AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for CCAAT/enhancer-binding protein alpha

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

P49715

UPID:

CEBPA_HUMAN

Alternative names:

-

Alternative UPACC:

P49715; A7LNP2; P78319; Q05CA4

Background:

CCAAT/enhancer-binding protein alpha (CEBPA) is a transcription factor pivotal in the regulation of cellular differentiation and proliferation, particularly in myeloid cells, adipocytes, and liver cells. It binds to specific DNA sequences, promoting the expression of genes involved in cell maturation and energy homeostasis. CEBPA's role is crucial in early embryogenesis, liver and lung development, and adipocyte differentiation.

Therapeutic significance:

Given its critical function in the differentiation of myeloid progenitors and its involvement in acute myelogenous leukemia (AML), CEBPA presents a promising target for therapeutic intervention. Understanding the role of CEBPA could open doors to potential therapeutic strategies in treating AML by correcting the differentiation process of hematopoietic precursors.

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