2005 - Fellow of Alfred P. Sloan Foundation
Michael Feig mainly investigates Molecular dynamics, Solvation, Chemical physics, Crystallography and Computational chemistry. His research integrates issues of Solvent, Macromolecule, Solvation shell, Protein structure and Diffusion in his study of Molecular dynamics. His Chemical physics research integrates issues from Membrane, Lipid bilayer, Biological membrane and Force field.
Within one scientific family, Michael Feig focuses on topics pertaining to Dihedral angle under Force field, and may sometimes address concerns connected to Thermodynamics and Protein folding. His work carried out in the field of Crystallography brings together such families of science as Side chain and DNA. His study focuses on the intersection of Computational chemistry and fields such as Potential energy with connections in the field of Drude particle, Ab initio, Molecular model and Computational science.
The scientist’s investigation covers issues in Molecular dynamics, Biophysics, Chemical physics, Protein structure and Crystallography. His Molecular dynamics study improves the overall literature in Computational chemistry. His Biophysics research includes elements of Macromolecule, Cytoplasm, Biochemistry, Active site and RNA polymerase II.
His research investigates the connection with Chemical physics and areas like Solvation which intersect with concerns in Statistical physics, Poisson–Boltzmann equation and Folding. As part of one scientific family, Michael Feig deals mainly with the area of Protein structure, narrowing it down to issues related to the Algorithm, and often Sampling. The various areas that Michael Feig examines in his Crystallography study include Base pair and Hydrogen bond.
His primary areas of investigation include Molecular dynamics, Biophysics, Protein structure, Chemical physics and Macromolecule. Michael Feig works in the field of Molecular dynamics, focusing on Force field in particular. His Force field research is classified as research in Computational chemistry.
His research brings together the fields of Molecular model and Protein structure. He interconnects Intrinsically disordered proteins, Nucleic acid, Polymer and Rotational diffusion in the investigation of issues within Chemical physics. His Macromolecule research also works with subjects such as
His main research concerns Molecular dynamics, Protein structure, Force field, Biophysics and Macromolecule. His Molecular dynamics study introduces a deeper knowledge of Computational chemistry. His studies deal with areas such as Machine learning, Molecular model and Artificial intelligence as well as Protein structure.
His Force field research incorporates elements of Chemical physics and Intrinsically disordered proteins. The study incorporates disciplines such as Solvent, Viscosity, Molecule, Intermolecular force and Protein–protein interaction in addition to Biophysics. His Macromolecule study incorporates themes from Cytoplasm and Dynamics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
CHARMM: the biomolecular simulation program.
B. R. Brooks;C. L. Brooks;A. D. Mackerell;L. Nilsson.
Journal of Computational Chemistry (2009)
Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles.
Robert B. Best;Xiao Zhu;Jihyun Shim;Pedro E. M. Lopes.
Journal of Chemical Theory and Computation (2012)
Extending the treatment of backbone energetics in protein force fields: limitations of gas-phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations.
Alexander D. Mackerell;Michael Feig;Charles L. Brooks.
Journal of Computational Chemistry (2004)
CHARMM36m: An improved force field for folded and intrinsically disordered proteins
Jing Huang;Sarah Rauscher;Grzegorz Nawrocki;Ting Ran.
Nature Methods (2017)
Improved treatment of the protein backbone in empirical force fields.
Alexander D. MacKerell;Michael Feig;Charles L. Brooks.
Journal of the American Chemical Society (2004)
MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology
Michael Feig;John Karanicolas;Charles L. Brooks.
Journal of Molecular Graphics & Modelling (2004)
Recent advances in the development and application of implicit solvent models in biomolecule simulations.
Michael Feig;Charles L Brooks.
Current Opinion in Structural Biology (2004)
Performance comparison of generalized born and Poisson methods in the calculation of electrostatic solvation energies for protein structures.
Michael Feig;Alexey Onufriev;Michael S. Lee;Wonpil Im.
Journal of Computational Chemistry (2004)
New analytic approximation to the standard molecular volume definition and its application to generalized Born calculations.
Michael S. Lee;Michael Feig;Freddie R. Salsbury;Charles L. Brooks.
Journal of Computational Chemistry (2003)
An Implicit Membrane Generalized Born Theory for the Study of Structure, Stability, and Interactions of Membrane Proteins
Wonpil Im;Michael Feig;Charles L. Brooks.
Biophysical Journal (2003)
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