AI-ACCELERATED DRUG DISCOVERY
Available from Reaxense
This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of BPI fold-containing family A member 1 including:
1. LLM-powered literature research
Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into BPI fold-containing family A member 1 therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.
Fig. 1. Preliminary target research workflow
2. AI-Driven Conformational Ensemble Generation
Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of BPI fold-containing family A member 1, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.
Fig. 2. AI-powered molecular dynamics simulations workflow
3. Binding pockets identification and characterization
We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.
Fig. 3. AI-based binding pocket detection workflow
4. AI-Powered Virtual Screening
Our ecosystem is equipped to perform AI-driven virtual screening on BPI fold-containing family A member 1. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of BPI fold-containing family A member 1. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.
Fig. 4. The screening workflow of Receptor.AI
Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.
The focused library for BPI fold-containing family A member 1 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.
BPI fold-containing family A member 1
partner:
Reaxense
upacc:
Q9NP55
UPID:
BPIA1_HUMAN
Alternative names:
Lung-specific protein X; Nasopharyngeal carcinoma-related protein; Palate lung and nasal epithelium clone protein; Secretory protein in upper respiratory tracts; Short PLUNC1; Tracheal epithelium-enriched protein; Von Ebner protein Hl
Alternative UPACC:
Q9NP55; A6XMV5; A8K9R3; E1P5M9; Q9NZT0
Background:
BPI fold-containing family A member 1, known for its alternative names such as Lung-specific protein X and Secretory protein in upper respiratory tracts, is a lipid-binding protein with high specificity for DPPC. It plays a crucial role in the innate immune responses of the upper airways, reducing surface tension in airway secretions and inhibiting biofilm formation by Gram-negative bacteria. Additionally, it regulates the cleavage of SCNN1G, contributing to airway surface liquid homeostasis and mucus clearance.
Therapeutic significance:
Understanding the role of BPI fold-containing family A member 1 could open doors to potential therapeutic strategies. Its involvement in airway immune responses and mucus clearance highlights its potential as a target for treating respiratory conditions.
