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Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits

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Book cover Computational Protein Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1529))

Abstract

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

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Acknowledgments

The authors thank the financial support from Fundação para a Ciência e a Tecnologia, Portugal, through contracts SFRH/BD/90644/2012 (H.F.C.), SFRH/BPD/69163/2010 (R.J.F.B.), and ERA-IB-2/0001/2013. This work was supported by the Unidade de Ciõncias Biomoleculares Aplicadas-UCIBIO, which is financed by national funds from FCT/MEC (UID/Multi/04378/2013) and co-financed by the ERDF under the PT2020 Partnership Agreement (POCI-01-0145-FEDER-007728). The authors would like to thank also the support from Centre National de la Recherche Scientifique (CNRS), France and FCT, Portugal, through the International Program of Scientific Cooperation (PROJECT PICS-147340).

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Correspondence to Olga Iranzo or Ricardo J. F. Branco .

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Carvalho, H.F., Barbosa, A.J.M., Roque, A.C.A., Iranzo, O., Branco, R.J.F. (2017). Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits. In: Samish, I. (eds) Computational Protein Design. Methods in Molecular Biology, vol 1529. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6637-0_8

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  • DOI: https://doi.org/10.1007/978-1-4939-6637-0_8

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6635-6

  • Online ISBN: 978-1-4939-6637-0

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