The HABD: Home of All Biological Databases Empowering Biological Research With Cutting‐Edge Database Systems

Ullah, Shahid; Rahman, Wajeeha; Ullah, Farhan; Ullah, Anees; Ahmad, Gulzar; Ijaz, Muhammad; Ullah, Hameed; Sharafmal, Din Mohammad

doi:10.1002/cpz1.1063

Current Protocols

2024

DOI: 10.1002/cpz1.1063

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The HABD: Home of All Biological Databases Empowering Biological Research With Cutting‐Edge Database Systems

Shahid Ullah,

Wajeeha Rahman,

Farhan Ullah

et al.

Abstract: The emergence of computer technologies and computing power has led to the development of several database systems that provide standardized access to vast quantities of data, making it possible to collect, search, index, evaluate, and extract useful knowledge across various fields. The Home of All Biological Databases (HABD) has been established as a continually expanding platform that aims to store, organize, and distribute biological data in a searchable manner, removing all dead and non‐accessible data. The… Show more

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2024

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Cited by 2 publications

References 90 publications

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CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations

Ullah,

Li,

Rahman

et al. 2024

Database

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Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths’, country-wise distribution, ‘new cases and recovery’, and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/

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CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations

Ullah,

Li,

Rahman

et al. 2024

Database

View full text Add to dashboard Cite

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Elucidating the inhibitory mechanism of Zika virus NS2B-NS3 protease with dipeptide inhibitors: Insights from molecular docking and molecular dynamics simulations

Ullah,

Rahman

et al. 2024

PLoS ONE

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Microcephaly, Guillain-Barré syndrome, and potential sexual transmission stand as prominent complications associated with Zika virus (ZIKV) infection. The absence of FDA-approved drugs or vaccines presents a substantial obstacle in combatting the virus. Furthermore, the inclusion of pregnancy in the pharmacological screening process complicates and extends the endeavor to ensure molecular safety and minimal toxicity. Given its pivotal role in viral assembly and maturation, the NS2B-NS3 viral protease emerges as a promising therapeutic target against ZIKV. In this context, a dipeptide inhibitor was specifically chosen as a control against 200 compounds for docking analysis. Subsequent molecular dynamics simulations extending over 200 ns were conducted to ascertain the stability of the docked complex and confirm the binding of the inhibitor at the protein’s active site. The simulation outcomes exhibited conformity to acceptable thresholds, encompassing parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), ligand-protein interaction analysis, ligand characterization, and surface area analysis. Notably, analysis of ligand angles bolstered the identification of prospective ligands capable of inhibiting viral protein activity and impeding virus dissemination. In this study, the integration of molecular docking and dynamics simulations has pinpointed the dipeptide inhibitor as a potential candidate ligand against ZIKV protease, thereby offering promise for therapeutic intervention against the virus.

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The HABD: Home of All Biological Databases Empowering Biological Research With Cutting‐Edge Database Systems

Cited by 2 publications

References 90 publications

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations

Elucidating the inhibitory mechanism of Zika virus NS2B-NS3 protease with dipeptide inhibitors: Insights from molecular docking and molecular dynamics simulations

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