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A Probabilistic Graphical Model for Ab Initio Folding.

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.

SUBMITTER: Zhao F

PROVIDER: S-EPMC3583211 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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A Probabilistic Graphical Model for Ab Initio Folding.

Zhao Feng F Peng Jian J Debartolo Joe J Freed Karl F KF Sosnick Tobin R TR Xu Jinbo J

Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- ) 20090101

Despite significant progress in recent years, <i>ab initio</i> 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 gra ...[more]

PMID: 23459639

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