A recent research study outlines a structured and efficient method for virtual screening and developing new polypeptide-based molecules that create organized secondary structures useful in biological and materials science fields.
The study, co-led by Gaetano Montelione, Ph.D., a Professor and Constellation Endowed Chair of Chemistry and Chemical Biology at Rensselaer Polytechnic Institute (RPI), and David Baker, Ph.D., a biochemistry professor, HHMI investigator, and head of the Institute for Protein Design (IPD) at the University of Washington School of Medicine, presents a systematic and high-throughput design technique for the virtual screening and development of innovative polypeptide molecules that build regular secondary structures applicable in biology and materials science research. Baker has recently been honored as a co-recipient of the 2024 Nobel Prize in Chemistry for his pioneering work in the growing field of de novo protein design.
Regular secondary structures such as alpha helices and beta sheets are critical components of protein architecture. They are vital for comprehending protein folding and function, assisting in structure prediction, identifying drug targets, and investigating the molecular mechanisms behind diseases. The research team examined over 200,000 combinations of 130 non-biological amino acids with a wide range of chemical properties, broadening the spectrum of polypeptide secondary structures. This groundbreaking approach, created by Adam Moyer, Ph.D., led to the identification of hundreds of unique low-energy repeating structures.
“We studied 10 newly uncovered dipeptide repeating structures using circular dichroism spectroscopy, comparing them with their computed spectra,” stated Montelione. The calculated spectra predict the absorption or emission of light at specific wavelengths, aiding in characterizing the molecular forms of the polymers. These 10 dipeptide repeat polymers displayed ordered structures, as anticipated. Further NMR and X-ray crystallography investigations of two of these polymers confirmed they aligned with their computational models, validating the design approach. This computational framework is versatile for various polymers, paving the way for expansive applications in material design.
“The IPD is a global frontrunner in creating artificial intelligence and other computational methods for designing new proteins and polypeptides beneficial for numerous biotechnological and materials science uses,” remarked Montelione. “Our collaboration amplifies the effectiveness of these artificial proteins and introduces advanced technologies to RPI, boosting our ongoing scientific research initiatives aimed at developing novel biomolecules that can influence protein-protein interaction networks in cancer biology and viral infection dynamics.”
“This study provides a roadmap for designing new materials with tailored specific properties,” indicated Curt Breneman, Ph.D., the dean of RPI’s School of Science. “Additionally, it enhances our understanding of polymer structure and stability modeling.”
The research was spearheaded by recent Baker Lab graduate Adam Moyer and Theresa Ramelot, a senior research scientist in the Montelione Lab. Collaborators included RPI’s Roberto Tejero; University of Washington’s Alex Kang, Asim K. Bera, and Patrick J. Salveson; Mariano Curti and Elisabet Romero from the Barcelona Institute of Science and Technology; Margaret A. Eastman from Oklahoma State University; and Carles Curutchet from Universitat de Barcelona. Montelione, Ramelot, and Tejero are all affiliated with RPI’s Center for Biotechnology and Interdisciplinary Studies.
