Laufer Junior Fellows


  
emilano Emiliano Brini is an expert in integrating external information with physics-based simulations in order to understand biologically and pharmacologically relevant problems. These problems include the prediction of protein tertiary and quaternary structures, the effects of mutations on protein stability, and the process of drug binding. (Citations)
jason1 Jason Wagoner is interested in the study of chemical/biological problems using the perspective and tools drawn from chemical physics and statistical mechanics. This includes the study of aqueous solvation and molecular assembly, as well as the development of new simulation techniques for the multiscale modeling of biomolecular systems. (Citations)

 

 

Postdoctoral Associates

  
luca Luca Agozzino. My research interest is understanding the physical principles underlying molecular evolution and developing statistical models to correlate the rate of evolution to fitness. I am also interested in modeling molecular evolution using diffusion processes.
kamal Kamal K. Barley is an IRACDA NY-CAPS Postdoctoral Associate. My research is on the trans-disciplinary interface between biology, computational science, mathematics, and social sciences. In particular, it focuses on the use of computational and mathematical modeling and numerical approaches to obtain new insights into mechanisms underlying the dynamics in molecular, cellular, and population biology. My current research agenda aims at understanding the mechanisms underlying developmental timing mediated by MicroRNAs regulation and APOBEC driven mutagenesis in host and virus co-evolution.
dignon Gregory Dignon. The goal of my research is to develop theory, and computation-based approaches to aid in designing drug formulations for monoclonal antibodies. I am particularly interested in modeling protein-cosolvent interactions, and exploring how they may disrupt protein self-interactions, thus reducing high concentration viscosity and aggregation propensity.
sridip Sridip Parui. The broad area of my research is the prediction of structures of biomolecules and the underlying pathways such as protein folding and conformational transitions. Knowing the three-dimensional structure and the related pathways is important for understanding biomolecular function. I believe MELD, which efficiently integrates external information with physics-based modeling, can serve these purposes.
bhanita Bhanita Sharma. My research focuses on probing the protein aggregation and fibril formation using MELD simulation method. Protein aggregation involves self-assembly of normally soluble proteins into insoluble amyloid fibrils, which are linked to several diseases. I believe that the powerful approach of combined physics-based atomistic model with enhanced conformational sampling techniques can provide important insights into the early stages of protein aggregation and fibril formation, structural characteristics of protein fibrils and binding mode of amyloid inhibitors.