Dr. Shachi Gosavi - Research
Protein Dynamics, Folding, Design and Assembly.
Natural proteins fold robustly because of a funnel-shaped energy landscape. This funnel shape arises because native interactions dominate the folding landscape while interactions not present in the native state (i.e., non-native interactions) contribute only in an average way. Structure based models (SBMs) of proteins ignore non-native interactions by encoding only the folded structure of the protein into the energy function. This energy function can then be used to perform molecular dynamics (MD) simulations. SBMs have been successfully used by us and others to understand the folding routes and the folding rates of several proteins. The advantage of SBMs is that they simplify the energy function such that large proteins can be folded and unfolded. In my group, we use and develop SBMs and variants to understand the folding and the conformational dynamics of natural and designed proteins.
Natural proteins have evolved to fold on a biologically reasonable timescale and to be as stable as is necessary to perform their function. However, selection directly acts only on the functional residues (where function could be binding, catalysis, cellular localization, etc.). These, functional residues cannot be mutated to make protein folding more efficient or protein stability greater. Given the choice of only twenty amino acids at each position, it has become apparent that parts of the protein which function are likely to be the least foldable or stable. Functional regions thus perturb folding from the “ideal” and we use SBMs to understand both what ideal folding is and how functional regions perturb it.
We also use understanding acquired from SBMs to experimentally design and assemble proteins.
Lab Github page: /sglabncbs