Structure-Based Ab Initio Prediction of Transcription Factor–Binding Sites

  • L. Angela Liu
  • Joel S. Bader
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 541)

Abstract

We present an all-atom molecular modeling method that can predict the binding specificity of a transcription factor based on its 3D structure, with no further information required. We use molecular dynamics and free energy calculations to compute the relative binding free energies for a transcription factor with multiple possible DNA sequences. These sequences are then used to construct a position weight matrix to represent the transcription factor–binding sites. Free energy differences are calculated by morphing one base pair into another using a multi-copy representation in which multiple base pairs are superimposed at a single DNA position. Water-mediated hydrogen bonds between transcription factor side chains and DNA bases are known to contribute to binding specificity for certain transcription factors. To account for this important effect, the simulation protocol includes an explicit molecular water solvent and counter-ions. For computational efficiency, we use a standard additive approximation for the contribution of each DNA base pair to the total binding free energy. The additive approximation is not strictly necessary, and more detailed computations could be used to investigate non-additive effects.

Key words

Transcription factor–binding sites molecular dynamics free energy position weight matrix (PWM) multi-copy thermodynamic integration protein–DNA binding 

Notes

Acknowledgments

LAL acknowledges funding from the Department of Energy (DE-FG0204ER25626). JSB acknowledges funding from NSF CAREER 0546446, NIH/NCRR U54RR020839, and the Whitaker foundation. We acknowledge a starter grant and an MRAC grant of computer time from the Pittsburgh Supercomputer Center, MCB060010P, MCB060033P, and MCB060056N.

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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • L. Angela Liu
    • 1
  • Joel S. Bader
    • 2
  1. 1.Department of Biomedical Engineering and Institute for Multiscale Modeling of Biological InteractionsJohn Hopkins UniversityBaltimoreUSA
  2. 2.Department of Biomedical Engineering and High-Throughput Biology CenterJohn Hopkins UniversityBaltimoreUSA

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