Predicting Optimal DEER Label Positions to Study Protein Conformational Heterogeneity

Abstract

Double electron-electron resonance (DEER) spectroscopy is a powerful experimental technique for understanding the conformational heterogeneity of proteins. It involves attaching nitroxide spin labels to two residues in the protein to obtain a distance distribution between them. However, the choice of residue pairs to label in the protein requires careful thought, as experimentalists must pick label positions from a large set of all possible residue-pair combinations in the protein. In this article, we address the problem of the choice of DEER spin-label positions in a protein. For this purpose, we utilize all-atom molecular dynamics simulations of protein dynamics, to rank the sets of labeled residue pairs in terms of their ability to capture the conformational dynamics of the protein. Our design methodology is based on the following two criteria: (1) An ideal set of DEER spin-label positions should capture the slowest conformational-change processes observed in the protein dynamics, and (2) any two sets of residue pairs should describe orthogonal conformational-change processes to maximize the overall information gain and reduce the number of labeled residue pairs. We utilize Markov state models of protein dynamics to identify slow dynamical processes and a genetic-algorithm-based approach to predict the optimal choices of residue pairs with limited computational time requirements. We predict the optimal residue pairs for DEER spectroscopy in β adrenergic receptor, the C-terminal domain of calmodulin, and peptide transporter PepT. We find that our choices were ranked higher than those used to perform DEER experiments on the proteins investigated in this study. Hence, the predicted choices of DEER residue pairs determined by our method provide maximum insight into the conformational heterogeneity of the protein while using the minimum number of labeled residues.

Free Energy Landscape of the Complete Transport Cycle in a Key Bacterial Transporter

“… 42 − 44 To obtain an optimal set of residue pairs, we assigned an “optimal probe score” to each of the possible residue pair sets (see Methods ). 45 A higher score indicates slower kinetics of the MSM based on the chosen residue pair distances and hence can be considered as a better model to understand the underlying dynamics of the system. The residues pairs that are high ranked can be used for SDSL DEER spectroscopy experiments in membrane proteins.…”

“…The comparison of simulation DEER distance distributions exhibit good agreement with experimentally obtained DEER data. Using the Optimal Probe method, 45 we also predict the best DEER SDSL positions for future experiments. We suggest six distance measurements, three on either of the sides of PepT So which can capture the dynamics involved in the movement of the helices of this protein.…”

Structural Basis for Negative Regulation of ABA Signaling by ROP11 GTPase

“…From a broad perspective, our computational framework used in this study can be extended to study other PPIs involved in a variety of biological processes. As MD methodology continues to develop, in-cluding improved force field accuracy and integration of sequence co-evolution [59][60][61] and experimental information 43,62 , we expect that molecular simulations can be increasingly useful in understanding and engineering plant proteins and complexes.…”

Automatic Feature Selection in Markov State Models Using Genetic Algorithm

“…Therefore, the goal of our method is optimizing a set of residue pairs that gives the highest GMRQ score. The framework of our GA-based method is adapted from the "Optimal Probes" method proposed by Mittal and Shukla [35]. In their study, an optimal choice of residue pairs, capturing the slow conformational dynamics, is successfully predicted for double electron-election resonance spectroscopy, an experimental technique capable of detecting conformational changes by monitoring the distance between electron spins.…”