Current Zika virus (ZIKV) outbreaks that spread in several areas of Africa, Southeast Asia, and in pacific islands is declared as a global health emergency by World Health Organization (WHO). It causes Zika fever and illness ranging from severe autoimmune to neurological complications in humans. To facilitate research on this virus, we have developed an integrative multi-omics platform; ZikaVR (http://bioinfo.imtech.res.in/manojk/zikavr/), dedicated to the ZIKV genomic, proteomic and therapeutic knowledge. It comprises of whole genome sequences, their respective functional information regarding proteins, genes, and structural content. Additionally, it also delivers sophisticated analysis such as whole-genome alignments, conservation and variation, CpG islands, codon context, usage bias and phylogenetic inferences at whole genome and proteome level with user-friendly visual environment. Further, glycosylation sites and molecular diagnostic primers were also analyzed. Most importantly, we also proposed potential therapeutically imperative constituents namely vaccine epitopes, siRNAs, miRNAs, sgRNAs and repurposing drug candidates.

Autophagy is a degradation pathway involving lysosomal machinery for degradation of damaged organelles like the endoplasmic reticulum and mitochondria into their building blocks to maintain homeostasis within the cell. ULK1, a serine/threonine kinase, is conserved across species, from yeasts to mammals, and plays a central role in autophagy pathway. It receives signals from upstream modulators such as TIP60, mTOR and AMPK and relays them to its downstream substrates like Ambra1 and ZIP kinase. The activity of this complex is regulated through protein-protein interactions and post-translational modifications. Applying in silico analysis we identified (i) conserved patterns of ULK1 that showed its evolutionary relationship between the species which were closely related in a family compared to others. (ii) A total of 23 TFBS distributed throughout ULK1 and nuclear factor (erythroid-derived) 2 (NFE2) is of utmost significance because of its high importance rate. NEF2 has already been shown experimentally to play a role in the autophagy pathway. Most of these were of zinc coordinating class and we suggest that this information could be utilized to modulate this pathway by modifying interactions of these TFs with ULK1. (iii) CATTT haplotype was prominently found with frequency 0.774 in the studied population and nsSNPs which could have harmful effect on ULK1 protein and these could further be tested. (iv) A total of 83 phosphorylation sites were identified; 26 are already known and 57 are new that include one at tyrosine residue which could further be studied for its involvement in ULK1 regulation and hence autophagy. Furthermore, 4 palmitoylation sites at positions 426, 927, 1003 and 1049 were also found which could further be studied for protein-protein interactions as well as in trafficking.

The 5-hydroxymethylcytosine (5-hmC) is known to exist as a predictive indicator for a variety of cancers, neurological abnormalities and other perilous diseases. The precursor of 5-hmC i.e. 5-methylcytosine (5mC) has already gained attention as an important epigenetic regulator whereas 5-hmC remains less explored. The two modified DNA bases (5mC and 5-hmC) have absolute diverse distribution, i.e. 5-hmC is mostly restrained to the 5' end of DNA with levels directing the gene transcription whereas 5mC is mainly located at the intra- or intergenic regions of DNA repeats and within certain gene bodies. It has been reported that levels of 5-hmC in different tissues provide a useful tool for detecting numerous associated diseases and their progression. Therefore, to unravel the role of hydroxymethylation in various resulting diseases in humans, comprehensive information on this crucial process has been explored and compiled for its implication in DNA repair system. The role of miRNAs in cancer through hypo- and hypermethylation has also been explored and discussed. In this review, a broad and exclusive insight into hydroxymethylation and its association with repair mechanisms is extensively presented and it is estimated that the accessible information will be of utmost use to the biological community working in the relevant research area.

For examining the intricate biological processes concerned with colorectal cancer (CRC), a systems biology approach integrating several biological components and other influencing factors is essential to understand. We performed a comprehensive system level analysis for CRC which assisted in unravelling crucial network components and many regulatory elements through a coordinated view. Using this integrative approach, the perceptive of complexity hidden in a biological phenomenon is extensively simplified. The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1. The transcriptional regulation of these genes was deliberated widely by examining transcription factors such as hnf4, nr2f1, znf219 and dr1 which directly influence the expression. Further, interactions of these genes/proteins were evaluated and crucial network motifs were detected to associate with the pathophysiology of CRC. The available standard statistical parameters such as z-score, p-value and significance profile were explored for the identification of key signatures from CRC pathway whereas a few novel parameters representing over-represented structures were also designed in the study. The applied approach revealed 5 key genes i.e. kras, araf, pik3r5, ralgds and akt3 via our novel designed parameters illustrating high statistical significance. These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways. Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

Immunosuppression proved as a captivating therapy in several autoimmune disorders, asthma as well as in organ transplantation. Immunosuppressive peptides are specific for reducing efficacy of immune system with wide range of therapeutic implementations. `ImmunoSPdb' is a comprehensive, manually curated database of around 500 experimentally verified immunosuppressive peptides compiled from 79 research article and 32 patents. The current version comprises of 553 entries providing extensive information including peptide name, sequence, chirality, chemical modification, origin, nature of peptide, its target as well as mechanism of action, amino acid frequency and composition, etc. Data analysis revealed that most of the immunosuppressive peptides are linear (91%), are shorter in length i.e. up to 20 amino acids (62%) and have L form of amino acids (81%). About 30% peptide are either chemically modified or have end terminal modification. Most of the peptides either are derived from proteins (41%) or naturally (27%) exist. Blockage of potassium ion channel (24%) is one a major target for immunosuppressive peptides. In addition, we have annotated tertiary structure by using PEPstrMOD and I-TASSER. Many user-friendly, web-based tools have been integrated to facilitate searching, browsing and analyzing the data. We have developed a user-friendly responsive website to assist a wide range of users.

Due to advancement in sequencing technology, genomes of thousands of cancer tissues or cell-lines have been sequenced. Identification of cancer-specific epitopes or neoepitopes from cancer genomes is one of the major challenges in the field of immunotherapy or vaccine development. This paper describes a platform Cancertope, developed for designing genome-based immunotherapy or vaccine against a cancer cell. Broadly, the integrated resources on this platform are apportioned into three precise sections. First section explains a cancer-specific database of neoepitopes generated from genome of 905 cancer cell lines. This database harbors wide range of epitopes (e.g., B-cell, CD8+ T-cell, HLA class I, HLA class II) against 60 cancer-specific vaccine antigens. Second section describes a partially personalized module developed for predicting potential neoepitopes against a user-specific cancer genome. Finally, we describe a fully personalized module developed for identification of neoepitopes from genomes of cancerous and healthy cells of a cancer-patient. In order to assist the scientific community, wide range of tools are incorporated in this platform that includes screening of epitopes against human reference proteome (http://www.imtech.res.in/raghava/cancertope/).

Xeroderma pigmentosum (XP) is a rare genetic skin disorder caused due to the extreme sensitivity for ultraviolet (UV) radiations. On its exposure, DNA acquires damages leading to skin and often neurological abnormalities. The DNA repair implicated in fixing UV-induced damages is NER and mutations in genes involved in NER and TLS form the basis of XP. The analyses of such mutations are vital for understanding XP and involved cancer genetics to facilitate the identification of crucial biomarkers and anticancer therapeutics. We detected the deleterious nsSNPs and examined them at structure-level by altering the structure, estimating secondary structure, solvent accessibility and performing site specific analysis. Crucial phosphorylation sites were also identified for their role in the disorder. These mutational and structural analyses offer valuable insight to the fundamental association of genetic mutations with phenotypic variations in XP and will assist experimental biologists to evaluate the mutations and their impact on genome.

Mismatch repair is a highly conserved process from prokaryotes to eukaryotes. Defects in mismatch repair can lead to mutations in human homologues of the Mut proteins and affect genomic stability which can result in microsatellite instability (MI). MI is implicated in most human cancers and majority of hereditary nonpolyposis colorectal cancers (HNPCCs) are attributed to defects in MLH1.

In this study, an attempt has been made to identify expression-based gene biomarkers that can discriminate early and late stage of clear cell renal cell carcinoma (ccRCC) patients. We have analyzed the gene expression of 523 samples to identify genes that are differentially expressed in the early and late stage of ccRCC. First, a threshold-based method has been developed, which attained a maximum accuracy of 71.12% with ROC 0.67 using single gene NR3C2. To improve the performance of threshold-based method, we combined two or more genes and achieved maximum accuracy of 70.19% with ROC of 0.74 using eight genes on the validation dataset. These eight genes include four underexpressed (NR3C2, ENAM, DNASE1L3, FRMPD2) and four overexpressed (PLEKHA9, MAP6D1, SMPD4, C11orf73) genes in the late stage of ccRCC. Second, models were developed using state-of-art techniques and achieved maximum accuracy of 72.64% and 0.81 ROC using 64 genes on validation dataset. Similar accuracy was obtained on 38 genes selected from subset of genes, involved in cancer hallmark biological processes. Our analysis further implied a need to develop gender-specific models for stage classification. A web server, CancerCSP, has been developed to predict stage of ccRCC using gene expression data derived from RNAseq experiments.