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.

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.

Structure-based analyses of gut microbiome-related proteins by neural networks and molecular dynamics simulations.

An imbalance in the gut microbiome is linked to immune disorders, such as autoimmune, allergic, and chronic inflammatory disorders. Elucidation of disease mechanisms is a matter of urgency. It requires precise elucidation of the structure-based mechanisms of protein interactions involved in disease onset. In addition, an understanding of the protein dynamics is vital because these fluctuations affect the function and interaction of disease-associated proteins. Experimental evaluation of not only protein interactions, functions, and structures but also the dynamics are time-consuming; therefore, computational predictions are necessary to elucidate disease mechanisms. Here, we introduce recent studies on structure-based analyses of proteins using computational approaches, particularly artificial intelligence (AI) and molecular dynamics (MD) simulations.

Autoencoder-based detection of the residues involved in G protein-coupled receptor signaling.

Regulator binding and mutations alter protein dynamics. The transmission of the signal of these alterations to distant sites through protein motion results in changes in protein expression and cell function. The detection of residues involved in signal transmission contributes to an elucidation of the mechanisms underlying processes as vast as cellular function and disease pathogenesis. We developed an autoencoder (AE) based method that detects residues essential for signaling by comparing the fluctuation data, particularly the time fluctuation of the side-chain distances between residues, during molecular dynamics simulations between the ligand-bound and -unbound forms or wild-type and mutant forms of proteins. Here, the AE-based method was applied to the G protein-coupled receptor (GPCR) system, particularly a class A-type GPCR, CXCR4, to detect the essential residues involved in signaling. Among the residues involved in the signaling of the homolog CXCR2, which were extracted from the literature based on the complex structures of the ligand and G protein, our method could detect more than half of the essential residues involved in G protein signaling, including those spanning the fifth and sixth transmembrane helices in the intracellular region, despite the lack of information regarding the interaction with G protein in our CXCR4 models.

Rebuilding Ring-Type Assembly of Peroxiredoxin by Chemical Modification.

Direct control of the protein quaternary structure (QS) is challenging owing to the complexity of the protein structure. As a protein with a characteristic QS, peroxiredoxin from Aeropyrum pernix K1 (ApPrx) forms a decamer, wherein five dimers associate to form a ring. Here, we disrupted and reconstituted ApPrx QS via amino acid mutations and chemical modifications targeting hot spots for protein assembly. The decameric QS of an ApPrx* mutant, wherein all cysteine residues in wild-type ApPrx were mutated to serine, was destructed to dimers via an F80C mutation. The dimeric ApPrx*F80C mutant was then modified with a small molecule and successfully assembled as a decamer. Structural analysis confirmed that an artificially installed chemical moiety potentially facilitates suitable protein-protein interactions to rebuild a native structure. Rebuilding of dodecamer was also achieved through an additional amino acid mutation. This study describes a facile method to regulate the protein assembly state.

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.

Actin Cytoskeletal Reorganization Function of JRAB/MICAL-L2 Is Fine-tuned by Intramolecular Interaction between First LIM Zinc Finger and C-terminal Coiled-coil Domains.

JRAB/MICAL-L2 is an effector protein of Rab13, a member of the Rab family of small GTPase. JRAB/MICAL-L2 consists of a calponin homology domain, a LIM domain, and a coiled-coil domain. JRAB/MICAL-L2 engages in intramolecular interaction between the N-terminal LIM domain and the C-terminal coiled-coil domain, and changes its conformation from closed to open under the effect of Rab13. Open-form JRAB/MICAL-L2 induces the formation of peripheral ruffles via an interaction between its calponin homology domain and filamin. Here, we report that the LIM domain, independent of the C-terminus, is also necessary for the function of open-form JRAB/MICAL-L2. In mechanistic terms, two zinc finger domains within the LIM domain bind the first and second molecules of actin at the minus end, potentially inhibiting the depolymerization of actin filaments (F-actin). The first zinc finger domain also contributes to the intramolecular interaction of JRAB/MICAL-L2. Moreover, the residues of the first zinc finger domain that are responsible for the intramolecular interaction are also involved in the association with F-actin. Together, our findings show that the function of open-form JRAB/MICAL-L2 mediated by the LIM domain is fine-tuned by the intramolecular interaction between the first zinc finger domain and the C-terminal domain.

Autoencoder-Based Detection of Dynamic Allostery Triggered by Ligand Binding Based on Molecular Dynamics.

Dynamic allostery on proteins, triggered by regulator binding or chemical modifications, transmits information from the binding site to distant regions, dramatically altering protein function. It is accompanied by subtle changes in side-chain conformations of the protein, indicating that the changes in dynamics, and not rigid or large conformational changes, are essential to understand regulation of protein function. Although a lot of experimental and theoretical studies have been dedicated to investigate this issue, the regulation mechanism of protein function is still being debated. Here, we propose an autoencoder-based method that can detect dynamic allostery. The method is based on the comparison of time fluctuations of protein structures, in the form of distance matrices, obtained from molecular dynamics simulations in ligand-bound and -unbound forms. Our method detected that the changes in dynamics by ligand binding in the PDZ2 domain led to the reorganization of correlative fluctuation motions among residue pairs, which revealed a different view of the correlated motions from the PCA and DCCM. In addition, other correlative motions were also found as a result of the dynamic perturbation from the ligand binding, which may lead to dynamic allostery. This autoencoder-based method would be usefully applied to the signal transduction and mutagenesis systems involved in protein functions and severe diseases.

New tools and functions in data-out activities at Protein Data Bank Japan (PDBj).

The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode-Elastic server for normal mode analysis, a virtual reality system for the eF-site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches.

A study of CDR3 loop dynamics reveals distinct mechanisms of peptide recognition by T-cell receptors exhibiting different levels of cross-reactivity.

T-cell receptors (TCRs) can productively interact with many different peptides bound within the MHC binding groove. This property varies with the level of cross-reactivity of TCRs; some TCRs are particularly hyper cross-reactive while others exhibit greater specificity. To elucidate the mechanism behind these differences, we studied five TCRs in complex with the same class II MHC (1Ab )-peptide (3K), that are known to exhibit different levels of cross-reactivity. Although these complexes have similar binding affinities, the interface areas between the TCR and the peptide-MHC (pMHC) differ significantly. We investigated static and dynamic structural features of the TCR-pMHC complexes and of TCRs in a free state, as well as the relationship between binding affinity and interface area. It was found that the TCRs known to exhibit lower levels of cross-reactivity bound to pMHC using an induced-fitting mechanism, forming large and tight interfaces rich in specific hydrogen bonds. In contrast, TCRs known to exhibit high levels of cross-reactivity used a more rigid binding mechanism where non-specific π-interactions involving the bulky Trp residue in CDR3ß dominated. As entropy loss upon binding in these highly degenerate and rigid TCRs is smaller than that in less degenerate TCRs, they can better tolerate changes in residues distal from the major contacts with MHC-bound peptide. Hence, our dynamics study revealed that differences in the peptide recognition mechanisms by TCRs appear to correlate with the levels of T-cell cross-reactivity.

Visualization and quantitation of epidermal growth factor receptor homodimerization and activation with a proximity ligation assay.

OBJECTIVES: Activation of the epidermal growth factor receptor (EGFR) results from receptor homodimerization and autophosphorylation and confers sensitivity to tyrosine kinase inhibitors in some tumors. However, the visual detection and quantitation of activated EGFR in the clinical setting has not been established. MATERIALS AND METHODS: A proximity ligation assay (PLA) was applied to detect EGFR homodimers in non-small cell lung cancer (NSCLC) cell lines and tissue specimens. RESULTS: PLA signals corresponding to EGFR homodimers were higher in NSCLC cell lines and tissue specimens positive for activating EGFR mutations than in those wild type (WT) for EGFR. Stimulation with EGF in NSCLC cells WT for EGFR or forced overexpression of EGFR in Ba/F3 cells resulted in marked EGFR homodimerization. The extent of EGFR homodimerization appeared related to that of EGFR autophosphorylation in NSCLC cells WT for EGFR. CONCLUSION: PLA may provide a new tool for detection and quantitation of EGFR homodimers in NSCLC and other tumors.

Protein Data Bank Japan (PDBj): updated user interfaces, resource description framework, analysis tools for large structures.

The Protein Data Bank Japan (PDBj, http://pdbj.org), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined macromolecular structures. While maintaining the archive in collaboration with other wwPDB partners, PDBj also provides a wide range of services and tools for analyzing structures and functions of proteins. We herein outline the updated web user interfaces together with RESTful web services and the backend relational database that support the former. To enhance the interoperability of the PDB data, we have previously developed PDB/RDF, PDB data in the Resource Description Framework (RDF) format, which is now a wwPDB standard called wwPDB/RDF. We have enhanced the connectivity of the wwPDB/RDF data by incorporating various external data resources. Services for searching, comparing and analyzing the ever-increasing large structures determined by hybrid methods are also described.

Conformational plasticity of JRAB/MICAL-L2 provides "law and order" in collective cell migration.

In fundamental biological processes, cells often move in groups, a process termed collective cell migration. Collectively migrating cells are much better organized than a random assemblage of individual cells. Many molecules have been identified as factors involved in collective cell migration, and no one molecule is adequate to explain the whole picture. Here we show that JRAB/MICAL-L2, an effector protein of Rab13 GTPase, provides the "law and order" allowing myriad cells to behave as a single unit just by changing its conformation. First, we generated a structural model of JRAB/MICAL-L2 by a combination of bioinformatic and biochemical analyses and showed how JRAB/MICAL-L2 interacts with Rab13 and how its conformational change occurs. We combined cell biology, live imaging, computational biology, and biomechanics to show that impairment of conformational plasticity in JRAB/MICAL-L2 causes excessive rigidity and loss of directionality, leading to imbalance in cell group behavior. This multidisciplinary approach supports the concept that the conformational plasticity of a single molecule provides "law and order" in collective cell migration.

Substrate recognition of N,N'-diacetylchitobiose deacetylase from Pyrococcus horikoshii.

Enzymes of carbohydrate esterase (CE) family 14 catalyze hydrolysis of N-acetyl groups at the non-reducing end of the N-acetylglucosamine (GlcNAc) residue of chitooligosaccharides or related compounds. N,N'-diacetylchitobiose deacetylase (Dac) belongs to the CE-14 family and plays a role in the chitinolytic pathway in archaea by deacetylating N,N'-diacetylchitobiose (GlcNAc2), which is the end product of chitinase. In this study, we revealed the structural basis of reaction specificity in CE-14 deacetylases by solving a crystal structure of Dac from Pyrococcus horikoshii (Ph-Dac) in complex with a novel reaction intermediate analog. We developed 2-deoxy-2-methylphosphoramido-d-glucose (MPG) as the analog of the tetrahedral oxyanion intermediate of the monosaccharide substrate GlcNAc. The crystal structure of Ph-Dac in complex with MPG demonstrated that Arg92, Asp115, and His152 side chains interact with hydroxyl groups of the glucose moiety of the non-reducing-end GlcNAc residue. The amino acid residues responsible for recognition of the MPG glucose moiety are spatially conserved in other CE-14 deacetylases. Molecular dynamics simulation of the structure of the Ph-Dac-GlcNAc2 complex indicated that the reducing GlcNAc residue is placed in a large intermolecular cleft and is not involved with specific interactions with the enzyme. This observation was consistent with results indicating that Ph-Dac displayed similar kinetic parameters for both GlcNAc and GlcNAc2. This study provides the structural basis of reaction-site specificity of Dac and related CE-14 enzymes.

Ligand-induced Ordering of the C-terminal Tail Primes STING for Phosphorylation by TBK1.

The innate immune protein Stimulator of interferon genes (STING) promotes the induction of interferon beta (IFN-ß) production via the phosphorylation of its C-terminal tail (CTT) by TANK-binding kinase 1 (TBK1). Potent ligands of STING are, therefore, promising candidates for novel anti-cancer drugs or vaccine adjuvants. However, the intrinsically flexible CTT poses serious problems in in silico drug discovery. Here, we performed molecular dynamics simulations of the STING fragment containing the CTT in ligand-bound and unbound forms and observed that the binding of a potent ligand cyclic GMP-AMP (cGAMP) induced a local structure in the CTT, reminiscent of the known structure of a TBK1 substrate. The subsequent molecular biological experiments confirmed the observed dynamics of the CTT and identified essential residues for the activation of the IFN-ß promoter, leading us to propose a new mechanism of STING activation.

The diversity of H3 loops determines the antigen-binding tendencies of antibody CDR loops.

Of the complementarity-determining regions (CDRs) of antibodies, H3 loops, with varying amino acid sequences and loop lengths, adopt particularly diverse loop conformations. The diversity of H3 conformations produces an array of antigen recognition patterns involving all the CDRs, in which the residue positions actually in contact with the antigen vary considerably. Therefore, for a deeper understanding of antigen recognition, it is necessary to relate the sequence and structural properties of each residue position in each CDR loop to its ability to bind antigens. In this study, we proposed a new method for characterizing the structural features of the CDR loops and obtained the antigen-binding ability of each residue position in each CDR loop. This analysis led to a simple set of rules for identifying probable antigen-binding residues. We also found that the diversity of H3 loop lengths and conformations affects the antigen-binding tendencies of all the CDR loops.

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target.

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

Retinoblastoma-binding Protein 4-regulated Classical Nuclear Transport Is Involved in Cellular Senescence.

Nucleocytoplasmic trafficking is a fundamental cellular process in eukaryotic cells. Here, we demonstrated that retinoblastoma-binding protein 4 (RBBP4) functions as a novel regulatory factor to increase the efficiency of importin α/ß-mediated nuclear import. RBBP4 accelerates the release of importin ß1 from importin α via competitive binding to the importin ß-binding domain of importin α in the presence of RanGTP. Therefore, it facilitates importin α/ß-mediated nuclear import. We showed that the importin α/ß pathway is down-regulated in replicative senescent cells, concomitant with a decrease in RBBP4 level. Knockdown of RBBP4 caused both suppression of nuclear transport and induction of cellular senescence. This is the first report to identify a factor that competes with importin ß1 to bind to importin α, and it demonstrates that the loss of this factor can trigger cellular senescence.