Molmil: a molecular viewer for the PDB and beyond

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

SoDCoD: a comprehensive database of Cu/Zn superoxide dismutase conformational diversity caused by ALS-linked gene mutations and other perturbations

A structural alteration in copper/zinc superoxide dismutase (SOD1) is one of the common features caused by amyotrophic lateral sclerosis (ALS)-linked mutations. Although a large number of SOD1 variants have been reported in ALS patients, the detailed structural properties of each variant are not well summarized. We present SoDCoD, a database of superoxide dismutase conformational diversity, collecting our comprehensive biochemical analyses of the structural changes in SOD1 caused by ALS-linked gene mutations and other perturbations. SoDCoD version 1.0 contains information about the properties of 188 types of SOD1 mutants, including structural changes and their binding to Derlin-1, as well as a set of genes contributing to the proteostasis of mutant-like wild-type SOD1. This database provides valuable insights into the diagnosis and treatment of ALS, particularly by targeting conformational alterations in SOD1. Database URL: https://fujisawagroup.github.io/SoDCoDweb/.

Familial Episodic Pain Syndrome: A Japanese Family Harboring the Novel Variant c.2431C>T (p.Leu811Phe) in SCN11A

Familial episodic pain syndrome (FEPS) is an autosomal-dominant inherited disorder characterized by paroxysmal pain episodes. FEPS appears in early childhood, gradually disappearing with age, and pain episodes can be triggered by fatigue, bad weather, and cold temperatures. Several gain-of-function variants have been reported for SCN9A, SCN10A, or SCN11A, which encode the voltage-gated sodium channel α subunits Nav1.7, Nav1.8, and Nav1.9, respectively. In this study, we conducted genetic analysis in a four-generation Japanese pedigree. The proband was a 7-year-old girl, and her brother, sister, mother, and grandmother were also experiencing or had experienced pain episodes and were considered to be affected. The father was unaffected. Sequencing of SCN9A, SCN10A, and SCN11A in the proband revealed a novel heterozygous variant of SCN11A: g.38894937G>A (c.2431C>T, p.Leu811Phe). This variant was confirmed in other affected members but not in the unaffected father. The affected residue, Leu811, is located within the DII/S6 helix of Nav1.9 and is important for signal transduction from the voltage-sensing domain and pore opening. On the other hand, the c.2432T>C (p.Leu811Pro) variant is known to cause congenital insensitivity to pain (CIP). Molecular dynamics simulations showed that p.Leu811Phe increased the structural stability of Nav1.9 and prevented the necessary conformational changes, resulting in changes in the dynamics required for function. By contrast, CIP-related p.Leu811Pro destabilized Nav1.9. Thus, we speculate that p.Leu811Phe may lead to current leakage, while p.Leu811Pro can increase the current through Nav1.9.

Design and computational evaluation of a novel multi-epitope hybrid vaccine against monkeypox virus: Potential targets and immunogenicity assessment for pandemic preparedness

Monkeypox is a type of DNA-enveloped virus that belongs to the orthopoxvirus family, closely related to the smallpox virus. It can cause an infectious disease in humans known as monkeypox disease. Although there are multiple drugs and vaccines designed to combat orthopoxvirus infections, with a primary focus on smallpox, the recent spread of the monkeypox virus to over 50 countries have ignited a mounting global concern. This unchecked viral proliferation has raised apprehensions about the potential for a pandemic corresponding to the catastrophic impact of COVID-19. This investigation explored the structural proteins of monkeypox virus as potential candidates for designing a novel hybrid multi-epitope vaccine. The epitopes obtained from the selected proteins were screened to ensure their non-allergenicity, non-toxicity, and antigenicity to trigger T and B-cell responses. The interaction of the vaccine with toll-like receptor-3 (TLR-3) and major histocompatibility complexes (MHCs) was assessed using Cluspro 2.0. To establish the reliability of the docked complexes, a comprehensive evaluation was conducted using Immune and MD Simulations and Normal Mode Analysis. However, to validate the computational results of this study, additional in-vitro and in-vivo research is essential.

PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data

PlayMolecule Viewer is a web-based data visualization toolkit designed to streamline the exploration of data resulting from structural bioinformatics or computer-aided drug design efforts. By harnessing state-of-the-art web technologies such as WebAssembly, PlayMolecule Viewer integrates powerful Python libraries directly within the browser environment, which enhances its capabilities to manage multiple types of molecular data. With its intuitive interface, it allows users to easily upload, visualize, select, and manipulate molecular structures and associated data. The toolkit supports a wide range of common structural file formats and offers a variety of molecular representations to cater to different visualization needs. PlayMolecule Viewer is freely accessible at open.playmolecule.org, ensuring accessibility and availability to the scientific community and beyond.

Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations

Flavin mononucleotide riboswitches are common among many pathogenic bacteria and are therefore considered to be an attractive target for antibiotics development. The riboswitch binds riboflavin (RBF, also known as vitamin B2), and although an experimental structure of their complex has been solved with the ligand bound deep inside the RNA molecule in a seemingly unreachable state, the binding mechanism between these molecules is not yet known. We have therefore used our Multicanonical Molecular Dynamics (McMD)-based dynamic docking protocol to analyze their binding mechanism by simulating the binding process between the riboswitch aptamer domain and the RBF, starting from the apo state of the riboswitch. Here, the refinement stage was crucial to identify the native binding configuration, as several other binding configurations were also found by McMD-based docking simulations. RBF initially binds the interface between P4 and P6 including U61 and G62, which forms a gateway where the ligand lingers until this gateway opens sufficiently to allow the ligand to pass through and slip into the hidden binding site including A48, A49, and A85.

Elucidation of binding mechanism, affinity, and complex structure between mWT1 tumor-associated antigen peptide and HLA-A*24:02

We have applied our advanced computational and experimental methodologies to investigate the complex structure and binding mechanism of a modified Wilms' Tumor 1 (mWT1) protein epitope to the understudied Asian-dominant allele HLA-A*24:02 (HLA-A24) in aqueous solution. We have applied our developed multicanonical molecular dynamics (McMD)-based dynamic docking method to analyze the binding pathway and mechanism, which we verified by comparing the highest probability structures from simulation with our experimentally solved x-ray crystal structure. Subsequent path sampling MD simulations elucidated the atomic details of the binding process and indicated that first an encounter complex is formed between the N-terminal's positive charge of the 9-residue mWT1 fragment peptide and a cluster of negative residues on the surface of HLA-A24, with the major histocompatibility complex (MHC) molecule preferring a predominantly closed conformation. The peptide first binds to this closed MHC conformation, forming an encounter complex, after which the binding site opens due to increased entropy of the binding site, allowing the peptide to bind to form the native complex structure. Further sequence and structure analyses also suggest that although the peptide loading complex would help with stabilizing the MHC molecule, the binding depends in a large part on the intrinsic affinity between the MHC molecule and the antigen peptide. Finally, our computational tools and analyses can be of great benefit to study the binding mechanism of different MHC types to their antigens, where it could also be useful in the development of higher affinity variant peptides and for personalized medicine.

Mutual induced-fit mechanism drives binding between intrinsically disordered Bim and cryptic binding site of Bcl-xL

The intrinsically disordered region (IDR) of Bim binds to the flexible cryptic site of Bcl-xL, a pro-survival protein involved in cancer progression that plays an important role in initiating apoptosis. However, their binding mechanism has not yet been elucidated. We have applied our dynamic docking protocol, which correctly reproduced both the IDR properties of Bim and the native bound configuration, as well as suggesting other stable/meta-stable binding configurations and revealed the binding pathway. Although the cryptic site of Bcl-xL is predominantly in a closed conformation, initial binding of Bim in an encounter configuration leads to mutual induced-fit binding, where both molecules adapt to each other; Bcl-xL transitions to an open state as Bim folds from a disordered to an α-helical conformation while the two molecules bind each other. Finally, our data provides new avenues to develop novel drugs by targeting newly discovered stable conformations of Bcl-xL.

Thermal Stability Estimation of Single Domain Antibodies Using Molecular Dynamics Simulations

In this chapter, we describe a protocol to estimate the thermal stability of single domain antibodies (sdAbs) using molecular dynamics (MD) simulations. This method measures the Q-value, the fraction of the native contacts, along the trajectory of high-temperature MD simulations starting from the experimental X-ray structure. We show a good correlation between the Q-value and the experimental melting temperature (T_m) in seven sdAbs. Assessing the Q-value on a per-residue level enabled us to identify residues that contribute to the instability and thus demonstrate which residues could be mutated to improve the stability and have later been validated by experiments. Our protocol extends beyond the application on sdAbs, as it is also suitable for other proteins and to determine the interfacial stability between protein and ligand.

History of Protein Data Bank Japan: standing at the beginning of the age of structural genomics

Prof. Haruki Nakamura, who is the former head of Protein Data Bank Japan (PDBj) and an expert in computational biology, retired from Osaka University at the end of March 2018. He founded PDBj at the Institute for Protein Research, together with other faculty members, researchers, engineers, and annotators in 2000, and subsequently established the worldwide Protein Data Bank (wwPDB) in 2003 to manage the core archive of the Protein Data Bank (PDB), collaborating with RCSB-PDB in the USA and PDBe in Europe. As the former head of PDBj and also an expert in structural bioinformatics, he has grown PDBj to become a well-known data center within the structural biology community and developed several related databases, tools and integrated with new technologies, such as the semantic web, as primary services offered by PDBj.

Computational biophysics and structural biology of proteins-a Special Issue in honor of Prof. Haruki Nakamura's 70th birthday

Receiving his initial training jointly in theoretical and applied physics at the University of Tokyo, Professor Haruki Nakamura has had a long and eventful scientific career, along the way helping to shape the way that biophysics is carried out in Japan. Concentrating his research efforts on the simulation of protein structure and function, he has, over his career arc, acted as director of the Institute for Protein Research (Osaka, Japan), director of the Protein Data Bank of Japan (PDBj), president of the Biophysical Society of Japan (BSJ), president of the Protein Science Society of Japan (PSSJ), and group leader and professor of Bioinformatics and Computational Structural Biology at Osaka University. In 2022, Prof. Haruki Nakamura turned 70 years old, and to mark this occasion, his scientific colleagues from around the world have combined their efforts to produce this Festschrift Issue of the IUPAB Biophysical Reviews journal around the theme of the computational biophysics and structural biology of proteins.

Advancing the field of computational drug design using multicanonical molecular dynamics-based dynamic docking

Multicanonical molecular dynamics (McMD)-based dynamic docking is a powerful tool to not only predict the native binding configuration between two flexible molecules, but it can also be used to accurately simulate the binding/unbinding pathway. Furthermore, it can also predict alternative binding sites, including allosteric ones, by employing an exhaustive sampling approach. Since McMD-based dynamic docking accurately samples binding/unbinding events, it can thus be used to determine the molecular mechanism of binding between two molecules. We developed the McMD-based dynamic docking methodology based on the powerful, but woefully underutilized McMD algorithm, combined with a toolset to perform the docking and to analyze the results. Here, we showcase three of our recent works, where we have applied McMD-based dynamic docking to advance the field of computational drug design. In the first case, we applied our method to perform an exhaustive search between Hsp90 and one of its inhibitors to successfully predict the native binding configuration in its binding site, as we refined our analysis methods. For our second case, we performed an exhaustive search of two medium-sized ligands and Bcl-xL, which has a cryptic binding site that differs greatly between the apo and holo structures. Finally, we performed a dynamic docking simulation between a membrane-embedded GPCR molecule and a high affinity ligand that binds deep within its receptor's pocket. These advanced simulations showcase the power that the McMD-based dynamic docking method has, and provide a glimpse of the potential our methodology has to unravel and solve the medical and biophysical issues in the modern world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01010-z.

Prot2Prot: a deep learning model for rapid, photorealistic macromolecular visualization

Molecular visualization is a cornerstone of structural biology, providing insights into the form and function of biomolecules that are difficult to achieve any other way. Scientific analysis, publication, education, and outreach often benefit from photorealistic molecular depictions rendered using advanced computer-graphics programs such as Maya, 3ds Max, and Blender. However, setting up molecular scenes in these programs is laborious even for expert users, and rendering often requires substantial time and computer resources. We have created a deep-learning model called Prot2Prot that quickly imitates photorealistic visualization styles, given a much simpler, easy-to-generate molecular representation. The resulting images are often indistinguishable from images rendered using industry-standard 3D graphics programs, but they can be created in a fraction of the time, even when running in a web browser. To the best of our knowledge, Prot2Prot is the first example of image-to-image translation applied to macromolecular visualization. Prot2Prot is available free of charge, released under the terms of the Apache License, Version 2.0. Users can access a Prot2Prot-powered web app without registration at http://durrantlab.com/prot2prot .

Hybridization Gamified: A Mobile App for Learning About Hybridization

For years, hybridization in chemistry has been taught using static pictures and model kits. We decided to reimagine how students learn hybridization through the development of a mobile learning tool. The tool contains gamification features such as achievements and progressive leveling that keep students engaged, while the mobile platform allows students to study anywhere, anytime. A study conducted at the University of Arizona showed that playing the hybridization exercises increased academic performance, confidence, and engagement on the topic of hybridization. This work highlights the development and course implementation of a novel mobile hybridization learning tool.

Metnase and EEPD1: DNA Repair Functions and Potential Targets in Cancer Therapy

Cells respond to DNA damage by activating signaling and DNA repair systems, described as the DNA damage response (DDR). Clarifying DDR pathways and their dysregulation in cancer are important for understanding cancer etiology, how cancer cells exploit the DDR to survive endogenous and treatment-related stress, and to identify DDR targets as therapeutic targets. Cancer is often treated with genotoxic chemicals and/or ionizing radiation. These agents are cytotoxic because they induce DNA double-strand breaks (DSBs) directly, or indirectly by inducing replication stress which causes replication fork collapse to DSBs. EEPD1 and Metnase are structure-specific nucleases, and Metnase is also a protein methyl transferase that methylates histone H3 and itself. EEPD1 and Metnase promote repair of frank, two-ended DSBs, and both promote the timely and accurate restart of replication forks that have collapsed to single-ended DSBs. In addition to its roles in HR, Metnase also promotes DSB repair by classical non-homologous recombination, and chromosome decatenation mediated by TopoIIα. Although mutations in Metnase and EEPD1 are not common in cancer, both proteins are frequently overexpressed, which may help tumor cells manage oncogenic stress or confer resistance to therapeutics. Here we focus on Metnase and EEPD1 DNA repair pathways, and discuss opportunities for targeting these pathways to enhance cancer therapy.

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.

N-Terminal-Driven Binding Mechanism of an Antigen Peptide to Human Leukocyte Antigen-A*2402 Elucidated by Multicanonical Molecular Dynamic-Based Dynamic Docking and Path Sampling Simulations

We have applied our advanced multicanonical molecular dynamics (McMD)-based dynamic docking methodology to investigate the binding mechanism of an HIV-1 Nef protein epitope to the Asian-dominant allele human leukocyte antigen (HLA)-A*2402. Even though pMHC complex formation [between a Major histocompatibility complex (MHC) class I molecule, which is encoded by an HLA allele, and an antigen peptide] is one of the fundamental processes of the adaptive human immune response, its binding mechanism has not yet been well studied, partially due to the high allelic variation of HLAs in the population. We have used our developed McMD-based dynamic docking method and have successfully reproduced the native complex structure, which is located near the free energy global minimum. Subsequent path sampling MD simulations elucidated the atomic details of the binding process and indicated that the peptide binding is initially driven by the highly positively charged N-terminus of the peptide that is attracted to the various negatively charged residues on the MHC molecule's surface. Upon nearing the pocket, the second tyrosine residue of the peptide anchors the peptide by strongly binding to the B-site of the MHC molecule via hydrophobic driven interactions, resulting in a very strong bound complex structure. Our methodology can be effectively used to predict the bound complex structures between MHC molecules and their antigens to study their binding mechanism in close detail, which would help with the development of new vaccines against cancers, as well as viral infections such as HIV and COVID-19.

Worldwide Protein Data Bank (wwPDB): A virtual treasure for research in biotechnology

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RSCB PDB) provides a wide range of digital data regarding biology and biomedicine. This huge internet resource involves a wide range of important biological data, obtained from experiments around the globe by different scientists. The Worldwide Protein Data Bank (wwPDB) represents a brilliant collection of 3D structure data associated with important and vital biomolecules including nucleic acids (RNAs and DNAs) and proteins. Moreover, this database accumulates knowledge regarding function and evolution of biomacromolecules which supports different disciplines such as biotechnology. 3D structure, functional characteristics and phylogenetic properties of biomacromolecules give a deep understanding of the biomolecules' characteristics. An important advantage of the wwPDB database is the data updating time, which is done every week. This updating process helps users to have the newest data and information for their projects. The data and information in wwPDB can be a great support to have an accurate imagination and illustrations of the biomacromolecules in biotechnology. As demonstrated by the SARS-CoV-2 pandemic, rapidly reliable and accessible biological data for microbiology, immunology, vaccinology, and drug development are critical to address many healthcare-related challenges that are facing humanity. The aim of this paper is to introduce the readers to wwPDB, and to highlight the importance of this database in biotechnology, with the expectation that the number of scientists interested in the utilization of Protein Data Bank's resources will increase substantially in the coming years.

The crystal structure of D-amino acid oxidase with a substrate analogue, o-aminobenzoate

Since the discovery of D-Amino acid oxidase (DAO) in 1935, many studies have been conducted without clarifying its three-dimensional structure for a long time. In 1996, the crystal structure of DAO was determined, and it was shown that the catalytic bases required for the two catalytic mechanisms were not present in the active site. The crystal structure of DAO in complex with o-aminobenzoate was solved and is used for modeling Michaelis complex. The Michaelis complex model provided structural information leading to a new mechanism for reductive half-reaction of DAO. Currently, DAO is being researched for medical and applied purposes.

Accurate Binding Configuration Prediction of a G-Protein-Coupled Receptor to Its Antagonist Using Multicanonical Molecular Dynamics-Based Dynamic Docking

We have performed dynamic docking between a prototypic G-protein-coupled receptor (GPCR) system, the β₂-adrenergic receptor, and its antagonist, alprenolol, using one of the enhanced conformation sampling methods, multicanonical molecular dynamics (McMD), which does not rely on any prior knowledge for the definition of the reaction coordinate. Although we have previously applied our McMD-based dynamic docking protocol to various globular protein systems, its application to GPCR systems would be difficult because of their complicated design, which include a lipid bilayer, and because of the difficulty in sampling the configurational space of a binding site that exists deep inside the GPCR. Our simulations sampled a wide array of ligand-bound and ligand-unbound structures, and we measured 427 binding events during our 48 μs production run. Analysis of the ensemble revealed several stable and meta-stable structures, where the most stable structure at the global free energy minimum matches the experimental one. Additional canonical MD simulations were used for refinement and validation of the structures, revealing that most of the intermediates are sufficiently stable to trap the ligand in these intermediary states and furthermore validated our prediction results. Given the difficulty in reaching the orthosteric binding site, chemical optimization of the compound for the second ranking configuration, which binds near the pocket's entrance, might lead to a high-affinity allosteric inhibitor. Accordingly, we show that the application of our methodology can be used to provide crucial insights for the rational design of drugs that target GPCRs.

3dRS, a Web-Based Tool to Share Interactive Representations of 3D Biomolecular Structures and Molecular Dynamics Trajectories

3D Representation Sharing (3dRS) is a web-based tool designed to share biomolecular structure representations, including 4D ensembles derived from Molecular Dynamics (MD) trajectories. The server offers a team working in different locations a single URL to share and discuss structural data in an interactive fashion, with the possibility to use it as a live figure for scientific papers. The web tool allows an easy upload of structures and trajectories in different formats. The 3D representation, powered by NGL viewer, offers an interactive display with smooth visualization in modern web browsers. Multiple structures can be loaded and superposed in the same scene. 1D sequences from the loaded structures are presented and linked to the 3D representation. Multiple, pre-defined 3D molecular representations are available. The powerful NGL selection syntax allows the definition of molecular regions that can be then displayed using different representations. Important descriptors such as distances or interactions can be easily added into the representation. Trajectory frames can be explored using a common video player control panel. Trajectories are efficiently stored and transferred to the NGL viewer thanks to an MDsrv-based data streaming. The server design offers all functionalities in one single web page, with a curated user experience, involving a minimum learning curve. Extended documentation is available, including a gallery with a collection of scenes. The server requires no registration and is available at https://mmb.irbbarcelona.org/3dRS.

Comparative Analysis of the IclR-Family of Bacterial Transcription Factors and Their DNA-Binding Motifs: Structure, Positioning, Co-Evolution, Regulon Content

The IclR-family is a large group of transcription factors (TFs) regulating various biological processes in diverse bacteria. Using comparative genomics techniques, we have identified binding motifs of IclR-family TFs, reconstructed regulons and analyzed their content, finding co-occurrences between the regulated COGs (clusters of orthologous genes), useful for future functional characterizations of TFs and their regulated genes. We describe two main types of IclR-family motifs, similar in sequence but different in the arrangement of the half-sites (boxes), with GKTYCRYW_3-4RYGRAMC and TGRAACAN_1-2TGTTYCA consensuses, and also predict that TFs in 32 orthologous groups have binding sites comprised of three boxes with alternating direction, which implies two possible alternative modes of dimerization of TFs. We identified trends in site positioning relative to the translational gene start, and show that TFs in 94 orthologous groups bind tandem sites with 18-22 nucleotides between their centers. We predict protein-DNA contacts via the correlation analysis of nucleotides in binding sites and amino acids of the DNA-binding domain of TFs, and show that the majority of interacting positions and predicted contacts are similar for both types of motifs and conform well both to available experimental data and to general protein-DNA interaction trends.

Cryptic-site binding mechanism of medium-sized Bcl-xL inhibiting compounds elucidated by McMD-based dynamic docking simulations

We have performed multicanonical molecular dynamics (McMD) based dynamic docking simulations to study and compare the binding mechanism between two medium-sized inhibitors (ABT-737 and WEHI-539) that bind to the cryptic site of Bcl-xL, by exhaustively sampling the conformational and configurational space. Cryptic sites are binding pockets that are transiently formed in the apo state or are induced upon ligand binding. Bcl-xL, a pro-survival protein involved in cancer progression, is known to have a cryptic site, whereby the shape of the pocket depends on which ligand is bound to it. Starting from the apo-structure, we have performed two independent McMD-based dynamic docking simulations for each ligand, and were able to obtain near-native complex structures in both cases. In addition, we have also studied their interactions along their respective binding pathways by using path sampling simulations, which showed that the ligands form stable binding configurations via predominantly hydrophobic interactions. Although the protein started from the apo state, both ligands modulated the pocket in different ways, shifting the conformational preference of the sub-pockets of Bcl-xL. We demonstrate that McMD-based dynamic docking is a powerful tool that can be effectively used to study binding mechanisms involving a cryptic site, where ligand binding requires a large conformational change in the protein to occur.

Cutinases from thermophilic bacteria (actinomycetes): From identification to functional and structural characterization

Thermophilic cutinases are mainly obtained from thermophilic actinomycetes, and are categorized into two groups, i.e., those with higher (>70°C) or lower (<70°C) thermostabilities. The thermostabilities of cutinases are highly relevant to their ability to degrade polyethylene terephthalate (PET). Many crystal structures of thermophilic cutinases have been solved, showing that their overall backbone structures are identical, irrespective of their ability to hydrolyze PET. One of the unique properties of cutinases is that metal ion-binding on the enzyme's surface both elevates their melting temperatures and activates the enzyme. In this chapter, we introduce the methodology for the identification and cloning of thermophilic cutinases from actinomycetes. For detailed characterization of cutinases, we describe the approach to analyze the intricate dynamics of the enzyme, based on its crystal structures complexed with metal ions and model substrates using a combination of experimental and computational techniques.

jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population

In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.

Dynamic Docking Using Multicanonical Molecular Dynamics: Simulating Complex Formation at the Atomistic Level

Multicanonical molecular dynamics (McMD)-based dynamic docking has been applied to predict the native binding configurations for several protein receptors and their ligands. Due to the enhanced sampling capabilities of McMD, it can exhaustively sample bound and unbound ligand configurations, as well as receptor conformations, and thus enables efficient sampling of the conformational and configurational space, not possible using canonical MD simulations. As McMD samples a wide configurational space, extensive analysis is required to study the diverse ensemble consisting of bound and unbound structures. By projecting the reweighted ensemble onto the first two principal axes obtained via principal component analysis of the multicanonical ensemble, the free energy landscape (FEL) can be obtained. Further analysis produces representative structures positioned at the local minima of the FEL, where these structures are then ranked by their free energy. In this chapter, we describe our dynamic docking methodology, which has successfully reproduced the native binding configuration for small compounds, medium-sized compounds, and peptide molecules.

BinaryCIF and CIFTools-Lightweight, efficient and extensible macromolecular data management

3D macromolecular structural data is growing ever more complex and plentiful in the wake of substantive advances in experimental and computational structure determination methods including macromolecular crystallography, cryo-electron microscopy, and integrative methods. Efficient means of working with 3D macromolecular structural data for archiving, analyses, and visualization are central to facilitating interoperability and reusability in compliance with the FAIR Principles. We address two challenges posed by growth in data size and complexity. First, data size is reduced by bespoke compression techniques. Second, complexity is managed through improved software tooling and fully leveraging available data dictionary schemas. To this end, we introduce BinaryCIF, a serialization of Crystallographic Information File (CIF) format files that maintains full compatibility to related data schemas, such as PDBx/mmCIF, while reducing file sizes by more than a factor of two versus gzip compressed CIF files. Moreover, for the largest structures, BinaryCIF provides even better compression—factor ten and four versus CIF files and gzipped CIF files, respectively. Herein, we describe CIFTools, a set of libraries in Java and TypeScript for generic and typed handling of CIF and BinaryCIF files. Together, BinaryCIF and CIFTools enable lightweight, efficient, and extensible handling of 3D macromolecular structural data.

The Protein Imager: a full-featured online molecular viewer interface with server-side HQ-rendering capabilities

SUMMARY

Molecular viewers' long learning curve is hindering researchers in approaching the field of structural biology for the first time. Herein, we present 'The Protein Imager', a lightweight, powerful and easy-to-use interface as a next-gen online molecular viewer. Furthermore, the interface is linked to an automated server-side rendering system able to generate publication-quality molecular illustrations. The Protein Imager interface has been designed for easy usage for beginners and experts in the field alike. The interface allows the preparation of very complex molecular views maintaining a high level of responsiveness even on mobile devices.

AVAILABILITY AND IMPLEMENTATION

The Protein Imager interface is freely available online at https://3dproteinimaging.com/protein-imager.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Modern Scientific Visualizations on the Web

Modern scientific visualization is web-based and uses emerging technology such as WebGL (Web Graphics Library) and WebGPU for three-dimensional computer graphics and WebXR for augmented and virtual reality devices. These technologies, paired with the accessibility of websites, potentially offer a user experience beyond traditional standalone visualization systems. We review the state-of-the-art of web-based scientific visualization and present an overview of existing methods categorized by application domain. As part of this analysis, we introduce the Scientific Visualization Future Readiness Score (SciVis FRS) to rank visualizations for a technology-driven disruptive tomorrow. We then summarize challenges, current state of the publication trend, future directions, and opportunities for this exciting research field.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

Exhaustive search of the configurational space of heat-shock protein 90 with its inhibitor by multicanonical molecular dynamics based dynamic docking

Multicanonical molecular dynamics based dynamic docking was used to exhaustively search the configurational space of an inhibitor binding to the N-terminal domain of heat-shock protein 90 (Hsp90). The obtained structures at 300 K cover a wide structural ensemble, with the top two clusters ranked by their free energy coinciding with the native binding site. The representative structure of the most stable cluster reproduced the experimental binding configuration, but an interesting conformational change in Hsp90 could be observed. The combined effects of solvation and ligand binding shift the equilibrium from a preferred loop-in conformation in the unbound state to an α-helical one in the bound state for the flexible lid region of Hsp90. Thus, our dynamic docking method is effective at predicting the native binding site while exhaustively sampling a wide configurational space, modulating the protein structure upon binding.

atomium-a Python structure parser

SUMMARY

Structural biology relies on specific file formats to convey information about macromolecular structures. Traditionally this has been the PDB format, but increasingly newer formats, such as PDBML, mmCIF and MMTF are being used. Here we present atomium, a modern, lightweight, Python library for parsing, manipulating and saving PDB, mmCIF and MMTF file formats. In addition, we provide a web service, pdb2json, which uses atomium to give a consistent JSON representation to the entire Protein Data Bank.

AVAILABILITY AND IMPLEMENTATION

atomium is implemented in Python and its performance is equivalent to the existing library BioPython. However, it has significant advantages in features and API design. atomium is available from atomium.bioinf.org.uk and pdb2json can be accessed at pdb2json.bioinf.org.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Biological Structure Model Archive (BSM-Arc): an archive for in silico models and simulations

We present the Biological Structure Model Archive (BSM-Arc, https://bsma.pdbj.org), which aims to collect raw data obtained via in silico methods related to structural biology, such as computationally modeled 3D structures and molecular dynamics trajectories. Since BSM-Arc does not enforce a specific data format for the raw data, depositors are free to upload their data without any prior conversion. Besides uploading raw data, BSM-Arc enables depositors to annotate their data with additional explanations and figures. Furthermore, via our WebGL-based molecular viewer Molmil, it is possible to recreate 3D scenes as shown in the corresponding scientific article in an interactive manner. To submit a new entry, depositors require an ORCID ID to login, and to finally publish the data, an accompanying peer-reviewed paper describing the work must be associated with the entry. Submitting their data enables researchers to not only have an external backup but also provide an opportunity to promote their work via an interactive platform and to provide third-party researchers access to their raw data.

Mutual population-shift driven antibody-peptide binding elucidated by molecular dynamics simulations

Antibody based bio-molecular drugs are an exciting, new avenue of drug development as an alternative to the more traditional small chemical compounds. However, the binding mechanism and the effect on the conformational ensembles of a therapeutic antibody to its peptide or protein antigen have not yet been well studied. We have utilized dynamic docking and path sampling simulations based on all-atom molecular dynamics to study the binding mechanism between the antibody solanezumab and the peptide amyloid-β (Aβ). Our docking simulations reproduced the experimental structure and gave us representative binding pathways, from which we accurately estimated the binding free energy. Not only do our results show why solanezumab has an explicit preference to bind to the monomeric form of Aβ, but that upon binding, both molecules are stabilized towards a specific conformation, suggesting that their complex formation follows a novel, mutual population-shift model, where upon binding, both molecules impact the dynamics of their reciprocal one.

Development of p53-targeting drugs that increase radioresistance in normal tissues

Radiation damage to normal tissues is a serious concern in radiation therapy. Advances in radiotherapeutic technology have improved the dose distribution of the target volumes and risk organs, but damage to risk organs that are located within the irradiation field still limits the allowable prescription dose. To overcome this dose-limiting toxicity, and to further improve the efficacy of radiotherapy, the development of drugs that protect normal tissues but not cancer tissues from the effects of radiation are expected to be developed based on molecular target-based drugs. p53 is a well-known transcription factor that is closely associated with radiation-induced cell death. In radiation-injured tissues, p53 induces apoptosis in hematopoietic lineages, whereas it plays a radioprotective role in the gastrointestinal epithelium. These facts suggest that p53 inhibitor would be effective for radioprotection of the hematopoietic system, and that a drug that upregulates the radioprotective functions of p53 would enhance the radioresistance of gastrointestinal tissues. In this review, we summarize recent progress regarding the prevention of radiation injury by regulating p53 and provide new strategic insights into the development of radioprotectors in radiotherapy. J. Med. Invest. 66 : 219-223, August, 2019.

NGL viewer: web-based molecular graphics for large complexes

Motivation

The interactive visualization of very large macromolecular complexes on the web is becoming a challenging problem as experimental techniques advance at an unprecedented rate and deliver structures of increasing size.

Results

We have tackled this problem by developing highly memory-efficient and scalable extensions for the NGL WebGL-based molecular viewer and by using Macromolecular Transmission Format (MMTF), a binary and compressed MMTF. These enable NGL to download and render molecular complexes with millions of atoms interactively on desktop computers and smartphones alike, making it a tool of choice for web-based molecular visualization in research and education.

Availability and implementation

The source code is freely available under the MIT license at github.com/arose/ngl and distributed on NPM (npmjs.com/package/ngl). MMTF-JavaScript encoders and decoders are available at github.com/rcsb/mmtf-javascript.

Sharing Data from Molecular Simulations

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/ ). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.

Metal binding to cutinase-like enzyme from Saccharomonospora viridis AHK190 and its effects on enzyme activity and stability

A cutinase from Saccharomonospora viridis AHK190, Cut190, can hydrolyze polyethylene terephthalate and has a unique feature that the activity and stability are regulated by Ca2+ binding. Our recent structural and functional analyses showed three Ca2+ binding sites and their respective roles. Here, we analysed the binding thermodynamics of Mn2+, Zn2+ and Mg2+ to Cut190 and their effects on the catalytic activity and thermal stability. The binding affinities of Mn2+ and Zn2+ were higher than that of Mg2+ and are all entropy driven with a binding stoichiometry of three, one and one for Zn2+, Mn2+ and Mg2+, respectively. The catalytic activity was measured in the presence of the respective metals, where the activity of 0.25 mM Mn2+ was comparable to that of 2.5 mM Ca2+. Our 3D Reference Interaction Site Model calculations suggested that all the ions exhibited a high occupancy rate for Site 2. Thus, Mn2+ and Mg2+ would most likely bind to Site 2 (contributes to stability) with high affinity, while to Sites 1 and 3 (contributes to activity) with low affinity. We elucidate the metal-dependent structural and functional properties of Cut190 and show the subtle balance on structure stability and flexibility is controlled by specific metal ions.

GenProBiS: web server for mapping of sequence variants to protein binding sites

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein–protein, protein–nucleic acid, protein–compound, and protein–metal ion binding sites. The concept of a protein–compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org.

Thermal stability of single-domain antibodies estimated by molecular dynamics simulations

Single‐domain antibodies (sdAbs) function like regular antibodies, however, consist of only one domain. Because of their low molecular weight, sdAbs have advantages with respect to production and delivery to their targets and for applications such as antibody drugs and biosensors. Thus, sdAbs with high thermal stability are required. In this work, we chose seven sdAbs, which have a wide range of melting temperature (T_m) values and known structures. We applied molecular dynamics (MD) simulations to estimate their relative stability and compared them with the experimental data. High‐temperature MD simulations at 400 K and 500 K were executed with simulations at 300 K as a control. The fraction of native atomic contacts, Q, measured for the 400 K simulations showed a fairly good correlation with the T_m values. Interestingly, when the residues were classified by their hydrophobicity and size, the Q values of hydrophilic residues exhibited an even better correlation, suggesting that stabilization is correlated with favorable interactions of hydrophilic residues. Measuring the Q value on a per‐residue level enabled us to identify residues that contribute significantly to the instability and thus demonstrating how our analysis can be used in a mutant case study.

Structural Dynamics of the PET-Degrading Cutinase-like Enzyme from Saccharomonospora viridis AHK190 in Substrate-Bound States Elucidates the Ca2+-Driven Catalytic Cycle

A cutinase-type polyesterase from Saccharomonospora viridis AHK190 (Cut190) has been shown to degrade the inner block of polyethylene terephthalate. A unique feature of Cut190 is that its function and stability are regulated by Ca²⁺ binding. Our previous crystal structure analysis of Cut190S226P showed that one Ca²⁺ binds to the enzyme, which induces large conformational changes in several loop regions to stabilize an open conformation [Miyakawa, T., et al. (2015) Appl. Microbiol. Biotechnol. 99, 4297]. In this study, to analyze the substrate recognition mechanism of Cut190, we determined the crystal structure of the inactive form of a Cut190 mutant, Cut190*S176A, in complex with calcium ions and/or substrates. We found that three calcium ions bind to Cut190*S176A, which is supported by analysis using native mass spectrometry experiments and 3D Reference Interaction Site Model calculations. The complex structures with the two substrates, monoethyl succinate and monoethyl adipate (engaged and open forms), presumably correspond to the pre- and post-reaction states, as the ester bond is close to the active site and pointing outward from the active site, respectively, for the two complexes. Ca²⁺ binding induces the pocket to open, enabling the substrate to access the pocket more easily. Molecular dynamics simulations suggest that a post-reaction state in the engaged form presumably exists between the experimentally observed forms, indicating that the substrate would be cleaved in the engaged form and then requires the enzyme to change to the open form to release the product, a process that Ca²⁺ can greatly accelerate.

A Rapid and Precise Mutation-Activated Fluorescence Reporter for Analyzing Acute Mutagenesis Frequency

Mutagenesis reporters are critical for quantifying genome stability. However, current methods rely on cell survival/death to report mutation, which takes weeks and prevents evaluation of acute or time-dependent changes. Existing methods also have other limitations, such as cell type restrictions. Using our discovery that mCherryFP fluorescence depends on residue Trp98, we replaced this codon with a stop codon to generate a mutation biosensor (termed CherryOFF), with a green fluorescence protein (GFP) as an internal control. We found that the red fluorescence of this biosensor is activated by a specific A/T-G/C nucleotide transition. Compared with the established hypoxanthine phosphoribosyl transferase assay, our reporter has similar or better ability to detect changes of mutation frequency induced by physical/chemical mutagens or manipulation of mutation-related genes. Furthermore, CherryOFF-GFP can report mutagenesis independently of cell-death events, can be adapted to many cell types, and can generate readouts within 1 day for the measurement of acute or time-dependent events.

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions

Background

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs.

Results

In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer.

Conclusion

MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on docking calculations with biochemical pathways and enables users to easily and quickly assess PPI feasibilities by archiving PPI predictions. MEGADOCK-Web also promotes the discovery of new PPIs and protein functions and is freely available for use at http://www.bi.cs.titech.ac.jp/megadock-web/.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2073-x) contains supplementary material, which is available to authorized users.

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.

MMTF-An efficient file format for the transmission, visualization, and analysis of macromolecular structures

Recent advances in experimental techniques have led to a rapid growth in complexity, size, and number of macromolecular structures that are made available through the Protein Data Bank. This creates a challenge for macromolecular visualization and analysis. Macromolecular structure files, such as PDB or PDBx/mmCIF files can be slow to transfer, parse, and hard to incorporate into third-party software tools. Here, we present a new binary and compressed data representation, the MacroMolecular Transmission Format, MMTF, as well as software implementations in several languages that have been developed around it, which address these issues. We describe the new format and its APIs and demonstrate that it is several times faster to parse, and about a quarter of the file size of the current standard format, PDBx/mmCIF. As a consequence of the new data representation, it is now possible to visualize structures with millions of atoms in a web browser, keep the whole PDB archive in memory or parse it within few minutes on average computers, which opens up a new way of thinking how to design and implement efficient algorithms in structural bioinformatics. The PDB archive is available in MMTF file format through web services and data that are updated on a weekly basis.