Molecular simulation assisted identification of Ca(2+) binding residues in TMEM16A.

Calcium-activated chloride channels (CaCCs) play vital roles in a variety of physiological processes. Transmembrane protein 16A (TMEM16A) has been confirmed as the molecular counterpart of CaCCs which greatly pushes the molecular insights of CaCCs forward. However, the detailed mechanism of Ca(2+) binding and activating the channel is still obscure. Here, we utilized a combination of computational and electrophysiological approaches to discern the molecular mechanism by which Ca(2+) regulates the gating of TMEM16A channels. The simulation results show that the first intracellular loop serves as a Ca(2+) binding site including D439, E444 and E447. The experimental results indicate that a novel residue, E447, plays key role in Ca(2+) binding. Compared with WT TMEM16A, E447Y produces a 30-fold increase in EC50 of Ca(2+) activation and leads to a 100-fold increase in Ca(2+) concentrations that is needed to fully activate the channel. The following steered molecular dynamic (SMD) simulation data suggests that the mutations at 447 reduce the Ca(2+) dissociation energy. Our results indicated that both the electrical property and the size of the side-chain at residue 447 have significant effects on Ca(2+) dependent gating of TMEM16A.

Statistical properties and error threshold of quasispecies on single-peak Gaussian-distributed fitness landscapes.

The stochastic Eigen model proposed by Feng et al. (2007) (Journal of Theoretical Biology, 246, 28) showed that error threshold is no longer a phase transition point but a crossover region whose width depends on the strength of the random fluctuation in an environment. The underlying cause of this phenomenon has not yet been well examined. In this article, we adopt a single peak Gaussian distributed fitness landscape instead of a constant one to investigate and analyze the change of the error threshold and the statistical property of the quasi-species population. We find a roughly linear relation between the width of the error threshold and the fitness fluctuation strength. For a given quasi-species, the fluctuation of the relative concentration has a minimum with a normal distribution of the relative concentration at the maximum of the averaged relative concentration, it has however a largest value with a bimodal distribution of the relative concentration near the error threshold. The above results deepen our understanding of the quasispecies and error threshold and are heuristic for exploring practicable antiviral strategies.

Combining fragment homology modeling with molecular dynamics aims at prediction of Ca²âº binding sites in CaBPs.

The family of calcium-binding proteins (CaBPs) consists of dozens of members and contributes to all aspects of the cell's function, from homeostasis to learning and memory. However, the Ca²âº-binding mechanism is still unclear for most of CaBPs. To identify the Ca²âº-binding sites of CaBPs, this study presented a computational approach which combined the fragment homology modeling with molecular dynamics simulation. For validation, we performed a two-step strategy as follows: first, the approach is used to identify the Ca²âº-binding sites of CaBPs, which have the EF-hand Ca²âº-binding site and the detailed binding mechanism. To accomplish this, eighteen crystal structures of CaBPs with 49 Ca²âº-binding sites are selected to be analyzed including calmodulin. The computational method identified 43 from 49 Ca²âº-binding sites. Second, we performed the approach to large-conductance Ca²âº-activated K⁺ (BK) channels which don't have clear Ca²âº-binding mechanism. The simulated results are consistent with the experimental data. The computational approach may shed some light on the identification of Ca²âº-binding sites in CaBPs.