Click-modified cyclodextrins as non-viral vectors for neuronal siRNA delivery

RNA interference (RNAi) holds great promise as a strategy to further our understanding of gene function in the central nervous system (CNS) and as a therapeutic approach for neurological and neurodegenerative diseases. However, the potential for its use is hampered by the lack of siRNA delivery vectors, which are both safe and highly efficient. Cyclodextrins have been shown to be efficient and low toxicity gene delivery vectors in various cell types in vitro. However, to date they have not been exploited for delivery of oligonucleotides to neurons. To this end, a modified β-cyclodextrin (CD) vector was synthesised, which complexed siRNA to form cationic nanoparticles of less than 200nm in size. Furthermore, it conferred stability in serum to the siRNA cargo. The in vitro performance of the CD in both immortalised hypothalamic neurons and primary hippocampal neurons was evaluated. The CD facilitated high levels of intracellular delivery of labelled siRNA, whilst maintaining at least 80% cell viability. Significant gene knockdown was achieved, with a reduction in luciferase expression of up to 68% and a reduction in endogenous glyceraldehyde phosphate dehydrogenase (GAPDH) expression of up to 40%. To our knowledge, this is the first time that a modified CD has been used as a safe and efficacious vector for siRNA delivery into neuronal cells

Stabilization of angiotensin-(1-7) by key substitution with a cyclic non-natural amino acid

Angiotensin-(1-7) [Ang-(1-7)], a heptapeptide hormone of the renin-angiotensin-aldosterone system (RAAS), is a promising candidate as a treatment for cancer that reflects its antiproliferative and anti-angiogenic properties. However, the peptide’s therapeutic potential is limited by the short half-life and low bioavailability resulting from rapid enzymatic metabolism by peptidases including angiotensin-converting enzyme (ACE) and dipeptidyl peptidase 3 (DPP 3). We report the facile assembly of three novel Ang-(1-7) analogues by solid-phase peptide synthesis which incorporates the cyclic non-natural δ-amino acid ACCA. The analogues containing the ACCA substitution at the site of ACE cleavage exhibit complete resistance to human ACE, while substitution at the DDP3 cleavage site provided stability against DPP 3 hydrolysis. Furthermore, the analogues retain the anti-proliferative properties of Ang-(1-7) against the 4T1 and HT-1080 cancer cell lines. These results suggest that ACCA-substituted Ang-(1-7) analogues which show resistance against proteolytic degradation by peptidases known to hydrolyze the native heptapeptide may be novel therapeutics in the treatment of cancer

AMP kinase–mediated activation of the BH3-only protein Bim couples energy depletion to stress-induced apoptosis

Disturbances in cellular ion gradients by excitotoxicity promote apoptosis through activation of the Bcl-2 family member Bim

Computational Approaches to Developing Short Cyclic Peptide Modulators of Protein-Protein Interactions

Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating 'difficult' targets, such as protein–protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non 'druglike' by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance—the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.Science Foundation Irelan

Computational survey of peptides derived from disulphide-bonded protein loops that may serve as mediators of protein-protein interactions

BACKGROUND: Bioactive cyclic peptides derived from natural sources are well studied, particularly those derived from non-ribosomal synthetases in fungi or bacteria. Ribosomally synthesised bioactive disulphide-bonded loops represent a large, naturally enriched library of potential bioactive compounds, worthy of systematic investigation. RESULTS: We examined the distribution of short cyclic loops on the surface of a large number of proteins, especially membrane or extracellular proteins. Available three-dimensional structures highlighted a number of disulphide-bonded loops responsible for the majority of the likely binding interactions in a variety of protein complexes, due to their location at protein-protein interfaces. We find that disulphide-bonded loops at protein-protein interfaces may, but do not necessarily, show biological activity independent of their parent protein. Examining the conservation of short disulphide bonded loops in proteins, we find a small but significant increase in conservation inside these loops compared to surrounding residues. We identify a subset of these loops that exhibit a high relative conservation, particularly among peptide hormones. CONCLUSIONS: We conclude that short disulphide-bonded loops are found in a wide variety of biological interactions. They may retain biological activity outside their parent proteins. Such structurally independent peptides may be useful as biologically active templates for the development of novel modulators of protein-protein interactions

Computational survey of peptides derived from disulphide-bonded protein loops that may serve as mediators of protein-protein interactions.

BACKGROUND: Bioactive cyclic peptides derived from natural sources are well studied, particularly those derived from non-ribosomal synthetases in fungi or bacteria. Ribosomally synthesised bioactive disulphide-bonded loops represent a large, naturally enriched library of potential bioactive compounds, worthy of systematic investigation. RESULTS: We examined the distribution of short cyclic loops on the surface of a large number of proteins, especially membrane or extracellular proteins. Available three-dimensional structures highlighted a number of disulphide-bonded loops responsible for the majority of the likely binding interactions in a variety of protein complexes, due to their location at protein-protein interfaces. We find that disulphide-bonded loops at protein-protein interfaces may, but do not necessarily, show biological activity independent of their parent protein. Examining the conservation of short disulphide bonded loops in proteins, we find a small but significant increase in conservation inside these loops compared to surrounding residues. We identify a subset of these loops that exhibit a high relative conservation, particularly among peptide hormones. CONCLUSIONS: We conclude that short disulphide-bonded loops are found in a wide variety of biological interactions. They may retain biological activity outside their parent proteins. Such structurally independent peptides may be useful as biologically active templates for the development of novel modulators of protein-protein interactions.</p

Virtual Screening Using Combinatorial Cyclic Peptide Libraries Reveals Protein Interfaces Readily Targetable by Cyclic Peptides

Protein–protein and protein–peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein–protein and protein–peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein–protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical 'hot spot' interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.Science Foundation Irelan

Virtual Screening Using Combinatorial Cyclic Peptide Libraries Reveals Protein Interfaces Readily Targetable by Cyclic Peptides

Protein–protein and protein–peptide interactions are responsible for the vast majority of biological functions <i>in vivo</i>, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein–protein and protein–peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein–protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical “hot spot” interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened