Ligand Binding Affinity Research Articles

Probing function in ligand-gated ion channels without measuring ion transport.

Although the functional properties of ion channels are most accurately assessed using electrophysiological approaches, a number of experimental situations call for alternative methods. Here, working on members of the pentameric ligand-gated ion channel (pLGIC) superfamily, we focused on the practical implementation of, and the interpretation of results from, equilibrium-type ligand-binding assays. Ligand-binding studies of pLGICs are by no means new, but the lack of uniformity in published protocols, large disparities between the results obtained for a given parameter by different groups, and a general disregard for constraints placed on the experimental observations by simple theoretical considerations suggested that a thorough analysis of this classic technique was in order. To this end, we present a detailed practical and theoretical study of this type of assay using radiolabeled α-bungarotoxin, unlabeled small-molecule cholinergic ligands, the human homomeric α7-AChR, and extensive calculations in the framework of a realistic five-binding-site reaction scheme. Furthermore, we show examples of the practical application of this method to tackle two longstanding questions in the field: our results suggest that ligand-binding affinities are insensitive to binding-site occupancy and that mutations to amino-acid residues in the transmembrane domain are unlikely to affect the channel's affinities for ligands that bind to the extracellular domain.

Machine-Learning- and Knowledge-Based Scoring Functions Incorporating Ligand and Protein Fingerprints.

We propose a novel machine-learning-based scoring function for drug discovery that incorporates ligand and protein structural information into a knowledge-based PMF score. Molecular docking, a simulation method for structure-based drug design (SBDD), is expected to reduce the enormous costs associated with conventional experimental methods in terms of rational drug discovery. Molecular docking has two main purposes: to predict ligand-binding structures for target proteins and to predict protein–ligand binding affinity. Currently available programs of molecular docking offer an accurate prediction of ligand binding structures for many systems. However, the accurate prediction of binding affinity remains challenging. In this study, we developed a new scoring function that incorporates fingerprints representing ligand and protein structures as descriptors in the PMF score. Here, regression analysis of the scoring function was performed using the following machine learning techniques: least absolute shrinkage and selection operator (LASSO) and light gradient boosting machine (LightGBM). The results on a test data set showed that the binding affinity delivered by the newly developed scoring function has a Pearson correlation coefficient of 0.79 with the experimental value, which surpasses that of the conventional scoring functions. Further analysis provided a chemical understanding of the descriptors that contributed significantly to the improvement in prediction accuracy. Our approach and findings are useful for rational drug discovery.

Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning

Protein–ligand interactions are increasingly profiled at high throughput using affinity selection and massively parallel sequencing. However, these assays do not provide the biophysical parameters that most rigorously quantify molecular interactions. Here we describe a flexible machine learning method, called ProBound, that accurately defines sequence recognition in terms of equilibrium binding constants or kinetic rates. This is achieved using a multi-layered maximum-likelihood framework that models both the molecular interactions and the data generation process. We show that ProBound quantifies transcription factor (TF) behavior with models that predict binding affinity over a range exceeding that of previous resources; captures the impact of DNA modifications and conformational flexibility of multi-TF complexes; and infers specificity directly from in vivo data such as ChIP-seq without peak calling. When coupled with an assay called KD-seq, it determines the absolute affinity of protein–ligand interactions. We also apply ProBound to profile the kinetics of kinase–substrate interactions. ProBound opens new avenues for decoding biological networks and rationally engineering protein–ligand interactions.

Differences in ligand-induced protein dynamics extracted from an unsupervised deep learning approach correlate with protein–ligand binding affinities

Prediction of protein–ligand binding affinity is a major goal in drug discovery. Generally, free energy gap is calculated between two states (e.g., ligand binding and unbinding). The energy gap implicitly includes the effects of changes in protein dynamics induced by ligand binding. However, the relationship between protein dynamics and binding affinity remains unclear. Here, we propose a method that represents ligand-binding-induced protein behavioral change with a simple feature that can be used to predict protein–ligand affinity. From unbiased molecular simulation data, an unsupervised deep learning method measures the differences in protein dynamics at a ligand-binding site depending on the bound ligands. A dimension reduction method extracts a dynamic feature that strongly correlates to the binding affinities. Moreover, the residues that play important roles in protein–ligand interactions are specified based on their contribution to the differences. These results indicate the potential for binding dynamics-based drug discovery.

Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors.

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand–protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

Structure–activity relationship and in silico development of c‐Met kinase inhibitors

AbstractOverexpression and concomitant drug resistance of c‐Met kinase are strongly associated with poor prognosis in gastric carcinoma. This needs the further development of existing lead compounds against c‐Met. Herein, we conducted molecular modeling studies of 4‐phenoxypyridine derivatives as c‐Met kinase inhibitors using docking, molecular dynamics (MD), and binding energy estimation to examine receptor–ligand interaction, complex stability, and binding affinity. We developed statistically significant three‐dimensional structure–activity relationship models (3D‐QSAR) to correlate the physicochemical characteristics of the inhibitors with their biological activities. The field effects of the chemical descriptors were determined as contour polyhedrons and emphasized as SAR. Thirty new compounds were designed according to the SAR scheme, and their activities were predicted using the 3D‐QSAR model. The designed compounds with higher predicted pIC50 values than the most active compounds in the dataset were subjected to absolute binding free‐energy evaluation by free energy perturbation (FEP) method.

Fatty Acid‐Binding Proteins Respond Differently When Interacting with Endogenous Cannabinoids under High Pressure

Liver‐type and intestinal fatty acid‐binding proteins (LFABP and IFABP, respectively) are both located in enterocytes, but their different functions are demonstrated by phenotypic differences observed in knockout mice for either protein. Though the two proteins are structurally similar, they differ significantly in their ligand‐binding cavities. The region of a protein with the greatest conformational variability is often found in the area surrounding the ligand‐binding cavity to enable an induced fit to a specific substrate. We used solution NMR spectroscopy while applying increasing pressure to investigate the interaction of these two proteins with ligand, in the hopes of capturing transient intermediate conformations of the protein and to identify potential on‐pathway states for substrate binding that would not otherwise be seen under standard conditions.Our initial experiments showed apo‐ and ligand‐bound IFABP remains stable under increasing pressure, up to 2500 bar. In contrast, apo‐LFABP and LFABP with anandamide completely unfolds at 1750 bar. Interestingly, the presence of oleate and arachidonic acid stabilizes LFABP, making it resistant to unfolding at high pressure. Our results show that this stabilization is ligand specific, correlating with the ligand binding affinities we determined previously. This trend suggests that specific protein/ligand interactions within the cavity are required for stability.To make a more detailed analysis of which residues are involved in binding, we generated plots of the pressure‐dependence of backbone 15N and 1H chemical shifts of LFABP and IFABP in either apo‐ or holo‐ form. Two regions of the protein were most responsive to changes in pressure as assessed by the nonlinear chemical shifts changes: i) the conformationally flexible portal and ii) a region of the ligand‐binding cavity we had previously reported as involved in the specificity of binding endocannabinoid ligands. This finding is consistent with the requirement of the conformational variability in these regions for ligand binding. We are currently performing a comprehensive analysis of these effects for the interaction of both proteins with a range of structurally related endogenous cannabinoids.

In Silico Identification of Novel Quinoline-3-carboxamide Derivatives Targeting Platelet-Derived Growth Factor Receptor

Background: Several computer-aided drug design (CADD) methods enable the design and development of novel chemical entities. Structure-based drug design (SBDD) and the knowledge of in silico methods enable the visualization of the binding process of ligands to targets and to predict the key binding pocket sites and affinity of ligands to their target macromolecules. Objective: The present study was carried out to identify novel N-2-amino-N-phenyl quinoline-3- carboxamide (AQCMs) derivatives targeting Platelet-derived growth factor receptor (PDGFR) to cure cancer using in silico approach. Materials and Methods: AQCMs were designed using ChemAxon Marvin Sketch 5.11.5 software. SwissADME and admetSAR online webserver were used to predict physicochemical properties as well as the toxicity of compounds. Ligand-receptor interactions between quinoline-3-carboxamide derivatives with the target receptor (PDB: 5GRN) were carried out using molecular docking technique by employing various software like AutoDock 1.1.2, MGL Tools 1.5.6, Discovery Studio Visualizer v 20.1.0.19295, Procheck, ProtParam tool, and PyMOL. Results: In silico results reveal that all designed compounds had acceptable pharmacokinetic properties, were found to be orally bioavailable, and less harmful. Molecules from 36 to 39 showed better docking scores as compared to standard drugs sunitinib and tasquinimod. Conclusion: Increase in binding energy and the number of H-bonds established by AQCMs with below 3.40 Å distance interactions allows a valuable starting point in order to optimize compounds for further investigation. Pharmacokinetics and toxicological profile build up the applicability of quinoline-3-carboxamide moiety as a potential new candidate for the cure of cancer that could help the medicinal chemists for additional extensive in vitro, in vivo chemical, and pharmacological investigations.

Screening of Machine Learning Predicted Inhibitors of Mur‐E Ligase

Antibiotic resistance is an ever‐growing threat, which necessitates the development of novel antibiotics. Peptidoglycan (PTG) is an ideal target for antibiotic development as it is necessary for the structural integrity of the cell and is unique to bacterial cells. Mur‐E, a cytoplasmic ligase, is an integral component of PTG synthesis and shares many conserved structures with PTG ligases in other bacterial species. Thus, inhibitors of Mur‐E are likely to be effective broad‐spectrum antibiotics. Mur‐E's role in PTG synthesis is to add meso‐A2pm or L‐lysine to a nucleotide precursor of PTG, UMAG; this reaction is facilitated by ATP hydrolysis. Residues N449, R451, K157, E220, D392 were identified in a mutagenesis study as having significant impacts on enzyme kinetics. This project combines the knowledge of each residue’s known impact on kinetics with an analytical, dynamics‐based investigation of protein structure using Essential Sit Scanning Analysis (ESSA) and ClustENMD. These two methodologies implement elastic network models of proteins to predict allosteric pockets and alternate conformations of the protein, respectively. This will give insight into which pockets are likely to be effective drug targets based on their impact on enzyme kinetics and protein dynamics; these pockets will be evaluated using a library of predicted ligands for Mur‐E to identify potential inhibitors with AutoDock Vina. By evaluating ligand binding sites and affinities, probable antibiotics can be determined. Targeting residue pockets that facilitate key Mur‐E functions, like ATP binding and substrate addition, will produce the most effective antibiotic treatment by compromising PTG production.

Protein/protein interactions in the human cytochrome P450 system

Human cytochrome P450 enzymes are heme‐containing monooxygenases that can act on diverse substrates including drugs, steroids, fatty acids, and vitamins. Most of these are microsomal enzymes that require electrons from NADPH‐cytochrome P450 reductase for catalysis. Specifically, the reductase FMN transfers electrons to the P450 heme, but little is known about the details of this transient interaction. Herein the reductase FMN domain was fused to various human P450 enzymes to promote their interaction, and the effects were measured on P450 ligand binding and catalysis occurring in the P450 active site some 15‐20 Å away from the FMN domain/P450 interaction. These FMN domain‐P450 fusion proteins were generated for both steroidogenic (CYP17A1 and CYP21A2) and drug‐metabolizing (CYP3A4, CYP2A6, and CYP2D6) P450 enzymes and compared with the respective isolated P450 enzyme. Fusion of the FMN domain does not appear to change the mode in which ligands bind in the P450 active site. Compounds that bound in the P450 active site either by displacing the heme water (type I interactions) or by directly binding the heme iron (type II interactions) in the isolated P450 enzyme, also did so in the corresponding FMN domain‐P450 fusion enzyme. However, among drug‐metabolizing enzymes fusion of the FMN domain can 1) alter the percentage of the P450 population that binds a particular ligand and 2) increase or decrease the ligand binding affinity, in a P450 and ligand‐specific way. The FMN domain appeared to have significantly less effects on steroidogenic enzymes, regardless of the ligand. Similar catalytic studies are being performed to relate these observed ligand binding trends to substrate metabolism. These current results demonstrate that the effect of the FMN domain is both isoform and ligand dependent, revealing an intricate communication between the P450 surface where the FMN domain binds and the buried P450 active site where substrates and inhibitors bind. This variability suggests that different P450 enzymes interact with the same reductase FMN domain in distinct ways. Since electron delivery is required for catalysis, this knowledge could potentially be exploited to selectively modulate the function of individual P450 enzymes to treat disease.

In Silico Investigation of Gastroprotective Compounds from n‐Butanol Fraction of Costus igneus on Antiulcer Druggable Targets

Gastric ulcer is a common gastrointestinal tract disorder characterized by discontinuation in the stomach mucosal lining and forming a painful lesion. Costus igneus is an ethnobotanical plant used in the management of gastrointestinal disturbances. This study characterized the gastroprotective bioactive compounds from n‐butanol fraction of C. igneus leaf (CIBF) and investigated their druggability effects on selected antiulcer targets using in silico approach.CIBF compounds were identified and characterized using gas chromatography‐mass spectrometry (GC‐MS) method. The 3D structures of CIBF compounds were downloaded in SDF format from Pubchem National Library of Medicine compound database and used as ligands to dock H+K+ATPase receptor (PDB ID: 5YLV), muscarinic receptor (PDB ID: 5ZHP), urease (PDB ID: 6ZJA) and histamine receptor (using Beta‐1‐adrenergic receptor [PDB ID: 2YCW] as a template). The 3D structures of the proteins were downloaded from the Protein Data Bank. Omeprazole, cimetidine and vonoprazan were used as reference drugs. The ligands and target proteins were processed and prepared for docking in pdb formats by using Chimera 1.14 and OpenBabel GUI version 2.3.2a, respectively. Multi‐targeted molecular docking was done using PyRx – Python Prescription 0.8. Physicochemical and pharmacokinetic properties were analyzed using Osiris DataWarrior version 5.5.0. Bioavailability and drug‐likeness analyses were done using the SwissADME web tool.GC‐MS analysis detected 15 suspected bioactive compounds in CIBF. Molecular docking study showed that 10‐11, (6ʹ,7ʹ) naphthoquinono [3.2] paracyclophane (NQP) had the highest ligand binding affinity for H+K+ATPase, muscarinic receptor, urease and histamine receptor when compared with the others 14 compounds, omeprazole, cimetidine and vonoprazan. Physicochemical properties of NQP did not violate the Lipinski, verber and lead likeness rules. Pharmacokinetic predictive analysis indicated that NQP possesses good oral bioavailability, high gastrointestinal absorption, blood‐brain barrier permeability and no inhibitory effect on cytochrome P450s.Findings from this study showed that NQP exhibited substantial inhibitory effects on proton pump, urease activity, muscarinic and histamine receptors. It also showed good physicochemical and pharmacokinetic properties. It is recommended that n‐butanol fraction of C. igneusleaves should be further explored as a potential source of drug lead candidate for the management of gastric ulcer disease.

The structural basis of effective LOX-1 inhibition.

Along with other scavenger receptors, splice variants of LOX-1 play an important role in modulating numerous subcellular mechanisms such as normal cell development, differentiation and growth in response to physiological stimuli. Thus, LOX-1 activity is a key regulator in determining the severity of many genetic, metabolic, cardiovascular, renal, andneurodegenerative diseases and/or cancer. Increased expression of LOX-1 precipitates pathological disorders during the aging process. Therefore, it becomes important to develop novel LOX-1 inhibitors based on its ligand binding polarity and/or affinity and disrupt the uptake of its ligand: oxidized low-density lipoproteins (ox-LDL). In this review, we shed light on the presently studied and developed novel LOX-1 inhibitors that may have potential for treatment of diseases characterized by LOX-1 activation.

Reversible domain closure modulates GlnBP ligand binding affinity.

Glutamine binding protein (GlnBP) is an Escherichia Coli periplasmic binding protein, which binds and carries glutamine to the inner membrane ATP-binding cassette (ABC) transporter. GlnBP binds the ligand with affinity around 0.1μM measured by isothermal titration calorimetry (ITC) and ligand binding stabilizes protein structure shown by its increase in thermodynamic stability. However, the molecular determinant of GlnBP ligand binding is not known. Electrostatic and hydrophobic interaction between GlnBP and glutamine are critical factors. We propose that the freedome of closure movement is also vital for ligand binding. In order to approve this hypothesis, we generate a series of mutants with different linker length that has different magnitude of domain closure. Mutants show different ligand binding affinity, which indicates that the propensity of domain closure determines the ligand binding affinity. Ligand binding triggers gradual ensemble conformational change. Structural changes upon ligand binding are monitored by combination of small angle x-ray scattering (SAXS) and NMR spectroscopy. Detailed structure characterization of GlnBP contributes to a better understanding of ligand binding and provides the structural basis for biosensor design.

Computational Analysis on the Allostery of Tryptophan Synthase: Relationship between α/β-Ligand Binding and Distal Domain Closure.

Tryptophan synthase (TRPS) is a bifunctional enzyme consisting of α and β-subunits and catalyzes the last two steps of l-tryptophan (L-Trp) biosynthesis, namely, cleavage of 3-indole-d-glycerol-3'-phosphate (IGP) into indole and glyceraldehyde-3-phosphate (G3P) in the α-subunit, and a pyridoxal phosphate (PLP)-dependent reaction of indole and l-serine (L-Ser) to produce L-Trp in the β-subunit. Importantly, the IGP binding at the α-subunit affects the β-subunit conformation and its ligand-binding affinity, which, in turn, enhances the enzymatic reaction at the α-subunit. The intersubunit communications in TRPS have been investigated extensively for decades because of the fundamental and pharmaceutical importance, while it is still difficult to answer how TRPS allostery is regulated at the atomic detail. Here, we investigate the allosteric regulation of TRPS by all-atom classical molecular dynamics (MD) simulations and analyze the potential of mean-force (PMF) along conformational changes of the α- and β-subunits. The present simulation has revealed a widely opened conformation of the β-subunit, which provides a pathway for L-Ser to enter into the β-active site. The IGP binding closes the α-subunit and induces a wide opening of the β-subunit, thereby enhancing the binding affinity of L-Ser to the β-subunit. Structural analyses have identified critical hydrogen bonds (HBs) at the interface of the two subunits (αG181-βS178, αP57-βR175, etc.) and HBs between the β-subunit (βT110 - βH115) and a complex of PLP and L-Ser (an α-aminoacrylate intermediate). The former HBs regulate the allosteric, β-subunit opening, whereas the latter HBs are essential for closing the β-subunit in a later step. The proposed mechanism for how the interdomain communication in TRPS is realized with ligand bindings is consistent with the previous experimental data, giving a general idea to interpret the allosteric regulations in multidomain proteins.

Bioactive La(III), Er(III), Yb(III), Ru(III), and Ta(V) complexes of new organometallic Schiff base: Preparation, structural characterization, antibacterial, anticancer activities, and MOE studies

AbstractBioactive complexes [La(L)(H2O)3Cl]Cl2.2H2O (1), [Er(L)(H2O)3Cl]Cl2 (2), [Yb(L)(H2O)2Cl2]Cl.4H2O (3), [Ru(L)(H2O)2Cl2]Cl.H2O (4), and [Ta(L)(H2O)Cl5] (5) have been prepared from 2‐acetylferrocene derivative Schiff base (L) and characterized with different spectroscopic tools. Infrared (IR) spectral data proved the action of the ligand as a neutral bidentate Schiff base, coordinating via N‐azomethine and N‐pyrazole. Ta(V)‐complex was eight‐coordinated complex, whereas others were six‐coordinated complexes. Molar conductance results showed that La(III) and Er(III) chelates were 1:2 electrolytes, Yb(III) and Ru(III) chelates were 1:1 electrolytes, and Ta(V) chelate was non‐electrolyte. Thermal behavior of all compounds was characterized by thermogravimetric analysis/differential thermogravimetric analysis (TG/DTG) curves with mass loss related to dehydration, coordination, and decomposition steps. Growth inhibitory effect and IC50 values of compounds toward MCF‐7 cancer cell line were measured, and the data revealed that all complexes showed higher anticancer activity than free ligand. The lowest IC50 value was 4.5 μg/mL for La(III) and Ru(III) complexes. Furthermore, almost complexes showed good activities against Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus aureus species with inhibition zone diameter in the range of 10–15 mm/mg. While, they had no antifungal activities against Candida albicans and Aspergillus flavas species. Finally, the strong binding affinity of ligand and its complexes with different protein receptors was confirmed by MOE studies.

Computer-Aided Screening of the Binding Affinities of Some Anti-Diabetic Ligands Obtained from Annona muricata Linn. (Soursop) and their Derivatives against Alpha-glucosidase

BackgroundDelaying glucose absorption into the blood – post-prandial – after food intake can play a major ameliorative role in the lifestyle and economic advantage of diabetic (DM) patients, making type 2 diabetes (T2DM), unlike type 1 (T1DM), considerably more, manageable, curable, and preventable. Identifying plant-based lead compounds that will offer much more precise and potent anti-DM activities, with lesser side effects is beneficial. MethodIn this experiment, virtual investigations were done to study the binding properties of some phytoconstituents of Annona muricata (annonaceous acetogenin and flavonoids) and their analogues, against α-glucosidase, to identify possible variations of binding affinities with changes in side-chain moieties, modification of carbon-skeleton through increased cyclisation, side-chain hydroxylation, steric-distortion of the beta-lactone ring of acetogenins, the effect of the introduction of glycoside side-chain moiety. ResultsThe acetogenins and naringenin analogues, pentahydroxy flavanone (-10.40 Kcal/mole), floro-tetrahydroxyflavan (-10.20 Kcal/mole), tetrahydroxyflavan (-10.00 Kcal/mole), naringenin (-09.40 Kcal/mole), naringenin analogue (-09.20 Kcal/mole), as well as, 15 – acetyl – guanacone – 3 (-9.20 Kcal/mole), recorded relatively high binding energies, suggesting that they bonded better as inhibitors, compared to the other compounds, and the standards, metformin (-4.60 Kcal/mole), except acarbose (-9.70 Kcal/mole). The observed major amino acid residues targeted for bonding by the ligands ranged between Arg422, Asn424, Tyr425, and Arg426. ConclusionIt was, however, observed that the addition of glycoside moiety, increasing the number of hydroxyl groups and rings within the carbon-carbon chain (which ultimately generates constitutional isomers) of α-glucosidase inhibitors could further increase their inhibitory potentials against their binding site.

Estimation of binding rates and affinities from multiensemble Markov models and ligand decoupling.

Accurate and efficient simulation of the thermodynamics and kinetics of protein-ligand interactions is crucial for computational drug discovery. Multiensemble Markov Model (MEMM) estimators can provide estimates of both binding rates and affinities from collections of short trajectories but have not been systematically explored for situations when a ligand is decoupled through scaling of non-bonded interactions. In this work, we compare the performance of two MEMM approaches for estimating ligand binding affinities and rates: (1) the transition-based reweighting analysis method (TRAM) and (2) a Maximum Caliber (MaxCal) based method. As a test system, we construct a small host-guest system where the ligand is a single uncharged Lennard-Jones (LJ) particle, and the receptor is an 11-particle icosahedral pocket made from the same atom type. To realistically mimic a protein-ligand binding system, the LJ ϵ parameter was tuned, and the system was placed in a periodic box with 860 TIP3P water molecules. A benchmark was performed using over 80 µs of unbiased simulation, and an 18-state Markov state model was used to estimate reference binding affinities and rates. We then tested the performance of TRAM and MaxCal when challenged with limited data. Both TRAM and MaxCal approaches perform better than conventional Markov state models, with TRAM showing better convergence and accuracy. We find that subsampling of trajectories to remove time correlation improves the accuracy of both TRAM and MaxCal and that in most cases, only a single biased ensemble to enhance sampled transitions is required to make accurate estimates.

The metalloprotease ADAM10 generates soluble interleukin-2 receptor alpha (sCD25) in vivo

The cytokine interleukin-2 (IL-2) plays a critical role in controlling the immune homeostasis by regulating the proliferation and differentiation of immune cells, especially T cells. IL-2 signaling is mediated via the IL-2 receptor (IL-2R) complex, which consists of the IL-2Rα (CD25), the IL-2Rβ, and the IL-2Rγ. While the latter are required for signal transduction, IL-2Rα controls the ligand-binding affinity of the receptor complex. A soluble form of the IL-2Rα (sIL-2Rα) is found constitutively in human serum, though its levels are increased under various pathophysiological conditions. The sIL-2Rα originates partly from activated T cells through proteolytic cleavage, but neither the responsible proteases nor stimuli that lead to IL-2Rα cleavage are known. Here, we show that the metalloproteases ADAM10 and ADAM17 can cleave the IL-2Rα and generate a soluble ectodomain, which functions as a decoy receptor that inhibits IL-2 signaling in T cells. We demonstrate that ADAM10 is mainly responsible for constitutive shedding of the IL-2Rα, while ADAM17 is involved in IL-2Rα cleavage upon T cell activation. In vivo, we found that mice with a CD4-specific deletion of ADAM10, but not ADAM17, show reduced steady-state sIL-2Rα serum levels. We propose that the identification of proteases involved in sIL-2Rα generation will allow for manipulation of IL-2Rα cleavage, especially as constitutive and induced cleavage of IL-2Rα are executed by different proteases, and thus offer a novel opportunity to alter IL-2 function.

In Silico Study of Secondary Metabolites in Dendrobium spp. as SARS-CoV-2 Antivirus on Main Protease (Mpro)

Infection and deaths cases by SARS-CoV-2 still increase and have not decreased significantly. Main protease (Mpro) is playing an important role in the replication of SARS-CoV-2 life cycle and causes of rapid transmission. Natural compounds are potential to be antiviral candidates with high bioavailability and low cytotoxicity. Orchids of Dendrobium genus have high diversity in Indonesia. Dendrobium has been used as traditional Chinese medicine and contains a group of secondary metabolites with antiviral activity. This study aimed to determine the potential of secondary metabolites of Dendrobium orchids as antiviral candidates against Mpro SARS-CoV-2 with in silico molecular docking. Secondary metabolites obtained from the KNApSAck and PubChem act as ligands. N3 inhibitors as native ligands were obtained from the RCSB. Mpro SARS-CoV-2 (6LU7) as a target macromolecule. Molecular docking was carried out using the online Covid-19 Docking Server using AutoDock Vina device. The most negative binding affinity value for each ligand compared to the native ligand binding affinity. Visualization with Discovery Studio software has been used to observe the protein amino acid residues contact for each ligand. The binding affinity of the native ligand inhibitor N3 is -7.5 kcal/mol. Based on the results of Mpro docking, three phytochemicals from Dendrobium spp., i.e., dendrocandin B, denthyrsinone, and denthyrsinol compounds have binding affinities of -7.7 kcal/mol, -7.9 kcal/mol, and -8.1 kcal/mol, respectively. It can be concluded that in Dendrobium orchid, denthyrsinol has the highest chance of binding so it has the potential to inhibit the Mpro SARS-CoV-2 activity.

An original approach to measure ligand/receptor binding affinity in non-purified samples

Several biochemical and biophysical methods are available to determine ligand binding affinities between a biological target and its ligands, most of which require purification, labelling or surface immobilisation. These measurements, however, remain challenging in regards to membrane proteins, as purification processes require their extraction from their native lipid environment, which may in turn impact receptor conformation and functionality. In this study, we have developed a novel experimental procedure using microscale thermophoresis (MST) directly from cell membrane fragments, to determine different ligand binding affinities to a membrane protein, the dopamine D2 receptor (D2R). In order to achieve this, two main challenges had to be overcome: determining the concentration of dopamine D2R in the crude sample; finding ways to minimize or account for non-specific binding of the ligand to cell fragments. Using MST, we were able to determine the D2R concentration in cell membrane fragments to approximately 36.8 ± 2.6 pmol/mg. Next, the doses-responses curves allowed for the determination of KD, to approximately 5.3 ± 1.7 nM, which is very close to the reported value. Important details of the experimental procedure have been detailed in this paper to allow the application of this novel method to various membrane proteins.