PoSSuM v.3: A Major Expansion of the PoSSuM Database for Finding Similar Binding Sites of Proteins.

Information on structures of protein-ligand complexes, including comparisons of known and putative protein-ligand-binding pockets, is valuable for protein annotation and drug discovery and development. To facilitate biomedical and pharmaceutical research, we developed PoSSuM (https://possum.cbrc.pj.aist.go.jp/PoSSuM/), a database for identifying similar binding pockets in proteins. The current PoSSuM database includes 191 million similar pairs among almost 10 million identified pockets. PoSSuM drug search (PoSSuMds) is a resource for investigating ligand and receptor diversity among a set of pockets that can bind to an approved drug compound. The enhanced PoSSuMds covers pockets associated with both approved drugs and drug candidates in clinical trials from the latest release of ChEMBL. Additionally, we developed two new databases: PoSSuMAg for investigating antibody-antigen interactions and PoSSuMAF to simplify exploring putative pockets in AlphaFold human protein models.

Predicting global distributions of eukaryotic plankton communities from satellite data.

Satellite remote sensing is a powerful tool to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here, we present an approach to identify community types from a global plankton network that includes phytoplankton and heterotrophic protists and to predict their biogeography using global satellite observations. Six plankton community types were identified from a co-occurrence network inferred using a novel rDNA 18 S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to construct a model that predicted these community types from satellite data. The model showed an overall 67% accuracy in the prediction of the community types. The prediction using 17 satellite-derived parameters showed better performance than that using only temperature and/or the concentration of chlorophyll a. The constructed model predicted the global spatiotemporal distribution of community types over 19 years. The predicted distributions exhibited strong seasonal changes in community types in the subarctic-subtropical boundary regions, which were consistent with previous field observations. The model also identified the long-term trends in the distribution of community types, which suggested responses to ocean warming.

A multipoint guidance mechanism for ß-barrel folding on the SAM complex.

Mitochondrial ß-barrel proteins are essential for the transport of metabolites, ions and proteins. The sorting and assembly machinery (SAM) mediates their folding and membrane insertion. We report the cryo-electron microscopy structure of the yeast SAM complex carrying an early eukaryotic ß-barrel folding intermediate. The lateral gate of Sam50 is wide open and pairs with the last ß-strand (ß-signal) of the substrate-the 19-ß-stranded Tom40 precursor-to form a hybrid barrel in the membrane plane. The Tom40 barrel grows and curves, guided by an extended bridge with Sam50. Tom40's first ß-segment (ß1) penetrates into the nascent barrel, interacting with its inner wall. The Tom40 amino-terminal segment then displaces ß1 to promote its pairing with Tom40's last ß-strand to complete barrel formation with the assistance of Sam37's dynamic α-protrusion. Our study thus reveals a multipoint guidance mechanism for mitochondrial ß-barrel folding.

Protein-protein interaction prediction methods: from docking-based to AI-based approaches.

Protein-protein interactions (PPIs), such as protein-protein inhibitor, antibody-antigen complex, and supercomplexes play diverse and important roles in cells. Recent advances in structural analysis methods, including cryo-EM, for the determination of protein complex structures are remarkable. Nevertheless, much room remains for improvement and utilization of computational methods to predict PPIs because of the large number and great diversity of unresolved complex structures. This review introduces a wide array of computational methods, including our own, for estimating PPIs including antibody-antigen interactions, offering both historical and forward-looking perspectives.

Distinct immune cell dynamics correlate with the immunogenicity and reactogenicity of SARS-CoV-2 mRNA vaccine.

Two doses of Pfizer/BioNTech BNT162b2 mRNA vaccine elicit robust severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies with frequent adverse events. Here, by applying a high-dimensional immune profiling on 92 vaccinees, we identify six vaccine-induced immune dynamics that correlate with the amounts of neutralizing antibodies, the severity of adverse events, or both. The early dynamics of natural killer (NK)/monocyte subsets (CD16+ NK cells, CD56high NK cells, and non-classical monocytes), dendritic cell (DC) subsets (DC3s and CD11c- Axl+ Siglec-6+ [AS]-DCs), and NKT-like cells are revealed as the distinct cell correlates for neutralizing-antibody titers, severity of adverse events, and both, respectively. The cell correlates for neutralizing antibodies or adverse events are consistently associated with elevation of interferon gamma (IFN-γ)-inducible chemokines, but the chemokine receptors CCR2 and CXCR3 are expressed in distinct manners between the two correlates: vaccine-induced expression on the neutralizing-antibody correlate and constitutive expression on the adverse-event correlate. The finding may guide vaccine strategies that balance immunogenicity and reactogenicity.

Application of Homology Modeling by Enhanced Profile-Profile Alignment and Flexible-Fitting Simulation to Cryo-EM Based Structure Determination.

Application of cryo-electron microscopy (cryo-EM) is crucially important for ascertaining the atomic structure of large biomolecules such as ribosomes and protein complexes in membranes. Advances in cryo-EM technology and software have made it possible to obtain data with near-atomic resolution, but the method is still often capable of producing only a density map with up to medium resolution, either partially or entirely. Therefore, bridging the gap separating the density map and the atomic model is necessary. Herein, we propose a methodology for constructing atomic structure models based on cryo-EM maps with low-to-medium resolution. The method is a combination of sensitive and accurate homology modeling using our profile-profile alignment method with a flexible-fitting method using molecular dynamics simulation. As described herein, this study used benchmark applications to evaluate the model constructions of human two-pore channel 2 (one target protein in CASP13 with its structure determined using cryo-EM data) and the overall structure of Enterococcus hirae V-ATPase complex.

Crystal structure of Tam41 cytidine diphosphate diacylglycerol synthase from a Firmicutes bacterium.

Translocator assembly and maintenance 41 (Tam41) catalyses the synthesis of cytidine diphosphate diacylglycerol (CDP-DAG), which is a high-energy intermediate phospholipid critical for generating cardiolipin in mitochondria. Although Tam41 is present almost exclusively in eukaryotic cells, a Firmicutes bacterium contains the gene encoding Tam41-type CDP-DAG synthase (FbTam41). FbTam41 converted phosphatidic acid (PA) to CDP-DAG using a ternary complex mechanism in vitro. Additionally, FbTam41 functionally substituted yeast Tam41 in vivo. These results demonstrate that Tam41-type CDP-DAG synthase functions in some prokaryotic cells. We determined the crystal structure of FbTam41 lacking the C-terminal 18 residues in the cytidine triphosphate (CTP)-Mg2+ bound form at a resolution of 2.6 Å. The crystal structure showed that FbTam41 contained a positively charged pocket that specifically accommodated CTP-Mg2+ and PA in close proximity. By using this structure, we constructed a model for the full-length structure of FbTam41 containing the last a-helix, which was missing in the crystal structure. Based on this model, we propose a molecular mechanism for CDP-DAG synthesis in bacterial cells and mitochondria.

PreBINDS: An Interactive Web Tool to Create Appropriate Datasets for Predicting Compound-Protein Interactions.

Given the abundant computational resources and the huge amount of data of compound-protein interactions (CPIs), constructing appropriate datasets for learning and evaluating prediction models for CPIs is not always easy. For this study, we have developed a web server to facilitate the development and evaluation of prediction models by providing an appropriate dataset according to the task. Our web server provides an environment and dataset that aid model developers and evaluators in obtaining a suitable dataset for both proteins and compounds, in addition to attributes necessary for deep learning. With the web server interface, users can customize the CPI dataset derived from ChEMBL by setting positive and negative thresholds to be adjusted according to the user's definitions. We have also implemented a function for graphic display of the distribution of activity values in the dataset as a histogram to set appropriate thresholds for positive and negative examples. These functions enable effective development and evaluation of models. Furthermore, users can prepare their task-specific datasets by selecting a set of target proteins based on various criteria such as Pfam families, ChEMBL's classification, and sequence similarities. The accuracy and efficiency of in silico screening and drug design using machine learning including deep learning can therefore be improved by facilitating access to an appropriate dataset prepared using our web server (https://binds.lifematics.work/).

HMGB1 signaling phosphorylates Ku70 and impairs DNA damage repair in Alzheimer's disease pathology.

DNA damage is increased in Alzheimer's disease (AD), while the underlying mechanisms are unknown. Here, we employ comprehensive phosphoproteome analysis, and identify abnormal phosphorylation of 70 kDa subunit of Ku antigen (Ku70) at Ser77/78, which prevents Ku70-DNA interaction, in human AD postmortem brains. The abnormal phosphorylation inhibits accumulation of Ku70 to the foci of DNA double strand break (DSB), impairs DNA damage repair and eventually causes transcriptional repression-induced atypical cell death (TRIAD). Cells under TRIAD necrosis reveal senescence phenotypes. Extracellular high mobility group box 1 (HMGB1) protein, which is released from necrotic or hyper-activated neurons in AD, binds to toll-like receptor 4 (TLR4) of neighboring neurons, and activates protein kinase C alpha (PKCα) that executes Ku70 phosphorylation at Ser77/78. Administration of human monoclonal anti-HMGB1 antibody to post-symptomatic AD model mice decreases neuronal DSBs, suppresses secondary TRIAD necrosis of neurons, prevents escalation of neurodegeneration, and ameliorates cognitive symptoms. TRIAD shares multiple features with senescence. These results discover the HMGB1-Ku70 axis that accounts for the increase of neuronal DNA damage and secondary enhancement of TRIAD, the cell death phenotype of senescence, in AD.

Mitochondrial sorting and assembly machinery operates by ß-barrel switching.

The mitochondrial outer membrane contains so-called ß-barrel proteins, which allow communication between the cytosol and the mitochondrial interior1-3. Insertion of ß-barrel proteins into the outer membrane is mediated by the multisubunit mitochondrial sorting and assembly machinery (SAM, also known as TOB)4-6. Here we use cryo-electron microscopy to determine the structures of two different forms of the yeast SAM complex at a resolution of 2.8-3.2 Å. The dimeric complex contains two copies of the ß-barrel channel protein Sam50-Sam50a and Sam50b-with partially open lateral gates. The peripheral membrane proteins Sam35 and Sam37 cap the Sam50 channels from the cytosolic side, and are crucial for the structural and functional integrity of the dimeric complex. In the second complex, Sam50b is replaced by the ß-barrel protein Mdm10. In cooperation with Sam50a, Sam37 recruits and traps Mdm10 by penetrating the interior of its laterally closed ß-barrel from the cytosolic side. The substrate-loaded SAM complex contains one each of Sam50, Sam35 and Sam37, but neither Mdm10 nor a second Sam50, suggesting that Mdm10 and Sam50b function as placeholders for a ß-barrel substrate released from Sam50a. Our proposed mechanism for dynamic switching of ß-barrel subunits and substrate explains how entire precursor proteins can fold in association with the mitochondrial machinery for ß-barrel assembly.

Rab7D small GTPase is involved in phago-, trogocytosis and cytoskeletal reorganization in the enteric protozoan Entamoeba histolytica.

Rab small GTPases regulate membrane traffic between distinct cellular compartments of all eukaryotes in a tempo-spatially specific fashion. Rab small GTPases are also involved in the regulation of cytoskeleton and signalling. Membrane traffic and cytoskeletal regulation play pivotal role in the pathogenesis of Entamoeba histolytica, which is a protozoan parasite responsible for human amebiasis. E. histolytica is unique in that its genome encodes over 100 Rab proteins, containing multiple isotypes of conserved members (e.g., Rab7) and Entamoeba-specific subgroups (e.g., RabA, B, and X). Among them, E. histolytica Rab7 is the most diversified group consisting of nine isotypes. While it was previously demonstrated that EhRab7A and EhRab7B are involved in lysosome and phagosome biogenesis, the individual roles of other Rab7 members and their coordination remain elusive. In this study, we characterised the third member of Rab7, Rab7D, to better understand the significance of the multiplicity of Rab7 isotypes in E. histolytica. Overexpression of EhRab7D caused reduction in phagocytosis of erythrocytes, trogocytosis (meaning nibbling or chewing of a portion) of live mammalian cells, and phagosome acidification and maturation. Conversely, transcriptional gene silencing of EhRab7D gene caused opposite phenotypes in phago/trogocytosis and phagosome maturation. Furthermore, EhRab7D gene silencing caused reduction in the attachment to and the motility on the collagen-coated surface. Image analysis showed that EhRab7D was occasionally associated with lysosomes and prephagosomal vacuoles, but not with mature phagosomes and trogosomes. Finally, in silico prediction of structural organisation of EhRab7 isotypes identified unique amino acid changes on the effector binding surface of EhRab7D. Taken together, our data suggest that EhRab7D plays coordinated counteracting roles: a inhibitory role in phago/trogocytosis and lyso/phago/trogosome biogenesis, and an stimulatory role in adherence and motility, presumably via interaction with unique effectors. Finally, we propose the model in which three EhRab7 isotypes are sequentially involved in phago/trogocytosis.

Import of Entamoeba histolytica Mitosomal ATP Sulfurylase Relies on Internal Targeting Sequences.

Mitochondrial matrix proteins synthesized in the cytosol often contain amino (N)-terminal targeting sequences (NTSs), or alternately internal targeting sequences (ITSs), which enable them to be properly translocated to the organelle. Such sequences are also required for proteins targeted to mitochondrion-related organelles (MROs) that are present in a few species of anaerobic eukaryotes. Similar to other MROs, the mitosomes of the human intestinal parasite Entamoeba histolytica are highly degenerate, because a majority of the components involved in various processes occurring in the canonical mitochondria are either missing or modified. As of yet, sulfate activation continues to be the only identified role of the relic mitochondria of Entamoeba. Mitosomes influence the parasitic nature of E. histolytica, as the downstream cytosolic products of sulfate activation have been reported to be essential in proliferation and encystation. Here, we investigated the position of the targeting sequence of one of the mitosomal matrix enzymes involved in the sulfate activation pathway, ATP sulfurylase (AS). We confirmed by immunofluorescence assay and subcellular fractionation that hemagluttinin (HA)-tagged EhAS was targeted to mitosomes. However, its ortholog in the δ-proteobacterium Desulfovibrio vulgaris, expressed as DvAS-HA in amoebic trophozoites, indicated cytosolic localization, suggesting a lack of recognizable mitosome targeting sequence in this protein. By expressing chimeric proteins containing swapped sequences between EhAS and DvAS in amoebic cells, we identified the ITSs responsible for mitosome targeting of EhAS. This observation is similar to other parasitic protozoans that harbor MROs, suggesting a convergent feature among various MROs in favoring ITS for the recognition and translocation of targeted proteins.

Structural Modeling and Ligand-Binding Prediction for Analysis of Structure-Unknown and Function-Unknown Proteins Using FORTE Alignment and PoSSuM Pocket Search.

Structural data of biomolecules, such as those of proteins and nucleic acids, provide much information for estimation of their functions. For structure-unknown proteins, structure information is obtainable by modeling their structures based on sequence similarity of proteins. Moreover, information related to ligands or ligand-binding sites is necessary to elucidate protein functions because the binding of ligands can engender not only the activation and inactivation of the proteins but also the modification of protein functions. This chapter presents methods using our profile-profile alignment server FORTE and the PoSSuM ligand-binding site database for prediction of the structure and potential ligand-binding sites of structure-unknown and function-unknown proteins, aimed at protein function prediction.

Comprehensive analysis of PPARγ agonist activities of stereo-, regio-, and enantio-isomers of hydroxyoctadecadienoic acids.

Hydroxyoctadecadienoic acids (HODEs) are produced by oxidation and reduction of linoleates. There are several regio- and stereo-isomers of HODE, and their concentrations in vivo are higher than those of other lipids. Although conformational isomers may have different biological activities, comparative analysis of intracellular function of HODE isomers has not yet been performed. We evaluated the transcriptional activity of peroxisome proliferator-activated receptor γ (PPARγ), a therapeutic target for diabetes, and analyzed PPARγ agonist activity of HODE isomers. The lowest scores for docking poses of 12 types of HODE isomers (9-, 10-, 12-, and 13-HODEs) were almost similar in docking simulation of HODEs into PPARγ ligand-binding domain (LBD). Direct binding of HODE isomers to PPARγ LBD was determined by water-ligand observed via gradient spectroscopy (WaterLOGSY) NMR experiments. In contrast, there were differences in PPARγ agonist activities among 9- and 13-HODE stereo-isomers and 12- and 13-HODE enantio-isomers in a dual-luciferase reporter assay. Interestingly, the activity of 9-HODEs was less than that of other regio-isomers, and 9-(E,E)-HODE tended to decrease PPARγ-target gene expression during the maturation of 3T3-L1 cells. In addition, 10- and 12-(Z,E)-HODEs, which we previously proposed as biomarkers for early-stage diabetes, exerted PPARγ agonist activity. These results indicate that all HODE isomers have PPARγ-binding affinity; however, they have different PPARγ agonist activity. Our findings may help to understand the biological function of lipid peroxidation products.

Neural networks for protein structure and function prediction and dynamic analysis.

Hardware and software advancements along with the accumulation of large amounts of data in recent years have together spurred a remarkable growth in the application of neural networks to various scientific fields. Machine learning based on neural networks with multiple (hidden) layers is becoming an extremely powerful approach for analyzing data. With the accumulation of large amounts of protein data such as structural and functional assay data, the effects of such approaches within the field of protein informatics are increasing. Here, we introduce our recent studies based on applications of neural networks for protein structure and function prediction and dynamic analysis involving: (i) inter-residue contact prediction based on a multiple sequence alignment (MSA) of amino acid sequences, (ii) prediction of protein-compound interaction using assay data, and (iii) detection of protein allostery from trajectories of molecular dynamic (MD) simulation.

DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.

BACKGROUND: Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on deep neural networks (DNNs) and multiple sequence alignments (MSAs) of target proteins. Protein sequences are accumulating to an increasing degree such that abundant sequences to construct an MSA of a target protein are readily obtainable. Nevertheless, many cases present different ends of the number of sequences that can be included in an MSA used for contact prediction. The abundant sequences might degrade prediction results, but opportunities remain for a limited number of sequences to construct an MSA. To resolve these persistent issues, we strove to develop a novel framework using DNNs in an end-to-end manner for contact prediction. RESULTS: We developed neural network models to improve precision of both deep and shallow MSAs. Results show that higher prediction accuracy was achieved by assigning weights to sequences in a deep MSA. Moreover, for shallow MSAs, adding a few sequential features was useful to increase the prediction accuracy of long-range contacts in our model. Based on these models, we expanded our model to a multi-task model to achieve higher accuracy by incorporating predictions of secondary structures and solvent-accessible surface areas. Moreover, we demonstrated that ensemble averaging of our models can raise accuracy. Using past CASP target protein domains, we tested our models and demonstrated that our final model is superior to or equivalent to existing meta-predictors. CONCLUSIONS: The end-to-end learning framework we built can use information derived from either deep or shallow MSAs for contact prediction. Recently, an increasing number of protein sequences have become accessible, including metagenomic sequences, which might degrade contact prediction results. Under such circumstances, our model can provide a means to reduce noise automatically. According to results of tertiary structure prediction based on contacts and secondary structures predicted by our model, more accurate three-dimensional models of a target protein are obtainable than those from existing ECA methods, starting from its MSA. DeepECA is available from https://github.com/tomiilab/DeepECA.

Crim1C140S mutant mice reveal the importance of cysteine 140 in the internal region 1 of CRIM1 for its physiological functions.

Cysteine-rich transmembrane bone morphogenetic protein regulator 1 (CRIM1) is a type I transmembrane protein involved in the organogenesis of many tissues via its interactions with growth factors including BMP, TGF-ß, and VEGF. In this study, we used whole-exome sequencing and linkage analysis to identify a novel Crim1 mutant allele generated by ENU mutagenesis in mice. This allele is a missense mutation that causes a cysteine-to-serine substitution at position 140, and is referred to as Crim1C140S. In addition to the previously reported phenotypes in Crim1 mutants, Crim1C140S homozygous mice exhibited several novel phenotypes, including dwarfism, enlarged seminal vesicles, and rectal prolapse. In vitro analyses showed that Crim1C140S mutation affected the formation of CRIM1 complexes and decreased the amount of the overexpressed CRIM1 proteins in the cell culture supernatants. Cys140 is located in the internal region 1 (IR1) of the N-terminal extracellular region of CRIM1 and resides outside any identified functional domains. Inference of the domain architecture suggested that the Crim1C140S mutation disturbs an intramolecular disulfide bond in IR1, leading to the protein instability and the functional defects of CRIM1. Crim1C140S highlights the functional importance of the IR1, and Crim1C140S mice should serve as a valuable model for investigating the functions of CRIM1 that are unidentified as yet.

Genome-Wide Analysis of Known and Potential Tetraspanins in Entamoeba histolytica.

Tetraspanins are membrane proteins involved in intra- and/or intercellular signaling, and membrane protein complex formation. In some organisms, their role is associated with virulence and pathogenesis. Here, we investigate known and potential tetraspanins in the human intestinal protozoan parasite Entamoeba histolytica. We conducted sequence similarity searches against the proteome data of E. histolytica and newly identified nine uncharacterized proteins as potential tetraspanins in E. histolytica. We found three subgroups within known and potential tetraspanins, as well as subgroup-associated features in both their amino acid and nucleotide sequences. We also examined the subcellular localization of a few representative tetraspanins that might be potentially related to pathogenicity. The results in this study could be useful resources for further understanding and downstream analyses of tetraspanins in Entamoeba.

Accurate Classification of Biological and non-Biological Interfaces in Protein Crystal Structures using Subtle Covariation Signals.

Proteins often work as oligomers or multimers in vivo. Therefore, elucidating their oligomeric or multimeric form (quaternary structure) is crucially important to ascertain their function. X-ray crystal structures of numerous proteins have been accumulated, providing information related to their biological units. Extracting information of biological units from protein crystal structures represents a meaningful task for modern biology. Nevertheless, although many methods have been proposed for identifying biological units appearing in protein crystal structures, it is difficult to distinguish biological protein-protein interfaces from crystallographic ones. Therefore, our simple but highly accurate classifier was developed to infer biological units in protein crystal structures using large amounts of protein sequence information and a modern contact prediction method to exploit covariation signals (CSs) in proteins. We demonstrate that our proposed method is promising even for weak signals of biological interfaces. We also discuss the relation between classification accuracy and conservation of biological units, and illustrate how the selection of sequences included in multiple sequence alignments as sources for obtaining CSs affects the results. With increased amounts of sequence data, the proposed method is expected to become increasingly useful.