Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.

Consider a system with an arbitrary constraint on its electron density (e.g. that there are N charges on an acceptor group). We show that the minimum energy state consistent with the constraint is actually a maximum with respect to the constraint potential, and that this solution is unique. This leads us to an efficient algorithm for performing Kohn-Sham density functional theory calculations on constrained systems. Illustrative studies are shown for charge transfer in: the zincbacteriochlorin-bacteriochlorin complex, polyene and alkane chains, and stretched H2.

The ability to advance our understanding of multiple exciton generation (MEG) in organic materials has been restricted by the limited number of materials capable of singlet fission. A particular challenge is the development of materials that undergo efficient intramolecular fission, such that local order and strong nearest-neighbour coupling is no longer a design constraint. Here we address these challenges by demonstrating that strong intrachain donor-acceptor interactions are a key design feature for organic materials capable of intramolecular singlet fission. By conjugating strong-acceptor and strong-donor building blocks, small molecules and polymers with charge-transfer states that mediate population transfer between singlet excitons and triplet excitons are synthesized. Using transient optical techniques, we show that triplet populations can be generated with yields up to 170%. These guidelines are widely applicable to similar families of polymers and small molecules, and can lead to the development of new fission-capable materials with tunable electronic structure, as well as a deeper fundamental understanding of MEG.

Constrained density functional theory (DFT) is a useful tool for studying electron transfer (ET) reactions. It can straightforwardly construct the charge-localized diabatic states and give a direct measure of the inner-sphere reorganization energy. In this work, a method is presented for calculating the electronic coupling matrix element (Hab) based on constrained DFT. This method completely avoids the use of ground-state DFT energies because they are known to irrationally predict fractional electron transfer in many cases. Instead it makes use of the constrained DFT energies and the Kohn-Sham wave functions for the diabatic states in a careful way. Test calculations on the Zn2+ and the benzene-Cl atom systems show that the new prescription yields reasonable agreement with the standard generalized Mulliken-Hush method. We then proceed to produce the diabatic and adiabatic potential energy curves along the reaction pathway for intervalence ET in the tetrathiafulvalene-diquinone (Q-TTF-Q) anion. While the unconstrained DFT curve has no reaction barrier and gives Hab approximately 17 kcal/mol, which qualitatively disagrees with experimental results, the Hab calculated from constrained DFT is about 3 kcalmol and the generated ground state has a barrier height of 1.70 kcal/mol, successfully predicting (Q-TTF-Q)- to be a class II mixed-valence compound.

A direct optimization method is developed for the computation of the Kohn–Sham kinetic energy density functional Ts from a given electron density and the exchange–correlation potential vxc if this density is from a ground state. The method is based on the construction of a variational functional of the one-electron potential. This functional is derived from the conventional Levy constrained-search formulation and is shown to be closely related to the Lieb functional construction. The one-electron potential is expanded in terms of some fixed terms plus a linear expansion in a basis set. The determination of the Kohn–Sham kinetic energy for an input density is then turned into the maximization of this functional of potential. The analytic first and second derivatives of the variational functional with respect to the linear basis set expansion coefficients and also the nonlinear parameters in the basis set are derived. This enables very efficient iterative optimization of the potential and hence the calculation of Ts and vxc. The efficiency and accuracy of the method is shown in the numerical implementation for atomic and molecular calculations with Gaussian basis set expansions both for molecular orbitals and for one-electron potentials. Finally, this direct optimization method is extended to general density functionals and the analytic derivatives are also developed for use in optimization methods.