Rational Design of Antiangiogenic Helical Oligopeptides Targeting the Vascular Endothelial Growth Factor Receptors

Enhancing Chemical Stability through Structural Modification of Antimicrobial Peptides with Non-Proteinogenic Amino Acids

Multidrug-resistant bacteria (MDRB) remain a significant threat to humanity, resulting in over 1.2 million deaths per year. To combat this problem effectively, the development of therapeutic agents with diverse mechanisms of action is crucial. Antimicrobial peptides (AMPs) have emerged as promising next-generation therapeutics to combat infectious diseases, particularly MDRB. By targeting microbial membranes and inducing lysis, AMPs can effectively inhibit microbial growth, making them less susceptible to the development of resistance. Numerous structural advancements have been made to optimize the efficacy of AMPs. Previously, we developed 17KKV-Aib, a derivative of the Magainin 2 (Mag2) peptide, by incorporating a,a-disubstituted amino acids (dAAs) to modulate its secondary structure. 17KKV-Aib demonstrated potent antimicrobial activity against Gram-positive and Gram-negative bacteria, including multidrug-resistant Pseudomonas aeruginosa (MDRP), with minimal hemolytic activity against human red blood cells. However, 17KKV-Aib faces challenges regarding its susceptibility to digestive enzymes, hindering its potential as an antimicrobial agent. In this study, we designed and synthesized derivatives of 17KKV-Aib, replacing Lys residues with 4-aminopiperidine-4-carboxylic acid (Api), which is a cyclized dAA residue possessing cationic properties on its side chain. We investigated the impact of Api substitution on the secondary structure, antimicrobial activity, hemolytic activity, and resistance to digestive enzymes. Our findings revealed that introducing Api residues preserved the helical structure and antimicrobial activity and enhanced resistance to digestive enzymes, with a slight increase in hemolytic activity.

Structure-Based Design of Peptides Targeting VEGF/VEGFRs

Vascular endothelial growth factor (VEGF) and its receptors (VEGFRs) play a main role in the regulation of angiogenesis and lymphangiogenesis. Furthermore, they are implicated in the onset of several diseases such as rheumatoid arthritis, degenerative eye conditions, tumor growth, ulcers and ischemia. Therefore, molecules able to target the VEGF and its receptors are of great pharmaceutical interest. Several types of molecules have been reported so far. In this review, we focus on the structure-based design of peptides mimicking VEGF/VEGFR binding epitopes. The binding interface of the complex has been dissected and the different regions challenged for peptide design. All these trials furnished a better understanding of the molecular recognition process and provide us with a wealth of molecules that could be optimized to be exploited for pharmaceutical applications.

Conformational landscapes of artificial peptides predicted by various force fields: are we ready to simulate β-amino acids?

With the introduction of artificial peptides as antimicrobial agents and organic catalysts, numerous efforts have been made to design foldamers with desirable structures and functions. Computational tools are a helpful proxy for revealing the dynamic structures at atomic resolution and understanding foldamer's complex structure-function relationships. However, the performance of conventional force fields in predicting the structures of artificial peptides has not been systematically evaluated. In this study, we critically assessed three popular force fields, AMBER ff14SB, CHARMM36m, and OPLS-AA/L, in predicting conformational propensities of a β-peptide foldamer at monomer and hexamer levels. Simulation results were compared to those obtained from quantum chemistry calculations and experimental data. We also utilised replica exchange molecular dynamics simulations to investigate the energy landscape of each force field and assess the similarities and differences between force fields. We compared different solvent systems in the AMBER ff14SB and CHARMM36m frameworks and confirmed the unanimous role of hydrogen bonds in shaping energy landscapes. We anticipate that our data will pave the way for further improvements to force fields and for understanding the role of solvents in peptide folding, crystallisation, and engineering.

Conformational switch and multiple supramolecular structures of a newly identified self-assembling protein-mimetic peptide from Pseudomonas aeruginosa YeaZ protein

Protein-mimetic peptides (PMPs) are shorter sequences of self-assembling proteins, that represent remarkable building blocks for the generation of bioinspired functional supramolecular structures with multiple applications. The identification of novel aminoacidic sequences that permit the access to valuable biocompatible materials is an attractive area of research. In this work, in silico analysis of the Pseudomonas aeruginosa YeaZ protein (PaYeaZ) led to the identification of a tetradecapeptide that represents the shortest sequence responsible for the YeaZ-YeaZ dimer formation. Based on its sequence, an innovative 20-meric peptide, called PMP-2, was designed, synthesized, and characterized in terms of secondary structure and self-assembly properties. PMP-2 conserves a helical character and self-assembles into helical nanofibers in non-polar solvents (DMSO and trifluoroethanol), as well as in dilute (0.5 mM) aqueous solutions. In contrast, at higher concentrations (>2 mM) in water, a conformational transition from α-helix to β-sheet occurs, which is accompanied by the Protein-mimetic peptide aggregation into 2D-sheets and formation supramolecular gel in aqueous environment. Our findings reveal a newly identified Protein-mimetic peptide that could turn as a promising candidate for future material applications.

Computational assessment of pigment epithelium-derived factor as an anti-cancer protein during its interaction with the receptors

Pigment epithelium-derived factor (PEDF) is a member of the serine proteinase inhibitor (serpin) with antiangiogenic, anti-tumorigenic, antioxidant, anti-atherosclerosis, antithrombotic, anti-inflammatory, and neuroprotective properties. The PEDF can bind to low-density lipoprotein receptor-related protein 6 (LRP6), laminin (LR), vascular endothelial growth factor receptor 1 (VEGFR1), vascular endothelial growth factor receptor 2 (VEGFR2), and ATP synthase β-subunit receptors. In this study, we aimed to investigate the structural basis of the interaction between PEDF and its receptors using bioinformatics approaches to identify the critical amino acids for designing anticancer peptides. The human ATP synthase β-subunit was predicted by homology modeling. The molecular docking, molecular dynamics (MD) simulation, and Molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) were used to study this protein-receptor complex. The molecular docking showed PEDF could bind to the Laminin and VEGFR2 much stronger than ATP synthase β-subunit, VEGFR1, and LRP6. The PEDF could effectively interact with various receptors during the simulation. The N-terminal of PEDF has an important role in the interaction with the receptors. The MM/PBSA showed the electrostatic (ΔE_Elec) and van der Waals interactions (ΔE_VdW) contributed positively to the binding process of the complexes. The critical amino acids in the binding interaction of PEDF to its receptors in the MD simulation were determined. The interaction mode of 34-mer PEDF to laminin, VEGFR2, and LRP6 were different from VEGFR1, ATP synthase β-subunit. The 34-mer PEDF has an important role in the interaction with different receptors and these critical amino acids can be used for designing peptides for future therapeutic aims.Communicated by Ramaswamy H. Sarma.

Rational Design of Anti-Angiogenic Peptides to Inhibit VEGF/VEGFR2 Interactions for Cancer Therapeutics

BACKGROUND

Angiogenesis is a critical physiological process that plays a key role in tumor progression, metastatic dissemination, and invasion. In the last two decades, the vascular endothelial growth factor (VEGF) signaling pathway has been the area of extensive researches. VEGF executes its special effects by binding to vascular endothelial growth factor receptors (VEGFRs), particularly VEGFR-2.

OBJECTIVE

The inhibition of VEGF/VEGFR2 interaction is known as an effective cancer therapy strategy. The current study pointed to design and model an anti-VEGF peptide based on VEGFR2 binding regions.

METHOD

The large-scale peptide mutation screening was used to achieve a potent peptide with high binding affinity to VEGF for possible application in inhibition of VEGF/VEGFR2 interaction. The AntiCP and Peptide Ranker servers were used to generate the possible peptides library with anticancer activities and prediction of peptides bioactivity. Then, the interaction of VEGF and all library peptides were analyzed using Hex 8.0.0 and ClusPro tools. A number of six peptides with favorable docking scores were achieved. All of the best docking scores of peptides in complexes with VEGF were evaluated to confirm their stability, using molecular dynamics simulation (MD) with the help of the GROMACS software package.

RESULTS

As a result, two antiangiogenic peptides with 13 residues of PepA (NGIDFNRDFFLGL) and PepC (NGIDFNRDKFLFL) were achieved and introduced to inhibit VEGF/VEGFR2 interactions.

CONCLUSIONS

In summary, this study provided new insights into peptide-based therapeutics development for targeting VEGF signaling pathway in tumor cells. PepA and PepC are recommended as potentially promising anticancer agents for further experimental evaluations.

Bioinformatics and Biosimulations as Toolbox for Peptides and Peptidomimetics Design: Where Are We?

Peptides and peptidomimetics are strongly re-emerging as amenable candidates in the development of therapeutic strategies against a plethora of pathologies. In particular, these molecules are extremely suitable to treat diseases in which a major role is played by protein-protein interactions (PPIs). Unlike small organic compounds, peptides display both a high degree of specificity avoiding secondary off-targets effects and a relatively low degree of toxicity. Further advantages are provided by the possibility to easily conjugate peptides to functionalized nanoparticles, so improving their delivery and cellular uptake. In many cases, such molecules need to assume a specific three-dimensional conformation that resembles the bioactive one of the endogenous ligand. To this end, chemical modifications are introduced in the polypeptide chain to constrain it in a well-defined conformation, and to improve the drug-like properties. In this context, a successful strategy for peptide/peptidomimetics design and optimization is to combine different computational approaches ranging from structural bioinformatics to atomistic simulations. Here, we review the computational tools for peptide design, highlighting their main features and differences, and discuss selected protocols, among the large number of methods available, used to assess and improve the stability of the functional folding of the peptides. Finally, we introduce the simulation techniques employed to predict the binding affinity of the designed peptides for their targets.