg peptides and an inverted hexagonal phase observed with poly-Lys peptides. Here we show that simulations with the coarse-grained (CG) BMW-MARTINI model reproduce the experimental results. An analysis using atomistic and CG models reveals that electrostatic and glycerol–peptide interactions play a crucial role in determining the phase behavior of peptide–lipid mixtures, with the difference between Arg and Lys arising from the stron...

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Scalable molecular dynamics on CPU and GPU architectures with NAMD.

Abstract: NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Improved Parameters for the Martini Coarse-Grained Protein Force Field

Abstract: The Martini coarse-grained force field has been successfully used for simulating a wide range of (bio)molecular systems. Recent progress in our ability to test the model against fully atomistic force fields, however, has revealed some shortcomings. Most notable, phenylalanine and proline were too hydrophobic, and dimers formed by polar residues in apolar solvents did not bind strongly enough. Here, we reparametrize these residues either through reassignment of particle types or by introducing embedded charges. The new parameters are tested with respect to partitioning across a lipid bilayer, membrane binding of Wimley–White peptides, and dimerization free energy in solvents of different polarity. In addition, we improve some of the bonded terms in the Martini protein force field that lead to a more realistic length of α-helices and to improved numerical stability for polyalanine and glycine repeats. The new parameter set is denoted Martini version 2.2.

Perspective on the Martini model.

Abstract: The Martini model, a coarse-grained force field for biomolecular simulations, has found a broad range of applications since its release a decade ago. Based on a building block principle, the model combines speed and versatility while maintaining chemical specificity. Here we review the current state of the model. We describe recent highlights as well as shortcomings, and our ideas on the further development of the model.

Black Phosphorus Nanosheet‐Based Drug Delivery System for Synergistic Photodynamic/Photothermal/Chemotherapy of Cancer

Abstract: A black phosphorus (BP)-based drug delivery system for synergistic photodynamic/photothermal/chemotherapy of cancer is constructed. As a 2D nanosheet, BP shows super high drug loading capacity and pH-/photoresponsive drug release. The intrinsic photothermal and photodynamic effects of BP enhance the antitumor activities. The synergistic photodynamic/photothermal/chemotherapy makes BP-based drug delivery system a multifunctional nanomedicine platform.