Focused On-demand Library for Fibroblast growth factor receptor 1

Available from Reaxense
Predicted by Alphafold

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

Basic fibroblast growth factor receptor 1; Fms-like tyrosine kinase 2; N-sam; Proto-oncogene c-Fgr

Alternative UPACC:

P11362; A8K6T9; A8K8V5; C1KBH8; P17049; Q02063; Q02065; Q14306; Q14307; Q53H63; Q59H40; Q5BJG2; Q8N685; Q9UD50; Q9UDF0; Q9UDF1; Q9UDF2


Fibroblast growth factor receptor 1 (FGFR1), also known as Basic fibroblast growth factor receptor 1, Fms-like tyrosine kinase 2, N-sam, and Proto-oncogene c-Fgr, plays a pivotal role in embryonic development, cell proliferation, differentiation, and migration. It acts as a cell-surface receptor for fibroblast growth factors, essential for normal mesoderm patterning, axial organization, skeletogenesis, and the development of the gonadotropin-releasing hormone (GnRH) neuronal system.

Therapeutic significance:

FGFR1's involvement in diseases such as Pfeiffer syndrome, Hypogonadotropic hypogonadism 2, Osteoglophonic dysplasia, Hartsfield syndrome, Trigonocephaly 1, Encephalocraniocutaneous lipomatosis, and Jackson-Weiss syndrome highlights its therapeutic significance. Targeting FGFR1 could lead to innovative treatments for these genetic disorders.

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