Binding methylarginines and methyllysines as free amino acids: a comparative study of multiple supramolecular host classes

Methylated free amino acids are an important class of targets for host-guest chemistry that have recognition properties distinct from those of methylated peptides and proteins. We present comparative binding studies for three different host classes that are each studied with multiple methylated arginines and lysines to determine fundamental structure-function relationships. The hosts studied are all anionic and include three calixarenes, two acyclic cucurbiturils, and two cleft-like hosts. We determined the binding association constants for a panel of methylated amino acids using indicator displacement assays. The calixarene hosts show weak binding that favours the higher methylation states, with the strongest binding observed for trimethyllysine. The acyclic cucurbiturils display stronger binding to the methylated amino acids, and some unique patterns of selectivity. The cleft-like hosts follow two different trends, one shallow host following similar trends to the calixarenes, and the other more closed host binding certain less-methylated amino acids stronger than their per-methylated counterparts. Molecular modeling sheds some light on the different preferences of different hosts. The results identify hosts with selectivities that will be useful for certain biomedical applications. The overall selectivity patterns are explained by a common framework that considers the topology, depth of binding pockets, and functional group participation across all host classes.

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k_off) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k_off values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures. These results show that COMBINE analysis is a promising method to guide the design of compounds that bind to flexible proteins with improved binding kinetics. </div>

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k_off) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k_off values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures, showing that COMBINE analysis is a promising method to design leads with improved kinetic rates for flexible proteins.</div>

Prediction of Drug-Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis

<div>There is growing consensus that the optimization of the kinetic parameters for drug-protein binding leads to improved drug efficacy. Therefore, computational methods have been developed to predict kinetic rates and to derive quantitative structure-kinetic relationships (QSKRs). Many of these methods are based on crystal structures of ligand-protein complexes. However, a drawback is that each protein-ligand complex is usually treated as having a single structure. Here, we present a modification of COMparative BINding Energy (COMBINE) analysis, which uses the structures of protein-</div><div>ligand complexes to predict binding parameters. We introduce the option to use multiple structures to describe each ligand-protein complex into COMBINE analysis and</div><div>apply this to study the effects of protein flexibility on the derivation of dissociation rate constants (k_off) for inhibitors of p38 mitogen-activated protein (MAP) kinase, which has a flexible binding site. Multiple structures were obtained for each ligand-protein complex by performing docking to an ensemble of protein configurations obtained from molecular dynamics simulations. Coefficients to scale ligand-protein interaction energies determined from energy-minimized structures of ligand-protein complexes were obtained by partial least squares regression and allowed the computation of k_off values. The QSKR model obtained using single, energy minimized crystal structures for each ligand-protein complex had a higher predictive power than the QSKR model obtained with multiple structures from ensemble docking. However, the incorporation of protein-ligand flexibility helped to highlight additional ligand-protein interactions that lead to longer residence times, like interactions with residues Arg67 and Asp168, which are close to the ligand in many crystal structures, showing that COMBINE analysis is a promising method to design leads with improved kinetic rates for flexible proteins.</div>

Preliminary Characterization and Comparison of Mucilage from Leaves of Hibiscus Sabdariffa L. as A Tablet Binder

The present research dealt with the extraction and characterization of mucilage from the Hibiscus sabdariffa leaves. Compared with normal binding agents such as starch and Poly Vinyl Pyrrolidine (PVP), the mucilage of Hibiscus sabdariffa (HSM) was assessed for its binding properties in tablet formulations. Tablets were formulated using HSM, starch and PVP as binders at a various concentration to evaluate its comparative binding efficiency. The compressed tablets were analyze for their quality control tests as per IP. The extracted HSM showed the characteristics of mucilage and good physicochemical properties. The FTIR and thermal analysis compatibility tests showed that there were no significant reactions between the drug and mucilage. Granule properties of various formulations were found to be comparable and have excellent flow characteristics. Post compression parameters suggested that tablets formulated with mucilage had better hardness and friability as that of the tablets prepared with starch and PVP. The formulations exhibited a better and more consistent release as compared to standard formulations using starch and PVP as a binder. The statistical analysis of in vitro dissolution profile by using DD solver software for difference factor (f1), similarity factor (f2), and Rescigno index (ξ) values also indicated promising results. The results notably indicate that binding property of HSM was at par with starch and PVP.