A structural biology community assessment of AlphaFold2 applications

Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods for protein structure predictions have reached the accuracy of experimentally determined models. Although this has been independently verified, the implementation of these methods across structural-biology applications remains to be tested. Here, we evaluate the use of AlphaFold2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modeling of interactions; and modeling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modeled when compared with homology modeling, identifying structural features rarely seen in the Protein Data Bank. AF2-based predictions of protein disorder and complexes surpass dedicated tools, and AF2 models can be used across diverse applications equally well compared with experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life-science research

Extracellular Vesicles in Chronic Demyelinating Diseases: Prospects in Treatment and Diagnosis of Autoimmune Neurological Disorders

Extracellular vesicles (EVs) represent membrane-enclosed structures that are likely to be secreted by all living cell types in the animal organism, including cells of peripheral (PNS) and central nervous systems (CNS). The ability to cross the blood-brain barrier (BBB) provides the possibility not only for various EV-loaded molecules to be delivered to the brain tissues but also for the CNS-to-periphery transmission of these molecules. Since neural EVs transfer proteins and RNAs are both responsible for functional intercellular communication and involved in the pathogenesis of neurodegenerative diseases, they represent attractive diagnostic and therapeutic targets. Here, we discuss EVs’ role in maintaining the living organisms’ function and describe deviations in EVs’ structure and malfunctioning during various neurodegenerative diseases

Reprogramming Extracellular Vesicles for Protein Therapeutics Delivery

Delivering protein therapeutics specifically into target cells and tissues is a promising avenue in medicine. Advancing this process will significantly enhance the efficiency of the designed drugs. In this regard, natural membrane-based systems are of particular interest. Extracellular vesicles (EVs), being the bilayer lipid particles secreted by almost all types of cells, have several principal advantages: biocompatibility, carrier stability, and blood–brain barrier penetrability, which make them a perspective tool for protein therapeutic delivery. Here, we evaluate the engineered genetically encoded EVs produced by a human cell line, which allow efficient cargo loading. In the devised system, the protein of interest is captured by self-assembling structures, i.e., “enveloped protein nanocages” (EPN). In their turn, EPNs are encapsulated in fusogenic EVs by the overexpression of vesicular stomatitis virus G protein (VSV-G). The proteomic profiles of different engineered EVs were determined for a comprehensive evaluation of their therapeutic potential. EVs loading mediated by bio-safe Fos–Jun heterodimerization demonstrates an increased efficacy of active cargo loading and delivery into target cells. Our results emphasize the outstanding technological and biomedical potential of the engineered EV systems, including their application in adoptive cell transfer and targeted cell reprogramming

Putative Mechanisms Underlying High Inhibitory Activities of Bimodular DNA Aptamers to Thrombin

Nucleic acid aptamers are prospective molecular recognizing elements. Similar to antibodies, aptamers are capable of providing specific recognition due to their spatial structure. However, the apparent simplicity of oligonucleotide folding is often elusive, as there is a balance between several conformations and, in some cases, oligomeric structures. This research is focused on establishing a thermodynamic background and the conformational heterogeneity of aptamers taking a series of thrombin DNA aptamers having G-quadruplex and duplex modules as an example. A series of aptamers with similar modular structures was characterized with spectroscopic and chromatographic techniques, providing examples of the conformational homogeneity of aptamers with high inhibitory activity, as well as a mixture of monomeric and oligomeric species for aptamers with low inhibitory activity. Thermodynamic parameters for aptamer unfolding were calculated, and their correlation with aptamer functional activity was found. Detailed analysis of thrombin complexes with G-quadruplex aptamers bound to exosite I revealed the similarity of the interfaces of aptamers with drastically different affinities to thrombin. It could be suggested that there are some events during complex formation that have a larger impact on the affinity than the states of initial and final macromolecules. Possible mechanisms of the complex formation and a role of the duplex module in the association process are discussed

PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries

Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads

Membrane Binding of Neuronal Calcium Sensor-1: Highly Specific Interaction with Phosphatidylinositol-3-Phosphate

Neuronal calcium sensors are a family of N-terminally myristoylated membrane-binding proteins possessing a different intracellular localization and thereby targeting unique signaling partner(s). Apart from the myristoyl group, the membrane attachment of these proteins may be modulated by their N-terminal positively charged residues responsible for specific recognition of the membrane components. Here, we examined the interaction of neuronal calcium sensor-1 (NCS-1) with natural membranes of different lipid composition as well as individual phospholipids in form of multilamellar liposomes or immobilized monolayers and characterized the role of myristoyl group and N-terminal lysine residues in membrane binding and phospholipid preference of the protein. NCS-1 binds to photoreceptor and hippocampal membranes in a Ca2+-independent manner and the binding is attenuated in the absence of myristoyl group. Meanwhile, the interaction with photoreceptor membranes is less dependent on myristoylation and more sensitive to replacement of K3, K7, and/or K9 of NCS-1 by glutamic acid, reflecting affinity of the protein to negatively charged phospholipids. Consistently, among the major phospholipids, NCS-1 preferentially interacts with phosphatidylserine and phosphatidylinositol with micromolar affinity and the interaction with the former is inhibited upon mutating of N-terminal lysines of the protein. Remarkably, NCS-1 demonstrates pronounced specific binding to phosphoinositides with high preference for phosphatidylinositol-3-phosphate. The binding does not depend on myristoylation and, unexpectedly, is not sensitive to the charge inversion mutations. Instead, phosphatidylinositol-3-phosphate can be recognized by a specific site located in the N-terminal region of the protein. These data provide important novel insights into the general mechanism of membrane binding of NCS-1 and its targeting to specific phospholipids ensuring involvement of the protein in phosphoinositide-regulated signaling pathways

Modulation of Toll-like receptor 1 intracellular domain structure and activity by Zn2+ ions

Toll-like receptors (TLRs) play an important role in the innate immune response. While a lot is known about the structures of their extracellular parts, many questions are still left unanswered, when the structural basis of TLR activation is analyzed for the TLR intracellular domains. Here we report the structure and dynamics of TLR1 toll-interleukin like (TIR) cytoplasmic domain in crystal and in solution. We found that the TLR1-TIR domain is capable of specific binding of Zn with nanomolar affinity. Interactions with Zn are mediated by cysteine residues 667 and 686 and C667 is essential for the Zn binding. Potential structures of the TLR1-TIR/Zn complex were predicted in silico. Using the functional assays for the heterodimeric TLR1/2 receptor, we found that both Zn addition and Zn depletion affect the activity of TLR1, and C667A mutation disrupts the receptor activity. Analysis of C667 position in the TLR1 structure and possible effects of C667A mutation, suggests that zinc-binding ability of TLR1-TIR domain is critical for the receptor activation

Multiscale computation delivers organophosphorus reactivity and stereoselectivity to immunoglobulin scavengers

Quantum mechanics/molecular mechanics (QM/MM) maturation of an immunoglobulin (Ig) powered by supercomputation delivers novel functionality to this catalytic template and facilitates artificial evolution of biocatalysts. We here employ density functional theory-based (DFT-b) tight binding and funnel metadynamics to advance our earlier QM/MM maturation of A17 Ig-paraoxonase (WTIgP) as a reactibody for organophosphorus toxins. It enables regulation of biocatalytic activity for tyrosine nucleophilic attack on phosphorus. The single amino acid substitution l-Leu47Lys results in 340-fold enhanced reactivity for paraoxon. The computed ground-state complex shows substrate-induced ionization of the nucleophilic l-Tyr37, now H-bonded to l-Lys47, resulting from repositioning of l-Lys47. Multiple antibody structural homologs, selected by phenylphosphonate covalent capture, show contrasting enantioselectivities for a P-chiral phenylphosphonate toxin. That is defined by crystallographic analysis of phenylphosphonylated reaction products for antibodies A5 and WTIgP. DFT-b analysis using QM regions based on these structures identifies transition states for the favored and disfavored reactions with surprising results. This stereoselection analysis is extended by funnel metadynamics to a range of WTIgP variants whose predicted stereoselectivity is endorsed by experimental analysis. The algorithms used here offer prospects for tailored design of highly evolved, genetically encoded organophosphorus scavengers and for broader functionalities of members of the Ig superfamily, including cell surface-exposed receptors

A structural biology community assessment of AlphaFold2 applications

Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods for protein structure predictions have reached the accuracy of experimentally determined models. Although this has been independently verified, the implementation of these methods across structural-biology applications remains to be tested. Here, we evaluate the use of AlphaFold2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modeling of interactions; and modeling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modeled when compared with homology modeling, identifying structural features rarely seen in the Protein Data Bank. AF2-based predictions of protein disorder and complexes surpass dedicated tools, and AF2 models can be used across diverse applications equally well compared with experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life-science research.ISSN:1545-9993ISSN:1545-998