Lee-Ping Wang

MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories

As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing MD simulations. MDTraj reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between MD data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. MDTraj is a powerful and user-friendly software package that simplifies the analysis of MD data and connects these datasets with the modern interactive data science software ecosystem in Python.

The Diabatic Picture of Electron Transfer, Reaction Barriers, and Molecular Dynamics

Diabatic states have a long history in chemistry, beginning with early valence bond pictures of molecular bonding and extending through the construction of model potential energy surfaces to the modern proliferation of methods for computing these elusive states. In this review, we summarize the basic principles that define the diabatic basis and demonstrate how they can be applied in the specific context of constrained density functional theory. Using illustrative examples from electron transfer and chemical reactions, we show how the diabatic picture can be used to extract qualitative insight and quantitative predictions about energy landscapes. The review closes with a brief summary of the challenges and prospects for the further application of diabatic states in chemistry.

Acid−Base Mechanism for Ruthenium Water Oxidation Catalysts

We present a detailed theoretical study of the pathway for water oxidation in synthetic ruthenium-based catalysts. As a first step, we consider a recently discovered single center catalyst, where experimental observations suggest a purely single-center mechanism. We find low activation energies (<5 kcal/mol) for each rearrangement in the catalytic cycle. In the crucial step of O-O bond formation, a solvent water acts as a Lewis base and attacks a highly oxidized Ru(V)=O. Armed with the structures and energetics of the single-center catalyst, we proceed to consider a representative Ru-dimer which was designed to form O(2) via coupling between the two centers. We discover a mechanism that proceeds in analogous fashion to the monomer case, with all the most significant steps occurring at a single catalytic center within the dimer. This acid-base mechanism suggests a new set of strategies for the rational design of multicenter catalysts: rather than coordinating the relative orientations of the subunits, one can focus on coordinating solvation-shell water molecules or tuning redox potentials.

Building Force Fields: An Automatic, Systematic, and Reproducible Approach

The development of accurate molecular mechanics force fields is a significant challenge that must be addressed for the continued success of molecular simulation. We developed the ForceBalance method to automatically derive accurate force field parameters using flexible combinations of experimental and theoretical reference data. The method is demonstrated in the parametrization of two rigid water models, yielding new parameter sets (TIP3P-FB and TIP4P-FB) that accurately describe many physical properties of water.

Discovering chemistry with an ab initio nanoreactor

Chemical understanding is driven by the experimental discovery of new compounds and reactivity, and is supported by theory and computation that provides detailed physical insight. While theoretical and computational studies have generally focused on specific processes or mechanistic hypotheses, recent methodological and computational advances harken the advent of their principal role in discovery. Here we report the development and application of the ab initio nanoreactor – a highly accelerated, first-principles molecular dynamics simulation of chemical reactions that discovers new molecules and mechanisms without preordained reaction coordinates or elementary steps. Using the nanoreactor we show new pathways for glycine synthesis from primitive compounds proposed to exist on the early Earth, providing new insight into the classic Urey-Miller experiment. These results highlight the emergence of theoretical and computational chemistry as a tool for discovery in addition to its traditional role of interpreting experimental findings.

Single-cell electroporation arrays with real-time monitoring and feedback control

Rapid well-controlled intracellular delivery of drug compounds, RNA, or DNA into a cell--without permanent damage to the cell--is a pervasive challenge in basic cell biology research, drug discovery, and gene delivery. To address this challenge, we have developed a bench-top system comprised of a control interface, that mates to disposable 96-well-formatted microfluidic devices, enabling the individual manipulation, electroporation and real-time monitoring of each cell in suspension. This is the first demonstrated real-time feedback-controlled electroporation of an array of single-cells. Our computer program automatically detects electroporation events and subsequently releases the electric field, precluding continued field-induced damage of the cell, to allow for membrane resealing. Using this novel set-up, we demonstrate the reliable electroporation of an array (n = 15) of individual cells in suspension, using low applied electric fields (<1 V) and the rapid and localized intracellular delivery of otherwise impermeable compounds (Calcein and Orange Green Dextran). Such multiplexed electrical and optical measurements as a function of time are not attainable with typical electroporation setups. This system, which mounts on an inverted microscope, obviates many issues typically associated with prototypical microfluidic chip setups and, more importantly, offers well-controlled and reproducible parallel pressure and electrical application to individual cells for repeatability.

Systematic Parametrization of Polarizable Force Fields from Quantum Chemistry Data

We introduce ForceBalance, a method and free software package for systematic force field optimization with the ability to parametrize a wide variety of functional forms using flexible combinations of reference data. We outline several important challenges in force field development and how they are addressed in ForceBalance, and present an example calculation where these methods are applied to develop a highly accurate polarizable water model. ForceBalance is available for free download at https://simtk.org/home/forcebalance.

Electronic properties of disordered organic semiconductors via QM/MM simulations.

Organic semiconductors (OSCs) have recently received significant attention for their potential use in photovoltaic, light emitting diode, and field effect transistor devices. Part of the appeal of OSCs is the disordered, amorphous nature of these materials, which makes them more flexible and easier to process than their inorganic counterparts. In addition to their technological applications, OSCs provide an attractive laboratory for examining the chemistry of heterogeneous systems. Because OSCs are both electrically and optically active, researchers have access to a wealth of electrical and spectroscopic probes that are sensitive to a variety of localized electronic states in these materials. In this Account, we review the basic concepts in first-principles modeling of the electronic properties of disordered OSCs. There are three theoretical ingredients in the computational recipe. First, Marcus theory of nonadiabatic electron transfer (ET) provides a direct link between energy and kinetics. Second, constrained density functional theory (CDFT) forms the basis for an ab initio model of the diabatic charge states required in ET. Finally, quantum mechanical/molecular mechanical (QM/MM) techniques allow us to incorporate the influence of the heterogeneous environment on the diabatic states. As an illustration, we apply these ideas to the small molecule OSC tris(8- hydroxyquinolinato)aluminum (Alq(3)). In films, Alq(3) can possess a large degree of short-range order, placing it in the middle of the order-disorder spectrum (in this spectrum, pure crystals represent one extreme and totally amorphous structures the opposite extreme). We show that the QM/MM recipe reproduces the transport gap, charge carrier hopping integrals, optical spectra, and reorganization energies of Alq(3) in quantitative agreement with available experiments. However, one cannot specify any of these quantities accurately with a single number. Instead, one must characterize each property by a distribution that reflects the influence of the heterogeneous environment on the electronic states involved. For example, the hopping integral between a given pair of Alq(3) molecules can vary by as much as a factor of 5 on the nanosecond timescale, but the integrals for two different pairs can easily differ by a factor of 100. To accurately predict mesoscopic properties such as carrier mobilities based on these calculations, researchers must account for the dynamic range of the microscopic inputs, rather than just their average values. Thus, we find that many of the computational tools required to characterize these materials are now available. As we continue to improve this computational toolbox, we envision a future scenario in which researchers can use basic information about OSC deposition to simulate device operation on the atomic scale. This type of simulation could allow researchers to obtain data that not only aids in the interpretation of experimental results but also guides the design of more efficient devices.

Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model

A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient, and dielectric constant. The viscosity, self-diffusion constant, and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2-20 water molecules, the AMOEBA14 model yields results similar to AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model.

What Can Density Functional Theory Tell Us about Artificial Catalytic Water Splitting

Water splitting by artificial catalysts is a critical process in the production of hydrogen gas as an alternative fuel. In this paper, we examine the essential role of theoretical calculations, with particular focus on density functional theory (DFT), in understanding the water-splitting reaction on these catalysts. First, we present an overview of DFT thermochemical calculations on water-splitting catalysts, addressing how these calculations are adapted to condensed phases and room temperature. We show how DFT-derived chemical descriptors of reactivity can be surprisingly good estimators for reactive trends in water-splitting catalysts. Using this concept, we recover trends for bulk catalysts using simple model complexes for at least the first-row transition-metal oxides. Then, using the CoPi cobalt oxide catalyst as a case study, we examine the usefulness of simulation for predicting the kinetics of water splitting. We demonstrate that the appropriate treatment of solvent effects is critical for computing accurate redox potentials with DFT, which, in turn, determine the rate-limiting steps and electrochemical overpotentials. Finally, we examine the ability of DFT to predict mechanism, using ruthenium complexes as a focal point for discussion. Our discussion is intended to provide an overview of the current strengths and weaknesses of the state-of-the-art DFT methodologies for condensed-phase molecular simulation involving transition metals and also to guide future experiments and computations toward the understanding and development of novel water-splitting catalysts.