Current Opinion in Structural Biology

The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of proteins...

Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field...

Structure-based virtual screening can be a valuable approach to computationally select hit candidates based on their predicted interaction with a protein of interest. The recent explosion in the size of chemical libraries increases the chances of hitting high-quality compounds during virtual screening exercises but also poses new challenges as the number of chemically accessible molecules grows faster than the computing power necessary to screen them. We review here two novel approaches rapidly gaining in popularity to address this problem: machine learning-accelerated and synthon-based library screening...

Molecular glue (MG) degraders are monovalent small molecule compounds that co-opt E3 ubiquitin ligases to target neo-substrates for proteasomal degradation. Here, we provide a concise review of recent advances in rational MG discovery, which are categorized into two major strategies, ligand modification and de novo discovery. We also highlight the structural mechanisms underlying the formation of MG-enabled ternary complexes and their thermodynamic properties. Finally, we summarize the broader category of proximity inducers including MGs, proteolysis-targeting chimeras (PROTACs), peptides, and viral proteins...

Oxidative stress leads to the production of oxidized phospholipids (oxPLs) that modulate the biophysical properties of phospholipid monolayers and bilayers. As many immune cells are responsible for surveilling cells and tissues for the presence of oxPLs, oxPL-dependent mechanisms have been suggested as targets for treating chronic kidney disease, atherosclerosis, diabetes, and cancer metastasis. This review details recent experimental and computational studies that characterize oxPLs' behaviors in various monolayers and bilayers...

No abstract text is available yet for this article.

Molecular dynamics simulations have emerged as a powerful set of tools to unravel the intricate dynamics of ribosomes during protein synthesis. Recent advancements in this field have enabled simulations to delve deep into the conformational rearrangements of ribosomes and associated factors, providing invaluable insights into the intricacies of translation. Emphasis on simulations has recently been on translation elongation, such as tRNA selection, translocation, and ribosomal head-swivel motions. These studies have offered crucial structural interpretations of how genetic information is faithfully translated into proteins...

An important consideration in drug discovery is the prioritization of tractable protein targets that are not only amenable to binding small molecules, but also alter disease biology in response to small molecule binding. Covalent fragment-based drug discovery has emerged as a powerful approach to aid in the identification of such protein targets. The application of irreversible binding mechanisms enables the identification of fragment hits for challenging-to-target proteins, allows proteome-wide screening in a cellular context, and makes it possible to determine functional effects with modestly potent ligands without the requirement for extensive compound optimization...

Serial femtosecond X-ray crystallography has emerged as a powerful method for investigating biomolecular structure and dynamics. With the new generation of X-ray free-electron lasers, which generate ultrabright X-ray pulses at megahertz repetition rates, we can now rapidly probe ultrafast conformational changes and charge movement in biomolecules. Over the last year, another innovation has been the deployment of Frontier, the world's first exascale supercomputer. Synergizing extremely high repetition rate X-ray light sources and exascale computing has the potential to accelerate discovery in biomolecular sciences...

The chromatin compaction activity of Polycomb group proteins has traditionally been considered essential for transcriptional repression. However, there is very little information on how Polycomb group proteins compact chromatin at the molecular level and no causal link between the compactness of chromatin and transcriptional repression. Recently, a more complete picture of Polycomb-dependent chromatin architecture has started to emerge, owing to advanced methods for imaging and chromosome conformation capture...

In the last two decades, our existing notion that most foldable proteins have a unique native state has been challenged by the discovery of metamorphic proteins, which reversibly interconvert between multiple, sometimes highly dissimilar, native states. As the number of known metamorphic proteins increases, several computational and experimental strategies have emerged for gaining insights about their refolding processes and identifying unknown metamorphic proteins amongst the known proteome. In this review, we describe the current advances in biophysically and functionally ascertaining the structural interconversions of metamorphic proteins and how coevolution can be harnessed to identify novel metamorphic proteins from sequence information...

Although defocus can be used to generate partial phase contrast in transmission electron microscope images, cryo-electron microscopy (cryo-EM) can be further improved by the development of phase plates which increase contrast by applying a phase shift to the unscattered part of the electron beam. Many approaches have been investigated, including the ponderomotive interaction between light and electrons. We review the recent successes achieved with this method in high-resolution, single-particle cryo-EM. We also review the status of using pulsed or near-field enhanced laser light as alternatives, along with approaches that use scanning transmission electron microscopy (STEM) with a segmented detector rather than a phase plate...

Methods of transmission electron microscopy (TEM) are typically used to resolve structures of vitrified biological specimens using both single particle analysis (SPA) and tomographic methods and use both conventional as well as scanning transmission modes of data collection. Automation of data collection for each method has been developed to different levels of convenience for the users. Automation of methods using the conventional TEM mode has progressed the furthest. Beam-image shift strategies first used in data collection for SPA were shown to be equally valuable for cryo-electron tomography (cryo-ET)...

X-ray crystallography and cryo-electron microscopy have enabled the determination of structures of numerous viruses at high resolution and have greatly advanced the field of structural virology. These structures represent only a subset of snapshot end-state conformations, without describing all conformational transitions that virus particles undergo. Allostery plays a critical role in relaying the effects of varied perturbations both on the surface through environmental changes and protein (receptor/antibody) interactions into the genomic core of the virus...

Protein-ligand binding site prediction is critical for protein function annotation and drug discovery. Biological experiments are time-consuming and require significant equipment, materials, and labor resources. Developing accurate and efficient computational methods for protein-ligand interaction prediction is essential. Here, we summarize the key challenges associated with ligand binding site (LBS) prediction and introduce recently published methods from their input features, computational algorithms, and ligand types...

Proteome complexity has expanded tremendously over evolutionary time, enabling biological diversification. Much of this complexity is achieved by combining a limited set of structural units into long polypeptides. This widely used evolutionary strategy poses challenges for folding of the resulting multi-domain proteins. As a consequence, their folding differs from that of small single-domain proteins, which generally fold quickly and reversibly. Co-translational processes and chaperone interactions are important aspects of multi-domain protein folding...

Allostery is a fundamental mechanism of cellular homeostasis by intra-protein communication between distinct functional sites. It is an internal process of proteins to steer interactions not only with each other but also with other biomolecules such as ligands, lipids, and nucleic acids. In addition, allosteric regulation is particularly important in enzymatic activities. A major challenge in structural and molecular biology today is unraveling allosteric sites in proteins, to elucidate the detailed mechanism of allostery and the development of allosteric drugs...

No abstract text is available yet for this article.

Protein-protein interactions play crucial roles in many biological processes. Traditionally, protein complex structures are normally built by protein-protein docking. With the rapid development of artificial intelligence and its great success in monomer protein structure prediction, deep learning has widely been applied to modeling protein-protein complex structures through inter-protein contact prediction and end-to-end approaches in the past few years. This article reviews the recent advances of deep-learning-based approaches in modeling protein-protein complex structures as well as their advantages and limitations...

Many protein and nucleoprotein complexes exist as helical polymers. As a result, much effort has been invested in developing methods for using electron microscopy to determine the structure of these assemblies. With the revolution in cryo-electron microscopy (cryo-EM), it has now become routine to reach a near-atomic level of resolution for these structures, and it is the exception when this is not possible. However, the greatest challenge is frequently determining the correct symmetry. This review focuses on why this can be so difficult and the current absence of a better approach than trial-and-error...