Pilot Grants to Explore the Use of the American Heart Association Protein Binding Atlas to Discover Novel Protein Interactions

Award Details

Duration: Up to one year of funding from date of funding, contingent upon milestones and timelines being met.
Grant Amount: Each award will total $100,000 (including 10% indirect costs)
Number of Awards: The AHA anticipates awarding up to four grants; the AHA reserves the right to determine the final number of awardees.

Description

The purpose of this request for proposals (RFP) is to solicit applications for innovative pilot projects aimed at predicting and understanding protein-protein and protein-small molecule interactions involved in key biological processes associated with cardiovascular, kidney, and metabolic diseases, including obesity. The proposed projects are encouraged to utilize the American Heart Association (AHA) Protein Portal.

The AHA Protein Binding Atlas was established through a Cooperative Research and Development Agreement between the AHA and the Lawrence Livermore National Laboratory (LLNL). Its objective is to combine world-class technology and high-impact biology to develop a comprehensive reference atlas of cell-protein targets to accelerate and hone drug discovery. The AHA Protein Binding Atlas leverages the world-class high performance computing power of Lawrence Livermore National Laboratory and machine learning algorithms for protein-molecule binding predictions to refine and accelerate candidate drug selection for clinical development. The Protein Binding Atlas consists of approximately two million small molecules fully simulated against nearly 15,000 proteins to model binding predictions. The Atlas is a static database of in-silico calculations of protein-ligand interactions, as well as supplemental information for proteins and ligands, intended to provide insight into drug-candidate molecules regarding on-target interactions and off-target interactions.

A successful proposal will integrate the AHA Protein Portal and may focus on computational modeling, proteomics, network biology, and systems biology to deliver predictive insights for therapeutic development in these disease areas.

A successful proposal will include one or more of the following:

1. Identify Druggable Targets: Investigate and predict small molecules, peptides, or other entities that bind to key proteins involved in cardiovascular, kidney, and metabolic diseases, including
2. obesity.
3. Identify Opportunities to Repurpose Existing Drugs by evaluating “off-target” protein binding that may represent druggable targets.
4. Predict Off-Target Effects: Utilize computational and experimental approaches to predict potential off-target effects of molecules that interact with proteins involved in disease processes. This will aid in improving the safety and specificity of future drug candidates.
5. Predict Ligand-Protein Binding using a Machine Learning Approach
6. Predict the Impact of Post-Translational Modifications (PTMs): Predict how post-translational modifications, such as phosphorylation, acetylation, glycosylation, and ubiquitination, alter the activity and function of proteins relevant to disease pathways.
7. Analyze Gene Mutations and Their Impact on Protein Binding and Function: Investigate how mutations in genes associated with cardiovascular, kidney, and metabolic diseases, including obesity, may alter protein binding dynamics, protein function, and overall disease progression.

 

For more information, please see the opportunity webpage.