Effective Fragment Potentials for Flexible Molecules: Transferability of Parameters and Amino Acid Database

An accurate but efficient description of noncovalent interactions is a key to predictive modeling of biological and materials systems. The effective fragment potential (EFP) is an ab initio-based force field that provides a physically meaningful decomposition of noncovalent interactions of a molecular system into Coulomb, polarization, dispersion, and exchange-repulsion components. An EFP simulation protocol consists of two steps, preparing parameters for molecular fragments by a series of ab initio calculations on each individual fragment, and calculation of interaction energy and properties of a total molecular system based on the prepared parameters. As the fragment parameters (distributed multipoles, polarizabilities, localized wave function, etc.) depend on a fragment geometry, straightforward application of the EFP method requires recomputing parameters of each fragment if its geometry changes, for example, during thermal fluctuations of a molecular system. Thus, recomputing fragment parameters can easily become both computational and human bottlenecks and lead to a loss of efficiency of a simulation protocol. An alternative approach, in which fragment parameters are adjusted to different fragment geometries, referred to as “flexible EFP”, is explored here. The parameter adjustment is based on translations and rotations of local coordinate frames associated with fragment atoms. The protocol is validated on extensive benchmark of amino acid dimers extracted from molecular dynamics snapshots of a cryptochrome protein. A parameter database for standard amino acids is developed to automate flexible EFP simulations in proteins. To demonstrate applicability of flexible EFP in large-scale protein simulations, binding energies and vertical electron ionization and electron attachment energies of a lumiflavin chromophore of the cryptochrome protein are computed. The results obtained with flexible EFP are in a close agreement with the standard EFP procedure but provide a significant reduction in computational cost

Quantum Computation of Finite-Temperature Static and Dynamical Properties of Spin Systems Using Quantum Imaginary Time Evolution

Developing scalable quantum algorithms to study finite-temperature physics of quantum many-body systems has attracted considerable interest due to recent advancements in quantum hardware. However, such algorithms in their present form require resources that exceed the capabilities of current quantum computers except for a limited range of system sizes and observables. Here, we report calculations of finite-temperature properties including energies, static and dynamical correlation functions, and excitation spectra of spin Hamiltonians with up to four sites on five-qubit IBM Quantum devices. These calculations are performed using the quantum imaginary time evolution (QITE) algorithm and made possible by several algorithmic improvements, including a method to exploit symmetries that reduces the quantum resources required by QITE, circuit optimization procedures to reduce circuit depth, and error mitigation techniques to improve the quality of raw hardware data. Our work demonstrates that the ansatz-independent QITE algorithm is capable of computing diverse finite-temperature observables on near-term quantum devices

Quantum Computation of Finite-Temperature Static and Dynamical Properties of Spin Systems Using Quantum Imaginary Time Evolution

Developing scalable quantum algorithms to study finite-temperature physics of quantum many-body systems has attracted considerable interest due to recent advancements in quantum hardware. However, such algorithms in their present form require resources that exceed the capabilities of current quantum computers except for a limited range of system sizes and observables. Here, we report calculations of finite-temperature properties, including energy, static and dynamical correlation functions, and excitation spectra of spin systems with up to four sites on five-qubit IBM Quantum devices. These calculations are performed using the quantum imaginary time evolution (QITE) algorithm and made possible by several algorithmic improvements, including a method to exploit symmetries that reduces the quantum resources required by QITE, circuit optimization procedures to reduce circuit depth, and error-mitigation techniques to improve the quality of raw hardware data. Our work demonstrates that the ansatz-independent QITE algorithm is capable of computing diverse finite-temperature observables on near-term quantum devices

Free Energies of Redox Half-Reactions from First-Principles Calculations

Quantitative prediction of the energetics of redox half-reactions is still a challenge for modern computational chemistry. Here, we propose a simple scheme for reliable calculations of vertical ionization and attachment energies, as well as of redox potentials of solvated molecules. The approach exploits linear response approximation in the context of explicit solvent simulations with spherical boundary conditions. It is shown that both vertical ionization energies and vertical electron affinities, and, consequently redox potentials, exhibit linear dependence on the inverse radius of the solvation sphere. The explanation of the linear dependence is provided, and an extrapolation scheme is suggested. The proposed approach accounts for the specific short-range interactions within hybrid DFT and effective fragment potential approach as well as for the asymptotic system-size effects. The computed vertical ionization energies and redox potentials are in excellent agreement with the experimental values

Photoactivation of Cryptochromes Invokes Competing Inter- and Intramolecular Electron Transfer

Growing experimental and theoretical evidence points to the key role of cryptochrome proteins in magnetoreception by migratory birds and insects. Cryptochrome photoactivation is achieved through a cascade of electron transfer events leading to formation of a long-lived spin-correlated radical pair. The electron transfer cascade is initiated by photoexcitation of the FAD cofactor and subsequent electron transfer through three conserved tryptophan residues, the so-called tryptophan triad. Presence of ATP was shown to increase the yield of the semireduced form of FAD. While electron transfer through the tryptophan triad is well characterized by both theoretical and experimental methods, the effects of ATP binding are still not well understood. The present work aims to unravel the mechanism of ultrafast photoinduced electron transfer in a cryptochrome protein with a focus on effects of ATP on the FAD photoreduction process. Photoinduced electron transfer is described by means of state-of-the-art theoretical methods: a hybrid quantum-classical polarizable embedding scheme is utilized to accurately parameterize a generalized local excited/charge transfer state system-bath model Hamiltonian and the photoinduced electron transfer process is described by a semiclassical path integral-based dynamics method. The results draw attention to the crucial role of the intramolecular electron transfer from adenine to the flavin moiety of the FAD cofactor for formation of the semireduced form of FAD, providing an explanation for the increased yield of the semireduced form in the presence of the cellular metabolites in vitro and in vivo.</div

eMap: A Web Application for Identifying and Visualizing Electron or Hole Hopping Pathways in Proteins

eMap is a web-based platform for identifying and visualizing electron or hole transfer pathways in proteins based on their crystal structures. The underlying model can be viewed as a coarse-grained version of the Pathways model, where each tunneling step between hopping sites represented by electron transfer active (ETA) moieties is described with one effective decay parameter that describes protein-mediated tunneling. ETA moieties include aromatic amino acid residue side chains and aromatic fragments of cofactors that are automatically detected, and, in addition, electron/hole residing sites that can be specified by the users. The software searches for the shortest paths connecting the user-specified electron/hole source to either all surface-exposed ETA residues or to the user-specified target. The identified pathways are ranked based on their length. The pathways are visualized in 2D as a graph, in which each node represents an ETA site, and in 3D using available protein visualization tools. Here, we present the capability and user interface of eMap 1.0, which is available at https://emap.bu.edu.</p

Simulating Redox Potentials of Biomolecules: the Case of Cryptochrome 1 from Arabidopsis thaliana

Redox reactions play a key role in various biological processes, including photosynthesis and respiration. Quantitative and predictive computational characterization of redox events is therefore highly desirable for enriching our knowledge on mechanistic features of biological redox-active macromolecules. Here, we present the results of computational studies of the redox potential of flavin adenine dinucleotide (FAD) in cryptochrome 1 from Arabidopsis thaliana (Cry1At). The special attention is paid to fundamental aspects of the theoretical description such as the effects of environment polarization and of the long-range electrostatic interactions on the computed energetic parameters. Environment (protein and the solvent) polarization is shown to be crucial for accurate estimates of the redox potential: hybrid quantum-classical results with and without account for environment polarization differ by 1.4 V. Long-range electrostatic interactions are shown to contribute significantly to the computed redox potential value even at the distances far beyond the protein outer surface. The theoretical estimate (0.07 V) of the midpoint reduction potential of FAD in Cry1At is reported for the first time and is in good agreement with available experimental data