| Grant number: | 17/03191-2 |
| Support type: | Scholarships abroad - Research |
| Effective date (Start): | March 01, 2018 |
| Effective date (End): | August 31, 2018 |
| Field of knowledge: | Interdisciplinary Subjects |
| Principal researcher: | Rodrigo Vargas Honorato |
| Grantee: | Rodrigo Vargas Honorato |
| Host: | Alexandre Bonvin |
| Home Institution: | Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). Campinas , SP, Brazil |
| Research place: | Utrecht University (UU), Netherlands |
Abstract The computational modeling of protein structures, interactions and dynamics has been advancing steadily in the past decades. Nonetheless researchers still face challenges when modeling biomolecular systems with large conformational spaces. Lowering the level of representation from all-atom to coarse-grained is a way to bypass limitations such as algorithmic efficiency and available computing power. The objective of a coarse-grained representation is to reduce the degrees of freedom, replacing side chains with pseudo-atoms. In order to develop coarse-grained force fields, efforts have been applied in two fronts; physics-based, following the same philosophy of it full-atom counterpart, basing it on molecular physics and knowledge-based that takes advantage the growing databases via statistical analysis. Here we will expound on the knowledge-based approach, the MARTINI force field. Four non-hydrogen atoms are mapped to one CG bead which describes one or more chemical building blocks along with its properties. Nucleotides are mapped to six or seven CG beads. The phosphate accounts for one bead and sugar for two, pyrimidines are represented as three-bead rings and purines as four-bead rings. Computational docking is a powerful tool to model three-dimensional structures of macromolecular interactions. By sampling a large number of possible conformations and selecting those with low interaction energies it is possible to obtain a native-like conformational of a macromolecular complex. The high ambiguity driven docking approach software HADDOCK developed in Alexandre Bonvin Lab uses biochemical and/or biophysical interactions to predict such interactions. The proposed research project aims to implement and benchmark a coarse-grained DNA/RNA model into HADDOCK. The use of coarse-grained models has enabled researchers to simulate large-scale biomolecular processes on time scales that were previously inaccessible to full-atom models. For such the following will be carried out; conversion of structures to CG models will be carried out by a conversion script adapted from the one provided by the research group responsible for MARTINI, adaptation of the MARTINI DNA/RNA topology and parameters to the CNS format, integration of the MARTINI CG DNA/RNA force field into HADDOCK, performance evaluation using a benchmark of Protein-DNA complexes and final assessment according to CAPRI criteria. Optimization of the scoring functions will consist of an evaluation of different ranges of weights in each of interaction energies and comparison with the CAPRI evaluation in order to obtain optimal weights to correctly identify the best generated complexes. | |
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