Antiviral peptides (AVPs) have exhibited huge potential in inhibiting viruses by targeting various stages of their life cycle. Therefore, we have developed AVPdb, available online at http://crdd.osdd.net/servers/avpdb, to provide a dedicated resource of experimentally verified AVPs targeting over 60 medically important viruses including Influenza, HCV, HSV, RSV, HBV, DENV, SARS, etc. However, we have separately provided HIV inhibiting peptides in ‘HIPdb’. AVPdb contains detailed information of 2683 peptides, including 624 modified peptides experimentally tested for antiviral activity. In modified peptides a chemical moiety is attached for increasing their efficacy and stability. Detailed information include: peptide sequence, length, source, virus targeted, virus family, cell line used, efficacy (qualitative/quantitative), target step/protein, assay used in determining the efficacy and PubMed reference. The database also furnishes physicochemical properties and predicted structure for each peptide. We have provided user-friendly browsing and search facility along with other analysis tools to help the users. Entering of many synthetic peptide-based drugs in various stages of clinical trials reiterate the importance for the AVP resources. AVPdb is anticipated to cater to the needs of scientific community working for the development of antiviral therapeutics.

Peptide‐based antiviral therapeutics has gradually paved their way into mainstream drug discovery research. Experimental determination of peptides' antiviral activity as expressed by their IC ₅₀ values involves a lot of effort. Therefore, we have developed “AVP‐IC ₅₀ Pred,” a regression‐based algorithm to predict the antiviral activity in terms of IC ₅₀ values (μM). A total of 759 non‐redundant peptides from AVPdb and HIPdb were divided into a training/test set having 683 peptides (T ⁶⁸³ ) and a validation set with 76 independent peptides (V ⁷⁶ ) for evaluation. We utilized important peptide sequence features like amino‐acid compositions, binary profile of N8‐C8 residues, physicochemical properties and their hybrids. Four different machine learning techniques (MLTs) namely Support vector machine, Random Forest, Instance‐based classifier, and K‐Star were employed. During 10‐fold cross validation, we achieved maximum Pearson correlation coefficients (PCCs) of 0.66, 0.64, 0.56, 0.55, respectively, for the above MLTs using the best combination of feature sets. All the predictive models also performed well on the independent validation dataset and achieved maximum PCCs of 0.74, 0.68, 0.59, 0.57, respectively, on the best combination of feature sets. The AVP‐IC ₅₀ Pred web server is anticipated to assist the researchers working on antiviral therapeutics by enabling them to computationally screen many compounds and focus experimental validation on the most promising set of peptides, thus reducing cost and time efforts. The server is available at http://crdd.osdd.net/servers/ic50avp . © 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 104: 753–763, 2015.

Pathological lipid accumulation is often associated with enhanced uptake of free fatty acids via specific transporters in cardiomyocytes. Here, we identify SIRT6 as a critical transcriptional regulator of fatty acid transporters in cardiomyocytes. We find that SIRT6 deficiency enhances the expression of fatty acid transporters, leading to enhanced fatty acid uptake and lipid accumulation. Interestingly, the haploinsufficiency of SIRT6 is sufficient to induce the expression of fatty acid transporters and cause lipid accumulation in murine hearts. Mechanistically, SIRT6 depletion enhances the occupancy of the transcription factor PPARγ on the promoters of critical fatty acid transporters without modulating the acetylation of histone 3 at Lys 9 and Lys 56. Notably, the binding of SIRT6 to the DNA-binding domain of PPARγ is critical for regulating the expression of fatty acid transporters in cardiomyocytes. Our data suggest exploiting SIRT6 as a potential therapeutic target for protecting the heart from metabolic diseases.

Mycobacterium tuberculosis possesses an unusually large representation of type II toxin–antitoxin (TA) systems, whose functions and targets are mostly unknown. To better understand the basis of their unique expansion and to probe putative functional similarities among these systems, here we computationally and experimentally investigated their sequence relationships. Bioinformatic and phylogenetic investigations revealed that 51 sequences of the VapBC toxin family group into paralogous sub-clusters. On the basis of conserved sequence fingerprints within paralogues, we predicted functional residues and residues at the putative TA interface that are useful to evaluate TA interactions. Substitution of these likely functional residues abolished the toxin's growth-inhibitory activity. Furthermore, conducting similarity searches in 101 mycobacterial and ∼4500 other prokaryotic genomes, we assessed the relative conservation of the M. tuberculosis TA systems and found that most TA orthologues are well-conserved among the members of the M. tuberculosis complex, which cause tuberculosis in animal hosts. We found that soil-inhabiting, free-living Actinobacteria also harbor as many as 12 TA pairs. Finally, we identified five novel putative TA modules in M. tuberculosis. For one of them, we demonstrate that overexpression of the putative toxin, Rv2514c, induces bacteriostasis and that co-expression of the cognate antitoxin Rv2515c restores bacterial growth. Taken together, our findings reveal that toxin sequences are more closely related than antitoxin sequences in M. tuberculosis. Furthermore, the identification of additional TA systems reported here expands the known repertoire of TA systems in M. tuberculosis.

CRISPR system is a powerful defense mechanism in bacteria and archaea to provide immunity against viruses. Recently, this process found a new application in intended targeting of the genomes. CRISPR-mediated genome editing is performed by two main components namely single guide RNA and Cas9 protein. Despite the enormous data generated in this area, there is a dearth of high throughput resource. Therefore, we have developed CrisprGE, a central hub of CRISPR/Cas-based genome editing. Presently, this database holds a total of 4680 entries of 223 unique genes from 32 model and other organisms. It encompasses information about the organism, gene, target gene sequences, genetic modification, modifications length, genome editing efficiency, cell line, assay, etc. This depository is developed using the open source LAMP (Linux Apache MYSQL PHP) server. User-friendly browsing, searching facility is integrated for easy data retrieval. It also includes useful tools like BLAST CrisprGE, BLAST NTdb and CRISPR Mapper. Considering potential utilities of CRISPR in the vast area of biology and therapeutics, we foresee this platform as an assistance to accelerate research in the burgeoning field of genome engineering. Database URL : http://crdd.osdd.net/servers/crisprge/ .