Brainpeps: the blood–brain barrier peptide database

Dorpe, Sylvia Van; Bronselaer, Antoon; Nielandt, Joachim; Stalmans, Sofie; Wynendaele, Evelien; Audenaert, Kurt; Wiele, Christophe Van de; Burvenich, Christian; Peremans, Kathelijne; Hsuchou, Hung; Tré, Guy De; Spiegeleer, Bart De

doi:10.1007/s00429-011-0375-0

Cited by 71 publications

(54 citation statements)

References 197 publications

(386 reference statements)

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“…For the first model using The BBB-influx classification system for peptides as proposed by Stalmans et al (2015b) indicated that BEA and ENNs are located in class 5, corresponding to a very high brain influx, which was also confirmed by comparing our obtained influx data of BEA/ENNs with those of other peptides (Van Dorpe et al, 2012).…”

Section: Discussionsupporting

confidence: 76%

Blood-brain barrier transport kinetics of the cyclic depsipeptide mycotoxins beauvericin and enniatins

et al. 2016

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Section: Discussionsupporting

confidence: 76%

Blood-brain barrier transport kinetics of the cyclic depsipeptide mycotoxins beauvericin and enniatins

et al. 2016

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“…A large number of peptides like insulin [2], cyclosporine [3], corticotropin [4] are used for treating various diseases like diabetes and immunoregulatory disorders [5–7]. Owing to their immense therapeutic importance, peptides have been curated from literature and stored in form of databases such as Hemolytik [8], PhytAMP [9], APD2 [10], DAMPD [11], CAMP [12], YADAMP [13], CPPsite [14], TumorHoPe [15], Quorumpeps [16], Brainpeps [17], MilkAMP [18], DADP [19], LAMP [20] and AVPdb [21] to name a few. Also, a number of computation tools such as CellPPD [22], TumorHPD [23], AntiCP [24], AVPpred [25] and ToxinPred [26] have been developed to predict and design cell penetrating, tumor homing, anticancer, antiviral and toxic peptides, respectively.…”

Section: Introductionmentioning

confidence: 99%

Designing of peptides with desired half-life in intestine-like environment

et al. 2014

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BackgroundIn past, a number of peptides have been reported to possess highly diverse properties ranging from cell penetrating, tumor homing, anticancer, anti-hypertensive, antiviral to antimicrobials. Owing to their excellent specificity, low-toxicity, rich chemical diversity and availability from natural sources, FDA has successfully approved a number of peptide-based drugs and several are in various stages of drug development. Though peptides are proven good drug candidates, their usage is still hindered mainly because of their high susceptibility towards proteases degradation. We have developed an in silico method to predict the half-life of peptides in intestine-like environment and to design better peptides having optimized physicochemical properties and half-life.ResultsIn this study, we have used 10mer (HL10) and 16mer (HL16) peptides dataset to develop prediction models for peptide half-life in intestine-like environment. First, SVM based models were developed on HL10 dataset which achieved maximum correlation R/R2 of 0.57/0.32, 0.68/0.46, and 0.69/0.47 using amino acid, dipeptide and tripeptide composition, respectively. Secondly, models developed on HL16 dataset showed maximum R/R2 of 0.91/0.82, 0.90/0.39, and 0.90/0.31 using amino acid, dipeptide and tripeptide composition, respectively. Furthermore, models that were developed on selected features, achieved a correlation (R) of 0.70 and 0.98 on HL10 and HL16 dataset, respectively. Preliminary analysis suggests the role of charged residue and amino acid size in peptide half-life/stability. Based on above models, we have developed a web server named HLP (Half Life Prediction), for predicting and designing peptides with desired half-life. The web server provides three facilities; i) half-life prediction, ii) physicochemical properties calculation and iii) designing mutant peptides.ConclusionIn summary, this study describes a web server ‘HLP’ that has been developed for assisting scientific community for predicting intestinal half-life of peptides and to design mutant peptides with better half-life and physicochemical properties. HLP models were trained using a dataset of peptides whose half-lives have been determined experimentally in crude intestinal proteases preparation. Thus, HLP server will help in designing peptides possessing the potential to be administered via oral route (http://www.imtech.res.in/raghava/hlp/).Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-282) contains supplementary material, which is available to authorized users.

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“…The results of these studies were promising and raised a hope for the fight against these devastating diseases. Keeping in mind the huge pharmacological importance of therapeutic peptides, many databases of therapeutic peptides have been developed so far that include CPPsite (24), APD2 (13), CAMP (12), Brainpeps (25), Quorumpeps (26), TumorHope (27), Hemolytik (28) and DAMPD (14). However, no attempt has been made to catalog APPs and to understand the properties of these peptides.…”

Section: Discussionmentioning

confidence: 99%

ParaPep: a web resource for experimentally validated antiparasitic peptide sequences and their structures

et al. 2014

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ParaPep is a repository of antiparasitic peptides, which provides comprehensive information related to experimentally validated antiparasitic peptide sequences and their structures. The data were collected and compiled from published research papers, patents and from various databases. The current release of ParaPep holds 863 entries among which 519 are unique peptides. In addition to peptides having natural amino acids, ParaPep also consists of peptides having d-amino acids and chemically modified residues. In ParaPep, most of the peptides have been evaluated for growth inhibition of various species of Plasmodium, Leishmania and Trypanosoma. We have provided comprehensive information about these peptides that include peptide sequence, chemical modifications, stereochemistry, antiparasitic activity, origin, nature of peptide, assay types, type of parasite, mode of action and hemolytic activity. Structures of peptides consisting of natural, as well as modified amino acids have been determined using state-of-the-art software, PEPstr. To facilitate users, various user-friendly web tools, for data fetching, analysis and browsing, have been integrated. We hope that ParaPep will be advantageous in designing therapeutic peptides against parasitic diseases.Database URL: http://crdd.osdd.net/raghava/parapep/

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Brainpeps: the blood–brain barrier peptide database

Cited by 71 publications

References 197 publications

Blood-brain barrier transport kinetics of the cyclic depsipeptide mycotoxins beauvericin and enniatins

Blood-brain barrier transport kinetics of the cyclic depsipeptide mycotoxins beauvericin and enniatins

Designing of peptides with desired half-life in intestine-like environment

ParaPep: a web resource for experimentally validated antiparasitic peptide sequences and their structures

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