Molecular Binding Sites Research Articles

Molecular tumor board: molecularly adjusted therapy upon identification and functional validation of a novel ALK resistance mutation in a case of lung adenocarcinoma.

We report a case of a long-term surviving patient with EML4/ALK translocated non-small cell adenocarcinoma of the lung in UICC8 stage IVA. During recurrence under continuous crizotinib therapy, a hitherto insufficiently characterized missense mutation in the ALK gene (Arg1181His) was identified through targeted sequencing. The aforementioned EML4/ALK translocation could still be detected in this situation. Employing a 3D reconstruction of the ALK tertiary structure, considering its interaction with various ALK inhibitors at the molecular binding site, our analysis indicated the presence of a mutation associated with crizotinib resistance. To validate the biological relevance of this previously unknown mutation, we carried out an in vitro validation approach in cell culture in addition to the molecular diagnostics accompanied by the molecular tumor board. The tumor scenario was mimicked through retroviral transfection. Our comparative in vitro treatment regimen paired with the clinical trajectory of the patient, corroborated our initial clinical and biochemical suspicions. Our approach demonstrates preclinical, in silico, and clinical evidence of a novel crizotinib resistance mutation in ALK as well as sensitivity toward brigatinib and potentially lorlatinib. In future cases, this procedure represents an important contribution to functional diagnostics in the context of molecular tumor boards.

Network pharmacology and in vivo experiment-based strategy for investigating the mechanism of chronic prostatitis/chronic pelvic pain syndrome in QianLieJinDan tablets

BackgroundChronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common urinary system disease that is prone to recurrence. It typically leads to varying degrees of pelvic pain and discomfort, as well as symptoms related to the urinary system in affected patients. QianLieJinDan tablets (QLJD), a traditional Chinese medicine, have shown promising therapeutic effects on CP/CPPS in clinical practice, but the underlying mechanisms of QLJD in treating CP/CPPS have not been determined. ObjectiveTo reveal the phytochemical characterization and multitarget mechanism of QLJD on CP/CPPS. MethodsThe concentrations of the components of QLJD were determined using UHPLC-Q Exactive Orbitrap-MS. Utilizing network pharmacology approaches, the potential components, targets, and pathways involved in the treatment of CP/CPPS caused by QLJD were screened. Molecular docking calculations were employed to assess the affinity between the components of the QLJD and potential targets, revealing the optimal molecular conformation and binding site. Finally, the therapeutic efficacy and potential underlying mechanisms of QLJD were investigated through pharmacological experiments. ResultsIn this study, a total of 35 components targeting 29 CP-related genes were identified, among which quercetin, baicalin, icariin, luteolin, and gallic acid were the major constituents. Enrichment analysis revealed that the potential targets were involved mainly in the regulation of cytokines, cell proliferation and apoptosis, and the oxidative stress response and were primarily associated with the cytokine‒cytokine receptor interaction pathway, the IL-17 signaling pathway, the Th17 cell differentiation pathway, and the JAK-STAT signaling pathway. In vivo experiments demonstrated that QLJD effectively attenuated the infiltration of CD3+ T cells and the expression of ROS in a CP/CPPS model rat prostate tissue. Furthermore, through the inhibition of IL-6 and STAT3 expression, QLJD reduced the differentiation of Th17 cells, thereby ameliorating pathological injury and prostatic index in prostate tissue. ConclusionThe potential of QLJD as an anti-CP/CPPS agent lies in its ability to interfere with the expression of IL-6 and STAT3, inhibit Th17 cell differentiation, reduce inflammatory cell infiltration in rat prostate tissue, and alleviate oxidative stress damage through its multi-component, multi-target, and multi-pathway effects.

Molecular docking and dynamics simulation studies uncover the host-pathogen protein-protein interactions in Penaeus vannamei and Vibrio parahaemolyticus.

Shrimp aquaculture contributes significantly to global economic growth, and the whiteleg shrimp, Penaeus vannamei, is a leading species in this industry. However, Vibrio parahaemolyticus infection poses a major challenge in ensuring the success of P. vannamei aquaculture. Despite its significance in this industry, the biological knowledge of its pathogenesis remains unclear. Hence, this study was conducted to identify the interaction sites and binding affinity between several immune-related proteins of P. vannamei with V. parahaemolyticus proteins associated with virulence factors. Potential interaction sites and the binding affinity between host and pathogen proteins were identified using molecular docking and dynamics (MD) simulation. The P. vannamei-V. parahaemolyticus protein-protein interaction of Complex 1 (Ferritin-HrpE/YscL family type III secretion apparatus protein), Complex 2 (Protein kinase domain-containing protein-Chemotaxis CheY protein), and Complex 3 (GPCR-Chemotaxis CheY protein) was found to interact with -4319.76, -5271.39, and -4725.57 of the docked score and the formation of intermolecular bonds at several interacting residues. The docked scores of Complex 1, Complex 2, and Complex 3 were validated using MD simulation analysis, which revealed these complexes greatly contribute to the interactions between P. vannamei and V. parahaemolyticus proteins, with binding free energies of -22.50 kJ/mol, -30.20 kJ/mol, and -26.27 kJ/mol, respectively. This finding illustrates the capability of computational approaches to search for molecular binding sites between host and pathogen, which could increase the knowledge of Vibrio spp. infection on shrimps, which then can be used to assist in the development of effective treatment.

Evaluation of Myocilin Variant Protein Structures Modeled by AlphaFold2.

Deep neural network-based programs can be applied to protein structure modeling by inputting amino acid sequences. Here, we aimed to evaluate the AlphaFold2-modeled myocilin wild-type and variant protein structures and compare to the experimentally determined protein structures. Molecular dynamic and ligand binding properties of the experimentally determined and AlphaFold2-modeled protein structures were also analyzed. AlphaFold2-modeled myocilin variant protein structures showed high similarities in overall structure to the experimentally determined mutant protein structures, but the orientations and geometries of amino acid side chains were slightly different. The olfactomedin-like domain of the modeled missense variant protein structures showed fewer folding changes than the nonsense variant when compared to the predicted wild-type protein structure. Differences were also observed in molecular dynamics and ligand binding sites between the AlphaFold2-modeled and experimentally determined structures as well as between the wild-type and variant structures. In summary, the folding of the AlphaFold2-modeled MYOC variant protein structures could be similar to that determined by the experiments but with differences in amino acid side chain orientations and geometries. Careful comparisons with experimentally determined structures are needed before the applications of the in silico modeled variant protein structures.

Enhancing encapsulation of curcumin by pH-driven and sodium alginate blending with ovalbumin as a carrier

Curcumin is a hydrophobic polyphenol with various health benefits, but its poor water solubility and stability limit its application in the food and pharmaceutical industries. In this study, a pH-driven method was developed to prepare ovalbumin (OVA)-curcumin nanocomplexes without organic solvents, reducing the environmental impact. The results showed that curcumin was encapsulated in OVA with a high efficiency of over 95% and remained in an amorphous state within the protein molecules. Molecular docking and spectroscopic analyses revealed that curcumin was mainly bound and stabilized by hydrogen bonds and hydrophobic interactions in the hydrophobic core of OVA. The binding strength of the intermediate stage of the pH-driven method was stronger than that of the final stage, due to the exposure of OVA molecular binding sites and the involvement of electrostatic attraction. Furthermore, the potential of polysaccharide blending to enhance the stability of the nanocomplexes was investigated. The results showed that sodium alginate effectively enhanced the photostability and thermal stability of the OVA-curcumin nanocomplexes by co-solubilization and electrostatic complex formation. In addition, simulated in vitro digestion also demonstrated that the pH-driven method combined with polysaccharide blending increased the bioaccessibility of curcumin in nanocomplexes from 17.79% to 52.54%. Therefore, the pH-driven method coupled with polysaccharide blending ensures the encapsulation and stabilization of hydrophobic bioactive substances for use in their delivery systems to improve bioaccessibility.

Crystal Engineering of a Chiral Crystalline Sponge That Enables Absolute Structure Determination and Enantiomeric Separation.

Chiral metal-organic materials (CMOMs), can offer molecular binding sites that mimic the enantioselectivity exhibited by biomolecules and are amenable to systematic fine-tuning of structure and properties. Herein, we report that the reaction of Ni(NO3)2, S-indoline-2-carboxylic acid (S-IDECH), and 4,4'-bipyridine (bipy) afforded a homochiral cationic diamondoid, dia, network, [Ni(S-IDEC)(bipy)(H2O)][NO3], CMOM-5. Composed of rod building blocks (RBBs) cross-linked by bipy linkers, the activated form of CMOM-5 adapted its pore structure to bind four guest molecules, 1-phenyl-1-butanol (1P1B), 4-phenyl-2-butanol (4P2B), 1-(4-methoxyphenyl)ethanol (MPE), and methyl mandelate (MM), making it an example of a chiral crystalline sponge (CCS). Chiral resolution experiments revealed enantiomeric excess, ee, values of 36.2-93.5%. The structural adaptability of CMOM-5 enabled eight enantiomer@CMOM-5 crystal structures to be determined. The five ordered crystal structures revealed that host-guest hydrogen-bonding interactions are behind the observed enantioselectivity, three of which represent the first crystal structures determined of the ambient liquids R-4P2B, S-4P2B, and R-MPE.

PO-01-206 MOLECULAR MODELING OF CLINICAL KCNJ2 MUTATIONS REVEALS STRUCTURE-FUNCTION IMPACT ON PIP2 BINDING SITE

Binding phosphatidylinositol 4,5-bisphosphate (PIP2) is essential for Kir2.1(encoded by KCNJ2), function. Disease associated KCNJ2 mutations, such as those associated with Andersen-Tawil Syndrome (ATS), may exert molecular dysfunction by interrupting PIP2 binding, however a full-length molecular model of Kir2.1 has not been developed to explore this hypothesis. Elucidate the molecular structure of Kir2.1 and determine the functional impact of clinical KCNJ2 mutations on PIP2 binding using experimental and improved molecular dynamic (MD) method. Whole-cell patch clamp experiments of WT-Kir2.1 and selected mutations were performed on stably transfected HEK293 cells using a standard protocol. A full-length Kir2.1 tetramer model (open and closed conformational states) based on Kir2.2 cryo-EM structure using MOE was created. Mutations (R67Q, G300D, R218L) were individually introduced to the channel, and a mutagenesis analysis was performed. Initially, MD simulation for 100ns was performed for wild-type (WT) and mutated structures (GROMACS software). We expanded the model to include +/- bound PIP2. Due to > 77% degree of homology of Kir2.2 (6m84) with Kir2.1, we developed a MD protocol with Kir2.2 as test system. The 2.5% free PIP2 molecules were released into the membrane and MD simulation was performed for 700ns using Amber software. Homomeric WT demonstrated normal Kir2.1 function while mutations G300D, R67Q, and R218L showed complete loss of function. Mutational analysis revealed that residue changes result in disruption of hydrogen bonding and affects the structural conformation at the residue sight and caused fluctuation of residues in other regions, i.e., selectivity filter and pore domain. The improved MD protocol validated Kir2.2 PIP2 binding sites. Moreover, we found mutation disruption of hydrogen bonds and hydrophobic interaction analysis between the channel and PIP2 molecules revealed significant structural changes. We developed the first full length MD model of Kir2.1 and found that ATS KCNJ2 mutations disrupt normal conformation and hydrogen bonding. Further, we validated PIP2 binding sites which illustrate the robustness of our method, and this technique can be applied to delineate Kir2.1 molecular PIP2 binding sites. Combined with experimental validation, our modeling will increase our understanding of structure-function relationships of KCNJ2 clinical mutations.

Exploring the active ingredients and potential mechanisms of action of sinomenium acutum in the treatment of rheumatoid arthritis based on systems biology and network pharmacology.

Objective: To investigate and predict the targets and signaling pathways of sinomenium acutum (SA) in the treatment of rheumatoid arthritis (RA) through systems biology and network pharmacology, and to elucidate its possible mechanisms of action. Methods: We screened the active ingredients and corresponding target proteins of SA in Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN); and obtained the targets of rheumatoid arthritis diseases in a database of gene-disease associations (DisGeNET), Online Mendelian Inheritance in Man (OMIM) database. The two targets were mapped by Venn diagram and the intersection was taken. The intersecting targets were used to construct protein-protein interaction (PPI) network maps in the String database, and Metascape was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Finally, the molecular docking technique was applied to validate and further clarify the core target of SA for the treatment of rheumatoid arthritis. Results: A total of six active ingredients and 217 potential targets were obtained after screening; 2,752 rheumatoid arthritis-related targets and 66 targets common to RA and SA. GO function and KEGG pathway enrichment analysis yielded 751 GO function entries (652 GO biological processes, 59 GO molecular functions and 40 GO cellular components) and 77 KEGG signaling pathways. It mainly involves pathways related to neural activity ligand-receptor interaction pathways, cancer pathways, calcium signaling channels, Th17 cell differentiation and others, which are mainly classified into four categories, including regulation of immunity, anti-inflammation, regulation of cell growth and apoptosis, and signaling. The molecular docking results showed that the binding energy of PTGS2, CASP3, JUN and PPARG to the key components beta-sitosterol, 16-epi-Isositsirikine, Sinomenine and Stepholidine were ≤ -6.5kcal/mol, suggesting the existence of molecular binding sites. Conclusion: SA acts on key targets such as PTGS2, CASP3, JUN, and PPARG to modulate signaling pathways such as neural activity ligand-receptor interaction, cancer, calcium ion, NF-κB, and Th17 cell differentiation to regulate immunity, anti-inflammation, modulation of cell cycle, bone metabolism, and signaling for the treatment of RA. It was also confirmed that the treatment of RA with SA has multi-component, multi-target, multi-pathway and multi-mechanism characteristics.

Rapid and Reversible Sensing Performance of Hydrogen-Substituted Graphdiyne.

The design of new nanomaterials for rapid and reversible detection of molecules in existence is critical for real-world sensing applications. Current nanomaterial libraries such as carbon nanotubes, graphene, MoS2, and MXene are fundamentally limited by their slow detection speed and small signals; thus, the atomic-level material design of molecular transport pathways and active binding sites must be accompanied. Herein, we fully explore the chemical and physical properties of a hydrogen-substituted graphdiyne (HsGDY) for its molecular sensing properties. This new carbon framework comprises reactive sp carbons in acetylenic linkages throughout the 16.3 Å nanopores and allows for detecting target molecules (e.g., H2) with an exceptionally high sensitivity (ΔR/Rb = 542%) and fast response/recovery time (τ90 = 8 s and τ10 = 38 s) even without any postmodification process. It possesses 2 orders of magnitude higher sensing ability than that of existing nanomaterial libraries. We demonstrate that rapid and reversible molecular binding is attributed to the cooperative interaction with adjacent double sp carbon in the layered nanoporous structure of HsGDY. This new class of carbon framework provides fundamental solutions for nanomaterials in reliable sensor applications that accelerate real-world interfacing.

1H, 13C, 15N Backbone and sidechain chemical shift assignments of the C-terminal domain of human UDP-glucuronosyltransferase 2B17 (UGT2B17-C).

UDP-glucuronosyltransferases are the principal enzymes involved in the glucuronidation of metabolites and xenobiotics for physiological clearance in humans. Though glucuronidation is an indispensable process in the phase II metabolic pathway, UGT-mediated glucuronidation of most prescribed drugs (> 55%) and clinical evidence of UGT-associated drug resistance are major concerns for therapeutic development. While UGTs are highly conserved enzymes, they manifest unique substrate and inhibitor specificity which is poorly understood given the dearth of experimentally determined full-length structures. Such information is important not only to conceptualize their specificity but is central to the design of inhibitors specific to a given UGT in order to avoid toxicity associated with pan-UGT inhibitors. Here, we provide the 1H, 13C and 15N backbone (~ 90%) and sidechain (~ 62%) assignments for the C-terminal domain of UGT2B17, which can be used to determine the molecular binding sites of inhibitor and substrate, and to understand the atomic basis for inhibitor selectivity between UGT2B17 and other members of the UGT2B subfamily. Given the physiological relevance of UGT2B17 in the elimination of hormone-based cancer drugs, these assignments will contribute towards dissecting the structural basis for substrate specificity, selective inhibitor recognition and other aspects of enzyme activity with the goal of selectively overcoming glucuronidation-based drug resistance.

Inside-Out Design of Zinc-Binding Proteins with Non-Native Backbones.

The de novo design of functional proteins requires specification of tertiary structure and incorporation of molecular binding sites. Here, we develop an inside-out design strategy in the molecular modeling program Rosetta that begins with amino acid side chains from one or two α-helices making well-defined contacts with a ligand. A full-sized protein is then built around the ligand by adding additional helices that promote the formation of a protein core and allow additional contacts with the ligand. The protocol was tested by designing 12 zinc-binding proteins, each with 4-5 helices. Four of the designs were folded and bound to zinc with equilibrium dissociation constants varying between 95 nM and 1.1 μM. The design with the tightest affinity for zinc, N12, adopts a unique conformation in the folded state as assessed with nuclear magnetic resonance (NMR) and the design model closely matches (backbone root-mean-square deviation (RMSD) < 1 Å) an AlphaFold model of the sequence. Retrospective analysis with AlphaFold suggests that the sequences of many of the failed designs did not encode the desired tertiary packing.

To Improve Prediction of Binding Residues With DNA, RNA, Carbohydrate, and Peptide Via Multi-Task Deep Neural Networks.

The interactions of proteins with DNA, RNA, peptide, and carbohydrate play key roles in various biological processes. The studies of uncharacterized protein-molecules interactions could be aided by accurate predictions of residues that bind with partner molecules. However, the existing methods for predicting binding residues on proteins remain of relatively low accuracies due to the limited number of complex structures in databases. As different types of molecules partially share chemical mechanisms, the predictions for each molecular type should benefit from the binding information with other molecule types. In this study, we employed a multiple task deep learning strategy to develop a new sequence-based method for simultaneously predicting binding residues/sites with multiple important molecule types named MTDsite. By combining four training sets for DNA, RNA, peptide, and carbohydrate-binding proteins, our method yielded accurate and robust predictions with AUC values of 0.852, 0836, 0.758, and 0.776 on their respective independent test sets, which are 0.52 to 6.6% better than other state-of-the-art methods. To my best knowledge, this is the first method using multi-task framework to predict multiple molecular binding sites simultaneously.

Identification of a binding site on soluble RANKL that can be targeted to inhibit soluble RANK-RANKL interactions and treat osteoporosis

One of the major challenges for discovering protein-protein interaction inhibitors is identifying selective and druggable binding sites at the protein surface. Here, we report an approach to identify a small molecular binding site to selectively inhibit the interaction of soluble RANKL and RANK for designing anti-osteoporosis drugs without undesirable immunosuppressive effects. Through molecular dynamic simulations, we discovered a binding site that allows a small molecule to selectively interrupt soluble RANKL-RANK interaction and without interfering with the membrane RANKL-RANK interaction. We describe a highly potent inhibitor, S3-15, and demonstrate its specificity to inhibit the soluble RANKL-RANK interaction with in vitro and in vivo studies. S3-15 exhibits anti-osteoporotic effects without causing immunosuppression. Through in silico and in vitro experiments we further confirm the binding model of S3-15 and soluble RANKL. This work might inspire structure-based drug discovery for targeting protein-protein interactions.

Novel bis naphthalene-2-ol based colorimetric chemosensor for the detection of Fe2+ in physiological pH and its DFT calculation studies

A novel bis naphthalene-2-ol-based multi-functional chromogenic chemosensor was synthesized in a single step and thoroughly characterized by Fourier-Transform Infrared Spectroscopy, Mass spectrometry, Nuclear Magnetic Resonance and Single Crystal-X-ray for the detection of Fe2+ and CN− ions in physiological pH. The detection limit of Fe2+ was initiated as 4.35 μM is much superior to the United States Environmental Protection Agency parameter value for drinking water (5.37 μM). The 3-Fe2+ complex we can reversibly reuse after the treatment with CN− ion. A noteworthy red-shifted with hypochromic shift spectrum and “naked eye” colour change has been observed from yellow colour to light pink colour within 5 s for Fe2+ ion but not for other competing metal ions. Without any complex pretreatment, our chemosensor easily discriminates Fe2+ and Fe3+ ions. From Job's plot analysis, 1H NMR titration and MS analysis confirm the binding stoichiometry among probe 3 and Fe2+ metal ion as 1:1. The experimental active molecular binding site results are correlated well with the Density Functional Theory calculation to understand the sensing mechanism.

Photomotor Responses in Zebrafish and Electrophysiology Reveal Varying Interactions of Anesthetics Targeting Distinct Sites on γ-Aminobutyric Acid Type A Receptors.

Etomidate, barbiturates, alfaxalone, and propofol are anesthetics that allosterically modulate γ-aminobutyric acid type A (GABAA) receptors via distinct sets of molecular binding sites. Two-state concerted coagonist models account for anesthetic effects and predict supra-additive interactions between drug pairs acting at distinct sites. Some behavioral and molecular studies support these predictions, while other findings suggest potentially complex anesthetic interactions. We therefore evaluated interactions among four anesthetics in both animals and GABAA receptors. The authors used video assessment of photomotor responses in zebrafish larvae and isobolography to evaluate hypnotic drug pair interactions. Voltage clamp electrophysiology and allosteric shift analysis evaluated coagonist interactions in α1β3γ2L receptors activated by γ-aminobutyric acid (GABA) versus anesthetics [log(d, AN):log(d, GABA) ratio]. Anesthetic interactions at concentrations relevant to zebrafish were assessed in receptors activated with low GABA. In zebrafish larvae, etomidate interacted additively with both propofol and the barbiturate R-5-allyl-1-methyl m-trifluoromethyl mephobarbital (R-mTFD-MPAB; mean ± SD α = 1.0 ± 0.07 and 0.96 ± 0.11 respectively, where 1.0 indicates additivity), while the four other drug pairs displayed synergy (mean α range 0.76 to 0.89). Electrophysiologic allosteric shifts revealed that both propofol and R-mTFD-MPAB modulated etomidate-activated receptors much less than GABA-activated receptors [log(d, AN):log(d, GABA) ratios = 0.09 ± 0.021 and 0.38 ± 0.024, respectively], while alfaxalone comparably modulated receptors activated by GABA or etomidate [log(d) ratio = 0.87 ± 0.056]. With low GABA activation, etomidate combined with alfaxalone was supra-additive (n = 6; P = 0.023 by paired t test), but etomidate plus R-mTFD-MPAB or propofol was not. In both zebrafish and GABAA receptors, anesthetic drug pairs interacted variably, ranging from additivity to synergy. Pairs including etomidate displayed corresponding interactions in animals and receptors. Some of these results challenge simple two-state coagonist models and support alternatives where different anesthetics may stabilize distinct receptor conformations, altering the effects of other drugs.

Building large-scale unimolecular scaffolding for electronic devices

The fabrication of a future generation of (opto)electronic devices based on molecular components and materials will require careful chemical design, coupled with assembly methods that permit precise spatial orientation and arrangement of the functional molecules within device structures. Although unimolecular electronics are already a laboratory reality, the variation in the arrangement of the molecule within a molecular junction from measurement to measurement is considerable. Consequently, controlling the precise geometry at the molecule–metal contacts is a long-standing and largely unresolved challenge. Here, a strategy to fabricate uniform unimolecular junctions distributed in a regular pattern is reported. A monolayer of zinc metalloporphyrins, peripherally functionalised by bulky dendrons, is used to provide a well-defined array of molecular binding sites with precise spatial distribution. The dendrons are then photochemically cross-linked to form a robust base-layer. Parallel, uniformly-spaced unimolecular structures are subsequently assembled on these binding sites through a layer-by-layer (LbL) strategy. This LbL strategy proceeds through coordination of an α,ω-amino functionalised oligo(phenylene)ethynylene (OPE) molecule to the zinc ions of the metalloporphyrin template base-layer. The structure is then extended through alternating self-assembled layers of (cross-linked) zinc porphyrin and OPE. The coordination interaction between the zinc(II) sites and the bifunctional OPE wire ensures a high degree of registry between the layers and good electrical contact through the extended arrays and offer fine control over the chemical composition.

GraphSite: Ligand Binding Site Classification with Deep Graph Learning.

The binding of small organic molecules to protein targets is fundamental to a wide array of cellular functions. It is also routinely exploited to develop new therapeutic strategies against a variety of diseases. On that account, the ability to effectively detect and classify ligand binding sites in proteins is of paramount importance to modern structure-based drug discovery. These complex and non-trivial tasks require sophisticated algorithms from the field of artificial intelligence to achieve a high prediction accuracy. In this communication, we describe GraphSite, a deep learning-based method utilizing a graph representation of local protein structures and a state-of-the-art graph neural network to classify ligand binding sites. Using neural weighted message passing layers to effectively capture the structural, physicochemical, and evolutionary characteristics of binding pockets mitigates model overfitting and improves the classification accuracy. Indeed, comprehensive cross-validation benchmarks against a large dataset of binding pockets belonging to 14 diverse functional classes demonstrate that GraphSite yields the class-weighted F1-score of 81.7%, outperforming other approaches such as molecular docking and binding site matching. Further, it also generalizes well to unseen data with the F1-score of 70.7%, which is the expected performance in real-world applications. We also discuss new directions to improve and extend GraphSite in the future.

Katacine Is a New Ligand of CLEC-2 that Acts as a Platelet Agonist.

Background CLEC-2 is a platelet receptor with an important role in thromboinflammation but a minor role in hemostasis. Two endogenous ligands of CLEC-2 have been identified, the transmembrane protein podoplanin and iron-containing porphyrin hemin, which is formed following hemolysis from red blood cells. Other exogenous ligands such as rhodocytin have contributed to our understanding of the role of CLEC-2. Objectives To identify novel CLEC-2 small-molecule ligands to aid therapeutic targeting of CLEC-2. Methods ALPHA screen technology has been used for the development of a high-throughput screening (HTS) assay recapitulating the podoplanin–CLEC-2 interaction. Light transmission aggregometry was used to evaluate platelet aggregation. Immunoprecipitation and western blot were used to evaluate direct phosphorylation of CLEC-2 and downstream protein phosphorylation. Autodock vina software was used to predict the molecular binding site of katacine and mass spectrometry to determine the polymeric nature of the ligand. Results and Conclusion We developed a CLEC-2–podoplanin interaction assay in a HTS format and screened 5,016 compounds from a European Union-open screen library. We identified katacine, a mixture of polymers of proanthocyanidins, as a novel ligand for CLEC-2 and showed that it induces platelet aggregation and CLEC-2 phosphorylation via Syk and Src kinases. Platelet aggregation induced by katacine is inhibited by the anti-CLEC-2 monoclonal antibody fragment AYP1 F(ab)′2. Katacine is a novel nonprotein ligand of CLEC-2 that could contribute to a better understanding of CLEC-2 activation in human platelets.

Synthesis and Visualization of Entangled 3D Covalent Organic Frameworks with High-Valency Stereoscopic Molecular Nodes for Gas Separation.

The structural diversity of three-dimensional (3D) covalent organic frameworks (COFs) are limited as there are only a few choices of building units with multiple symmetrically distributed connection sites. To date, 4 and 6-connected stereoscopic nodes with Td , D3h , D3d and C3 symmetries have been mostly reported, delivering limited 3D topologies. We propose an efficient approach to expand the 3D COF repertoire by introducing a high-valency quadrangular prism (D4h ) stereoscopic node with a connectivity of eight, based on which two isoreticular 3D imine-linked COFs can be created. Low-dose electron microscopy allows the direct visualization of their 2-fold interpenetrated bcu networks. These 3D COFs are endowed with unique pore architectures and strong molecular binding sites, and exhibit excellent performance in separating C2 H2 /CO2 and C2 H2 /CH4 gas pairs. The introduction of high-valency stereoscopic nodes would lead to an outburst of new topologies for 3D COFs.

Synthesis and Visualization of Entangled 3D Covalent Organic Frameworks with High‐Valency Stereoscopic Molecular Nodes for Gas Separation

AbstractThe structural diversity of three‐dimensional (3D) covalent organic frameworks (COFs) are limited as there are only a few choices of building units with multiple symmetrically distributed connection sites. To date, 4 and 6‐connected stereoscopic nodes with Td, D3h, D3d and C3 symmetries have been mostly reported, delivering limited 3D topologies. We propose an efficient approach to expand the 3D COF repertoire by introducing a high‐valency quadrangular prism (D4h) stereoscopic node with a connectivity of eight, based on which two isoreticular 3D imine‐linked COFs can be created. Low‐dose electron microscopy allows the direct visualization of their 2‐fold interpenetrated bcu networks. These 3D COFs are endowed with unique pore architectures and strong molecular binding sites, and exhibit excellent performance in separating C2H2/CO2 and C2H2/CH4 gas pairs. The introduction of high‐valency stereoscopic nodes would lead to an outburst of new topologies for 3D COFs.