Stronger Binders Research Articles

Physics-Guided Deep Generative Model for New Ligand Discovery.

Structure-based drug discovery aims to identify small molecules that can attach to a specific target protein and change its functionality. Recently, deep learning has shown great promise in generating drug-like molecules with specific biochemical features and conditioned with structural features. However, they usually fail to incorporate an essential factor: the underlying physics which guides molecular formation and binding in real-world scenarios. In this work, we describe a physics-guided deep generative model for new ligand discovery, conditioned not only on the binding site but also on physics-based features that describe the binding mechanism between a receptor and a ligand. The proposed hybrid model has been tested on large protein-ligand complexes and small host-guest systems. Using the top-N methodology, on average more than 75% of the generated structures by our hybrid model were stronger binders than the original reference ligand. All of them had higher ΔGbind (affinity) values than the ones generated by the previous state-of-the-art method by an average margin of 1.88 kcal/mol. The visualization of the top-5 ligands generated by the proposed physics-guided model and the reference deep learning model demonstrate more feasible conformations and orientations by the former. The future directions include training and testing the hybrid model on larger datasets, adding more relevant physics-based features, and interpreting the deep learning outcomes from biophysical perspectives.

Fluorescence polarization reveals a possible displacement model of competition in PRC2:RNA:DNA interactions

PRC2 is a histone methyltransferase that acts on histone subunit H3 at lysine 27 to repress chromatin state and inhibit gene expression. The interactions between PRC2 and RNA have been heavily studied in vivo and in vitro with conflicting results reported on the relationship, but there is less data on interactions between PRC2 and DNA. Fluorescence polarization-based methodology was used with various RNA and DNA species to study the binding kinetics of PRC2 with RNA and DNA. Previous data indicate that PRC2 has a relatively high affinity for DNA species that are rich in consecutive G and C nucleotides. Double-stranded DNA species with lengths of 50-60 bp were designed for this project. Fluorescence polarization binding experiments were used to identify the general binding affinity of the DNA and RNA species to PRC2 by calculating the Kd apparent for the binding curve. After the apparent binding affinities were determined, various FP-competition experiments were performed to determine if each DNA species could be competed off by an RNA species or itself, and vice versa. These results showed that the DNA species were more effective competitors although the RNA species were stronger binders. These results suggest a mechanism for RNA-mediated PRC2 regulation that could reconcile the conflicting experimental results and interpretations of past experiments. Further FP-based Kd experiments under varying salt concentrations revealed PRC2 has ionic interactions with DNA that are not seen with RNA. This suggests PRC2 has extra unique interactions with DNA, which could explain the differing effectiveness of DNA versus RNA as competitors. Altogether, the results imply that DNA has additional contacts with PRC2 that limit its displacement by RNA, allowing for RNA to guide PRC2 to its target genetic loci and then for PRC2 to deposit its methyl marks without being sequestered by RNA. Lay Summary PRC2 is a protein involved in gene expression. Its role is to repress chromatin state, inhibiting gene expression during development. This protein is vital to developmentand has been linked to multiple diseases of the body including skin cancer and other forms. When the protein is doing its job correctly, it interacts with DNA in order to repress chromatin. RNA has been shown to be vital in anchoring PRC2 in the correct spot on chromatin, but studies have shown conflicting results in how it interacts with PRC2. In order to study how PRC2 interacts with DNA and RNA, fluorescence polarization-based methodology was used with various RNA and DNA species to study their binding kinetics to PRC2 individually. After the apparent binding affinities were determined, various FP-competition experiments were performed to determine if each DNA species could be competed off by an RNA species or itself, and vice versa. The DNA species were more effective competitors although the RNA species were stronger binders. These results along with other experiments revealed PRC2 has ionic interactions with DNA that are unique to DNA, which explains how the DNA species could compete off RNA. Altogether, the results imply that DNA has additional contacts with PRC2 that limit its displacement by RNA, allowing for RNA to guide PRC2 to its target genetic loci and then for PRC2 to deposit its methyl marks without being sequestered by RNA. To see the complete thesis, please visit https://scholar.colorado.edu/concern/undergraduate_honors_theses/5x21tg835.

Physicochemical Limitations of Capillary Models Applied to High-Concentration Polymer Solutions.

Advances in binder jet printing (BJP) require the development of new binder–powder systems, for example, to increase compatibility with better performance metal alloys or to increase the strength of parts using stronger binders. The dynamics of binder absorption are principally understood through capillary models. However, validation of these models in BJP has focused on variation of powder properties. Using a design-of-experiments approach and an optical observation method to track absorption of droplets, this study tests the influence of fluid properties on absorption time against the predictions of capillary models. Properties specific to polymeric binders, such as molecular weight and entanglement state, are also considered. Capillary models are found to be generally accurate in predicting absorption time in dilute systems; however, these predictions are not accurate for highly concentrated binder solutions. The effect of polymer entanglement becomes prevalent as the solution concentration increases, which can also potentially occur as a result of increased evaporation due to powder bed heating. Specifically, concentrated solutions close to the onset of entanglement will absorb much more slowly than predicted. Future models of BJP systems must account for the possibility of polymer entanglement throughout the absorption process. Improved models will provide a more accurate understanding of the flow and solidification of the binder in the powder, allowing faster development of new binders for improved performance in printing.

Improved RAD51 binders through motif shuffling based on the modularity of BRC repeats

Exchanges of protein sequence modules support leaps in function unavailable through point mutations during evolution. Here we study the role of the two RAD51-interacting modules within the eight binding BRC repeats of BRCA2. We created 64 chimeric repeats by shuffling these modules and measured their binding to RAD51. We found that certain shuffled module combinations were stronger binders than any of the module combinations in the natural repeats. Surprisingly, the contribution from the two modules was poorly correlated with affinities of natural repeats, with a weak BRC8 repeat containing the most effective N-terminal module. The binding of the strongest chimera, BRC8-2, to RAD51 was improved by -2.4 kCal/mol compared to the strongest natural repeat, BRC4. A crystal structure of RAD51:BRC8-2 complex shows an improved interface fit and an extended β-hairpin in this repeat. BRC8-2 was shown to function in human cells, preventing the formation of nuclear RAD51 foci after ionizing radiation.

Developing and characterizing a single-domain antibody (nanobody) against human cytotoxic T-lymphocyte-associated protein 4 (hCTLA-4).

Objective(s):Cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) is the most important human immune checkpoint that modulates T cells activity and brings about immune-homeostasis. Accordingly, checkpoint inhibitor cancer therapy has been approved as a growing method to block over-expressed immune checkpoints, such as CTLA-4 receptors. Considering the competitive characteristics of single-domain antibodies with monoclonal antibodies, we tried to develop a camelid Nanobody against human CTLA-4. Materials and Methods:We have constructed the VHH gene library by using immunized-camel peripheral blood mononuclear cells and carrying out the Nested-PCR technique. VHH-library was screened by phage display technique and specific nanobodies against CTLA-4 protein were selected and amplified with bio-panning steps. Stronger binders were screened by Periplasmic Extract-ELISA, followed by estimating the complexity of the library. Specific anti-CTLA-4 Nanobody and 3hCTL55, with longer CDR3 and a higher binding rate, were selected for more assays. Results:Results revealed the existence of two different clones in the library with 108 binders. In comparison with seven different antigens, using the ELISA technique confirmed the specificity of Nanobody 3hCTL55 against human CTLA-4 antigen. We calculated Nanobody 3hCTL55 affinity for human CTLA-4 antigen at 50×10-9 M, approximately. Performing western blot and Flow-cytometry techniques showed that Nanobody 3hCTL55 was able to specifically detect and attach both commercial human CTLA-4 protein and human CTLA-4 antigen on the cell surface and in the cell lysate. Conclusion:Taken together, this developed camelid-specific anti-CTLA-4 Nanobody 3hCTL55, selected from a high-quality immune library by phage display technique, may be effective for further study about cancer diagnosis and cancer-therapy purposes.

In Silico Prediction of the Mechanism of Action of Pyriproxyfen and 4'-OH-Pyriproxyfen against A. mellifera and H. sapiens Receptors.

Background. Poisoning from pesticides can be extremely hazardous for non-invasive species, such as bees, and humans causing nearly 300,000 deaths worldwide every year. Several pesticides are recognized as endocrine disruptors compounds that alter the production of the normal hormones mainly by acting through their interaction with nuclear receptors (NRs). Among the insecticides, one of the most used is pyriproxyfen. As analogous to the juvenile hormone, the pyriproxyfen acts in the bee’s larval growth and creates malformations at the adult organism level. Methods. This work aims to investigate the possible negative effects of pyriproxyfen and its metabolite, the 4′-OH-pyriproxyfen, on human and bee health. We particularly investigated the mechanism of binding of pyriproxyfen and its metabolite with ultraspiracle protein/ecdysone receptor (USP-EcR) dimer of A. mellifera and the relative heterodimer farnesoid X receptor/retinoid X receptor alpha (FXR-RXRα) of H. sapiens using molecular dynamic simulations. Results. The results revealed that pyriproxyfen and its metabolite, the 4′-OH- pyriproxyfen, stabilize each dimer and resulted in stronger binders than the natural ligands. Conclusion. We demonstrated the endocrine interference of two pesticides and explained their possible mechanism of action. Furthermore, in vitro studies should be carried out to evaluate the biological effects of pyriproxyfen and its metabolite.

Live-Cell-Templated Dynamic Combinatorial Chemistry.

Dynamic covalent chemistry combines in a single step the screening and synthesis of ligands for biomolecular recognition. In order to do that, a chemical entity is used as template within a dynamic combinatorial library of interconverting species, so that the stronger binders are amplified due to the efficient interaction with the target. Here we employed whole A549 living cells as template in a dynamic mixture of imines, for which amplification reflects the efficient and selective interaction with the corresponding extracellular matrix. The amplified polyamine showed strong interaction with the A549 extracellular matrix in on-cell NMR experiments, while combination of NMR, SPR, and molecular dynamics simulations in model systems provided insights on the molecular recognition event. Notably, our work pioneers the use of whole living cells in dynamic combinatorial chemistry, which paves the way towards the discovery of new bioactive molecules in a more biorelevant environment.

Live‐Cell‐Templated Dynamic Combinatorial Chemistry

AbstractDynamic covalent chemistry combines in a single step the screening and synthesis of ligands for biomolecular recognition. In order to do that, a chemical entity is used as template within a dynamic combinatorial library of interconverting species, so that the stronger binders are amplified due to the efficient interaction with the target. Here we employed whole A549 living cells as template in a dynamic mixture of imines, for which amplification reflects the efficient and selective interaction with the corresponding extracellular matrix. The amplified polyamine showed strong interaction with the A549 extracellular matrix in on‐cell NMR experiments, while combination of NMR, SPR, and molecular dynamics simulations in model systems provided insights on the molecular recognition event. Notably, our work pioneers the use of whole living cells in dynamic combinatorial chemistry, which paves the way towards the discovery of new bioactive molecules in a more biorelevant environment.

Computational MHC-I epitope predictor identifies 95% of experimentally mapped HIV-1 clade A and D epitopes in a Ugandan cohort

BackgroundIdentifying immunogens that induce HIV-1-specific immune responses is a lengthy process that can benefit from computational methods, which predict T-cell epitopes for various HLA types.MethodsWe tested the performance of the NetMHCpan4.0 computational neural network in re-identifying 93 T-cell epitopes that had been previously independently mapped using the whole proteome IFN-γ ELISPOT assays in 6 HLA class I typed Ugandan individuals infected with HIV-1 subtypes A1 and D. To provide a benchmark we compared the predictions for NetMHCpan4.0 to MHCflurry1.2.0 and NetCTL1.2.ResultsNetMHCpan4.0 performed best correctly predicting 88 of the 93 experimentally mapped epitopes for a set length of 9-mer and matched HLA class I alleles. Receiver Operator Characteristic (ROC) analysis gave an area under the curve (AUC) of 0.928. Setting NetMHCpan4.0 to predict 11-14mer length did not improve the prediction (37–79 of 93 peptides) with an inverse correlation between the number of predictions and length set. Late time point peptides were significantly stronger binders than early peptides (Wilcoxon signed rank test: p = 0.0000005). MHCflurry1.2.0 similarly predicted all but 2 of the peptides that NetMHCpan4.0 predicted and NetCTL1.2 predicted only 14 of the 93 experimental peptides.ConclusionNetMHCpan4.0 class I epitope predictions covered 95% of the epitope responses identified in six HIV-1 infected individuals, and would have reduced the number of experimental confirmatory tests by > 80%. Algorithmic epitope prediction in conjunction with HLA allele frequency information can cost-effectively assist immunogen design through minimizing the experimental effort.

NMR detects molecular interactions of graphene with aromatic and aliphatic hydrocarbons in water

Polyaromatic carbon is widely held to be strongly diamagnetic and hydrophobic, with textbook van der Waals and ‘π-stacked’ binding of hydrocarbons, which disrupt their self-assembled supramolecular structures. The NMR of organic molecules sequestered by polyaromatic carbon is expected to be dominated by shielding from the orbital diamagnetism of π electrons. We report the first evidence of very different polar and magnetic behavior in water, wherein graphene remained well-dispersed after extensive dialysis and behaved as a 1H-NMR-silent ghost. Magnetic effects dominated the NMR of organic structures which interacted with graphene, with changes in spin–spin coupling, vast increase in relaxation, line broadening and decrease in NMR peak heights when bound to graphene. However, the interactions were weak, reversible and did not disrupt organic self-assemblies reliant on hydrophobic ‘π-stacking’, even when substantially sequestered on the surface of graphene by the high surface area available. Interacting assemblies of aromatic molecules retained their strongly-shielded NMR signals and remained within self-assembled structures, with slower rates of diffusion from association with graphene, but with no further shielding from graphene. Binding to graphene was selective for positively-charged organic assemblies, weaker for non-aromatic and negligible for strongly-negatively-charged molecules, presumably repelled by a negative zeta potential of graphene in water. Stronger binders, or considerable excess of weaker binders readily reversed physisorption, with no evidence of structural changes from chemisorption. The fundamental nature of these different electronic interactions between organic and polyaromatic carbon is considered with relevance to electronics, charge storage, sensor, medical, pharmaceutical and environmental research.

Impact of Amino Acids on the Isomerization of the Aluminum Tridecamer Al13.

The stability of the Keggin polycation ε-Al13 is monitored by 27Al NMR and ferron colorimetric assay upon heating aluminum aqueous solutions containing different amino acids with overall positive, negative, or no charge at pH 4.2. A focus on the effect of the amino acids on the isomerization process from ε- to δ-Al13 is made, compared and discussed as a function of the type of organic additive. Amino acids such as glycine and β-alanine, with only one functional group interacting relatively strongly with aluminum polycations, accelerate isomerization in a concentration-dependent manner. The effect of this class of amino acids is also found increasing with the pKa of their carboxylic acid moiety, from a low impact from proline up to more than a 15-fold increased rate from the stronger binders such as glycine or β-alanine. Amino acids with relatively low C-terminal pKa, but bearing additional potential binding moieties such as free alcohol (hydroxyl group) moiety of serine or the amide of glutamine, speed the isomerization comparatively and even more than glycine or β-alanine, glutamine leading to the fastest rates observed so far. With aspartic and glutamic acids, changes in aluminum speciation are faster and significant even at room temperature but rather related to the reorganization toward slow reacting complexed oligomers than to the Al13 isomerization process. The linear relation between the apparent rate constant of isomerization and the additive concentration points to a first-order process with respect to the additives. Most likely, the dominant process is an accelerated ε-Al13 dissociation, increasing the probability of δ isomer formation.

Zinc complexes of diflunisal: Synthesis, characterization, structure, antioxidant activity, and in vitro and in silico study of the interaction with DNA and albumins

From the reaction of ZnCl2 with the non-steroidal anti-inflammatory drug diflunisal (Hdifl), complex [Zn(difl-O)2(MeOH)4], 1 was formed, while in the presence of a N,N′-donor heterocyclic ligand 2,2′-bipyridylamine (bipyam), 2,2′-bipyridine (bipy), 1,10-phenanthroline (phen) and 2,2′-dipyridylketone oxime (Hpko), the complexes [Zn(difl-O,O')2(bipyam)], 2, [Zn(difl-O,O′)2(bipy)], 3, [Zn(difl-O,O′)2(phen)], 4 and [Zn(difl-O)2(Hpko)2], 5 were isolated, respectively. The complexes were characterized by physicochemical and spectroscopic techniques and the crystal structures of complexes 2, 3 and 5 were determined by X-ray crystallography. The ability of the complexes to scavenge 1,1-diphenyl-picrylhydrazyl, 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) and hydroxyl radicals and to inhibit soybean lipoxygenase was studied and the complexes were more active than free Hdifl. The interaction of the complexes with serum albumins was monitored by fluorescence emission spectroscopy and the corresponding binding constants were calculated. UV–vis spectroscopy, viscosity measurements and fluorescence emission spectroscopy for the competitive studies of the complexes with ethidium bromide were employed to investigate the interaction of the complexes with calf-thymus DNA and revealed intercalation as the most possible DNA-binding mode. Computational techniques were used to identify possible binding sites of albumins and DNA, and determine the druggability of human and bovine serum albumins with the five novel complexes. The majority of the complexes are stronger binders than the free Hdifl. This is the first study incorporating experimental and computational results to explore the binding activity of metal-NSAID complexes with DNA and serum albumins, suggesting their application as potential metallodrugs.

Drugs Against Avian Influenza A Virus: Design of Novel Sulfonate Inhibitors of Neuraminidase N1

The outbreak of avian influenza A (H5N1) virus has raised a global concern for both the animal as well as human health. Besides vaccination, that may not achieve full protection in certain groups of patients, inhibiting neuraminidase or the transmembrane protein M2 represents the main measure of controlling the disease. Due to alarming emergence of influenza virus strains resistant to the currently available drugs, development of new neuraminidase N1 inhibitors is of utmost importance. The present paper provides an overview of the recent advances in the design of new antiviral drugs against avian influenza. It also reports findings in binding free energy calculations for nine neuraminidase N1 inhibitors (oseltamivir, zanamivir, and peramivir -carboxylate, -phosphonate, and -sulfonate) using the Linear Interaction Energy method. Molecular dynamics simulations of these inhibitors were performed in a free and two bound states - the so called open and closed conformations of neuraminidase N1. Obtained results successfully reproduce the experimental binding affinities of the already known neuraminidase N1 inhibitors, i.e. peramivir being a stronger binder than zanamivir that is in turn stronger binder than oseltamivir, or phosphonate inhibitors being stronger binders than their carboxylate analogues. In addition, the newly proposed sulfonate inhibitors are predicted to be the strongest binders - a fact to be confirmed by their chemical synthesis and a subsequent test of their biological activity. Finally, contributions of individual inhibitor moieties to the overall binding affinity are explicitly evaluated to assist further drug development towards inhibition of the H5N1 avian influenza A virus.

Computational Thrombin Inhibitor Optimization

Of the plethora of computational methods for the estimation of binding free energies, molecular dynamics based alchemical approaches provide remarkable accuracy at an affordable computational cost. The computationally less expensive empirical ligand and structure based methods require training a predictive model to yield accurate free energy estimates. In the current study we utilized a combinatorial chemistry library and combined the chemoinformatic and alchemical approaches to optimize a set of known thrombin inhibitors. A confirmed ligand scaffold (D-Phe-Pro) was selected as a basis for modifications. Prior to designing new compounds, we verified the non-equilibrium alchemical free energy calculation setup on a set of inhibitors with experimentally measured binding affinities. Afterwards, a combinatorial chemistry library was constructed by modifying substituents at the ortho, meta and para positions on a benzene ring facing the S1 thrombin pocket. Navigation in the library was guided by training the Partial Least Squares based regression models using topological, structural, physicochemical descriptors and COMFA-like coordinates of the molecular electrostatic surfaces. The predicted potential binders were subjected to the alchemical free energy calculations, and, subsequently, the obtained estimates were used to update the regression models and improve prediction accuracy. Few iterations sufficed to reach convergence towards stronger binders, several of which were predicted to have a higher binding affinity than the strongest inhibitors in the initial compound set. While the newly identified ligands are to be validated in an ITC experiment, the computational workflow utilizing chemoinformatic approaches for navigation in a combinatorial chemistry library and first principles based alchemical calculations for accurate free energy estimates appears to be a powerful approach for ligand optimization.

Solid-phase synthesis and evaluation of TAR RNA targeted β-carboline–nucleoside conjugates

Four types of beta-carboline-nucleoside conjugates were synthesized. The binding affinities of these beta-carboline-nucleoside conjugates , and to TAR RNA were evaluated by affinity capillary electrophoresis. The data of binding affinities to TAR RNA show that conjugates and are stronger binders than the parent compound . Computer modeling indicates that the beta-carboline-nucleoside conjugate can fit to the UCU three-nucleotide bulge region of TAR RNA.

Supramolecular chirogenesis in zinc porphyrins: equilibria, binding properties, and thermodynamics.

Complexation mechanism, binding properties and thermodynamic parameters of supramolecular chirality induction in the achiral host molecule, syn (face-to-face conformation) ethane-bridged bis(zinc porphyrin), upon interaction with chiral monoamine and monoalcohol guests have been studied by means of the UV-vis, CD, (1)H NMR, and ESI MS techniques. It was found that the chirogenesis process includes three major equilibria steps: the first guest ligation to a zinc porphyrin subunit of the host (K(1)), syn to anti conformational switching (K(S)), and further ligation by a second guest molecule to the remaining ligand-free zinc porphyrin subunit (K(2)), thus forming the final bis-ligated species possessing supramolecular chirality. The validity of this equilibria model is confirmed by the excellent match between the calculated and experimentally observed spectral parameters of the bis-ligated species. The second ligation proceeds in a cooperative manner as K(2) > K(1) for all supramolecular systems studied, regardless of the structure of the chiral ligand used. The binding properties are highly dependent on the nature of the functional group (amines are stronger binders than alcohols) and on the structure of the chiral guests (primary and aliphatic amines have overall binding constant values greater than those of secondary and aromatic amines, respectively).