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 Signal peptidase complex catalytic subunit SEC11C 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 Signal peptidase complex catalytic subunit SEC11C 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 Signal peptidase complex catalytic subunit SEC11C, 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 Signal peptidase complex catalytic subunit SEC11C. 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 Signal peptidase complex catalytic subunit SEC11C. 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 Signal peptidase complex catalytic subunit SEC11C 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.
Signal peptidase complex catalytic subunit SEC11C
partner:
Reaxense
upacc:
Q9BY50
UPID:
SC11C_HUMAN
Alternative names:
Microsomal signal peptidase 21 kDa subunit; SEC11 homolog C; SEC11-like protein 3; SPC21
Alternative UPACC:
Q9BY50; B2RAA3
Background:
The Signal peptidase complex catalytic subunit SEC11C, also known as Microsomal signal peptidase 21 kDa subunit, SEC11 homolog C, SEC11-like protein 3, and SPC21, plays a crucial role in protein synthesis. It is a catalytic component of the signal peptidase complex (SPC) that specializes in the cleavage of N-terminal signal sequences from nascent proteins during their translocation into the endoplasmic reticulum. This process is vital for the proper folding and function of many proteins, as it specifically targets N-terminal signal peptides with a hydrophobic alpha-helix shorter than 18-20 amino acids.
Therapeutic significance:
Understanding the role of Signal peptidase complex catalytic subunit SEC11C could open doors to potential therapeutic strategies. Its pivotal function in protein processing within the endoplasmic reticulum highlights its potential as a target for interventions in diseases related to protein misfolding and trafficking.
