Modulation of α-synuclein aggregation amid diverse environmental perturbation.

Intrinsically disordered protein α-synuclein (αS) is implicated in Parkinson's disease due to its aberrant aggregation propensity. In a bid to identify the traits of its aggregation, here we computationally simulate the multi-chain association process of αS in aqueous as well as under diverse environmental perturbations. In particular, the aggregation of αS in aqueous and varied environmental condition led to marked concentration differences within protein aggregates, resembling liquid-liquid phase separation (LLPS). Both saline and crowded settings enhanced the LLPS propensity. However, the surface tension of αS droplet responds differently to crowders (entropy-driven) and salt (enthalpy-driven). Conformational analysis reveals that the IDP chains would adopt extended conformations within aggregates and would maintain mutually perpendicular orientations to minimize inter-chain electrostatic repulsions. The droplet stability is found to stem from a diminished intra-chain interactions in the C-terminal regions of αS, fostering inter-chain residue-residue interactions. Intriguingly, a graph theory analysis identifies small-world-like networks within droplets across environmental conditions, suggesting the prevalence of a consensus interaction patterns among the chains. Together these findings suggest a delicate balance between molecular grammar and environment-dependent nuanced aggregation behavior of αS.

Review of AlphaFold 3: Transformative Advances in Drug Design and Therapeutics.

Google DeepMind Technologies Limited (London, United Kingdom) recently released its new version of the biomolecular structure predictor artificial intelligence (AI) model named AlphaFold 3. Superior in accuracy and more powerful than its predecessor AlphaFold 2, this innovation has astonished the world with its capacity and speed. It takes humans years to determine the structure of various proteins and how the shape works with the receptors but AlphaFold 3 predicts the same structure in seconds. The version's utility is unimaginable in the field of drug discoveries, vaccines, enzymatic processes, and determining the rate and effect of different biological processes. AlphaFold 3 uses similar machine learning and deep learning models such as Gemini (Google DeepMind Technologies Limited). AlphaFold 3 has already established itself as a turning point in the field of computational biochemistry and drug development along with receptor modulation and biomolecular development. With the help of AlphaFold 3 and models similar to this, researchers will gain unparalleled insights into the structural dynamics of proteins and their interactions, opening up new avenues for scientists and doctors to exploit for the benefit of the patient. The integration of AI models like AlphaFold 3, bolstered by rigorous validation against high-standard research publications, is set to catalyze further innovations and offer a glimpse into the future of biomedicine.

Deciphering the actin structure-dependent preferential cooperative binding of cofilin.

The mechanism underlying the preferential and cooperative binding of cofilin and the expansion of clusters toward the pointed-end side of actin filaments remains poorly understood. To address this, we conducted a principal component analysis based on available filamentous actin (F-actin) and C-actin (cofilins were excluded from cofilactin) structures and compared to monomeric G-actin. The results strongly suggest that C-actin, rather than F-ADP-actin, represented the favourable structure for binding preference of cofilin. High-speed atomic force microscopy explored that the shortened bare half helix adjacent to the cofilin clusters on the pointed end side included fewer actin protomers than normal helices. The mean axial distance (MAD) between two adjacent actin protomers along the same long-pitch strand within shortened bare half helices was longer (5.0-6.3 nm) than the MAD within typical helices (4.3-5.6 nm). The inhibition of torsional motion during helical twisting, achieved through stronger attachment to the lipid membrane, led to more pronounced inhibition of cofilin binding and cluster formation than the presence of inorganic phosphate (Pi) in solution. F-ADP-actin exhibited more naturally supertwisted half helices than F-ADP.Pi-actin, explaining how Pi inhibits cofilin binding to F-actin with variable helical twists. We propose that protomers within the shorter bare helical twists, either influenced by thermal fluctuation or induced allosterically by cofilin clusters, exhibit characteristics of C-actin-like structures with an elongated MAD, leading to preferential and cooperative binding of cofilin.

Tricks and tips for trips.

Finding out about sample preparation and transportation of structural biology samples in Acta Crystallographica F, Structural Biology Communications.

Differential conformational dynamics in two type-A RNA-binding domains drive the double-stranded RNA recognition and binding.

Trans-activation response (TAR) RNA-binding protein (TRBP) has emerged as a key player in the RNA interference pathway, wherein it binds to different pre-microRNAs (miRNAs) and small interfering RNAs (siRNAs), each varying in sequence and/or structure. We hypothesize that TRBP displays dynamic adaptability to accommodate heterogeneity in target RNA structures. Thus, it is crucial to ascertain the role of intrinsic and RNA-induced protein dynamics in RNA recognition and binding. We have previously elucidated the role of intrinsic and RNA-induced conformational exchange in the double-stranded RNA-binding domain 1 (dsRBD1) of TRBP in shape-dependent RNA recognition. The current study delves into the intrinsic and RNA-induced conformational dynamics of the TRBP-dsRBD2 and then compares it with the dsRBD1 study carried out previously. Remarkably, the two domains exhibit differential binding affinity to a 12-bp dsRNA owing to the presence of critical residues and structural plasticity. Furthermore, we report that dsRBD2 depicts constrained conformational plasticity when compared to dsRBD1. Although, in the presence of RNA, dsRBD2 undergoes induced conformational exchange within the designated RNA-binding regions and other residues, the amplitude of the motions remains modest when compared to those observed in dsRBD1. We propose a dynamics-driven model of the two tandem domains of TRBP, substantiating their contributions to the versatility of dsRNA recognition and binding.

Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles.

Organelle heterogeneity and inter-organelle contacts within a single cell contribute to the limited sensitivity of current organelle separation techniques, thus hindering organelle subpopulation characterization. Here, we use direct current insulator-based dielectrophoresis (DC-iDEP) as an unbiased separation method and demonstrate its capability by identifying distinct distribution patterns of insulin vesicles from INS-1E insulinoma cells. A multiple voltage DC-iDEP strategy with increased range and sensitivity has been applied, and a differentiation factor (ratio of electrokinetic to dielectrophoretic mobility) has been used to characterize features of insulin vesicle distribution patterns. We observed a significant difference in the distribution pattern of insulin vesicles isolated from glucose-stimulated cells relative to unstimulated cells, in accordance with maturation of vesicles upon glucose stimulation. We interpret the difference in distribution pattern to be indicative of high-resolution separation of vesicle subpopulations. DC-iDEP provides a path for future characterization of subtle biochemical differences of organelle subpopulations within any biological system.

On the pH-dependence of α-synuclein amyloid polymorphism and the role of secondary nucleation in seed-based amyloid propagation.

The aggregation of the protein α-synuclein is closely associated with several neurodegenerative disorders and as such the structures of the amyloid fibril aggregates have high scientific and medical significance. However, there are dozens of unique atomic-resolution structures of these aggregates, and such a highly polymorphic nature of the α-synuclein fibrils hampers efforts in disease-relevant in vitro studies on α-synuclein amyloid aggregation. In order to better understand the factors that affect polymorph selection, we studied the structures of α-synuclein fibrils in vitro as a function of pH and buffer using cryo-EM helical reconstruction. We find that in the physiological range of pH 5.8-7.4, a pH-dependent selection between Type 1, 2, and 3 polymorphs occurs. Our results indicate that even in the presence of seeds, the polymorph selection during aggregation is highly dependent on the buffer conditions, attributed to the non-polymorph-specific nature of secondary nucleation. We also uncovered two new polymorphs that occur at pH 7.0 in phosphate-buffered saline. The first is a monofilament Type 1 fibril that highly resembles the structure of the juvenile-onset synucleinopathy polymorph found in patient-derived material. The second is a new Type 5 polymorph that resembles a polymorph that has been recently reported in a study that used diseased tissues to seed aggregation. Taken together, our results highlight the shallow amyloid energy hypersurface that can be altered by subtle changes in the environment, including the pH which is shown to play a major role in polymorph selection and in many cases appears to be the determining factor in seeded aggregation. The results also suggest the possibility of producing disease-relevant structure in vitro.

Structure of the human heparan-α-glucosaminide N-acetyltransferase (HGSNAT).

Degradation of heparan sulfate (HS), a glycosaminoglycan (GAG) comprised of repeating units of N-acetylglucosamine and glucuronic acid, begins in the cytosol and is completed in the lysosomes. Acetylation of the terminal non-reducing amino group of α-D-glucosamine of HS is essential for its complete breakdown into monosaccharides and free sulfate. Heparan-α-glucosaminide N-acetyltransferase (HGSNAT), a resident of the lysosomal membrane, catalyzes this essential acetylation reaction by accepting and transferring the acetyl group from cytosolic acetyl-CoA to terminal α-D-glucosamine of HS in the lysosomal lumen. Mutation-induced dysfunction in HGSNAT causes abnormal accumulation of HS within the lysosomes and leads to an autosomal recessive neurodegenerative lysosomal storage disorder called mucopolysaccharidosis IIIC (MPS IIIC). There are no approved drugs or treatment strategies to cure or manage the symptoms of, MPS IIIC. Here, we use cryo-electron microscopy (cryo-EM) to determine a high-resolution structure of the HGSNAT-acetyl-CoA complex, the first step in the HGSNAT-catalyzed acetyltransferase reaction. In addition, we map the known MPS IIIC mutations onto the structure and elucidate the molecular basis for mutation-induced HGSNAT dysfunction.

Zika virus capsid protein closed structure modulates binding to host lipid systems.

Zika virus (ZIKV), a mosquito-borne Flavivirus of international concern, causes congenital microcephaly in newborns and Guillain-Barré syndrome in adults. ZIKV capsid (C) protein, one of three key structural proteins, is essential for viral assembly and encapsidation. In dengue virus, a closely related flavivirus, the homologous C protein interacts with host lipid systems, namely intracellular lipid droplets, for successful viral replication. Here, we investigate ZIKV C interaction with host lipid systems, showing that it binds host lipid droplets but, contrary to expected, in an unspecific manner. Contrasting with other flaviviruses, ZIKV C also does not bind very-low density-lipoproteins. Comparing with other Flavivirus, capsid proteins show that ZIKV C structure is particularly thermostable and seems to be locked into an auto-inhibitory conformation due to a disordered N-terminal, hence blocking specific interactions and supporting the experimental differences observed. Such distinct structural features must be considered when targeting capsid proteins in drug development.

Scorpion α-toxin LqhαIT specifically interacts with a glycan at the pore domain of voltage-gated sodium channels.

Voltage-gated sodium (Nav) channels sense membrane potential and drive cellular electrical activity. The deathstalker scorpion α-toxin LqhαIT exerts a strong action potential prolonging effect on Nav channels. To elucidate the mechanism of action of LqhαIT, we determined a 3.9 Å cryoelectron microscopy (cryo-EM) structure of LqhαIT in complex with the Nav channel from Periplaneta americana (NavPas). We found that LqhαIT binds to voltage sensor domain 4 and traps it in an "S4 down" conformation. The functionally essential C-terminal epitope of LqhαIT forms an extensive interface with the glycan scaffold linked to Asn330 of NavPas that augments a small protein-protein interface between NavPas and LqhαIT. A combination of molecular dynamics simulations, structural comparisons, and prior mutagenesis experiments demonstrates the functional importance of this toxin-glycan interaction. These findings establish a structural basis for the specificity achieved by scorpion α-toxins and reveal the conserved glycan as an essential component of the toxin-binding epitope.

Genetic code expansion, click chemistry, and light-activated PI3K reveal details of membrane protein trafficking downstream of receptor tyrosine kinases.

Ligands such as insulin, epidermal growth factor, platelet-derived growth factor, and nerve growth factor (NGF) initiate signals at the cell membrane by binding to receptor tyrosine kinases (RTKs). Along with G-protein-coupled receptors, RTKs are the main platforms for transducing extracellular signals into intracellular signals. Studying RTK signaling has been a challenge, however, due to the multiple signaling pathways to which RTKs typically are coupled, including MAP/ERK, PLCγ, and Class 1A phosphoinositide 3-kinases (PI3K). The multi-pronged RTK signaling has been a barrier to isolating the effects of any one downstream pathway. Here, we used optogenetic activation of PI3K to decouple its activation from other RTK signaling pathways. In this context, we used genetic code expansion to introduce a click chemistry noncanonical amino acid into the extracellular side of membrane proteins. Applying a cell-impermeant click chemistry fluorophore allowed us to visualize delivery of membrane proteins to the plasma membrane in real time. Using these approaches, we demonstrate that activation of PI3K, without activating other pathways downstream of RTK signaling, is sufficient to traffic the TRPV1 ion channels and insulin receptors to the plasma membrane.

Generative artificial intelligence performs rudimentary structural biology modeling.

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures for the 20 standard amino acids and an α-helical polypeptide chain, with the latter incorporating Wolfram mathematical computation. We also used GPT-4 to perform structural interaction analysis between the anti-viral nirmatrelvir and its target, the SARS-CoV-2 main protease. Geometric parameters of the generated structures typically approximated close to experimental references. However, modeling was sporadically error-prone and molecular complexity was not well tolerated. Interaction analysis further revealed the ability of GPT-4 to identify specific amino acid residues involved in ligand binding along with corresponding bond distances. Despite current limitations, we show the current capacity of natural language generative AI to perform basic structural biology modeling and interaction analysis with atomic-scale accuracy.

Structural and biochemical characterization of the C-terminal region of the human RTEL1 helicase.

RTEL1 is an essential DNA helicase which plays an important role in various aspects of genome stability, from telomere metabolism to DNA replication, repair and recombination. RTEL1 has been implicated in a number of genetic diseases and cancer development, including glioma, breast, lung and gastrointestinal tumors. RTEL1 is a FeS helicase but, in addition to the helicase core, it comprises a long C-terminal region which includes a number of folded domains connected by intrinsically disordered loops and mediates RTEL1 interaction with factors involved in pivotal cellular pathways. However, information on the architecture and the function of this region is still limited. We expressed and purified a variety of fragments encompassing the folded domains and the unstructured regions. We determined the crystal structure of the second repeat, confirming that it has a fold similar to the harmonin homology domains. SAXS data provide low-resolution information on all the fragments and suggest that the presence of the RING domain affects the overall architecture of the C-terminal region, making the structure significantly more compact. NMR data provide experimental information on the interaction between PCNA and the RTEL1 C-terminal region, revealing a putative low-affinity additional site of interaction. A biochemical analysis shows that the C-terminal region, in addition to a preference for telomeric RNA and DNA G-quadruplexes, has a high affinity for R-loops and D-loops, consistent with the role played by the RTEL1 helicase in homologous recombination, telomere maintenance and preventing replication-transcription conflicts. We further dissected the contribution of each domain in binding different substrates.

Defining the functional properties of cyclopropane fatty acid synthase from Pseudomonas aeruginosa PAO1.

Cyclopropane fatty acid synthases (CFAS) catalyze the conversion of unsaturated fatty acids to cyclopropane fatty acids (CFAs) within bacterial membranes. This modification alters the biophysical properties of membranes and has been correlated with virulence in several human pathogens. Despite the central role played by CFAS enzymes in regulating bacterial stress responses, the mechanistic properties of the CFAS enzyme family and the consequences of CFA biosynthesis remain largely uncharacterized in most bacteria. We report the first characterization of the CFAS enzyme from Pseudomonas aeruginosa (PA), an opportunistic human pathogen with complex membrane biology that is frequently associated with antimicrobial resistance and high tolerance to various external stressors. We demonstrate that CFAs are produced by a single enzyme in PA and that cfas gene expression is upregulated during the transition to stationary phase and in response to oxidative stress. Analysis of PA lipid extracts reveal a massive increase in CFA production as PA cells enter stationary phase and help define the optimal membrane composition for in vitro assays. The purified PA-CFAS enzyme forms a stable homodimer and preferentially modifies phosphatidylglycerol lipid substrates and membranes with a higher content of unsaturated acyl chains. Bioinformatic analysis across bacterial phyla shows highly divergent amino acid sequences within the lipid-binding domain of CFAS enzymes, perhaps suggesting distinct membrane-binding properties among different orthologs. This work lays an important foundation for further characterization of CFAS in P. aeruginosa and for examining the functional differences between CFAS enzymes from different bacteria.

Monitoring GPCR conformation with GFP-inspired dyes.

Solvatochromic compounds have emerged as valuable environment-sensitive probes for biological research. Here we used thiol-reactive solvatochromic analogs of the green fluorescent protein (GFP) chromophore to track conformational changes in two proteins, recoverin and the A2A adenosine receptor (A2AAR). Two dyes showed Ca2+-induced fluorescence changes when attached to recoverin. Our best-performing dye, DyeC, exhibited agonist-induced changes in both intensity and shape of its fluorescence spectrum when attached to A2AAR; none of these effects were observed with other common environment-sensitive dyes. Molecular dynamics simulations showed that activation of the A2AAR led to a more confined and hydrophilic environment for DyeC. Additionally, an allosteric modulator of A2AAR induced distinct fluorescence changes in the DyeC spectrum, indicating a unique receptor conformation. Our study demonstrated that GFP-inspired dyes are effective for detecting structural changes in G protein-coupled receptors (GPCRs), offering advantages such as intensity-based and ratiometric tracking, redshifted fluorescence spectra, and sensitivity to allosteric modulation.

STED super-resolution microscopy unveils the dynamics of Atg30 on yeast Pex3-labeled peroxisomes.

Peroxisomes are dynamic organelles with important metabolic functions. Yeast Pex3 is a multifunctional membrane protein aiding in peroxisomal biogenesis, inheritance, and degradation (pexophagy), by interacting with process-specific factors. Using multicolor (live-cell) stimulated emission depletion (STED) nanoscopy, we studied the localization of Pex3 and its binding partners in Hansenula polymorpha. Unlike confocal microscopy, STED allows resolving the membrane of tiny peroxisomes, enabling accurate measurements of the size of all Pex3-labeled peroxisomes. We localized Pex3 and its binding partners at peroxisome-repressing and -inducing conditions and during pexophagy. In-depth quantitative analysis of Pex3 and pexophagy receptor Atg30 showed dynamic changes in their (co)localization. One remarkable response of Atg30 was the shift in position from being sandwiched between clustered peroxisomes at proliferation conditions, to the cytosolically exposed parts of peroxisome clusters upon pexophagy induction. Summarizing, we show that STED allows characterizing dynamics of the localization of peroxisomal proteins in yeast cells.

A new mode of inhibition.

Complementary structural biology approaches reveal how an agonist and a covalent inhibitor simultaneously bind to a nuclear receptor.

Decoupling of the onset of anharmonicity between a protein and its surface water around 200 K.

The protein dynamical transition at ~200 K, where the biomolecule transforms from a harmonic, non-functional form to an anharmonic, functional state, has been thought to be slaved to the thermal activation of dynamics in its surface hydration water. Here, by selectively probing the dynamics of protein and hydration water using elastic neutron scattering and isotopic labeling, we found that the onset of anharmonicity in the two components around 200 K is decoupled. The one in protein is an intrinsic transition, whose characteristic temperature is independent of the instrumental resolution time, but varies with the biomolecular structure and the amount of hydration, while the one of water is merely a resolution effect.

AlphaFold2 in biomedical research: facilitating the development of diagnostic strategies for disease.

Proteins, as the primary executors of physiological activity, serve as a key factor in disease diagnosis and treatment. Research into their structures, functions, and interactions is essential to better understand disease mechanisms and potential therapies. DeepMind's AlphaFold2, a deep-learning protein structure prediction model, has proven to be remarkably accurate, and it is widely employed in various aspects of diagnostic research, such as the study of disease biomarkers, microorganism pathogenicity, antigen-antibody structures, and missense mutations. Thus, AlphaFold2 serves as an exceptional tool to bridge fundamental protein research with breakthroughs in disease diagnosis, developments in diagnostic strategies, and the design of novel therapeutic approaches and enhancements in precision medicine. This review outlines the architecture, highlights, and limitations of AlphaFold2, placing particular emphasis on its applications within diagnostic research grounded in disciplines such as immunology, biochemistry, molecular biology, and microbiology.