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 Interferon-induced helicase C domain-containing protein 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 Interferon-induced helicase C domain-containing protein 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 Interferon-induced helicase C domain-containing protein 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 Interferon-induced helicase C domain-containing protein 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 Interferon-induced helicase C domain-containing protein 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 Interferon-induced helicase C domain-containing protein 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.
Interferon-induced helicase C domain-containing protein 1
partner:
Reaxense
upacc:
Q9BYX4
UPID:
IFIH1_HUMAN
Alternative names:
Clinically amyopathic dermatomyositis autoantigen 140 kDa; Helicase with 2 CARD domains; Interferon-induced with helicase C domain protein 1; Melanoma differentiation-associated protein 5; Murabutide down-regulated protein; RIG-I-like receptor 2; RNA helicase-DEAD box protein 116
Alternative UPACC:
Q9BYX4; Q2NKL6; Q6DC96; Q86X56; Q96MX8; Q9H3G6
Background:
Interferon-induced helicase C domain-containing protein 1, also known as MDA5, plays a pivotal role in the innate immune response. It acts as a cytoplasmic sensor of viral nucleic acids, triggering antiviral responses including the induction of type I interferons and pro-inflammatory cytokines. MDA5 detects a wide range of viruses, from Picornaviridae family members to coronaviruses like SARS-CoV-2, highlighting its critical role in viral infection defense mechanisms.
Therapeutic significance:
MDA5's involvement in diseases such as Type 1 diabetes mellitus, Aicardi-Goutieres syndrome, Singleton-Merten syndrome, and Immunodeficiency 95 underscores its therapeutic potential. Understanding the role of MDA5 could open doors to potential therapeutic strategies, offering hope for treatments targeting these conditions by modulating the innate immune response.
