Structural characterization of the ACDC domain from ApiAP2 proteins of the malaria parasite.

The Apicomplexan AP2 (ApiAP2) proteins are the best characterized family of DNA-binding proteins in the malaria parasite. Apart from the AP2 DNA-binding domain, there is little sequence similarity between ApiAP2 proteins and no other functional domains have been extensively characterized. One protein domain, which is present in a subset of the ApiAP2 proteins, is the conserved AP2-coincident domain mostly at the C-terminus (ACDC domain). Here we solved for the first time the crystal structure of the ACDC domain from two distinct Plasmodium falciparum ApiAP2 proteins and one orthologue from P. vivax , revealing a non-canonical four-helix bundle. Despite little sequence conservation between the ACDC domains from the two proteins, the structures are remarkably similar and do not resemble that of any other known protein domains. Due to their unique protein architecture and lack of homologues in the human genome, we performed in silico docking calculations against a library of known antimalarial compounds and we identified a small molecule that can potentially bind to any Apicomplexan ACDC domain within a pocket highly conserved amongst ApiAP2 proteins. Inhibitors based on this compound would disrupt the function of the ACDC domain and thus of the ApiAP2 proteins containing it, providing a new therapeutic window for targeting the malaria parasite and other Apicomplexans.

A Perspective on the Prospective Use of AI in Protein Structure Prediction.

AlphaFold2 (AF2) and RoseTTaFold (RF) have revolutionized structural biology, serving as highly reliable and effective methods for predicting protein structures. This article explores their impact and limitations, focusing on their integration into experimental pipelines and their application in diverse protein classes, including membrane proteins, intrinsically disordered proteins (IDPs), and oligomers. In experimental pipelines, AF2 models help X-ray crystallography in resolving the phase problem, while complementarity with mass spectrometry and NMR data enhances structure determination and protein flexibility prediction. Predicting the structure of membrane proteins remains challenging for both AF2 and RF due to difficulties in capturing conformational ensembles and interactions with the membrane. Improvements in incorporating membrane-specific features and predicting the structural effect of mutations are crucial. For intrinsically disordered proteins, AF2's confidence score (pLDDT) serves as a competitive disorder predictor, but integrative approaches including molecular dynamics (MD) simulations or hydrophobic cluster analyses are advocated for accurate dynamics representation. AF2 and RF show promising results for oligomeric models, outperforming traditional docking methods, with AlphaFold-Multimer showing improved performance. However, some caveats remain in particular for membrane proteins. Real-life examples demonstrate AF2's predictive capabilities in unknown protein structures, but models should be evaluated for their agreement with experimental data. Furthermore, AF2 models can be used complementarily with MD simulations. In this Perspective, we propose a "wish list" for improving deep-learning-based protein folding prediction models, including using experimental data as constraints and modifying models with binding partners or post-translational modifications. Additionally, a meta-tool for ranking and suggesting composite models is suggested, driving future advancements in this rapidly evolving field.

Ensemble-based molecular docking and spectrofluorometric analysis of interaction between cytotoxin and tumor necrosis factor receptor 1.

Cytotoxin (CTX) is a three-finger toxin presents predominantly in cobra venom. The functional site of the toxin is located at its three hydrophobic loop tips. Its actual mechanism of cytotoxicity remains inconclusive as few conflicting hypotheses have been proposed in addition to direct cytolytic effects. The present work investigated the interaction between CTX and death receptor families via ensemble-based molecular docking and fluorescence titration analysis. Multiple sequence alignments of different CTX isoforms obtained a conserved CTX sequence. The three-dimensional structure of the conserved CTX was later determined using homology modelling, and its quality was validated. Ensemble-based molecular docking of CTX was performed with different death receptors, such as Fas-ligand and tumor necrosis factor receptor families. Our results showed that tumor necrosis factor receptor 1 (TNFR1) was the best receptor interacting with CTX attributed to the interaction of all three functional loops and evinced with low HADDOCK, Z-score and RMSD value. The interaction between CTX and TNFR1 was also supported by a concentration-dependent reduction of fluorescence intensity with increasing binding affinity. The possible intermolecular interactions between CTX and TNFR1 were Van der Waals forces and hydrogen bonding. Our findings suggest a possibility that CTX triggers apoptosis cell death through non-covalent interactions with TNFR1.Communicated by Ramaswamy H. Sarma.

De novo modelling of HEV replication polyprotein: Five-domain breakdown and involvement of flexibility in functional regulation.

Hepatitis E virus (HEV), a major cause of acute viral hepatitis, is a single-stranded, positive-sense RNA virus. As such, it encodes a 1700-residue replication polyprotein pORF1 that directs synthesis of new viral RNA in infected cells. Here we report extensive modeling with AlphaFold2 of the full-length pORF1, and its production by in vitro translation. From this, we give a detailed update on the breakdown into domains of HEV pORF1. We also provide evidence that pORF1's N-terminal domain is likely to oligomerize to form a dodecameric pore, homologously to what has been described for Chikungunya virus. Beyond providing accurate folds for its five domains, our work highlights that there is no canonical protease encoded in pORF1 and that flexibility in several functionally important regions rather than proteolytic processing may serve to regulate HEV RNA synthesis.

Dissecting peripheral protein-membrane interfaces.

Peripheral membrane proteins (PMPs) include a wide variety of proteins that have in common to bind transiently to the chemically complex interfacial region of membranes through their interfacial binding site (IBS). In contrast to protein-protein or protein-DNA/RNA interfaces, peripheral protein-membrane interfaces are poorly characterized. We collected a dataset of PMP domains representative of the variety of PMP functions: membrane-targeting domains (Annexin, C1, C2, discoidin C2, PH, PX), enzymes (PLA, PLC/D) and lipid-transfer proteins (START). The dataset contains 1328 experimental structures and 1194 AphaFold models. We mapped the amino acid composition and structural patterns of the IBS of each protein in this dataset, and evaluated which were more likely to be found at the IBS compared to the rest of the domains' accessible surface. In agreement with earlier work we find that about two thirds of the PMPs in the dataset have protruding hydrophobes (Leu, Ile, Phe, Tyr, Trp and Met) at their IBS. The three aromatic amino acids Trp, Tyr and Phe are a hallmark of PMPs IBS regardless of whether they protrude on loops or not. This is also the case for lysines but not arginines suggesting that, unlike for Arg-rich membrane-active peptides, the less membrane-disruptive lysine is preferred in PMPs. Another striking observation was the over-representation of glycines at the IBS of PMPs compared to the rest of their surface, possibly procuring IBS loops a much-needed flexibility to insert in-between membrane lipids. The analysis of the 9 superfamilies revealed amino acid distribution patterns in agreement with their known functions and membrane-binding mechanisms. Besides revealing novel amino acids patterns at protein-membrane interfaces, our work contributes a new PMP dataset and an analysis pipeline that can be further built upon for future studies of PMPs properties, or for developing PMPs prediction tools using for example, machine learning approaches.

Septin 9 has Two Polybasic Domains Critical to Septin Filament Assembly and Golgi Integrity.

Septins are GTP-binding proteins involved in several membrane remodeling mechanisms. They associate with membranes, presumably using a polybasic domain (PB1) that interacts with phosphoinositides (PIs). Membrane-bound septins assemble into microscopic structures that regulate membrane shape. How septins interact with PIs and then assemble and shape membranes is poorly understood. Here, we found that septin 9 has a second polybasic domain (PB2) conserved in the human septin family. Similar to PB1, PB2 binds specifically to PIs, and both domains are critical for septin filament formation. However, septin 9 membrane association is not dependent on these PB domains, but on putative PB-adjacent amphipathic helices. The presence of PB domains guarantees protein enrichment in PI-contained membranes, which is critical for PI-enriched organelles. In particular, we found that septin 9 PB domains control the assembly and functionality of the Golgi apparatus. Our findings offer further insight into the role of septins in organelle morphology.

TTClust: A Versatile Molecular Simulation Trajectory Clustering Program with Graphical Summaries.

It is extremely helpful to be able to partition the thousands of frames produced in molecular dynamics simulations into a limited number of most dissimilar conformations. While robust clustering algorithms are already available to do so, there is a distinct need for an easy-to-use clustering program with complete user control, taking as input a trajectory from any molecular dynamics (MD) package and outputting an intuitive display of results with plots allowing at-a-glance analysis. We present TTClust (for Trusty Trajectory Clustering), a python program that uses the MDTraj package to fill this need.

Membrane alterations induced by nonstructural proteins of human norovirus.

Human noroviruses (huNoV) are the most frequent cause of non-bacterial acute gastroenteritis worldwide, particularly genogroup II genotype 4 (GII.4) variants. The viral nonstructural (NS) proteins encoded by the ORF1 polyprotein induce vesical clusters harboring the viral replication sites. Little is known so far about the ultrastructure of these replication organelles or the contribution of individual NS proteins to their biogenesis. We compared the ultrastructural changes induced by expression of norovirus ORF1 polyproteins with those induced upon infection with murine norovirus (MNV). Characteristic membrane alterations induced by ORF1 expression resembled those found in MNV infected cells, consisting of vesicle accumulations likely built from the endoplasmic reticulum (ER) which included single membrane vesicles (SMVs), double membrane vesicles (DMVs) and multi membrane vesicles (MMVs). In-depth analysis using electron tomography suggested that MMVs originate through the enwrapping of SMVs with tubular structures similar to mechanisms reported for picornaviruses. Expression of GII.4 NS1-2, NS3 and NS4 fused to GFP revealed distinct membrane alterations when analyzed by correlative light and electron microscopy. Expression of NS1-2 induced proliferation of smooth ER membranes forming long tubular structures that were affected by mutations in the active center of the putative NS1-2 hydrolase domain. NS3 was associated with ER membranes around lipid droplets (LDs) and induced the formation of convoluted membranes, which were even more pronounced in case of NS4. Interestingly, NS4 was the only GII.4 protein capable of inducing SMV and DMV formation when expressed individually. Our work provides the first ultrastructural analysis of norovirus GII.4 induced vesicle clusters and suggests that their morphology and biogenesis is most similar to picornaviruses. We further identified NS4 as a key factor in the formation of membrane alterations of huNoV and provide models of the putative membrane topologies of NS1-2, NS3 and NS4 to guide future studies.

Dynamics and asymmetry in the dimer of the norovirus major capsid protein.

Noroviruses are the major cause of non-bacterial acute gastroenteritis in humans and livestock worldwide, despite being physically among the simplest animal viruses. The icosahedral capsid encasing the norovirus RNA genome is made of 90 dimers of a single ca 60-kDa polypeptide chain, VP1, arranged with T = 3 icosahedral symmetry. Here we study the conformational dynamics of this main building block of the norovirus capsid. We use molecular modeling and all-atom molecular dynamics simulations of the VP1 dimer for two genogroups with 50% sequence identity. We focus on the two points of flexibility in VP1 known from the crystal structure of the genogroup I (GI, human) capsid and from subsequent cryo-electron microscopy work on the GII capsid (also human). First, with a homology model of the GIII (bovine) VP1 dimer subjected to simulated annealing then classical molecular dynamics simulations, we show that the N-terminal arm conformation seen in the GI crystal structure is also favored in GIII VP1 but depends on the protonation state of critical residues. Second, simulations of the GI dimer show that the VP1 spike domain will not keep the position found in the GII electron microscopy work. Our main finding is a consistent propensity of the VP1 dimer to assume prominently asymmetric conformations. In order to probe this result, we obtain new SAXS data on GI VP1 dimers. These data are not interpretable as a population of symmetric dimers, but readily modeled by a highly asymmetric dimer. We go on to discuss possible implications of spontaneously asymmetric conformations in the successive steps of norovirus capsid assembly. Our work brings new lights on the surprising conformational range encoded in the norovirus major capsid protein.

Three-dimensional representations of complex carbohydrates and polysaccharides--SweetUnityMol: a video game-based computer graphic software.

A molecular visualization program tailored to deal with the range of 3D structures of complex carbohydrates and polysaccharides, either alone or in their interactions with other biomacromolecules, has been developed using advanced technologies elaborated by the video games industry. All the specific structural features displayed by the simplest to the most complex carbohydrate molecules have been considered and can be depicted. This concerns the monosaccharide identification and classification, conformations, location in single or multiple branched chains, depiction of secondary structural elements and the essential constituting elements in very complex structures. Particular attention was given to cope with the accepted nomenclature and pictorial representation used in glycoscience. This achievement provides a continuum between the most popular ways to depict the primary structures of complex carbohydrates to visualizing their 3D structures while giving the users many options to select the most appropriate modes of representations including new features such as those provided by the use of textures to depict some molecular properties. These developments are incorporated in a stand-alone viewer capable of displaying molecular structures, biomacromolecule surfaces and complex interactions of biomacromolecules, with powerful, artistic and illustrative rendering methods. They result in an open source software compatible with multiple platforms, i.e., Windows, MacOS and Linux operating systems, web pages, and producing publication-quality figures. The algorithms and visualization enhancements are demonstrated using a variety of carbohydrate molecules, from glycan determinants to glycoproteins and complex protein-carbohydrate interactions, as well as very complex mega-oligosaccharides and bacterial polysaccharides and multi-stranded polysaccharide architectures.