The Born–Oppenheimer approximation underlies much of chemical simulation and provides the framework defining the potential energy surfaces that are used for much of our pictorial understanding of ...chemical phenomena. However, this approximation breaks down when the dynamics of molecules in excited electronic states are considered. Describing dynamics when the Born–Oppenheimer approximation breaks down requires a quantum mechanical description of the nuclei. Chemical reaction dynamics on excited electronic states is critical for many applications in renewable energy, chemical synthesis, and bioimaging. Furthermore, it is necessary in order to connect with many ultrafast pump–probe spectroscopic experiments. In this review, we provide an overview of methods that can describe nonadiabatic dynamics, with emphasis on those that are able to simultaneously address the quantum mechanics of both electrons and nuclei. Such ab initio quantum molecular dynamics methods solve the electronic Schrödinger equation alongside the nuclear dynamics and thereby avoid the need for precalculation of potential energy surfaces and nonadiabatic coupling matrix elements. Two main families of methods are commonly employed to simulate nonadiabatic dynamics in molecules: full quantum dynamics, such as the multiconfigurational time-dependent Hartree method, and classical trajectory-based approaches, such as trajectory surface hopping. In this review, we describe a third class of methods that is intermediate between the two: Gaussian basis set expansions built around trajectories.
The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. ...We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.
We develop an extension of the variational quantum eigensolver (VQE) algorithm-multistate contracted VQE (MC-VQE)-that allows for the efficient computation of the transition energies between the ...ground state and several low-lying excited states of a molecule, as well as the oscillator strengths associated with these transitions. We numerically simulate MC-VQE by computing the absorption spectrum of an ab initio exciton model of an 18-chromophore light-harvesting complex from purple photosynthetic bacteria.
Few would dispute that theoretical chemistry tools can now provide keen insights into chemical phenomena. Yet the holy grail of efficient and reliable prediction of complex reactivity has remained ...elusive. Fortunately, recent advances in electronic structure theory based on the concepts of both element- and rank-sparsity, coupled with the emergence of new highly parallel computer architectures, have led to a significant increase in the time and length scales which can be simulated using first principles molecular dynamics. This opens the possibility of new discovery-based approaches to chemical reactivity, such as the recently proposed ab initio nanoreactor. We argue that due to these and other recent advances, the holy grail of computational discovery for complex chemical reactivity is rapidly coming within our reach.
Repetitive DNA sequences are abundant in a broad range of species, from bacteria to mammals, and they cover nearly half of the human genome. Repeats have always presented technical challenges for ...sequence alignment and assembly programs. Next-generation sequencing projects, with their short read lengths and high data volumes, have made these challenges more difficult. From a computational perspective, repeats create ambiguities in alignment and assembly, which, in turn, can produce biases and errors when interpreting results. Simply ignoring repeats is not an option, as this creates problems of its own and may mean that important biological phenomena are missed. We discuss the computational problems surrounding repeats and describe strategies used by current bioinformatics systems to solve them.
The spinal dorsal horn receives input from primary afferent axons, which terminate in a modality-specific fashion in different laminae. The incoming somatosensory information is processed through ...complex synaptic circuits involving excitatory and inhibitory interneurons, before being transmitted to the brain via projection neurons for conscious perception. The dorsal horn is important, firstly because changes in this region contribute to chronic pain states, and secondly because it contains potential targets for the development of new treatments for pain. However, at present, we have only a limited understanding of the neuronal circuitry within this region, and this is largely because of the difficulty in defining functional populations among the excitatory and inhibitory interneurons. The recent discovery of specific neurochemically defined interneuron populations, together with the development of molecular genetic techniques for altering neuronal function in vivo, are resulting in a dramatic improvement in our understanding of somatosensory processing at the spinal level.
The cereal pathogen Fusarium graminearum is the primary cause of Fusarium head blight (FHB) and a significant threat to food safety and crop production. To elucidate population structure and identify ...genomic targets of selection within major FHB pathogen populations in North America we sequenced the genomes of 60 diverse F. graminearum isolates. We also assembled the first pan-genome for F. graminearum to clarify population-level differences in gene content potentially contributing to pathogen diversity. Bayesian and phylogenomic analyses revealed genetic structure associated with isolates that produce the novel NX-2 mycotoxin, suggesting a North American population that has remained genetically distinct from other endemic and introduced cereal-infecting populations. Genome scans uncovered distinct signatures of selection within populations, focused in high diversity, frequently recombining regions. These patterns suggested selection for genomic divergence at the trichothecene toxin gene cluster and thirteen additional regions containing genes potentially involved in pathogen specialization. Gene content differences further distinguished populations, in that 121 genes showed population-specific patterns of conservation. Genes that differentiated populations had predicted functions related to pathogenesis, secondary metabolism and antagonistic interactions, though a subset had unique roles in temperature and light sensitivity. Our results indicated that F. graminearum populations are distinguished by dozens of genes with signatures of selection and an array of dispensable accessory genes, suggesting that FHB pathogen populations may be equipped with different traits to exploit the agroecosystem. These findings provide insights into the evolutionary processes and genomic features contributing to population divergence in plant pathogens, and highlight candidate genes for future functional studies of pathogen specialization across evolutionarily and ecologically diverse fungi.
PDF
