Enhancement in the rate of conversion of peptide Cys-Pro esters to peptide thioesters by structural modification

We previously reported that the peptide containing a Cys-Pro ester (CPE) moiety is spontaneously transformed into a peptide thioester via an N to S acyl shift followed by diketopiperazine formation. In an attempt to identify more reactive structures for the formation of a peptide thioester, we modified the CPE structure, in which the Pro residue in the CPE moiety was replaced with N-substituted glycine derivatives. These peptides were transformed into a peptide thioester more rapidly. Alternatively, the addition of an amino acid residue at the C-terminus of the CPE moiety also accelerated thioester formation.     

Molecular dynamics simulation of configurational ensembles compatible with experimental FRET efficiency data through a restraint on instantaneous FRET efficiencies

Förster resonance energy transfer (FRET) measurements are widely used to investigate (bio)molecular interactions or/and association. FRET efficiencies, the primary data obtained from this method, give, in combination with the common assumption of isotropic chromophore orientation, detailed insight into the lengthscale of molecular phenomena. This study illustrates the application of a FRET efficiency restraint during classical atomistic molecular dynamics simulations of a mutant mastoparan X peptide in either water or 7 M aqueous urea. The restraint forces acting on the donor and acceptor chromophores ensure that the sampled peptide configurational ensemble satisfies the experimental primary data by modifying interchromophore separation and chromophore transition dipole moment orientations. By means of a conformational cluster analysis, it is seen that indeed different configurational ensembles may be sampled without and with application of the restraint. In particular, while the FRET efficiency and interchromophore distances monitored in an unrestrained simulation may differ from the experimentally‐determined values, they can be brought in agreement with experimental data through usage of the FRET efficiency restraining potential. Furthermore, the present results suggest that the assumption of isotropic chromophore orientation is not always justified. The FRET efficiency restraint allows the generation of configurational ensembles that may not be accessible with unrestrained simulations, and thereby supports a meaningful interpretation of experimental FRET results in terms of the underlying molecular degrees of freedom. Thus, it offers an additional tool to connect the realms of computer and wet‐lab experimentation. © 2014 Wiley Periodicals, Inc.     

N-Aryl Isoleucine Derivatives as Angiotensin?II AT2 Receptor Ligands

A novel series of ligands for the recombinant human AT₂ receptor has been synthesized utilizing a fast and efficient palladium-catalyzed procedure for aminocarbonylation as the key reaction. Molybdenum hexacarbonyl [Mo(CO)₆] was employed as the carbon monoxide source, and controlled microwave heating was applied. The prepared N-aryl isoleucine derivatives, encompassing a variety of amide groups attached to the aromatic system, exhibit binding affinities at best with K_i values in the low micromolar range versus the recombinant human AT₂ receptor. Some of the new nonpeptidic isoleucine derivatives may serve as starting points for further structural optimization. The presented data emphasize the importance of using human receptors in drug discovery programs.     

Fibril Structure Demonstrates the Role of Iodine Labelling on a Pentapeptide Self-Assembly

Iodination has long been employed as a successful labelling strategy to gain structural insights into proteins and other biomolecules via several techniques, including Small Angle X-ray Scattering, Inductively Coupled Plasma Mass Spectrometer (ICP-MS), and single-crystal crystallography. However, when dealing with smaller biomolecular systems, interactions driven by iodine may significantly alter their self-assembly behaviour. The engineering of amyloidogenic peptides for the development of ordered nanomaterials has greatly benefitted from this possibility. Still, to date, iodination has exclusively been applied to aromatic residues. In this work, an aliphatic bis-iodinated amino acid was synthesized and included into a custom pentapeptide, which showed enhanced fibrillogenic behaviour. Peptide single crystal X-ray structure and powder X-ray diffraction on its dried water solution demonstrated the key role of iodine atoms in promoting intermolecular interactions that drive the peptide self-assembly into amyloid fibrils. These findings enlarge the library of halogenated moieties available for directing and engineering the self-assembly of amyloidogenic peptides.     

Chiral Fibers Formation Upon Assembly of Tetraphenylalanine Peptide Conjugated to a PNA Dimer

Self-assembly of biomolecules such as peptides, nucleic acids or their analogues affords supramolecular objects, exhibiting structures and physical properties dependent on the amino-acid or nucleobase composition. Conjugation of the peptide diphenylalanine (FF) to peptide nucleic acids triggers formation of self-assembled structures, mainly stabilized by interactions between FF. In this work we report formation of homogeneous chiral fibers upon self-assembly of the hybrid composed of the tetraphenylalanine peptide (4F) conjugated to the PNA dimer adenine-thymine (at). In this case nucleobases seem to play a key role in determining the morphology and chirality of the fibers. When the PNA “at” is replaced by guanine-cytosine dimer “gc”, disordered structures are observed. Spectroscopic characterization of the self-assembled hybrids, along with AFM and SEM studies is reported. Finally, a structural model consistent with the experimental evidence has also been obtained, showing how the building blocks of 4Fat arrange to give helical fibers.     

Atomistic De-novo Inhibitor Generation-Guided Drug Repurposing for SARS-CoV-2 Spike Protein with Free-Energy Validation by Well-Tempered Metadynamics

Computational drug design is increasingly becoming important with new and unforeseen diseases like COVID-19. In this study, we present a new computational de novo drug design and repurposing method and applied it to find plausible drug candidates for the receptor binding domain (RBD) of SARS-CoV-2 (COVID-19). Our study comprises three steps: atom-by-atom generation of new molecules around a receptor, structural similarity mapping to existing approved and investigational drugs, and validation of their binding strengths to the viral spike proteins based on rigorous all-atom, explicit-water well-tempered metadynamics free energy calculations. By choosing the receptor binding domain of the viral spike protein, we showed that some of our new molecules and some of the repurposable drugs have stronger binding to RBD than hACE2. To validate our approach, we also calculated the free energy of hACE2 and RBD, and found it to be in an excellent agreement with experiments. These pool of drugs will allow strategic repurposing against COVID-19 for a particular prevailing conditions.     

Identification,Characterization and Antihypertensive Effect In Vivo of a Novel ACE-Inhibitory Heptapeptide from Defatted Areca Nut Kernel Globulin Hydrolysates

The areca (Areca catechu L.) nut kernel (ANK) is a good potential protein source for its high protein content of 9.89–14.62 g/100 g and a high yield of around 300,000 tons per year in China. However, utilization of the areca nut kernel is limited. To expand the usage of ANK in pharmaceutical or foods industries, areca nut kernel globulin was extracted and angiotensin-I converting enzyme (ACE) inhibition peptides were prepared and identified using gel chromatography, reversed phase HPLC separation, UPLC-ESI-MS/MS analysis and in silico screening. Finally, a novel ACE-inhibitory heptapeptide (Ala–Pro–Lys–Ile–Glu–Glu–Val) was identified and chemically synthesized. The combination pattern between APKIEEV and ACE, and the inhibition kinetics, antihypertensive effect and endothlein-1 inhibition activity of APKIEEV were studied. The results of the molecular docking demonstrated that APKIEEV could bind to four active sites (not the key active sites) of ACE via short hydrogen bonds and demonstrated high ACE-inhibitory activity (IC₅₀: 550.41 μmol/L). Moreover, APKIEEV exhibited a significantly lowering effect on both the systolic blood pressure and diastolic blood pressure of spontaneously hypertensive rats, and had considerable suppression ability on intracellular endothelin-1. These results highlight the potential usage of APKIEEV as ingredients of antihypertensive drugs or functional foods.     

Electrochemical Peptide-Based Sensors for Foodborne Pathogens Detection

Food safety and quality control pose serious issues to food industry and public health domains, in general, with direct effects on consumers. Any physical, chemical, or biological unexpected or unidentified food constituent may exhibit harmful effects on people and animals from mild to severe reactions. According to the World Health Organization (WHO), unsafe foodstuffs are especially dangerous for infants, young children, elderly, and chronic patients. It is imperative to continuously develop new technologies to detect foodborne pathogens and contaminants in order to aid the strengthening of healthcare and economic systems. In recent years, peptide-based sensors gained much attention in the field of food research as an alternative to immuno-, apta-, or DNA-based sensors. This review presents an overview of the electrochemical biosensors using peptides as molecular bio-recognition elements published mainly in the last decade, highlighting their possible application for rapid, non-destructive, and in situ analysis of food samples. Comparison with peptide-based optical and piezoelectrical sensors in terms of analytical performance is presented. Methods of foodstuffs pretreatment are also discussed.     

PepFun: Open Source Protocols for Peptide-Related Computational Analysis

Peptide research has increased during the last years due to their applications as biomarkers, therapeutic alternatives or as antigenic sub-units in vaccines. The implementation of computational resources have facilitated the identification of novel sequences, the prediction of properties, and the modelling of structures. However, there is still a lack of open source protocols that enable their straightforward analysis. Here, we present PepFun, a compilation of bioinformatics and cheminformatics functionalities that are easy to implement and customize for studying peptides at different levels: sequence, structure and their interactions with proteins. PepFun enables calculating multiple characteristics for massive sets of peptide sequences, and obtaining different structural observables derived from protein-peptide complexes. In addition, random or guided library design of peptide sequences can be customized for screening campaigns. The package has been created under the python language based on built-in functions and methods available in the open source projects BioPython and RDKit. We present two tutorials where we tested peptide binders of the MHC class II and the Granzyme B protease.