European Biophysics Journal最新文献

Neuropathic pain (NP) is characterized by hyperalgesia, allodynia, and spontaneous pain. Hyperpolarization-activated cyclic nucleotide-gated (HCN) channel involved in neuronal hyperexcitability, has emerged as an important target for the drug development of NP. HCN channels exist in four different isoforms, where HCN1 is majorly expressed in dorsal root ganglion having an imperative role in NP pathophysiology. A specific HCN1 channel inhibitor will hold the better potential to treat NP without disturbing the physiological roles of other HCN isoforms. The main objective is to identify and analyze the chemical properties of scaffolds with higher HCN1 channel specificity. The 3D-QSAR studies highlight the hydrophobic & hydrogen bond donor groups enhance specificity towards the HCN1 channel. Further, the molecular interaction of the scaffolds with the HCN1 pore was studied by generating an open-pore model of the HCN1 channel using homology modelling and then docking the molecules with it. In addition, the important residues involved in the interaction between HCN1 pore and scaffolds were also identified. Moreover, ADME predictions revealed that compounds had good oral bioavailability and solubility characteristics. Subsequently, molecular dynamics simulation studies revealed the better stability of the lead molecules A7 and A9 during interactions and ascertained them as potential drug candidates. Cumulative studies provided the important structural features for enhancing HCN1 channel-specific inhibition, paving the way to design and develop novel specific HCN1 channel inhibitors.

In a bid to quantify the contribution of molecular structure to non-specific interactions leading to functionally important structural changes in cellular processes, the self-interaction of dextran-T70 (DT70) and its interaction with each of bovine serum albumin (BSA) and ovomucoid trypsin inhibitor (OVO) were studied at pH 7.4 between 5 and 37 °C. The dependences of the apparent molecular weight of each of BSA, OVO and DT70 on the concentration of DT70 were independent of temperature. The activity coefficient of the interaction of each species on DT70 concentration was also independent of temperature. The change in activity coefficient was however dependent on the molecular structure and size of the interacting species. The energy of insertion of each macromolecule in DT70 increased in the order DT70 > BSA > OVO. These findings show that although the enthalpic contribution is negligible, the extent of the entropic contribution to the macromolecular activity coefficient of interaction is chiefly the consequence of the exclusion volume of the interacting macromolecules.

The interconnected processes of protein folding, mutations, epistasis, and evolution have all been the subject of extensive analysis throughout the years due to their significance for structural and evolutionary biology. The origin (molecular basis) of epistasis—the non-additive interactions between mutations—is still, nonetheless, unknown. The existence of a new perspective on protein folding, a problem that needs to be conceived as an ‘analytic whole’, will enable us to shed light on the origin of mutational epistasis at the simplest level—within proteins—while also uncovering the reasons why the genetic background in which they occur, a key component of molecular evolution, could foster changes in epistasis effects. Additionally, because mutations are the source of epistasis, more research is needed to determine the impact of post-translational modifications, which can potentially increase the proteome’s diversity by several orders of magnitude, on mutational epistasis and protein evolvability. Finally, a protein evolution thermodynamic-based analysis that does not consider specific mutational steps or epistasis effects will be briefly discussed. Our study explores the complex processes behind the evolution of proteins upon mutations, clearing up some previously unresolved issues, and providing direction for further research.

Atherosclerosis is one of the important diseases of the circulatory system because atherosclerotic plaques cause significant disruption of blood flow. Therefore, it is very important to properly understand these processes and skillfully simulate blood flow. In our work, we consider blood flow through an abdominal aorta with iliac arteries, assuming that the right iliac artery is narrowed by an atherosclerotic lesion. Blood flow is simulated using the laminar, standard (k-omega) and standard (k-epsilon) models. The obtained results show that despite the use of identical initial conditions, the distribution of velocity flow and wall shear stress depends on the choice of flow simulation model. For the (k-epsilon) model, we obtain higher values of speed and wall shear stress on atherosclerotic plaque than in the other two models. The laminar and (k-omega) models predict larger areas where reverse blood flow occurs in the area behind the atherosclerotic lesion. This effect is associated with negative wall shear stress. These two models give very similar results. The results obtained by us, and those reported in the literature, indicate that (k-omega) model is the most suitable for blood flow analysis.

This communication summarizes findings from the earliest encounters with extreme enthalpy‒entropy compensation, a phenomenon first detected in the 1950s by a reappraisal of isopiestic and calorimetric measurements on aqueous urea solutions in terms of solute self-association. Because concurrent studies of carboxylic acid association were confined to measurement of the equilibrium constant by conductance, IR spectrophotometry or potentiometric titration measurements, temperature-independence of the dimerization constant was mistakenly taken to signify a value of zero for Δ(H^o) instead of (Δ(H^o) ‒ TΔ(S^o)). In those studies of small-solute self-association the extreme enthalpy‒entropy compensation was reflecting the action of water as a reactant whose hydroxyl groups were competing for the solute carbonyl involved in self-association. Such action gives rise to a positive temperature dependence of Δ(H^o) that could well be operating in concert with that responsible for the commonly observed negative dependence for protein‒ligand interactions exhibiting extreme enthalpy‒entropy compensation, where the solvent contribution to the energetics reflects changes in the extent of ordered water structure in hydrophobic environments.

This study aimed to calculate the effect of nanopatterns’ peak sharpness, width, and spacing parameters on P. aeruginosa and S. aureus cell walls by artificial neural network and finite element analysis. Elastic and creep deformation models of bacteria were developed in silico. Maximum deformation, maximum stress, and maximum strain values of the cell walls were calculated. According to the results, while the spacing of the nanopatterns is constant, it was determined that when their peaks were sharpened and their width decreased, maximum deformation, maximum stress, and maximum strain affecting the cell walls of both bacteria increased. When sharpness and width of the nano-patterns are kept constant and the spacing is increased, maximum deformation, maximum stress, and maximum strain in P. aeruginosa cell walls increase, but a decrease in S. aureus was observed. This study proves that changes in the geometric structures of nanopatterned surfaces can show different effects on different bacteria.

Antifreeze proteins (AFPs) have unique features to sustain life in sub-zero environments due to ice recrystallization inhibition (IRI) and thermal hysteresis (TH). AFPs are in demand as agents in cryopreservation, but some antifreeze proteins have low levels of activity. This research aims to improve the cryopreservation activity of an AFPIV. In this in silico study, the helical peptide afp1m from an Antarctic yeast AFP was modeled into a sculpin AFPIV, to replace each of its four α-helices in turn, using various computational tools. Additionally, a new linker between the first two helices of AFPIV was designed, based on a flounder AFPI, to boost the ice interaction activity of the mutants. Bioinformatics tools such as ExPASy Prot-Param, Pep-Wheel, SOPMA, GOR IV, Swiss-Model, Phyre2, MODFOLD, MolPropity, and ProQ were used to validate and analyze the structural and functional properties of the model proteins. Furthermore, to evaluate the AFP/ice interaction, molecular dynamics (MD) simulations were executed for 20, 100, and 500 ns at various temperatures using GROMACS software. The primary, secondary, and 3D modeling analysis showed the best model for a redesigned antifreeze protein (AFP1mb, with afp1m in place of the fourth AFPIV helix) with a QMEAN (Swiss-Model) Z score value of 0.36, a confidence of 99.5%, a coverage score of 22%, and a p value of 0.01. The results of the MD simulations illustrated that AFP1mb had more rigidity and better ice interactions as a potential cryoprotectant than the other models; it also displayed enhanced activity in limiting ice growth at different temperatures.