Binding Of Molecules Research Articles

PTP1B inhibitor alleviates deleterious septic lung injury through Src signaling.

Septic lung injury is an unmet clinical challenge due to its high mortality, and there is a lack of effective treatment. Accumulating evidence suggests that an uncontrolled pulmonary inflammatory response is important in the pathogenesis of lung injury in sepsis. Therefore, limiting excessive early inflammatory responses may be an effective strategy. We established a septic lung injury model using cecal ligation and puncture. Western blotting and immunofluorescence analyses were performed to assess the expression of PTP1B and endoplasmic reticulum (ER) stress and pyroptosis. Co-immunoprecipitation was used to analyze the binding of PTP1B and Src molecules. PTP1B is upregulated in both in vivo and in vitro models of septic lung injury. PTP1B directly binds to Src and aggravates inflammation by regulating the ER stress-pyroptosis axis. The inhibition of PTP1B alleviates inflammation and improves the prognosis of septic mice. Our study suggesting that PT1B inhibitors have clinical application value in the treatment of septic lung injury. This may provide a new strategy for the treatment of septic lung injury.

Salvianolic acid B improves the microcirculation in a mouse model of sepsis through a mechanism involving the platelet receptor CD226.

Salvianolic acid B (SalB) demonstrates diverse clinical applications, particularly in cardiovascular and cerebral protection. This study primarily investigated the effects of SalB on sepsis. The model of sepsis via caecal ligation puncture (CLP) was established in male C57BL/6 mice. Therapeutic effects of SalB on hepatic and pulmonary injury, inflammatory responses and microcirculatory disturbances in sepsis were evaluated. Platelet aggregation and adhesion were measured via flow cytometry and an adhesion test. After overexpression of platelet-related activating molecules by 293T cells, the efficient binding of SalB and platelet CD226 molecules was further evaluated. Finally, neutralizing antibody experiments were used to assess the mechanism of SalB in alleviating the progression of sepsis. SalB mitigated hepatic and pulmonary impairments, reduced inflammatory cytokine levels and enhanced mesenteric microvascular blood flow in septic mice. SalB enhanced CLP-induced reduction of platelet count and platelet pressure cumulative volume. SalB reduced platelet adhesion to endothelial cells and platelet aggregation to leukocytes. A high binding efficiency was observed between SalB and the platelet adhesion molecule CD226. Ex vivo, interactions between SalB and platelets from CD226-knockout mice were markedly decreased. In vivo administration of CD226 neutralizing antibodies significantly delayed disease progression and enhanced mesenteric microcirculation in septic mice. In our murine model of sepsis, treatment with SalB improved the microcirculatory disturbance and hindered the progression of sepsis by inhibiting platelet CD226 function. Our results suggest SalB is a promising therapeutic approach to the treatment of sepsis.

Some possible peculiarities of a ligand molecule binding inside of a protein macromolecule

Some possible peculiarities of a ligand molecule binding inside of a protein macromolecule

Small Molecule RNA Degraders

AbstractRNA is a central molecule in life, involved in a plethora of biological processes and playing a key role in many diseases. Targeting RNA emerges as a significant endeavor in drug discovery, diverging from conventional protein‐centric approaches to tackle various pathologies. Whilst identifying small molecules that bind to specific RNA regions is the first step, the abundance of non‐functional RNA segments renders many interactions biologically inert. Consequently, small molecule binding does not necessarily meet stringent criteria for clinical translation, calling for solutions to push the field forward. Converting RNA‐binders into RNA‐degraders presents a promising avenue to enhance RNA‐targeting. This mini‐review outlines strategies and exemplars wherein simple small molecule RNA binders are reprogrammed into active degraders through the linkage of functional groups. These approaches encompass mechanisms that induce degradation via endogenous enzymes, termed RIBOTACs, as well as those with functional moieties acting autonomously to degrade RNA. Through this exploration, we aim to offer insights into advancing RNA‐targeted therapeutic strategies.

Characterization and Hemocompatibility of α, β, and γ Cyclodextrin-Modified Magnetic Nano-Adsorbents

Kidney dysfunction leads to the retention of metabolites within the blood that are not effectively cleared with conventional hemodialysis. Magnetic nanoparticle (MNP)-based absorbents have inherent properties that make them amenable to capturing toxins in the blood, notably a large surface area that can be chemically modified to enhance toxin capture and the ability to be easily collected from the blood using an external magnetic field. Cyclodextrins (CDs) present a chemical structure that facilitates the binding of small molecules. However, the hemocompatibility of MNPs modified with films composed of different native types of CDs (α, β, or γ) has not yet been investigated, which is information crucial to the potential clinical application of MNPs to supplement hemodialysis. To this end, films of α-, β-, or γ-CDs were formed on MNPs and characterized. The impact of these films on the adsorbed protein structure, composition of key adsorbed proteins, and clotting kinetics were evaluated. It was found that modified MNPs did not significantly affect the secondary structure of some proteins (albumin, lysozyme, α-lactalbumin). The adsorbed proteome from platelet-poor human plasma was evaluated as a function of film properties. Compared to non-modified nanoparticles, CD-modified MNPs exhibited a significant decrease in the adsorbed protein per surface area of MNPs. The immunoblot results showed variations in the adsorption levels of C3, fibrinogen, antithrombin, Factor XI, and plasminogen across CD-modified MNPs. The hemocompatibility experiments showed that CD-modified MNPs are compatible with human whole blood, with no significant impact on platelet activation, hemolysis, or hemostasis.

Potential allosteric pockets identification of glucagon receptor based on molecular dynamics simulations

Glucagon receptor (GCGR) is an important target for the treatment of type 2 diabetes mellitus. Although several small molecules with antagonistic activity have been discovered, so far, only one small molecule binding site has been resolved. To discover more novel allosteric pockets and allosteric molecules, we started with the unique full-length inactive conformation of GCGR and applied all-atom molecular dynamics (MD) simulations to obtain extensive dynamic conformations of the GCGR/glucagon complex. For the first time, MDpocket, FTMove and FTMap were used to detect allosteric pockets in simulation trajectories, selecting 4 stable pockets with a total of 14 structures as templates for virtual screening. From the results of virtual screening, 14 compounds were ultimately selected after a series of filtering steps. The cAMP accumulation assay indicated that compound gs6 has antagonistic activity, and MD simulations further revealed the allosteric mechanism of gs6. We are the first to identify new allosteric pockets and allosteric molecules in simulation trajectories of the GCGR/glucagon complex, providing a reference for research on other G-protein-coupled receptors (GPCR). However, there is still considerable room for improvement, such as using more simulation methods to obtain a richer set of dynamic conformations.

Semistable Half‐Sandwich Cp*Co(II)(P‐X) (X=N, O) Complexes: Synthesis, Characterization and Electrochemical Properties

AbstractThree Cp*Co(II)(P−X) (X=N, O) complexes were synthesized using cyclopentadienyl anionic and [P N]/[P O] bidentate ligands. Crystallographic analysis revealed five‐coordinate, 17‐electron unsaturated structures with low‐spin d⁷ Co(II) configurations. Electrochemical studies showed reversible Co(II)/Co(III) redox couples and an irreversible Co(II)/Co(I) process of Cp*Co(II)(P−O) complexes, while complex Cp*Co(II)(P−N) exhibited irreversible Co(II)/Co(III) process due to the pyridine imine ligand. Oxidation with AgBF4 produced stable Co(III) complexes, confirmed by crystallographic data and NMR data. These complexes exhibit significant electrochemical properties and stability, indicating potential for catalytic and organic molecule binding applications.

Dynamics of the Pre-Powerstroke Myosin Lever Arm and the Effects of Omecamtiv Mecarbil.

The binding of small molecules to sarcomeric myosin can elicit powerful effects on the chemomechanical cycle, making them effective therapeutics in the clinic and research tools at the benchtop. However, these myotropes can have complex effects that act on different phases of the crossbridge cycle and which depend on structural, dynamic, and environmental variables. While small molecule binding sites have been identified crystallographically and their effects on contraction studied extensively, small molecule-induced dynamic changes that link structure-function are less studied. Here, we use molecular dynamics simulations to explore how omecamtiv mecarbil (OM), a cardiac myosin-specific myotrope, alters the coordinated dynamics of the lever arm and the motor domain in the pre-powerstroke state. We show that the lever arm adopts a range of orientations and find that different lever arm orientations are accompanied by changes in the hydrogen bonding patterns near the converter. We find that the binding of OM to myosin reduces the conformational heterogeneity of the lever arm orientation and also adjusts the average lever arm orientation. Finally, we map out the distinct conformations and ligand-protein interactions adopted by OM. These results uncover some structural factors that govern the motor domain-tail orientations and the mechanisms by which OM primes the pre-powerstroke myosin heads.

Unveiling Temperature-Induced Structural Phase Transformations and CO2 Binding Sites in CALF-20.

The increase in atmospheric carbon dioxide concentration linked to climate change has created a need for new sorbents capable of separating CO2 from exhaust gases. Recently, an easily produced metal-organic framework, CALF-20, was shown to withstand over 450,000 adsorption/desorption cycles in steam and wet acid gases. Further development and industrial application of such materials require an understanding of the observed processes. Herein, we demonstrate that conditioning as-synthesized CALF-20 single crystal transforms it into a different phase, γ-CALF-20. The transformation resulted in significant structural changes, including the binding of water molecules to Zn(II), accompanied by a reduction of 9% in the unit cell volume. Our experimental findings were supported by the energy-volume dependence of CALF-20 in the presence and absence of water molecules calculated from density functional theory. We have also monitored the sorption process of the dominant greenhouse gas, CO2, on the initial phase of CALF-20 at atomic resolution using in situ single-crystal X-ray diffraction under specific pressure. The new understanding of CALF-20 chemistry from these studies should facilitate development of novel sorbents for gas adsorption technologies.

Kinetic Studies on the Interaction of HIV-1 Gag Protein with the HIV-1 RNA Packaging Signal

During HIV-1 virus assembly, the genomic RNA (vRNA) is selected for packaging by the viral protein Gag because it contains a specific packaging signal, Psi. While there have been numerous studies of Gag–Psi interactions, there is almost no information on the kinetic aspects of this interaction. We investigated the kinetics of Gag binding to different RNAs using switchSENSE DRX2 technology. We measured the association rate of Gag binding to monomeric Psi, to a “Multiple Binding Site Mutant” Psi that is inactive for genome packaging in vivo, and to a scrambled Psi. We discovered that Gag binds more rapidly to Psi RNA than to the mutant or scrambled RNAs. Furthermore, rapid Gag association kinetics are retained within sub-regions of Psi: Gag associates more rapidly with RNA containing only the 3′ two of the three Psi stem-loops than with monomeric RNA containing the 5′ two stem-loops or a scrambled RNA. No differences were detectable with individual Psi stem-loops. Interestingly, the rate of binding of Gag molecules to Psi increases with increasing Gag concentration, suggesting cooperativity in binding. The results are consistent with the hypothesis that selectivity in packaging derives from kinetic differences in initiation of particle assembly.

Switchback RNA.

Intricately designed DNA and RNA motifs guide the assembly of robust and functional nucleic acid nanostructures. In this work, we present a globally left-handed RNA motif with two parallel strands called switchback RNA and report its assembly, biophysical, and biochemical characterization. Switchback RNA can be assembled in buffers without Mg2+, with improved thermal stability in buffers containing Mg2+, Na+, or K+. Differences in the binding of small molecules to switchback RNA and conventional RNA indicate design-based approaches for small molecule loading on RNA nanostructures. Further, the differential affinity of the two component strands in switchback or conventional duplex conformations allows for toehold-less strand displacement. Enzyme studies showed that the switchback and conventional RNA structures have similar levels of nuclease resistance. These results provide insights for employing switchback RNA as a structural motif in RNA nanotechnology. Our observation that RNA strands with switchback complementarity can form stable complexes at low magnesium concentrations encourages studies into the potential occurrence of switchback RNA in nature.

Turbocharging protein binding site prediction with geometric attention, inter-resolution transfer learning, and homology-based augmentation

BackgroundLocating small molecule binding sites in target proteins, in the resolution of either pocket or residue, is critical in many drug-discovery scenarios. Since it is not always easy to find such binding sites using conventional methods, different deep learning methods to predict binding sites out of protein structures have been developed in recent years. The existing deep learning based methods have several limitations, including (1) the inefficiency of the CNN-only architecture, (2) loss of information due to excessive post-processing, and (3) the under-utilization of available data sources.MethodsWe present a new model architecture and training method that resolves the aforementioned problems. First, by layering geometric self-attention units on top of residue-level 3D CNN outputs, our model overcomes the problems of CNN-only architectures. Second, by configuring the fundamental units of computation as residues and pockets instead of voxels, our method reduced the information loss from post-processing. Lastly, by employing inter-resolution transfer learning and homology-based augmentation, our method maximizes the utilization of available data sources to a significant extent.ResultsThe proposed method significantly outperformed all state-of-the-art baselines regarding both resolutions—pocket and residue. An ablation study demonstrated the indispensability of our proposed architecture, as well as transfer learning and homology-based augmentation, for achieving optimal performance. We further scrutinized our model’s performance through a case study involving human serum albumin, which demonstrated our model’s superior capability in identifying multiple binding sites of the protein, outperforming the existing methods.ConclusionsWe believe that our contribution to the literature is twofold. Firstly, we introduce a novel computational method for binding site prediction with practical applications, substantiated by its strong performance across diverse benchmarks and case studies. Secondly, the innovative aspects in our method— specifically, the design of the model architecture, inter-resolution transfer learning, and homology-based augmentation—would serve as useful components for future work.

Development of a high throughput cytochrome P450 ligand-binding assay

Human cytochrome P450 enzymes are membrane-embedded monooxygenases responsible for xenobiotic metabolism, steroidogenesis, fatty acid metabolism, and vitamin metabolism. Their active sites can accommodate diverse small molecules and understanding these interactions is key to decoding enzymatic functionality and designing drugs. The most common method for characterizing small molecule binding is quantifying absorbance changes that typically occur when ligands enter the active site near the heme iron. Traditionally, such titrations are monitored by a spectrophotometer, requiring significant manual time, protein, and increasing solvents. This assay was adapted for semi-automated high throughput screening, increasing throughput 50-fold while requiring less protein and keeping solvent concentrations constant. This 384-well assay was validated for both type I and II shifts typically observed for substrates and heme-coordinating inhibitors, respectively. This assay was used to screen a library of ∼100 diverse imidazole-containing compounds which can coordinate with the heme iron if compatible with the overall active site. Three human cytochrome P450 enzymes were screened: drug-metabolizing CYP2A6 and CYP2D6 and sterol-metabolizing CYP8B1. Each bound different sets of imidazole compounds with varying Kd values, providing a unique binding fingerprint. As a final validation, the Kd values were used to generate pharmacophores to compare to experimental X-ray structures. Applications for the high-throughput assay include the following: 1) facilitating generation of pharmacophores for enzymes where structures are not available, 2) screening to identify ligands for P450 orphans, 3) screening for inhibitors of P450s drug targets, 4) screening potential new drugs to avoid and/or control P450 metabolism, and 5) efficient validation of computational ligand binding predictions.

Variation within the non-coding genome influences genetic and epigenetic regulation of the human leukocyte antigen genes.

Variation within the non-coding genome may influence the regulation and expression of important genes involved in immune control such as the human leukocyte antigen (HLA) system. Class I and Class II HLA molecules are essential for peptide presentation which is required for T lymphocyte activation. Single nucleotide polymorphisms within non-coding regions of HLA Class I and Class II genes may influence the expression of these genes by affecting the binding of transcription factors and chromatin modeling molecules. Furthermore, an interplay between genetic and epigenetic factors may also influence HLA expression. Epigenetic factors such as DNA methylation and non-coding RNA, regulate gene expression without changing the DNA sequence. However, genetic variation may promote or allow genes to escape regulation by epigenetic factors, resulting in altered expression. The HLA system is central to most diseases, therefore, understanding the role of genetics and epigenetics on HLA regulation will tremendously impact healthcare. The knowledge gained from these studies may lead to novel and cost-effective diagnostic approaches and therapeutic interventions. This review discusses the role of non-coding variants on HLA regulation. Furthermore, we discuss the interplay between genetic and epigenetic factors on the regulation of HLA by evaluating literature based on polymorphisms within DNA methylation and miRNA regulatory sites within class I and Class II HLA genes. We also provide insight into the importance of the HLA non-coding genome on disease, discuss ethnic-specific differences across the HLA region and provide guidelines for future HLA studies.

Aldehyde-based activation of C2α-lactylthiamin diphosphate decarboxylation on bacterial 1-deoxy-d-xylulose 5-phosphate synthase.

1-Deoxy-d-xylulose 5-phosphate synthase (DXPS) catalyzes the thiamin diphosphate (ThDP)-dependent formation of DXP from pyruvate (donor substrate) and d-glyceraldehyde 3-phosphate (d-GAP, acceptor substrate) in bacterial central metabolism. DXPS uses a ligand-gated mechanism in which binding of a small molecule "trigger" activates the first enzyme-bound intermediate, C2α-lactylThDP (LThDP), to form the reactive carbanion via LThDP decarboxylation. d-GAP is the natural acceptor substrate for DXPS and also serves a role as a trigger to induce LThDP decarboxylation in the gated step. Additionally, we have shown that O2 and d-glyceraldehyde (d-GA) can induce LThDP decarboxylation. We hypothesize this ligand-gated mechanism poises DXPS to sense and respond to cellular cues in metabolic remodeling during bacterial adaptation. Here we sought to characterize features of small molecule inducers of LThDP decarboxylation. Using a combination of CD, NMR and biochemical methods, we demonstrate that the α-hydroxy aldehyde moiety of d-GAP is sufficient to induce LThDP decarboxylation en route to DXP formation. A variety of aliphatic aldehydes also induce LThDP decarboxylation. The study highlights the capacity of DXPS to respond to different molecular cues, lending support to potential multifunctionality of DXPS and its metabolic regulation by this mechanism.

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence and secondary structure features and neglect small molecule characteristics, and resulting in poor performance on unknown small molecule testing. To overcome this limitation, we developed a double-layer stacking-based machine learning model called ZHMol-RLinter. This approach more effectively predicts RNA-small molecule binding preferences by learning RNA and small molecule features to capture their interaction information. ZHMol-RLinter also combines sequence and secondary structural features with structural geometric and physicochemical environment information to capture the specificity of RNA spatial conformations in recognizing small molecules. Our results demonstrate that ZHMol-RLinter has a success rate of 90.8% on the published RL98 testing set, representing a significant improvement over existing methods. Additionally, ZHMol-RLinter achieved a success rate of 77.1% on the unknown small molecule UNK96 testing set, showing substantial improvement over the existing methods. The evaluation of predicted structures confirms that ZHMol-RLinter is reliable and accurate for predicting RNA-small molecule binding preferences, even for challenging unknown small molecule testing. Predicting RNA-small molecule binding preferences can help in the understanding of RNA-small molecule interactions and promote the design of RNA-related drugs for biological and medical applications.

On-Demand Elongation of Peptide Nanofibrils at Cellular Interfaces to Modulate Cell-Cell Interactions.

Natural cells can achieve specific cell-cell interactions by enriching nonspecific binding molecules on demand at intercellular contact faces, a pathway currently beyond synthetic capabilities. We are inspired to construct responsive peptide fibrils on cell surfaces, which elongate upon encountering target cells while maintaining a short length when contacting competing cells, as directed by a strand-displacement reaction arranged on target cell surfaces. With the display of ligands that bind to both target and competing cells, the contact-induced, region-selective fibril elongation selectively promotes host-target cell interactions via the accumulation of nonspecific ligands between matched cells. This approach is effective in guiding natural killer cells, the broad-spectrum effector lymphocytes, to eliminate specific cancer cells. In contrast to conventional methods relying on target cell-specific binding molecules for the desired cellular interactions, this dynamic scaffold-based approach would broaden the scope of cell combinations for manipulation and enhance the adjustability of cell behaviors for future applications.

The fitness cost of spurious phosphorylation.

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known. Here, we use Saccharomyces cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, the resulting tyrosine phosphorylation is biologically spurious. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3500 proteins. The number of spurious pY sites generated correlates strongly with decreased growth, and we predict over 1000 pY events to be deleterious. However, we also find that many of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with tyrosine kinases. Our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE.

Small-molecule drug design hinges on obtaining co-crystallized ligand-protein structures. Despite AlphaFold2's strides in protein native structure prediction, its focus on apo structures overlooks ligands and associated holo structures. Moreover, designing selective drugs often benefits from the targeting of diverse metastable conformations. Therefore, direct application of AlphaFold2 models in virtual screening and drug discovery remains tentative. Here, we demonstrate an AlphaFold2-based framework combined with all-atom enhanced sampling molecular dynamics and Induced Fit docking, named AF2RAVE-Glide, to conduct computational model-based small-molecule binding of metastable protein kinase conformations, initiated from protein sequences. We demonstrate the AF2RAVE-Glide workflow on three different mammalian protein kinases and their type I and II inhibitors, with special emphasis on binding of known type II kinase inhibitors which target the metastable classical DFG-out state. These states are not easy to sample from AlphaFold2. Here, we demonstrate how with AF2RAVE these metastable conformations can be sampled for different kinases with high enough accuracy to enable subsequent docking of known type II kinase inhibitors with more than 50% success rates across docking calculations. We believe the protocol should be deployable for other kinases and more proteins generally.

Naphthalimide-Based Amphiphiles: Synthesis and DFT Studies of the Aggregation and Interaction of a Simplified Model System with Water Molecules.

Systems containing amphiphilic/pathic molecules have the tremendous capacity to self-assemble under appropriate conditions to form morphologies with well-defined structural order (systematic arrangement), nanometer-scale dimensions, and unique properties. In this work, the synthesis of novel naphthalimide-based amphiphilic probes that have 1,8-naphthalimide as the fluorescence signal reporting group, octyl as hydrophobic head, and PEG as hydrophilic tail, is described. These designed molecules represent a new class of self-assembling structures with some promising features. The lack of literature data on the use of 1,8-naphthalimides with cyclic and acyclic hydrophilic PEG fragments as self-assembling structures gives us the opportunity to initiate a new field in materials science. The successful synthesis of such structures is fundamental to synthetic chemistry, and computational studies of the aggregation and binding of water molecules shed light on the ability of these new systems to function as membrane water channels. This study not only expands the list of 1,8-naphthalimide derivatives but may also serve as a new platform for the development of membrane additives based on PEG-functionalized naphthalimides.