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Computational Chemistry and Biophysics lab
Location :Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA.
Understanding the physical process by which a polypeptide sequence adapts a unique three-dimensional structure is one of the most fundamental problems in biology. Recent experimental studies suggest a link between protein misfolding, aggregation and a class of human disorders, such as the Alzheimerís, Parkinsonís and mad cow diseases, underscoring the need for a detailed mechanistic understanding of protein folding.
Over the last decade, significant progress has been made in theoretical investigations of protein folding. Notably, the energy landscape theory has enabled computational studies based on simplified and coarse-grained models. High performance computing power, implicit solvent models and advanced conformational sampling methods have allowed in silico folding of small proteins at atomic resolution.
Our major research interest is to obtain atomic-level understanding of how molecular interactions and cellular factors, such as pH, salt, metal ions, macromolecular crowding and molecular chaperons influence protein folding, misfolding and aggregation. To achieve this goal, we are interested in developing theoretical methods and physical models based on classical, statistical and quantum mechanical theories as well as in implementing these methods and models using advanced numerical algorithms and computing architectures.