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Cancer is the second biggest cause of death globally, and the use of therapeutic peptides to specifically target and destroy cancer cells has gotten much interest. Cancer peptides or vaccinations are utilized to treat cancer nowadays, apart from chemotherapy, which has significant discomfort, side effects and costly. It is time demanding to identify and predict potential anticancer peptides using computational biology approaches. Thus, 3-D molecular modeling is being used to find possible ACP candidates. In this research, Curcuma longa has predicted peptide sequences were docked on breast cancer receptors and used a molecular docking technique to assess the anticipated peptides’ binding affinities to MHC molecules. A similar approach was utilized to simulate the interactions of the chosen peptide with the TCR. Additionally, the Pep10 LIRQHVASNIGIAKSKIREPIV was examined, and our findings indicated interaction with MHC classes I and II. However, the maximum binding energy was obtained with TCR at 695.61, giving strength through eight hydrogen bonds. Similarly, the Pep20, GAIIGNRKIKLQPHIIIRID, the projected, has the most significant overall binding energy with MHC classes I and II but a lower global E total value with TCR, namely −600.97 kj/Mol, and also four hydrogen bonds. This research could lead to the development of novel anticancer drugs based on the anticancer activity of the Curcuma longa medicinal plant. [ABSTRACT FROM AUTHOR]

Aims: Respiratory cancer database (RespCanDB) is a genomic and proteomic database of cancer of respiratory organ. It also includes the information of medicinal plants used for the treatment of various respiratory cancers with structure of its active constituents as well as pharmacological and chemical information of drug associated with various respiratory cancers.Materials and Methods: Data in RespCanDB has been manually collected from published research article and from other databases. Data has been integrated using MySQL an object-relational database management system. MySQL manages all data in the back-end and provides commands to retrieve and store the data into the database. The web interface of database has been built in ASP.Results and Conclusions: RespCanDB is expected to contribute to the understanding of scientific community regarding respiratory cancer biology as well as developments of new way of diagnosing and treating respiratory cancer. Currently, the database consist the oncogenomic information of lung cancer, laryngeal cancer, and nasopharyngeal cancer. Data for other cancers, such as oral and tracheal cancers, will be added in the near future. The URL of RespCanDB is http://ridb.subdic-bioinformatics-nitrr.in/. [ABSTRACT FROM AUTHOR]

Gastrointestinal Cancer Database (GICDB) is a repository of genetic association studies on gastrointestinal cancer which allows researchers to interpret the risk factors of the disease accurately and provide new insights towards further work. GICDB has been developed to provide a platform to clinicians and researchers for the easy retrieval of appropriate information. All data are stored and managed in MySQL and web interface has been developed in ASP. Currently, the database integrates information of 463 genes and 713 miRNA; these genes are implicated in the diverse phases of various gastrointestinal (GI) cancers. GICDB is distinct from other databases in that: (i) it consists of information on genes and miRNAs involved in various GI cancers; (ii) data in GICDB are linked to other on-line resources such as Entrez, Ensemble, UniGene, Swiss-Prot and On-Line Mendelian Inheritance in Man; (iii) there is information on GI cancer-associated drugs retrieved from DrugBank, and (iv) it also integrates the information related to medicinal plants and their use in the treatment of different GI cancers with the structure of their chemical constituents. Unambiguously this database would provide a platform to retrieve genuine information for researchers working on GI cancer. [ABSTRACT FROM AUTHOR]

One of the severe monogenic conditions with the highest prevalence in the globe is sickle cell disease. Although the significance of chronic anemia, hemolysis, and vasculopathy has been established, hemoglobin polymerization, which results in erythrocyte stiffness and Vaso-occlusion, is important to the pathophysiology of this disease. Clinical management is elementary, and there is scant reliable data for many treatments. The onset of cerebrovascular illness and cognitive impairment are two of the major issues associated with sickle cell disease in children, and it is only now that researchers are beginning to understand how blood transfusions and hydroxycarbamide can prevent these complications. When Vaso occlusion and inflammation occur repeatedly, the majority of organs are gradually damaged, including the brain, kidneys, lungs, bones, and cardiovascular system. This damage worsens with age. In our study, we focused on the specific pathways which are affected by the involvement of effected genes. Firstly, we retrieved the gene datasets from the publically available data source website DisGNET. Using literature-based genes, we identified 290 highly regulated genes that are directly associated with sickle cell disease. We subsequently performed a gene expression analysis and extracted a gene set using GEO2R analysis, which was then used to prune 290 differentially expressed genes (DEGs). After pruning we got 60 highly expressed genes. After identification of DEGs, we used these genes for pathway analysis. For the pathway analysis, we used Reactome software and we found that these DEGs are directly associated with 7 different pathways, which are alpha beta signaling pathways, 15 antiviral mechanism, Oligoadenylate synthetase (OAS) antiviral response, interleukin 1 signaling pathways, interleukin 4 and 13, interleukin 10 signaling pathway, and aspirin ADME pathway. After pathway analysis, we can exactly relate how sickle cell disease alters the gene expression and how these genes affect the different pathways. Additionally, we performed gene ontology of 60 genes and identified the gene biological process, cellular component, and molecular functions as we mentioned in our results. With the help of our study data, there is a chance for pre-identification of sickle cell disease person. Our gene result was used as a biomarker of sickle cell disease. In this paper, our result is the primary approach for sickle cell disease; with the help of this paper any researcher can get their primary data and use that for further research., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Advanced technology innovations allow cost-effective, high-throughput profiling of biological systems. It enabled genome sequencing in days using advanced technologies (e.g., next-generation sequencing, microarrays, and mass spectrometry). Since technology has been developed, massive biological data (e.g., genomics, proteomics) has been produced cheaply, allowing the "big data" era to create new opportunities to solve medical and biological complications in many disciplines-preventive medicine, biology, Personalized Medicine, gene sequencing, healthcare, and industry. Computational biology and bioinformatics are interdisciplinary fields that develop and apply computational methods (e.g., analytical methods, mathematical modeling, and simulation) to analyze large collections of biological data, such as genetic sequences, cell populations, or protein samples, to make new predictions or discover new biology. Biological data storage, mining, and analysis have challenges because data is much more heterogeneous. In this study, the big data resources of genomics, proteomics, and metabolomics have been explored to solve biological problems using big data analysis approaches. The goal is to build a network of relationship-based gene-disease associations to prioritize phenotypes common to epilepsy and seizure disease. Through network analysis, The 10 seed genes, 22 associated genes, 132 microRNAs, and 38 transcription factors have been identified that have a direct effect on all forms of epilepsy and seizures. The majority of seed genes, according to the results of a functional analysis of seed genes, are involved in the acetylcholine-gated channel complex (10%) and the heterotrimeric G-protein complex (10%) pathways related to cellular components, followed by a role in the regulation of action potential (20%) and positive regulation of vascular endothelial growth factor production (20%) in Epilepsy and Seizures pathways related to biological processes. This study might provide insight into the workings of the disease and shows the importance of continued research into epilepsy and other conditions that can trigger seizure activity., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)