Improving Structure-Based Function Prediction Using Molecular Dynamics

Abstract

Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods.

Molecular Dynamics as an Approach to Study Prion Protein Misfolding and the Effect of Pathogenic Mutations

“…A method that has had a particularly large impact is molecular dynamics (MD) simulation. This technique allows for the detailed examination of the complex internal motions and conformational changes in proteins, which is often important for understanding their function [27][28][29]. Furthermore, MD simulations provide uniquely detailed information necessary to understand protein folding [30,31] and, crucially, disease-related protein misfolding [32,33].…”

Classification of Enzymes Using Machine Learning Based Approaches: A Review

“…Table 3 shows the results obtained from tenfold cross-validation experiment. The overall accuracy achieved is 100%, which is quiet favorable when we compare it to other articles [18,19], like neural network which shows the accuracy of approximately 75% and 91.3%.…”

“…Structural dynamics can enhance the function prediction. To find the binding sites for enzyme function prediction, the author of paper [18] used the molecular dynamics simulation along with the structure based function prediction algorithm. The major limitations of this method is the availability of the high resolution structural data of enzymes.…”

Bioinformatics and variability in drug response: a protein structural perspective

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