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 Activating signal cointegrator 1 complex subunit 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 Activating signal cointegrator 1 complex subunit 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 Activating signal cointegrator 1 complex subunit 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 Activating signal cointegrator 1 complex subunit 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 Activating signal cointegrator 1 complex subunit 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 Activating signal cointegrator 1 complex subunit 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.
Activating signal cointegrator 1 complex subunit 1
partner:
Reaxense
upacc:
Q8N9N2
UPID:
ASCC1_HUMAN
Alternative names:
ASC-1 complex subunit p50; Trip4 complex subunit p50
Alternative UPACC:
Q8N9N2; Q5SW06; Q5SW07; Q96EI8; Q9Y307
Background:
Activating signal cointegrator 1 complex subunit 1 (ASC-1 complex subunit p50) is a pivotal protein involved in DNA damage repair as part of the ASCC complex. It also enhances NF-kappa-B, SRF, and AP1 transactivation within the ASC-1 complex. This protein plays a crucial role in the induction of SERPINB2 expression in response to gastrin-activated paracrine signals and is implicated in the development of neuromuscular junctions.
Therapeutic significance:
ASC-1 complex subunit p50 is linked to Barrett esophagus, a condition with increased risk of esophageal adenocarcinoma, and Spinal muscular atrophy with congenital bone fractures 2, a severe neuromuscular disorder. Understanding the role of this protein could open doors to potential therapeutic strategies for these diseases.
