Discovery of New Drug Targets and First-in-class Chemical Modulators: from Diverse 3D-AI data to Leads
First year funded by Mr. Joe Barnes.
From January 2025 the project is funded and administered by the Higher Education and Science Committee of Armenia.
Principal Investigator: Prof. Ruben Abagyan
University: UC San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences
Research Group: Zaruhi Karabekian, Hovakim Grabsky, Siranuysh Grabska, Gohar Sevoyan, Hayk Aghekyan, Daniel Polianczyk
Duration: 2023-2027
Project Importance
In Armenia, cardiovascular diseases and cancer are the top two most common causes of death. Armenia's cancer incidence and mortality have increased dramatically during the last two decades accounting for 21% of all deaths, with an even higher rise predicted by 2040. Unfortunately, many diseases become resistant to current treatments through mutations in drug targets. In those cases, the mutant targets need to be modulated with new therapeutic agents. Drug discovery is a multi-step process, which includes both computational and experimental techniques.
The objective for the computational part of the project is to develop a comprehensive and up-to-date computational platform based on the growing body of data, new 3D-AI methods, and continuously updated in silico models, for the discovery of new targets and binding pockets, screening for new binders/modulators, or repurposing of existing drugs. To discover new targets or disease and treatment-associated mutations, the platform will combine a diverse set of genomics, epigenomics, transcriptomics, and activity data. To this end, a platform will be developed that will cover many aspects of biological information and experimentation, which will help to design effective drugs against diseases. Once a set of likely drug candidates is identified, they will be synthesized or acquired and tested experimentally in assays to select the lead compounds with the best properties and activity profiles.
The project will be focused on therapeutic areas and molecular targets related to unmet medical needs with a particular focus on healthcare in Armenia. This platform will embrace multiple exponentially growing biomolecular, genomics data, and chemical catalogs of billions of compounds. It will facilitate the rapid discovery of the first modulators of new targets, and/or the repurposing of existing drugs for new indications.
This project will seek collaborations with experimental laboratories involved in molecular biomedicine and chemical biology in Armenia and abroad, including but not limited to the University of California, USA and the Center of Molecular Medicine of the Karolinska University Hospital in Stockholm, Sweden. The project will also include training a new generation of biomolecular researchers and drug designers in Armenia.
Expected Results and Impact
The project will significantly impact the development of drug design technology with applications in Armenia:
1. Identify therapeutic conditions including rare and neglected diseases frequent in Armenia, which are in urgent need of efficient pharmaceutical treatments. Identify and prioritize new molecular targets, and druggable pockets through which the pathways can be modulated by chemical compounds. This step can be achieved by large-scale analysis of the recently generated genomics, epigenomics, proteomics, and clinical data.
2. Deploy a robust large-scale computational drug discovery pipeline to enable, accelerate and discover an initial set of compound candidates with desired clinical profiles for experimental testing.
3. Discover first-in-class drug leads for novel targets by experimental testing of the identified in silico candidates. Existing drugs or drug candidates in clinical trials will also be considered for repurposing to a new target and/or therapeutic area using a similar approach.
4. The above goals will be accompanied by rigorous training of the participants, researchers, and students involved through seminars, publications, conferences, and exchanges with international centers of biomolecular medicine.
5. Further development of identified preclinical candidates may be licensed to new startups or partnered with pharmaceutical and biotechnology companies.
Eligibility Criteria and Selection Process
To be eligible for the project, the applicant is expected to:
Have/or to be in the process of obtaining a master's or PhD degree in mathematics, molecular structure and function, data science, medicinal chemistry, drug discovery, or biology,
Have expertise in large-scale computing, data analysis, AI and machine learning models, as well as computational methods for drug screening, discovery, and optimization,
Have a very good knowledge of English,
Plan to pursue a career in drug discovery research.