Biophysical chemistry最新文献

Voltage-gated ion channels play an important role in generating action potential in neurons. These ion channels are found to be in localized cluster form on the axonal membrane surface and behave cooperatively. However, in Hodgkin & Huxley's model of action potential the ion channels are considered to function independently. According to some recent reports, the activity of an ion channel is influenced by the neighboring ion channels' activities. We have modified the Hodgkin-Huxley's model based on our previous studies on cooperativity among ion channels. Computational analysis of the proposed model shows that the initiation of the action potential, amplitude and hyperpolarization are affected significantly by the cooperative interactions among the voltage-gated ion channels present on the axonal membrane surface. These results are qualitatively supported by the existing experimental facts.

In solution NMR, chemical shift perturbation (CSP) experiments are widely employed to study intermolecular interactions. However, excluding the nonsignificant peak shift is difficult because little is known about errors in CSP. Here, to address this issue, we introduce a method for estimating errors in CSP based on the noise level. First, we developed a technique that involves line shape fitting to estimate errors in peak position via Monte Carlo simulations. Second, this technique was applied to estimate errors in CSP. In intermolecular interaction analysis of VAP-A with SNX2, error estimation of CSP enabled the evaluation of small but significant changes in peak position and yielded detailed insights that are unattainable with conventional CSP analysis. Third, this technique was successfully applied to estimate errors in residual dipolar couplings. In conclusion, our error estimation method improves CSP analysis by excluding the nonsignificant peak shift.

Understanding the mechanisms by which drugs interact with cell membranes is crucial for unraveling the underlying biochemical and biophysical processes that occur on the surface of these membranes. Our research focused on studying the interaction between an ester-type derivative of tristearoyl uridine and model cell membranes composed of lipid monolayers at the air-water interface. For that, we selected a specific lipid to simulate nontumorigenic cell membranes, namely 1,2-dihexadecanoyl-sn-glycero-3-phospho-l-serine. We noted significant changes in the surface pressure-area isotherms, with a noticeable shift towards larger areas, which was lower than expected for ideal mixtures, indicating monolayer condensation. Furthermore, the viscoelastic properties of the interfacial film demonstrated an increase in both the elastic and viscous parameters for the mixed film. We also observed structural alterations using vibrational spectroscopy, which revealed an increase in the all-trans to gauche conformers ratio. This confirmed the stiffening effect of the prodrug on the lipid monolayer. In summary, this study indicates that this lipophilic prodrug significantly impacts the lipid monolayer's thermodynamic, rheological, electrical, and molecular characteristics. This information is crucial for understanding how the drug interacts with specific sites on the cellular membrane. It also has implications for drug delivery, as the drug's passage into the cytosol may involve traversing the lipid bilayer.

High isotropic resolution is essential for the structural elucidation of samples with multiple sites. In this study, utilizing the benefits of TRAPDOR-based heteronuclear multiple quantum coherence (T-HMQC) and a pair of one rotor period long cosine amplitude modulated low-power (cos-lp) pulse-based symmetric-split-t₁ multiple-quantum magic angle spinning (MQMAS) methods, we have developed a proton-detected 2D ³⁵Cl/¹H T-HMQC-MQMAS pulse sequence under fast MAS (70 kHz) to achieve high-resolution in the indirect dimension of the spin-3/2 (³⁵Cl) nuclei connected via protons. As T-HMQC polarizes not only single-quantum central transition (SQ_CT) but also triple-quantum (TQ) coherences, the proposed 2D pulse sequence is implemented via selection of two coherence pathways (SQ_CT $\to$TQ $\to$SQ_CT and TQ $\to$ SQ_CT $\to$TQ) resulting in the ³⁵Cl isotropic dimension and is superior to the existing double-quantum satellite-transition (DQ_ST) T-HMQC in terms of resolution.

The prediction of binding affinity changes caused by missense mutations can elucidate antigen-antibody interactions. A few accessible structure-based online computational tools have been proposed. However, selecting suitable software for particular research is challenging, especially research on the SARS-CoV-2 spike protein with antibodies. Therefore, benchmarking of the mutation-diverse SARS-CoV-2 datasets is critical. Here, we collected the datasets including 1216 variants about the changes in binding affinity of antigens from 22 complexes for SARS-CoV-2 S proteins and 22 monoclonal antibodies as well as applied them to evaluate the performance of seven binding affinity prediction tools. The tested tools' Pearson correlations between predicted and measured changes in binding affinity were between −0.158 and 0.657, while accuracy in classification tasks on predicting increasing or decreasing affinity ranged from 0.444 to 0.834. These tools performed relatively better on predicting single mutations, especially at epitope sites, whereas poor performance on extremely decreasing affinity. The tested tools were relatively insensitive to the experimental techniques used to obtain structures of complexes. In summary, we constructed a list of datasets and evaluated a range of structure-based online prediction tools that will explicate relevant processes of antigen-antibody interactions and enhance the computational design of therapeutic monoclonal antibodies.

Amylin is a systemic neuroendocrine hormone co-expressed and co-secreted with insulin by pancreatic β-cells. In persons with thype-2 diabetes, amylin forms pancreatic amyloid triggering inflammasome and interleukin-1β signaling and inducing β-cell apoptosis. Here, we summarize recent progress in understanding the potential link between amyloid-forming pancreatic amylin and Alzheimer's disease (AD). Clinical data describing amylin pathology in AD alongside mechanistic studies in animals are reviewed. Data from multiple research teams indicate higher amylin concentrations are associated with increased frequency of cognitive impairment and amylin co-aggregates with β-amyloid in AD-type dementia. Evidence from rodent models further suggests cerebrovascular amylin accumulation as a causative factor underlying neurological deficits. Analysis of relevant literature suggests that modulating the amylin-interleukin-1β pathway may provide an approach for counteracting neuroinflammation in AD.

The cationic antimicrobial peptides PGLa and magainin 2 (Mag2) are known for their antimicrobial activity and synergistic enhancement in antimicrobial and membrane leakage assays. Further use of peptides in combinatory therapy requires knowledge of the mechanisms of action of both individual peptides and their mixtures. Here, electron paramagnetic resonance (EPR), double electron-electron resonance (DEER, also known as PELDOR) and electron spin echo envelope modulation (ESEEM) spectroscopies were applied to study self-assembly and localization of spin-labeled PGLa and Mag2 in POPE/POPG membranes with a wide range of peptide/lipid ratios (P/L) from ∼1/1500 to 1/50. EPR and DEER data showed that both peptides tend to organize in clusters, which occurs already at the lowest peptide/lipid molar ratio of 1/1500 (0.067 mol%). For individual peptides, these clusters are quite dense with intermolecular distances of the order of ∼2 nm. In the presence of a synergistic peptide partner, these homo-clusters are transformed into lipid-diluted hetero-clusters. These clusters are characterized by a local surface density that is several times higher than expected from a random distribution. ESEEM data indicate a slightly different insertion depth of peptides in hetero-clusters when compared to homo-clusters.

In Drosophila melanogaster, Dcr-2:R2D2 heterodimer binds to the 21 nucleotide siRNA duplex to form the R2D2/Dcr-2 Initiator (RDI) complex, which is critical for the initiation of siRNA-induced silencing complex (RISC) assembly. During RDI complex formation, R2D2, a protein that contains three dsRNA binding domains (dsRBD), senses two aspects of the siRNA: thermodynamically more stable end (asymmetry sensing) and the 5′-phosphate (5'-P) recognition. Despite several detailed studies to date, the molecular determinants arising from R2D2 for performing these two tasks remain elusive. In this study, we have performed structural, biophysical, and biochemical characterization of R2D2 dsRBDs. We found that the solution NMR-derived structure of R2D2 dsRBD1 yielded a canonical α1-β1-β2-β3-α2 fold, wherein two arginine salt bridges provide additional stability to the R2D2 dsRBD1. Furthermore, we show that R2D2 dsRBD1 interacts with thermodynamically asymmetric siRNA duplex independent of its 5′-phosphorylation state, whereas R2D2 dsRBD2 prefers to interact with 5'-P siRNA duplex. The mutation of key arginine residues, R53 and R101, in concatenated dsRBDs of R2D2 results in a significant loss of siRNA duplex recognition. Our study deciphers the active roles of R2D2 dsRBDs by showing that dsRBD1 initiates siRNA recognition, whereas dsRBD2 senses 5′-phosphate as an authentic mark on functional siRNA.

Understanding oligomerization and aggregation of the amyloid-β protein is important to elucidate the pathological mechanisms of Alzheimer's disease, and lipid membranes play critical roles in this process. In addition to studies reported by other groups, our group has also reported that the negatively-charged lipid bilayers with a high positive curvature induced α-helix-to-β-sheet conformational transitions of amyloid-β-(1–40) upon increase in protein density on the membrane surface and promoted amyloid fibril formation of the protein. Herein, we investigated detailed mechanisms of the conformational transition and oligomer formation of the amyloid-β protein on the membrane surface. Changes in the fractions of the three protein conformers (free monomer, membrane-bound α-helix-rich conformation, and β-sheet-rich conformation) were determined from the fluorescent spectral changes of the tryptophan probe in the protein. The helix-to-sheet structural transition on the surface was described by a thermodynamic model of octamer formation driven by entropic forces including hydrophobic interactions. These findings provide useful information for understanding the self-assembly of amyloidogenic proteins on lipid membrane surfaces.

Parkinson's disease (PD) is one of many neurodegenerative diseases. The protein associated with PD is α-synuclein (AS). Aggregation of AS protein into oligomers, protofilaments, and finally to fibrils yields to the development of PD. The aggregation process of AS leads to the formation of polymorphic AS fibrils. Herein, we compared four polymorphic full-length AS_1–140 fibrils, using extensive computational tools. The main conclusion of this study emphasizes the role of the structurally packed non-amyloid component (NAC) core domain in AS fibrils. Polymorphic AS fibrils that presented a packed NAC core domain, exhibited more β-sheets and fewer fluctuations in the NAC domain. Hence, these AS fibrils are more stable and populated than the AS fibrils, by which the NAC domains are more exposed, more fluctuate and less packed in the fibrillary structure. Therefore, this study emphasizes the importance of the NAC domain packing in the morphology of AS fibrils. The results obtained in this study will initiate future studies to develop compounds to prevent and inhibit AS aggregation.