Analysis and Visualization of Protein Channels, Tunnels, and Pores with MOLEonline and ChannelsDB 2.0.

Channels, tunnels, and pores serve as pathways for the transport of molecules and ions through protein structures, thus participating to their functions. MOLEonline ( https://mole.upol.cz ) is an interactive web-based tool with enhanced capabilities for detecting and characterizing channels, tunnels, and pores within protein structures. MOLEonline has two distinct calculation modes for analysis of channel and tunnels or transmembrane pores. This application gives researchers rich analytical insights into channel detection, structural characterization, and physicochemical properties. ChannelsDB 2.0 ( https://channelsdb2.biodata.ceitec.cz/ ) is a comprehensive database that offers information on the location, geometry, and physicochemical characteristics of tunnels and pores within macromolecular structures deposited in Protein Data Bank and AlphaFill databases. These tunnels are sourced from manual deposition from literature and automatic detection using software tools MOLE and CAVER. MOLEonline and ChannelsDB visualization is powered by the LiteMol Viewer and Mol* viewer, ensuring a user-friendly workspace. This chapter provides an overview of user applications and usage.

Crystal-Phase- and B-Content-Dependent Electrochemical Behavior of Pd─B Nanocrystals toward Oxygen Reduction Reaction.

The manipulation of crystal phases in metal-nonmetal interstitial alloy nanostructures has attracted considerable attention due to the formation of unique electronic structures and surface atomic arrangements, resulting in unprecedented catalytic performances. However, achieving simultaneous control over crystal phase and nonmetal elements in metal-nonmetal interstitial alloy nanostructures has remained a formidable challenge. Here, a novel synthesis approach is presented for Pd─B interstitial alloy nanocrystals (NCs) that allows investigation of the crystal-phase- and B-content-dependent catalytic performance. Through comparison of the oxygen reduction reaction (ORR) properties of Pd─BX interstitial alloy NCs with different crystal phases and B contents, achieved by precise control of reaction temperature and time, the influences of crystal phase and B contents in the Pd─BX interstitial alloy NCs on ORR are precisely investigated. The hexagonal closed packed (hcp) PdB0.5 NCs exhibit superior catalytic activity, with mass activities reaching 2.58 A mg-1, surpassing Pd/C by 10.3 times, attributed to synergistic effects by the hcp crystal phase and relatively high B contents. This study not only provides a novel approach to fabricate interstitial alloy nanostructures with unconventional crystal phases and finely controlled nonmetal elements but also elucidates the importance of crystal phase and nonmetal element content in optimizing electrocatalytic efficiency.

FP-Zernike: An Open-source Structural Database Construction Toolkit for Fast Structure Retrieval.

The release of AlphaFold2 has sparked a rapid expansion in protein model databases. Efficient protein structure retrieval is crucial for the analysis of structure models, while measuring the similarity between structures is the key challenge in structural retrieval. Although existing structure alignment algorithms can address this challenge, they are often time-consuming. Currently, the state-of-the-art approach involves converting protein structures into three-dimensional (3D) Zernike descriptors and assessing similarity using Euclidean distance. However, the methods for computing 3D Zernike descriptors mainly rely on structural surfaces and are predominantly web-based, thus limiting their application in studying custom datasets. To overcome this limitation, we developed FP-Zernike, a user-friendly toolkit for computing different types of Zernike descriptors based on feature points. Users simply need to enter a single line of command to calculate the Zernike descriptors of all structures in customized datasets. FP-Zernike outperforms the leading method in terms of retrieval accuracy and binary classification accuracy across diverse benchmark datasets. In addition, we showed the application of FP-Zernike in the construction of the descriptor database and the protocol used for the Protein Data Bank (PDB) dataset to facilitate the local deployment of this tool for interested readers. Our demonstration contained 590,685 structures, and at this scale, our system required only 4-9 s to complete a retrieval. The experiments confirmed that it achieved the state-of-the-art accuracy level. FP-Zernike is an open-source toolkit, with the source code and related data accessible at https://ngdc.cncb.ac.cn/biocode/tools/BT007365/releases/0.1, as well as through a webserver at http://www.structbioinfo.cn/.

From PDB files to protein features: a comparative analysis of PDB bind and STCRDAB datasets.

Understanding protein structures is crucial for various bioinformatics research, including drug discovery, disease diagnosis, and evolutionary studies. Protein structure classification is a critical aspect of structural biology, where supervised machine learning algorithms classify structures based on data from databases such as Protein Data Bank (PDB). However, the challenge lies in designing numerical embeddings for protein structures without losing essential information. Although some effort has been made in the literature, researchers have not effectively and rigorously combined the structural and sequence-based features for efficient protein classification to the best of our knowledge. To this end, we propose numerical embeddings that extract relevant features for protein sequences fetched from PDB structures from popular datasets such as PDB Bind and STCRDAB. The features are physicochemical properties such as aromaticity, instability index, flexibility, Grand Average of Hydropathy (GRAVY), isoelectric point, charge at pH, secondary structure fracture, molar extinction coefficient, and molecular weight. We also incorporate scaling features for the sliding windows (e.g., k-mers), which include Kyte and Doolittle (KD) hydropathy scale, Eisenberg hydrophobicity scale, Hydrophilicity scale, Flexibility of the amino acids, and Hydropathy scale. Multiple-feature selection aims to improve the accuracy of protein classification models. The results showed that the selected features significantly improved the predictive performance of existing embeddings.

Determining Protein Structures Using X-Ray Crystallography.

X-ray crystallography is a robust and widely used technique that facilitates the three-dimensional structure determination of proteins at an atomic scale. This methodology entails the growth of protein crystals under controlled conditions followed by their exposure to X-ray beams and the subsequent analysis of the resulting diffraction patterns via computational tools to determine the three-dimensional architecture of the protein. However, achieving high-resolution structures through X-ray crystallography can be quite challenging due to complexities associated with protein purity, crystallization efficiency, and crystal quality.In this chapter, we provide a detailed overview of the gene to structure determination pipeline used in X-ray crystallography, a crucial tool for understanding protein structures. The chapter covers the steps in protein crystallization, along with the processes of data collection, processing, structure determination, and refinement. The most commonly faced challenges throughout this procedure are also addressed. Finally, the importance of standardized protocols for reproducibility and accuracy is emphasized, as they are crucial for advancing the understanding of protein structure and function.

Diphenylene Iodonium as a Prominent Halogen Bond Donor: The Case of Human Monoamine Oxidase B.

Herein we have investigated the formation and interplay of several noncovalent interactions (NCIs) involved in the inhibition of human monoamine oxidase B (MAO B). Concretely, an inspection of the Protein Data Bank (PDB) revealed the formation of a halogen bond (HlgB) between a diphenylene iodonium (DPI) inhibitor and a water molecule present in the active site, in addition to a noncovalent network of interactions (e. g. lone pair-π, hydrogen bonding, OH-π, CH-π and π-stacking interactions) with surrounding protein residues. Several theoretical models were built to understand the strength and directionality features of the HlgB in addition to the interplay with other NCIs present in the active site of the enzyme. Besides, a computational study was carried out using DPI as HlgB donor and several electron rich molecules (CO, H2O, CH2O, HCN, pyridine, OCN-, SCN-, Cl- and Br-) as HlgB acceptors. The results were analyzed using several state-of-the-art computational tools. We expect that our results will be useful for those scientists working in the fields of rational drug design, chemical biology as well as supramolecular chemistry.

IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods.

IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.

Conformational Preferences at the Glycosidic Linkage of Saccharides in Solution as Deduced from NMR Experiments and MD Simulations: Comparison to Crystal Structures.

Glycans are central to information content and regulation in biological systems. These carbohydrate molecules are active either as oligo- or polysaccharides, often in the form of glycoconjugates. The monosaccharide entities are joined by glycosidic linkages and stereochemical arrangements are of utmost importance in determining conformation and flexibility of saccharides. The conformational preferences and population distributions at the glycosidic torsion angles φ and ψ have been investigated for O-methyl glycosides of three disaccharides where the substitution takes place at a secondary alcohol, viz., in α-l-Fucp-(1→3)-ß-d-Glcp-OMe, α-l-Fucp-(1→3)-α-d-Galp-OMe and α-d-Glcp-(1→4)-α-d-Galp-OMe, corresponding to disaccharide structural elements present in bacterial polysaccharides. Stereochemical differences at or adjacent to the glycosidic linkage were explored by solution state NMR spectroscopy using one-dimensional 1 H,1 H-NOESY NMR experiments to obtain transglycosidic proton-proton distances and one- and two-dimensional heteronuclear NMR experiments to obtain 3 JCH transglycosidic coupling constants related to torsion angles φ and ψ. Computed effective proton-proton distances from molecular dynamics (MD) simulations showed excellent agreement to experimentally derived distances for the α-(1→3)-linked disaccharides and revealed that for the bimodal distribution at the ψ torsion angle for the α-(1→4)-linked disaccharide experiment and simulation were at variance with each other, calling for further force field developments. The MD simulations disclosed a highly intricate inter-residue hydrogen bonding pattern for the α-(1→4)-linked disaccharide, including a nonconventional hydrogen bond between H5' in the glucosyl residue and O3 in the galactosyl residue, supported by a large downfield 1 H NMR chemical shift displacement compared to α-d-Glcp-OMe. Comparison of population distributions of the glycosidic torsion angles φ and ψ in the disaccharide entities to those of corresponding crystal structures highlighted the potential importance of solvation on the preferred conformation.

Structure determination needs to go viral.

Viral diseases are expected to cause new epidemics in the future, therefore, it is essential to assess how viral diversity is represented in terms of deposited protein structures. Here, data were collected from the Protein Data Bank to screen the available structures of viruses of interest to WHO. Excluding SARS-CoV-2 and HIV-1, less than 50 structures were found per year, indicating a lack of diversity. Efforts to determine viral structures are needed to increase preparedness for future public health challenges.

Structural highlights of macromolecular complexes and assemblies.

The structures of macromolecular assemblies have given us deep insights into cellular processes and have profoundly impacted biological research and drug discovery. We highlight the structures of macromolecular assemblies that have been modeled using integrative and computational methods and describe how open access to these structures from structural archives has empowered the research community. The arsenal of experimental and computational methods for structure determination ensures a future where whole organelles and cells can be modeled.

Unveiling the multifaceted landscape of N-glycosylation in antibody variable domains: Insights and implications.

N-glycosylation at the antibody variable domain has emerged as an important modification influencing antibody function. Despite its significance, information regarding its role and regulation remains limited. To address this gap, we comprehensively explored antibody structures housing N-glycosylation within the Protein Data Bank, yielding fresh insights into this intricate landscape. Our findings revealed that among 208 structures, N-glycosylation was more prevalent in human and mouse antibodies containing IGHV1-8 and IGHV2-2 germline genes, respectively. Moreover, our research highlights the potential for somatic hypermutation to introduce N-glycosylation sites by substituting polar residues (Ser or Thr) in germline variable genes with asparagine. Notably, our study underscores the prevalence of N-glycosylation in antiviral antibodies, especially anti-HIV. Besides antigen-antibody interaction, our findings suggest that N-glycosylation may impact antibody specificity, affinity, and avidity by influencing Fab dimer formation and complementary-determining region orientation. We also identified different glycan structures in HIV and SARS-CoV-2 antibody proteomic datasets, highlighting disparities from the N-glycan structures between PDB antibodies and biological repertoires further highlighting the complexity of N-glycosylation patterns. Our findings significantly enrich our understanding of the N-glycosylation's multifaceted characteristics within the antibody variable domain. Additionally, they underscore the pressing imperative for a more comprehensive characterization of its impact on antibody function.

Paget's disease of bone in the patient presented with a bowed leg.

Key Clinical Message: In dealing with bowed limbs along with increased alkaline phosphatase (ALP), even if the typical changes to the face are not very noticeable at first glance, Paget's disease of the bone (PDB) should be suspected, and the necessary investigations should be carried out to confirm the diagnosis. Abstract: Paget's disease of the bone (PDB) is the second most prevalent metabolic bone disorder worldwide with disorganized bone remodeling. Here, a patient is presented with pain and bending of the right leg, whose skull and forehead changes are not noticeable at first glance, but with clinical suspicion and additional diagnostic evaluations, PDB diagnosis is confirmed for the patient.

PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank.

While the Protein Data Bank (PDB) contains a wealth of structural information on ligands bound to macromolecules, their analysis can be challenging due to the large amount and diversity of data. Here, we present PDBe CCDUtils, a versatile toolkit for processing and analysing small molecules from the PDB in PDBx/mmCIF format. PDBe CCDUtils provides streamlined access to all the metadata for small molecules in the PDB and offers a set of convenient methods to compute various properties using RDKit, such as 2D depictions, 3D conformers, physicochemical properties, scaffolds, common fragments, and cross-references to small molecule databases using UniChem. The toolkit also provides methods for identifying all the covalently attached chemical components in a macromolecular structure and calculating similarity among small molecules. By providing a broad range of functionality, PDBe CCDUtils caters to the needs of researchers in cheminformatics, structural biology, bioinformatics and computational chemistry.

Electronic Structure and Chemical Bonding of the First-, Second-, and Third-Row-Transition-Metal Monoborides: The Formation of Quadruple Bonds in RhB, RuB, and TcB.

Boron presents an important role in chemistry, biology, and materials science. Diatomic transition-metal borides (MBs) are the building blocks of many complexes and materials, and they present unique electronic structures with interesting and peculiar properties and a variety of bonding schemes which are analyzed here. In the first part of this paper, we present a review on the available experimental and theoretical studies on the first-row-transition-metal borides, i.e., ScB, TiB, VB, CrB, MnB, FeB, CoB, NiB, CuB, and ZnB; the second-row-transition-metal borides, i.e., YB, ZrB, NbB, MoB, TcB, RuB, RhB, PdB, AgB, and CdB; and the third-row-transition-metal borides, i.e., LaB, HfB, TaB, WB, ReB, OsB, IrB, PtB, AuB, and HgB. Consequently, in the second part, the second- and third-row MBs are studied via DFT calculations using the B3LYP, TPSSh, and MN15 functionals and, in some cases, via multi-reference methods, MRCISD+Q, in conjunction with the aug-cc-pVQZ-PPM/aug-cc-pVQZB basis sets. Specifically, bond distances, dissociation energies, frequencies, dipole moments, and natural NPA charges are reported. Comparisons between MB molecules along the three rows are presented, and their differences and similarities are analyzed. The bonding of the diatomic borides is also described; it is found that, apart from RhB(X1Σ+), which was just recently found to form quadruple bonds, RuB(X2Δ) and TcB(X3Σ-) also form quadruple σ2σ2π2π2 bonds in their X states. Moreover, to fill the gap existing in the current literature, here, we calculate the TcB molecule.

New tetrazolopyrrolidine-1,2,3-triazole analogues as potent anticancer agents: design, synthesis and molecular docking studies.

1,2,3-Triazole and tetrazole derivatives bearing pyrrolidines are found to exhibit notable biological activity and have become useful scaffolds in medicinal chemistry for application in lead discovery and optimization. We report design, synthesis and molecular docking studies of tetrazolyl-1,2,3-triazole derivatives (7a-i) bearing pyrrolidine moiety and evaluating their anticancer activity against four cancer cell lines viz. Hela, MCF-7, HCT-116 and HepG2. The structures of the new compounds were ascertained by spectral means IR, NMR: 1H &13C and Mass spectrum. From the studies compounds7a and 7i exhibited significant anticancer activity against the Hela cell line with IC50 = 0.32 ± 1.00, 1.80 ± 0.22 µM when compared to reference drug Doxorubicin (IC50 = 2.34 ± 0.11 µM), whereas 7h, 7i, and 7b were found to be active against MCF-7, HCT-116 and HepG2 cell lines with IC50 = 3.20 ± 1.40, 1.38 ± 0.06 and 0.97 ± 0.12 µM respectively. Notably 7a exhibited highest conventional hydrogen bondings TyrA:40, SerA:17, LysA:117, AlaA:146, Tyr218 with 3HB4and SerA:17, LysA:117, AlaA:146, TyrA:40 with 6IBZ and docking energy - 10.85, - 8.21 kcal/mol respectively. These compounds were further evaluated for their ADMET and physicochemical properties by using SwissADME. The results of the in vitro and in silico studies suggest that the tetrazole incorporated pyrrolidine-triazoles may possess the ideal structural requirements for further developing new anticancer agents.

Challenges in bridging the gap between protein structure prediction and functional interpretation.

The rapid evolution of protein structure prediction tools has significantly broadened access to protein structural data. Although predicted structure models have the potential to accelerate and impact fundamental and translational research significantly, it is essential to note that they are not validated and cannot be considered the ground truth. Thus, challenges persist, particularly in capturing protein dynamics, predicting multi-chain structures, interpreting protein function, and assessing model quality. Interdisciplinary collaborations are crucial to overcoming these obstacles. Databases like the AlphaFold Protein Structure Database, the ESM Metagenomic Atlas, and initiatives like the 3D-Beacons Network provide FAIR access to these data, enabling their interpretation and application across a broader scientific community. Whilst substantial advancements have been made in protein structure prediction, further progress is required to address the remaining challenges. Developing training materials, nurturing collaborations, and ensuring open data sharing will be paramount in this pursuit. The continued evolution of these tools and methodologies will deepen our understanding of protein function and accelerate disease pathogenesis and drug development discoveries.

On the Importance of Halogen and Chalcogen Bonds in the Solid State of Nucleic Acids: A Combined Crystallographic and Theoretical Perspective.

In this work, intra- and intermolecular halogen and chalcogen bonds (HlgBs and ChBs, respectively) present in the solid state of nucleic acids (NAs) have been studied at the RI-MP2/def2-TZVP level of theory. To achieve this, a Protein Data Bank (PDB) survey was carried out, revealing a series of structures in which Br/I or S/Se/Te atoms belonging to nucleobases or pentose rings were involved in noncovalent interactions (NCIs) with electron-rich species. The energetics and directionality of these NCIs were rationalized through a computational study, which included the use of Molecular Electrostatic Potential (MEP) surfaces, the Quantum Theory of Atoms in Molecules (QTAIM), and Non Covalent Interaction plot (NCIplot) and Natural Bonding Orbital (NBO) techniques.

Interaction of Vanadium Complexes with Proteins: Revisiting the Reported Structures in the Protein Data Bank (PDB) since 2015.

The structural determination and characterization of molecules, namely proteins and enzymes, is crucial to gaining a better understanding of their role in different chemical and biological processes. The continuous technical developments in the experimental and computational resources of X-ray diffraction (XRD) and, more recently, cryogenic Electron Microscopy (cryo-EM) led to an enormous growth in the number of structures deposited in the Protein Data Bank (PDB). Bioinorganic chemistry arose as a relevant discipline in biology and therapeutics, with a massive number of studies reporting the effects of metal complexes on biological systems, with vanadium complexes being one of the relevant systems addressed. In this review, we focus on the interactions of vanadium compounds (VCs) with proteins. Several types of binding are established between VCs and proteins/enzymes. Considering that the V-species that bind may differ from those initially added, the mentioned structural techniques are pivotal to clarifying the nature and variety of interactions of VCs with proteins and to proposing the mechanisms involved either in enzymatic inhibition or catalysis. As such, we provide an account of the available structural information of VCs bound to proteins obtained by both XRD and/or cryo-EM, mainly exploring the more recent structures, particularly those containing organic-based vanadium complexes.

Sex influences clinical phenotype in valosin-containing protein mutations: A case family report and systematic literature review.

OBJECTIVE: Mutations in the valosin-containing protein (VCP) gene cause autosomal dominant multisystem proteinopathy 1 (MSP1), characterized by a variable combination of inclusion body myopathy (IBM), Paget's disease of bone (PDB), and frontotemporal dementia (FTD). Here we report a novel VCP missense mutations in an Italian family with FTD as the prevalent manifestation and compare our results with those described in the literature. METHODS: We described the clinical, molecular, and imaging data of the studied family. We also conducted a systematic literature search with the aim of comparing our findings with previously reported VCP-related phenotypes. RESULTS: A novel heterozygous VCP missense mutation (c 0.473 T > C/p.Met158Thr) was found in all the affected family members. The proband is a 69-year-old man affected by progressive muscle weakness since the age of 49. Muscle MRI showed patchy fatty infiltration in most muscles, and STIR sequences revealed an unusual signal increase in distal leg muscles. At age 65, he presented a cognitive disorder suggestive of behavioral variant FTD. A bone scintigraphy also revealed PDB. The patient's mother, his maternal aunt and her daughter had died following a history of cognitive deterioration consistent with FTD; the mother also had PDB. No relatives had any muscular impairments. Reviewing the literature data, we observed a different sex distribution of VCP-related phenotypes, being FTD prevalence higher among women as compared to men (51.2 % vs 31.2 %) and IBM prevalence higher among men as compared to women (92.1 % vs 72.8 %). DISCUSSION: This study broadened our clinical, genetic, and imaging knowledge of VCP-related disorders.

The Interactome of Protein, DNA, and RNA.

Proteins participate in many processes of the organism and are very important for maintaining the health of the organism. However, proteins cannot function independently in the body. They must interact with proteins, DNA, RNA, and other substances to perform biological functions and maintain the body's health. At present, there are many experimental methods and software tools that can detect and predict the interaction between proteins and other substances. There are also many databases that record the interaction between proteins and other substances. This article mainly describes protein-protein, protein-DNA, and protein-RNA interactions in detail by introducing some commonly used experimental methods, the software tools produced with the accumulation of experimental data and the rapid development of machine learning, and the related databases that record the relationship between proteins and some substances. By this review, we hope that through the analysis and summary of various aspects, it will be convenient for researchers to conduct further research on protein interactions.