Professor Manukyan Receives a CCRG-MURG Award

Anna Manukyan, Assistant Professor
Natural Sciences

In my current research, I investigate the physicochemical properties of constrained chiral synthetic nucleic acids (SNA), and their binding abilities to DNA and RNA. These synthetic biomolecules bind with high sequence specificity to DNA and RNA in a gene sequence, and are of major interest in medicinal and biotechnological applications. They are used for the development of gene therapeutic agents, diagnostic devices for genetic analysis, and as molecular tools for nucleic acid manipulations.

The CCRG –MURG (Community College Research Grant – Mentored Undergraduate Research Grant) grant will allow me to perform detailed investigations of double stranded complexes formed between chiral SNAs and DNA or RNA.  Due to their properties, chiral SNAs can provide insight into the interplay between the various interactions in oligonucleotide systems. The results of this study will provide information crucial to the design of such analogues that bind exclusively and more strongly to RNA or DNA, which will aid in the discovery of new biological applications and SNA-based drug candidates.

This grant also offers opportunities to involve undergraduate students in supervised research experiences. The methods and results of my computational studies are highly interdisciplinary. By working on these interdisciplinary projects, students are given the opportunity to bridge four core disciplines of their curriculum: physics, chemistry, biology, and computer science. They are also exposed to advanced mathematical methods; a natural extension of their knowledge gained in the classroom.

Dr. Anna Manukyan is an Assistant Professor in the Department of Natural Sciences at Hostos Community College. She is an author of numerous publications in the field of theoretical and computational chemistry, and has been an invited speaker at many seminars and scientific conferences. Her primary research goals are directed toward understanding the fundamental framework of molecular recognition at the atomic level using physics-based computational methods.



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