AlgPred 2.0 is a web server developed for predicting allergenic proteins and allergenic regions in a protein. It is an updated version of AlgPred developed in 2006. The dataset used for training, testing and validation consists of 10 075 allergens and 10 075 non-allergens. In addition, 10 451 experimentally validated immunoglobulin E (IgE) epitopes were used to identify antigenic regions in a protein. All models were trained on 80% of data called training dataset, and the performance of models was evaluated using 5-fold cross-validation technique. The performance of the final model trained on the training dataset was evaluated on 20% of data called validation dataset; no two proteins in any two sets have more than 40% similarity. First, a Basic Local Alignment Search Tool (BLAST) search has been performed against the dataset, and allergens were predicted based on the level of similarity with known allergens. Second, IgE epitopes obtained from the IEDB database were searched in the dataset to predict allergens based on their presence in a protein. Third, motif-based approaches like multiple EM for motif elicitation/motif alignment and search tool have been used to predict allergens. Fourth, allergen prediction models have been developed using a wide range of machine learning techniques. Finally, the ensemble approach has been used for predicting allergenic protein by combining prediction scores of different approaches. Our best model achieved maximum performance in terms of area under receiver operating characteristic curve 0.98 with Matthew’s correlation coefficient 0.85 on the validation dataset. A web server AlgPred 2.0 has been developed that allows the prediction of allergens, mapping of IgE epitope, motif search and BLAST search (https://webs.iiitd.edu.in/raghava/algpred2/).

Cells manage to survive, thrive, and divide with high accuracy despite the constant threat of DNA damage. Cells have evolved with several systems that efficiently repair spontaneous, isolated DNA lesions with a high degree of accuracy. Ionizing radiation and a few radiomimetic chemicals can produce clustered DNA damage comprising complex arrangements of single-strand damage and DNA double-strand breaks (DSBs). There is substantial evidence that clustered DNA damage is more mutagenic and cytotoxic than isolated damage. Radiation-induced clustered DNA damage has proven difficult to study because the spectrum of induced lesions is very complex, and lesions are randomly distributed throughout the genome. Nonetheless, it is fairly well-established that radiation-induced clustered DNA damage, including non-DSB and DSB clustered lesions, are poorly repaired or fail to repair, accounting for the greater mutagenic and cytotoxic effects of clustered lesions compared to isolated lesions. High linear energy transfer (LET) charged particle radiation is more cytotoxic per unit dose than low LET radiation because high LET radiation produces more clustered DNA damage. Studies with I-SceI nuclease demonstrate that nuclease-induced DSB clusters are also cytotoxic, indicating that this cytotoxicity is independent of radiogenic lesions, including single-strand lesions and chemically “dirty” DSB ends. The poor repair of clustered DSBs at least in part reflects inhibition of canonical NHEJ by short DNA fragments. This shifts repair toward HR and perhaps alternative NHEJ, and can result in chromothripsis-mediated genome instability or cell death. These principals are important for cancer treatment by low and high LET radiation.

The oral microbiome is diverse in its composition due to continuous contact of oral cavity with the external environment. Temperatures, diet, pH, feeding habits are important factors that contribute in the establishment of oral microbiome. Both culture dependent and culture independent approaches have been employed in the analysis of oral microbiome. Gene-based methods like PCR amplification techniques, random amplicon cloning, PCR-RELP, T-RELP, DGGE and DNA microarray analysis have been applied to increase oral microbiome related knowledge. Studies revealed that microbes from the phyla Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Fusobacteria, Neisseria , TM7 predominately inhabits the oral cavity. Culture-independent molecular techniques revealed the presence of genera Megasphaera , Parvimonas and Desulfobulbus in periodontal disease. Bacteria, fungi and protozoa colonize themselves on various surfaces in oral cavity. Microbial biofilms are formed on the buccal mucosa, dorsum of the tongue, tooth surfaces and gingival sulcus. Various studies demonstrate relationship between unbalanced microflora and development of diseases like tooth caries, periodontal diseases, type 2 diabetes, circulatory system related diseases etc. Transcriptome-based remodelling of microbial metabolism in health and disease associated states has been well reported. Human diets and habitat can trigger virus activation and influence phage members of oral microbiome. As it is said, “Mouth, is the gateway to the total body wellness, thus oral microbiome influences overall health of an individual”.

NUCKS1 (nuclear casein kinase and cyclin-dependent kinase substrate 1) is a 27 kD chromosomal, vertebrate-specific protein, for which limited functional data exist. Here, we demonstrate that NUCKS1 shares extensive sequence homology with RAD51AP1 (RAD51 associated protein 1), suggesting that these two proteins are paralogs. Similar to the phenotypic effects of RAD51AP1 knockdown, we find that depletion of NUCKS1 in human cells impairs DNA repair by homologous recombination (HR) and chromosome stability. Depletion of NUCKS1 also results in greatly increased cellular sensitivity to mitomycin C (MMC), and in increased levels of spontaneous and MMC-induced chromatid breaks. NUCKS1 is critical to maintaining wild type HR capacity, and, as observed for a number of proteins involved in the HR pathway, functional loss of NUCKS1 leads to a slow down in DNA replication fork progression with a concomitant increase in the utilization of new replication origins. Interestingly, recombinant NUCKS1 shares the same DNA binding preference as RAD51AP1, but binds to DNA with reduced affinity when compared to RAD51AP1. Our results show that NUCKS1 is a chromatin-associated protein with a role in the DNA damage response and in HR, a DNA repair pathway critical for tumor suppression.

Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides (ACPs). ACPs residue composition analysis show the preference of A, F, K, L and W. Positional preference analysis revealed that residues A, F and K are favored at N-terminus and residues L and K are preferred at C-terminus. Motif analysis revealed the presence of motifs like LAKLA, AKLAK, FAKL and LAKL in ACPs. Machine learning models were developed using various input features and implementing different machine learning classifiers on two datasets main and alternate dataset. In the case of main dataset, dipeptide composition based ETree classifier model achieved maximum Matthews correlation coefficient (MCC) of 0.51 and 0.83 area under receiver operating characteristics (AUROC) on the training dataset. In the case of alternate dataset, amino acid composition based ETree classifier performed best and achieved the highest MCC of 0.80 and AUROC of 0.97 on the training dataset. Five-fold cross-validation technique was implemented for model training and testing, and their performance was also evaluated on the validation dataset. Best models were implemented in the webserver AntiCP 2.0, which is freely available at https://webs.iiitd.edu.in/raghava/anticp2/. The webserver is compatible with multiple screens such as iPhone, iPad, laptop and android phones. The standalone version of the software is available at GitHub; docker-based container also developed.

The human T cell leukemia virus type 1 (HTLV-1) is the causative agent of adult T cell leukemia/lymphoma. The multifunctional virally encoded oncoprotein Tax is responsible for malignant transformation and potent activation of HTLV-1 transcription. Tax, in complex with phosphorylated cAMP response element binding protein (pCREB), strongly recruits the cellular coactivators CREB binding protein (CBP)/p300 to the viral promoter concomitant with transcriptional activation. Although the mechanism of activator/coactivator-mediated transcriptional activation is poorly understood, the recruitment of CBP/p300 by regulatory factors appears to function, in part, by promoting changes in chromatin architecture that are permissive to transcriptional activation. Here, we show that CBP/p300 recruitment promotes histone acetylation and eviction of the histone octamer from the chromatin-assembled HTLV-1 promoter template in vitro. Nucleosome disassembly is strictly acetyl-CoA dependent and is not linked to ATP utilization. We find that the histone chaperone, nucleosome assembly protein 1 (NAP1), cooperates with CBP/p300 in eviction of the acetylated histones from the chromatin template. These findings reveal a unique mechanism in which the DNA-bound Tax/pCREB complex recruits CBP/p300, and together with NAP1, the coactivators cooperate to dramatically reduce nucleosome occupancy at the viral promoter in an acetylation-dependent and transcription-independent fashion.Tax ͉ cAMP response element binding protein ͉ acetylation ͉ chromatin ͉ histone acetyltransferase

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Histone posttranslational modifications and chromatin dynamics are inextricably linked to eukaryotic gene expression. Among the many modifications that have been characterized, histone tail acetylation is most strongly correlated with transcriptional activation. In Metazoa , promoters of transcriptionally active genes are generally devoid of physically repressive nucleosomes, consistent with the contemporaneous binding of the large RNA polymerase II transcription machinery. The histone acetyltransferase p300 is also detected at active gene promoters, flanked by regions of histone hyperacetylation. Although the correlation between histone tail acetylation and gene activation is firmly established, the mechanisms by which acetylation facilitates this fundamental biological process remain poorly understood. To explore the role of acetylation in nucleosome dynamics, we utilized an immobilized template carrying a natural promoter reconstituted with various combinations of wild-type and mutant histones. We find that the histone H3 N-terminal tail is indispensable for activator, p300, and acetyl-CoA-dependent nucleosome eviction mediated by the histone chaperone Nap1. Significantly, we identify H3 lysine 14 as the essential p300 acetylation substrate required for dissociation of the histone octamer from the promoter DNA. Together, a total of 11 unique mutant octamer sets corroborated these observations and revealed a striking correlation between nucleosome eviction and strong activator and acetyl-CoA-dependent transcriptional activation. These novel findings uncover an exclusive role for H3 lysine 14 acetylation in facilitating the ATP-independent and transcription-independent disassembly of promoter nucleosomes by Nap1. Furthermore, these studies directly couple nucleosome disassembly with strong, activator-dependent transcription.