Moonlighting peptides with emerging function

Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides

With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as short half-life, limited oral bioavailability and susceptibility to plasma degradation. The rise of computational tools and artificial intelligence (AI) in peptide research has spurred the development of advanced methodologies and databases that are pivotal in the exploration of these complex macromolecules. This perspective delves into integrating AI in peptide development, encompassing classifier methods, predictive systems and the avant-garde design facilitated by deep-generative models like generative adversarial networks and variational autoencoders. There are still challenges, such as the need for processing optimization and careful validation of predictive models. This work outlines traditional strategies for machine learning model construction and training techniques and proposes a comprehensive AI-assisted peptide design and validation pipeline. The evolving landscape of peptide design using AI is emphasized, showcasing the practicality of these methods in expediting the development and discovery of novel peptides within the context of peptide-based drug discovery.

Current therapeutic approaches and promising perspectives of using bioengineered peptides in fighting chemoresistance in triple-negative breast cancer

Breast cancer is a collation of malignancies that manifest in the mammary glands at the early stages. Among breast cancer subtypes, triple-negative breast cancer (TNBC) shows the most aggressive behavior, with apparent stemness features. Owing to the lack of response to hormone therapy and specific targeted therapies, chemotherapy remains the first line of the TNBC treatment. However, the acquisition of resistance to chemotherapeutic agents increase therapy failure, and promotes cancer recurrence and distant metastasis. Invasive primary tumors are the birthplace of cancer burden, though metastasis is a key attribute of TNBC-associated morbidity and mortality. Targeting the chemoresistant metastases-initiating cells via specific therapeutic agents with affinity to the upregulated molecular targets is a promising step in the TNBC clinical management. Exploring the capacity of peptides as biocompatible entities with the specificity of action, low immunogenicity, and robust efficacy provides a principle for designing peptide-based drugs capable of increasing the efficacy of current chemotherapy agents for selective targeting of the drug-tolerant TNBC cells. Here, we first focus on the resistance mechanisms that TNBC cells acquire to evade the effect of chemotherapeutic agents. Next, the novel therapeutic approaches employing tumor-targeting peptides to exploit the mechanisms of drug resistance in chemorefractory TNBC are described.

Antimicrobial peptides with cell-penetrating activity as prophylactic and treatment drugs

Health is fundamental for the development of individuals and evolution of species. In that sense, for human societies is relevant to understand how the human body has developed molecular strategies to maintain health. In the present review, we summarize diverse evidence that support the role of peptides in this endeavor. Of particular interest to the present review are antimicrobial peptides (AMP) and cell-penetrating peptides (CPP). Different experimental evidence indicates that AMP/CPP are able to regulate autophagy, which in turn regulates the immune system response. AMP also assists in the establishment of the microbiota, which in turn is critical for different behavioral and health aspects of humans. Thus, AMP and CPP are multifunctional peptides that regulate two aspects of our bodies that are fundamental to our health: autophagy and microbiota. While it is now clear the multifunctional nature of these peptides, we are still in the early stages of the development of computational strategies aimed to assist experimentalists in identifying selective multifunctional AMP/CPP to control nonhealthy conditions. For instance, both AMP and CPP are computationally characterized as amphipatic and cationic, yet none of these features are relevant to differentiate these peptides from non-AMP or non-CPP. The present review aims to highlight current knowledge that may facilitate the development of AMP’s design tools for preventing or treating illness.

Selective Moonlighting Cell-Penetrating Peptides

Cell penetrating peptides (CPPs) are molecules capable of passing through biological membranes. This capacity has been used to deliver impermeable molecules into cells, such as drugs and DNA probes, among others. However, the internalization of these peptides lacks specificity: CPPs internalize indistinctly on different cell types. Two major approaches have been described to address this problem: (i) targeting, in which a receptor-recognizing sequence is added to a CPP, and (ii) activation, where a non-active form of the CPP is activated once it interacts with cell target components. These strategies result in multifunctional peptides (i.e., penetrate and target recognition) that increase the CPP's length, the cost of synthesis and the likelihood to be degraded or become antigenic. In this work we describe the use of machine-learning methods to design short selective CPP; the reduction in size is accomplished by embedding two or more activities within a single CPP domain, hence we referred to these as moonlighting CPPs. We provide experimental evidence that these designed moonlighting peptides penetrate selectively in targeted cells and discuss areas of opportunity to improve in the design of these peptides.

Cell-penetrating peptide conjugates of indole-3-acetic acid-based DNA primase/Gyrase inhibitors as potent anti-tubercular agents against planktonic and biofilm culture of Mycobacterium smegmatis

Mycobacterium tuberculosis (Mtb) is a pathogenic bacterium that caused 1.5 million fatalities globally in 2018. New strains of Mtb resistant to all known classes of antibiotics pose a global healthcare problem. In this work, we have conjugated novel indole-3-acetic acid-based DNA primase/gyrase inhibitor with cell-penetrating peptide via cleavable and non-cleavable bonds. For non-cleavable linkage, inhibitor was conjugated with peptide via an amide bond to the N-terminus, whereas a cleavable linkage was obtained by conjugating the inhibitor through a disulfide bond. We performed the conjugation of the inhibitor either directly on a solid surface or by using solution-phase chemistry. M. smegmatis (non-pathogenic model of Mtb) was used to determine the minimal inhibitory concentration (MIC) of the synthetic conjugates. Conjugates were found more active as compared to free inhibitor molecules. Strikingly, the conjugate also impairs the development of biofilm, showing a therapeutic potential against infections caused by both planktonic and sessile forms of mycobacterium species.

Antimicrobial Peptide against Mycobacterium Tuberculosis That Activates Autophagy Is an Effective Treatment for Tuberculosis

Mycobacterium tuberculosis (MTB) is the principal cause of human tuberculosis (TB), which is a serious health problem worldwide. The development of innovative therapeutic modalities to treat TB is mainly due to the emergence of multi drug resistant (MDR) TB. Autophagy is a cell-host defense process. Previous studies have reported that autophagy-activating agents eliminate intracellular MDR MTB. Thus, combining a direct antibiotic activity against circulating bacteria with autophagy activation to eliminate bacteria residing inside cells could treat MDR TB. We show that the synthetic peptide, IP-1 (KFLNRFWHWLQLKPGQPMY), induced autophagy in HEK293T cells and macrophages at a low dose (10 μM), while increasing the dose (50 μM) induced cell death; IP-1 induced the secretion of TNFα in macrophages and killed Mtb at a dose where macrophages are not killed by IP-1. Moreover, IP-1 showed significant therapeutic activity in a mice model of progressive pulmonary TB. In terms of the mechanism of action, IP-1 sequesters ATP in vitro and inside living cells. Thus, IP-1 is the first antimicrobial peptide that eliminates MDR MTB infection by combining four activities: reducing ATP levels, bactericidal activity, autophagy activation, and TNFα secretion.

Peptides with Dual Antimicrobial-Anticancer Activity: Strategies to Overcome Peptide Limitations and Rational Design of Anticancer Peptides

Peptides are naturally produced by all organisms and exhibit a wide range of physiological, immunomodulatory, and wound healing functions. Furthermore, they can provide with protection against microorganisms and tumor cells. Their multifaceted performance, high selectivity, and reduced toxicity have positioned them as effective therapeutic agents, representing a positive economic impact for pharmaceutical companies. Currently, efforts have been made to invest in the development of new peptides with antimicrobial and anticancer properties, but the poor stability of these molecules in physiological environments has triggered a bottleneck. Therefore, some tools, such as nanotechnology and in silico approaches can be applied as alternatives to try to overcome these obstacles. In silico studies provide a priori knowledge that can lead to the development of new anticancer peptides with enhanced biological activity and improved stability. This review focuses on the current status of research in peptides with dual antimicrobial-anticancer activity, including advances in computational biology using in silico analyses as a powerful tool for the study and rational design of these types of peptides.

Improving the anticancer effect of afatinib and microRNA by using lipid polymeric nanoparticles conjugated with dual pH-responsive and targeting peptides

Background

The emergence of resistance to chemotherapy or target therapy, tumor metastasis, and systemic toxicity caused by available anticancer drugs hamper the successful colorectal cancer (CRC) treatment. The rise in epidermal growth factor receptor (EGFR; human epidermal growth factor receptor 1; HER1) expression and enhanced phosphorylation of HER2 and HER3 are associated with tumor resistance, metastasis and invasion, thus resulting in poor outcome of anti-CRC therapy. The use of afatinib, a pan-HER inhibitor, is a potential therapeutic approach for resistant CRC. Additionally, miR-139 has been reported to be negatively correlated with chemoresistance, metastasis, and epithelial–mesenchymal transition (EMT) of CRC. Hence, we develop a nanoparticle formulation consisting of a polymer core to carry afatinib or miR-139, which is surrounded by lipids modified with a targeting ligand and a pH-sensitive penetrating peptide to improve the anticancer effect of cargos against CRC cells.

Results

Our findings show that this formulation displays a spherical shape with core/shell structure, homogeneous particle size distribution and negative zeta potential. The prepared formulations demonstrate a pH-sensitive release profile and an enhanced uptake of cargos into human colorectal adenocarcinoma Caco-2 cells in response to the acidic pH. This nanoparticle formulation incorporating afatinib and miR-139 exhibits low toxicity to normal cells but shows a better inhibitory effect on Caco-2 cells than other formulations. Moreover, the encapsulation of afatinib and miR-139 in peptide-modified nanoparticles remarkably induces apoptosis and inhibits migration and resistance of Caco-2 cells via suppression of pan-HER tyrosine kinase/multidrug resistance/metastasis pathways.

Conclusion

This study proposes a multifunctional nanoparticle formulation for targeted modulation of apoptosis/EGFR/HER/EMT/resistance/progression pathways to increase the sensitivity of colon cancer cells to afatinib.

Electronic supplementary material

The online version of this article (10.1186/s12951-019-0519-6) contains supplementary material, which is available to authorized users.

An Antimicrobial Peptide Induces FIG1-Dependent Cell Death During Cell Cycle Arrest in Yeast

Although most antibiotics act on cells that are actively dividing and non-dividing cells such as in microbe sporulation or cancer stem cells represent a new paradigm for the control of disease. In addition to their relevance to health, such antibiotics may promote our understanding of the relationship between the cell cycle and cell death. No antibiotic specifically acting on microbial cells arrested in their cell cycle has been identified until the present time. In this study we used an antimicrobial peptide derived from α-pheromone, IP-1, targeted against MATa Saccharomyces cerevisiae cells in order to assess its dependence on cell cycle arrest to kill cells. Analysis by flow cytometry and fluorescence microscopy of various null mutations of genes involved in biological processes activated by the pheromone pathway (the mitogen-activated protein kinase pathway, cell cycle arrest, cell proliferation, autophagy, calcium influx) showed that IP-1 requires arrest in G₀/G₁ in order to kill yeast cells. Isolating cells in different cell cycle phases by elutriation provided further evidence that entry into cell cycle arrest, and not into G₁ phase, is necessary if our peptide is to kill yeast cells. We also describe a variant of IP-1 that does not activate the pheromone pathway and consequently does not kill yeast cells that express the pheromone’s receptor; the use of this variant peptide in combination with different cell cycle inhibitors that induce cell cycle arrest independently of the pheromone pathway confirmed that it is cell cycle arrest that is required for the cell death induced by this peptide in yeast. We show that the cell death induced by IP-1 differs from that induced by α-pheromone and depends on FIG1 in a way independent of the cell cycle arrest induced by the pheromone. Thus, IP-1 is the first molecule described that specifically kills microbial cells during cell cycle arrest, a subject of interest beyond the process of mating in yeast cells. The experimental system described in this study should be useful in the study of the mechanisms at play in the communication between cell cycle arrest and cell death on other organisms, hence promoting the development of new antibiotics.

Using Confocal Microscopy and Computational Modeling to Investigate the Cell-Penetrating Properties of Antimicrobial Peptides

Antimicrobial peptides (AMPs) may display the ability to penetrate cells, which may be relevant for their antibiotic activity. To investigate the relevance of the penetrating activity for the antibiotic activity of AMPs, here we describe a method based on the combined use of confocal microscopy and computational modeling coupled with cell death kinetics.

Effective Design of Multifunctional Peptides by Combining Compatible Functions

Multifunctionality is a common trait of many natural proteins and peptides, yet the rules to generate such multifunctionality remain unclear. We propose that the rules defining some protein/peptide functions are compatible. To explore this hypothesis, we trained a computational method to predict cell-penetrating peptides at the sequence level and learned that antimicrobial peptides and DNA-binding proteins are compatible with the rules of our predictor. Based on this finding, we expected that designing peptides for CPP activity may render AMP and DNA-binding activities. To test this prediction, we designed peptides that embedded two independent functional domains (nuclear localization and yeast pheromone activity), linked by optimizing their composition to fit the rules characterizing cell-penetrating peptides. These peptides presented effective cell penetration, DNA-binding, pheromone and antimicrobial activities, thus confirming the effectiveness of our computational approach to design multifunctional peptides with potential therapeutic uses. Our computational implementation is available at http://bis.ifc.unam.mx/en/software/dcf.

Most proteins and peptides in nature display multiple activities either by fusing different domains (with different activities) or by evolving multiple activities in a single domain. Understanding which activities may be combined to render multifunctional proteins remains an open question relevant to understanding the organization of living organisms and to improve the design of pharmacological peptides. To address this problem, we introduce the concept of compatible activities, that is, activities that may combine without losing any of these in a single polypeptide chain. To identify compatible activities in peptide sequences, we used a machine-learning approach and discovered that a penetrating activity should be compatible with DNA-binding and antimicrobial activities. To test if these activities may combine without any functional loss, we designed peptide sequences that harbor two independent activities (nuclear localization and pheromone) and experimentally showed that all our designed peptides display penetrability, pheromone, antimicrobial and DNA-binding activities, supporting the idea that multifunctionality may be achieved combining compatible activities.

Autophagy as a target for therapeutic uses of multifunctional peptides

The emergence of complex diseases is promoting a change from one-target to multitarget drugs and peptides are ideal molecules to fulfill this polypharmacologic role. Here we review current status in the design of polypharmacological peptides aimed to treat complex diseases, focusing on tuberculosis. In this sense, combining multiple activities in single molecules is a two-sided sword, as both positive and negative side effects might arise. These polypharmacologic compounds may be directed to regulate autophagy, a catabolic process that enables cells to eliminate intracellular microbes (xenophagy), such as Mycobacterium tuberculosis (MBT). Here we review some strategies to control MBT infection and propose that a peptide combining both antimicrobial and pro-autophagic activities would have a greater potential to limit MBT infection. This endeavor may complement the knowledge gained in understanding the mechanism of action of antibiotics and may lead to the design of better polypharmacological peptides to treat complex diseases such as tuberculosis.

SATPdb: a database of structurally annotated therapeutic peptides

SATPdb (http://crdd.osdd.net/raghava/satpdb/) is a database of structurally annotated therapeutic peptides, curated from 22 public domain peptide databases/datasets including 9 of our own. The current version holds 19192 unique experimentally validated therapeutic peptide sequences having length between 2 and 50 amino acids. It covers peptides having natural, non-natural and modified residues. These peptides were systematically grouped into 10 categories based on their major function or therapeutic property like 1099 anticancer, 10585 antimicrobial, 1642 drug delivery and 1698 antihypertensive peptides. We assigned or annotated structure of these therapeutic peptides using structural databases (Protein Data Bank) and state-of-the-art structure prediction methods like I-TASSER, HHsearch and PEPstrMOD. In addition, SATPdb facilitates users in performing various tasks that include: (i) structure and sequence similarity search, (ii) peptide browsing based on their function and properties, (iii) identification of moonlighting peptides and (iv) searching of peptides having desired structure and therapeutic activities. We hope this database will be useful for researchers working in the field of peptide-based therapeutics.

Enzyme informatics

Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many chemoinformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking.

Cell penetrating peptides and cationic antibacterial peptides: two sides of the same coin

Cell penetrating peptides (CPP) and cationic antibacterial peptides (CAP) have similar physicochemical properties and yet it is not understood how such similar peptides display different activities. To address this question, we used Iztli peptide 1 (IP-1) because it has both CPP and CAP activities. Combining experimental and computational modeling of the internalization of IP-1, we show it is not internalized by receptor-mediated endocytosis, yet it permeates into many different cell types, including fungi and human cells. We also show that IP-1 makes pores in the presence of high electrical potential at the membrane, such as those found in bacteria and mitochondria. These results provide the basis to understand the functional redundancy of CPPs and CAPs.