A probabilistic graphical model for ab initio folding

Feng Zhao, Jian Peng, Joe De Bartolo, K. F. Freed, Tobin R. Sosnick, Jinbo Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 13th Annual International Conference, RECOMB 2009, Proceedings
Pages59-73
Number of pages15
DOIs
StatePublished - 2009
Externally publishedYes
Event13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009 - Tucson, AZ, United States
Duration: May 18 2009May 21 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5541 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009
Country/TerritoryUnited States
CityTucson, AZ
Period5/18/095/21/09

Keywords

  • Ab initio folding
  • Conditional random fields (CRFs)
  • Directional statistics
  • Fragment assembly
  • Lattice model
  • Protein structure prediction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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