EGFRIndb is a specialized, literature-curated database focused on small synthetic molecular inhibitors of the Epidermal Growth Factor Receptor (EGFR) family. This resource centralizes experimental data on compounds targeting EGFR and its various isoforms, which are critical pharmacological targets due to their association with cancers such as lung and breast cancer.
Web Server: https://webs.iiitd.edu.in/raghava/egfrindb/
This dataset can also be found on Zenodo at https://doi.org/10.5281/zenodo.20068093
The EGFR family consists of four trans-membrane protein isoforms: EGFR (ErbB1), ErbB2, ErbB3, and ErbB4. Aberrant activity, such as overexpression or mutation in these receptors, often leads to uncontrolled cell proliferation and cancer. EGFRIndb was developed to pool scattered biological activity data into a single platform to support drug discovery and decision-making.
- Data Scope: Curated from PubMed and Google Scholar search results through December 2013.
- Target Diversity: Includes inhibitors for EGFR, ErbB2, ErbB4, and clinically relevant mutants.
The database currently houses 4,581 unique synthetic compounds. Each entry provides:
- Structural Information: 2D and 3D structures, SMILES, InChI, and InChIKey.
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Inhibitory Activity: Quantitative values such as
$IC_{50}$ ,$K_{i}$ ,$K_{d}$ ,$EC_{50}$ , and percentage inhibition. - Physicochemical Properties: Molecular mass, logP, polar surface area (PSA), and hydrogen bond donor/acceptor counts.
EGFRIndb tracks specific classes of inhibitors designed to overcome clinical drug resistance:
- Irreversible Inhibitors: 367 compounds that bind covalently to specific residues, such as Cys773 of EGFR or Cys805 of ErbB2.
- Dual Inhibitors: 618 compounds that target both EGFR and ErbB2 simultaneously.
- Mutant Inhibitors: Data for compounds targeting resistant mutations like T790M, L858R, and the double mutant L858R/T790M.
- Filters: Compounds are evaluated against rules like Lipinski’s rule of five, Veber, Ghose, Muegge, and Lead-likeliness to determine oral bioavailability and drug-likeliness.
- Selectivity Data: Provides curated inhibitory activity against other non-EGFR kinases to help assess compound specificity and selectivity.
EGFRIndb offers several user-friendly modules for data exploration:
- Simple & Advanced Search: Query by molecule name, IUPAC name, PMID, or specific ranges of physicochemical properties and inhibitory values.
- Similarity Search: Features an integrated JME molecular editor allowing users to draw structures online and search for similar molecules in the database.
- Browse Module: Allows access to the entire collection by inhibitor class (e.g., quinazolines, pyrimidines), cell line (e.g., A431, MCF-7), or inhibitory range.
- Data Download: Supports single compound downloads in mol format or batch downloads of specific datasets.
- Chemo-informatics: Developing QSAR models and virtual screening protocols.
- Lead Optimization: Identifying scaffolds with higher potency than established drugs like gefitinib or erlotinib.
- Mechanism Research: Understanding the chemistry of reversible versus irreversible binding modes.
Dr. Subhash M. Agarwal (Corresponding Author)
Prof. Gajendra P.S. Raghava (Corresponding Author) raghava@iiitd.ac.in Department of Computational Biology, Indraprastha Institute of Information Technology (IIIT Delhi), New Delhi, India.
EGFRIndb was supported by the Department of Biotechnology (DBT) and the Indian Council of Medical Research (ICMR). The website is hosted on the Open Source Drug Discovery (OSDD) platform and IIIT Delhi.