Aromatic Esters of Bicyclic Amines as Antimicrobials against Streptococcus pneumoniae

A double approach was followed in the search of novel inhibitors of the surface choline‐binding proteins (CBPs) of Streptococcus pneumoniae (pneumococcus) with antimicrobial properties. First, a library of 49 rationally‐designed esters of alkyl amines was screened for their specific binding to CBPs. The best binders, being esters of bicyclic amines (EBAs), were then tested for their in vitro effect on pneumococcal growth and morphology. Second, the efficiency of EBA‐induced CBP inhibition was enhanced about 45 000‐fold by multivalency effects upon synthesizing a poly(propylene imine) dendrimer containing eight copies of an atropine derivative. Both approaches led to compounds that arrest bacterial growth, dramatically decrease cell viability, and exhibit a protection effect in animal disease models, demonstrating that the pneumococcal CBPs are adequate targets for the discovery of novel antimicrobials that overcome the currently increasing antimicrobial resistance issues.     

Fragment‐based quantum mechanical calculation of protein–protein binding affinities

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE‐GMFCC) method has been successfully utilized for efficient linear‐scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE‐GMFCC method for calculation of binding affinity of Endonuclease colicin–immunity protein complex. The binding free energy changes between the wild‐type and mutants of the complex calculated by EE‐GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6‐31G*‐D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein–protein binding affinities. Moreover, the self‐consistent calculation of PB solvation energy is required for accurate calculations of protein–protein binding free energies. This study demonstrates that the EE‐GMFCC method is capable of providing reliable prediction of relative binding affinities for protein–protein complexes. © 2018 Wiley Periodicals, Inc.     

SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

Structure‐based virtual screening usually involves docking of a library of chemical compounds onto the functional pocket of the target receptor so as to discover novel classes of ligands. However, the overall success rate remains low and screening a large library is computationally intensive. An alternative to this “ab initio” approach is virtual screening by binding homology search. In this approach, potential ligands are predicted based on similar interaction pairs (similarity in receptors and ligands). SPOT‐Ligand is an approach that integrates ligand similarity by Tanimoto coefficient and receptor similarity by protein structure alignment program SPalign. The method was found to yield a consistent performance in DUD and DUD‐E docking benchmarks even if model structures were employed. It improves over docking methods (DOCK6 and AUTODOCK Vina) and has a performance comparable to or better than other binding‐homology methods (FINDsite and PoLi) with higher computational efficiency. The server is available at http://sparks-lab.org . © 2016 Wiley Periodicals, Inc.     

Fast and accurate predictions of binding free energies using MM‐PBSA and MM‐GBSA

In the drug discovery process, accurate methods of computing the affinity of small molecules with a biological target are strongly needed. This is particularly true for molecular docking and virtual screening methods, which use approximated scoring functions and struggle in estimating binding energies in correlation with experimental values. Among the various methods, MM‐PBSA and MM‐GBSA are emerging as useful and effective approaches. Although these methods are typically applied to large collections of equilibrated structures of protein‐ligand complexes sampled during molecular dynamics in water, the possibility to reliably estimate ligand affinity using a single energy‐minimized structure and implicit solvation models has not been explored in sufficient detail. Herein, we thoroughly investigate this hypothesis by comparing different methods for the generation of protein‐ligand complexes and diverse methods for free energy prediction for their ability to correlate with experimental values. The methods were tested on a series of structurally diverse inhibitors of Plasmodium falciparum DHFR with known binding mode and measured affinities. The results showed that correlations between MM‐PBSA or MM‐GBSA binding free energies with experimental affinities were in most cases excellent. Importantly, we found that correlations obtained with the use of a single protein‐ligand minimized structure and with implicit solvation models were similar to those obtained after averaging over multiple MD snapshots with explicit water molecules, with consequent save of computing time without loss of accuracy. When applied to a virtual screening experiment, such an approach proved to discriminate between true binders and decoy molecules and yielded significantly better enrichment curves. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Carbohydrate Coated Polymer Particles: Preparation and Protein-binding Studies

A facile and effective organic synthesis route was provided for preparation of the carbohydrate coated polymer small particles. First, amino‐activated particles were prepared from PAN (polyacrylonitrile) by the heterogeneous cross‐linking method, then the amino groups on the particle were converted into hydrazide groups by N‐alkylation and hydrazine activation, meanwhile the length of linker was prolonged to the designed value. FTIR (Fourier Transform Infrared Spectroscopy) was used to study the reactions in the synthesis steps and to optimize part of the synthesis conditions. Two carbohydrates (maltose and heparin) were then directly coupled to the hydrazide‐activated particles in a relative high yield, the obtained particles were used to interact with BSA (bovine serum albumin) and typical heparin‐binding proteins. All of these particles had some nonspecific interactions with proteins and heparin coated particles showed additional strong binding ability with the heparin‐binding proteins. Data also showed that a longer linker length not only weakened nonspecific interaction but also increased the specific binding ability. As the carbohydrate coated particles are independent, flexible and easily detectable, they should be good acceptors for the diverse bioactive studies of carbohydrates.     

Computational analysis of the cathepsin B inhibitors activities through LR‐MMPBSA binding affinity calculation based on docked complex

Cathepsin B, a ubiquitous lysosomal cysteine protease, is involved in many biological processes related to several human diseases. Inhibitors targeting the enzyme have been investigated as possible diseases treatments. A set of 37 compounds were recently found active in a high throughput screening assay to inhibit the catalytic activity of Cathepsin B, with chemical structures and biological test results available to the public in the PubChem BioAssay Database (AID 820). In this study, we compare these experimental activities to the results of theoretical predictions from binding affinity calculation with a LR‐MM‐PNSA approach based on docked complexes. Strong correlations (r² = 0.919 and q² = 0.887 for the best) are observed between the theoretical predictions and experimental biological activity. The models are cross‐validated by four independent predictive experiments with randomly split compounds into training and test sets. Our results also show that the results based on protein dimer show better correlations with experimental activity when compared to results based on monomer in the in silico calculations. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

Electrokinetic chromatographic estimation of the enantioselective binding of nomifensine to human serum albumin and total plasma proteins

This report is the first evidence of enantioselective binding of nomifensine to human serum albumin (HSA) and plasma proteins. The overall process with HSA included: (i) consistent experimental design along two independent sessions; (ii) incubation of nomifensine–HSA designed mixtures; (iii) ultrafiltration for separating the unbound enantiomers fraction; (iv) electrokinetic chromatography (EKC) using heptakis‐2,3,6‐tri‐O‐methyl‐β‐cyclodextrin as chiral selector to provide experimental data for enantiomers (first, E1, and second, E2, eluted ones); and (v) a recent direct equation allowing univariate tests and robust statistics to provide consistent parameters and uncertainty. A significant enantioselectivity to HSA (2.7 ± 0.1) was encountered, related to a 1:1 stoichiometry and log affinity constants of 3.24 ± 0.10 and 3.67 ± 0.08 for E1 and E2, respectively. The protein binding (PB) estimated at physiological concentration levels was 40 ± 5 and 63 ± 4% for E1 and E2, respectively. The use of synthetic human sera allowed in vitro estimation of the total plasma PB for the racemate (61 ± 5%; coincident with in vivo values), and its enantiomers (58 ± 7 and 64 ± 4% for E1 and E2, respectively). Comparison allowed the relative importance of HSA respect to other plasma proteins for binding nomifensine to be established. Copyright © 2012 John Wiley & Sons, Ltd.     

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

The growing number of protein–ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein–ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein–ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein–ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein–ligand complex structures available to improve predictions on binding.     

The serum protein binding of pharmacologically active gallium(III) compounds assessed by hyphenated CE‐MS techniques

Transition metal‐based drugs exhibit high affinity to the soft donors of human serum proteins, especially of the high‐abundance protein HSA and of transferrin (Tf), whereas Ga(III) salts are known to bind to Tf and other iron‐containing metalloproteins, thereby interfering with the iron metabolism. Herein, the utilization of CE‐MS methods for studying the binding behavior of a therapeutic gallium nitrate formulation and the anticancer drug candidate Tris(8‐oxyquinolinato)gallium(III) to Tf and HSA under simulated physiological conditions is described. Both the Ga(III) salt and the complex were found to bind to Tf exclusively in the presence of carbonate, however, at different kinetics and to a different extent. Fe(III) induces the release of the Ga ions due to the higher affinity constant and also prevents the Ga(III) species from accessing the iron‐binding pockets of Tf. In contrast, only low affinity to HSA was observed and even when present at ca. 20‐fold excess, the majority of the Ga was attached to Tf.     

Drug efficiency indices for improvement of molecular docking scoring functions

A dataset of protein‐drug complexes with experimental binding energy and crystal structure were analyzed and the performance of different docking engines and scoring functions (as well as components of these) for predicting the free energy of binding and several ligand efficiency indices were compared. The aim was not to evaluate the best docking method, but to determine the effect of different efficiency indices on the experimental and predicted free energy. Some ligand efficiency indices, such as ΔG/W (Wiener index), ΔG/NoC (number of carbons), and ΔG/P (partition coefficient), improve the correlation between experimental and calculated values. This effect was shown to be valid across the different scoring functions and docking programs. It also removes the common bias of scoring functions in favor of larger ligands. For all scoring functions, the efficiency indices effectively normalize the free energy derived indices, to give values closer to experiment. Compound collection filtering can be done prior or after docking, using pharmacokinetic as well as pharmacodynamic profiles. Achieving these better correlations with experiment can improve the ability of docking scoring functions to predict active molecules in virtual screening. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

Density functional studies of LiN and LiN+ (N = 2–30) clusters: Structure,binding and charge distribution

Density functional calculations using B3LYP/6‐311G method have been carried out for small to medium‐sized lithium clusters (Li_N, N = 2–30). The optimized geometries of neutral and singly charged clusters, their binding energies, ionization potential, electron affinity, chemical potential, softness, hardness, highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO–LUMO) gap, and static dipole polarizability have been investigated systematically. In addition, we study the distribution of partial charges in detail using natural population analysis (NPA) in small‐sized clusters (Li_N, N = 2–10), both neutral and cationic, and demonstrate the correlation between symmetry and charge. Uniform distribution of charges in cationic clusters confirms them to be energetically more favorable than the neutral counterparts. Whenever possible, results have been compared with available data. An excellent agreement in every case supports new results as reliable predictions. A careful study of optimized geometries shows that Li₉ is derivable from bulk Li structure, i.e., body centered cubic cell, and higher clusters have optimized shapes derived from this. Further, the turnover form two to three dimensional structure occurs at cluster size N = 6. The quantity α^1/3 (α = polarizability) per atom is found to be broadly proportional to softness (per atom) as well as inverse ionization potential (per atom). The present work forms a sound basis for further study of large‐sized clusters as well as other atomic clusters. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012     

Assessment and acceleration of binding energy calculations for protein–ligand complexes by the fragment molecular orbital method

In the field of drug discovery, it is important to accurately predict the binding affinities between target proteins and drug applicant molecules. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics‐based force fields, although they cannot fully describe protein–ligand interactions. A noteworthy computational method in development involves large‐scale electronic structure calculations. Fragment molecular orbital (FMO) method, which is one of such large‐scale calculation techniques, is applied in this study for calculating the binding energies between proteins and ligands. By testing the effects of specific FMO calculation conditions (including fragmentation size, basis sets, electron correlation, exchange‐correlation functionals, and solvation effects) on the binding energies of the FK506‐binding protein and 10 ligand complex molecule, we have found that the standard FMO calculation condition, FMO2‐MP2/6‐31G(d), is suitable for evaluating the protein–ligand interactions. The correlation coefficient between the binding energies calculated with this FMO calculation condition and experimental values is determined to be R = 0.77. Based on these results, we also propose a practical scheme for predicting binding affinities by combining the FMO method with the quantitative structure–activity relationship (QSAR) model. The results of this combined method can be directly compared with experimental binding affinities. The FMO and QSAR combined scheme shows a higher correlation with experimental data (R = 0.91). Furthermore, we propose an acceleration scheme for the binding energy calculations using a multilayer FMO method focusing on the protein–ligand interaction distance. Our acceleration scheme, which uses FMO2‐HF/STO‐3G:MP2/6‐31G(d) at R_int = 7.0 Å, reduces computational costs, while maintaining accuracy in the evaluation of binding energy. © 2015 Wiley Periodicals, Inc.     

Electrostatic component of binding energy: Interpreting predictions from poisson–boltzmann equation and modeling protocols

Macromolecular interactions are essential for understanding numerous biological processes and are typically characterized by the binding free energy. Important component of the binding free energy is the electrostatics, which is frequently modeled via the solutions of the Poisson–Boltzmann Equations (PBE). However, numerous works have shown that the electrostatic component (ΔΔG_elec) of binding free energy is very sensitive to the parameters used and modeling protocol. This prompted some researchers to question the robustness of PBE in predicting ΔΔG_elec. We argue that the sensitivity of the absolute ΔΔG_elec calculated with PBE using different input parameters and definitions does not indicate PBE deficiency, rather this is what should be expected. We show how the apparent sensitivity should be interpreted in terms of the underlying changes in several numerous and physical parameters. We demonstrate that PBE approach is robust within each considered force field (CHARMM‐27, AMBER‐94, and OPLS‐AA) once the corresponding structures are energy minimized. This observation holds despite of using two different molecular surface definitions, pointing again that PBE delivers consistent results within particular force field. The fact that PBE delivered ΔΔG_elec values may differ if calculated with different modeling protocols is not a deficiency of PBE, but natural results of the differences of the force field parameters and potential functions for energy minimization. In addition, while the absolute ΔΔG_elec values calculated with different force field differ, their ordering remains practically the same allowing for consistent ranking despite of the force field used. © 2016 Wiley Periodicals, Inc.     

Fabrication of Highly Stable Glyco‐Gold Nanoparticles and Development of a Glyco‐Gold Nanoparticle‐Based Oriented Immobilized Antibody Microarray for Lectin (GOAL) Assay

The design of high‐affinity lectin ligands is critical for enhancing the inherently weak binding affinities of monomeric carbohydrates to their binding proteins. Glyco‐gold nanoparticles (glyco‐AuNPs) are promising multivalent glycan displays that can confer significantly improved functional affinity of glyco‐AuNPs to proteins. Here, AuNPs are functionalized with several different carbohydrates to profile lectin affinities. We demonstrate that AuNPs functionalized with mixed thiolated ligands comprising glycan (70 mol %) and an amphiphilic linker (30 mol %) provide long‐term stability in solutions containing high concentrations of salts and proteins, with no evidence of nonspecific protein adsorption. These highly stable glyco‐AuNPs enable the detection of model plant lectins such as Concanavalin A, wheat germ agglutinin, and Ricinus communis Agglutinin 120, at subnanomolar and low picomolar levels through UV/Vis spectrophotometry and dynamic light scattering, respectively. Moreover, we develop in situ glyco‐AuNPs‐based agglutination on an oriented immobilized antibody microarray, which permits highly sensitive lectin sensing with the naked eye. In addition, this microarray is capable of detecting lectins presented individually, in other environmental settings, or in a mixture of samples. These results indicate that glyconanoparticles represent a versatile and highly sensitive method for detecting and probing the binding of glycan to proteins, with significant implications for the construction of a variety of platforms for the development of glyconanoparticle‐based biosensors.     

Glycopeptide Mimetics Recapitulate High‐Mannose‐Type Oligosaccharide Binding and Function

High‐mannose‐type glycans (HMTGs) decorating viral spike proteins are targets for virus neutralization. For carbohydrate‐binding proteins, multivalency is important for high avidity binding and potent inhibition. To define the chemical determinants controlling multivalent interactions we designed glycopeptide HMTG mimetics with systematically varied mannose valency and spacing. Using the potent antiviral lectin griffithsin (GRFT) as a model, we identified by NMR spectroscopy, SPR, analytical ultracentrifugation, and microcalorimetry glycopeptides that fully recapitulate the specificity and kinetics of binding to Man₉GlcNAc₂Asn and a synthetic nonamannoside. We find that mannose spacing and valency dictate whether glycopeptides engage GRFT in a face‐to‐face or an intermolecular binding mode. Surprisingly, although face‐to‐face interactions are of higher affinity, intermolecular interactions are longer lived. These findings yield key insights into mechanisms involved in glycan‐mediated viral inhibition.     

The F130L mutation in streptavidin reduces its binding affinity to biotin through electronic polarization effect

Recently, Baugh et al. discovered that a distal point mutation (F130L) in streptavidin causes no distinct variation to the structure of the binding pocket but a 1000‐fold reduction in biotin binding affinity. In this work, we carry out molecular dynamics simulations and apply an end‐state free energy method to calculate the binding free energies of biotin to wild type streptavidin and its F130L mutant. The absolute binding affinities based on AMBER charge are repulsive, and the mutation induced binding loss is underestimated. When using the polarized protein‐specific charge, the absolute binding affinities are significantly enhanced. In particular, both the absolute and relative binding affinities are in line with the experimental measurements. Further investigation indicates that polarization effect is indispensable in both the generation of structural ensembles and the calculation of interaction energies. This work verifies Baugh's conjecture that electrostatic polarization effect plays an essential role in modulating the binding affinity of biotin to the streptavidin through F130L mutation. © 2013 Wiley Periodicals, Inc.     

Enhancement of the StreptoTag method for isolation of endogenously expressed proteins with complex RNA binding targets

StreptoTag is a novel affinity chromatography-based method for the isolation of high- and low-affinity RNA binding proteins. Originally it was shown possible to isolate recombinant protein from yeast or bacterial extracts using small, specific, well-characterised RNA binding targets. Here we show that using an enhanced aptamer it is not only possible to efficiently immobilise large, highly structured RNA binding targets onto the streptomycin columns but also that the StreptoTag method can be used for the isolation and purification of endogenously expressed regulatory proteins, with relatively low abundance, from eukaryotic extracts. As an example for this we uncover the identity of a karyophilic cellular protein which specifically binds to an area within the large, highly folded structure that characterises the mRNA from the unique 3' region (U3) of the mouse mammary tumour virus (MMTV) long terminal repeat (LTR). Hence, this method is now suitable for the quick and efficient isolation and identification of novel RNA binding proteins such as regulatory factors.     

Cell‐ and Tissue‐Based Proteome Profiling and Bioimaging with Probes Derived from a Potent AXL Kinase Inhibitor

AXL has been defined as a novel target for cancer therapeutics. However, only a few potent and selective inhibitors targeting AXL are available to date. Recently, our group has developed a lead compound, 9im, capable of displaying potent and specific inhibition of AXL. To further identify the cellular on/off targets, in this study, competitive affinity‐based proteome profiling was carried out, leading to the discovery of several unknown cellular targets such as BCAP31, LPCAT3, POR, TM9SF3, SCCPDH and CANX. In addition, trans‐cyclooctene (TCO) and acedan‐containing probes were developed to image the binding between 9im and its target proteins inside live cells and tumor tissues. These probes would be useful tools in the detection of AXL in various biosystems.     

Calculation of relative binding affinities of fructose 1,6-bisphosphatase mutants with adenosine monophosphate using free energy perturbation method

The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between inhibitors and protein variants. In this article, the importance of hydrophobic and hydrophilic residues to the binding of adenosine monophosphate (AMP) to the fructose 1,6-bisphosphatase (FBPase), a target enzyme for type-II diabetes, was examined by FEP method. Five mutations were made to the FBPase enzyme with AMP inhibitor bound: 113Tyr --> 113Phe, 31Thr --> 31Ala, 31Thr --> 31Ser, 177Met --> 177Ala, and 30Leu --> 30Phe. These mutations test the strength of hydrogen bonds and van der Waals interactions between the ligand and enzyme. The calculated relative free energies indicated that: 113Tyr and 31Thr play an important role, each via two hydrogen bonds affecting the binding affinity of inhibitor AMP to FBPase, and any changes in these hydrogen bonds due to mutations on the protein will have significant effect on the binding affinity of AMP to FBPase, consistent to experimental results. Also, the free energy calculations clearly show that the hydrophilic interactions are more important than the hydrophobic interactions of the binding pocket of FBPase.     

Computation of the binding affinities of catechol‐O‐methyltransferase inhibitors: Multisubstate relative free energy calculations

Alchemical free energy simulations are amongst the most accurate techniques for the computation of the free energy changes associated with noncovalent protein–ligand interactions. A procedure is presented to estimate the relative binding free energies of several ligands to the same protein target where multiple, low‐energy configurational substates might coexist, as opposed to one unique structure. The contributions of all individual substates were estimated, explicitly, with the free energy perturbation method, and combined in a rigorous fashion to compute the overall relative binding free energies and dissociation constants. It is shown that, unless the most stable bound forms are known a priori, inaccurate results may be obtained if the contributions of multiple substates are ignored. The method was applied to study the complex formed between human catechol‐O‐methyltransferase and BIA 9‐1067, a newly developed tight‐binding inhibitor that is currently under clinical evaluation for the therapy of Parkinson's disease. Our results reveal an exceptionally high‐binding affinity (K_d in subpicomolar range) and provide insightful clues on the interactions and mechanism of inhibition. The inhibitor is, itself, a slowly reacting substrate of the target enzyme and is released from the complex in the form of O‐methylated product. By comparing the experimental catalytic rate (k_cat) and the estimated dissociation rate (k_off) constants of the enzyme‐inhibitor complex, one can conclude that the observed inhibition potency (K_i) is primarily dependent on the catalytic rate constant of the inhibitor's O‐methylation, rather than the rate constant of dissociation of the complex. © 2012 Wiley Periodicals, Inc.