Designing highly specific immunotherapeutics through structure-based cytokine engineering: A combined in silico and deep learning approach.
Implementing Organization
Plaksha University
Principal Investigator
Dr. Monika Sharma
Plaksha University
About
Cytokines are small, non-structural signaling proteins that regulate immune functions and are involved in physiological and pathophysiological processes. They can orchestrate immune responses to combat specific threats but can also mediate inflammatory autoimmune diseases and cause host tissue injury. Identifying the determinants for individual cellular responses to cytokines is crucial for harnessing their potential as therapeutics. Recent structural studies have solved many cytokine-receptor extracellular domain ECD complexes, and the kinetics of complex formation and stability are influenced by ligand-receptor binding affinity, which affects signal activation strength and duration. Cytokine profiling has been used as a biomarker to evaluate disease progression, making cytokines promising targets for drugs. However, our knowledge of cytokine biology is limited due to observed degeneracy in cytokine behavior. The proposed studies aim to identify the parameters used to modulate cytokine activities and pave the way for future biomolecular engineering studies. In silico modeling and simulation will be used to obtain biophysical parameters about the stability and dynamics of ligand-receptor complexes. The energetics of complex formation will be investigated in silico using enhanced umbrella sampling techniques. The successful conclusion of these studies will provide a deep learning model to identify underlying parameters contributing to cytokine specificity and allow designing ligand variants that can alter the cytokine-receptor complex and regulate the downstream signal pathway.