ArticleProceedings of the National Academy of Sciences of the United States of America2014
Predictive energy landscapes for folding α-helical transmembrane proteins.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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24 citing papers in PubMed, 41 citations in OpenAlex.
- Recent advances in machine learning and coarse-grained potentials for biomolecular simulations.Biophysical journal · 2026Review
- Biomolecular Condensates as Emerging Biomaterials: Functional Mechanisms and Advances in Computational and Experimental Approaches.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Electrically controlling and optically observing the membrane potential of supported lipid bilayers.Biophysical journal · 2022Article
- Untangling the complexity of membrane protein folding.Current opinion in structural biology · 2022Review
- Molecular docking and simulation of IcaC protein as O-succinyltransferase function inCurrent research in structural biology · 2022Article
- Binding Dynamics of Disordered Linker Histone H1 with a Nucleosomal Particle.Journal of molecular biology · 2021Article
- OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations.PLoS computational biology · 2021Article
- From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules.Frontiers in molecular biosciences · 2021Review
- Structural and Dynamical Order of a Disordered Protein: Molecular Insights into Conformational Switching of PAGE4 at the Systems Level.Biomolecules · 2019Article
- A strategy to characterize chlorophyll protein interaction in LIL3.Plant methods · 2019Article
- AWSEM-IDP: A Coarse-Grained Force Field for Intrinsically Disordered Proteins.The journal of physical chemistry. B · 2018Article
- Energy landscape underlying spontaneous insertion and folding of an alpha-helical transmembrane protein into a bilayer.Nature communications · 2018Article
- A Membrane Burial Potential with H-Bonds and Applications to Curved Membranes and Fast Simulations.Biophysical journal · 2018Article
- Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for α/β Proteins.The journal of physical chemistry. B · 2017Article
- The cellular membrane as a mediator for small molecule interaction with membrane proteins.Biochimica et biophysica acta · 2016Article
- Protein Folding and Structure Prediction from the Ground Up: The Atomistic Associative Memory, Water Mediated, Structure and Energy Model.The journal of physical chemistry. B · 2016Article
- Atomic-level description of protein-lipid interactions using an accelerated membrane model.Biochimica et biophysica acta · 2016Review
- Topological constraints and modular structure in the folding and functional motions of GlpG, an intramembrane protease.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Constructing sequence-dependent protein models using coevolutionary information.Protein science : a publication of the Protein Society · 2016Article
- Predictive energy landscapes for folding membrane protein assemblies.The Journal of chemical physics · 2015Article
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3 authors at 2 institutions in 1 country.
Funding
Abstract
We explore the hypothesis that the folding landscapes of membrane proteins are funneled once the proteins' topology within the membrane is established. We extend a protein folding model, the associative memory, water-mediated, structure, and energy model (AWSEM) by adding an implicit membrane potential and reoptimizing the force field to account for the differing nature of the interactions that stabilize proteins within lipid membranes, yielding a model that we call AWSEM-membrane. Once the protein topology is set in the membrane, hydrophobic attractions play a lesser role in finding the native structure, whereas polar-polar attractions are more important than for globular proteins. We examine both the quality of predictions made with AWSEM-membrane when accurate knowledge of the topology and secondary structure is available and the quality of predictions made without such knowledge, instead using bioinformatically inferred topology and secondary structure based on sequence alone. When no major errors are made by the bioinformatic methods used to assign the topology of the transmembrane helices, these two types of structure predictions yield roughly equivalent quality structures. Although the predictive energy landscape is transferable and not structure based, within the correct topological sector we find the landscape is indeed very funneled: Thermodynamic landscape analysis indicates that both the total potential energy and the contact energy decrease as native contacts are formed. Nevertheless the near symmetry of different helical packings with respect to native contact formation can result in multiple packings with nearly equal thermodynamic occupancy, especially at temperatures just below collapse.
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