Binding Affinity Of Inhibitors Research Articles

Searching therapeutic agents for treatment of Alzheimer disease using the Monte Carlo method

Quantitative structure - activity relationships (QSARs) for the pIC50 (binding affinity) of gamma-secretase inhibitors can be constructed with the Monte Carlo method using CORAL software (http://www.insilico.eu/coral). The considerable influence of the presence of rings of various types with respect to the above endpoint has been detected. The mechanistic interpretation and the domain of applicability of the QSARs are discussed. Methods to select new potential gamma-secretase inhibitors are suggested.

Highly resistant HIV-1 proteases and strategies for their inhibition.

The virally encoded protease is an important drug target for AIDS therapy. Despite the potency of the current drugs, infections with resistant viral strains limit the long-term effectiveness of therapy. Highly resistant variants of HIV protease from clinical isolates have different combinations of about 20 mutations and several orders of magnitude worse binding affinity for clinical inhibitors. Strategies are being explored to inhibit these highly resistant mutants. The existing inhibitors can be modified by introducing groups with the potential to form new interactions with conserved protease residues, and the flexible flaps. Alternative strategies are discussed, including designing inhibitors to bind to the open conformation of the protease dimer, and inhibition of the protease-catalyzed processing of the Gag-Pol precursor.

Contribution of a low-barrier hydrogen bond to catalysis is not significant in ketosteroid isomerase.

Low-barrier hydrogen bonds (LBHBs) have been proposed to have important influences on the enormous reaction rate increases achieved by many enzymes. Δ5-3-ketosteroid isomerase (KSI) catalyzes the allylic isomerization of Δ5-3-ketosteroid to its conjugated Δ4-isomers at a rate that approaches the diffusion limit. Tyr14, a catalytic residue of KSI, has been hypothesized to form an LBHB with the oxyanion of a dienolate steroid intermediate generated during the catalysis. The unusual chemical shift of a proton at 16.8 ppm in the nuclear magnetic resonance spectrum has been attributed to an LBHB between Tyr14 Oη and C3-O of equilenin, an intermediate analogue, in the active site of D38N KSI. This shift in the spectrum was not observed in Y30F/Y55F/D38N and Y30F/Y55F/Y115F/D38N mutant KSIs when each mutant was complexed with equilenin, suggesting that Tyr14 could not form LBHB with the intermediate analogue in these mutant KSIs. The crystal structure of Y30F/Y55F/Y115F/D38N-equilenin complex revealed that the distance between Tyr14 Oη and C3-O of the bound steroid was within a direct hydrogen bond. The conversion of LBHB to an ordinary hydrogen bond in the mutant KSI reduced the binding affinity for the steroid inhibitors by a factor of 8.1–11. In addition, the absence of LBHB reduced the catalytic activity by only a factor of 1.7–2. These results suggest that the amount of stabilization energy of the reaction intermediate provided by LBHB is small compared with that provided by an ordinary hydrogen bond in KSI.

Drug Design Investigation of both Traditional FDA Drugs and POSS to Serve as an Effective HIV Protease Inhibitor

During the HIV life cycle, HIV Protease cleaves the Gag-Pol polyprotein to form new HIV virions. Since the discovery of HIV, eleven FDA protease inhibitor drugs have been approved for public use. This project utilizes computational techniques (docking, molecular dynamics) to evaluate the binding affinity of these approved inhibitors for the HIV-1 and HIV-2 proteases along with an evaluation of binding of a novel cage-like protease inhibitor. This new inhibitor is based upon Polyhedral Oligomeric Silsesquioxane (POSS) - a synthetic nanostructured hybrid molecule comprised of Oxygen, Silicon, and Hydrogen atoms. Our studies have shown that the FDA drugs are not as effective in HIV-2 Proteases as they are with HIV-1 Proteases. Furthermore, baseline measurements of POSS with various R-groups attached suggest that alcohol has the greatest propensity to optimally interact with the critical amino acid residues needed for catalysis in the HIV protease active site. The goal for both subsections of the project is to create more biologically relevant, complex R-groups that would lead to greater stability of the respective drugs in the binding pocket, in order to serve as a more effective inhibitor.

A two-component 'double-click' approach to peptide stapling.

Peptide cyclization is a useful strategy for the stabilization of short flexible peptides into well-defined bioactive conformations, thereby enhancing their ability to interact with proteins and other important biomolecules. We present an optimized procedure for the stabilization of linear diazido peptides in an α-helical conformation upon reaction with dialkynyl linkers under Cu(I) catalysis. As this procedure generates side chain-cyclized peptides bearing a bis-triazole linkage, it is referred to as 'double-click' stapling. Double-click stapling can enhance the binding affinity, proteolytic stability and cellular activity of a peptide inhibitor. A distinguishing feature of double-click stapling is the efficiency with which peptides bearing different staple linkages can be synthesized, thus allowing for modular control over peptide bioactivity. This protocol describes the double-click reaction between a 1,3-dialkynylbenzene linker and peptides that contain azidoornithine. Subsequent peptide purification and confirmation steps are also described. The entire double-click stapling protocol can be completed in ∼48 h, including two overnight lyophilization steps.

Functionalization of fluorinated benzenesulfonamides and their inhibitory properties toward carbonic anhydrases.

Substituted tri- and tetrafluorobenzenesulfonamides were designed, synthesized, and evaluated as high-affinity and isoform-selective carbonic anhydrase (CA) inhibitors. Their binding affinities for recombinant human CA I, II, VA, VI, VII, XII, and XIII catalytic domains were determined by fluorescent thermal shift assay, isothermal titration calorimetry, and a stopped-flow CO2 hydration assay. Variation of the substituents at the 2-, 3-, and 4-positions yielded compounds with a broad range of binding affinities and isoform selectivities. Several 2,4-substituted-3,5,6-trifluorobenzenesulfonamides were effective CA XIII inhibitors with high selectivity over off-target CA I and CA II. 3,4-Disubstituted-2,5,6-trifluorobenzenesulfonamides bound CAs with higher affinity than 2,4-disubstituted-3,5,6-trifluorobenzenesulfonamides. Many such fluorinated benzenesulfonamides were found to be nanomolar inhibitors of CA II, CA VII, tumor-associated CA IX and CA XII, and CA XIII. X-ray crystal structures of inhibitors bound in the active sites of several CA isoforms provide structure-activity relationship information for inhibitor binding affinities and selectivity.

A comparative study of trypsin specificity based on QM/MM molecular dynamics simulation and QM/MM GBSA calculation

Hydrogen bonding and polar interactions play a key role in identification of protein-inhibitor binding specificity. Quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) simulations combined with DFT and semi-empirical Hamiltonian (AM1d, RM1, PM3, and PM6) methods were performed to study the hydrogen bonding and polar interactions of two inhibitors BEN and BEN1 with trypsin. The results show that the accuracy of treating the hydrogen bonding and polar interactions using QM/MM MD simulation of PM6 can reach the one obtained by the DFT QM/MM MD simulation. Quantum mechanics/molecular mechanics generalized Born surface area (QM/MM-GBSA) method was applied to calculate binding affinities of inhibitors to trypsin and the results suggest that the accuracy of binding affinity prediction can be significantly affected by the accurate treatment of the hydrogen bonding and polar interactions. In addition, the calculated results also reveal the binding specificity of trypsin: (1) the amidinium groups of two inhibitors generate favorable salt bridge interaction with Asp189 and form hydrogen bonding interactions with Ser190 and Gly214, (2) the phenyl of inhibitors can produce favorable van der Waals interactions with the residues His58, Cys191, Gln192, Trp211, Gly212, and Cys215. This systematic and comparative study can provide guidance for the choice of QM/MM MD methods and the designs of new potent inhibitors targeting trypsin.

Developing High-Throughput Fluorescence-Based Assays for Measuring Kinase Inhibitor Free Energies of Binding

Understanding the specificity of kinase inhibitors has tremendous therapeutic significance. To predict inhibitor selectivity computationally, an iterative approach incorporating experimental measurements is ideal. This work describes the development of a high-throughput label-free fluorescent ligand-binding assay to measure inhibitor affinities. Taking advantage of the intrinsic fluorescence increase of a group of FDA-approved kinase inhibitors upon binding kinases, we are able to measure inhibitor binding affinity with small amounts of protein and without any fluorescent labels. This facilitates rapid characterization of a wide range of kinase inhibitors and kinase resistance mutants, within a system that can be reproduced identically in molecular dynamics simulations.

Atomistic characterization of binding modes and affinity of peptide inhibitors to amyloid-β protein

The aggregation of amyloid β-protein (Aβ) is tightly linked to the pathogenesis of Alzheimer’s disease. Previous studies have found that three peptide inhibitors (i.e., KLVFF, VVIA, and LPFFD) can inhibit Aβ aggregation and alleviate Aβ-induced neurotoxicity. However, atomic details of binding modes and binding affinities between these peptide inhibitors and Aβ have not been revealed. Here, using molecular dynamics simulations and molecular mechanics Poisson Boltzmann surface area (MM/PBSA) analysis, we examined the effect of three peptide inhibitors (KLVFF, VVIA, and LPFFD) on their sequence-specific interactions with Aβ and the molecular basis of their inhibition. All inhibitors exhibit varied binding affinity to Aβ, in which KLVFF has the highest binding affinity, whereas LPFFD has the least. MM/PBSA analysis further revealed that different peptide inhibitors have different modes of interaction with Aβ, consequently hotspot binding residues, and underlying driving forces. Specific residue-based interactions between inhibitors and Aβ were determined and compared for illustrating different binding and inhibition mechanisms. This work provides structure-based binding information for further modification and optimization of these three peptide inhibitors to enhance their binding and inhibitory abilities against Aβ aggregation.

Deformation density components analysis of fullerene-based anti-HIV drugs.

Deformation density analysis is performed on fullerene-based anti-HIV agents to investigate the influence of charge redistribution on the capability of binding to HIV enzymes. Two types of HIV inhibitors including malonic acid- and amino acid-type C60 derivatives are considered to study. Total deformation density and its components including orbital relaxation and kinetic energy pressure are obtained for C60 derivatives. The deformation natural orbitals for each component of deformation density are assessed and their amounts of charge displacement are quantified to evaluate the binding affinity of HIV inhibitors. The results show that the orbital relaxation plays a more prominent role in deformation of electron density of studied compounds. Among the considered drugs, the amino acid-type derivatives, N-(carboxymethyl)-2,5-dicarboxylic fulleropyrrolidines, show the most charge displacement. Moreover, the investigation into the deformation density of amino acid-type functional groups on C60 reveals that the connection of functional groups to the 5,6-ring junction results more displaced charge than the connection to the 6,6-ring junction.

Structure–Activity Relationships of Glycogen Phosphorylase Inhibitor FR258900 and Its Analogues: A Combined Synthetic, Enzyme Kinetics, and Computational Study

AbstractA series of O‐ or N‐cinnamoylated, p‐coumaroylated, feruloylated, phenyl, and substituted phenylpropiolated derivatives of L‐malic, 3‐hydroxypentanedioic, and L‐glutamic acids were synthesized as analogues of the natural product glycogen phosphorylase (GP) inhibitor FR258900 (2,3‐bis(4‐hydroxycinnamoyloxy)glutaric acid). These compounds proved practically inactive against rabbit muscle glycogen phosphorylase b. A structure–activity study involving previously synthesized tartaric acid analogues of FR258900 revealed that two acyl moieties must be present in the compounds to make a good inhibitor. Molecular modeling methods (docking and quantitative structure–activity relationship (QSAR) calculations) were used to understand the nature of the binding affinities of these GP inhibitors. The generated 3D models for GP–inhibitor complexes showed that both the polar allosteric site pocket and the hydrophobic pocket at the interface of the homodimeric units of GP were important for effective binding of the acyl and aromatic moieties of the inhibitors. The predictive QSAR models consist of empirical and quantum mechanics descriptors and provide good explanatory and predictive abilities (prediction coefficient Q2=0.7–0.9 when cross‐validation procedures were performed).

Drug resistance conferred by mutations outside the active site through alterations in the dynamic and structural ensemble of HIV-1 protease.

HIV-1 protease inhibitors are part of the highly active antiretroviral therapy effectively used in the treatment of HIV infection and AIDS. Darunavir (DRV) is the most potent of these inhibitors, soliciting drug resistance only when a complex combination of mutations occur both inside and outside the protease active site. With few exceptions, the role of mutations outside the active site in conferring resistance remains largely elusive. Through a series of DRV–protease complex crystal structures, inhibition assays, and molecular dynamics simulations, we find that single and double site mutations outside the active site often associated with DRV resistance alter the structure and dynamic ensemble of HIV-1 protease active site. These alterations correlate with the observed inhibitor binding affinities for the mutants, and suggest a network hypothesis on how the effect of distal mutations are propagated to pivotal residues at the active site and may contribute to conferring drug resistance.

Snake venom glutaminyl cyclases: Purification, cloning, kinetic study, recombinant expression, and comparison with the human enzyme

Among various snake venom components, glutaminyl cyclase (vQC) is one of the least understood protein family and none of its members has been purified or characterized. Here we confirmed the presence of vQC activity in a wide spectrum of venom species via enzymatic assay using a synthetic fluorogenic substrate. We have also cloned novel vQC cDNAs from seven species including Crotalus atrox. The results revealed more than 96% sequence similarities among vQCs and ∼75% sequence identities between vQCs and human secretory QC (hQC). The vQC glycoprotein of 43 kDa was isolated from C. atrox venom, and its N-terminal sequence was determined. The optimal pH range for vQC reaction was 7.5–8.0, and the enzymes were stable up to 50 °C. Similar to hQC, vQCs were substantially inactivated by 1 mM 1,10-phenanthroline but slightly affected by 20 mM EDTA, suggestive of a similar zinc-catalytic environment for these enzymes. Although their catalytic residues were highly conserved, vQCs were less susceptible to inhibition by synthetic imidazole derivatives which potently inhibited hQC. The 3D-models revealed that vQC and hQC structures display different surface charge distributions around the active sites, which might affect substrate and inhibitor binding affinities. The recombinant vQCs prepared from Escherichia coli displayed weaker substrate binding affinities relative to the native vQCs, possibly due to the lack of glycosylation. The present report offers new structural and functional insights into vQCs and sheds light on the specificity differences between vQCs and hQC.

Computational identification of significant missense mutations in AKT1 gene.

The AKT1 gene is of supreme importance in cell signaling and human cancer. In the present study, we aim to understand the phenotype variations that were believed to have the highest impact in AKT1 gene by different computational approaches. The analysis was initiated with SIFT tool followed by PolyPhen 2.0, I-Mutant 2.0, and SNPs&GO tools with the aid of 22 nonsynonymous (nsSNPs) retrieved from dbSNP. A total of five AKT1 variants such as E17K, E17S, E319G, L357P, and P388T are found to exert deleterious effects on the protein structure and function. Furthermore, the molecular docking study indicates the lesser binding affinity of inhibitor with the mutant structure than the native type. In addition, root mean square deviation and hydrogen bond details were also analyzed in the 10ns molecular dynamics simulation study. These computational evidences suggested that E17K, E17S, E319G, L357P, and P388T variants of AKT1 could destabilize the protein networks, thus causing functional deviations of protein to some extent. Moreover, the findings strongly indicate that screening for AKT1, E17K, E17S, E319G, L357P, and P388T variants may be useful for disease molecular diagnosis and also to design the potential AKT inhibitors.

Toward a Global View of the Conformational Landscape of the Human Kinome

The human genome contains about 500 protein kinases, which play a central role in the regulation of the majority of cellular pathways. Mutations in kinase genes - often resulting in dysregulation of their phosphotransferase activity - are a frequent cause of disease, including many types of cancer. Kinases are especially flexible proteins, and undergo significant conformational changes during their catalytic and regulatory cycles. This conformational heterogeneity is also of fundamental importance in determining the binding affinity and selectivity of inhibitory ligands, their susceptibility to resistance mutations, and the discovery of putative allosteric binding sites. Markov state models have recently emerged as a practical computational approach to the enumeration of protein conformational states, and can be constructed by aggregating the data from multiple, independent, short molecular dynamics trajectories in a statistical fashion. We aim to apply this technique to the entire human kinome, simulating each protein kinase catalytic domain using a range of high performance compute resources, including the distributed simulation framework, Folding@Home. In combination with recent developments in GPU-accelerated simulation algorithms, this approach allows us to obtain aggregate trajectory lengths on the order of milliseconds. An automated software pipeline provides the ability to quickly generate multiple starting configurations for each kinase, while a central database of publicly available kinase data has been set up and used for tasks such as the selection of catalytic domain sequences and the assignment of relative priorities to each kinase. In parallel with our computational approach, we are working towards expressing a diverse range of kinases in bacterial systems, and scaling up a fluorescence-based assay to plate format for direct measurement of kinase inhibitor binding affinities. Our poster will present preliminary results from these efforts.

Comprehending renin inhibitor’s binding affinity using structure-based approaches

The performance of several structure-based design (SBD) approaches in predicting the binding affinity of diverse small molecule inhibitors co-crystallized to human renin was assessed to ascertain the modeling tool and method of choice required when dealing with structure-based lead optimization projects. Most of the SBD approaches investigated here were able to provide qualitative guidance, but quantitative accuracy as well as decisive discrimination between [in]actives is still not within reach. Such an outcome suggests that the current methods need improvement to capture the overall physics of the binding phenomenon for consistent applications in a lead optimization setting.

Identification of irreversible protein splicing inhibitors as potential anti-TB drugs: insight from hybrid non-covalent/covalent docking virtual screening and molecular dynamics simulations

Tuberculosis is responsible for ~3 million deaths annually and is one of the most prevalent infectious diseases known to mankind. Despite ongoing developments in medicine, the emergence of drug resistant Mycobacterium tuberculosis remains of great interest, specifically in developing countries where medical treatment is not readily available. The aim of this study is to identify and explore the binding affinities of novel potential inhibitors that can irreversibly inhibit the intein protein via a covalent bond formation with its active site cysteine. Our search for new leads as potential protein splicing inhibitors is based on Michael acceptor-like structures since they are strong electrophiles which react covalently with the nucleophilic cysteine SH group in the enzyme active site. Structure-based virtual screening using a hybrid non-covalent/covalent docking was performed. Furthermore, molecular dynamic simulations (MD) and extensive post-dynamic analysis were performed in order to ensure the stability of the docked ligand-enzyme complexes and provide insight into the binding affinities and interaction patterns of the screened inhibitors. Interestingly, three novel hits have shown better binding affinity in comparison to experimentally determined compounds with known protein splicing inhibitory activity. MD simulations also revealed that the docked compounds are fairly stable in the protein active site. Per-residue interaction analysis has highlighted the most important active site residues contributing to the inhibitor binding.

Enhanced Stability of Monomer Fold Correlates with Extreme Drug Resistance of HIV-1 Protease

During treatment, mutations in HIV-1 protease (PR) are selected rapidly that confer resistance by decreasing affinity to clinical protease inhibitors (PIs). As these unique drug resistance mutations can compromise the fitness of the virus to replicate, mutations that restore conformational stability and activity while retaining drug resistance are selected on further evolution. Here we identify several compensating mechanisms by which an extreme drug-resistant mutant bearing 20 mutations (PR20) with >5-fold increased Kd and >4000-fold decreased affinity to the PI darunavir functions. (1) PR20 cleaves, albeit poorly, Gag polyprotein substrates essential for viral maturation. (2) PR20 dimer, which exhibits distinctly enhanced thermal stability, has highly attenuated autoproteolysis, thus likely prolonging its lifetime in vivo. (3) The enhanced stability of PR20 results from stabilization of the monomer fold. Both monomeric PR20(T26A) and dimeric PR20 exhibit Tm values 6-7.5 °C higher than those for their PR counterparts. Two specific mutations in PR20, L33F and L63P at sites of autoproteolysis, increase the Tm of monomeric PR(T26A) by ~8 °C, similar to PR20(T26A). However, without other compensatory mutations as seen in PR20, L33F and L63P substitutions, together, neither restrict autoproteolysis nor significantly reduce binding affinity to darunavir. To determine whether dimer stability contributes to binding affinity for inhibitors, we examined single-chain dimers of PR and PR(D25N) in which the corresponding identical monomer units were covalently linked by GGSSG sequence. Linking of the subunits did not appreciably change the ΔTm on inhibitor binding; thus stabilization by tethering appears to have little direct effect on enhancing inhibitor affinity.

Combinatorial Clustering of Residue Position Subsets Predicts Inhibitor Affinity across the Human Kinome

The protein kinases are a large family of enzymes that play fundamental roles in propagating signals within the cell. Because of the high degree of binding site similarity shared among protein kinases, designing drug compounds with high specificity among the kinases has proven difficult. However, computational approaches to comparing the 3-dimensional geometry and physicochemical properties of key binding site residue positions have been shown to be informative of inhibitor selectivity. The Combinatorial Clustering Of Residue Position Subsets (ccorps) method, introduced here, provides a semi-supervised learning approach for identifying structural features that are correlated with a given set of annotation labels. Here, ccorps is applied to the problem of identifying structural features of the kinase atp binding site that are informative of inhibitor binding. ccorps is demonstrated to make perfect or near-perfect predictions for the binding affinity profile of 8 of the 38 kinase inhibitors studied, while only having overall poor predictive ability for 1 of the 38 compounds. Additionally, ccorps is shown to identify shared structural features across phylogenetically diverse groups of kinases that are correlated with binding affinity for particular inhibitors; such instances of structural similarity among phylogenetically diverse kinases are also shown to not be rare among kinases. Finally, these function-specific structural features may serve as potential starting points for the development of highly specific kinase inhibitors.

Controlling enzyme inhibition using an expanded set of genetically encoded amino acids

Enzyme inhibition plays an important role in drug development, metabolic pathway regulation, and biocatalysis with product inhibition. When an inhibitor has high structural similarities to the substrate of an enzyme, controlling inhibitor binding without affecting enzyme substrate binding is often challenging and requires fine-tuning of the active site. We hypothesize that an extended set of genetically encoded amino acids can be used to design an enzyme active site that reduces enzyme inhibitor binding without compromising substrate binding. As a model case, we chose murine dihydrofolate reductase (mDHFR), substrate dihydrofolate, and inhibitor methotrexate. Structural models of mDHFR variants containing non-natural amino acids complexed with each ligand were constructed to identify a key residue for inhibitor binding and non-natural amino acids to replace the key residue. Then, we discovered that replacing the key phenylalanine residue with two phenylalanine analogs (p-bromophenylalanine (pBrF) and L-2-naphthylalanine (2Nal)) enhances binding affinity toward the substrate dihydrofolate over the inhibitor by 4.0 and 5.8-fold, respectively. Such an enhanced selectivity is mainly due to a reduced inhibitor binding affinity by 2.1 and 4.3-fold, respectively. The catalytic efficiency of the mDHFR variant containing pBrF is comparable to that of wild-type mDHFR, whereas the mDHFR variant containing 2Nal exhibits a moderate decrease in the catalytic efficiency. The work described here clearly demonstrates the feasibility of selectively controlling enzyme inhibition using an expanded set of genetically encoded amino acids.