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Identifying interactions between drugs and targets is crucial for drug discovery and development. Nevertheless, the determination of drug-target binding affinities (DTAs) through traditional experimental methods is a time-consuming process. Conventional approaches to predicting drug-target interactions (DTIs) frequently prove inadequate due to an insufficient representation of drugs and targets, resulting in ineffective feature capture and questionable interpretability of results. To address these challenges, we introduce CGPDTA, a novel deep learning framework empowered by transfer learning, designed explicitly for the accurate prediction of DTAs. CGPDTA leverages the complementarity of drug-drug and protein-protein interaction knowledge through advanced drug and protein language models. It further enhances predictive capability and interpretability by incorporating molecular substructure graphs and protein pocket sequences to represent local features of drugs and targets effectively. Our findings demonstrate that CGPDTA not only outperforms existing methods in accuracy but also provides meaningful insights into the predictive process, marking a significant advancement in the field of drug discovery., (© 2024 Wiley Periodicals LLC.)

Human dihydroorotate dehydrogenase (hDHODH) is a flavin mononucleotide-dependent enzyme that can limit de novo pyrimidine synthesis, making it a therapeutic target for diseases such as autoimmune disorders and cancer. In this study, using the docking structures of complexes generated by AutoDock Vina, we integrate interaction features and ligand features, and employ support vector regression to develop a target-specific scoring function for hDHODH (TSSF-hDHODH). The Pearson correlation coefficient values of TSSF-hDHODH in the cross-validation and external validation are 0.86 and 0.74, respectively, both of which are far superior to those of classic scoring function AutoDock Vina and random forest (RF) based generic scoring function RF-Score. TSSF-hDHODH is further used for the virtual screening of potential inhibitors in the FDA-Approved & Pharmacopeia Drug Library. In conjunction with the results from molecular dynamics simulations, crizotinib is identified as a candidate for subsequent structural optimization. This study can be useful for the discovery of hDHODH inhibitors and the development of scoring functions for additional targets., (© 2024 Wiley Periodicals LLC.)

Prediction of protein fitness from computational modeling is an area of active research in rational protein design. Here, we investigated whether protein fluctuations computed from molecular dynamics simulations can be used to predict the expression levels of SARS-CoV-2 receptor binding domain (RBD) mutants determined in the deep mutational scanning experiment of Starr et al. [Science (New York, N.Y.) 2022, 377, 420] Specifically, we performed more than 0.7 milliseconds of molecular dynamics (MD) simulations of 557 mutant RBDs in triplicate to achieve statistical significance under various simulation conditions. Our results show modest but significant anticorrelation in the range [-0.4, -0.3] between expression and RBD protein flexibility. A simple linear regression machine learning model achieved correlation coefficients in the range [0.7, 0.8], thus outperforming MD-based models, but required about 25 mutations at each residue position for training., (© 2024 Wiley Periodicals LLC.)

Predicting drug target binding affinity has huge relevance in Modern drug discovery and drug repositioning processes which assist doctors to come up with new drugs or even use the existing drugs for new target proteins. In silico models, using advanced deep learning techniques could further assist these prediction tasks by providing most prominent drug target pairs. Considering these factors, a deep learning based algorithmic framework is developed in this study to support drug target interaction prediction. The proposed SeqDPI model extract the relevant drug and protein features from the one dimensional Sequential representation of the dataset considered using optimized CNN networks that deploy convolutions on varying length of amino acid subsequence's to capture hidden pattern, the convolved drug- protein features obtained are then used as an input to L2 penalized feed forward neural network which matches the local residue patterns in protein classes with molecular fingerprints of drugs to predict the binding strength for all drug target pairs. The proposed model reduces the convolution strain typically encountered in existing in silico models that utilize complex 3D structures of drug protein datasets. The result shows that the SeqDPI model achieves a mean square error MSE of (0.167) across cross validation folds, outperforming baseline models such as KronRLS (0.406), Simboost (0.226), and DeepPS (0.214). Additionally, SeqDPI attains a high CI score of 0.9114 on the benchmark KIBA dataset, demonstrating its statistical significance and computational efficiency compared to existing methods. This gives the relevance and effectiveness of SeqDPI model in accurately predicting binding affinities while working with simpler one-dimensional data, making it a robust and computationally cost-effective solution for drug-target interaction prediction., (© 2024 Wiley Periodicals LLC.)

Metal ions are significant ligands that bind to proteins and play crucial roles in cell metabolism, material transport, and signal transduction. Predicting the protein-metal ion ligand binding residues (PMILBRs) accurately is a challenging task in theoretical calculations. In this study, the authors employed fused amino acids and their derived information as feature parameters to predict PMILBRs using three classical machine learning algorithms, yielding favourable prediction results. Subsequently, deep learning algorithm was incorporated in the prediction, resulting in improved results for the sets of Ca 2+ and Mg 2+ compared to previous studies. The validation matrix provided the optimal prediction model for each ionic ligand binding residue, exhibiting the capability of effectively predicting the binding sites of metal ion ligands for real protein chains., (© 2025 The Author(s). IET Systems Biology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.)

Nucleic acid sequencing technologies have gone through extraordinary advancements in the past several decades, significantly increasing throughput while reducing cost. To create similar advancement in proteomics, numerous approaches are being investigated to advance protein sequencing. One of the promising approaches uses N-terminal amino acid binders (NAABs), also referred to as recognizers, that selectively can identify amino acids at the N-terminus of a peptide. However, there are only a few engineered NAABs currently available that bind to specific amino acids and meet the requirements of a biotechnology reagent. Therefore, additional NAABs need to be identified and engineered to enable confident identification and, ultimately, de novo protein sequencing. To fill this gap, a human protein GID4 was engineered to create a NAAB for N-terminal proline (Nt-Pro). While native GID4 binds Nt-Pro, its binding is weak (µmol/L) and greatly influenced by the identity of residues following the Nt-Pro. Through directed evolution, yeast-surface display, and fluorescence-activated cell sorting, we identified sequence variants of GID4 with increased binding response to Nt-Pro. Moreover, variants with an A252V mutation showed a reduced influence from residues in the second and third positions of the target peptide when binding to Nt-Pro. The workflow outlined here is shown to be a viable strategy for engineering NAABs, even when starting from native Nt-binding proteins whose binding is strongly impacted by the identity of residues following Nt-amino acid., (© 2024 Wiley Periodicals LLC.)

The human V1b receptor (V1bR) is primarily expressed in the corticotropic cells of the anterior pituitary where it is involved in the regulation of the hypothalamic-pituitary-adrenal (HPA) axis. The activation of V1bR induces the secretion of adrenocorticotropin hormone (ACTH) from the anterior pituitary cells which, in turn, stimulates the production of cortisol via the adrenal cortex. Clinical studies have demonstrated the chronic dysfunction of the HPA axis in patients with several psychiatric disorders. Thus, the inhibition of the V1b receptor and normalizing the HPA axis hyperactivity is a promising approach to the treatment of many stress-related disorders such as anxiety and depression. Nelivaptan is a selective V1bR antagonist that can be used for this purpose and an excellent molecule to study how antagonists interact with V1bR, especially since in recent years the experimental structures of vasopressin V2 and oxytocin receptors were solved, providing high-similarity templates for homology modeling of V1bR. Therefore, in this work, six independent molecular dynamics simulations of a V1bR-nelivaptan complex in a fully hydrated lipid bilayer, yielding a total simulation time of 6.0 μs, have been conducted. In the lowest-energy complexes obtained in this work and proposed to be the most probable structure of the V1bR-nelivaptan complex, the location of the ligand inside the receptor pocket is very similar to that of the other ligands observed in the experimental structures of the vasopressin/oxytocin receptor family. The receptor-ligand interaction has been analyzed and described, revealing the details of the molecular mechanism of this antagonist binding to V1bR and a probable contribution of L200 5×40 and T203 5×43 to binding selectivity., (© 2024 Wiley Periodicals LLC.)

Predicting protein-ligand binding affinity is a crucial and challenging task in structure-based drug discovery. With the accumulation of complex structures and binding affinity data, various machine-learning scoring functions, particularly those based on deep learning, have been developed for this task, exhibiting superiority over their traditional counterparts. A fusion model sequentially connecting a graph neural network (GNN) and a convolutional neural network (CNN) to predict protein-ligand binding affinity is proposed in this work. In this model, the intermediate outputs of the GNN layers, as supplementary descriptors of atomic chemical environments at different levels, are concatenated with the input features of CNN. The model demonstrates a noticeable improvement in performance on CASF-2016 benchmark compared to its constituent CNN models. The generalization ability of the model is evaluated by setting a series of thresholds for ligand extended-connectivity fingerprint similarity or protein sequence similarity between the training and test sets. Masking experiment reveals that model can capture key interaction regions. Furthermore, the fusion model is applied to a virtual screening task for a novel target, PI5P4Kα. The fusion strategy significantly improves the ability of the constituent CNN model to identify active compounds. This work offers a novel approach to enhancing the accuracy of deep learning models in predicting binding affinity through fusion strategies., (© 2024 Wiley Periodicals LLC.)

Affinity precipitation is a powerful separation method in that it combines the binding selectivity of affinity chromatography with precipitation of captured biomolecules via phase separation triggered by small changes in the environment, e.g., pH, ionic strength, temperature, light, etc. Elastin-like polypeptides (ELPs) are thermally responsive biopolymers composed of pentapeptide repeats VPGVG that undergo reversible phase separation, where they aggregate when temperature and/or salt concentration are increased. Here we describe the generation of an ELP fusion to a soluble streptavidin mutant that enables rapid purification of any Strep-tag II fusion protein of interest. This heterobifunctional protein takes advantage of the native tetrameric structure of streptavidin, leading to binding-induced multivalent crosslinking upon protein capture. The efficient biotin-mediated dissociation of the bound Strep-tag II fusion protein from the streptavidin-ELP capturing scaffold allows for mild elution conditions. We also show that this platform is particularly effective in the purification of a virus-like particle (VLP)-like E2 protein nanoparticle, likely because the high valency of the protein particle causes binding-induced crosslinking and precipitation. Considering the importance of VLP for gene therapy applications, we believe this is a particularly exciting advance. We demonstrated this feasibility by the efficient purification of a VLP-like E2 protein nanoparticle as a surrogate., (© 2024 Wiley Periodicals LLC.)

Drug-target binding determines a drug's pharmacodynamics but can also have a profound impact on a drug's pharmacokinetics, known as target-mediated drug disposition (TMDD). TMDD models describe the influence of drug-target binding and target turnover on unbound drug concentrations and are frequently used for biologics and drugs with nonlinear plasma pharmacokinetics. For drug targets expressed in tissues, the effect of TMDD may not be detected when analyzing plasma concentration curves, but it might still affect tissue concentrations and occupancy. This review aimed to investigate the likeliness of such a scenario by reviewing the literature for a typical range of TMDD parameter values and their impact on local drug concentrations and target occupancy in a whole-body PBPK model with TMDD. Our analysis demonstrated that tissue drug concentrations are impacted and significantly depleted in many physiological scenarios. In contrast, the effect on plasma concentrations is much lower, specifically for smaller organs with lower perfusion. Moreover, in scenarios with fast internalization of the drug-target complex, the distribution of large molecules from plasma to tissue interstitial space emerges as a rate-limiting step for the drug-target interaction. These factors may lead to overpredicting local drug concentrations when considering only plasma pharmacokinetics. A sensitivity analysis revealed the high and not always intuitive impact of drug-specific parameters, including the drug molecule hydrodynamic radius, dissociation constant (K d ), drug-target complex internalization rate constant (k int ), and target dissociation rate constant (k off ), on the drug's pharmacokinetics. Our analysis demonstrated that tissue TMDD needs to be considered even if plasma pharmacokinetics are linear., (© 2024 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) is a membrane protein that plays an important role in a variety of immune and non-immune functions. Such functions are regulated by its activity as a homophilic ligand but also through its ability to interact as a heterophilic ligand with various host proteins. These include CEACAM5, T cell immunoglobulin-mucin like protein-3 (TIM-3) and, potentially, protein death protein 1 (PD-1). Furthermore, CEACAM1 is targeted by various pathogens to allow them to invade a host and bypass an effective immune response. Clinically, CEACAM1 plays an important role in infectious diseases, autoimmunity and cancer. In this review, we describe the structural basis for CEACAM1 interactions as a homophilic and heterophilic ligand. We discuss the regulation of its monomeric, dimeric and oligomeric states in cis and trans binding as well as the consequences for eliciting downstream signalling activities. Furthermore, we explore the potential role of avidity in determining CEACAM1's activities., (© 2024 Stichting European Society for Clinical Investigation Journal Foundation. Published by John Wiley & Sons Ltd.)

Background: Though receptor binding specificity is well established as a contributor to host tropism and spillover potential of influenza A viruses, determining receptor binding preference of a specific virus still requires expensive and time-consuming laboratory analyses. In this study, we pilot a machine learning approach for prediction of binding preference., Methods: We trained a convolutional neural network to predict the α2,6-linked sialic acid preference of influenza A viruses given the hemagglutinin amino acid sequence. The model was evaluated with an independent test dataset to assess the standard performance metrics, the impact of missing data in the test sequences, and the prediction performance on novel subtypes. Further, features found to be important to the generation of predictions were tested via targeted mutagenesis of H9 and H16 proteins expressed on pseudoviruses., Results: The final model developed in this study produced predictions on a test dataset correctly 94% of the time and an area under the receiver operating characteristic curve of 0.93. The model tolerated about 10% missing test data without compromising accurate prediction performance. Predictions on novel subtypes revealed that the model can extrapolate feature relationships between subtypes when generating binding predictions. Finally, evaluation of the features important for model predictions helped identify positions that alter the sialic acid conformation preference of hemagglutinin proteins in practice., Conclusions: Ultimately, our results provide support to this in silico approach to hemagglutinin receptor binding preference prediction. This work emphasizes the need for ongoing research efforts to produce tools that may aid future pandemic risk assessment., (© 2024 The Author(s). Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd.)

The stability of α-crystallin, the major protein of the mammalian eye lens and a molecular chaperone, is one of the most crucial factors for its survival and function. The chaperone-like activity and stability of α-crystallin dramatically increased in the presence of Zn 2 . Each subunit of α-crystallin could bind multiple zinc atoms through inter-subunit bridging and cause enhanced stability. Three histidines H104, H111, and H119 of recombinant human αB-crystallin (HSPB5) are found to be the Zn 2+ binding residues. In this article, we did site-directed mutagenesis of six histidine residues and made five-point mutants and a double mutant of αB-crystallin. We studied the effect of zinc on the chaperone function, surface hydrophobicity, and stability of the histidine mutants. We removed the histidine tag from H18A and H101V mutants and studied the stability and chaperone function in the presence and absence of zinc. H83 and H111 mutations showed similar enhancement in chaperone function like WT in the presence of Zn 2+ . Point mutants having his tags showed similar stability enhancement, but point mutant H18A without his tag showed less enhancement in stability in the presence of zinc. This indicates the significance of the presence of his tags in the study of zinc binding interaction with recombinant human αB-crystallin., (© 2025 Wiley Periodicals LLC.)

The translation of in vitro potency of a candidate drug, as determined by traditional pharmacology metrics (such as EC 50 /IC 50 and K D /K i values), to in vivo efficacy and safety is challenging. Residence time, which represents the duration of drug-target interaction, can be part of a more comprehensive understanding of the dynamic nature of drug-target interactions in vivo, thereby enabling better prediction of drug efficacy and safety. As a consequence, a prolonged residence time may help in achieving sustained pharmacological activity, while transient interactions with shorter residence times may be favourable for targets associated with side effects. Therefore, integration of residence time into the early stages of drug discovery and development has yielded a number of clinical candidates with promising in vivo efficacy and safety profiles. Insights from residence time research thus contribute to the translation of in vitro potency to in vivo efficacy and safety. Further research and advances in measuring and optimizing residence time will bring a much-needed addition to the drug discovery process and the development of safer and more effective drugs. In this review, we summarize recent research progress on residence time, highlighting its importance from a translational perspective., (© 2023 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Equilibrium binding assays are one of the mainstays of current drug discovery efforts to evaluate the interaction of drugs with receptors in membranes and intact cells. However, in recent years, there has been increased focus on the kinetics of the drug-receptor interaction to gain insight into the lifetime of drug-receptor complexes and the rate of association of a ligand with its receptor. Furthermore, drugs that act on topically distinct sites (allosteric) from those occupied by the endogenous ligand (orthosteric site) can induce conformational changes in the orthosteric binding site leading to changes in the association and/or dissociation rate constants of orthosteric ligands. Conformational changes in the orthosteric ligand binding site can also be induced through interaction with neighbouring accessory proteins and receptor homodimerisation and heterodimerisation. In this review, we provide an overview of the use of fluorescent ligand technologies to interrogate ligand-receptor kinetics in living cells and the novel insights that they can provide into the conformational changes induced by drugs acting on a variety of cell surface receptors including G protein-coupled receptors (GPCRs), receptor tyrosine kinases (RTKs) and cytokine receptors., (© 2023 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Two trials were performed to evaluate the effect of renal and hepatic impairment on the pharmacokinetics of pritelivir and its metabolites. The renal impairment trial included subjects with mild, moderate, and severe impairment, while the hepatic impairment trial included subjects with moderate impairment. Both trials recruited a matched control group of healthy subjects. Following a single oral dose of 100 mg of pritelivir, mild and moderate renal impairment and moderate hepatic impairment did not have a clinically relevant effect on the pharmacokinetics of pritelivir. In subjects with severe renal impairment, pritelivir exposure (area under the plasma concentration-time curve from time 0 to infinity (AUC 0- ) was 57% higher compared with controls. Pritelivir plasma protein binding was similar in subjects and controls with renal impairment, while the free fraction was higher in subjects with moderate hepatic impairment, increasing unbound pritelivir exposure by 23%. For the metabolites pyridinyl phenyl acetic acid (PPA), amino thiazole sulfonamide (ATS), and PPA-acyl glucuronide, generally higher exposure was observed with increasing degree of renal impairment (ie, moderate to severe), but not with mild impairment. A modest effect of moderate hepatic impairment was observed for PPA and ATS. Pritelivir was safe and well tolerated in healthy subjects and subjects with renal or hepatic impairment.inf ) was 57% higher compared with controls. Pritelivir plasma protein binding was similar in subjects and controls with renal impairment, while the free fraction was higher in subjects with moderate hepatic impairment, increasing unbound pritelivir exposure by 23%. For the metabolites pyridinyl phenyl acetic acid (PPA), amino thiazole sulfonamide (ATS), and PPA-acyl glucuronide, generally higher exposure was observed with increasing degree of renal impairment (ie, moderate to severe), but not with mild impairment. A modest effect of moderate hepatic impairment was observed for PPA and ATS. Pritelivir was safe and well tolerated in healthy subjects and subjects with renal or hepatic impairment., (© 2024 AiCuris Anti‐infective Cures AG. Clinical Pharmacology in Drug Development published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

Background and Purpose: Neurosteroids are allosteric modulators of GABA A currents, acting through several functional binding sites although their affinity and specificity for each site are unknown. The goal of this study was to measure steady-state binding affinities of various neurosteroids for specific sites on the GABA A receptor., Experimental Approach: Two methods were developed to measure neurosteroid binding affinity: (1) quenching of specific tryptophan residues in neurosteroid binding sites by the neurosteroid 17-methylketone group, and (2) FRET between MQ290 (an intrinsically fluorescent neurosteroid) and tryptophan residues in the binding sites. The assays were developed using ELIC-α1GABA A R, a chimeric receptor containing transmembrane domains of the α 1 -GABA A receptor. Tryptophan mutagenesis was used to identify specific interactions., Key Results: Allopregnanolone (3α-OH neurosteroid) was shown to bind at intersubunit and intrasubunit sites with equal affinity, whereas epi-allopregnanolone (3β-OH neurosteroid) binds at the intrasubunit site. MQ290 formed a strong FRET pair with W246, acting as a site-specific probe for the intersubunit site. The affinity and site-specificity of several neurosteroid agonists and inverse agonists was measured using the MQ290 binding assay. The FRET assay distinguishes between competitive and allosteric inhibition of MQ290 binding and demonstrated an allosteric interaction between the two neurosteroid binding sites., Conclusions and Implications: The affinity and specificity of neurosteroid binding to two sites in the ELIC-α1GABA A R were directly measured and an allosteric interaction between the sites was revealed. Adaptation of the MQ290 FRET assay to a plate-reader format will enable screening for high affinity agonists and antagonists for neurosteroid binding sites., (© 2024 The Author(s). British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Patients with severe and sometimes moderate hemophilia B are prophylactically treated with factor IX concentrates to prevent bleeding. For some time now, various extended terminal half-life (EHL) recombinant factor IX concentrates are available allowing less frequent administration during prophylaxis in comparison to standard half-life recombinant FIX (rFIX). Especially, recombinant FIX-Fc fusion protein (rFIXFc; Alprolix®) exhibits a rapid distribution phase, potentially due to binding to type IV collagen (Col4) in the extravascular space. Studies suggest that the presence of extravascular rFIXFc is protective against bleeding as without measurable FIX activity in plasma, and no extra bleeding seems to occur. The physiologically based pharmacokinetic (PBPK) model for rFIXFc which we describe in this study, is able to accurately predict the observed concentration-time profiles of rFIXFc in plasma and is able to quantify the binding of rFIXFc to Col4 in the extravascular space after an intravenous dose of 50 IU/kg rFIXFc in a male population. Our model predicts that the total AUC of rFIXFc bound to Col4 in the extravascular space is approximately 19 times higher compared to the AUC of rFIXFc in plasma. This suggests that rFIXFc present in the extravascular compartment may play an important role in achieving hemostasis after rFIXFc administration. Further studies on extravascular distribution of rFIXFc and the distribution profile of other EHL-FIX concentrates are needed to evaluate the predictions of our PBPK model and to investigate its clinical relevance., (© 2024 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The study of metal ion's role in the biological processes of Alzheimer's disease has spurred investigations into the coordination chemistry of amyloid beta peptide and its fragments. Nano-electrospray ionization mass spectrometry (nESI-MS) has been utilized to examine the stabilization of bound anions on multiprotein complexes without bulk solvent. However, the effects of anions on metal ion binding interactions with amyloid beta peptide have not been explored. This study directly examined metal-peptide complexes using nESI-MS and investigated the effects of various anions on the binding ratio and stability of these complexes from ammonium salt solutions. The results indicate that different anions have distinct effects on the binding ratio and stability of various metal-peptide complexes. Of these, the bicarbonate ion exhibits the highest binding ratios for metal-peptide complexes, while binding ratios for these complexes in phosphate are comparatively low. Our results suggest that acetate, formate, bicarbonate, and phosphate have weak affinities and act as weak stabilizers of the metal-peptide complex structure in the gas phase. Intriguingly, chloride and sulfate act as stabilizers of the metal-peptide complex in the gas phase. The rank order determined from these data is substantially different from the Hofmeister salt series in solution. Although this outcome was anticipated due to the reduced influence of anions and water solvation, our findings correlate well with expected anion binding in solution and emphasize the importance of both hydration layer and anion-metal-peptide binding effects for Hofmeister-type stabilization in solution. This approach proved useful in examining the interactions between metal ions and amyloid beta peptide, which are relevant to Alzheimer's disease, using direct ESI-MS., (© 2024 The Author(s). Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Background and Purpose: Wnt binding to Frizzleds (FZD) is a crucial step that leads to the initiation of signalling cascades governing multiple processes during embryonic development, stem cell regulation and adult tissue homeostasis. Recent efforts have enabled us to shed light on Wnt-FZD pharmacology using overexpressed HEK293 cells. However, assessing ligand binding at endogenous receptor expression levels is important due to differential binding behaviour in a native environment. Here, we study FZD paralogue, FZD 7 , and analyse its interactions with Wnt-3a in live CRISPR-Cas9-edited SW480 cells typifying colorectal cancer., Experimental Approach: SW480 cells were CRISPR-Cas9-edited to insert a HiBiT tag on the N-terminus of FZD 7 , preserving the native signal peptide. These cells were used to study eGFP-Wnt-3a association with endogenous and overexpressed HiBiT-FZD 7 using NanoBiT/bioluminescence resonance energy transfer (BRET) and NanoBiT to measure ligand binding and receptor internalization., Key Results: With this new assay the binding of eGFP-Wnt-3a to endogenous HiBiT-FZD 7 was compared with overexpressed receptors. Receptor overexpression results in increased membrane dynamics, leading to an apparent decrease in binding on-rate and consequently in higher, up to 10 times, calculated K d . Thus, measurements of binding affinities to FZD 7 obtained in overexpressed cells are suboptimal compared with the measurements from endogenously expressing cells., Conclusions and Implications: Binding affinity measurements in the overexpressing cells fail to replicate ligand binding affinities assessed in a (patho)physiologically relevant context where receptor expression is lower. Therefore, future studies on Wnt-FZD 7 binding should be performed using receptors expressed under endogenous promotion., (© 2023 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

The traditional formulation Hanchuan zupa granules (HCZPs) have been widely used for controlling coronavirus disease 2019 (COVID-19). However, its active components remain unknown. Here, HCZP components targeting the spike receptor-binding domain (S-RBD) of SARS-CoV-2 were investigated using a surface plasmon resonance (SPR) biosensor-based active ingredient recognition system (SPR-AIRS). Recombinant S-RBD proteins were immobilized on the SPR chip by amine coupling for the prescreening of nine HCZP medicinal herbs. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) identified gallic acid (GA) and methyl gallate (MG) from Rosa rugosa as S-RBD ligands, with K D values of 2.69 and 0.95 μM, respectively, as shown by SPR. Molecular dynamics indicated that GA formed hydrogen bonds with G496, N501, and Y505 of S-RBD, and MG with G496 and Y505, inhibiting S-RBD binding to angiotensin-converting enzyme 2 (ACE2). SPR-based competition analysis verified that both compounds blocked S-RBD and ACE2 binding, and SPR demonstrated that GA and MG bound to ACE2 (K D  = 5.10 and 4.05 μM, respectively), suggesting that they blocked the receptor and neutralized SARS-CoV-2. Infection with SARS-CoV-2 pseudovirus showed that GA and MG suppressed viral entry into 293T-ACE2 cells. These S-RBD inhibitors have potential for drug design, while the findings provide a reference on HCZP composition and its use for treating COVID-19., (© 2024 John Wiley & Sons Ltd.)

Toll-like receptors (TLRs) are innate immune sensors for the presence of pathogens and endogenous danger signals. TLR activation results in conserved intracellular signaling events that orchestrate inflammation and antimicrobial defense. While the identity and interplay of key TLR signaling components are well established, how these largely cytosolic proteins are physically connected is not well understood. For the activation of conserved intracellular signaling events, most TLRs engage the adapter MyD88 (myeloid differentiation primary response 88), which assembles into higher-order protein complexes, myddosomes. In their recent publication, Fisch et al. present evidence that oligomeric myddosomes detach from initiating TLRs and evolve into larger scaffolds that dynamically assemble not only proximal but also distal cytosolic elements required to execute the entire cascade of the TLR-MyD88 signaling pathway. Coinciding with decline in TLR signaling over time, myddosomes progressively recruit autophagy machinery that mediates myddosome clearance. These findings expand the current understanding of TLR signaling by positioning myddosomes as the central structural element that physically assembles the key executors and regulators of TLR-MyD88-dependent intracellular signaling cascades., (© 2024 the Australian and New Zealand Society for Immunology, Inc.)

Biofilm formation by Staphylococcus aureus is a major challenge in clinical settings due to its role in persistent infections. The AgrA protein, a key regulator in biofilm development, is a promising target for therapeutic intervention. This study investigates the antibiofilm potential of halogenated phenazine compounds by targeting AgrA and explores their molecular interactions to provide insights for drug development. We employed molecular docking, molecular dynamics simulations, and computational mutagenesis to evaluate the binding of halogenated phenazine compounds (C1 to C7, HP, and HP-14) to AgrA. Binding free energy analysis was performed to assess the affinity of these compounds for the AgrA-DNA complex. Additionally, the impact of these compounds on AgrA's structural conformation and salt bridge interactions was examined. The binding-free energy analysis revealed that all compounds enhance binding affinity compared to the Apo form of AgrA, which has a Δ G bind of -80.75 kcal/mol. The strongest binding affinities were observed with compounds C7 (-113.84 kcal/mol), HP-14 (-115.23 kcal/mol), and HP (-112.28 kcal/mol), highlighting their effectiveness. Molecular dynamics simulations demonstrated that these compounds bind at the hydrophobic cleft of AgrA, disrupting essential salt bridge interactions between His174-Glu163 and His174-Glu226. This disruption led to structural conformational changes and reduced DNA binding affinity, aligning with experimental findings on biofilm inhibition. The halogenated phenazine compounds effectively inhibit biofilm formation by targeting AgrA, disrupting its DNA-binding function. The study supports the potential of these compounds as antibiofilm agents and provides a foundation for rational drug design targeting the AgrA-DNA interaction. Future research should focus on further optimizing these lead compounds and exploring additional active sites on AgrA to develop novel treatments for biofilm-associated infections., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Prince Manu et al.)

In binding free energy calculations, simulations must sample all relevant conformations of the system in order to obtain unbiased results. For instance, different ligands can bind to different metastable states of a protein, and if these protein conformational changes are not sampled in relative binding free energy calculations, the contribution of these states to binding is not accounted for and thus calculated binding free energies are inaccurate. In this work, we investigate the impact of different beta-sectretase 1 (BACE1) protein conformations obtained from x-ray crystallography on the binding of BACE1 inhibitors. We highlight how these conformational changes are not adequately sampled in typical molecular dynamics simulations. Furthermore, we show that insufficient sampling of relevant conformations induces substantial error in relative binding free energy calculations, as judged by a variation in calculated relative binding free energies up to 2 kcal/mol depending on the starting protein conformation. These results emphasize the importance of protein conformational sampling and pose this BACE1 system as a challenge case for further method development in the area of enhanced protein conformational sampling, either in combination with binding calculations or as an endpoint correction., (© 2024 Wiley Periodicals LLC.)

Flowthrough (FT) anion exchange (AEX) chromatography is a widely used polishing step for the purification of monoclonal antibody (mAb) formats. To accelerate downstream process development, high throughput screening (HTS) tools have proven useful. In this study, the binding behavior of six monovalent mAbs (mvAbs) was investigated by HTS in batch binding mode on different AEX and mixed-mode resins at process-relevant pH and NaCl concentrations. The HTS entailed the evaluation of mvAb partition coefficients (K p ) and visualization of results in surface-response models. Interestingly, the HTS data grouped the mvAbs into either a strong-binding group or a weak-binding/FT group independent of theoretical Isoelectric point. Mapping the charged and hydrophobic patches by in silico protein surface property analyses revealed that the distribution of patches play a major role in predicting FT behavior. Importantly, the conditions identified by HTS were successfully verified by 1 mL on-column experiments. Finally, employing the optimal FT conditions (7-9 mS/cm and pH 7.0) at a mini-pilot scale (CV = 259 mL) resulted in 99% yield and a 21-23-fold reduction of host cell protein to <100 ppm, depending on the varying host cell protein (HCP) levels in the load. This work opens the possibility of using HTS in FT mode to accelerate downstream process development for mvAb candidates in early research., (© 2023 Wiley Periodicals LLC.)

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies., (© 2024 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.)

Analysis of noncovalent interactions between natural products and proteins is important for rapid screening of active ingredients and understanding their pharmacological activities. In this work, the intensity fading MALDI-TOF mass spectrometry (IF-MALDI-MS) method with improved reproducibility was implemented to investigate the binding interactions between saponins from Panax notoginseng and lysozyme. The benchmark IF-MALDI-MS experiment was established using N,N',N″-triacetylchitotriose-lysozyme as a model system. The reproducibility of ion intensities in IF-MALDI-MS was improved by scanning the whole sample deposition with a focused laser beam. The relative standard deviation (RSD) of deposition scanning IF-MALDI-MS is 5.7%. Similar decay trends of the relative intensities of notoginseng saponins against increasing amounts of lysozyme were observed for all six notoginseng saponins. The half-maximal fading concentration (FC 50 ) was calculated to quantitatively characterize the binding affinity of each ligand based on the decay curve. According to the FC 50 values obtained, the binding affinities of the six notoginseng saponins were evaluated in the following order: notoginsenoside S > notoginsenoside Fc > ginsenoside Rb1 > ginsenoside Rd > notoginsenoside Ft1 > ginsenoside Rg1. The binding order was in accordance with molecular docking studies, which showed hydrogen bonding might play a key role in stabilizing the binding interaction. Our results demonstrated that deposition scanning IF-MALDI-MS can provide valuable information on the noncovalent interactions between ligands and proteins., (© 2024 John Wiley & Sons Ltd.)

The glycosylation of macromolecules can vary both among tissue structural components and by adverse conditions, potentially providing an alternative marker of stress in organisms. Lectins are proteins that bind carbohydrate moieties and lectin histochemistry is a common method to visualize microstructures in biological specimens and diagnose pathophysiological states in human tissues known to alter glycan profiles. However, this technique is not commonly used to assess broad-spectrum changes in cellular glycosylation in response to environmental stressors. In addition, the binding of various lectins has not been studied in elasmobranchs (sharks, skates, and rays). We surveyed the binding tissue structure specificity of 14 plant-derived lectins, using both immunoblotting and immunofluorescence, in the pectoral fins of neonate little skates (Leucoraja erinacea). Skates were reared under present-day or elevated (+5°C above ambient) temperature regimes and evaluated for lectin binding as an indicator of changing cellular glycosylation and tissue structure. Lectin labeling was highly tissue and microstructure specific. Dot blots revealed no significant changes in lectin binding between temperature regimes. In addition, lectins only detected in the elevated temperature treatment were Canavalia ensiformis lectin (Concanavalin A) in spindle cells of muscle and Ricinus communis agglutinin in muscle capillaries. These results provide a reference for lectin labeling in elasmobranch tissue that may aid future investigations., (© 2024 Wiley Periodicals LLC.)

Molecular vibrations and quantum tunneling may link ligand binding to the function of pharmacological receptors. The well-established lock-and-key model explains a ligand's binding and recognition by a receptor; however, a general mechanism by which receptors translate binding into activation, inactivation, or modulation remains elusive. The Vibration Theory of Olfaction was proposed in the 1930s to explain this subset of receptor-mediated phenomena by correlating odorant molecular vibrations to smell, but a mechanism was lacking. In the 1990s, inelastic electron tunneling was proposed as a plausible mechanism for translating molecular vibration to odorant physiology. More recently, studies of ligands' vibrational spectra and the use of deuterated ligand analogs have provided helpful information to study this admittedly controversial hypothesis in metabotropic receptors other than olfactory receptors. In the present work, based in part on published experiments from our laboratory using planarians as an experimental organism, I will present a rationale and possible experimental approach for extending this idea to ligand-gated ion channels., (© 2024 Wiley Periodicals LLC.)

This study describes the interaction of human serum albumin (HSA) with the binol derivative (R)-(+)-3,3'-dibromo-1,1'-bi-2-naphthol (R-BrB), which has its optical activity based on the prohibitive energetic barrier for conversion into the enantiomer (S)-(+)-3,3'-dibromo-1,1'-bi-2-naphthol (S-BrB). The objective was to assess the ability of HSA to differentiate axial enantiomers based on their binding efficiency and their impact on the CD spectra. We discovered that both enantiomers were effective ligands, and the CD signal disappeared when equimolar amounts of R-BrB and S-BrB were simultaneously added, indicating no preference for either enantiomer. The complexation resulted in a significant signal increase at 250 nm and a bathochromic effect at 370 nm. Molecular docking simulations were performed, and the lower energy pose of R-BrB was selected for DFT calculations. The theoretical CD spectra of free and complexed R-BrB were obtained and showed alterations corroborating the experimental results. By comparing the difference spectrum (HSA:R-BrB minus HSA) with the spectrum of free RBrB in water or ethyl alcohol, we concluded that the CD signal intensification was due to the increased solubilization of R-BrB upon binding to HSA., (© 2024 Wiley Periodicals LLC.)

EWSR1 (Ewing Sarcoma Related protein 1) is an RNA binding protein that is ubiquitously expressed across cell lines and involved in multiple parts of RNA processing, such as transcription, splicing, and mRNA transport. EWSR1 has also been implicated in cellular mechanisms to control formation of R-loops, a three-stranded nucleic acid structure consisting of a DNA:RNA hybrid and a displaced single-stranded DNA strand. Unscheduled R-loops result in genomic and transcription stress. Loss of function of EWSR1 functions commonly found in Ewing Sarcoma correlates with high abundance of R-loops. In this study, we investigated the mechanism for EWSR1 to recognize an R-loop structure specifically. Using electrophoretic mobility shift assays (EMSA), we detected the high affinity binding of EWSR1 to substrates representing components found in R-loops. EWSR1 specificity could be isolated to the DNA fork region, which transitions between double- and single-stranded DNA. Our data suggests that the Zinc-finger domain (ZnF) with flanking arginine and glycine rich (RGG) domains provide high affinity binding, while the RNA recognition motif (RRM) with its RGG domains offer improved specificity. This model offers a rational for EWSR1 specificity to encompass a wide range in contexts due to the DNA forks always found with R-loops., (© 2024 The Authors. Biopolymers published by Wiley Periodicals LLC.)

Trichosporon asahii is a pathogenic yeast that cause trichosporonosis. T. asahii exhibits several colony morphologies, such as white (W)- or off-white (O)-type, which may affect virulence. In this study, we compared the expression pattern of heparin-binding proteins in various colony morphologies and identified heparin-binding protein in T. asahii. Surface plasmon resonance analysis revealed that cell surface molecules attached more strongly to heparin in W- than O-type cells. We purified and identified a heparin-binding protein strongly expressed in W-type cells using heparin-Sepharose beads, named it heparin-binding protein 1 (HepBP1), and expressed Flag-tagged HepBP1 in mammalian cells. The heparin-binding ability of Flag-tagged HepBP1 was confirmed by pulldown assay using heparin-Sepharose beads. Thus, HepBP1 is a heparin-binding protein on T. asahii cell surface. These results suggest that several T. asahii cell surface proteins interact with glycosaminoglycans; therefore, they could contribute to infection., (© 2024 John Wiley & Sons Ltd.)

Bicuculline is a natural isoquinoline alkaloid that works as a gamma-aminobutyric acid receptor antagonist. It is widely found in Papaveraceae plants used in traditional Chinese medicines. Bicuculline not only has been shown to have favorable analgesic, memory-improving, and anxiolytic effects but may also cause adverse effects such as convulsions and epilepsy. A simple, rapid, and sensitive method was developed and validated for the determination of bicuculline in the plasma and tissue samples in rats by ultra-high-performance liquid chromatography-tandem mass spectrometry (MS/MS). The chromatographic separation was performed on a Thermo Scientific C18 column. The MS/MS system was operated in the positive multiple reaction monitoring mode, and the precursor-product ion transitions were optimized as m/z 368.0 → 307.1 for bicuculline and as 354.1 → 188.1 for protopine (internal standard). The linearity, accuracy, precision, recovery, and matrix effect were within acceptable limits. The experimental data showed that bicuculline was rapidly absorbed and eliminated in rats, with a moderate plasma protein binding ratio and low bioavailability. The main tissues of distribution were the kidney, liver, and brain; bicuculline could exert its pharmacological effects across the blood-brain barrier. This study has positive implications for the clinical use of herbal medicines containing bicuculline and for further development., (© 2023 John Wiley & Sons, Ltd.)