Computational modeling of membrane proteins

Abstract

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefitted from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.

Challenges and advances in atomistic simulations of potassium and sodium ion channel gating and permeation

“…Furthermore, as the structures of many ion channels and other membrane proteins remain unresolved at this time, molecular homology modelling can serve as a powerful predictive tool that circumvents the challenges of de novo protein modelling (Koehler Leman et al . ). Homology modelling approaches assume that protein structure is more conserved than sequence.…”

“…They use different algorithms for protein structure and energy predictions (Koehler Leman et al . ), but each has been successfully used for ion channel structural modelling in the past (Khalili‐Araghi et al . ; Durdagi et al .…”

Deletion of a Predicted β-Sheet Domain within the Amino Terminus of Herpes Simplex Virus Glycoprotein K Conserved among Alphaherpesviruses Prevents Virus Entry into Neuronal Axons

“…Consequently, Ͻ2% of structures available in the Protein Data Bank (PDB) are membrane proteins. Computational methods, such as homology-based modeling, are instrumental in shedding light on the secondary and tertiary structures of membrane proteins (68). Homology modeling is a well-established technique to study protein functions and mechanisms (69,70).…”

Systematic evaluation of CS-Rosetta for membrane protein structure prediction with sparse NOE restraints

“…While crystallization is a challenge for structure determination by means of X‐ray crystallography, solution‐state NMR is complicated by the slow tumbling of the MP‐detergent complexes. These limitations underline the importance of computational methods for MP structure prediction . Due to the small number of known structures, conventional template‐based homology modeling is often challenging for MPs .…”