Search

Numerous therapeutic peptides do not enter the clinical trials just because of their high hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining experimentally validated hemolytic and non-hemolytic peptides. The present study describes a web server and mobile app developed for predicting, and screening of peptides having hemolytic potency. Firstly, we generated a dataset HemoPI-1 that contains 552 hemolytic peptides extracted from Hemolytik database and 552 random non-hemolytic peptides (from Swiss-Prot). The sequence analysis of these peptides revealed that certain residues (e.g., L, K, F, W) and motifs (e.g., "FKK", "LKL", "KKLL", "KWK", "VLK", "CYCR", "CRR", "RFC", "RRR", "LKKL") are more abundant in hemolytic peptides. Therefore, we developed models for discriminating hemolytic and non-hemolytic peptides using various machine learning techniques and achieved more than 95% accuracy. We also developed models for discriminating peptides having high and low hemolytic potential on different datasets called HemoPI-2 and HemoPI-3. In order to serve the scientific community, we developed a web server, mobile app and JAVA-based standalone software (http://crdd.osdd.net/raghava/hemopi/).

CPPsite 2.0 (http://crdd.osdd.net/raghava/cppsite/) is an updated version of manually curated database (CPPsite) of cell-penetrating peptides (CPPs). The current version holds around 1850 peptide entries, which is nearly two times than the entries in the previous version. The updated data were curated from research papers and patents published in last three years. It was observed that most of the CPPs discovered/ tested, in last three years, have diverse chemical modifications (e.g. non-natural residues, linkers, lipid moieties, etc.). We have compiled this information on chemical modifications systematically in the updated version of the database. In order to understand the structure-function relationship of these peptides, we predicted tertiary structure of CPPs, possessing both modified and natural residues, using state-of-the-art techniques. CPPsite 2.0 also maintains information about model systems (in vitro/in vivo) used for CPP evaluation and different type of cargoes (e.g. nucleic acid, protein, nanoparticles, etc.) delivered by these peptides. In order to assist a wide range of users, we developed a user-friendly responsive website, with various tools, suitable for smartphone, tablet and desktop users. In conclusion, CPPsite 2.0 provides significant improvements over the previous version in terms of data content., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

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/, (© The Author(s) 2014. Published by Oxford University Press.)

Pancreatic cancer is the fifth most aggressive malignancy and urgently requires new biomarkers to facilitate early detection. For providing impetus to the biomarker discovery, we have developed Pancreatic Cancer Methylation Database (PCMDB, http://crdd.osdd.net/raghava/pcmdb/), a comprehensive resource dedicated to methylation of genes in pancreatic cancer. Data was collected and compiled manually from published literature. PCMdb has 65907 entries for methylation status of 4342 unique genes. In PCMdb, data was compiled for both cancer cell lines (53565 entries for 88 cell lines) and cancer tissues (12342 entries for 3078 tissue samples). Among these entries, 47.22% entries reported a high level of methylation for the corresponding genes while 10.87% entries reported low level of methylation. PCMdb covers five major subtypes of pancreatic cancer; however, most of the entries were compiled for adenocarcinomas (88.38%) and mucinous neoplasms (5.76%). A user-friendly interface has been developed for data browsing, searching and analysis. We anticipate that PCMdb will be helpful for pancreatic cancer biomarker discovery.

Hemolytik (http://crdd.osdd.net/raghava/hemolytik/) is a manually curated database of experimentally determined hemolytic and non-hemolytic peptides. Data were compiled from a large number of published research articles and various databases like Antimicrobial Peptide Database, Collection of Anti-microbial Peptides, Dragon Antimicrobial Peptide Database and Swiss-Prot. The current release of Hemolytik database contains ∼3000 entries that include ∼2000 unique peptides whose hemolytic activities were evaluated on erythrocytes isolated from as many as 17 different sources. Each entry in Hemolytik provides comprehensive information about a peptide, like its name, sequence, origin, reported function, property such as chirality, types (linear and cyclic), end modifications as well as details pertaining to its hemolytic activity. In addition, tertiary structure of each peptide has been predicted, and secondary structure states have been assigned. To facilitate the scientific community, a user-friendly interface has been developed with various tools for data searching and analysis. We hope, Hemolytik will be useful for researchers working in the field of designing therapeutic peptides.

Delivering drug molecules into the cell is one of the major challenges in the process of drug development. In past, cell penetrating peptides have been successfully used for delivering a wide variety of therapeutic molecules into various types of cells for the treatment of multiple diseases. These peptides have unique ability to gain access to the interior of almost any type of cell. Due to the huge therapeutic applications of CPPs, we have built a comprehensive database 'CPPsite', of cell penetrating peptides, where information is compiled from the literature and patents. CPPsite is a manually curated database of experimentally validated 843 CPPs. Each entry provides information of a peptide that includes ID, PubMed ID, peptide name, peptide sequence, chirality, origin, nature of peptide, sub-cellular localization, uptake efficiency, uptake mechanism, hydrophobicity, amino acid frequency and composition, etc. A wide range of user-friendly tools have been incorporated in this database like searching, browsing, analyzing, mapping tools. In addition, we have derived various types of information from these peptide sequences that include secondary/tertiary structure, amino acid composition and physicochemical properties of peptides. This database will be very useful for developing models for predicting effective cell penetrating peptides. Database URL: http://crdd.osdd.net/raghava/cppsite/.

Background: Cancer is responsible for millions of immature deaths every year and is an economical burden on developing countries. One of the major challenges in the present era is to design drugs that can specifically target tumor cells not normal cells. In this context, tumor homing peptides have drawn much attention. These peptides are playing a vital role in delivering drugs in tumor tissues with high specificity. In order to provide service to scientific community, we have developed a database of tumor homing peptides called TumorHoPe., Description: TumorHoPe is a manually curated database of experimentally validated tumor homing peptides that specifically recognize tumor cells and tumor associated microenvironment, i.e., angiogenesis. These peptides were collected and compiled from published papers, patents and databases. Current release of TumorHoPe contains 744 peptides. Each entry provides comprehensive information of a peptide that includes its sequence, target tumor, target cell, techniques of identification, peptide receptor, etc. In addition, we have derived various types of information from these peptide sequences that include secondary/tertiary structure, amino acid composition, and physicochemical properties of peptides. Peptides in this database have been found to target different types of tumors that include breast, lung, prostate, melanoma, colon, etc. These peptides have some common motifs including RGD (Arg-Gly-Asp) and NGR (Asn-Gly-Arg) motifs, which specifically recognize tumor angiogenic markers. TumorHoPe has been integrated with many web-based tools like simple/complex search, database browsing and peptide mapping. These tools allow a user to search tumor homing peptides based on their amino acid composition, charge, polarity, hydrophobicity, etc., Conclusion: TumorHoPe is a unique database of its kind, which provides comprehensive information about experimentally validated tumor homing peptides and their target cells. This database will be very useful in designing peptide-based drugs and drug-delivery system. It is freely available at http://crdd.osdd.net/raghava/tumorhope/.