An easy-to-use and powerful tool for improved Rosetta comparative modeling of proteins

DESCRIPTION provided by applicant In this project we aim to improve on the state of the art homology modeling pipeline in the Rosetta software package strengthen its capability in modeling large proteins and structure refinement with near atomic resolution density data and sparse NMR data We will also develop a graphical user interface GUI and an easy to use backend that will allow a user to easily set up modeling tasks and access large amounts of computing The success of this project will facilitate drug design and other applications requiring accurate computational models It will also provide accuracy estimations to inform the userandapos s trust in the output model The software developed here establishes a framework in which both academic and commercial users without an extensive computational background or the time to learn a complex new command line tool can interact with the Rosetta modeling software package via a GUI The three overlapping areas to be investigated here are Improving homology modeling methods We will further develop the broken chain kinematics system incorporated in RosettaCM and benchmark against a large dataset collected from previous CASP and CAMEO experiments A more hierarchical kinematics system will be developed for modeling with known contact information and tested using a dataset with sparse NMR data Graphical user interface GUI One of the challenges of using a modeling software package such as Rosetta is that it requires a large amount of prior training in computer science including basic Linux skills software compilation simple scripting and tabular data manipulation We will develop a powerful GUI so that interactions with the Rosetta software package become much easier without sacrificing user control over key aspects of modeling Cloud computing Large computing resources are necessary to achieve massive amounts of sampling during structure modeling and this often leads to more accurate results However to the access to such computing resources is scarce and expensive to deploy locally By developing a deployment mechanism that is deliverable on both a local cluster or via cloud computing we can ensure that tasks that require large amounts of sampling are easily accessible to all scientific users PUBLIC HEALTH RELEVANCE This project addresses several challenges in making Rosetta protein modeling package more general and accessible While Rosetta has shown its capability in many structural biology tasks its flexibility in applying to a larger range of tasks outside of academic setting is a major challenge We will develop RosettaCM to be more interactive and improve the kinematics system used in RosettaCM By adding a user interface and cloud compute capability users can easily add input data adjust parameters and access large amount of computational power With this project additional features will be continuously added so that both academic and commercial users can access other applications of Rosetta modeling and design software package