Abstract
Despite significant progress in recent years, ab initio folding is still one of the most challenging problems in structural biology. This paper presents a probabilistic graphical model for ab initio folding, which employs Conditional Random Fields (CRFs) and directional statistics to model the relationship between the primary sequence of a protein and its three-dimensional structure. Different from the widely-used fragment assembly method and the lattice model for protein folding, our graphical model can explore protein conformations in a continuous space according to their probability. The probability of a protein conformation reflects its stability and is estimated from PSI-BLAST sequence profile and predicted secondary structure. Experimental results indicate that this new method compares favorably with the fragment assembly method and the lattice model.
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Zhao, F., Peng, J., DeBartolo, J., Freed, K.F., Sosnick, T.R., Xu, J. (2009). A Probabilistic Graphical Model for Ab Initio Folding. In: Batzoglou, S. (eds) Research in Computational Molecular Biology. RECOMB 2009. Lecture Notes in Computer Science(), vol 5541. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02008-7_5
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DOI: https://doi.org/10.1007/978-3-642-02008-7_5
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