Protein epitope mimetics as anti-infectives

Current state and novel outlook on prevention and treatment of rising antibiotic resistance in urinary tract infections

Antibiotic-resistant bacteria are currently an important public health concern posing a serious threat due to their resistance to the current arsenal of antibiotics. Uropathogens Escherichia coli (UPEC), Proteus mirabilis, Klebsiella pneumoniae and Enterococcus faecalis, antibiotic-resistant gram-negative bacteria, cause serious cases of prolonged UTIs, increasing healthcare costs and potentially even leading to the death of an affected patient. This review discusses current knowledge about the increasing resistance to currently recommended antibiotics for UTI therapy, as well as novel therapeutic options. Traditional antibiotics are still a part of the therapy guidelines for UTIs, although they are often not effective and have serious side effects. Hence, novel drugs are being developed, such as combinations of β-lactam antibiotics with cephalosporins and carbapenems. Siderophoric cephalosporins, such as cefiderocol, have shown potential in the treatment of individuals with significant gram-negative bacterial infections, as well as aminoglycosides, fluoroquinolones and tetracyclines that are also undergoing clinical trials. The use of cranberry and probiotics is another potential curative and preventive method that has shown antimicrobial and anti-inflammatory effects. However, further studies are needed to assess the efficacy and safety of probiotics containing cranberry extract for UTI prevention and treatment. An emerging novel approach for UTI treatment is the use of immuno-prophylactic vaccines, as well as different nanotechnology solutions such as nanoparticles (NP). NP have the potential to be used as delivery systems for drugs to specific targets. Furthermore, nanotechnology could enable the development of nano antibiotics with improved features by the application of different NPs in their structure, such as gold and copper NPs. However, further high-quality research is required for the synthesis and testing of these novel molecules, such as safety evaluation and pharmacovigilance.

Antimicrobial resistance crisis: could artificial intelligence be the solution?

Antimicrobial resistance is a global public health threat, and the World Health Organization (WHO) has announced a priority list of the most threatening pathogens against which novel antibiotics need to be developed. The discovery and introduction of novel antibiotics are time-consuming and expensive. According to WHO's report of antibacterial agents in clinical development, only 18 novel antibiotics have been approved since 2014. Therefore, novel antibiotics are critically needed. Artificial intelligence (AI) has been rapidly applied to drug development since its recent technical breakthrough and has dramatically improved the efficiency of the discovery of novel antibiotics. Here, we first summarized recently marketed novel antibiotics, and antibiotic candidates in clinical development. In addition, we systematically reviewed the involvement of AI in antibacterial drug development and utilization, including small molecules, antimicrobial peptides, phage therapy, essential oils, as well as resistance mechanism prediction, and antibiotic stewardship.

Heterogeneous-Backbone Proteomimetic Analogues of Lasiocepsin, a Disulfide-Rich Antimicrobial Peptide with a Compact Tertiary Fold

The emergence of resistance to clinically used antibiotics by bacteria presents a significant problem in public health. Natural antimicrobial peptides (AMPs) are a valuable source of antibiotics that act by a mechanism less prone to the evolutionary development of resistance. In an effort to realize the promise of AMPs while overcoming limitations such as poor biostability, researchers have sought sequence-defined oligomers with artificial amide-based backbones that show membrane-disrupting functions similar to natural agents. Most of this precedent has focused on short peptidomimetic analogues of unstructured chains or secondary folds; however, the natural antimicrobial arsenal includes a number of small- and medium-sized proteins that act via an ordered tertiary structure. Generating proteomimetic analogues of these scaffolds poses a challenge due to the increased complexity of the target for mimicry. Here, we report the development of heterogeneous-backbone variants of lasiocepsin, a 27-residue disulfide-rich AMP found in bee venom that adopts a compact tertiary fold. Iterative cycles of design, synthesis, and biological evaluation yielded analogues of the natural domain with ∼30 to 40% artificial backbone content, comparable antibacterial activity, reduced host cell toxicity, and improved stability to proteolytic degradation. High-resolution structures determined for several variants by NMR provide insights into the interplay among backbone composition, tertiary fold, and biological properties. Collectively, the results reported here broaden the scope of protein functional mimicry by artificial backbone analogues of tertiary folding patterns and suggest protein backbone engineering as a means to tune protein function by exerting site-specific control over protein folded structure.

Cryptic Host Defense Peptides: Multifaceted Activity and Prospects for Medicinal Chemistry

Host defense peptides (HDPs) comprise a heterogeneous group of evolutionarily conserved and biologically active small molecules that are produced by different organisms. HDPs are widely researched because they often have multiple biological activities, for example antimicrobial, immunomodulatory and anticancer activity. In this context, in this review we focus on cryptic HDPs, molecules derived specifically from proteolytic processing of endogenous precursor proteins. Here, we explore the biological activity of such molecules and we further discuss the development of optimized sequences based on these natural cryptic HDPs. In addition, we present clinical-phase studies of cryptic HDPs (natural or optimized), and point out the possible applicability of these molecules in medicinal chemistry.

Antifungal Peptides as Therapeutic Agents

Fungi have been used since ancient times in food and beverage-making processes and, more recently, have been harnessed for the production of antibiotics and in processes of relevance to the bioeconomy. Moreover, they are starting to gain attention as a key component of the human microbiome. However, fungi are also responsible for human infections. The incidence of community-acquired and nosocomial fungal infections has increased considerably in recent decades. Antibiotic resistance development, the increasing number of immunodeficiency- and/or immunosuppression-related diseases and limited therapeutic options available are triggering the search for novel alternatives. These new antifungals should be less toxic for the host, with targeted or broader antimicrobial spectra (for diseases of known and unknown etiology, respectively) and modes of actions that limit the potential for the emergence of resistance among pathogenic fungi. Given these criteria, antimicrobial peptides with antifungal properties, i.e., antifungal peptides (AFPs), have emerged as powerful candidates due to their efficacy and high selectivity. In this review, we provide an overview of the bioactivity and classification of AFPs (natural and synthetic) as well as their mode of action and advantages over current antifungal drugs. Additionally, natural, heterologous and synthetic production of AFPs with a view to greater levels of exploitation is discussed. Finally, we evaluate the current and potential applications of these peptides, along with the future challenges relating to antifungal treatments.

In Silico Approach for Prediction of Antifungal Peptides

This paper describes in silico models developed using a wide range of peptide features for predicting antifungal peptides (AFPs). Our analyses indicate that certain types of residue (e.g., C, G, H, K, R, Y) are more abundant in AFPs. The positional residue preference analysis reveals the prominence of the particular type of residues (e.g., R, V, K) at N-terminus and a certain type of residues (e.g., C, H) at C-terminus. In this study, models have been developed for predicting AFPs using a wide range of peptide features (like residue composition, binary profile, terminal residues). The support vector machine based model developed using compositional features of peptides achieved maximum accuracy of 88.78% on the training dataset and 83.33% on independent or validation dataset. Our model developed using binary patterns of terminal residues of peptides achieved maximum accuracy of 84.88% on training and 84.64% on validation dataset. We benchmark models developed in this study and existing methods on a dataset containing compositionally similar antifungal and non-AFPs. It was observed that binary based model developed in this study preforms better than any model/method. In order to facilitate scientific community, we developed a mobile app, standalone and a user-friendly web server ‘Antifp’ (http://webs.iiitd.edu.in/raghava/antifp).

The interaction of antimicrobial peptides with membranes

The interaction of antimicrobial peptides (AMPs) with biological membranes is in the focus of research since several years, and the most important features and modes of action of AMPs are described in this review. Different model systems can be used to understand such interactions on a molecular level. As a special example, we use 2D and 3D model membranes to investigate the interaction of the natural cyclic (Ar-1) and the synthetic linear molecule arenicin with selected amphiphiles and phospholipids. A panoply of sophisticated methods has been used to analyze these interactions on a molecular level. As a general trend, one observes that cationic antimicrobial peptides do not interact with cationic amphiphiles due to electrostatic repulsion, whereas with non-ionic amphiphiles, the peptide interacts only with aggregated systems and not with monomers. The interaction is weak (hydrophobic interaction) and requires an aggregated state with a large surface (cylindrical micelles). Anionic amphiphiles (as monomers or micelles) exhibit strong electrostatic interactions with the AMPs leading to changes in the peptide conformation. Both types of peptides interact strongly with anionic phospholipid monolayers with a preference for fluid layers. The interaction with a zwitterionic layer is almost absent for the linear derivative but measurable for the cyclic arenicin Ar-1. This is in accordance with biological experiments showing that Ar-1 forms well defined stable pores in phospholipid and lipopolysaccharide (LPS) membranes (cytotoxicity). The synthetic linear arenicin, which is less cytotoxic, does not affect the mammalian lipids to such an extent. The interaction of arenicin with bacterial membrane lipids is dominated by hydrogen bonding together with electrostatic and hydrophobic interactions.

New potent and selective αvβ3 integrin ligands: Macrocyclic peptides containing RGD motif synthesized by sortase A-mediated ligation

Three 14-mer macrocyclic peptides 1-3 containing mono-, di- and tri-RGD structure motif were designed and synthesized by sortase A-mediated ligation in good yields. The results of in intro cell-based biological assays indicated that linear peptide 5 and macrocyclic peptide 1, containing di-RGD and mono-RGD motif respectively, showed remarkable potency and selectivity to α_vβ₃ integrin.

Rational Structure-Based Rescaffolding Approach to De Novo Design of Interleukin 10 (IL-10) Receptor-1 Mimetics

Tackling protein interfaces with small molecules capable of modulating protein-protein interactions remains a challenge in structure-based ligand design. Particularly arduous are cases in which the epitopes involved in molecular recognition have a non-structured and discontinuous nature. Here, the basic strategy of translating continuous binding epitopes into mimetic scaffolds cannot be applied, and other innovative approaches are therefore required. We present a structure-based rational approach involving the use of a regular expression syntax inspired in the well established PROSITE to define minimal descriptors of geometric and functional constraints signifying relevant functionalities for recognition in protein interfaces of non-continuous and unstructured nature. These descriptors feed a search engine that explores the currently available three-dimensional chemical space of the Protein Data Bank (PDB) in order to identify in a straightforward manner regular architectures containing the desired functionalities, which could be used as templates to guide the rational design of small natural-like scaffolds mimicking the targeted recognition site. The application of this rescaffolding strategy to the discovery of natural scaffolds incorporating a selection of functionalities of interleukin-10 receptor-1 (IL-10R1), which are relevant for its interaction with interleukin-10 (IL-10) has resulted in the de novo design of a new class of potent IL-10 peptidomimetic ligands.

Protein/peptide secondary structural mimics: design, characterization, and modulation of protein–protein interactions

This review discusses general aspects of novel artificial peptide secondary structure mimics for modulation of PPIs, their therapeutic applications and future prospects.

Constraining cyclic peptides to mimic protein structure motifs

Many proteins exert their biological activities through small exposed surface regions called epitopes that are folded peptides of well-defined three-dimensional structures. Short synthetic peptide sequences corresponding to these bioactive protein surfaces do not form thermodynamically stable protein-like structures in water. However, short peptides can be induced to fold into protein-like bioactive conformations (strands, helices, turns) by cyclization, in conjunction with the use of other molecular constraints, that helps to fine-tune three-dimensional structure. Such constrained cyclic peptides can have protein-like biological activities and potencies, enabling their uses as biological probes and leads to therapeutics, diagnostics and vaccines. This Review highlights examples of cyclic peptides that mimic three-dimensional structures of strand, turn or helical segments of peptides and proteins, and identifies some additional restraints incorporated into natural product cyclic peptides and synthetic macrocyclic peptidomimetics that refine peptide structure and confer biological properties.

QSAR modeling: where have you been? Where are you going to?

Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.

Amphiphilic cationic β(3R3)-peptides: membrane active peptidomimetics and their potential as antimicrobial agents

We introduce a novel class of membrane active peptidomimetics, the amphiphilic cationic β(3R3)-peptides, and evaluate their potential as antimicrobial agents. The design criteria, the building block and oligomer synthesis as well as a detailed structure-activity relationship (SAR) study are reported. Specifically, infrared reflection absorption spectroscopy (IRRAS) was employed to investigate structural features of amphiphilic cationic β(3R3)-peptide sequences at the hydrophobic/hydrophilic air/liquid interface. Furthermore, Langmuir monolayers of anionic and zwitterionic phospholipids have been used to model the interactions of amphiphilic cationic β(3R3)-peptides with prokaryotic and eukaryotic cellular membranes in order to predict their membrane selectivity and elucidate their mechanism of action. Lastly, antimicrobial activity was tested against Gram-positive M. luteus and S. aureus as well as against Gram-negative E. coli and P. aeruginosa bacteria along with testing hemolytic activity and cytotoxicity. We found that amphiphilic cationic β(3R3)-peptide sequences combine high and selective antimicrobial activity with exceptionally low cytotoxicity in comparison to values reported in the literature. Overall, this study provides further insights into the SAR of antimicrobial peptides and peptidomimetics and indicates that amphiphilic cationic β(3R3)-peptides are strong candidates for further development as antimicrobial agents with high therapeutic index.

Structure and coordination determination of peptide-metal complexes using 1D and 2D ¹H NMR

Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox reactions. The Cu (I) complex of the peptide model of a Cu (I) binding metallochaperone protein, which includes the sequence MTCSGCSRPG (underlined is conserved), was determined in solution under inert conditions by NMR spectroscopy. NMR is a widely accepted technique for the determination of solution structures of proteins and peptides. Due to difficulty in crystallization to provide single crystals suitable for X-ray crystallography, the NMR technique is extremely valuable, especially as it provides information on the solution state rather than the solid state. Herein we describe all steps that are required for full three-dimensional structure determinations by NMR. The protocol includes sample preparation in an NMR tube, 1D and 2D data collection and processing, peak assignment and integration, molecular mechanics calculations, and structure analysis. Importantly, the analysis was first conducted without any preset metal-ligand bonds, to assure a reliable structure determination in an unbiased manner.

The future of peptide-based drugs

The suite of currently used drugs can be divided into two categories - traditional 'small molecule' drugs with typical molecular weights of <500 Da but with oral bioavailability, and much larger 'biologics' typically >5000 Da that are not orally bioavailable and need to be delivered via injection. Due to their small size, conventional small molecule drugs may suffer from reduced target selectivity that often ultimately manifests in human side-effects, whereas protein therapeutics tend to be exquisitely specific for their targets due to many more interactions with them, but this comes at a cost of low bioavailability, poor membrane permeability, and metabolic instability. The time has now come to reinvestigate new drug leads that fit between these two molecular weight extremes, with the goal of combining advantages of small molecules (cost, conformational restriction, membrane permeability, metabolic stability, oral bioavailability) with those of proteins (natural components, target specificity, high potency). This article uses selected examples of peptides to highlight the importance of peptide drugs, some potential new opportunities for their exploitation, and some difficult challenges ahead in this field.

Designing antimicrobial peptides: form follows function

Multidrug-resistant bacteria are a severe threat to public health. Conventional antibiotics are becoming increasingly ineffective as a result of resistance, and it is imperative to find new antibacterial strategies. Natural antimicrobials, known as host defence peptides or antimicrobial peptides, defend host organisms against microbes but most have modest direct antibiotic activity. Enhanced variants have been developed using straightforward design and optimization strategies and are being tested clinically. Here, we describe advanced computer-assisted design strategies that address the difficult problem of relating primary sequence to peptide structure, and are delivering more potent, cost-effective, broad-spectrum peptides as potential next-generation antibiotics.