FlexE: Using elastic network models to compare models of protein structure

By Alberto Pérez, Zheng Yang, Ivet Bahar, Ken A. Dill, Justin L. MacCallum. 2012

24 citations recorded by the source corpus.

It is often valuable to compare protein structures to determine how similar they are. Structure comparison methods such as RMSD and GDT-TS are based solely on fixed geometry and do not take into account the intrinsic flexibility or energy landscape of the protein. We propose a method, which we call FlexE, that is based on a simple elastic network model and uses the deformation energy as measure of the similarity between two structures. FlexE can distinguish biologically relevant conformational changes from random changes, while existing geometry-based methods cannot. Additionally, FlexE incorporates the concept of thermal energy, which provides a rational way to determine when two models are “the same”. FlexE provides a unique measure of the similarity between protein structures that is complementary to existing methods.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests (2013, neutral): “Recently, methods using elastic network models have been proposed to computationally explore the intrinsic flexibility landscape for a single reference protein (Perez et al., 2012).”
Evaluation of predictions in the CASP10 model refinement category (2013, methodology): “…17,18 In combination with increasingly accurate physics-based force fields such as CHARMM, which have been used to successfully fold structurally diverse sets of fast-folding proteins,19–22 the major problems limiting the application of MD to protein refinement can now be mitigated to some extent.”
Virtual screening strategies in drug discovery: a critical review. (2013, methodology): “FlexE [90] Incremental build Ensemble of protein structure Empirical score”