Computational Biology Core

总结（核心B）

SUMMARY (Core B) One of the key strengths of this Program Project is the powerful reciprocal relationship of in silico modeling and simulation with targeted structural and functional experimentation. Thus, experimental results can be channeled back into in situ studies to iteratively improve models. The overarching goal of the Computational Biology Core (Core B) is to take advantage of information from the literature, experimental results from our Program, and ab initio modeling to create, and continually improve, molecularly detailed structural models and functional hypotheses for each step, and each major player, in cholesterol efflux. The core is structured to provide the following services: 1) create model structures and perform several varieties of molecular dynamics (MD) simulations of molecular models—SMD, CGMD, STMD—relevant to each Project; 2) refine structures of ABCA1, APOA1, and various HDL particles generated during the previous PPG cycle; 3) provide a platform for comparing molecular models to experimental data (chemical crosslinking, HDL particle sizes derived from ion mobility analyses, HDL composition, etc.). One primary tool will be construction of protein contact maps; 4) use LOCATE to analyze and refine the molecular basis for interactions of amphipathic helical domains of APOA1, APOA2, and other apolipoproteins with each other as well as their interactions with ABCA1; 5) use Rosetta for ab initio modeling and docking (e.g. APOA1’s interactions with ABCA1; APOA2’s interactions with APOA1, etc.). Core B will be led by Jere Segrest, MD, PhD, working closely with Hyun Song, PhD, at Vanderbilt University Medical Center campus, near where Project 3 is located. Both investigators have extensive, well- documented expertise in all areas of the Core’s proposed services. In the previous PPG cycle, the Core executed thousands of hours of computer simulations that generated dozens of detailed molecular models for experimental testing by all three Projects. Many of these models will contribute critically to the ongoing studies proposed in this renewal cycle.