Peptide based therapeutics and their use for the treatment of neurodegenerative and other diseases

ToxinPred 3.0: An improved method for predicting the toxicity of peptides

Toxicity emerges as a prominent challenge in the design of therapeutic peptides, causing the failure of numerous peptides during clinical trials. In 2013, our group developed ToxinPred, a computational method that has been extensively adopted by the scientific community for predicting peptide toxicity. In this paper, we propose a refined variant of ToxinPred that showcases improved reliability and accuracy in predicting peptide toxicity. Initially, we utilized a similarity/alignment-based approach employing BLAST to predict toxic peptides, which yielded satisfactory accuracy; however, the method suffered from inadequate coverage. Subsequently, we employed a motif-based approach using MERCI software to uncover specific patterns or motifs that are exclusively observed in toxic peptides. The search for these motifs in peptides allowed us to predict toxic peptides with a high level of specificity with poor sensitivity. To overcome the coverage limitations, we developed alignment-free methods using machine/deep learning techniques to balance sensitivity and specificity of prediction. Deep learning model (ANN - LSTM with fixed sequence length) developed using one-hot encoding achieved a maximum AUROC of 0.93 with MCC of 0.71 on an independent dataset. Machine learning model (extra tree) developed using compositional features of peptides achieved a maximum AUROC of 0.95 with MCC of 0.78. We also developed large language models and achieved maximum AUC of 0.93 using ESM2-t33. Finally, we developed hybrid or ensemble methods combining two or more methods to enhance performance. Our specific hybrid method, which combines a motif-based approach with a machine learning-based model, achieved a maximum AUROC of 0.98 with MCC 0.81 on an independent dataset. In this study, all models were trained and tested on 80 % of data using five-fold cross-validation and evaluated on the remaining 20 % of data called independent dataset. The evaluation of all methods on an independent dataset revealed that the method proposed in this study exhibited better performance than existing methods. To cater to the needs of the scientific community, we have developed a standalone software, pip package and web-based server ToxinPred3 (https://github.com/raghavagps/toxinpred3 and https://webs.iiitd.edu.in/raghava/toxinpred3/).

A Computational Approach to Identifying Peptide Inhibitors against White Spot Syndrome Virus: Targeting the Virus Envelope Protein

The white spot syndrome virus (WSSV), a rapidly replicating and highly lethal pathogen that targets Penaeid shrimp, has emerged as one of the most widespread viruses globally due to its high virulence. With effective chemotherapeutics still unavailable, the pursuit of novel and viable strategies against WSSV remains a crucial focus in the field of shrimp farming. The envelope proteins of WSSV are essential for virus entry, serving as excellent targets for the development of antiviral therapeutics. Novel strategies in the design of inhibitory peptides, especially those targeting envelope protein (VP28) located on the surface of the virus particle, play a critical role as a significant virulence factor during the early stages of inherent WSSV infection in shrimp. In this direction, the current computational study focused on identifying self-inhibitory peptides from the hydrophobic membrane regions of the VP28 protein, employing peptide docking and molecular dynamics simulation (MDS) approaches. Such inhibitory peptides could be useful building blocks for the rational engineering of inhibitory therapeutics since they imitate the mechanism of binding to homologous partners used by their origin domain to interact with other molecules. The N-terminal sequence of VP28 has been reported as the potential site for membrane interactions during the virus entry. Moreover, drug delivery systems mediated by chitosan and gold nanoparticles are being developed to enhance the therapeutic efficacy of anti-viral peptides. These systems can increase the solubility, stability, and selectivity of peptides, possessing better qualities than conventional delivery methods. This computational study on self-inhibitory peptides could be a valuable resource for further in vitro and in vivo studies on anti-viral therapeutics in the aquaculture industry.

In silico and in vivo discovery of antioxidant sea cucumber peptides with antineurodegenerative properties

Since oxidative stress is often associated with neurodegenerative diseases, antioxidants are likely to confer protection against neurodegeneration. Despite an increasing number of food-derived peptides being identified as antioxidants, their antineurodegenerative potentials remain largely unexplored. Here, a sea cucumber peptide preparation - the peptide-rich fraction of <3 kDa (UF<3K) obtained by ultrafiltration from Apostichopus japonicus protein hydrolyzate - was found to protect PC12 cells and Caenorhabditis elegans from neurodegeneration by reducing oxidative stress and apoptosis, demonstrating its in vitro and in vivo neuroprotective effects. As many food-originated peptides are cryptides (cryptic peptides - short amino acid sequences encrypted in parent proteins) released in quantities by protein hydrolysis, UF<3K was subjected to sequencing analysis. As expected, a large repertoire of peptides were identified in UF<3K, establishing a sea cucumber cryptome (1238 peptides in total). Then 134 peptides were randomly selected from the cryptome (>10%) and analyzed for their antioxidant activities using a number of in silico bioinformatic programs as well as in vivo experimental assays in C. elegans. From these results, a novel antioxidant peptide - HoloPep#362 (FETLMPLWGNK) - was shown to not only inhibit aggregation of neurodegeneration-associated polygluatmine proteins but also ameliorate behavioral deficits in proteotoxicity nematodes. Proteomic analysis revealed an increased expression of several lysosomal proteases by HoloPep#362, suggesting proteostasis maintenance as a mechanism for its antineurodegenerative action. These findings provide an insight into the health-promoting potential of sea cucumber peptides as neuroprotective nutraceuticals and also into the importance of training in silico peptide bioactivity prediction programs with in vivo experimental data.

Targeted Liposomal Drug Delivery: Overview of the Current Applications and Challenges

In drug development, it is not uncommon that an active substance exhibits efficacy in vitro but lacks the ability to specifically reach its target in vivo. As a result, targeted drug delivery has become a primary focus in the pharmaceutical sciences. Since the approval of Doxil® in 1995, liposomes have emerged as a leading nanoparticle in targeted drug delivery. Their low immunogenicity, high versatility, and well-documented efficacy have led to their clinical use against a wide variety of diseases. That being said, every disease is accompanied by a unique set of physiological conditions, and each liposomal product must be formulated with this consideration. There are a multitude of different targeting techniques for liposomes that can be employed depending on the application. Passive techniques such as PEGylation or the enhanced permeation and retention effect can improve general pharmacokinetics, while active techniques such as conjugating targeting molecules to the liposome surface may bring even further specificity. This review aims to summarize the current strategies for targeted liposomes in the treatment of diseases.

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.

The First Reciprocal Activities of Chiral Peptide Pharmaceuticals: Thymogen and Thymodepressin, as Examples

Peptides show high promise in the targeting and intracellular delivery of next-generation biotherapeutics. The main limitation is peptides' susceptibility to proteolysis in biological systems. Numerous strategies have been developed to overcome this challenge by chemically enhancing the resistance to proteolysis. In nature, amino acids, except glycine, are found in L- and D-enantiomers. The change from one form to the other will change the primary structure of polypeptides and proteins and may affect their function and biological activity. Given the inherent chiral nature of biological systems and their high enantiomeric selectivity, there is rising interest in manipulating the chirality of polypeptides to enhance their biomolecular interactions. In this review, we discuss the first examples of up-and-down homeostasis regulation by two enantiomeric drugs: immunostimulant Thymogen (L-Glu-L-Trp) and immunosuppressor Thymodepressin (D-Glu(D-Trp)). This study shows the perspective of exploring chirality to remove the chiral wall between L- and D-biomolecules. The selected clinical result will be discussed.

Synthesis and Biological Activities of Some Metal Complexes of Peptides: A Review

Peptides, both natural and synthetic, are well suited for a wide range of purposes and offer versatile applications in different fields such as biocatalysts, injectable hydrogels, tumor treatment, and drug delivery. The research of the better part of the cited papers was conducted using various database platforms such as MetalPDB. The rising prominence of therapeutic peptides encompasses anticancer, antiviral, antimicrobial, and anti-neurodegenerative properties. The metals Na, K, Mg, Ca, Fe, Mn, Co, Cu, Zn, and Mo are ten of the twenty elements that are considered essential for life. Crucial for understanding the biological role of metals is the exploration of metal-bound proteins and peptides. Aside from essential metals, there are other non-essential metals that also interact biologically, exhibiting either therapeutic or toxic effects. Irregularities in metal binding contribute to diseases like Alzheimer's, neurodegenerative disorders, Wilson's, and Menkes disease. Certain metal complexes have potential applications as radiopharmaceuticals. The examination of these complexes was achieved by preforming UV-Vis, IR, EPR, NMR spectroscopy, and X-ray analysis. This summary, although unable to cover all of the studies in the field, offers a review of the ongoing experimentation and is a basis for new ideas, as well as strategies to explore and gain knowledge from the extensive realm of peptide-chelated metals and biotechnologies.

New Insights into Antioxidant Peptides: An Overview of Efficient Screening, Evaluation Models, Molecular Mechanisms, and Applications

Antioxidant peptides are currently a hotspot in food science, pharmaceuticals, and cosmetics. In different fields, the screening, activity evaluation, mechanisms, and applications of antioxidant peptides are the pivotal areas of research. Among these topics, the efficient screening of antioxidant peptides stands at the forefront of cutting-edge research. To this end, efficient screening with novel technologies has significantly accelerated the research process, gradually replacing the traditional approach. After the novel antioxidant peptides are screened and identified, a time-consuming activity evaluation is another indispensable procedure, especially in in vivo models. Cellular and rodent models have been widely used for activity evaluation, whilst non-rodent models provide an efficient solution, even with the potential for high-throughput screening. Meanwhile, further research of molecular mechanisms can elucidate the essence underlying the activity, which is related to several signaling pathways, including Keap1-Nrf2/ARE, mitochondria-dependent apoptosis, TGF-β/SMAD, AMPK/SIRT1/PGC-1α, PI3K/Akt/mTOR, and NF-κB. Last but not least, antioxidant peptides have broad applications in food manufacture, therapy, and the cosmetics industry, which requires a systematic review. This review introduces novel technologies for the efficient screening of antioxidant peptides, categorized with a new vision. A wide range of activity evaluation assays, encompassing cellular models, as well as rodent and non-rodent models, are provided in a comprehensive manner. In addition, recent advances in molecular mechanisms are analyzed with specific cases. Finally, the applications of antioxidant peptides in food production, therapy, and cosmetics are systematically reviewed.

Capillary electrophoresis in the analysis of therapeutic peptides-A review

Therapeutic peptides are a growing class of innovative drugs with high efficiency and a low risk of adverse effects. These biomolecules fall within the molecular mass range between that of small molecules and proteins. However, their inherent instability and potential for degradation underscore the importance of reliable and effective analytical methods for pharmaceutical quality control, therapeutic drug monitoring, and compliance testing. Liquid chromatography-mass spectrometry (LC-MS) has long time been the "gold standard" conventional method for peptide analysis, but capillary electrophoresis (CE) is increasingly being recognized as a complementary and, in some cases, superior, highly efficient, green, and cost-effective alternative technique. CE can separate peptides composed of different amino acids owing to differences in their net charge and size, determining their migration behavior in an electric field. This review provides a comprehensive overview of therapeutic peptides that have been used in the clinical environment for the last 25 years. It describes the properties, classification, current trends in development, and clinical use of therapeutic peptides. From the analytical point of view, it discusses the challenges associated with the analysis of therapeutic peptides in pharmaceutical and biological matrices, as well as the evaluation of CE as a whole and the comparison with LC methods. The article also highlights the use of microchip electrophoresis, nonaqueous CE, and nonconventional hydrodynamically closed CE systems and their applications. Overall, the article emphasizes the importance of developing new CE-based analytical methods to ensure the high quality, safety, and efficacy of therapeutic peptides in clinical practice.

Nose-to-Brain (N2B) Delivery: An Alternative Route for the Delivery of Biologics in the Management and Treatment of Central Nervous System Disorders

In recent years, there have been a growing number of small and large molecules that could be used to treat diseases of the central nervous system (CNS). Nose-to-brain delivery can be a potential option for the direct transport of molecules from the nasal cavity to different brain areas. This review aims to provide a compilation of current approaches regarding drug delivery to the CNS via the nose, with a focus on biologics. The review also includes a discussion on the key benefits of nasal delivery as a promising alternative route for drug administration and the involved pathways or mechanisms. This article reviews how the application of various auxiliary agents, such as permeation enhancers, mucolytics, in situ gelling/mucoadhesive agents, enzyme inhibitors, and polymeric and lipid-based systems, can promote the delivery of large molecules in the CNS. The article also includes a discussion on the current state of intranasal formulation development and summarizes the biologics currently in clinical trials. It was noted that significant progress has been made in this field, and these are currently being applied to successfully transport large molecules to the CNS via the nose. However, a deep mechanistic understanding of this route, along with the intimate knowledge of various excipients and their interactions with the drug and nasal physiology, is still necessary to bring us one step closer to developing effective formulations for nasal-brain drug delivery.

Neuroprotective Action of Humanin and Humanin Analogues: Research Findings and Perspectives

Humanin is a 24-mer peptide first reported in the early 2000s as a new neuroprotective/cytoprotective factor rescuing neuronal cells from death induced by various Alzheimer's disease-associated insults. Nowadays it is known that humanin belongs to the novel class of the so-called mitochondrial-derived peptides (which are encoded by mitochondrial DNA) and has been shown to exert beneficial cytoprotective effects in a series of in vitro and/or in vivo experimental models of human diseases, including not only neurodegenerative disorders but other human diseases as well (e.g., age-related macular degeneration, cardiovascular diseases, or diabetes mellitus). This review article is focused on the presentation of recent in vitro and in vivo research results associated with the neuroprotective action of humanin as well as of various, mainly synthetic, analogues of the peptide; moreover, the main mode(s)/mechanism(s) through which humanin and humanin analogues may exert in vitro and in vivo regarding neuroprotection have been reported. The prospects of humanin and humanin analogues to be further investigated in the frame of future research endeavors against neurodegenerative/neural diseases have also been briefly discussed.

Electrochemical Nickel-Catalyzed Selective Inter- and Intramolecular Arylations of Cysteine-Containing Peptides

Here we report a simple electrochemical route towards the synthesis of S-arylated peptides by a site selective coupling of peptides with aryl halides under base free conditions. This approach demonstrates the power of electrochemistry to access both highly complex peptide conjugates and cyclic peptides.

The Identification of a Novel Spider Toxin Peptide, Lycotoxin-Pa2a, with Antibacterial and Anti-Inflammatory Activities

With the increasing challenge of controlling infectious diseases due to the emergence of antibiotic-resistant strains, the importance of discovering new antimicrobial agents is rapidly increasing. Animal venoms contain a variety of functional peptides, making them a promising platform for pharmaceutical development. In this study, a novel toxin peptide with antibacterial and anti-inflammatory activities was discovered from the spider venom gland transcriptome by implementing computational approaches. Lycotoxin-Pa2a (Lytx-Pa2a) showed homology to known-spider toxin, where functional prediction indicated the potential of both antibacterial and anti-inflammatory peptides without hemolytic activity. The colony-forming assay and minimum inhibitory concentration test showed that Lytx-Pa2a exhibited comparable or stronger antibacterial activity against pathogenic strains than melittin. Following mechanistic studies revealed that Lytx-Pa2a disrupts both cytoplasmic and outer membranes of bacteria while simultaneously inducing the accumulation of reactive oxygen species. The peptide exerted no significant toxicity when treated to human primary cells, murine macrophages, and bovine red blood cells. Moreover, Lytx-Pa2a alleviated lipopolysaccharide-induced inflammation in mouse macrophages by suppressing the expression of inflammatory mediators. These findings not only suggested that Lytx-Pa2a with dual activity can be utilized as a new antimicrobial agent for infectious diseases but also demonstrated the implementation of in silico methods for discovering a novel functional peptide, which may enhance the future utilization of biological resources.

A prediction model for blood-brain barrier penetrating peptides based on masked peptide transformers with dynamic routing

Blood-brain barrier penetrating peptides (BBBPs) are short peptide sequences that possess the ability to traverse the selective blood-brain interface, making them valuable drug candidates or carriers for various payloads. However, the in vivo or in vitro validation of BBBPs is resource-intensive and time-consuming, driving the need for accurate in silico prediction methods. Unfortunately, the scarcity of experimentally validated BBBPs hinders the efficacy of current machine-learning approaches in generating reliable predictions. In this paper, we present DeepB3P3, a novel framework for BBBPs prediction. Our contribution encompasses four key aspects. Firstly, we propose a novel deep learning model consisting of a transformer encoder layer, a convolutional network backbone, and a capsule network classification head. This integrated architecture effectively learns representative features from peptide sequences. Secondly, we introduce masked peptides as a powerful data augmentation technique to compensate for small training set sizes in BBBP prediction. Thirdly, we develop a novel threshold-tuning method to handle imbalanced data by approximating the optimal decision threshold using the training set. Lastly, DeepB3P3 provides an accurate estimation of the uncertainty level associated with each prediction. Through extensive experiments, we demonstrate that DeepB3P3 achieves state-of-the-art accuracy of up to 98.31% on a benchmarking dataset, solidifying its potential as a promising computational tool for the prediction and discovery of BBBPs.

Defensin-based therapeutic peptide design in attenuating V30M TTR-induced Familial Amyloid Polyneuropathy

In the present study, we aimed to formulate an effective therapeutic candidate against V30M mutant transthyretin (TTR) protein to hinder its pathogenic misfolding. Nicotiana alata Defensin 1 (NaD1) Antimicrobial Peptide (AMP) was availed due to its tendency to aggregate, which may compete for aggregation-prone regions of pathogenic TTR protein. Based on NaD1's potential to bind to V30M TTR, we proposed NaD1-derived tetra peptides: CKTE and SKIL to be initial therapeutic candidates. Based on their association with mutant TTR protein, CKTE tetra peptide showed considerable interaction and curative potential as compared to SKIL tetra peptide. Further analyses from discrete molecular dynamics simulation corroborate CKTE tetra peptide's effectiveness as a 'beta-sheet breaker' against V30M TTR. Various post-simulation trajectory analyses suggested that CKTE tetra peptide alters the structural dynamics of pathogenic V30M TTR protein, thereby potentially attenuating its beta-sheets and impeding its aggregation. Normal mode analysis simulation corroborated that V30M TTR conformation is altered upon its interaction with CKTE peptide. Moreover, simulated thermal denaturation findings suggested that CKTE-V30M TTR complex is more susceptible to simulated denaturation, relative to pathogenic V30M TTR; further substantiating CKTE peptide's potential to alter V30M TTR's pathogenic conformation. Moreover, the residual frustration analysis augmented CKTE tetra peptide's proclivity in reorienting the conformation of V30M TTR. Therefore, we predicted that the tetra peptide, CKTE could be a promising therapeutic candidate in mitigating the amyloidogenic detrimental effects of V30M TTR-mediated familial amyloid polyneuropathy (FAP).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03646-4.

Multiple Metabolites Derived from Mushrooms and Their Beneficial Effect on Alzheimer's Diseases

Mushrooms with edible and medicinal potential have received widespread attention because of their diverse biological functions, nutritional value, and delicious taste, which are closely related to their rich active components. To date, many bioactive substances have been identified and purified from mushrooms, including proteins, carbohydrates, phenols, and vitamins. More importantly, molecules derived from mushrooms show great potential to alleviate the pathological manifestations of Alzheimer's disease (AD), which seriously affects the health of elderly people. Compared with current therapeutic strategies aimed at symptomatic improvement, it is particularly important to identify natural products from resource-rich mushrooms that can modify the progression of AD. This review summarizes recent investigations of multiple constituents (carbohydrates, peptides, phenols, etc.) isolated from mushrooms to combat AD. In addition, the underlying molecular mechanisms of mushroom metabolites against AD are discussed. The various mechanisms involved in the antiAD activities of mushroom metabolites include antioxidant and anti-neuroinflammatory effects, apoptosis inhibition, and stimulation of neurite outgrowth, etc. This information will facilitate the application of mushroom-derived products in the treatment of AD. However, isolation of new metabolites from multiple types of mushrooms and further in vivo exploration of the molecular mechanisms underlying their antiAD effect are still required.

Strategic Approaches to Improvise Peptide Drugs as Next Generation Therapeutics

In recent years, the occurrence of a wide variety of drug-resistant diseases has led to an increase in interest in alternate therapies. Peptide-based drugs as an alternate therapy hold researchers' attention in various therapeutic fields such as neurology, dermatology, oncology, metabolic diseases, etc. Previously, they had been overlooked by pharmaceutical companies due to certain limitations such as proteolytic degradation, poor membrane permeability, low oral bioavailability, shorter half-life, and poor target specificity. Over the last two decades, these limitations have been countered by introducing various modification strategies such as backbone and side-chain modifications, amino acid substitution, etc. which improve their functionality. This has led to a substantial interest of researchers and pharmaceutical companies, moving the next generation of these therapeutics from fundamental research to the market. Various chemical and computational approaches are aiding the production of more stable and long-lasting peptides guiding the formulation of novel and advanced therapeutic agents. However, there is not a single article that talks about various peptide design approaches i.e., in-silico and in-vitro along with their applications and strategies to improve their efficacy. In this review, we try to bring different aspects of peptide-based therapeutics under one article with a clear focus to cover the missing links in the literature. This review draws emphasis on various in-silico approaches and modification-based peptide design strategies. It also highlights the recent progress made in peptide delivery methods important for their enhanced clinical efficacy. The article would provide a bird's-eye view to researchers aiming to develop peptides with therapeutic applications.

Graphical Abstract

Aggregation Limiting Cell-Penetrating Peptides Derived from Protein Signal Sequences

Alzheimer's disease (AD) is the most common neurodegenerative disease (ND) and the leading cause of dementia. It is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in the biological alterations and the causes of the disease. One of the hallmarks of the AD is the progression of plaques of aggregated amyloid-β (Aβ) or neurofibrillary tangles of Tau. Currently there is no efficient treatment for the AD. Nevertheless, several breakthroughs in revealing the mechanisms behind progression of the AD have led to the discovery of possible therapeutic targets. Some of these include the reduction in inflammation in the brain, and, although highly debated, limiting of the aggregation of the Aβ. In this work we show that similarly to the Neural cell adhesion molecule 1 (NCAM1) signal sequence, other Aβ interacting protein sequences, especially derived from Transthyretin, can be used successfully to reduce or target the amyloid aggregation/aggregates in vitro. The modified signal peptides with cell-penetrating properties reduce the Aβ aggregation and are predicted to have anti-inflammatory properties. Furthermore, we show that by expressing the Aβ-EGFP fusion protein, we can efficiently assess the potential for reduction in aggregation, and the CPP properties of peptides in mammalian cells.

The manifold role of octapeptide repeats in prion protein assembly

Prion protein misfolding is associated with fatal neurodegenerative disorders such as kuru, Creutzfeldt-Jakob disease, and several animal encephalopathies. While the C-terminal 106-126 peptide has been well studied for its role in prion replication and toxicity, the octapeptide repeat (OPR) sequence found within the N-terminal domain has been relatively under explored. Recent findings that the OPR has both local and long-range effects on prion protein folding and assembly, as well as its ability to bind and regulate transition metal homeostasis, highlights the important role this understudied region may have in prion pathologies. This review attempts to collate this knowledge to advance a deeper understanding on the varied physiologic and pathologic roles the prion OPR plays, and connect these findings to potential therapeutic modalities focused on OPR-metal binding. Continued study of the OPR will not only elucidate a more complete mechanistic model of prion pathology, but may enhance knowledge on other neurodegenerative processes underlying Alzheimer's, Parkinson's, and Huntington's diseases.

An Integrated Machine Learning Model To Spot Peptide Binding Pockets in 3D Protein Screening

The prediction of peptide-protein binding sites is of utmost importance to tackle the onset of severe neurodegenerative diseases and cancer. In this work, we detail a novel machine learning model based on Linear Discriminant Analysis (LDA) demonstrating to be highly predictive in detecting the putative protein binding regions of small peptides. Starting from 439 high-quality pockets derived from peptide-protein crystallographic complexes, three sets of well-established peptide-binding regions were first selected through a Partitioning Around Medoids (PAM) clustering algorithm based on morphological and energetic 3D GRID-MIF molecular descriptors. Next, the best combination between all the putative interacting peptide pockets and related GRID-MIF scores was automatically explored by using the LDA-based protocol implemented in BioGPS. This approach proved successful to recognize the actual interacting peptide regions (that is, AUC = 0.86 and partial ROC enrichment at 5% of 0.48) from all the other pockets of the protein. Validated on two external collections sets, including 445 and 347 crystallographic peptide-protein complexes, our LDA-based model could be effective to further run peptide-protein virtual screening campaigns.

Studying Peptide-Metal Ion Complex Structures by Solution-State NMR

Metal chelation can provide structural stability and form reactive centers in metalloproteins. Approximately one third of known protein structures are metalloproteins, and metal binding, or the lack thereof, is often implicated in disease, making it necessary to be able to study these systems in detail. Peptide-metal complexes are both present in nature and can provide a means to focus on the binding region of a protein and control experimental variables to a high degree. Structural studies of peptide complexes with metal ions by nuclear magnetic resonance (NMR) were surveyed for all the essential metal complexes and many non-essential metal complexes. The various methods used to study each metal ion are presented together with examples of recent research. Many of these metal systems have been individually reviewed and this current overview of NMR studies of metallopeptide complexes aims to provide a basis for inspiration from structural studies and methodology applied in the field.

Peptide Utility (PU) search server: A new tool for peptide sequence search from multiple databases

Proteins are essential building blocks in humans that have garnered huge attention from researchers worldwide due to their numerous therapeutic applications. To date, different computational tools have been developed to extract pre-existing information on these biological molecules, but most of these tools suffer from limitations such as non-user friendly interface, redundancy of data, etc. To overcome these limitations, a user-friendly interface, the Peptide Utility (PU) webserver (https://chain-searching.herokuapp.com/) has been developed for searching and analyzing homologous and identical protein/peptide sequences that can be searched from approximately 0.4 million sequences (structural and sequence information) in both online and offline modes. The PU web server can also be used to study different types of interactions in PDBSum, identifying the most dominating interface residues, the most prevalent interactions, and the interaction preferences of different residues. The webserver would also pave way for the design of novel therapeutic peptides and folds by identifying conserved residues in the three-dimensional structure space of proteins.

Design of human immunodeficiency virus-1 neutralizing peptides targeting CD4-binding site: An integrative computational biologics approach

Peptide therapeutics have recently gained momentum in antiviral therapy due to their increased potency and cost-effectiveness. Interaction of the HIV-1 envelope gp120 with the host CD4 receptor is a critical step for viral entry, and therefore the CD4-binding site (CD4bs) of gp120 is a potential hotspot for blocking HIV-1 infection. The present study aimed to design short peptides from well-characterized CD4bs targeting broadly neutralizing antibodies (bNAbs), which could be utilized as bNAb mimetics for viral neutralization. Co-crystallized structures of HIV-1 gp120 in complex with CD4bs-directed bNAbs were used to derive hexameric peptides using the Rosetta Peptiderive protocol. Based on empirical insights into co-crystallized structures, peptides derived from the heavy chain alone were considered. The peptides were docked with both HIV-1 subtype B and C gp120, and the stability of the peptide–antigen complexes was validated using extensive Molecular Dynamics (MD) simulations. Two peptides identified in the study demonstrated stable intermolecular interactions with SER365, GLY366, and GLY367 of the PHE43 cavity in the CD4 binding pocket, and with ASP368 of HIV-1 gp120, thereby mimicking the natural interaction between ASP368gp120 and ARG59CD4–RECEPTOR. Furthermore, the peptides featured favorable physico-chemical properties for virus neutralization suggesting that these peptides may be highly promising bNAb mimetic candidates that may be taken up for experimental validation.

Ameliorating Fibrosis in Murine and Human Tissues with END55, an Endostatin-Derived Fusion Protein Made in Plants

Organ fibrosis, particularly of the lungs, causes significant morbidity and mortality. Effective treatments are needed to reduce the health burden. A fragment of the carboxyl-terminal end of collagen XVIII/endostatin reduces skin and lung fibrosis. This fragment was modified to facilitate its production in plants, which resulted in the recombinant fusion protein, END55. We found that expression of END55 had significant anti-fibrotic effects on the treatment and prevention of skin and lung fibrosis in a bleomycin mouse model. We validated these effects in a second mouse model of pulmonary fibrosis involving inducible, lung-targeted expression of transforming growth factor β1. END55 also exerted anti-fibrotic effects in human lung and skin tissues maintained in organ culture in which fibrosis was experimentally induced. The anti-fibrotic effect of END55 was mediated by a decrease in the expression of extracellular matrix genes and an increase in the levels of matrix-degrading enzymes. Finally, END55 reduced fibrosis in the lungs of patients with systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) who underwent lung transplantation due to the severity of their lung disease, displaying efficacy in human tissues directly relevant to human disease. These findings demonstrate that END55 is an effective anti-fibrotic therapy in different organs.

Cleavage-Responsive Biofactory T Cells Suppress Infectious Diseases-Associated Hypercytokinemia

Severe infectious diseases, such as coronavirus disease 2019 (COVID-19), can induce hypercytokinemia and multiple organ failure. In spite of the growing demand for peptide therapeutics against infectious diseases, current small molecule-based strategies still require frequent administration due to limited half-life and enzymatic digestion in blood. To overcome this challenge, a strategy to continuously express multi-level therapeutic peptide drugs on the surface of immune cells, is established. Here, chimeric T cells stably expressing therapeutic peptides are presented for treatment of severe infectious diseases. Using lentiviral system, T cells are engineered to express multi-level therapeutic peptides with matrix metallopeptidases- (MMP-) and tumor necrosis factor alpha converting enzyme- (TACE-) responsive cleavage sites on the surface. The enzymatic cleavage releases γ-carboxyglutamic acid of protein C (PC-Gla) domain and thrombin receptor agonist peptide (TRAP), which activate endothelial protein C receptor (EPCR) and protease-activated receptor-1 (PAR-1), respectively. These chimeric T cells prevent vascular damage in tissue-engineered blood vessel and suppress hypercytokinemia and lung tissue damages in vivo, demonstrating promise for use of engineered T cells against sepsis and other infectious-related diseases.

Current Advancement of Immunomodulatory Drugs as Potential Pharmacotherapies for Autoimmunity Based Neurological Diseases

Dramatic advancement has been made in recent decades to understand the basis of autoimmunity-mediated neurological diseases. These diseases create a strong influence on the central nervous system (CNS) and the peripheral nervous system (PNS), leading to various clinical manifestations and numerous symptoms. Multiple sclerosis (MS) is the most prevalent autoimmune neurological disease while NMO spectrum disorder (NMOSD) is less common. Furthermore, evidence supports the presence of autoimmune mechanisms contributing to the pathogenesis of amyotrophic lateral sclerosis (ALS), which is a neurodegenerative disorder characterized by the progressive death of motor neurons. Additionally, autoimmunity is believed to be involved in the basis of Alzheimer’s and Parkinson’s diseases. In recent years, the prevalence of autoimmune-based neurological disorders has been elevated and current findings strongly suggest the role of pharmacotherapies in controlling the progression of autoimmune diseases. Therefore, this review focused on the current advancement of immunomodulatory drugs as novel approaches in the management of autoimmune neurological diseases and their future outlook.

Artificial intelligence channelizing protein-peptide interactions pipeline for host-parasite paradigm in IL-10 and IL-12 reciprocity by SHP-1

Identification of molecular targets in any cellular phenomena is a challenge and a path that one endeavors upon independently. We have identified a phosphatase SHP-1 as a point of intervention of IL-10 and IL-12 reciprocity in leishmaniasis. The therapeutic model that we have developed uniquely targets this protein but the pipeline in general can be used by the researchers for their unique targets. Naturally occurring peptides are well known for their biochemical participation in cellular functions hence we were motivated to use this uniqueness of physico-chemical properties of peptides conferred by amino acids through machine learning to channelize a mode of therapeutic exploration in infectious disease. Using computational approaches, we identified high order sequence conservation and similarity in SHP-1 sequence which was also evolutionarily conserved, complete structure of Mouse SHP-1 was predicted and validated, a unique motif of the same was identified against which library of synthetic peptides were designed and validated followed by screening the library by docking them with MuSHP-1 protein structure. Our findings showed 3 peptides had high binding affinity and in future can be validated using cell based and in vivo assays.

Exploring bioactive peptides as potential therapeutic and biotechnology treasures: A contemporary perspective

In preceding years, bioactive peptides (BAPs) have piqued escalating attention owing to their multitudinous biological features. To date, many potential BAPs exhibiting anti-cancer activities have been documented; yet, obstacles such as their safety profiles and consumer acceptance continue to exist. Moreover, BAPs have been discovered to facilitate the suppression of Coronavirus Disease 2019 (CoVID-19) and maybe ideal for treating the CoVID-19 infection, as stated by published experimental findings, but their widespread knowledge is scarce. Likewise, there is a cornucopia of BAPs possessing neuroprotective effects that mend neurodegenerative diseases (NDs) by regulating gut microbiota, but they remain a subject of research interest. Additionally, a plethora of researchers have attempted next-generation approaches based on BAPs, but they need scientific attention. The text format of this critical review is organized around an overview of BAPs' versatility and diverse bio functionalities with emphasis on recent developments and novelties. The review is alienated into independent sections, which are related to either BAPs based disease management strategies or next-generation BAPs based approaches. BAPs based anti-cancer, anti-CoVID-19, and neuroprotective strategies have been explored, which may offer insights that could help the researchers and industries to find an alternate regimen against the three aforementioned fatal diseases. To the best of our knowledge, this is the first review that has systematically discussed the next-generation approaches in BAP research. Furthermore, it can be concluded that the BAPs may be optimal for the management of cancer, CoVID-19, and NDs; nevertheless, experimental and preclinical studies are crucial to validate their therapeutic benefits.

MIF1 and MIF2 Myostatin Peptide Inhibitors as Potent Muscle Mass Regulators

The use of peptides as drugs has progressed over time and continues to evolve as treatment paradigms change and new drugs are developed. Myostatin (MSTN) inhibition therapy has shown great promise for the treatment of muscle wasting diseases. Here, we report the MSTN-derived novel peptides MIF1 (10-mer) and MIF2 (10-mer) not only enhance myogenesis by inhibiting MSTN and inducing myogenic-related markers but also reduce adipogenic proliferation and differentiation by suppressing the expression of adipogenic markers. MIF1 and MIF2 were designed based on in silico interaction studies between MSTN and its receptor, activin type IIB receptor (ACVRIIB), and fibromodulin (FMOD). Of the different modifications of MIF1 and MIF2 examined, _Ac-MIF1 and _Ac-MIF2-_NH2 significantly enhanced cell proliferation and differentiation as compared with non-modified peptides. Mice pretreated with _Ac-MIF1 or _Ac-MIF2-_NH2 prior to cardiotoxin-induced muscle injury showed more muscle regeneration than non-pretreated controls, which was attributed to the induction of myogenic genes and reduced MSTN expression. These findings imply that _Ac-MIF1 and _Ac-MIF2-_NH2 might be valuable therapeutic agents for the treatment of muscle-related diseases.

Designing a Novel Functional Peptide With Dual Antimicrobial and Anti-inflammatory Activities via in Silico Methods

As spider venom is composed of various bioactive substances, it can be utilized as a platform for discovering future therapeutics. Host defense peptides are great candidates for developing novel antimicrobial agents due to their multifunctional properties. In this study, novel functional peptides were rationally designed to have dual antibacterial and anti-inflammatory activities with high cytocompatibility. Based on a template sequence from the transcriptome of spider Agelena koreana, a series of via in silico analysis were conducted, incorporating web-based machine learning tools along with the alteration of amino acid residues. Two peptides, Ak-N’ and Ak-N’m, were designed and were subjected to functional validation. The peptides inhibited gram-negative and gram-positive bacteria by disrupting the outer and bacterial cytoplasmic membrane. Moreover, the peptides down-regulated the expression of pro-inflammatory mediators, tumor necrosis factor-α, interleukin (IL)-1β, and IL6. Along with low cytotoxicity, Ak-N’m was shown to interact with macrophage surface receptors, inhibiting both Myeloid differentiation primary response 88-dependent and TIR-domain-containing adapter-inducing interferon-β-dependent pathways of Toll-like receptor 4 signaling on lipopolysaccharide-stimulated THP-1-derived macrophages. Here, we rationally designed functional peptides based on the suggested in silico strategy, demonstrating new insights for utilizing biological resources as well as developing therapeutic agents with enhanced properties.

Using nanotechnology to deliver biomolecules from nose to brain - peptides, proteins, monoclonal antibodies and RNA

There is a growing number of biomolecules, including peptides, proteins, monoclonal antibodies and RNA, that could be potentially used for the treatment of central nervous system (CNS) diseases. However, the realization of their potential is being hampered by the extraordinary difficulties these complex biomolecules have to reach the brain in therapeutically meaningful amounts. Nose-to-brain (N-to-B) delivery is now being investigated as a potential option for the direct transport of biomolecules from the nasal cavity to different brain areas. Here, we discuss how different technological approaches enhance this N-to-B transport, with emphasis on those that have shown a potential for clinical translation. We also analyse how the physicochemical properties of nanocarriers and their modification with cell-penetrating peptides (CPPs) and targeting ligands affect their efficacy as N-to-B carriers for biomolecules.

Development of Peptide Biopharmaceuticals in Russia

Peptides are low-molecular-weight substances that participate in numerous important physiological functions, such as human growth and development, stress, regulation of the emotional state, sexual behavior, and immune responses. Their mechanisms of action are based on receptor–ligand interactions, which result in highly selective effects. These properties and low toxicity enable them to be considered potent drugs. Peptide preparations became possible at the beginning of the 20th century after a method was developed for selectively synthesizing peptides; however, after synthesis of the first peptide drugs, several issues related to increasing the stability, bioavailability, half-life, and ability to move across cell membranes remain unresolved. Here, we briefly review the history of peptide production and development in the biochemical industry and outline potential areas of peptide biopharmaceutical applications and modern approaches for creating pharmaceuticals based on synthetic peptides and their analogs. We also focus on original peptide drugs and the approaches used for their development by the Russian Federation.

Biological Membrane-Penetrating Peptides: Computational Prediction and Applications

Peptides comprise a versatile class of biomolecules that present a unique chemical space with diverse physicochemical and structural properties. Some classes of peptides are able to naturally cross the biological membranes, such as cell membrane and blood-brain barrier (BBB). Cell-penetrating peptides (CPPs) and blood-brain barrier-penetrating peptides (B3PPs) have been explored by the biotechnological and pharmaceutical industries to develop new therapeutic molecules and carrier systems. The computational prediction of peptides’ penetration into biological membranes has been emerged as an interesting strategy due to their high throughput and low-cost screening of large chemical libraries. Structure- and sequence-based information of peptides, as well as atomistic biophysical models, have been explored in computer-assisted discovery strategies to classify and identify new structures with pharmacokinetic properties related to the translocation through biomembranes. Computational strategies to predict the permeability into biomembranes include cheminformatic filters, molecular dynamics simulations, artificial intelligence algorithms, and statistical models, and the choice of the most adequate method depends on the purposes of the computational investigation. Here, we exhibit and discuss some principles and applications of these computational methods widely used to predict the permeability of peptides into biomembranes, exhibiting some of their pharmaceutical and biotechnological applications.

Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions

Peptide-protein interactions play a key role for many cellular and metabolic processes involved in the onset of largely spread diseases such as cancer and neurodegenerative pathologies. Despite the progress in the structural characterization of peptide-protein interfaces, the in-depth knowledge of the molecular details behind their interactions is still a daunting task. Here, we present the first comprehensive in silico morphological and energetic study of peptide binding sites by focusing on both peptide and protein standpoints. Starting from the PixelDB database, a nonredundant benchmark collection of high-quality 3D crystallographic structures of peptide-protein complexes, a classification analysis of the most representative categories based on the nature of each cocrystallized peptide has been carried out. Several interpretable geometrical and energetic descriptors have been computed both from peptide and target protein sides in the attempt to unveil physicochemical and structural causative correlations. Finally, we investigated the most frequent peptide-protein residue pairs at the binding interface and made extensive energetic analyses, based on GRID MIFs, with the aim to study the peptide affinity-enhancing interactions to be further exploited in rational drug design strategies.

Relevance of AIF/CypA Lethal Pathway in SH-SY5Y Cells Treated with Staurosporine

The AIF/CypA complex exerts a lethal activity in several rodent models of acute brain injury. Upon formation, it translocates into the nucleus of cells receiving apoptotic stimuli, inducing chromatin condensation, DNA fragmentation, and cell death by a caspase-independent mechanism. Inhibition of this complex in a model of glutamate-induced cell death in HT-22 neuronal cells by an AIF peptide (AIF(370-394)) mimicking the binding site on CypA, restores cell survival and prevents brain injury in neonatal mice undergoing hypoxia-ischemia without apparent toxicity. Here, we explore the effects of the peptide on SH-SY5Y neuroblastoma cells stimulated with staurosporine (STS), a cellular model widely used to study Parkinson’s disease (PD). This will pave the way to understanding the role of the complex and the potential therapeutic efficacy of inhibitors in PD. We find that AIF(370-394) confers resistance to STS-induced apoptosis in SH-SY5Y cells similar to that observed with CypA silencing and that the peptide works on the AIF/CypA translocation pathway and not on caspases activation. These findings suggest that the AIF/CypA complex is a promising target for developing novel therapeutic strategies against PD.

Recent Advances in the Application Peptide and Peptoid in Diagnosis Biomarkers of Alzheimer's Disease in Blood

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with irreversible damage of the brain and a continuous pathophysiological process. Early detection and accurate diagnosis are essential for the early intervention of AD. Precise detection of blood biomarkers related to AD could provide a shortcut to identifying early-stage patients before symptoms. In recent years, targeting peptides or peptoids have been chosen as recognition elements in nano-sensors or fluorescence detection to increase the targeting specificity, while peptide-based probes were also developed considering their specific advantages. Peptide-based sensors and probes have been developed according to different strategies, such as natural receptors, high-throughput screening, or artificial design for AD detection. This review will briefly summarize the recent developments and trends of AD diagnosis platforms based on peptide and peptoid as recognition elements and provide insights into the application of peptide and peptoid with different sources and characteristics in the diagnosis of AD biomarkers.

Delineating the Aggregation-Prone Hotspot Regions (Peptides) in the Human Cu/Zn Superoxide Dismutase 1

Amyotrophic lateral sclerosis (ALS) is a fatal, incurable neurodegenerative disease described by progressive degeneration of motor neurons. The most common familial form of ALS (fALS) has been associated with mutations in the Cu/Zn superoxide dismutase (SOD1) gene. Mutation-induced misfolding and aggregation of SOD1 is often found in ALS patients. In this work, we probe the aggregation properties of peptides derived from the SOD1. To examine the source of SOD1 aggregation, we have employed a computational algorithm to identify four peptides from the SOD1 protein sequence that aggregates into a fibril. Aided by computational algorithms, we identified four peptides likely involved in SOD1 fibrillization. These four aggregation-prone peptides were 14VQGIINFE21, 30KVWGSIKGL38, 101DSVISLS107, and 147GVIGIAQ153. In addition, the formation of fibril propensities from the identified peptides was investigated through different biophysical techniques. The atomic structures of two fibril-forming peptides from the C-terminal SOD1 showed that the steric zippers formed by 101DSVISLS107 and 147GVIGIAQ153 vary in their arrangement. We also discovered that fALS mutations in the peptide 147GVIGIAQ153 increased the fibril-forming propensity and altered the steric zipper's packing. Thus, our results suggested that the C-terminal peptides of SOD1 have a central role in amyloid formation and might be involved in forming the structural core of SOD1 aggregation observed in vivo.

The Use of Peptides in the Treatment of Fragile X Syndrome: Challenges and Opportunities

Fragile X Syndrome (FXS) is the most frequent cause of inherited intellectual disabilities and autism spectrum disorders, characterized by cognitive deficits and autistic behaviors. The silencing of the Fmr1 gene and consequent lack of FMRP protein, is the major contribution to FXS pathophysiology. FMRP is an RNA binding protein involved in the maturation and plasticity of synapses and its absence culminates in a range of morphological, synaptic and behavioral phenotypes. Currently, there are no approved medications for the treatment of FXS, with the approaches under study being fairly specific and unsatisfying in human trials. Here we propose peptides/peptidomimetics as candidates in the pharmacotherapy of FXS; in the last years this class of molecules has catalyzed the attention of pharmaceutical research, being highly selective and well-tolerated. Thanks to their ability to target protein-protein interactions (PPIs), they are already being tested for a wide range of diseases, including cancer, diabetes, inflammation, Alzheimer's disease, but this approach has never been applied to FXS. As FXS is at the forefront of efforts to develop new drugs and approaches, we discuss opportunities, challenges and potential issues of peptides/peptidomimetics in FXS drug design and development.

Peptide-Based Vaccines for Neurodegenerative Diseases: Recent Endeavors and Future Perspectives

The development of peptide-based vaccines for treating human neurodegenerative diseases has been the eventual aim of many research endeavors, although no active immunotherapies have been approved for clinical use till now. A typical example of such endeavors is the effort to develop vaccines for Alzheimer’s disease based on the beta-amyloid peptide, which continues to be intensively investigated despite previous setbacks. In this paper, recent developments in peptide-based vaccines which target beta-amyloid as well as tau protein and α-synuclein are presented. Particular focus has been directed toward peptide epitopes and formulation systems selected/developed and employed to enhance vaccine efficacy and safety. Results from both, human clinical trials and animal preclinical studies conducted mainly in transgenic mice have been included. Future perspectives on the topic are also briefly discussed.

Oyster-Derived Tyr-Ala (YA) Peptide Prevents Lipopolysaccharide/D-Galactosamine-Induced Acute Liver Failure by Suppressing Inflammatory, Apoptotic, Ferroptotic, and Pyroptotic Signals

Models created by the intraperitoneal injection of lipopolysaccharide (LPS) and D-galactosamine (D-GalN) have been widely used to study the pathogenesis of human acute liver failure (ALF) and drug development. Our previous study reported that oyster (Crassostrea gigas) hydrolysate (OH) had a hepatoprotective effect in LPS/D-GalN-injected mice. This study was performed to identify the hepatoprotective effect of the tyrosine-alanine (YA) peptide, the main component of OH, in a LPS/D-GalN-injected ALF mice model. We analyzed the effect of YA on previously known mechanisms of hepatocellular injury in the model. LPS/D-GalN-injected mice showed inflammatory, apoptotic, ferroptotic, and pyroptotic liver injury. The pre-administration of YA (10 mg/kg or 50 mg/kg) significantly reduced the liver damage factors. The hepatoprotective effect of YA was higher in the 50 mg/kg YA pre-administered group than in the 10 mg/kg YA pre-administered group. These results showed that YA had a hepatoprotective effect by reducing inflammation, apoptosis, ferroptosis, and pyroptosis in the LPS/D-GalN-injected ALF mouse model. We suggest that YA can be used as a functional peptide for the prevention of acute liver injury.

Contribution of the Commensal Microflora to the Immunological Homeostasis and the Importance of Immune-Related Drug Development for Clinical Applications

Not long ago, self-reactive immune activity was considered as pathological trait. A paradigm shift has now led to the recognition of autoimmune processes as part of natural maintenance of molecular homeostasis. The immune system is assigned further roles beneath the defense against pathogenic organisms. Regarding the humoral immune system, the investigation of natural autoantibodies that are frequently found in healthy individuals has led to further hypotheses involving natural autoimmunity in other processes as the clearing of cellular debris or decrease in inflammatory processes. However, their role and origin have not been entirely clarified, but accumulating evidence links their formation to immune reactions against the gut microbiome. Antibodies targeting highly conserved proteins of the commensal microflora are suggested to show self-reactive properties, following the paradigm of the molecular mimicry. Here, we discuss recent findings, which demonstrate potential links of the commensal microflora to the immunological homeostasis and highlight the possible implications for various diseases. Furthermore, specific components of the immune system, especially antibodies, have become a focus of attention for the medical management of various diseases and provide attractive treatment options in the future. Nevertheless, the development and optimization of such macromolecules still represents a very time-consuming task, shifting the need to more medical agents with simple structural properties and low manufacturing costs. Synthesizing only the biologically active sites of antibodies has become of great interest for the pharmaceutical industry and offers a wide range of therapeutic application areas as it will be discussed in the present review article.

B3Pred: A Random-Forest-Based Method for Predicting and Designing Blood-Brain Barrier Penetrating Peptides

The blood–brain barrier is a major obstacle in treating brain-related disorders, as it does not allow the delivery of drugs into the brain. We developed a method for predicting blood–brain barrier penetrating peptides to facilitate drug delivery into the brain. These blood–brain barrier penetrating peptides (B3PPs) can act as therapeutics, as well as drug delivery agents. We trained, tested, and evaluated our models on blood–brain barrier peptides obtained from the B3Pdb database. First, we computed a wide range of peptide features. Then, we selected relevant peptide features. Finally, we developed numerous machine-learning-based models for predicting blood–brain barrier peptides using the selected features. The random-forest-based model performed the best with respect to the top 80 selected features and achieved a maximal 85.08% accuracy with an AUROC of 0.93. We also developed a webserver, B3pred, that implements our best models. It has three major modules that allow users to predict/design B3PPs and scan B3PPs in a protein sequence.