Engineered polyethylene terephthalate hydrolases: perspectives and limits.

Polyethylene terephthalate (PET) is a major component of plastic waste. Enzymatic PET hydrolysis is the most ecofriendly recycling technology. The biorecycling of PET waste requires the complete depolymerization of PET to terephthalate and ethylene glycol. The history of enzymatic PET depolymerization has revealed two critical issues for the industrial depolymerization of PET: industrially available PET hydrolases and pretreatment of PET waste to make it susceptible to full enzymatic hydrolysis. As none of the wild-type enzymes can satisfy the requirements for industrialization, various mutational improvements have been performed, through classical technology to state-of-the-art computational/machine-learning technology. Recent engineering studies on PET hydrolases have brought a new insight that flexibility of the substrate-binding groove may improve the efficiency of PET hydrolysis while maintaining sufficient thermostability, although the previous studies focused only on enzymatic thermostability above the glass transition temperature of PET. Industrial biorecycling of PET waste is scheduled to be implemented, using micronized amorphous PET. Next stage must be the development of PET hydrolases that can efficiently degrade crystalline parts of PET and expansion of target PET materials, not only bottles but also textiles, packages, and microplastics. This review discusses the current status of PET hydrolases, their potential applications, and their profespectal goals. KEY POINTS: • PET hydrolases must be thermophilic, but their operation must be below 70 °C • Classical and state-of-the-art engineering approaches are useful for PET hydrolases • Enzyme activity on crystalline PET is most expected for future PET biorecycling.

Structural Perspective of NR4A Nuclear Receptor Family and Their Potential Endogenous Ligands.

There are 48 nuclear receptors in the human genome, and many members of this superfamily have been implicated in human diseases. The NR4A nuclear receptor family consisting of three members, NR4A1, NR4A2, and NR4A3 (formerly annotated as Nur77, Nurr1, and NOR1, respectively), are still orphan receptors but exert pathological effects on immune-related and neurological diseases. We previously reported that prostaglandin A1 (PGA1) and prostaglandin A2 (PGA2) are potent activators of NR4A3, which bind directly to the ligand-binding domain (LBD) of the receptor. Recently, the co-crystallographic structures of NR4A2-LBD bound to PGA1 and PGA2 were reported, followed by reports of the neuroprotective effects of these possible endogenous ligands in mouse models of Parkinson's disease. Based on these structures, we modeled the binding structures of the other two members (NR4A1 and NR4A3) with these potential endogenous ligands using a template-based modeling method, and reviewed the similarity and diversity of ligand-binding mechanisms in the nuclear receptor family.

Molecular Interaction Mechanism of a 14-3-3 Protein with a Phosphorylated Peptide Elucidated by Enhanced Conformational Sampling.

Enhanced conformational sampling, a genetic-algorithm-guided multidimensional virtual-system coupled molecular dynamics, can provide equilibrated conformational distributions of a receptor protein and a flexible ligand at room temperature. The distributions provide not only the most stable but also semistable complex structures and propose a ligand-receptor binding process. This method was applied to a system consisting of a receptor protein, 14-3-3ε, and a flexible peptide, phosphorylated myeloid leukemia factor 1 (pMLF1). The results present comprehensive binding pathways of pMLF1 to 14-3-3ε. We identified four thermodynamically stable clusters of MLF1 on the 14-3-3ε surface and free-energy barriers among some clusters. The most stable cluster includes two high-density spots connected by a narrow corridor. When pMLF1 passes the corridor, a salt-bridge relay (switching) related to the phosphorylated residue of pMLF1 occurs. Conformations in one high-density spot are similar to the experimentally determined complex structure. Three-dimensional distributions of residues in the intermolecular interface rationally explain the binding constant changes resulting from the alanine mutation experiment for the residues. We also performed a simulation of nonphosphorylated peptide and 14-3-3ε, which demonstrated that the complex structure was unstable, suggesting that phosphorylation of the peptide is crucially important for binding to 14-3-3ε.

Current knowledge on enzymatic PET degradation and its possible application to waste stream management and other fields.

Enzymatic hydrolysis of polyethylene terephthalate (PET) has been the subject of extensive previous research that can be grouped into two categories, viz. enzymatic surface modification of polyester fibers and management of PET waste by enzymatic hydrolysis. Different enzymes with rather specific properties are required for these two processes. Enzymatic surface modification is possible with several hydrolases, such as lipases, carboxylesterases, cutinases, and proteases. These enzymes should be designated as PET surface-modifying enzymes and should not degrade the building blocks of PET but should hydrolyze the surface polymer chain so that the intensity of PET is not weakened. Conversely, management of PET waste requires substantial degradation of the building blocks of PET; therefore, only a limited number of cutinases have been recognized as PET hydrolases since the first PET hydrolase was discovered by Müller et al. (Macromol Rapid Commun 26:1400-1405, 2005). Here, we introduce current knowledge on enzymatic degradation of PET with a focus on the key class of enzymes, PET hydrolases, pertaining to the definition of enzymatic requirements for PET hydrolysis, structural analyses of PET hydrolases, and the reaction mechanisms. This review gives a deep insight into the structural basis and dynamics of PET hydrolases based on the recent progress in X-ray crystallography. Based on the knowledge accumulated to date, we discuss the potential for PET hydrolysis applications, such as in designing waste stream management.

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.

Gaussian-input Gaussian mixture model for representing density maps and atomic models.

A new Gaussian mixture model (GMM) has been developed for better representations of both atomic models and electron microscopy 3D density maps. The standard GMM algorithm employs an EM algorithm to determine the parameters. It accepted a set of 3D points with weights, corresponding to voxel or atomic centers. Although the standard algorithm worked reasonably well; however, it had three problems. First, it ignored the size (voxel width or atomic radius) of the input, and thus it could lead to a GMM with a smaller spread than the input. Second, the algorithm had a singularity problem, as it sometimes stopped the iterative procedure due to a Gaussian function with almost zero variance. Third, a map with a large number of voxels required a long computation time for conversion to a GMM. To solve these problems, we have introduced a Gaussian-input GMM algorithm, which considers the input atoms or voxels as a set of Gaussian functions. The standard EM algorithm of GMM was extended to optimize the new GMM. The new GMM has identical radius of gyration to the input, and does not suddenly stop due to the singularity problem. For fast computation, we have introduced a down-sampled Gaussian functions (DSG) by merging neighboring voxels into an anisotropic Gaussian function. It provides a GMM with thousands of Gaussian functions in a short computation time. We also have introduced a DSG-input GMM: the Gaussian-input GMM with the DSG as the input. This new algorithm is much faster than the standard algorithm.

Rigid-Body Fitting of Atomic Models on 3D Density Maps of Electron Microscopy.

Cryo electron microscopy has revolutionarily evolved for the determination of the 3D structure of macromolecular complexes. The modeling procedures on the 3D density maps of electron microscopy are roughly classified into three categories: fitting, de novo modeling and refinement. The registered atomic models from the maps have mostly been hand-built and auto-refined. Several programs aiming at automatic modeling have also been developed using various kinds of molecular representations. Among these three classes of the modeling procedures, the rigid body fitting is reviewed here, because it is the most basic modeling process applied before the other steps. The fitting problems are classified as the fittings of single subunit or multiple subunits, and the fittings on global or local parts of maps. A higher resolution map enables more local fitting. Various molecular representations have been employed in the fitting programs. A point and digital image models are generally used to represent molecules, but new representations, such as the Gaussian mixture model, have been applied recently.

Omokage search: shape similarity search service for biomolecular structures in both the PDB and EMDB.

UNLABELLED: Omokage search is a service to search the global shape similarity of biological macromolecules and their assemblies, in both the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB). The server compares global shapes of assemblies independent of sequence order and number of subunits. As a search query, the user inputs a structure ID (PDB ID or EMDB ID) or uploads an atomic model or 3D density map to the server. The search is performed usually within 1 min, using one-dimensional profiles (incremental distance rank profiles) to characterize the shapes. Using the gmfit (Gaussian mixture model fitting) program, the found structures are fitted onto the query structure and their superimposed structures are displayed on the Web browser. Our service provides new structural perspectives to life science researchers. AVAILABILITY AND IMPLEMENTATION: Omokage search is freely accessible at http://pdbj.org/omokage/.

HOMCOS: an updated server to search and model complex 3D structures.

The HOMCOS server ( http://homcos.pdbj.org ) was updated for both searching and modeling the 3D complexes for all molecules in the PDB. As compared to the previous HOMCOS server, the current server targets all of the molecules in the PDB including proteins, nucleic acids, small compounds and metal ions. Their binding relationships are stored in the database. Five services are available for users. For the services "Modeling a Homo Protein Multimer" and "Modeling a Hetero Protein Multimer", a user can input one or two proteins as the queries, while for the service "Protein-Compound Complex", a user can input one chemical compound and one protein. The server searches similar molecules by BLAST and KCOMBU. Based on each similar complex found, a simple sequence-replaced model is quickly generated by replacing the residue names and numbers with those of the query protein. A target compound is flexibly superimposed onto the template compound using the program fkcombu. If monomeric 3D structures are input as the query, then template-based docking can be performed. For the service "Searching Contact Molecules for a Query Protein", a user inputs one protein sequence as the query, and then the server searches for its homologous proteins in PDB and summarizes their contacting molecules as the predicted contacting molecules. The results are summarized in "Summary Bars" or "Site Table"display. The latter shows the results as a one-site-one-row table, which is useful for annotating the effects of mutations. The service "Searching Contact Molecules for a Query Compound" is also available.

Toward the next step in G protein-coupled receptor research: a knowledge-driven analysis for the next potential targets in drug discovery.

More than 800 G protein-coupled receptor (GPCR) genes have been discovered in the human genome. Towards the next step in GPCR research, we performed a knowledge-driven analysis of orphan class-A GPCRs that may serve as novel targets in drug discovery. We examined the relationship between 61 orphan class-A GPCR genes and diseases using the Online Mendelian Inheritance in Man (OMIM) database and the DDSS tool. The OMIM database contains data on disease-related variants of the genes. Particularly, the variants of GPR101, GPR161, and GPR88 are related to the genetic diseases: growth hormone-secreting pituitary adenoma 2, pituitary stalk interruption syndrome (not confirmed), and childhood-onset chorea with psychomotor retardation, respectively. On the other hand, the Drug Discovery and Diagnostic Support System (DDSS) tool suggests that 48 out of the 61 orphan receptor genes are related to diseases, judging from their co-occurrences in abstracts of biomedical literature. Notably, GPR50 and GPR3 are related to as many as 25 and 24 disease-associated keywords, respectively. GPR50 is related to 17 keywords of psychiatric disorders, whereas GPR3 is related to 11 keywords of neurological disorders. The aforementioned five orphan GPCRs were characterized genetically, structurally and functionally using the structural life science data cloud VaProS, so as to evaluate their potential as next targets in drug discovery.

VaProS: a database-integration approach for protein/genome information retrieval.

Life science research now heavily relies on all sorts of databases for genome sequences, transcription, protein three-dimensional (3D) structures, protein-protein interactions, phenotypes and so forth. The knowledge accumulated by all the omics research is so vast that a computer-aided search of data is now a prerequisite for starting a new study. In addition, a combinatory search throughout these databases has a chance to extract new ideas and new hypotheses that can be examined by wet-lab experiments. By virtually integrating the related databases on the Internet, we have built a new web application that facilitates life science researchers for retrieving experts' knowledge stored in the databases and for building a new hypothesis of the research target. This web application, named VaProS, puts stress on the interconnection between the functional information of genome sequences and protein 3D structures, such as structural effect of the gene mutation. In this manuscript, we present the notion of VaProS, the databases and tools that can be accessed without any knowledge of database locations and data formats, and the power of search exemplified in quest of the molecular mechanisms of lysosomal storage disease. VaProS can be freely accessed at http://p4d-info.nig.ac.jp/vapros/ .

3D flexible alignment using 2D maximum common substructure: dependence of prediction accuracy on target-reference chemical similarity.

A protein-bound conformation of a target molecule can be predicted by aligning the target molecule on the reference molecule obtained from the 3D structure of the compound-protein complex. This strategy is called "similarity-based docking". For this purpose, we develop the flexible alignment program fkcombu, which aligns the target molecule based on atomic correspondences with the reference molecule. The correspondences are obtained by the maximum common substructure (MCS) of 2D chemical structures, using our program kcombu. The prediction performance was evaluated using many target-reference pairs of superimposed ligand 3D structures on the same protein in the PDB, with different ranges of chemical similarity. The details of atomic correspondence largely affected the prediction success. We found that topologically constrained disconnected MCS (TD-MCS) with the simple element-based atomic classification provides the best prediction. The crashing potential energy with the receptor protein improved the performance. We also found that the RMSD between the predicted and correct target conformations significantly correlates with the chemical similarities between target-reference molecules. Generally speaking, if the reference and target compounds have more than 70% chemical similarity, then the average RMSD of 3D conformations is <2.0 Å. We compared the performance with a rigid-body molecular alignment program based on volume-overlap scores (ShaEP). Our MCS-based flexible alignment program performed better than the rigid-body alignment program, especially when the target and reference molecules were sufficiently similar.

Catalytic mechanism of short ethoxy chain nonylphenol dehydrogenase belonging to a polyethylene glycol dehydrogenase group in the GMC oxidoreductase family.

Ethoxy (EO) chain nonylphenol dehydrogenase (NPEO-DH) from Ensifer sp. AS08 and EO chain octylphenol dehydrogenase from Pseudomonas putida share common molecular characteristics with polyethylene glycol (PEG) dehydrogenases (PEG-DH) and comprise a PEG-DH subgroup in the family of glucose-methanol-choline (GMC) oxidoreductases that includes glucose/alcohol oxidase and glucose/choline dehydrogenase. Three-dimensional (3D) molecular modeling suggested that differences in the size, secondary structure and hydropathy in the active site caused differences in their substrate specificities toward EO chain alkylphenols and free PEGs. Based on 3D molecular modeling, site-directed mutagenesis was utilized to introduce mutations into potential catalytic residues of NPEO-DH. From steady state and rapid kinetic characterization of wild type and mutant NPEO-DHs, we can conclude that His465 and Asn507 are directly involved in the catalysis. Asn507 mediates the transfer of proton from a substrate to FAD and His465 transfers the same proton from the reduced flavin to an electron acceptor.

Biochemical and genetic analysis of a cutinase-type polyesterase from a thermophilic Thermobifida alba AHK119.

Recombinant polyesterase (Est119) from Thermobifida alba AHK119 was purified by two chromatography steps. The final protein was observed as a single band in SDS-PAGE, and the specific activity of Est119 for p-nitrophenyl butyrate was 2.30 u/mg. Purified Est119 was active with aliphatic and aliphatic-co-aromatic polyesters. Kinetic data indicated that p-nitrophenyl butyrate (pNPB) or hexanoate was the best substrate for Est119 among p-nitrophenyl acyl esters. Calcium was required for full activity and thermostability of Est119, which was stable at 50 °C for 16 h. Three-dimensional modeling and biochemical characterization showed that Est119 is a typical cutinase-type enzyme that has the compact ternary structure of an α/ß-hydrolase. Random and site-directed mutagenesis of wild-type Est119 resulted in improved activity with increased hydrophobic interaction between the antiparallel first and second ß-sheets (A68V had the greatest effect). Introduction of a proline residue (S219P) in a predicted substrate-docking loop increased the thermostability. The specific activity of the A68V/S219P mutant on pNPB was increased by more than 50-fold over the wild type. The mutant was further activated by 2.6-fold (299 u/mg) with 300 mM Ca(2+) and was stable up to 60 °C with 150 mM Ca(2+). Another identical gene was located in tandem in the upstream of est119.

Protein Data Bank Japan: Celebrating our 20th anniversary during a global pandemic as the Asian hub of three dimensional macromolecular structural data.

Protein Data Bank Japan (PDBj), a founding member of the worldwide Protein Data Bank (wwPDB) has accepted, processed and distributed experimentally determined biological macromolecular structures for 20 years. During that time, we have continuously made major improvements to our query search interface of PDBj Mine 2, the BMRBj web interface, and EM Navigator for PDB/BMRB/EMDB entries. PDBj also serves PDB-related secondary database data, original web-based modeling services such as Homology modeling of complex structure (HOMCOS), visualization services and utility tools, which we have continuously enhanced and expanded throughout the years. In addition, we have recently developed several unique archives, BSM-Arc for computational structure models, and XRDa for raw X-ray diffraction images, both of which promote open science in the structural biology community. During the COVID-19 pandemic, PDBj has also started to provide feature pages for COVID-19 related entries across all available archives at PDBj from raw experimental data and PDB structural data to computationally predicted models, while also providing COVID-19 outreach content for high school students and teachers.

Identification of ultra-rare disruptive variants in voltage-gated calcium channel-encoding genes in Japanese samples of schizophrenia and autism spectrum disorder.

Several large-scale whole-exome sequencing studies in patients with schizophrenia (SCZ) and autism spectrum disorder (ASD) have identified rare variants with modest or strong effect size as genetic risk factors. Dysregulation of cellular calcium homeostasis might be involved in SCZ/ASD pathogenesis, and genes encoding L-type voltage-gated calcium channel (VGCC) subunits Cav1.1 (CACNA1S), Cav1.2 (CACNA1C), Cav1.3 (CACNA1D), and T-type VGCC subunit Cav3.3 (CACNA1I) recently were identified as risk loci for psychiatric disorders. We performed a screening study, using the Ion Torrent Personal Genome Machine (PGM), of exon regions of these four candidate genes (CACNA1C, CACNA1D, CACNA1S, CACNA1I) in 370 Japanese patients with SCZ and 192 with ASD. Variant filtering was applied to identify biologically relevant mutations that were not registered in the dbSNP database or that have a minor allele frequency of less than 1% in East-Asian samples from databases; and are potentially disruptive, including nonsense, frameshift, canonical splicing site single nucleotide variants (SNVs), and non-synonymous SNVs predicted as damaging by five different in silico analyses. Each of these filtered mutations were confirmed by Sanger sequencing. If parental samples were available, segregation analysis was employed for measuring the inheritance pattern. Using our filter, we discovered one nonsense SNV (p.C1451* in CACNA1D), one de novo SNV (p.A36V in CACNA1C), one rare short deletion (p.E1675del in CACNA1D), and 14 NSstrict SNVs (non-synonymous SNV predicted as damaging by all of five in silico analyses). Neither p.A36V in CACNA1C nor p.C1451* in CACNA1D were found in 1871 SCZ cases, 380 ASD cases, or 1916 healthy controls in the independent sample set, suggesting that these SNVs might be ultra-rare SNVs in the Japanese population. The neuronal splicing isoform of Cav1.2 with the p.A36V mutation, discovered in the present study, showed reduced Ca2+-dependent inhibition, resulting in excessive Ca2+ entry through the mutant channel. These results suggested that this de novo SNV in CACNA1C might predispose to SCZ by affecting Ca2+ homeostasis. Thus, our analysis successfully identified several ultra-rare and potentially disruptive gene variants, lending partial support to the hypothesis that VGCC-encoding genes may contribute to the risk of SCZ/ASD.

Build-up algorithm for atomic correspondence between chemical structures.

Determining a one-to-one atom correspondence between two chemical compounds is important to measure molecular similarities and to find compounds with similar biological activities. This calculation can be formalized as the maximum common substructure (MCS) problem, which is well-studied and has been shown to be NP-complete. Although many rigorous and heuristic algorithms have been developed, none of these algorithms is sufficiently fast and accurate. We developed a new program, called "kcombu" using a build-up algorithm, which is a type of the greedy heuristic algorithms. The program can search connected and disconnected MCSs as well as topologically constrained disconnected MCS (TD-MCS), which is introduced in this study. To evaluate the performance of our program, we prepared two correct standards: the exact correspondences generated by the maximum clique algorithms and the 3D correspondences obtained from superimposed 3D structure of the molecules in a complex 3D structure with the same protein. For the five sets of molecules taken from the protein structure database, the agreement value between the build-up and the exact correspondences for the connected MCS is sufficiently high, but the computation time of the build-up algorithm is much smaller than that of the exact algorithm. The comparison between the build-up and the 3D correspondences shows that the TD-MCS has the best agreement value among the other types of MCS. Additionally, we observed a strong correlation between the molecular similarity and the agreement with the correct and 3D correspondences; more similar molecule pairs are more correctly matched. Molecular pairs with more than 40% Tanimoto similarities can be correctly matched for more than half of the atoms with the 3D correspondences.

Difference of binding modes among three ligands to a receptor mSin3B corresponding to their inhibitory activities.

A preceding experiment suggested that a compound, which inhibits binding of the REST/NRSF segment to the cleft of a receptor protein mSin3B, can be a potential drug candidate to ameliorate many neuropathies. We have recently developed an enhanced conformational sampling method, genetic-algorithm-guided multi-dimensional virtual-system-coupled canonical molecular dynamics, and in the present study, applied it to three systems consisting of mSin3B and one of three compounds, sertraline, YN3, and acitretin. Other preceding experiments showed that only sertraline inhibits the binding of REST/NRSF to mSin3B. The current simulation study produced the spatial distribution of the compounds around mSin3B, and showed that sertraline and YN3 bound to the cleft of mSin3B with a high propensity, although acitretin did not. Further analyses of the simulation data indicated that only the sertraline-mSin3B complex produced a hydrophobic core similar to that observed in the molecular interface of the REST/NRSF-mSin3B complex: An aromatic ring of sertraline sunk deeply in the mSin3B's cleft forming a hydrophobic core contacting to hydrophobic amino-acid residues located at the bottom of the cleft. The present study proposes a step to design a compound that inhibits competitively the binding of a ligand to its receptor.

Detection of multiscale pockets on protein surfaces using mathematical morphology.

Detection of pockets on protein surfaces is an important step toward finding the binding sites of small molecules. In a previous study, we defined a pocket as a space into which a small spherical probe can enter, but a large probe cannot. The radius of the large probes corresponds to the shallowness of pockets. We showed that each type of binding molecule has a characteristic shallowness distribution. In this study, we introduced fundamental changes to our previous algorithm by using a 3D grid representation of proteins and probes, and the theory of mathematical morphology. We invented an efficient algorithm for calculating deep and shallow pockets (multiscale pockets) simultaneously, using several different sizes of spherical probes (multiscale probes). We implemented our algorithm as a new program, ghecom (grid-based HECOMi finder). The statistics of calculated pockets for the structural dataset showed that our program had a higher performance of detecting binding pockets, than four other popular pocket-finding programs proposed previously. The ghecom also calculates the shallowness of binding ligands, R(inaccess) (minimum radius of inaccessible spherical probes) that can be obtained from the multiscale molecular volume. We showed that each part of the binding molecule had a bias toward a specific range of shallowness. These findings will be useful for predicting the types of molecules that will be most likely to bind putative binding pockets, as well as the configurations of binding molecules. The program ghecom is available through the Web server (http://biunit.naist.jp/ghecom).

HOMCOS: a server to predict interacting protein pairs and interacting sites by homology modeling of complex structures.

As protein-protein interactions are crucial in most biological processes, it is valuable to understand how and where protein pairs interact. We developed a web server HOMCOS (Homology Modeling of Complex Structure, http://biunit.naist.jp/homcos) to predict interacting protein pairs and interacting sites by homology modeling of complex structures. Our server is capable of three services. The first is modeling heterodimers from two query amino acid sequences posted by users. The server performs BLAST searches to identify homologous templates in the latest representative dataset of heterodimer structures generated from the PQS database. Structure validity is evaluated by the combination of sequence similarity and knowledge-based contact potential energy as previously described. The server generates a sequence-replaced model PDB file and a MODELLER script to build full atomic models of complex structures. The second service is modeling homodimers from one query sequence. The third service is identification of potentially interacting proteins for one query sequence. The server searches the dataset of heterodimer structures for a homologous template, outputs the candidate interacting sequences in the Uniprot database homologous for the interacting partner template proteins. These features are useful for wide range of researchers to predict putative interaction sites and interacting proteins.