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ABSTRACT: In molecular recognition, it is often the case that ligand binding is coupled to conformational change in one or both of the binding partners. Two hypotheses describe the limiting cases involved; the first is the induced fit and the second is the conformational selection model. The conformational selection model requires that the protein adopts conformations that are similar to the ligand-bound conformation in the absence of ligand, whilst the induced-fit model predicts that the ligand-bound conformation of the protein is only accessible when the ligand is actually bound. The flexibility of the apo protein clearly plays a major role in these interpretations. For many proteins involved in signaling pathways there is the added complication that they are often promiscuous in that they are capable of binding to different ligand partners. The relationship between protein flexibility and promiscuity is an area of active research and is perhaps best exemplified by the PDZ domain family of proteins. In this study we use molecular dynamics simulations to examine the relationship between flexibility and promiscuity in five PDZ domains: the human Dvl2 (Dishevelled-2) PDZ domain, the human Erbin PDZ domain, the PDZ1 domain of InaD (inactivation no after-potential D protein) from fruit fly, the PDZ7 domain of GRIP1 (glutamate receptor interacting protein 1) from rat and the PDZ2 domain of PTP-BL (protein tyrosine phosphatase) from mouse. We show that despite their high structural similarity, the PDZ binding sites have significantly different dynamics. Importantly, the degree of binding pocket flexibility was found to be closely related to the various characteristics of peptide binding specificity and promiscuity of the five PDZ domains. Our findings suggest that the intrinsic motions of the apo structures play a key role in distinguishing functional properties of different PDZ domains and allow us to make predictions that can be experimentally tested.
PLoS Computational Biology 11/2012; 8(11):e1002749. · 5.22 Impact Factor
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ABSTRACT: In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications. Availability: JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license .
Journal of Chemical Information and Modeling 12/2011; 52(1):255-9. · 4.68 Impact Factor
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BMC Bioinformatics. 01/2010; 11:188.
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ABSTRACT: The dynamic motions of many proteins are central to their function. It therefore follows that the dynamic requirements of a protein are evolutionary constrained. In order to assess and quantify this, one needs to compare the dynamic motions of different proteins. Comparing the dynamics of distinct proteins may also provide insight into how protein motions are modified by variations in sequence and, consequently, by structure. The optimal way of comparing complex molecular motions is, however, far from trivial. The majority of comparative molecular dynamics studies performed to date relied upon prior sequence or structural alignment to define which residues were equivalent in 3-dimensional space.
Here we discuss an alternative methodology for comparative molecular dynamics that does not require any prior alignment information. We show it is possible to align proteins based solely on their dynamics and that we can use these dynamics-based alignments to quantify the dynamic similarity of proteins. Our method was tested on 10 representative members of the PDZ domain family.
As a result of creating pair-wise dynamics-based alignments of PDZ domains, we have found evolutionarily conserved patterns in their backbone dynamics. The dynamic similarity of PDZ domains is highly correlated with their structural similarity as calculated with Dali. However, significant differences in their dynamics can be detected indicating that sequence has a more refined role to play in protein dynamics than just dictating the overall fold. We suggest that the method should be generally applicable.
BMC Bioinformatics 01/2010; 11:188. · 2.75 Impact Factor
