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Register a new userPhysics of selective conduction and point mutation in biological ion channels
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We introduce a statistical and linear response theory of selective conduction in biological ion channels with multiple binding sites and possible point mutations. We derive an effective grand-canonical ensemble and generalised Einstein relations for the selectivity filter, assuming strongly coordinated ionic motion, and allowing for ionic Coulomb blockade. The theory agrees well with data from the KcsA K$^+$ channel and a mutant. We show that the Eisenman relations for thermodynamic selectivity follow from the condition for fast conduction and find that maximum conduction requires the binding sites to be nearly identical.
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We present an equilibrium statistical-mechanical theory of selectivity in biological ion channels. In doing so, we introduce a grand canonical ensemble for ions in a channels selectivity filter coupled to internal and external bath solutions for a mixture of ions at arbitrary concentrations, we use linear response theory to find the current through the filter for small gradients of electrochemical potential, and we show that the conductivity of the filter is given by the generalized Einstein relation. We apply the theory to the permeation of ions through the potassium selectivity filter, and are thereby able to resolve the long-standing paradox of why the high selectivity of the filter brings no associated delay in permeation. We show that the Eisenman selectivity relation follows directly from the condition of diffusion-limited conductivity through the filter. We also discuss the effect of wall fluctuations on the filter conductivity.
ClC chloride channels possess a homodimeric structure in which each monomer contains an independent chloride ion pathway. ClC channel gating is regulated by chloride ion concentration, pH, and voltage. Based on structural and physiological evidence, it has been proposed that a glutamate residue on the extracellular end of the selectivity filter acts as a fast gate. We utilize a new search algorithm which incorporates electrostatic information to explore the ion transit pathways through wild-type and mutant bacterial ClC channels. Examination of the chloride ion permeation pathways supports the proposed important role of the glutamate residue in gating. An external chloride binding site previously postulated in physiological experiments is located near a conserved basic residue adjacent to the gate. In addition, access pathways are found for proton migration to the gate, enabling pH control at hyperpolarized membrane potentials. A chloride ion in the selectivity filter is required for the pH-dependent gating mechanism.
There are many controversial and challenging discussions about quantum effects in microscopic structures in neurons of the human brain. The challenge is mainly because of quick decoherence of quantum states due to hot, wet and noisy environment of the brain which forbids long life coherence for brain processing. Despite these critical discussions, there are only a few number of published papers about numerical aspects of decoherence in neurons. Perhaps the most important issue is offered by Max Tegmark who has calculated decoherence times for the systems of ions and microtubules in neurons of the brain. In fact, Tegmark did not consider ion channels which are responsible for ions displacement through the membrane and are the building blocks of electrical membrane signals in the nervous system. Here, we would like to re-investigate decoherence times for ionic superposition states by using the data obtained via molecular dynamics simulations. Our main approach is according to what Tegmark has used before. In fact, Tegmark didnt consider the ion channel structure and his estimates are only simple approximations. In this paper, we focus on the small nano-scale part of KcsA ion channels which is called selectivity filter and has a key role in the operation of an ion channel. Our results for superposition states of potassium ions indicate that decoherence times are in the order of picoseconds which are 10-100 million times bigger than the order calculated by Tegmark. This decoherence time is still not enough for cognitive processing in the brain, however it can be adequate for quantum states of cooled ions in the filter to leave their quantum traces on the filter and action potentials.
Microbial communities are ubiquitous in nature and come in a multitude of forms, ranging from communities dominated by a handful of species to communities containing a wide variety of metabolically distinct organisms. This huge range in diversity is not a curiosity - microbial diversity has been linked to outcomes of substantial ecological and medical importance. However, the mechanisms underlying microbial diversity are still under debate, as simple mathematical models only permit as many species to coexist as there are resources. A plethora of mechanisms have been proposed to explain the origins of microbial diversity, but many of these analyses omit a key property of real microbial ecosystems: the propensity of the microbes themselves to change their growth properties within and across generations. In order to explore the impact of this key property on microbial diversity, we expand upon a recently developed model of microbial diversity in fluctuating environments. We implement changes in growth strategy in two distinct ways. First, we consider the regulation of a cells enzyme levels within short, ecological times, and second we consider evolutionary changes driven by mutations across generations. Interestingly, we find that these two types of microbial responses to the environment can have drastically different outcomes. Enzyme regulation may collapse diversity over long enough times while, conversely, strategy-randomizing mutations can produce a rich-get-poorer effect that promotes diversity. This work makes explicit, using a simple serial-dilutions framework, the conflicting ways that microbial adaptation and evolution can affect community diversity.
We develop a kinetic reaction model for cells having irradiated DNA molecules due to ionizing radiation exposure. Our theory simultaneously accounts for the time-dependent reactions of the DNA damage, the DNA mutation, the DNA repair, and the proliferation and apoptosis of cells in a tissue with a minimal set of model parameters. In contrast to existing theories for radiation exposition, we do not assume the relationships between the total dose and the induced mutation frequency. Our theory provides a universal scaling function that reasonably explains the mega-mouse experiments in Ref.[W. L. Russell and E. M. Kelly, Proc. Natl. Acad. Sci. USA. {bf 79} (1982) 542.] with different dose rates. Furthermore, we have estimated the effective dose rate, which is biologically equivalent to the ionizing effects other than those caused by artificial irradiation. This value is $ 1.11 times 10^{-3} ~rm{[Gy/hr]}$, which is significantly larger than the effect caused by natural background radiation.
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