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1. Hybrid methods for combined experimental and computational determination of protein structure

   https://doi.org/10.1063/5.0026025  

   Seffernick, Justin T.; Lindert, Steffen (December 2020, The Journal of Chemical Physics)

   Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein–protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions. 

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2. Characterizing protein–surface and protein–nanoparticle conjugates: Activity, binding, and structure

   https://doi.org/10.1063/5.0101406  

   Correira, Joshua M.; Handali, Paul R.; Webb, Lauren J. (September 2022, The Journal of Chemical Physics)

   Many sensors and catalysts composed of proteins immobilized on inorganic materials have been reported over the past few decades. Despite some examples of functional protein–surface and protein–nanoparticle conjugates, thorough characterization of the biological–abiological interface at the heart of these materials and devices is often overlooked in lieu of demonstrating acceptable system performance. This has resulted in a focus on generating functioning protein-based devices without a concerted effort to develop reliable tools necessary to measure the fundamental properties of the bio–abio interface, such as surface concentration, biomolecular structure, and activity. In this Perspective, we discuss current methods used to characterize these critical properties of devices that operate by integrating a protein into both flat surfaces and nanoparticle materials. We highlight the advantages and drawbacks of each method as they relate to understanding the function of the protein–surface interface and explore the manner in which an informed understanding of this complex interaction leads directly to the advancement of protein-based materials and technology. 

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3. CHARMM‐GUI Membrane Builder for Lipid Droplet Modeling and Simulation

   https://doi.org/10.1002/cplu.202400013  

   Gee, Stephen; Glover, Kerney Jebrell; Wittenberg, Nathan J; Im, Wonpil (August 2024, ChemPlusChem)

   Abstract Lipid droplets (LDs) are organelles that are necessary for eukaryotic and prokaryotic metabolism and energy storage. They have a unique structure consisting of a spherical phospholipid monolayer encasing neutral lipids such as triacylglycerol (TAG). LDs have garnered increased interest for their implications in disease and for drug delivery applications. Consequently, there is an increased need for tools to study their structure, composition, and dynamics in biological contexts. In this work, we utilize CHARMM‐GUIMembrane Builderto simulate and analyze LDs with and without a plant LD protein, oleosin. The results show thatMembrane Buildercan generate biologically relevant all‐atom LD systems with relatively short equilibration times using a new TAG library having optimized headgroup parameters. TAG molecules originally inserted into a lipid bilayer aggregate in the membrane center, forming a TAG‐only core flanked by two monolayers. The TAG‐only core thickness stably grows with increasing TAG mole fraction. A 70 % TAG system has a core that is thick enough to house oleosin without its interactions with the distal leaflet or disruption of its secondary structure. We hope thatMembrane Buildercan aid in the future study of LD systems, including their structure and dynamics with and without proteins. 

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4. Classification of domains in predicted structures of the human proteome

   https://doi.org/10.1073/pnas.2214069120  

   Schaeffer, R. Dustin; Zhang, Jing; Kinch, Lisa N.; Pei, Jimin; Cong, Qian; Grishin, Nick V. (March 2023, Proceedings of the National Academy of Sciences)

   Recent advances in protein structure prediction have generated accurate structures of previously uncharacterized human proteins. Identifying domains in these predicted structures and classifying them into an evolutionary hierarchy can reveal biological insights. Here, we describe the detection and classification of domains from the human proteome. Our classification indicates that only 62% of residues are located in globular domains. We further classify these globular domains and observe that the majority (65%) can be classified among known folds by sequence, with a smaller fraction (33%) requiring structural data to refine the domain boundaries and/or to support their homology. A relatively small number (966 domains) cannot be confidently assigned using our automatic pipelines, thus demanding manual inspection. We classify 47,576 domains, of which only 23% have been included in experimental structures. A portion (6.3%) of these classified globular domains lack sequence-based annotation in InterPro. A quarter (23%) have not been structurally modeled by homology, and they contain 2,540 known disease-causing single amino acid variations whose pathogenesis can now be inferred using AF models. A comparison of classified domains from a series of model organisms revealed expansions of several immune response-related domains in humans and a depletion of olfactory receptors. Finally, we use this classification to expand well-known protein families of biological significance. These classifications are presented on the ECOD website ( http://prodata.swmed.edu/ecod/index_human.php ). 

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5. Biological Assembly of Modular Protein Building Blocks as Sensing, Delivery, and Therapeutic Agents

   https://doi.org/10.1146/annurev-chembioeng-101519-121526  

   Berckman, Emily A.; Hartzell, Emily J.; Mitkas, Alexander A.; Sun, Qing; Chen, Wilfred (June 2020, Annual Review of Chemical and Biomolecular Engineering)

   Nature has evolved a wide range of strategies to create self-assembled protein nanostructures with structurally defined architectures that serve a myriad of highly specialized biological functions. With the advent of biological tools for site-specific protein modifications and de novo protein design, a wide range of customized protein nanocarriers have been created using both natural and synthetic biological building blocks to mimic these native designs for targeted biomedical applications. In this review, different design frameworks and synthetic decoration strategies for achieving these functional protein nanostructures are summarized. Key attributes of these designer protein nanostructures, their unique functions, and their impact on biosensing and therapeutic applications are discussed. 

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