BUILDING COMPLEXITY INTO THE COMPUTER-AIDED DRUG DESIGN PIPELINE THROUGH

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. (A) OBJECTIVE The incorporation of nucleic acids into the drug discovery methodology is critical for a host of targets and may provide more selective therapeutics that are less amenable to resistance. This will provide insights into molecular recognition at the protein-nucleic acid level and alternate mechanisms for therapeutic design. Yet, techniques that efficiently and systematically include nucleic acids in the drug discovery pipeline are lacking, and crystallization of RNA can be challenging due to its inherent instability and flexibility. The goal of this collaborative project is to develop computational methodology to systematically incorporate nucleic acids, particularly RNA into the relaxed complex scheme (RCS), and subsequently build these new technologies into our Vision-based pipeline tool for computer-aided drug discovery (CADD). Developing a systematic computational infrastructure is central to our approach. The new CADD pipeline infrastructure that will be developed by NBCR will: (i) facilitate accurate and realistic simulations of hybrid protein-RNA biomolecular systems through the Vision workflow tool, (ii) develop and provide analysis tools for these simulations, (iii) provide a systematic framework to analyze and incorporate the resulting nucleic acid structural information into the RCS CADD pipeline. Our experimental collaborators are committed to testing our predictions  both in terms of biochemical assays and crystal structures of the very best binders  that result from these investigations, and this will be critical for verifying our methodology. Ultimately, a RCS CADD tool that is capable of handling RNA and hybrid protein-nucleic acid based drug targets will be developed and distributed as a tool for the larger scientific community.