99 research outputs found
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
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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
and -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()-states,
they acquire significant C() 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 Í‘which have lone pairsÍ’ the method yields very reliable results. The results for 1 JÍ‘Si-HÍ’ 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 Í‘through the Fermi-contact mechanismÍ’ on atoms to the right of the periodic table Í‘containing lone pairsÍ’. 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 ''on'' and ''off'' 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.
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