Michael Feig
Research Interests
We are using computational methods in order to study the structure,
dynamics, and energetics of biological macromolecules such as proteins
or nucleic acids. Our focus is concentrated in two areas: 1) The modeling
of large supramolecular assemblies in atomic detail and 2) the accurate
prediction of native protein structures.
As
an example of a supramolecular complex we are investigating the interaction
between the E.coli mismatch recognition protein MutS and DNA
with mismatched or missing base pairs. MutS recognizes defective DNA
after replication and initiates a multi-step process that leads to DNA
repair. A detailed understanding of the DNA mismatch repair system is
relevant for some types of cancer where the repair process is compromised.
Starting from crystal structures of the MutS protein-DNA complex we
apply computer simulation techniques to look at energetic and dynamic
aspects of this system.
The prediction of protein structures from sequence has seen great progress
through
recent methodological advances and the availability of an increasing
number of structural templates from experimental protein structures.
It is now often possible to generate approximate predictions that capture
many of the general features of the native fold. MORE
Recent Publications
Feig M, Burton ZF. RNA polymerase II flexibility during translocation from normal mode analysis. Proteins. 2009 Aug 5. [Epub ahead of print.]
Mukherjee S, Feig M. Conformational change in MSH2-MSH6 upon binding DNA coupled to ATPase activity. Biophys J. (2009) 96(11):L63-5.
Zavodszky MI, Stumpff-Kane AW, Lee DJ, Feig M. Scoring confidence index: statistical evaluation of ligand binding mode predictions. J Comput Aided Mol Des. (2009) 23(5):289-99.
Mukherjee S, Law SM, Feig M. Deciphering the mismatch recognition cycle in MutS and MSH2-MSH6 using normal-mode analysis. Biophys J. (2009) 96(5):1707-20.
Tanizaki, S, Clifford, J, Connelly, B, Feig, M. Conformational Sampling of Peptides in Cellular Environments. Biophysical Journal (2008) 94:747-759.
Feig M. Implicit membrane models for membrane protein simulation. Methods Mol Biol. (2008) 443:181-96.
Imamura D, Zhou R, Feig M, Kroos L. Evidence that the Bacillus subtilis SpoIIGA protein is a novel type of signal-transducing aspartic protease. J Biol Chem. (2008) 283(22):15287-99.
Kitiyaporn Wittayanarakul, Supot Hannongbua, Michael Feig Accurate prediction of protonation state as a prerequisite for reliable MM-PB(GB)SA binding free energy calculations of HIV-1 protease inhibitors. Journal of Computational Chemistry (2008) 29(5):673-685.
Zhou YC, Feig M, Wei GW. Highly accurate biomolecular electrostatics in continuum dielectric environments. J Comput Chem. (2008) Jan 15;291:87-97.
Tanizaki S, Clifford JW, Connelly BD, Feig M. Conformational Sampling of Peptides in Cellular Environments. Biophys J. (2008) Feb 1;94 3:747-59.
Olson MA, Feig M, Brooks CL 3rd. Prediction of protein loop conformations using multiscale modeling methods with physical energy scoring functions. J Comput Chem. (2008) 29(5):820-831.
Wittayanarakul K, Hannongbua S, Feig M. Accurate prediction of protonation state as a prerequisite for reliable MM-PB(GB)SA binding free energy calculations of HIV-1 protease inhibitors. J Comput Chem. (2008) 29(5):673-85.