Focused On-demand Library for Insulin-like growth factor I

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library 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.

We use our state-of-the-art dedicated workflow for designing focused libraries for receptors.

Fig. 1. The sreening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

P05019

UPID:

IGF1_HUMAN

Alternative names:

Mechano growth factor; Somatomedin-C

Alternative UPACC:

P05019; B2RWM7; E9PD02; P01343; Q14620

Background:

Insulin-like growth factor I, also known as Somatomedin-C or Mechano growth factor, plays a pivotal role in growth, glucose metabolism, and synapse maturation. It acts primarily by binding to its receptor, IGF1R, initiating signaling pathways crucial for cellular processes. Its unique ability to stimulate glucose transport and glycogen synthesis in osteoblasts distinguishes it from insulin, highlighting its significance in bone development.

Therapeutic significance:

The association of Insulin-like growth factor I with Insulin-like growth factor I deficiency, a disorder marked by growth retardation, sensorineural deafness, and intellectual disability, underscores its therapeutic potential. Understanding the role of Insulin-like growth factor I could open doors to potential therapeutic strategies for addressing not only growth disorders but also metabolic and neurological conditions.