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The atomistic description of the folding process of a structureless chain of amino acids to a functioning protein is still considered to be a challenge for computational biophysics. An in-depth understanding of protein-folding can be achieved through atomistic dynamics accounting for the solvent effects, combined with the theoretical description of conformational changes in shorter polypeptide chains. The present paper studies the folding transitions in short polypeptide chains consisting of 11 alanine residues in explicit solvent employing all-atom molecular dynamics. The multiple observed folding ↔ unfolding events of the peptide are interpreted as a dynamic process and rationalised through the analysis of the potential energy surface of the system. It is demonstrated that alanine polypeptide folding dynamics is governed by the backbone dihedral angles and involves the formation of spontaneously folded α -helices which emerge and live for ca. 1–20 picoseconds. The helical content within the polypeptide at different temperatures was quantified through a statistical mechanics approach, which showed a reasonable agreement with the results of molecular dynamics simulations and experiments performed for alanine-rich peptides. [ABSTRACT FROM AUTHOR]

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586–599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head–tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes. [ABSTRACT FROM AUTHOR]

α-Amylase inhibitory peptides are used to treat diabetes, but few studies have statistically characterized their interaction with α-amylase. This study performed the molecular docking of α-amylase with inhibitory peptides from published papers. The key sites, side chain chargeability, and hydrogen bond distribution characteristics were analyzed. Molecular dynamics simulated the role of key sites in complex stability. Moreover, partial least squares regression (PLSR) was used to analyze the contribution of different amino acids in the peptides to inhibition. The results showed that, for the α-amylase molecule, His201 and Gln63, with the highest interaction numbers (INs, 15, 15) and hydrogen bond values (HBVs, 11.50, 10.33), are the key sites on α-amylase, and amino acids with positively charged side chains were important for inhibitory activity. For the inhibitory peptides, Asp and Arg had the highest HBVs, and amino acids with charged side chains were more likely to form hydrogen bonds and exert inhibitory activity. In molecular dynamics simulations, peptides involving key binding sites formed more stable complexes with α-amylase than α-amylase alone, suggesting enhanced inhibitory effects. Further, PLSR results showed that amino acids close to the N-terminus of the inhibitory peptide, located in the third and fifth positions, were significantly correlated with its inhibitory activity. In conclusion, this study provides a new approach to developing and screening α-amylase inhibitors. [ABSTRACT FROM AUTHOR]

In this paper, we present a fast and adaptive correlation guided enhanced sampling method (CORE-MD II). The CORE-MD II technique relies, in part, on partitioning of the entire pathway into short trajectories that we refer to as instances. The sampling within each instance is accelerated by adaptive path-dependent metadynamics simulations. The second part of this approach involves kinetic Monte Carlo (kMC) sampling between the different states that have been accessed during each instance. Through the combination of the partition of the total simulation into short non-equilibrium simulations and the kMC sampling, the CORE-MD II method is capable of sampling protein folding without any a priori definitions of reaction pathways and additional parameters. In the validation simulations, we applied the CORE-MD II on the dialanine peptide and the folding of two peptides: TrpCage and TrpZip2. In a comparison with long time equilibrium Molecular Dynamics (MD), 1 µs replica exchange MD (REMD), and CORE-MD I simulations, we find that the level of convergence of the CORE-MD II method is improved by a factor of 8.8, while the CORE-MD II method reaches acceleration factors of ∼120. In the CORE-MD II simulation of TrpZip2, we observe the formation of the native state in contrast to the REMD and the CORE-MD I simulations. The method is broadly applicable for MD simulations and is not restricted to simulations of protein folding or even biomolecules but also applicable to simulations of protein aggregation, protein signaling, or even materials science simulations. [ABSTRACT FROM AUTHOR]

Solid surfaces have been shown to affect the aggregation and assembly of many biomolecular systems. One important example is the formation of protein fibrils, which can occur on a range of biological and synthetic surfaces. The rate of fibrillation depends on both the protein structure and the surface chemistry, with the different molecular and oligomer structures adopted by proteins on surfaces likely to be crucial. In this paper, the aggregation of the model amyloidogenic peptide, A β (16–22), corresponding to a hydrophobic segment of the amyloid beta protein on a gold surface is studied using molecular dynamics simulation. Previous simulations of this peptide on gold surfaces have shown that it adopts conformations on surfaces that are quite different from those in bulk solution. These simulations show that this then leads to significant differences in the oligomer structures formed in solution and on gold surfaces. In particular, oligomers formed on the surface are low in beta-strands so are unlike the structures formed in bulk solution. When oligomers formed in solution adsorb onto gold surfaces they can then restructure themselves. This can then help explain the inhibition of A β (16–22) fibrillation by gold surfaces and nanoparticles seen experimentally. [ABSTRACT FROM AUTHOR]

This paper reviews some of the graph theory-based methods that were recently developed in our group for post-processing molecular dynamics trajectories. We show that the use of algorithmic graph theory not only provides a direct and fast methodology to identify conformers that are sampled over time, but it also allows to follow in time the interconversions between the conformers through graphs of transitions, also provides statistical characterisations, that would otherwise be hard to obtain. Examples for a gas phase peptide and for the more complex inhomogeneous charged air–liquid water interface are presented in order to demonstrate the power of topological 2D-graphs and their versatility and transferability. [ABSTRACT FROM AUTHOR]

Obtaining compounds with specificity for certain isoforms of ion channels is a significant problem of curent physiology and pharmacology. In a series of papers, we have shown that the α-hairpinin fold can serve as a template for the rational design of peptide ligands of potassium channels. Here, we used molecular modeling to optimize the structure of the previously obtained Tk-hefu-10 peptide, a selective KV1.3 channel blocker, with a half-maximal inhibitory concentration (IC50) of ≈150 nM. Molecular dynamics simulation of the Tk-hefu-10–KV1.3 complex provided information on the interaction of individual amino acid residues of the peptide and channel, and the analysis of these interactions made it possible to propose amino acid substitutions in the structure of Tk-hefu-10 to increase its affinity. Novel Tk-hefu-12 peptide is a truncated analog of Tk-hefu-10 by one residue with five substitutions; it is characterized by an IC50 value of ≈70 nM against KV1.3. In addition, there are no methionine residues in the structure of Tk-hefu-12, which makes it possible to obtain Tk-hefu peptides using cyanogen bromide. [ABSTRACT FROM AUTHOR]

Alpha-Synuclein is a presynaptic neuronal protein whose masses are involved in Parkinson's disease, a chronic and progressive neurodegenerative disorder of the central nervous system. It has been observed that upon exposure to anionic surfactants, fluorinated alcohols and membranes in vitro, α -synuclein adopts alpha helix structure and can be fibrillated, while in aqueous solution, the protein is intrinsically disordered and the fibrillation is undesirable. Solvent is one of the most critical environmental parameters in biological studies as well as computer simulations. In this paper, we have investigated the effect of solvent composition on the conformation of α -synuclein protein using molecular dynamics (MD) simulations. For this purpose, the effect of different combinations of water and trifluoroethanol (TFE) solvents on the secondary structure of a fragment of α -synuclein was investigated. Moreover, thermodynamic calculations were performed through a coarse-grained (CG) model of solutions with different concentrations of α -synuclein in the aqueous phase and in TFE medium. The potential of mean force (PMF) calculations was performed as a function of separation distance between the centers of masses of two peptides. The results indicated that in the presence of TFE, the secondary structures have a regular arrangement of amino acids stabilized by hydrogen bonding patterns. In addition, decreasing the TFE concentration reduces the stability of α -helix structures of the protein. It seems that in diluted TFE solutions, high concentrations of water in the medium lead to the breakage of peptide–TFE hydrogen bonds. However, the hydrophobic nature of TFE and α -synuclein molecules prevents further aggregation in the concentrated solutions. The α-synuclein can be fibrillated in the presence of Trifluoroethanol (TFE). Stability of α-helix structure of peptide reduces as TFE concentration decreases. Hydrophobic nature of TFE and α-synuclein molecules prevents further aggregation. [ABSTRACT FROM AUTHOR]

Amyloid-β peptide (Aβ) aggregates are known to be correlated with pathological neurodegenerative diseases. The fibril formation process of such peptides in solution is influenced by several factors, such as the ionic strength of the buffer, concentration, pH, and presence of other molecules, just to mention a few. In this paper, we report a detailed analysis of in vitro Aβ42 fibril formation in the presence of cortisol at different relative concentrations. The thioflavin T fluorescence assay allowed us to monitor the fibril formation kinetics, while a morphological characterization of the aggregates was obtained by atomic force microscopy. Moreover, infrared absorption spectroscopy was exploited to investigate the secondary structure changes along the fibril formation path. Molecular dynamics calculations allowed us to understand the intermolecular interactions with cortisol. The combined results demonstrated the influence of cortisol on the fibril formation process: indeed, at cortisol-Aβ42 concentration ratio (ρ) close to 0.1 a faster organization of Aβ42 fragments into fibrils is promoted, while for ρ = 1 the formation of fibrils is completely inhibited. [ABSTRACT FROM AUTHOR]

The interactions between ligands and polymers are of great interest to drug delivery researches. In this work for the first time, Poly (lactic‐co‐glycolic acid) based polymers with arginine‐glycine‐aspartate (RGD) peptide ligands which are immediately self‐assembled into micellar nanoparticles (NPs) in contact with water have been investigated in the atomistic level. In this regard, the effect of polymer and RGD concentrations on the stability, size, interaction energies and other molecular properties of nanocarriers has been investigated using molecular dynamics simulation. In the next step, the microfluidic micellization and docetaxel (DTX) encapsulation has been simulated in comparison to bulk micellization. Results indicated that by employing only 20 wt % RGD‐conjugated polymer, the particles reach the stable properties and compactness without DTX. But, when the DTX was added, 30 wt.% of RGD‐conjugated polymers that assembled in microfluidic system is the best state nanocarrier for the smart target drug delivery for transfer of DTX drug into the Cancer cell. Comparisons of the results acquired in the current paper confirmed that engineering and tuning the self‐assembly in the interface of phases in microchennel resulted in a precise control on the particle size and resulted in the preparation of smaller and more stable NPs that can be exploited as ultra‐small, smart drug carriers. [ABSTRACT FROM AUTHOR]

In the eighth manuscript, Santos and co-workers [[8]] reported a novel casein-derived antibacterial polypeptide produced through a cheese whey fermentation methodology and capable of inhibiting matrix metalloproteases MMP-2 and MMP-9. The seventh paper, authored by Abioye and co-workers [[7]], reported the identification of three tetrapeptides, TNGQ, MANT, and YMSV, which inhibited islet amyloid polypeptide fibrillation. This Special Issue of the I International Journal of Molecular Sciences i is focused on bioactive peptides in foods or hydrolyzates of food by-products, the methods for the extraction and purification of bioactive peptides, their structural and functional characterization, and the mechanisms of action that regulate their activity and support the reported health benefits. [Extracted from the article]

Microbial ion-pumping rhodopsins (MRs) are extensively studied retinal-binding membrane proteins. However, their biogenesis, including oligomerisation and retinal incorporation, remains poorly understood. The bacterial green-light absorbing proton pump proteorhodopsin (GPR) has emerged as a model protein for MRs and is used here to address these open questions using cryo-electron microscopy (cryo-EM) and molecular dynamics (MD) simulations. Specifically, conflicting studies regarding GPR stoichiometry reported pentamer and hexamer mixtures without providing possible assembly mechanisms. We report the pentameric and hexameric cryo-EM structures of a GPR mutant, uncovering the role of the unprocessed N-terminal signal peptide in the assembly of hexameric GPR. Furthermore, certain proteorhodopsin-expressing bacteria lack retinal biosynthesis pathways, suggesting that they scavenge the cofactor from their environment. We shed light on this hypothesis by solving the cryo-EM structure of retinal-free proteoopsin, which together with mass spectrometry and MD simulations suggests that decanoate serves as a temporary placeholder for retinal in the chromophore binding pocket. Further MD simulations elucidate possible pathways for the exchange of decanoate and retinal, offering a mechanism for retinal scavenging. Collectively, our findings provide insights into the biogenesis of MRs, including their oligomeric assembly, variations in protomer stoichiometry and retinal incorporation through a potential cofactor scavenging mechanism. Microbial rhodopsins are prevalent retinal-binding membrane proteins. Here, authors reveal the roles of the N-terminal signal peptide in oligomerization and of decanoate as a retinal placeholder, providing proteorhodopsin structures and retinal incorporation mechanisms. [ABSTRACT FROM AUTHOR]

Oligonucleotide–peptide conjugates (OPCs) are a promising class of biologically active compounds with proven potential for improving nucleic acid therapeutics. OPCs are commonly recognized as an efficient instrument to enhance the cellular delivery of therapeutic nucleic acids. In addition to this application field, OPCs have an as yet unexplored potential for the post-SELEX optimization of DNA aptamers. In this paper, we report the preparation of designer thrombin aptamer OPCs with peptide side chains anchored to a particular thymidine residue of the aptamer. The current conjugation strategy utilizes unmodified short peptides and support-bound protected oligonucleotides with activated carboxyl functionality at the T3 thymine nucleobase. The respective modification of the oligonucleotide strand was implemented using N3-derivatized thymidine phosphoramidite. Aptamer OPCs retained the G-quadruplex architecture of the parent DNA structure and showed minor to moderate stabilization. In a series of five OPCs, conjugates bearing T3–Ser–Phe–Asn (SFN) or T3–Tyr–Trp–Asn (YWN) side chains exhibited considerably improved anticoagulant characteristics. Molecular dynamics studies of the aptamer OPC complexes with thrombin revealed the roles of the amino acid nature and sequence in the peptide subunit in modulating the anticoagulant activity. [ABSTRACT FROM AUTHOR]

The human protein lysine methyltransferase NSD2 catalyzes dimethylation at H3K36. It has very important roles in development and disease but many mechanistic features and its full spectrum of substrate proteins are unclear. Using peptide SPOT array methylation assays, we investigate the substrate sequence specificity of NSD2 and discover strong readout of residues between G33 (-3) and P38 (+2) on H3K36. Unexpectedly, we observe that amino acid residues different from natural ones in H3K36 are preferred at some positions. Combining four preferred residues led to the development of a super-substrate which is methylated much faster by NSD2 at peptide and protein level. Molecular dynamics simulations demonstrate that this activity increase is caused by distinct hyperactive conformations of the enzyme-peptide complex. To investigate the substrate spectrum of NSD2, we conducted a proteome wide search for nuclear proteins matching the specificity profile and discovered 22 peptide substrates of NSD2. In protein methylation studies, we identify K1033 of ATRX and K819 of FANCM as NSD2 methylation sites and also demonstrate their methylation in human cells. Both these proteins have important roles in DNA repair strengthening the connection of NSD2 and H3K36 methylation to DNA repair. Based on a specificity analysis, ATRX and FANCM are discovered as substrates of NSD2. Moreover, an artificial NSD2 super-substrate is designed that is methylated very fast due to distinct hyperactive conformations of the NSD2-peptide complex. [ABSTRACT FROM AUTHOR]

Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target–ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications. [ABSTRACT FROM AUTHOR]

β-lactoglobulin (BLG) forms amyloid-like aggregates at high temperatures, low pH, and low ionic strengths. At a pH below 2, BLG undergoes hydrolysis into peptides, with N-terminal peptides 1–33 and 1–52 being prone to fibrillization, forming amyloid-like fibrils. Due to their good mechanical properties, BLG amyloids demonstrate great potential for diverse applications, including biosensors, nanocomposites, and catalysts. Consequently, further studies are essential to comprehensively understand the factors governing the formation of BLG amyloid-like morphologies. In this study, all-atom molecular dynamics simulations were employed to explore the aggregation of N-terminal 1–33 and 1–52 BLG peptides under conditions of pH 2 and at 10 mM NaCl concentration. The simulations revealed that the peptides spontaneously assembled into aggregates of varying sizes. The aggregation process was enabled by the low charge of peptides and the presence of hydrophobic residues within them. As the peptides associated into aggregates, there was a concurrent increase in β-sheet structures and the establishment of hydrogen bonds, enhancing the stability of the aggregates. Notably, on average, 1–33 peptides formed larger aggregates compared to their 1–52 counterparts, while the latter exhibited a slightly higher content of β-sheets and higher cluster orderliness. The applied approach facilitated insights into the early stages of amyloid-like aggregation and molecular-level insight into the formation of β-sheets, which serve as nucleation points for further fibril growth. [ABSTRACT FROM AUTHOR]

In situ depot gel is a type of polymeric long-acting injectable (pLAI) drug delivery system; compared to microsphere technology, its preparation process is simpler and more conducive to industrialization. To ensure the chemical stability of peptide ACTY116, we avoided the use of harsh conditions such as high temperatures, high shear mixing, or homogenization; maintaining a water-free and oxygen-free environment was also critical to prevent hydrolysis and oxidation. Molecular dynamics (MDs) simulations were employed to assess the stability mechanism between ACTY116 and the pLAI system. The initial structure of ACTY116 with an alpha helix conformation was constructed using SYBYL-X, and the copolymer PLGA was generated by AMBER 16; results showed that PLGA-based in situ depot gel improved conformational stability of ACTY116 through hydrogen bonds formed between peptide ACTY116 and the components of the pLAI formulation, while PLGA (Poly(DL-lactide-co-glycolide)) also created steric hindrance and shielding effects to prevent conformational changes. As a result, the chemical and conformational stability and in vivo long-acting characteristics of ACTY116 ensure its enhanced efficacy. In summary, we successfully achieved our objective of developing a highly stable peptide-loaded long-acting injectable (LAI) in situ depot gel formulation that is stable for at least 3 months under harsh conditions (40 °C, above body temperature), elucidating the underlying stabilisation mechanism, and the high stability of the ACTY116 pLAI formulation creates favourable conditions for its in vivo pharmacological activity lasting for weeks or even months. [ABSTRACT FROM AUTHOR]

Developing unique mechanisms of action are essential to combat the growing issue of antimicrobial resistance. Supramolecular assemblies combining the improved biostability of non-natural compounds with the complex membrane-attacking mechanisms of natural peptides are promising alternatives to conventional antibiotics. However, for such compounds the direct visual insight on antibacterial action is still lacking. Here we employ a design strategy focusing on an inducible assembly mechanism and utilized electron microscopy (EM) to follow the formation of supramolecular structures of lysine-rich heterochiral β3-peptides, termed lamellin-2K and lamellin-3K, triggered by bacterial cell surface lipopolysaccharides. Combined molecular dynamics simulations, EM and bacterial assays confirmed that the phosphate-induced conformational change on these lamellins led to the formation of striped lamellae capable of incising the cell envelope of Gram-negative bacteria thereby exerting antibacterial activity. Our findings also provide a mechanistic link for membrane-targeting agents depicting the antibiotic mechanism derived from the in-situ formation of active supramolecules. Inspired by the alternating chirality backbone pattern of some effective peptide antimicrobials, here authors design lysine-rich heterochiral peptides that show antimicrobial activity. [ABSTRACT FROM AUTHOR]

There has been a long-standing debate as to how many hydrogen bonds a peptide backbone amide can form in aqueous solution. Hydrogen-bonding structural dynamics of N-ethylpropionamide (a β-peptide model) in water was examined using infrared (IR) spectroscopy. Two amide-I sub bands arise mainly from amide C=O group that forms strong H-bonds with solvent water molecules (SHB state), and minorly from that involving one weak H-bond with water (WHB state). This picture is supported by molecular dynamics simulations and ab-initio calculations. Further, thermodynamics and kinetics of the SHB and WHB species were examined mainly by chemical-exchange two-dimensional IR spectroscopy, yielding an activation energy for the SHB-to-WHB exchange of 13.25 ± 0.52 kJ mol‒1, which occurs in half picosecond at room temperature. Our results provided experimental evidence of an unstable water molecule near peptide backbone, allowing us to gain more insights into the dynamics of the protein backbone hydration. Water at the surface of proteins is known to be critically important in maintaining their conformation and function, but the dynamics of the backbone hydration of peptides remains somewhat elusive. Here, the authors study the hydrogen-bonding structural dynamics of N-ethylpropionamide, a β-peptide model, in heavy water using nonlinear infrared spectroscopy and MD simulations. [ABSTRACT FROM AUTHOR]

Dephosphorylation of pSer51 of the α subunit of translation initiation factor 2 (eIF2αP ) terminates signaling in the integrated stress response (ISR). A trimeric mammalian holophosphatase comprised of a protein phosphatase 1 (PP1) catalytic subunit, the conserved C-terminally located ~70 amino acid core of a substrate-specific regulatory subunit (PPP1R15A/GADD34 or PPP1R15B/CReP) and G-actin (an essential cofactor) efficiently dephosphorylate eIF2αP in vitro. Unlike their viral or invertebrate counterparts, with whom they share the conserved 70 residue core, the mammalian PPP1R15s are large proteins of more than 600 residues. Genetic and cellular observations point to a functional role for regions outside the conserved core of mammalian PPP1R15A in dephosphorylating its natural substrate, the eIF2 trimer. We have combined deep learning technology, all-atom molecular dynamics simulations, X-ray crystallography, and biochemistry to uncover binding of the γ subunit of eIF2 to a short helical peptide repeated four times in the functionally important N terminus of human PPP1R15A that extends past its conserved core. Binding entails insertion of Phe and Trp residues that project from one face of an α-helix formed by the conserved repeats of PPP1R15A into a hydrophobic groove exposed on the surface of eIF2γ in the eIF2 trimer. Replacing these conserved Phe and Trp residues with Ala compromises PPP1R15A function in cells and in vitro. These findings suggest mechanisms by which contacts between a distant subunit of eIF2 and elements of PPP1R15A distant to the holophosphatase active site contribute to dephosphorylation of eIF2αP by the core PPP1R15 holophosphatase and to efficient termination of the ISR in mammals. [ABSTRACT FROM AUTHOR]

Tumor necrosis factor (TNF) receptor 1 (TNFR1) plays a pivotal role in mediating TNF induced downstream signaling and regulating inflammatory response. Recent studies have suggested that TNFR1 activation involves conformational rearrangements of preligand assembled receptor dimers and targeting receptor conformational dynamics is a viable strategy to modulate TNFR1 signaling. Here, we used a combination of biophysical, biochemical, and cellular assays, as well as molecular dynamics simulation to show that an anti-inflammatory peptide (FKCRRWQWRMKK), which we termed FKC, inhibits TNFR1 activation allosterically by altering the conformational states of the receptor dimer without blocking receptor-ligand interaction or disrupting receptor dimerization. We also demonstrated the efficacy of FKC by showing that the peptide inhibits TNFR1 signaling in HEK293 cells and attenuates inflammation in mice with intraperitoneal TNF injection. Mechanistically, we found that FKC binds to TNFR1 cysteine-rich domains (CRD2/3) and perturbs the conformational dynamics required for receptor activation. Importantly, FKC increases the frequency in the opening of both CRD2/3 and CRD4 in the receptor dimer, as well as induces a conformational opening in the cytosolic regions of the receptor. This results in an inhibitory conformational state that impedes the recruitment of downstream signaling molecules. Together, these data provide evidence on the feasibility of targeting TNFR1 conformationally active region and open new avenues for receptor-specific inhibition of TNFR1 signaling. [ABSTRACT FROM AUTHOR]

Antioxidant peptides are a class of biologically active peptides with low molecular weights and stable antioxidant properties that are isolated from proteins. In this review, the progress in research on the activity evaluation, action mechanism, and structure-activity relationships of natural antioxidant peptides are summarized. The methods used to evaluate antioxidant activity are mainly classified into three categories: in vitro chemical, in vitro cellular, and in vivo animal methods. Also, the biological effects produced by these three methods are listed: the scavenging of free radicals, chelation of metal ions, inhibition of lipid peroxidation, inhibition of oxidative enzyme activities, and activation of antioxidant enzymes and non-enzymatic systems. The antioxidant effects of natural peptides primarily consist of the regulation of redox signaling pathways, which includes activation of the Nrf2 pathway and the inhibition of the NF-κB pathway. The structure-activity relationships of the antioxidant peptides are investigated, including the effects of peptide molecular weight, amino acid composition and sequence, and secondary structure on antioxidant activity. In addition, four computer-assisted methods (molecular docking, molecular dynamics simulation, quantum chemical calculations, and the determination of quantitative structure-activity relationships) for analyzing the structure-activity effects of natural peptides are summarized. Thus, this review lays a theoretical foundation for the development of new antioxidants, nutraceuticals, and cosmetics. [ABSTRACT FROM AUTHOR]

Arrest peptides containing RAPP (ArgAlaProPro) motifs have been discovered in both Gram-positive and Gram-negative bacteria, where they are thought to regulate expression of important protein localization machinery components. Here we determine cryo-EM structures of ribosomes stalled on RAPP arrest motifs in both Bacillus subtilis and Escherichia coli. Together with molecular dynamics simulations, our structures reveal that the RAPP motifs allow full accommodation of the A-site tRNA, but prevent the subsequent peptide bond from forming. Our data support a model where the RAP in the P-site interacts and stabilizes a single hydrogen atom on the Pro-tRNA in the A-site, thereby preventing an optimal geometry for the nucleophilic attack required for peptide bond formation to occur. This mechanism to short circuit the ribosomal peptidyltransferase activity is likely to operate for the majority of other RAPP-like arrest peptides found across diverse bacterial phylogenies. Translation of RAPP (Arg-AlaPro-Pro) motifs induces ribosome stalling. Here, structures of RAPP-stalled ribosomes reveal that RAPP motifs short circuit the ribosomal peptidyltransferase activity to induce stalling. [ABSTRACT FROM AUTHOR]

Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we introduce FRETpredict, an easy-to-use Python software to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses a rotamer library approach to describe the FRET probes covalently bound to the protein. The software efficiently and flexibly operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We provide access to rotamer libraries for many commonly used dyes and linkers and describe a general methodology to generate new rotamer libraries for FRET probes. We demonstrate the performance and accuracy of the software for different types of systems: a rigid peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict. The authors present and showcase applications for an easy-to-use Python package to predict FRET efficiencies from ensembles of protein conformations via a rotamer library approach. [ABSTRACT FROM AUTHOR]

We introduce a computational approach for the design of target-specific peptides. Our method integrates a Gated Recurrent Unit-based Variational Autoencoder with Rosetta FlexPepDock for peptide sequence generation and binding affinity assessment. Subsequently, molecular dynamics simulations are employed to narrow down the selection of peptides for experimental assays. We apply this computational strategy to design peptide inhibitors that specifically target β-catenin and NF-κB essential modulator. Among the twelve β-catenin inhibitors, six exhibit improved binding affinity compared to the parent peptide. Notably, the best C-terminal peptide binds β-catenin with an IC50 of 0.010 ± 0.06 μM, which is 15-fold better than the parent peptide. For NF-κB essential modulator, two of the four tested peptides display substantially enhanced binding compared to the parent peptide. Collectively, this study underscores the successful integration of deep learning and structure-based modeling and simulation for target specific peptide design. Here the authors report a computational approach which integrates deep learning and structural modelling to design target-specific peptides. They apply this to β-catenin and NF-κB essential modulator, resulting in improved binding, highlighting the efficacy of this strategy. [ABSTRACT FROM AUTHOR]

Adhesion G protein-coupled receptors (ADGRGs) play critical roles in the reproductive, neurological, cardiovascular, and endocrine systems. In particular, ADGRG2 plays a significant role in Ewing sarcoma cell proliferation, parathyroid cell function, and male fertility. In 2022, a cryo-EM structure was reported for the active ADGRG2 bound by an optimized peptide agonist IP15 and the Gs protein. The IP15 peptide agonist was also modified to antagonists 4PH-E and 4PH-D with mutations of the 4PH residue to Glu and Asp, respectively. However, experimental structures of inactive antagonist-bound ADGRs remain to be resolved, and the activation mechanism of ADGRs such as ADGRG2 is poorly understood. Here, we applied Gaussian accelerated molecular dynamics (GaMD) simulations to probe conformational dynamics of the agonist- and antagonist-bound ADGRG2. By performing GaMD simulations, we were able to identify important low-energy conformations of ADGRG2 in the active, intermediate, and inactive states, as well as explore the binding conformations of each peptide. Moreover, our simulations revealed critical peptide-receptor residue interactions during the deactivation of ADGRG2. In conclusion, through GaMD simulations, we uncovered mechanistic insights into peptide (agonist and antagonist) binding and deactivation of the ADGRG2. These findings will potentially facilitate rational design of new peptide modulators of ADGRG2 and other ADGRs. [ABSTRACT FROM AUTHOR]

T-cell specificity to differentiate between self and non-self relies on T-cell receptor (TCR) recognition of peptides presented by the Major Histocompatibility Complex (MHC). Investigations into the three-dimensional (3D) structures of peptide:MHC (pMHC) complexes have provided valuable insights of MHC functions. Given the limited availability of experimental pMHC structures and considerable diversity of peptides and MHC alleles, it calls for the development of efficient and reliable computational approaches for modeling pMHC structures. Here we present an update of PANDORA and the systematic evaluation of its performance in modelling 3D structures of pMHC class II complexes (pMHC-II), which play a key role in the cancer immune response. PANDORA is a modelling software that can build low-energy models in a few minutes by restraining peptide residues inside the MHC-II binding groove. We benchmarked PANDORA on 136 experimentally determined pMHC-II structures covering 44 unique ab chain pairs. Our pipeline achieves a median backbone Ligand-Root Mean Squared Deviation (L-RMSD) of 0.42 Å on the binding core and 0.88 Å on the whole peptide for the benchmark dataset. We incorporated software improvements to make PANDORA a pan-allele framework and improved the user interface and software quality. Its computational efficiency allows enriching the wealth of pMHC binding affinity and mass spectrometry data with 3D models. These models can be used as a starting point for molecular dynamics simulations or structure-boosted deep learning algorithms to identify MHC-binding peptides. PANDORA is available as a Python package through Conda or as a source installation at https://github.com/X-lab-3D/PANDORA. [ABSTRACT FROM AUTHOR]

The conformational landscapes of peptide/human leucocyte antigen (pHLA) protein complexes encompassing tumor neoantigens provide a rationale for target selection towards autologous T cell, vaccine, and antibody-based therapeutic modalities. Here, using complementary biophysical and computational methods, we characterize recurrent RAS55-64 Q61 neoepitopes presented by the common HLA-A*01:01 allotype. We integrate sparse NMR restraints with Rosetta docking to determine the solution structure of NRASQ61K/HLA-A*01:01, which enables modeling of other common RAS55-64 neoepitopes. Hydrogen/deuterium exchange mass spectrometry experiments alongside molecular dynamics simulations reveal differences in solvent accessibility and conformational plasticity across a panel of common Q61 neoepitopes that are relevant for recognition by immunoreceptors. Finally, we predict binding and provide structural models of NRASQ61K antigens spanning the entire HLA allelic landscape, together with in vitro validation for HLA-A*01:191, HLA-B*15:01, and HLA-C*08:02. Our work provides a basis to delineate the solution surface features and immunogenicity of clinically relevant neoepitope/HLA targets for cancer therapy. The authors use an integrative structural biology approach to elucidate molecular features of the RAS Q61 family of public tumor antigens. This information can be used to develop targeted therapeutics to combat a range of cancers. [ABSTRACT FROM AUTHOR]

Chemokine-like receptor 1 (CMKLR1), also known as chemerin receptor 23 (ChemR23) or chemerin receptor 1, is a chemoattractant G protein–coupled receptor (GPCR) that responds to the adipokine chemerin and is highly expressed in innate immune cells, including macrophages and neutrophils. The signaling pathways of CMKLR1 can lead to both pro- and anti-inflammatory effects depending on the ligands and physiological contexts. To understand the molecular mechanisms of CMKLR1 signaling, we determined a high-resolution cryo-electron microscopy (cryo-EM) structure of the CMKLR1-Gi signaling complex with chemerin9, a nanopeptide agonist derived from chemerin, which induced complex phenotypic changes of macrophages in our assays. The cryo-EM structure, together with molecular dynamics simulations and mutagenesis studies, revealed the molecular basis of CMKLR1 signaling by elucidating the interactions at the ligand-binding pocket and the agonist-induced conformational changes. Our results are expected to facilitate the development of small molecule CMKLR1 agonists that mimic the action of chemerin9 to promote the resolution of inflammation. Chemokine-like receptor 1 (CMKLR1) responds to the adipokine chemerin and is highly expressed in innate immune cells. A high-resolution structure of CMKLR1 in complex with G protein and a peptide agonist, together with mutagenesis and computational simulations studies, reveals mechanisms of peptide agonist recognition, receptor activation, and G protein-coupling. [ABSTRACT FROM AUTHOR]

The theory of fluids is used to modify the integral equations of the reference interaction site model (RISM) approximation. Its applicability to the study of biomolecules solvation is evaluated. Unlike traditional RISM applications, the new integral equation contains an intramolecular correlation matrix that only needs to be calculated once. This allows us to bypass the effort of repeatedly solving RISM equations and the time-consuming averaging of values obtained for each time point of a molecular trajectory. The new approach allows for the assessment of the conformational transience of dissolved molecules while taking into account the effects of solvation. The free energy of oxytocin, which is a peptide hormone, as well as self-assembled ionic peptide complexes calculated using both the traditional RISM and the new RISM with average matrix (RISM-AM) approach are estimated. The free energy of oxytocin calculated using RISM-AM shows that the statistical error does not exceed the error obtained by standard averaging of solutions in the RISM equation. Despite the somewhat ambiguous results obtained for ionic peptide self-assembly using RISM-AM with Lennard–Jones repulsion correction, this method can still be considered applicable for fast molecular dynamics analysis. Since the required computational power can be reduced by at least two orders of magnitude, the medium-matrix RISM is indeed a highly applicable tool for studying macromolecular conformations as well as corresponding solvation effects. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a neurodegenerative disease and the main pathological characteristic of AD is the deposition of Aβ42 in the brain. Inhibition of Aβ42 polymerization is one of the important research directions. Due to the pathological complexity of Alzheimer's disease, studies on Aβ42 polymerization inhibitors have not made significant progress worldwide. Using an independently constructed structure database of oligopeptides, in this study, molecular docking, umbrella sampling analysis of free energy, ThT fluorescence detection of Aβ42 polymerization, transmission electron microscopy, and flow cytometry detection of reactive oxygen species (ROS) and apoptosis were performed to screen tripeptides and pentapeptides that inhibit polymerization. It was found that two tripeptides, i.e., WRR and ERW, bind stably to the core of Aβ42 polymerization in the molecular dynamics analysis, and they significantly inhibited the aggregation of Aβ42 and reduced their cell toxicity in vitro. [ABSTRACT FROM AUTHOR]

Introduction: Reducing brain levels of both soluble and insoluble forms of amyloid beta (Aβ) remains the primary goal of most therapies that target Alzheimer's disease (AD). However, no treatment has so far resulted in patient benefit, and clinical trials of the most promising drug candidates have generally failed due to significant adverse effects. This highlights the need for safer and more selective ways to target and modulate Aβ biogenesis. Methods: Peptide technology has advanced to allow reliable synthesis, purification, and delivery of once‐challenging hydrophobic sequences. This is opening up new routes to target membrane processes associated with disease. Here we deploy a combination of atomic detail molecular dynamics (MD) simulations, living‐cell Förster resonance energy transfer (FRET), and in vitro assays to elucidate the atomic‐detail dynamics, molecular mechanisms, and cellular activity and selectivity of a membrane‐active peptide that targets the Aβ precursor protein (APP). Results: We demonstrate that Aβ biogenesis can be downregulated selectively using an APP occlusion peptide (APPOP). APPOP inhibits Aβ production in a dose‐dependent manner, with a mean inhibitory concentration (IC50) of 450 nM toward exogenous APP and 50 nM toward endogenous APP in primary rat cortical neuronal cultures. APPOP does not impact the γ‐secretase cleavage of Notch‐1, or exhibit toxicity toward cultured primary rat neurons, suggesting that it selectively shields APP from proteolysis. Discussion: Drugs targeting AD need to be given early and for very long periods to prevent the onset of clinical symptoms. This necessitates being able to target Aβ production precisely and without affecting the activity of key cellular enzymes such as γ‐secretase for other substrates. Peptides offer a powerful way for targeting key pathways precisely, thereby reducing the risk of adverse effects. Here we show that protecting APP from proteolytic processing offers a promising route to safely and specifically lower Aβ burden. In particular, we show that the amyloid pathway can be targeted directly and specificically. This reduces the risk of off‐target effects and paves the way for a safe prophylactic treatment. [ABSTRACT FROM AUTHOR]

Underwater adhesives are critical for many applications, including marine coatings, sealants, and medical devices. Research on natural underwater adhesives has shown that L-3,4-dihydroxyphenylalanine (DOPA) and amyloid nanostructures are vital to their adhesive abilities. The fusion of DOPA-containing chains and amyloid-forming peptides creates a new space for designing underwater adhesives capable of multi-surface adhesion. One critical question for this design is the interplay between the DOPA and amyloid-forming peptide regions. Here we investigate the effect of the sequence pattern of DOPA-containing chains on the aggregation conformation of conjugates. Discontinuous molecular dynamics simulations were performed for fourteen DOPA-amyloid conjugates with different sequence patterns along the DOPA-containing portion. The amyloid-forming portion is represented by KLVFFAE from the Aβ42 peptide. The structural properties of the DOPA-amyloid conjugates are characterised by the percentages of ordered secondary structures and residue-residue contact maps. The results showed that certain patterns of DOPA and glycine in the DOPA-containing tail allowed the KLVFFAE portions of the conjugates to form distinct ordered β-sheets, and the DOPA-containing portion and the KLVFFAE portion of the conjugates to remain separated both within the same chain and amongst different chains. Among the designs, the most promising sequences are KLVFFAE-G-YYGYYGYY (where Y represents DOPA) and KLVFFAE-G-YYYYGGGG. [ABSTRACT FROM AUTHOR]

In this paper, we propose and use a new approach for a relatively simple technique for conducting MD simulation (MDS) of various molecular nanostructures, determining the trajectory of the MD run and forming the final structure using external force actions. A molecular dynamics manipulator (MD manipulator) is a controlled MDS type. As an example, the applicability of the developed algorithm for assembling peptide nanotubes (PNT) from linear phenylalanine (F or Phe) chains of different chirality is presented. The most adequate regimes for the formation of nanotubes of right chirality D from the initial L-F and nanotubes of left chirality L of their initial dipeptides D-F modes were determined. We use the method of a mixed (vector–scalar) product of the vectors of the sequence of dipole moments of phenylalanine molecules located along the nanotube helix to calculate the magnitude and sign of chirality of self-assembled helical phenylalanine nanotubes, which shows the validity of the proposed approach. As result, all data obtained correspond to the regularity of the chirality sign change of the molecular structures with a hierarchical complication of their organization. [ABSTRACT FROM AUTHOR]

Despite the accumulating evidence linking the development of Alzheimer's disease (AD) to the aggregation of Aβ peptides and the emergence of Aβ oligomers, the FDA has approved very few anti-aggregation-based therapies over the past several decades. Here, we report the discovery of an Aβ peptide aggregation inhibitor: an ultra-small nanodot called C3N. C3N nanodots alleviate aggregation-induced neuron cytotoxicity, rescue neuronal death, and prevent neurite damage in vitro. Importantly, they reduce the global cerebral Aβ peptides levels, particularly in fibrillar amyloid plaques, and restore synaptic loss in AD mice. Consequently, these C3N nanodots significantly ameliorate behavioral deficits of APP/PS1 double transgenic male AD mice. Moreover, analysis of critical tissues (e.g., heart, liver, spleen, lung, and kidney) display no obvious pathological damage, suggesting C3N nanodots are biologically safe. Finally, molecular dynamics simulations also reveal the inhibitory mechanisms of C3N nanodots in Aβ peptides aggregation and its potential application against AD. In this work, the authors report the utilization of nano-inhibito C3N nanodots to inhibit Aβ peptides aggregation and fibrils disassembly, and show how they induce a cognitive enhancement in treated AD mice. [ABSTRACT FROM AUTHOR]

The adhesion of biomolecules to dental and orthopedic implants is a fundamental step in the process of osseointegration. Short peptide motifs, such as RGD or KRSR, carried by extracellular matrix proteins or coated onto implant surfaces, accelerate cell adhesion and tissue formation. For this reason, understanding the binding mechanisms of adhesive peptides to oxidized surfaces of titanium implants is of paramount importance. We performed molecular dynamics simulations to compare the adhesion properties of 6 peptides, including the tripeptide RGD, its variants KGD and LGD, as well as the tetrapeptide KRSR, its variant LRSR and its truncated version RSR, on anatase, rutile, and amorphous titanium dioxide (TiO2) surfaces. The migration of these molecules from the water phase to the surface was simulated in an aqueous environment. Based on these simulations, we calculated the residence time of each peptide bound to the three different TiO2 structures. It was found that the presence of an N-terminal lysine or arginine amino acid residue resulted in more efficient surface binding. A pulling simulation was performed to detach the adhered molecules. The maximum pulling force and the binding energy were determined from the results of these simulations. The tri- and tetrapeptides had slightly greater adhesion affinity to the amorphous and anatase structure than to rutile in general, however specific surface and peptide binding characters could be detected. The binding energies obtained from our simulations allowed us to rank the adhesion strengths of the studied peptides. [ABSTRACT FROM AUTHOR]

Cell-penetrating peptides (CPPs) are small peptides capable of translocating through biological membranes carrying various attached cargo into cells and even into the nucleus. They may also participate in transcellular transport. Our in silico study intends to model several peptides and their conjugates. We have selected three CPPs with a linear backbone, including penetratin, a naturally occurring oligopeptide; two of its modified sequence analogues (6,14-Phe-penetratin and dodeca-penetratin); and three natural CPPs with a cyclic backbone: Kalata B1, the Sunflower trypsin inhibitor 1 (SFT1), and Momordica cochinchinensis trypsin inhibitor II (MCoTI-II). We have also built conjugates with the small-molecule drug compounds doxorubicin, zidovudine, and rasagiline for each peptide. Molecular dynamics (MD) simulations were carried out with explicit membrane models. The analysis of the trajectories showed that the interaction of penetratin with the membrane led to spectacular rearrangements in the secondary structure of the peptide, while cyclic peptides remained unchanged due to their high conformational stability. Membrane–peptide and membrane–conjugate interactions have been identified and compared. Taking into account well-known examples from the literature, our simulations demonstrated the utility of computational methods for CPP complexes, and they may contribute to a better understanding of the mechanism of penetration, which could serve as the basis for delivering conjugated drug molecules to their intracellular targets. [ABSTRACT FROM AUTHOR]

G protein‐coupled receptors initiate signal transduction in response to ligand binding. Growth hormone secretagogue receptor (GHSR), the focus of this study, binds the 28 residue peptide ghrelin. While structures of GHSR in different states of activation are available, dynamics within each state have not been investigated in depth. We analyze long molecular dynamics simulation trajectories using "detectors" to compare dynamics of the apo and ghrelin‐bound states yielding timescale‐specific amplitudes of motion. We identify differences in dynamics between apo and ghrelin‐bound GHSR in the extracellular loop 2 and transmembrane helices 5–7. NMR of the GHSR histidine residues reveals chemical shift differences in these regions. We evaluate timescale specific correlation of motions between residues of ghrelin and GHSR, where binding yields a high degree of correlation for the first 8 ghrelin residues, but less correlation for the helical end. Finally, we investigate the traverse of GHSR over a rugged energy landscape via principal component analysis. [ABSTRACT FROM AUTHOR]

Studies have suggested that MHC class I (MHC I) molecules fluctuate rapidly between numerous conformational states and these motions support peptide sampling. To date, MHC I intermediates are largely uncharacterized experimentally and remain elusive. Here, we present x-ray crystal structures of HLA-B8 loaded with 20mer peptides that show pronounced distortions at the N-terminus of the groove. Long stretches of N-terminal amino acid residues are missing in the electron density maps creating an open-ended groove. Our structures also reveal highly unusual features in MHC I-peptide interaction at the N-terminus of the groove. Molecular dynamics simulations indicate that the complexes have varying degrees of conformational flexibility in a manner consistent with the structures. We suggest that our structures have captured the remarkable molecular dynamics of MHC I-peptide interaction. The visualization of peptide-dependent conformational motions in MHC I is a major step forward in our conceptual understanding of dynamics in high-affinity peptide selection. The unusual crystal structures of MHC I-peptide complexes provide a visualization of the remarkable ability of the groove to adapt conformationally to bound peptides, explaining how MHC I molecules edit peptides in antigen presentation. [ABSTRACT FROM AUTHOR]

Micro-Exon Genes are a widespread class of genes known for their high variability, widespread in the genome of parasitic trematodes such as Schistosoma mansoni. In this study, we present a strategy that allowed us to solve the structures of three alternatively spliced isoforms from the Schistoma mansoni MEG 2.1 family for the first time. All isoforms are hydrophobic, intrinsically disordered, and recalcitrant to be expressed in high yield in heterologous hosts. We resorted to the chemical synthesis of shorter pieces, before reconstructing the entire sequence. Here, we show that isoform 1 partially folds in a-helix in the presence of trifluoroethanol while isoform 2 features two rigid elbows, that maintain the peptide as disordered, preventing any structuring. Finally, isoform 3 is dominated by the signal peptide, which folds into a-helix. We demonstrated that combining biophysical techniques, like circular dichroism and nuclear magnetic resonance at natural abundance, with in silico molecular dynamics simulation for isoform 1 only, was the key to solve the structure of MEG 2.1. Our results provide a crucial piece to the puzzle of this elusive and highly variable class of proteins. [ABSTRACT FROM AUTHOR]

In molecular dynamics simulations of membrane systems, it is very important to evaluate the interactions between membrane bilayers and other molecules like small compounds, peptides, or proteins. When these interactions lead to local deformations in the membrane, it is essential to fully understand and accurately characterize them, since these deformations can impact the calculation of membrane properties. Here, we introduce MembIT, a simple standalone tool that calculates several membrane properties that are very useful to gauge system equilibration and quality control in molecular dynamics simulations. It has implemented a distinction between local and bulk lipids, which corrects the local deformations, that are often overlooked by other tools. We show examples of MembIT calculations of membrane insertion and deformation values in systems containing POPC and a small drug (sunitinib), a transmembrane peptide (pHLIP), and a transmembrane protein (ADP/ATP carrier). We hope that this tool will be adopted by the scientific community and that the analyses that it provides become good practices in MD simulations of membrane systems. We present a simple standalone tool (MembIT) that calculates several membrane properties from MD simulations. It is useful for studying the membrane thickness, insertion, and deformation induced by different solutes. We showcased its application on three different systems containing sunitinib, pHLIP, or the ADP/ATP carrier in a POPC bilayer. [ABSTRACT FROM AUTHOR]

The chemical evolution of biomolecules was clearly affected by the overall extreme environmental conditions found on Early Earth. Periodic temperature changes inside the Earth's crust may have played a role in the emergence and survival of functional peptides embedded in vesicular compartments. In this study, all-atom molecular dynamic (MD) simulations were used to elucidate the effect of temperature on the properties of functionalized vesicle membranes. A plausible prebiotic system was selected, constituted by a model membrane bilayer from an equimolar mixture of long-chain fatty acids and fatty amines, and an octapeptide, KSPFPFAA, previously identified as an optimized functional peptide in an evolution experiment. This peptide tends to form the largest spontaneous aggregates at higher temperatures, thereby enhancing the pore-formation process and the eventual transfer of essential molecules in a prebiotic scenario. The analyses also suggest that peptide–amphiphile interactions affect the structural properties of the membrane, with a significant increase in the degree of interdigitation at the lowest temperatures under study. [ABSTRACT FROM AUTHOR]

Personalized cancer vaccines based on neoantigens are a new and promising treatment for cancer; however, there are still multiple unresolved challenges to using this type of immunotherapy. Among these, the effective identification of immunogenic neoantigens stands out, since the in silico tools used generate a significant portion of false positives. Inclusion of molecular simulation techniques can refine the results these tools produce. In this work, we explored docking and molecular dynamics to study the association between the stability of peptide–HLA complexes and their immunogenicity, using as a proof of concept two HLA-A2-restricted neoantigens that were already evaluated in vitro. The results obtained were in accordance with the in vitro immunogenicity, since the immunogenic neoantigen ASTN1 remained bound at both ends to the HLA-A2 molecule. Additionally, molecular dynamic simulation suggests that position 1 of the peptide has a more relevant role in stabilizing the N-terminus than previously proposed. Likewise, the mutations may have a "delocalized" effect on the peptide–HLA interaction, which means that the mutated amino acid influences the intensity of the interactions of distant amino acids of the peptide with the HLA. These findings allow us to propose the inclusion of molecular simulation techniques to improve the identification of neoantigens for cancer vaccines. [ABSTRACT FROM AUTHOR]

In this work, we further developed a new approach for modeling the processes of the self-assembly of complex molecular nanostructures using molecular dynamics methods; in particular, using a molecular dynamics manipulator. Previously, this approach was considered using the example of the self-assembly of a phenylalanine helical nanotube. Now, a new application of the algorithm has been developed for implementing a similar molecular dynamic self-assembly into helical structures of peptide nanotubes (PNTs) based on other peptide molecules—namely diphenylalanine (FF) molecules of different chirality L-FF and D-FF. In this work, helical nanotubes were assembled from linear sequences of FF molecules with these initially different chiralities. The chirality of the obtained nanotubes was calculated by various methods, including calculation by dipole moments. In addition, a statistical analysis of the results obtained was performed. A comparative analysis of the structures of nanotubes was also performed using the method of visual differential analysis. It was found that FF PNTs obtained by the MD self-assembly method form helical nanotubes of different chirality. The regimes that form nanotubes of right chirality D from initial L-FF dipeptides and nanotubes of left chirality L from D-FF dipeptides are revealed. This corresponds to the law of changing the sign of the chirality of molecular helical structures as the level of their hierarchical organization becomes more complicated. [ABSTRACT FROM AUTHOR]

Peptide loading of MHC-I molecules plays a critical role in the T cell response to infections and tumors as well as to interactions with inhibitory receptors on natural killer (NK) cells. To facilitate and optimize peptide acquisition, vertebrates have evolved specialized chaperones to stabilize MHC-I molecules during their biosynthesis and to catalyze peptide exchange favoring high affinity or optimal peptides to permit transport to the cell surface where stable peptide/MHC-I (pMHC-I) complexes are displayed and are available for interaction with T cell receptors and any of a host of inhibitory and activating receptors. Although components of the endoplasmic reticulum (ER) resident peptide loading complex (PLC) were identified some 30 years ago, the detailed biophysical parameters that govern peptide selection, binding, and surface display have recently been understood better with advances in structural methods including X-ray crystallography, cryogenic electron microscopy (cryo-EM), and computational modeling. These approaches have provided refined mechanistic illustration of the molecular events involved in the folding of the MHC-I heavy chain, its coordinate glycosylation, assembly with its light chain, b2-microglobulin (b2m), its association with the PLC, and its binding of peptides. Our current view of this important cellular process as it relates to antigen presentation to CD8+ T cells is based on many different approaches: biochemical, genetic, structural, computational, cell biological, and immunological. In this review, taking advantage of recent X-ray and cryo-EM structural evidence and molecular dynamics simulations, examined in the context of past experiments, we attempt a dispassionate evaluation of the details of peptide loading in the MHC-I pathway. By critical evaluation of several decades of investigation, we outline aspects of the peptide loading process that are well-understood and indicate those that demand further detailed investigation. Further studies should contribute not only to basic understanding, but also to applications for immunization and therapy of tumors and infections. [ABSTRACT FROM AUTHOR]

Cancer is among the top causes of death, accounting for an estimated 9.6 million deaths in 2018, it appeared that approximately 500,000 people die from cancer in the United States alone annually. The SHP2 plays a major role in regulation of cell growth, proliferation, and differentiation, and functional upregulation of this enzyme is linked to oncogenesis and developmental disorders. SHP2 activity has been linked to several cancer types for which no drugs are currently available. In our study, we aimed to design peptide inhibitors against the SHP2 mutant. The crystal structure of the human Src SH2-PQpYEEIPI peptide mutant was downloaded from the protein databank. We generated several peptides from the native wild peptide using an in silico mutagenesis method, which showed that changes (P302W, Y304F, E306Q, and Q303A) might boost the peptide's affinity for binding to SHP2. Furthermore, the dynamical stability and binding affinities of the mutated peptide were confirmed using Molecular dynamics simulation and Molecular Mechanics with Generalized Born and Surface Area Solvation free energy calculations. The proposed substitution greatly enhanced the binding affinity at the residue level, according to a study that decomposed energy into its component residues. Our proposed peptide may prevent the spread of cancer by inhibiting SHP2, according to our detailed analyses of binding affinities. [ABSTRACT FROM AUTHOR]

The symptoms of malaria occur during the blood stage of infection, when the parasite replicates within human red blood cells. The human malaria parasite, Plasmodium vivax, selectively invades reticulocytes in a process which requires an interaction between the ectodomain of the human DARC receptor and the Plasmodium vivax Duffy-binding protein, PvDBP. Previous studies have revealed that a small helical peptide from DARC binds to region II of PvDBP (PvDBP-RII). However, it is also known that sulphation of tyrosine residues on DARC affects its binding to PvDBP and these residues were not observed in previous structures. We therefore present the structure of PvDBP-RII bound to sulphated DARC peptide, showing that a sulphate on tyrosine 41 binds to a charged pocket on PvDBP-RII. We use molecular dynamics simulations, affinity measurements and growth-inhibition experiments in parasites to confirm the importance of this interaction. We also reveal the epitope for vaccine-elicited growth-inhibitory antibody DB1. This provides a complete understanding of the binding of PvDBP-RII to DARC and will guide the design of vaccines and therapeutics to target this essential interaction. Plasmodium vivax is one of the major causes of human malaria. To replicate, it must get inside human blood cells, in a processing requiring binding of the parasite PvDBP protein to the human DARC receptor. This study reveals how PvDBP binds to DARC and will guide future vaccine design. [ABSTRACT FROM AUTHOR]

Understanding protein corona formation on nanoparticle surface is crucial to broad applications of nanomedicine and nanotechnologies. In this work, we performed mesoscopic coarse-grained molecular dynamics simulations to study the effect of nanoparticle surface's charge distribution on protein corona formation. Short peptide chains consisting of alternating oppositely charged amino acid residues were grafted on a gold nanoparticle surface to generate surface zwitterionic charge distribution and the ovispirin-1 peptide of high positive charge density was adopted as a model system to examine the zwitterionic nanoparticle's antibiofouling activities. Our mesoscopic simulations showed that the mixing of opposite charges on the nanoparticle's surface can significantly reduce the nanoparticle's electrostatic interactions with ovispirin-1 peptides in water. The formation of protein corona on the gold nanoparticle surface is effectively slowed down by 27% compared to a bare gold nanoparticle, thanks to the grafted zwitterionic peptide chains that introduce enhanced interfacial hydration, reduce hydrophobic interactions between the gold nanoparticle's core and ovispirin-1 peptides, and minimize electrostatic interactions. However, the presence of the small double charge layers as a result of the slightly selective adsorption of different amino acid residues, the local heterogeneity of charge distribution on the nanoparticle surface, and the nanoparticle-ovispirin-1 peptides hydrophobic interactions still result in a monolayer adsorption of ovispirin-1 peptides. Compared to a bare gold nanoparticle, ovispirin-1 peptides are more tilted on the zwitterionic nanoparticle surface. [ABSTRACT FROM AUTHOR]

The usage of glass beads as heterogeneous additives for the crystallization of glycine homopeptides is investigated, whereby glass beads are shown experimentally to increase the rate of crystallization. Induction time analysis indicates that the presence of glass beads acts enhances the kinetic factor for nucleation. These results are compared to those previously obtained by the authors for glycine and diglycine, and it is demonstrated that the increase in nucleation rate is proportional to the peptide chain length. Molecular dynamics simulations confirm that larger molecules exhibit faster nucleation in the presence of glass beads due to an increased number of interactions as observed with the longest hydrogen bond lifetime for triglycine, followed by diglycine and glycine. [ABSTRACT FROM AUTHOR]