An efficient Monte Carlo method for calculating ab initio transition state theory reaction rates in solution

In this article, we propose an efficient method for sampling the relevant state space in condensed phase reactions. In the present method, the reaction is described by solving the electronic Schr\"{o}dinger equation for the solute atoms in the presence of explicit solvent molecules. The sampling algorithm uses a molecular mechanics guiding potential in combination with simulated tempering ideas and allows thorough exploration of the solvent state space in the context of an ab initio calculation even when the dielectric relaxation time of the solvent is long. The method is applied to the study of the double proton transfer reaction that takes place between a molecule of acetic acid and a molecule of methanol in tetrahydrofuran. It is demonstrated that calculations of rates of chemical transformations occurring in solvents of medium polarity can be performed with an increase in the cpu time of factors ranging from 4 to 15 with respect to gas-phase calculations.Comment: 15 pages, 9 figures. To appear in J. Chem. Phy

Quantum Criticality at the Origin of Life

Why life persists at the edge of chaos is a question at the very heart of evolution. Here we show that molecules taking part in biochemical processes from small molecules to proteins are critical quantum mechanically. Electronic Hamiltonians of biomolecules are tuned exactly to the critical point of the metal-insulator transition separating the Anderson localized insulator phase from the conducting disordered metal phase. Using tools from Random Matrix Theory we confirm that the energy level statistics of these biomolecules show the universal transitional distribution of the metal-insulator critical point and the wave functions are multifractals in accordance with the theory of Anderson transitions. The findings point to the existence of a universal mechanism of charge transport in living matter. The revealed bio-conductor material is neither a metal nor an insulator but a new quantum critical material which can exist only in highly evolved systems and has unique material properties.Comment: 10 pages, 4 figure

Measurement and prediction of quantum coherence effects in biological processes

This themed issue presents a collection of articles on the measurement and prediction of quantum coherence effects in biological processes.</p

System-specific parameter optimization for non-polarizable and polarizable force fields

The accuracy of classical force fields (FFs) has been shown to be limited for the simulation of cation-protein systems despite their importance in understanding the processes of life. Improvements can result from optimizing the parameters of classical FFs or by extending the FF formulation by terms describing charge transfer and polarization effects. In this work, we introduce our implementation of the CTPOL model in OpenMM, which extends the classical additive FF formula by adding charge transfer (CT) and polarization (POL). Furthermore, we present an open-source parameterization tool, called FFAFFURR that enables the (system specific) parameterization of OPLS-AA and CTPOL models. The performance of our workflow was evaluated by its ability to reproduce quantum chemistry energies and by molecular dynamics simulations of a Zinc finger protein.Comment: 62 pages and 25 figures (including SI), manuscript to be submitted soo

The Effect of Structural Distortions on the Electronic Structure of Carbon Nanotubes

We calculated the effects of structural distortions on the electronic structure of carbon nanotubes. The key modification of the electronic structure brought about by bending a nanotube involves an increased mixing of $\sigma$ and $\pi$-states. This mixing leads to an enhanced density-of-states in the valence band near the Fermi energy region. While in a straight tube the states accessible for electrical conduction are essentially pure C($2p_{\pi}$)-states, they acquire significant C($2sp_{\sigma}$) character upon bending. Bending also leads to a charge polarization of the C-C bonds in the deformed region reminiscent of interface dipole formation. Scattering of conduction electrons at the distorted regions may lead to electron localization at low temperatures.Comment: 11 pages and 4 figures, (figure 4 corrected

Nuclear magnetic resonance spin–spin coupling constants from density functional theory: Problems and results

Our recently developed method for the calculation of indirect nuclear spin-spin coupling constants is studied in more detail. For the couplings between nuclei other than N, O, and F ͑which have lone pairs͒ the method yields very reliable results. The results for 1 J͑Si-H͒ couplings are presented and their dependence on the basis set quality is analyzed. Also, The limitations of the method, which is based on density functional theory, are connected with the inability of the present LDA and GGA exchange-correlation functionals to describe properly the spin-perturbations ͑through the Fermi-contact mechanism͒ on atoms to the right of the periodic table ͑containing lone pairs͒. However, the deviations from experiment of the calculated couplings for such nuclei are systematic, at least for one-bond couplings, and therefore these calculated couplings should still be useful for NMR structure determinations

Studying genetic regulatory networks at the molecular level: delayed reaction stochastic models

Abstract Current advances in molecular biology enable us to access the rapidly increasing body of genetic information. It is still challenging to model gene systems at the molecular level. Here, we propose two types of reaction kinetic models for constructing genetic networks. Time delays involved in transcription and translation are explicitly considered to explore the effects of delays, which may be significant in genetic networks featured with feedback loops. One type of model is based on delayed effective reactions, each reaction modeling a biochemical process like transcription without involving intermediate reactions. The other is based on delayed virtual reactions, each reaction being converted from a mathematical function to model a biochemical function like gene inhibition. The latter stochastic models are derived from the corresponding mean-field models. The former ones are composed of single gene expression modules. We thus design a model of gene expression. This model is verified by our simulations using a delayed stochastic simulation algorithm, which accurately reproduces the stochastic kinetics in a recent experimental study. Various simplified versions of the model are given and evaluated. We then use the two methods to study the genetic toggle switch and the repressilator. We define the &apos;&apos;on&apos;&apos; and &apos;&apos;off&apos;&apos; states of genes and extract a binary code from the stochastic time series. The binary code can be described by the corresponding Boolean network models in certain conditions. We discuss these conditions, suggesting a method to connect Boolean models, mean-field models, and stochastic chemical models.