Font Size: a A A

Novel Computational Methods for Modeling Backbone Flexibility and Improving Side-Chain Prediction for Protein Design Applications

Posted on:2017-03-14Degree:Ph.DType:Dissertation
University:Rensselaer Polytechnic InstituteCandidate:Schenkelberg, Christian DaneFull Text:PDF
GTID:1440390005978458Subject:Bioinformatics
Abstract/Summary:
The primary objective of this work is to develop and validate a novel form of protein design, termed "Plastic protein design" or "Plasticity", to improve side-chain predictions for protein engineering efforts. Traditionally, computational protein design assumes that the protein backbone remains fixed during design. Ostensibly, this simplifies the computation significantly by removing the degrees of freedom associated with perturbing the backbone. However, since protein design necessarily involves considering alternate primary sequences, modeling backbone changes becomes necessary in order to sample realistic protein backbone conformations for these alternate primary sequences.;This manuscript presents several computational landmarks in the development of the Plastic protein design algorithm. First, the Plastic protein design methodology is discussed, implemented, and evaluated for so-called "global" and "local" scoring schemes. The limitations of these scoring approaches are discussed. Second, a study in the effectiveness of modeling proteins as structural ensembles is presented and discussed. Plasticity depends very heavily on the reliability of structural ensembles to sample backbone space that is compatible with real primary sequences, so this study has direct implications for Plastic protein design. Third, an application of multiple-template protein design involving redesigning green fluorescent protein (GFP) to function as a programmable biosensor against pathogens is discussed. One significant aim of computational research involves testing its applicability to real experimental problems. The biosensor project is an ideal candidate for this aim because preliminary data suggests that one source of error in the GFP biosensor design process concerns failure to model multiple states of the GFP chromophore maturation pathway. Lastly, a project involving the creation of a sophisticated graphical user interface (GUI) for the Rosetta modeling suite, named "InteractiveROSETTA", is presented. The final chapter discusses some future direction for both the Plastic protein design project and the InteractiveROSETTA project.
Keywords/Search Tags:Protein design, Backbone, Computational, Modeling, Primary, Project
Related items