NGL viewer: web-based molecular graphics for large complexes

DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning

Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.

tracerDB: a crowdsourced fluorescent tracer database for target engagement analysis

Investigating ligand-protein complexes is essential in the areas of chemical biology and drug discovery. However, detailed information on key reagents such as fluorescent tracers and associated data for the development of widely used bioluminescence resonance energy transfer (BRET) assays including NanoBRET, time-resolved Förster resonance energy transfer (TR-FRET) and fluorescence polarization (FP) assays are not easily accessible to the research community. We created tracerDB, a curated database of validated tracers. This resource provides an open access knowledge base and a unified system for tracer and assay validation. The database is freely available at https://www.tracerdb.org/ .

Proscan: a structure-based proline design web server

The ability to control protein conformations and dynamics through structure-based design has been useful in various scenarios, including engineering of viral antigens for vaccines. One effective design strategy is the substitution of residues to proline amino acids, which due to its unique cyclic side chain can favor and rigidify key backbone conformations. To provide the community with a means to readily identify and explore proline designs for target proteins of interest, we developed the Proscan web server. Proscan provides assessment of backbone angles, energetic and deep learning-based favorability scores, and other parameters for proline substitutions at each position of an input structure, along with interactive visualization of backbone angles and candidate substitution sites on structures. It identifies known favorable proline substitutions for viral antigens, and was benchmarked against datasets of proline substitution stability effects from deep mutational scanning and thermodynamic measurements. This tool can enable researchers to identify and prioritize designs for prospective vaccine antigen targets, or other designs to favor stability of key protein conformations. Proscan is available at: https://proscan.ibbr.umd.edu.

The structure assessment web server: for proteins, complexes and more

The 'structure assessment' web server is a one-stop shop for interactive evaluation and benchmarking of structural models of macromolecular complexes including proteins and nucleic acids. A user-friendly web dashboard links sequence with structure information and results from a variety of state-of-the-art tools, which facilitates the visual exploration and evaluation of structure models. The dashboard integrates stereochemistry information, secondary structure information, global and local model quality assessment of the tertiary structure of comparative protein models, as well as prediction of membrane location. In addition, a benchmarking mode is available where a model can be compared to a reference structure, providing easy access to scores that have been used in recent CASP experiments and CAMEO. The structure assessment web server is available at https://swissmodel.expasy.org/assess.

SwissDock 2024: major enhancements for small-molecule docking with Attracting Cavities and AutoDock Vina

Drug discovery aims to identify potential therapeutic compounds capable of modulating the activity of specific biological targets. Molecular docking can efficiently support this process by predicting binding interactions between small molecules and macromolecular targets and potentially accelerating screening campaigns. SwissDock is a computational tool released in 2011 as part of the SwissDrugDesign project, providing a free web-based service for small-molecule docking after automatized preparation of ligands and targets. Here, we present the latest version of SwissDock, in which EADock DSS has been replaced by two state-of-the-art docking programs, i.e. Attracting Cavities and AutoDock Vina. AutoDock Vina provides faster docking predictions, while Attracting Cavities offers more accurate results. Ligands can be imported in various ways, including as files, SMILES notation or molecular sketches. Targets can be imported as PDB files or identified by their PDB ID. In addition, advanced search options are available both for ligands and targets, giving users automatized access to widely-used databases. The web interface has been completely redesigned for interactive submission and analysis of docking results. Moreover, we developed a user-friendly command-line access which, in addition to all options of the web site, also enables covalent ligand docking with Attracting Cavities. The new version of SwissDock is freely available at https://www.swissdock.ch/.

Monoclonal antibodies and aptamers: The future therapeutics for Alzheimer's disease

Alzheimer's disease (AD) is considered the most common and prevalent form of dementia of adult-onset with characteristic progressive impairment in cognition and memory. The cure for AD has not been found yet and the treatments available until recently were only symptomatic. Regardless of multidisciplinary approaches and efforts made by pharmaceutical companies, it was only in the past two years that new drugs were approved for the treatment of the disease. Amyloid beta (Aβ) immunotherapy is at the core of this therapy, which is one of the most innovative approaches looking to change the course of AD. This technology is based on synthetic peptides or monoclonal antibodies (mAb) to reduce Aβ levels in the brain and slow down the advance of neurodegeneration. Hence, this article reviews the state of the art about AD neuropathogenesis, the traditional pharmacologic treatment, as well as the modern active and passive immunization describing approved drugs, and drug prototypes currently under investigation in different clinical trials. In addition, future perspectives on immunotherapeutic strategies for AD and the rise of the aptamer technology as a non-immunogenic alternative to curb the disease progression are discussed.

MicroProteinDB: A database to provide knowledge on sequences, structures and function of ncRNA-derived microproteins

Omics-based technologies have revolutionized our comprehension of microproteins encoded by ncRNAs, revealing their abundant presence and pivotal roles within complex functional landscapes. Here, we developed MicroProteinDB (http://bio-bigdata.hrbmu.edu.cn/MicroProteinDB), which offers and visualizes the extensive knowledge to aid retrieval and analysis of computationally predicted and experimentally validated microproteins originating from various ncRNA types. Employing prediction algorithms grounded in diverse deep learning approaches, MicroProteinDB comprehensively documents the fundamental physicochemical properties, secondary and tertiary structures, interactions with functional proteins, family domains, and inter-species conservation of microproteins. With five major analytical modules, it will serve as a valuable knowledge for investigating ncRNA-derived microproteins.

CHARMM-GUI QM/MM Interfacer for a Quantum Mechanical and Molecular Mechanical (QM/MM) Simulation Setup: 1. Semiempirical Methods

Quantum mechanical (QM) treatments, when combined with molecular mechanical (MM) force fields, can effectively handle enzyme-catalyzed reactions without significantly increasing the computational cost. In this context, we present CHARMM-GUI QM/MM Interfacer, a web-based cyberinfrastructure designed to streamline the preparation of various QM/MM simulation inputs with ligand modification. The development of QM/MM Interfacer has been achieved through integration with existing CHARMM-GUI modules, such as PDB Reader and Manipulator, Solution Builder, and Membrane Builder. In addition, new functionalities have been developed to facilitate the one-stop preparation of QM/MM systems and enable interactive and intuitive ligand modifications and QM atom selections. QM/MM Interfacer offers support for a range of semiempirical QM methods, including AM1(+/d), PM3(+/PDDG), MNDO(+/d, +/PDDG), PM6, RM1, and SCC-DFTB, tailored for both AMBER and CHARMM. A nontrivial setup related to ligand modification, link-atom insertion, and charge distribution is automatized through intuitive user interfaces. To illustrate the robustness of QM/MM Interfacer, we conducted QM/MM simulations of three enzyme-substrate systems: dihydrofolate reductase, insulin receptor kinase, and oligosaccharyltransferase. In addition, we have created three tutorial videos about building these systems, which can be found at https://www.charmm-gui.org/demo/qmi. QM/MM Interfacer is expected to be a valuable and accessible web-based tool that simplifies and accelerates the setup process for hybrid QM/MM simulations.

The HADDOCK2.4 web server for integrative modeling of biomolecular complexes

Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server's various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody-antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types.

User-centric design of a 3D search interface for protein-ligand complexes

In this work, we present the frontend of GeoMine and showcase its application, focusing on the new features of its latest version. GeoMine is a search engine for ligand-bound and predicted empty binding sites in the Protein Data Bank. In addition to its basic text-based search functionalities, GeoMine offers a geometric query type for searching binding sites with a specific relative spatial arrangement of chemical features such as heavy atoms and intermolecular interactions. In contrast to a text search that requires simple and easy-to-formulate user input, a 3D input is more complex, and its specification can be challenging for users. GeoMine's new version aims to address this issue from the graphical user interface perspective by introducing an additional visualization concept and a new query template type. In its latest version, GeoMine extends its query-building capabilities primarily through input formulation in 2D. The 2D editor is fully synchronized with GeoMine's 3D editor and provides the same functionality. It enables template-free query generation and template-based query selection directly in 2D pose diagrams. In addition, the query generation with the 3D editor now supports predicted empty binding sites for AlphaFold structures as query templates. GeoMine is freely accessible on the ProteinsPlus web server ( https://proteins.plus ).

Targeting RAF dimers in RAS mutant tumors: From biology to clinic

RAS mutations occur in approximately 30% of tumors worldwide and have a poor prognosis due to limited therapies. Covalent targeting of KRAS G12C has achieved significant success in recent years, but there is still a lack of efficient therapeutic approaches for tumors with non-G12C KRAS mutations. A highly promising approach is to target the MAPK pathway downstream of RAS, with a particular focus on RAF kinases. First-generation RAF inhibitors have been authorized to treat BRAF mutant tumors for over a decade. However, their use in RAS-mutated tumors is not recommended due to the paradoxical ERK activation mainly caused by RAF dimerization. To address the issue of RAF dimerization, type II RAF inhibitors have emerged as leading candidates. Recent clinical studies have shown the initial effectiveness of these agents against RAS mutant tumors. Promisingly, type II RAF inhibitors in combination with MEK or ERK inhibitors have demonstrated impressive efficacy in RAS mutant tumors. This review aims to clarify the importance of RAF dimerization in cellular signaling and resistance to treatment in tumors with RAS mutations, as well as recent progress in therapeutic approaches to address the problem of RAF dimerization in RAS mutant tumors.

From complex data to clear insights: visualizing molecular dynamics trajectories

Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.

Magnolol-driven microbiota modulation elicits changes in tryptophan metabolism resulting in reduced skatole formation in pigs

Skatole of gut origin has garnered significant attention as a malodorous pollutant due to its escalating emissions, recalcitrance to biodegradation and harm to animal and human health. Magnolol is a health-promoting polyphenol with potential to considerably mitigate the skatole production in the intestines. To investigate the impact of magnolol and its underlying mechanism on the skatole formation, in vivo and in vitro experiments were conducted in pigs. Our results revealed that skatole concentrations in the cecum, colon, and faeces decreased by 58.24% (P = 0.088), 44.98% (P < 0.05) and 43.52% (P < 0.05), respectively, following magnolol supplementation. Magnolol supplementation significantly decreased the abundance of Lachnospira, Faecalibacterium, Paramuribaculum, Faecalimonas, Desulfovibrio, Bariatricus, and Mogibacterium within the colon (P < 0.05). Moreover, a strong positive correlation (P < 0.05) between skatole concentration and Desulfovibrio abundance was observed. Subsequent in silico studies showed that magnolol could dock well with indolepyruvate decarboxylase (IPDC) within Desulfovibrio. Further in vitro investigation unveiled that magnolol addition led to less indole-3-pyruvate diverted towards the oxidative skatole pathway by the potential docking of magnolol towards IPDC, thereby diminishing the conversion of substrate into skatole. Our findings offer novel targets and strategies for mitigating skatole emission from the source.

Emerging insight of whole genome sequencing coupled with protein structure prediction into the pyrazinamide-resistance signature of Mycobacterium tuberculosis

Pyrazinamide (PZA) is considered to be a pivotal drug to shorten the treatment of both drug-susceptible and drug-resistant tuberculosis, but its use is challenged by the reliability of drug-susceptibility testing (DST). PZA resistance in Mycobacterium tuberculosis (MTB) is relevant to the amino acid substitution of pyrazinamidase that is responsible for the conversion of PZA to active pyrazinoic acid (POA). The single nucleotide variants (SNVs) within ribosomal protein S1 (rpsA) or aspartate decarboxylase (panD), the binding targets of POA, has been reported to drive the PZA-resistance signature of MTB. In this study, whole genome sequencing (WGS) was used to identify SNVs within the pncA, rpsA and panD genes in 100 clinical MTB isolates associated with DST results for PZA. The potential influence of high-confidence, interim-confidence or emerging variants on the interplay between target genes and PZA or POA was simulated computationally, and predicted with a protein structure modelling approach. The DST results showed weak agreement with the identification of high-confidence variants within the pncA gene (Cohen's kappa coefficient=0.58), the analytic results of WGS coupled with protein structure modelling on pncA mutants (Cohen's kappa coefficient=0.524) or related genes (Cohen's kappa coefficient=0.504). Taken together, these results suggest the practicable application of a genotypic-coupled bioinformatic approach to manage PZA-containing regimens for patients with MTB.

Curation, nomenclature, and topological classification of receptor-like kinases from 528 plant species for novel domain discovery and functional inference

Receptor-like kinases (RLKs) are the most numerous signal transduction components in plants and play important roles in determining how different plants adapt to their ecological environments. Research on RLKs has focused mainly on a small number of typical RLK members in a few model plants. There is an urgent need to study the composition, distribution, and evolution of RLKs at the holistic level to increase our understanding of how RLKs assist in the ecological adaptations of different plant species. In this study, we collected the genome assemblies of 528 plant species and constructed an RLK dataset. Using this dataset, we identified and characterized 524 948 RLK family members. Each member underwent systematic topological classification and was assigned a gene ID based on a unified nomenclature system. Furthermore, we identified two novel extracellular domains in some RLKs, designated Xiao and Xiang. Evolutionary analysis of the RLK family revealed that the RLCK-XVII and RLCK-XII-2 classes were present exclusively in dicots, suggesting that diversification of RLKs between monocots and dicots may have led to differences in downstream cytoplasmic responses. We also used an interaction proteome to help empower data mining for inference of new RLK functions from a global perspective, with the ultimate goal of understanding how RLKs shape the adaptation of different plants to the environments/ecosystems. The assembled RLK dataset, together with annotations and analytical tools, forms an integrated foundation of multiomics data that is publicly accessible via the metaRLK web portal (http://metaRLK.biocloud.top).

Probe-dependent Proximity Profiling (ProPPr) Uncovers Similarities and Differences in Phospho-Tau-Associated Proteomes Between Tauopathies

Tauopathies represent a diverse group of neurodegenerative disorders characterized by the abnormal aggregation of the microtubule-associated protein tau. Despite extensive research, the precise mechanisms underlying the complexity of different types of tau pathology remain incompletely understood. Here we describe an approach for proteomic profiling of aggregate-associated proteomes on slides with formalin-fixed, paraffin-embedded (FFPE) tissue that utilizes proximity labelling upon high preservation of aggregate morphology, which permits the profiling of pathological aggregates regardless of their size. To comprehensively investigate the common and unique protein interactors associated with the variety of tau lesions present across different human tauopathies, Alzheimer's disease (AD), corticobasal degeneration (CBD), Pick's disease (PiD), and progressive supranuclear palsy (PSP), were selected to represent the major tauopathy diseases. Implementation of our widely applicable Probe-dependent Proximity Profiling (ProPPr) strategy, using the AT8 antibody, permitted identification and quantification of proteins associated with phospho-tau lesions in well-characterized human post-mortem tissue. The analysis revealed both common and disease-specific proteins associated with phospho-tau aggregates, highlighting potential targets for therapeutic intervention and biomarker development. Candidate validation through high-resolution co-immunofluorescence of distinct aggregates across disease and control cases, confirmed the association of retromer complex protein VPS35 with phospho-tau lesions across the studied tauopathies. Furthermore, we discovered disease-specific associations of proteins including ferritin light chain (FTL) and the neuropeptide precursor VGF within distinct pathological lesions. Notably, examination of FTL-positive microglia in CBD astrocytic plaques indicate a potential role for microglial involvement in the pathogenesis of these tau lesions. Our findings provide valuable insights into the proteomic landscape of tauopathies, shedding light on the molecular mechanisms underlying tau pathology. This first comprehensive characterization of tau-associated proteomes across different tauopathies enhances our understanding of disease heterogeneity and provides a resource for future functional investigation, as well as development of targeted therapies and diagnostic biomarkers.

Fast and accurate protein structure search with Foldseek

As structure prediction methods are generating millions of publicly available protein structures, searching these databases is becoming a bottleneck. Foldseek aligns the structure of a query protein against a database by describing tertiary amino acid interactions within proteins as sequences over a structural alphabet. Foldseek decreases computation times by four to five orders of magnitude with 86%, 88% and 133% of the sensitivities of Dali, TM-align and CE, respectively.

Synthesis and anxiolytic effect of europium metallic complex containing lapachol [Eu(DBM)3. LAP] in adult zebrafish through serotonergic neurotransmission: in vivo and in silico approach

Anxiety-related mental health problems are estimated at 3.6% globally, benzodiazepines (BZDs) are the class of drugs indicated for the treatment of anxiety, including lorazepam and diazepam. However, concerns have been raised about the short- and long-term risks associated with BZDs. Therefore, despite anxiolytic and antidepressant drugs, there is a need to develop more effective pharmacotherapies with fewer side effects than existing drugs. The present work reported the synthesis, anxiolytic activity, mechanism of action in Adult Zebrafish (Danio rerio) and in silico study of a europium metallic complex with Lapachol, [Eu(DBM)3. LAP]. Each animal (n = 6/group) was treated intraperitoneally (i.p.; 20 µL) with the synthesized complex (4, 20 and 40 mg/Kg) and with the vehicle (DMSO 3%; 20 µL), being submitted to the tests of locomotor activity and 96h acute toxicity. The light/dark test was also performed, and the serotonergic mechanism (5-HT) was evaluated through the antagonists of the 5-HTR1, 5-HTR2A/2C and 5-HTR3A/3B receptors. The complex was characterized using spectrometric techniques, and the anxiolytic effect of complex may be involved the neuromodulation of receptors 5-HT3A/3B, since the pre-treatment with pizotifen and cyproheptadine did not block the anxiolytic effect of [Eu(DBM)3. LAP], unlike fluoxetine had its anxiolytic effect reversed. In addition, molecular docking showed interaction between the [Eu(DBM)3. LAP] and 5HT3A receptor with binding energy -7.8 kcal/mol and the ADMET study showed that complex has low toxic risk. It is expected that the beginning of this study will allow the application of the new anxiolytic drugs, given the pharmacological potential of the lapachol complex.Communicated by Ramaswamy H. Sarma.

Foldy: An open-source web application for interactive protein structure analysis

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy's interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy's interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.

A new paradigm for molecular dynamics databases: the COVID-19 database, the legacy of a titanic community effort

Molecular dynamics (MD) simulations are keeping computers busy around the world, generating a huge amount of data that is typically not open to the scientific community. Pioneering efforts to ensure the safety and reusability of MD data have been based on the use of simple databases providing a limited set of standard analyses on single-short trajectories. Despite their value, these databases do not offer a true solution for the current community of MD users, who want a flexible analysis pipeline and the possibility to address huge non-Markovian ensembles of large systems. Here we present a new paradigm for MD databases, resilient to large systems and long trajectories, and designed to be compatible with modern MD simulations. The data are offered to the community through a web-based graphical user interface (GUI), implemented with state-of-the-art technology, which incorporates system-specific analysis designed by the trajectory providers. A REST API and associated Jupyter Notebooks are integrated into the platform, allowing fully customized meta-analysis by final users. The new technology is illustrated using a collection of trajectories obtained by the community in the context of the effort to fight the COVID-19 pandemic. The server is accessible at https://bioexcel-cv19.bsc.es/#/. It is free and open to all users and there are no login requirements. It is also integrated into the simulations section of the BioExcel-MolSSI COVID-19 Molecular Structure and Therapeutics Hub: https://covid.molssi.org/simulations/ and is part of the MDDB effort (https://mddbr.eu).

Be2+ Causes Hypersensitivity but Mg2+ and Ca2+ Do Not─Favorable Metal Coordination Is the Key for Differential Allosteric Modulation and Binding Affinities

Although the ion selectivity of metalloproteins has been well established, selective metal antigen recognition by immunoproteins remains elusive. One such case is the recognition of the Be2+ ion against its heavier congeners, Mg2+ and Ca2+, by the human leukocyte antigen immunoprotein (HLA-DP2), leading to immunotoxicity. Integrating with our previous mechanistic study on Be2+ toxicity, herein, we have explored the basis of characteristic nontoxicity of Mg2+ and Ca2+ ions despite their in vivo abundance. The ion binding cleft of the HLA-DP2-peptide complex is composed of four acidic residues, p4D and p7E from the peptide and β26E and β69E from the protein. While the tetrahedral coordination site of the smaller Be2+ ion is located deep inside the cavity, hexa- to octa-coordination sites of Mg2+ and Ca2+ ions are located closer to the protein surface. The intrinsic high coordination number of Mg2+/Ca2+ ions induces allosteric modifications on the HLA-DP2_M2 surface, which are atypical for TCR recognition. Furthermore, the lower binding energy of larger Mg2+ and Ca2+ ions with the cavity residues can be correlated to the lower charge density and reduced covalent bonding nature as compared to those of the smaller Be2+ ion. In short, weak binding of Mg2+ and Ca2+ ions and the unfavorable allosteric surface modifications are probably the major determinants for the absence of Mg2+/Ca2+ ion-mediated hypersensitivity in humans.

Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets

Small-molecule conformer generation (SMCG) is an extremely important task in both ligand- and structure-based computer-aided drug design, especially during the hit discovery phase. Recently, a multitude of artificial intelligence (AI) models tailored for SMCG have emerged. Despite developers typically furnishing performance evaluation data upon releasing their AI models, a comprehensive and equitable performance comparison between AI models and conventional methods is still lacking. In this study, we curated a new benchmarking data set comprising 3354 high-quality ligand bioactive conformations. Subsequently, we conducted a systematic assessment of the performance of four widely adopted traditional methods (i.e., ConfGenX, Conformator, OMEGA, and RDKit ETKDG) and five AI models (i.e., ConfGF, DMCG, GeoDiff, GeoMol, and torsional diffusion) in the tasks of reproducing bioactive and low-energy conformations of small molecules. In the former task, the AI models have no advantage, particularly with a maximum ensemble size of 1. Even the best-performing AI model GeoMol is still worse than any of the tested traditional methods. Conversely, in the latter task, the torsional diffusion model shows obvious advantages, surpassing the best-performing traditional method ConfGenX by 26.09 and 12.97% on the COV-R and COV-P metrics, respectively. Furthermore, the influence of force field-based fine-tuning on the quality of the generated conformers was also discussed. Finally, a user-friendly Web server called fastSMCG was developed to enable researchers to rapidly and flexibly generate small-molecule conformers using both traditional and AI methods. We anticipate that our work will offer valuable practical assistance to the scientific community in this field.

dms-viz: Structure-informed visualizations for deep mutational scanning and other mutation-based datasets

Understanding how mutations impact a protein's functions is valuable for many types of biological questions. High-throughput techniques such as deep-mutational scanning (DMS) have greatly expanded the number of mutation-function datasets. For instance, DMS has been used to determine how mutations to viral proteins affect antibody escape (Dadonaite et al. 2023), receptor affinity (Starr et al. 2020), and essential functions such as viral genome transcription and replication (Li et al. 2023). With the growth of sequence databases, in some cases the effects of mutations can also be inferred from phylogenies of natural sequences (Bloom and Neher 2023) (Figure 1). The mutation-based data generated by these approaches is often best understood in the context of a protein's 3D structure; for instance, to assess questions like how mutations that affect antibody escape relate to the physical antibody binding epitope on the protein. However, current approaches for visualizing mutation data in the context of a protein's structure are often cumbersome and require multiple steps and softwares. To streamline the visualization of mutation-associated data in the context of a protein structure, we developed a web-based tool, dms-viz. With dms-viz, users can straightforwardly visualize mutation-based data such as those from DMS experiments in the context of a 3D protein model in an interactive format. See https://dms-viz.github.io/ to use dms-viz.

JSONWP: a static website generator for protein bioinformatics research

Motivation

Presenting the integrated results of bioinformatics research can be challenging and requires sophisticated visualization components, which can be time-consuming to develop. This article presents a new way to effectively communicate research findings.

Results

We have developed a static web page generator, JSONWP, which is specifically designed for protein bioinformatics research. Utilizing React (a JavaScript library used to build interactive and dynamic user interfaces for web applications), we have integrated publicly available bioinformatics visualization components to provide standardized access to these components. JSON (or JavaScript Object Notation, is a lightweight textual data format often used to structure and exchange information between different software tools.) is used as the input source due to its ability to represent nearly all types of data using key and value pairs. This allows researchers to use their preferred programming language to create a JSON representation, which can then be converted into a website by JSONWP. No server or domain is required to host the website, as only the publicly accessible JSON file is required.

Conclusions

Overall, JSONWP provides a useful new tool for bioinformatics researchers to effectively communicate their findings. The open-source implementation is located at https://github.com/MesihK/react-json-wpbuilder, and the tool can be used at jsonwp.onrender.com.

CSM-Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces

Proteins are molecular machinery that participate in virtually all essential biological functions within the cell, which are tightly related to their 3D structure. The importance of understanding protein structure-function relationship is highlighted by the exponential growth of experimental structures, which has been greatly expanded by recent breakthroughs in protein structure prediction, most notably RosettaFold, and AlphaFold2. These advances have prompted the development of several computational approaches that leverage these data sources to explore potential biological interactions. However, most methods are generally limited to analysis of single types of interactions, such as protein-protein or protein-ligand interactions, and their complexity limits the usability to expert users. Here we report CSM-Potential2, a deep learning platform for the analysis of binding interfaces on protein structures. In addition to prediction of protein-protein interactions binding sites and classification of biological ligands, our new platform incorporates prediction of interactions with nucleic acids at the residue level and allows for ligand transplantation based on sequence and structure similarity to experimentally determined structures. We anticipate our platform to be a valuable resource that provides easy access to a range of state-of-the-art methods to expert and non-expert users for the study of biological interactions. Our tool is freely available as an easy-to-use web server and API available at https://biosig.lab.uq.edu.au/csm_potential.

Interactions of Nucleosomes with Acidic Patch-Binding Peptides: A Combined Structural Bioinformatics, Molecular Modeling, Fluorescence Polarization, and Single-Molecule FRET Study

In eukaryotic organisms, genomic DNA associates with histone proteins to form nucleosomes. Nucleosomes provide a basis for genome compaction, epigenetic markup, and mediate interactions of nuclear proteins with their target DNA loci. A negatively charged (acidic) patch located on the H2A-H2B histone dimer is a characteristic feature of the nucleosomal surface. The acidic patch is a common site in the attachment of various chromatin proteins, including viral ones. Acidic patch-binding peptides present perspective compounds that can be used to modulate chromatin functioning by disrupting interactions of nucleosomes with natural proteins or alternatively targeting artificial moieties to the nucleosomes, which may be beneficial for the development of new therapeutics. In this work, we used several computational and experimental techniques to improve our understanding of how peptides may bind to the acidic patch and what are the consequences of their binding. Through extensive analysis of the PDB database, histone sequence analysis, and molecular dynamic simulations, we elucidated common binding patterns and key interactions that stabilize peptide-nucleosome complexes. Through MD simulations and FRET measurements, we characterized changes in nucleosome dynamics conferred by peptide binding. Using fluorescence polarization and gel electrophoresis, we evaluated the affinity and specificity of the LANA1-22 peptide to DNA and nucleosomes. Taken together, our study provides new insights into the different patterns of intermolecular interactions that can be employed by natural and designed peptides to bind to nucleosomes, and the effects of peptide binding on nucleosome dynamics and stability.

EasyModel: a user-friendly web-based interface based on MODELLER

Three-dimensional protein structures are invaluable sources of information for the functional annotation of protein molecules. Describing the function of a protein sequence is one of the most common problems in biology. Generally, this problem can be facilitated by studying the tertiary structure of proteins. In the lack of protein structures, comparative modeling often provides a useful three-dimensional model of the protein associated with at least one known protein structure. Comparative modeling predicts the tertiary structure of a certain protein sequence (target) mainly based on its homological sequence to the sequence of one or more proteins with known structures (templates). MODELLER is one of the most widely used tools for homology or comparative modeling of three-dimensional protein structures. However, most users find it challenging to start with MODELLER as it is a command line based and requires knowledge of basic Python scripting to use it efficiently. In this study, a web-based interface has been designed to predict the tertiary structure of proteins based on Modeller, which does the comparative modeling automatically, and uses PHP and Python programming languages. This tool is called "EasyModel" and is available at http://bioinf.modares.ac.ir/software/easymodel/ . EasyModel provides a straightforward graphical interface for Modeller that can be used in only one browser.

The Southern European Atlantic Diet and Its Supplements: The Chemical Bases of Its Anticancer Properties

Scientific evidence increasingly supports the strong link between diet and health, acknowledging that a well-balanced diet plays a crucial role in preventing chronic diseases such as obesity, diabetes, cardiovascular issues, and certain types of cancer. This perspective opens the door to developing precision diets, particularly tailored for individuals at risk of developing cancer. It encompasses a vast research area and involves the study of an expanding array of compounds with multilevel "omics" compositions, including genomics, transcriptomics, proteomics, epigenomics, miRNomics, and metabolomics. We review here the components of the Southern European Atlantic Diet (SEAD) from both a chemical and pharmacological standpoint. The information sources consulted, complemented by crystallographic data from the Protein Data Bank, establish a direct link between the SEAD and its anticancer properties. The data collected strongly suggest that SEAD offers an exceptionally healthy profile, particularly due to the presence of beneficial biomolecules in its foods. The inclusion of olive oil and paprika in this diet provides numerous health benefits, and scientific evidence supports the anticancer properties of dietary supplements with biomolecules sourced from vegetables of the brassica genus. Nonetheless, further research is warranted in this field to gain deeper insights into the potential benefits of the SEAD's bioactive compounds against cancer.

Simulating structurally variable nuclear pore complexes for microscopy

MOTIVATION

The nuclear pore complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and an important reference standard in microscopy: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudoatomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single-molecule localization microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability. However, the true picture of this variability is unknown. In quantitative image analysis experiments, it is thus difficult to distinguish intrinsically high SMLM noise from variability of the underlying structure.

RESULTS

We introduce CIR4MICS ('ceramics', Configurable, Irregular Rings FOR MICroscopy Simulations), a pipeline that synthesizes ground truth datasets of structurally variable NPCs based on architectural models of the true NPC. Users can select one or more N- or C-terminally tagged NPC proteins, and simulate a wide range of geometric variations. We also represent the NPC as a spring-model such that arbitrary deforming forces, of user-defined magnitudes, simulate irregularly shaped variations. Further, we provide annotated reference datasets of simulated human NPCs, which facilitate a side-by-side comparison with real data. To demonstrate, we synthetically replicate a geometric analysis of real NPC radii and reveal that a range of simulated variability parameters can lead to observed results. Our simulator is therefore valuable to test the capabilities of image analysis methods, as well as to inform experimentalists about the requirements of hypothesis-driven imaging studies.

AVAILABILITY AND IMPLEMENTATION

Code: https://github.com/uhlmanngroup/cir4mics. Simulated data: BioStudies S-BSST1058.

Clustering predicted structures at the scale of the known protein universe

Proteins are key to all cellular processes and their structure is important in understanding their function and evolution. Sequence-based predictions of protein structures have increased in accuracy1, and over 214 million predicted structures are available in the AlphaFold database2. However, studying protein structures at this scale requires highly efficient methods. Here, we developed a structural-alignment-based clustering algorithm-Foldseek cluster-that can cluster hundreds of millions of structures. Using this method, we have clustered all of the structures in the AlphaFold database, identifying 2.30 million non-singleton structural clusters, of which 31% lack annotations representing probable previously undescribed structures. Clusters without annotation tend to have few representatives covering only 4% of all proteins in the AlphaFold database. Evolutionary analysis suggests that most clusters are ancient in origin but 4% seem to be species specific, representing lower-quality predictions or examples of de novo gene birth. We also show how structural comparisons can be used to predict domain families and their relationships, identifying examples of remote structural similarity. On the basis of these analyses, we identify several examples of human immune-related proteins with putative remote homology in prokaryotic species, illustrating the value of this resource for studying protein function and evolution across the tree of life.

PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams

In this article, we present PoseEdit, a new, interactive frontend of the popular pose visualization tool PoseView. PoseEdit automatically produces high-quality 2D diagrams of intermolecular interactions in 3D binding sites calculated from ligands in complex with protein, DNA, and RNA. The PoseView diagrams have been improved in several aspects, most notably in their interactivity. Thanks to the easy-to-use 2D editor of PoseEdit, the diagrams are extensively editable and extendible by the user, can be merged with other diagrams, and even be created from scratch. A large variety of graphical objects in the diagram can be moved, rotated, selected and highlighted, mirrored, removed, or even newly added. Furthermore, PoseEdit enables a synchronized 2D-3D view of macromolecule-ligand complexes simplifying the analysis of structural features and interactions. The representation of individual diagram objects regarding their visualized chemical properties, like stereochemistry, and general graphical styles, like the color of interactions, can additionally be edited. The primary objective of PoseEdit is to support scientists with an enhanced way to communicate ligand binding mode information through graphical 2D representations optimized with the scientist's input in accordance with objective criteria and individual needs. PoseEdit is freely available on the ProteinsPlus web server ( https://proteins.plus ).

Fluconazole-Induced Protein Changes in Osteogenic and Immune Metabolic Pathways of Dental Pulp Mesenchymal Stem Cells of Osteopetrosis Patients

Osteopetrosis is a rare inherited disease caused by osteoclast failure, resulting in increasing bone density in humans. Patients with osteopetrosis possess several dental and cranial complications. Since carbonic anhydrase II (CA-II) deficiency is a major cause of osteopetrosis, CA-II activators might be an attractive potential treatment option for osteopetrosis patients. We conducted comprehensive label-free quantitative proteomics analysis on Fluconazole-treated Dental Pulp Mesenchymal Stem/Stromal Cells from CA-II-Deficient Osteopetrosis Patients. We identified 251 distinct differentially expressed proteins between healthy subjects, as well as untreated and azole-treated derived cells from osteopetrosis patients. Twenty-six (26) of these proteins were closely associated with osteogenesis and osteopetrosis disease. Among them are ATP1A2, CPOX, Ap2 alpha, RAP1B and some members of the RAB protein family. Others include AnnexinA1, 5, PYGL, OSTF1 and PGAM4, all interacting with OSTM1 in the catalytic reactions of HCO3 and the Cl- channel via CAII regulation. In addition, the pro-inflammatory/osteoclast regulatory proteins RACK1, MTSE, STING1, S100A13, ECE1 and TRIM10 are involved. We have identified proteins involved in osteogenic and immune metabolic pathways, including ERK 1/2, phosphatase and ATPase, which opens the door for some CA activators to be used as an alternative drug therapy for osteopetrosis patients. These findings propose that fluconazole might be a potential treatment agent for CAII- deficient OP patients. Altogether, our findings provide a basis for further work to elucidate the clinical utility of azole, a CA activator, as a therapeutic for OP.

DockSurf: A Molecular Modeling Software for the Prediction of Protein/Surface Adhesion

The elucidation of structural interfaces between proteins and inorganic surfaces is a crucial aspect of bionanotechnology development. Despite its significance, the interfacial structures between proteins and metallic surfaces are yet to be fully understood, and the lack of experimental investigation has impeded the development of many devices. To overcome this limitation, we suggest considering the generation of protein/surface structures as a molecular docking problem with a homogenous plan as the target. To this extent, we propose a new software, DockSurf, which aims to quickly propose reliable protein/surface structures. Our approach considers the conformational exploration with Euler's angles, which provide a cartography instead of a unique structure. Interaction energies were derived from quantum mechanics computations for a set of small molecules that describe protein atom types and implemented in a Derjaguin, Landau, Verwey, and Overbeek potential for the consideration of large systems such as proteins. The validation of DockSurf software was conducted with molecular dynamics for corona proteins with gold surfaces and provided enthusiastic results. This software is implemented in the RPBS platform to facilitate widespread access to the scientific community.

Metasurfaces-Driven Hyperspectral Imaging via Multiplexed Plasmonic Resonance Energy Transfer

Obtaining single-molecular-level fingerprints of biomolecules and electron-transfer dynamic imaging in living cells are critically demanded in postgenomic life sciences and medicine. However, the possible solution called plasmonic resonance energy transfer (PRET) spectroscopy remains challenging due to the fixed scattering spectrum of a plasmonic nanoparticle and limited multiplexing. Here, multiplexed metasurfaces-driven PRET hyperspectral imaging, to probe biological light-matter interactions, is reported. Pixelated metasurfaces with engineered scattering spectra are first designed over the entire visible range by the precision nanoengineering of gap plasmon and grating effects of metasurface clusters. Pixelated metasurfaces are created and their full dark-field coloration is optically characterized with visible color palettes and high-resolution color printings of the art pieces. Furthermore, three different biomolecules (i.e., chlorophyll a, chlorophyll b, and cytochrome c) are applied on metasurfaces for color palettes to obtain selective molecular fingerprint imaging due to the unique biological light-matter interactions with application-specific biomedical metasurfaces. This metasurface-driven PRET hyperspectral imaging will open up a new path for multiplexed real-time molecular sensing and imaging methods.

Nitric oxide-mediated S-nitrosylation of IAA17 protein in intrinsically disordered region represses auxin signaling

The phytohormone auxin plays crucial roles in nearly every aspect of plant growth and development. Auxin signaling is activated through the phytohormone-induced proteasomal degradation of the Auxin/INDOLE-3-ACETIC ACID (Aux/IAA) family of transcriptional repressors. Notably, many auxin-modulated physiological processes are also regulated by nitric oxide (NO) that executes its biological effects predominantly through protein S-nitrosylation at specific cysteine residues. However, little is known about the molecular mechanisms in regulating the interactive NO and auxin networks. Here, we show that NO represses auxin signaling by inhibiting IAA17 protein degradation. NO induces the S-nitrosylation of Cys-70 located in the intrinsically disordered region of IAA17, which inhibits the TIR1-IAA17 interaction and consequently the proteasomal degradation of IAA17. The accumulation of a higher level of IAA17 attenuates auxin response. Moreover, an IAA17C70W nitrosomimetic mutation renders the accumulation of a higher level of the mutated protein, thereby causing partial resistance to auxin and defective lateral root development. Taken together, these results suggest that S-nitrosylation of IAA17 at Cys-70 inhibits its interaction with TIR1, thereby negatively regulating auxin signaling. This study provides unique molecular insights into the redox-based auxin signaling in regulating plant growth and development.

iORandLigandDB: A Website for Three-Dimensional Structure Prediction of Insect Odorant Receptors and Docking with Odorants

The use of insect-specific odorants to control the behavior of insects has always been a hot spot in research on "green" control strategies of insects. However, it is generally time-consuming and laborious to explore insect-specific odorants with traditional reverse chemical ecology methods. Here, an insect odorant receptor (OR) and ligand database website (iORandLigandDB) was developed for the specific exploration of insect-specific odorants by using deep learning algorithms. The website provides a range of specific odorants before molecular biology experiments as well as the properties of ORs in closely related insects. At present, the existing three-dimensional structures of ORs in insects and the docking data with related odorants can be retrieved from the database and further analyzed.

Clinical Characteristics and Genetic Analyses of Patients with Idiopathic Hypogonadotropic Hypogonadism

Objective

Idiopathic hypogonadotropic hypogonadism (IHH) is classified into two groups-Kalman syndrome and normosmic IHH (nIHH). Half of all cases can be explained by mutations in >50 genes. Targeted gene panel testing with nexrt generation sequencing (NGS) is required for patients without typical phenotypic findings. The aim was to determine the genetic etiologies of patients with IHH using NGS, including 54 IHH-associated genes, and to present protein homology modeling and protein stability analyzes of the detected variations.

Methods

Clinical and demographic data of 16 patients (eight female), aged between 11.6-17.8 years, from different families were assessed. All patients were followed up for a diagnosis of nIHH, had normal cranial imaging, were without anterior pituitary hormone deficiency other than gonadotropins, had no sex chromosome anomaly, had no additional disease, and underwent genetic analysis with NGS between the years 2008-2021. Rare variants were classified according to the variant interpretation framework of the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology. Changes in protein structure caused by variations were modeled using RoseTTAFold and changes in protein stability resulting from variation were analyzed.

Results

Half of the 16 had no detectable variation. Three (18.75%) had a homozygous (pathogenic) variant in the GNRHR gene, one (6.25%) had a compound heterozygous [likely pathogenic-variants of uncertain significance (VUS)] variant in PROK2 and four (25%) each had a heterozygous (VUS) variant in HESX1, FGF8, FLRT3 and DMXL2. Protein models showed that variants interpreted as VUS according to ACMG could account for the clinical IHH.

Conclusion

The frequency of variation detection was similar to the literature. Modelling showed that the variant in five different genes, interpreted as VUS according to ACMG, could explain the clinical IHH.

GS-SMD server for steered molecular dynamics of peptide substrates in the active site of the γ-secretase complex

Despite recent advances in research, the mechanism of Alzheimer's disease is not fully understood yet. Understanding the process of cleavage and then trimming of peptide substrates, can help selectively block γ-secretase (GS) to stop overproduction of the amyloidogenic products. Our GS-SMD server (https://gs-smd.biomodellab.eu/) allows cleaving and unfolding of all currently known GS substrates (more than 170 peptide substrates). The substrate structure is obtained by threading of the substrate sequence into the known structure of GS complex. The simulations are performed in an implicit water-membrane environment so they are performed rather quickly, 2-6 h per job, depending on the mode of calculations (part of GS complex or the whole structure). It is also possible to introduce mutations to the substrate and GS and pull any part of the substrate in any direction using the steered molecular dynamics (SMD) simulations with constant velocity. The obtained trajectories are visualized and analyzed in the interactive way. One can also compare multiple simulations using the interaction frequency analysis. GS-SMD server can be useful for revealing mechanisms of substrate unfolding and role of mutations in this process.

KVFinder-web: a web-based application for detecting and characterizing biomolecular cavities

Molecular interactions that modulate catalytic processes occur mainly in cavities throughout the molecular surface. Such interactions occur with specific small molecules due to geometric and physicochemical complementarity with the receptor. In this scenario, we present KVFinder-web, an open-source web-based application of parKVFinder software for cavity detection and characterization of biomolecular structures. The KVFinder-web has two independent components: a RESTful web service and a web graphical portal. Our web service, KVFinder-web service, handles client requests, manages accepted jobs, and performs cavity detection and characterization on accepted jobs. Our graphical web portal, KVFinder-web portal, provides a simple and straightforward page for cavity analysis, which customizes detection parameters, submits jobs to the web service component, and displays cavities and characterizations. We provide a publicly available KVFinder-web at https://kvfinder-web.cnpem.br, running in a cloud environment as docker containers. Further, this deployment type allows KVFinder-web components to be configured locally and customized according to user demand. Hence, users may run jobs on a locally configured service or our public KVFinder-web.

The LightDock Server: Artificial Intelligence-powered modeling of macromolecular interactions

Computational docking is an instrumental method of the structural biology toolbox. Specifically, integrative modeling software, such as LightDock, arise as complementary and synergetic methods to experimental structural biology techniques. Ubiquitousness and accessibility are fundamental features to promote ease of use and to improve user experience. With this goal in mind, we have developed the LightDock Server, a web server for the integrative modeling of macromolecular interactions, along with several dedicated usage modes. The server builds upon the LightDock macromolecular docking framework, which has proved useful for modeling medium-to-high flexible complexes, antibody-antigen interactions, or membrane-associated protein assemblies. We believe that this free-to-use resource will be a valuable addition to the structural biology community and can be accessed online at: https://server.lightdock.org/.

PAE viewer: a webserver for the interactive visualization of the predicted aligned error for multimer structure predictions and crosslinks

The development of AlphaFold for protein structure prediction has opened a new era in structural biology. This is even more the case for AlphaFold-Multimer for the prediction of protein complexes. The interpretation of these predictions has become more important than ever, but it is difficult for the non-specialist. While an evaluation of the prediction quality is provided for monomeric protein predictions by the AlphaFold Protein Structure Database, such a tool is missing for predicted complex structures. Here, we present the PAE Viewer webserver (http://www.subtiwiki.uni-goettingen.de/v4/paeViewerDemo), an online tool for the integrated visualization of predicted protein complexes using a 3D structure display combined with an interactive representation of the Predicted Aligned Error (PAE). This metric allows an estimation of the quality of the prediction. Importantly, our webserver also allows the integration of experimental cross-linking data which helps to interpret the reliability of the structure predictions. With the PAE Viewer, the user obtains a unique online tool which for the first time allows the intuitive evaluation of the PAE for protein complex structure predictions with integrated crosslinks.

To Target or Not to Target Schistosoma mansoni Cyclic Nucleotide Phosphodiesterase 4A?

Schistosomiasis is a neglected tropical disease with high morbidity. Recently, the Schistosoma mansoni phosphodiesterase SmPDE4A was suggested as a putative new drug target. To support SmPDE4A targeted drug discovery, we cloned, isolated, and biochemically characterized the full-length and catalytic domains of SmPDE4A. The enzymatically active catalytic domain was crystallized in the apo-form (PDB code: 6FG5) and in the cAMP- and AMP-bound states (PDB code: 6EZU). The SmPDE4A catalytic domain resembles human PDE4 more than parasite PDEs because it lacks the parasite PDE-specific P-pocket. Purified SmPDE4A proteins (full-length and catalytic domain) were used to profile an in-house library of PDE inhibitors (PDE4NPD toolbox). This screening identified tetrahydrophthalazinones and benzamides as potential hits. The PDE inhibitor NPD-0001 was the most active tetrahydrophthalazinone, whereas the approved human PDE4 inhibitors roflumilast and piclamilast were the most potent benzamides. As a follow-up, 83 benzamide analogs were prepared, but the inhibitory potency of the initial hits was not improved. Finally, NPD-0001 and roflumilast were evaluated in an in vitro anti-S. mansoni assay. Unfortunately, both SmPDE4A inhibitors were not effective in worm killing and only weakly affected the egg-laying at high micromolar concentrations. Consequently, the results with these SmPDE4A inhibitors strongly suggest that SmPDE4A is not a suitable target for anti-schistosomiasis therapy.

Self-Assembly-Driven Bi2S3 Nanobelts Integrated a Silk-Fibroin-Based 3D-Printed Aerogel-Based Scaffold with a Dual-Network Structure for Photothermal Bone Cancer Therapy

Multifunctional all-in-one biomaterial combining the therapeutic and regeneration functionalities for successive tumor therapy and tissue regeneration is in high demand in interdisciplinary research. In this study, a three-dimensional (3D) aerogel-based composite scaffold with a dual-network structure generated through self-assembly and photo-cross-linking with combined properties of photothermally triggered controlled anticancer drug release and photothermal cancer cell ablation was successfully fabricated. The fabrication of composites consists of self-assembly of a silk fibroin methacrylate (SF-MA) biopolymer incorporated with hydrothermally driven bismuth sulfide (Bi₂S₃) methacrylate nanobelts, followed by a photo-cross-linking-assisted 3D-printing process. The developed scaffolds presented hierarchically organized porosity and excellent photothermal conversion thanks to the strong near-infrared (NIR) photon absorption of incorporated Bi₂S₃ nanobelts inside the scaffold matrix. The heat generated in the scaffold mediated by laser irradiation has not only triggered controlled and prolonged release of the anticancer drug but also significantly ablated the bone cancer cells adhered on the scaffold. In addition, the developed 3D composite scaffolds have demonstrated excellent biodegradability for organic and inorganic network constituents at different media, enabling them as potential implants to be replaced by de novo tissue. In combination of chemotherapy and photothermal therapy, the multifunctional 3D-printed composite aerogel scaffold is expected to be an excellent implantable material in bone tissue engineering (BTE) for successive cancer therapy and tissue regeneration.

Exploring the target and molecular mechanism of Astragalus membranaceus in the treatment of vascular cognitive impairment based on network pharmacology and molecular docking

Astragalus membranaceus (AM) is a traditional Chinese herbal medicine extensively utilized in vascular cognitive impairment (VCI) treatment. However, due to the complex components of AM, its exact molecular mechanism remains unclear. Therefore, this study investigated the target and molecular mechanism of AM to treat VCI based on network pharmacology and molecular docking. Firstly, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, STITCH, and SwissTargetPrediction were utilized to gather the primary active ingredients of AM. The potential therapeutic targets of VCI were collected through GeneCards, OMIM, and DisGeNET databases. Secondly, the protein-protein interaction network was built using the STRING database. The enrichment analysis of gene ontology and the Kyoto Encyclopedia of Genes and Genome pathways was carried out in the R language. Finally, The network topology calculation of Cytoscape software was combined with module analysis to predict the binding properties of its active ingredients and targets. Twenty effective compounds and 733 targets were screened from AM, among which 158 targets were seen as possible targets of AM to treat VCI. MAPK3 and MMP9 were the critical targets of AM intervention in VCI. The crucial pathways include PI3K/Akt, MAPK, Rap1, and Ras signaling pathways. Besides, calycosin and quercetin might be the potential active compounds of AM for VCI treatment. AM intervenes in VCI through a multi-ingredient, multi-target, and multi-pathway coordination mechanism. These findings provide a foundation for a deeper understanding of the molecular mechanisms by which AM is effective in treating VCI.

Biallelic TLR4 deficiency in humans

BACKGROUND

Toll-like receptors (TLRs) mediate functions for host defense and inflammatory responses. TLR4 recognizes LPS, a component of gram-negative bacteria as well as host-derived endogenous ligands such as S100A8 and S100A9 proteins.

OBJECTIVE

We sought to report phenotype and cellular function of individuals with complete TLR4 deficiency.

METHODS

We performed genome sequencing and investigated exome and genome sequencing databases. Cellular responses were studied on primary monocytes, macrophages, and neutrophils, as well as cell lines using flow cytometry, reporter, and cytokine assays.

RESULTS

We identified 2 individuals in a family of Qatari origin carrying a homozygous stop codon variant p.Q188X in TLR4 presenting with a variable phenotype (asymptomatic and inflammatory bowel disease consistent with severe perianal Crohn disease). A third individual with homozygous p.Y794X was identified in a population database. In contrast to hypomorphic polymorphisms p.D299G and p.T399I, the variants p.Q188X and p.Y794X completely abrogated LPS-induced cytokine responses whereas TLR2 response was normal. TLR4 deficiency causes a neutrophil CD62L shedding defect, whereas antimicrobial activity toward intracellular Salmonella was intact.

CONCLUSIONS

Biallelic TLR4 deficiency in humans causes an inborn error of immunity in responding to LPS. This complements the spectrum of known primary immunodeficiencies, in particular myeloid differentiation primary response 88 (MYD88) or the IL-1 receptor-associated kinase 4 (IRAK4) deficiency that are downstream of TLR4 and TLR2 signaling.

Genetic determinants of host tropism in Klebsiella phages

Bacteriophages play key roles in bacterial ecology and evolution and are potential antimicrobials. However, the determinants of phage-host specificity remain elusive. Here, we isolate 46 phages to challenge 138 representative clinical isolates of Klebsiella pneumoniae, a widespread opportunistic pathogen. Spot tests show a narrow host range for most phages, with <2% of 6,319 phage-host combinations tested yielding detectable interactions. Bacterial capsule diversity is the main factor restricting phage host range. Consequently, phage-encoded depolymerases are key determinants of host tropism, and depolymerase sequence types are associated with the ability to infect specific capsular types across phage families. However, all phages with a broader host range found do not encode canonical depolymerases, suggesting alternative modes of entry. These findings expand our knowledge of the complex interactions between bacteria and their viruses and point out the feasibility of predicting the first steps of phage infection using bacterial and phage genome sequences.

Constructing hollow ZIF-8/CDs@MIPs fluorescent sensor from Osmanthus leaves to specifically recognize bovine hemoglobin

To develop non-toxic, highly efficient and selective fluorescence sensors was a significance research. In this work, a novel hollow fluorescence sensor was designed with biomass carbon dots (CDs), ZIF-8 and molecularly imprinted polymers (MIPs) via aqueous polymerization. The results demonstrated such unique structure fluorescence sensor exhibited fast response time, excellent stability and highly selectively towards bovine hemoglobin (BHb). Even in a complex environment, the hollow fluorescence sensor (H-ZIF-8/CDs@MIPs) still has a good recognition effect on BHb. Under an optimized condition, the hollow fluorescence sensor was quenched linearly with BHb concentration in the range of 0.058-4.5 μM with the detection limit of 15.6 nM. In addition, a possible quenching mechanism of hollow fluorescence towards BHb was confirmed resonance energy transfer (FRET). In the actual application process, the hollow fluorescence sensor showed a better detection performance towards BHb with the recoveries ranged of 98.6-101.1 %. This work provided a strategy to design green and unique hollow fluorescence sensor for practical application.

Network pharmacology integrated with experimental validation to explore the therapeutic role and potential mechanism of Epimedium for spinal cord injury

Objective

Epimedium (EPI) is a common Chinese herb with neuroprotective effects against a variety of central nervous system disorders, especially spinal cord injury (SCI). In this study, we performed network pharmacology and molecular docking analyses to reveal the mechanism underlying EPI treatment of SCI, then validated its efficacy using animal models.

Methods

The active ingredients and targets of EPI were screened by Traditional Chinese Medicine Systems Pharmacology (TCMSP) and their targets annotated on the UniProt platform. SCI-related targets were searched from OMIM, TTD, and GeneCards databases. We employed the STRING platform to construct a protein-protein interaction (PPI) network then visualized the results using Cytoscape (3.8.2) software. We also subjected key EPI targets to ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, then docked the main active ingredients with the key targets. Finally, we established an SCI rat model to evaluate efficacy of EPI in treating SCI and validate the effects of different biofunctional modules predicted by network pharmacology.

Results

A total of 133 EPI targets were associated with SCI. GO terms and KEGG pathway enrichment results showed that EPI's effect in treating SCI was significantly associated with inflammatory response, oxidative stress and the PI3K/AKT signaling pathway. Molecular docking results indicated that EPI's active ingredients have a high affinity for the key targets. Results from animal experiments revealed that EPI not only markedly improved Basso, Beattie, and Bresnahan scores in SCI rats, but also significantly improved p-PI3K/PI3K and p-AKT/AKT ratio. Moreover, EPI treatment not only mediated a significant decrease in malondialdehyde (MDA) but also increased both superoxide dismutase (SOD), and glutathione (GSH). However, this phenomenon was successfully reversed by LY294002, a PI3K inhibitor.

Conclusion

EPI improves behavioral performance in SCI rats through anti-oxidative stress, which may be mediated by activation of the PI3K/AKT signaling pathway.

GABAA and serotonergic receptors participation in anxiolytic effect of chalcones in adult zebrafish

The prevalence of anxiety is a significant public health problem, being the 24th leading cause of disability in individuals affected by this disorder. In this context, chalcones, a flavonoid subclass obtained from natural or synthetic sources, interact with central nervous system (CNS) receptors at the same binding site as benzodiazepines, the primary drugs used in the treatment of anxiety. Thus, our study investigates the anxiolytic effect of synthetic chalcones derived from the natural product 2-hydroxy-3,4,6-trimethoxyacetophenone isolated from Croton anisodontus Müll.Arg. in modulating anxiolytic activity via GABAergic and serotoninergic neurotransmission in an adult zebrafish model. Chalcones 1 and 2 were non-toxic to adult zebrafish and showed anxiolytic activity via GABAA receptors. Chalcone 2 also had its anxiolytic action reversed by the antagonist granisetron, indicating the participation of serotonergic receptors 5HTR3A/3B in the anxiolytic effect. In addition, molecular docking results showed that chalcones have a higher affinity for the GABAA receptor than DZP and binding in the same region of the DZP binding site, indicating a similar effect to the drug. Furthermore, the interaction of chalcones with GABAA and 5-HT3A receptors demonstrates the anxiolytic effect potential of these molecules.Communicated by Ramaswamy H. Sarma.