Rank-ordering protein-ligand binding affinity by a quantum mechanics/molecular mechanics/Poisson-Boltzmann-surface area model.
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Azepines↗
Biomedical subjects
Chung F Wong
Publications and source records attributed to Chung F Wong.
Molecular dynamics simulation of laser desorption of a fragment of protein kinase A from two MALDI matrices.
We have carried out molecular dynamics simulations to study the desorption of a dephosphorylated fragment of protein kinase A from two matrices, sinapic acid (SA) and 2,5-dihydroxybenzoic acid (DHB), after laser excitation. We have examined the results as a function of the laser fluence and of the burial depth of the guest peptide in the matrices. In most cases, we found that the energy transferred from the matrix to the guest peptide was not sufficiently large to fragment the peptide. Exceptions occurred when the peptide was more buried. This finding suggested that protein analytes might be less likely to break into smaller fragments if they were placed closer to the surface of the matrix. We have also examined how likely the guest peptide could form small clusters with the matrix molecules and found that the results depended on the degree of burial of the peptide, on the laser fluence, and on which matrix was used. Generally, stable clusters were more likely to be formed for guest peptides that were more buried, at a lower laser fluence, and in the SA rather than the DHB matrix. In addition, we found that the DHB matrix was broken down more easily by the laser than the SA matrix.
Adsorption↗
Calculation of solvation free energy from quantum mechanical charge density and continuum dielectric theory.
We have combined ultrasoft pseudopotential density functional theory utilizing plane wave basis with a Poisson-Boltzmann/solvent-accessible surface area (PB/SA) model to calculate the solvation free energy of small neutral organic compounds in water. The solute charge density obtained from density functional theory was directly used in solving the Poisson-Boltzmann equation to obtain the reaction field. The polarized electronic wave function of the solute in the solvent was solved by including the reaction field in the density functional Hamiltonian. The quantum mechanical and Poisson-Boltzmann equations were solved self-consistently until the charge density and reaction field converged. Using the solute charge density directly instead of a point-charge representation permitted asymmetric distortion and spreading out of the electron cloud. Because the electron density could leave the van der Waals surface to penetrate into the high-dielectric solvent, the reaction field generated by this density was generally smaller than that obtained by using the point-charge representation. In applying this model to calculate the solvation free energy of 31 small neutral organic molecules spanning a range of 25 kcal/mol, we obtained a root-mean-square error of only 1.3 kcal/mol if we allowed one adjustable parameter to shift the calculated solvation free energy.
Algorithms↗
Direct estimation of entropy loss due to reduced translational and rotational motions upon molecular binding.
The entropic cost due to the loss of translational and rotational (T-R) degree of freedom upon binding has been well recognized for several decades. Tightly bound ligands have higher entropic costs than loosely bound ligands. Quantifying the ligand's residual T-R motions after binding, however, is not an easy task. We describe an approach that uses a reduced Hessian matrix to estimate the contributions due to translational and rotational degrees of freedom to entropy change upon molecular binding. The calculations use a harmonic model for the bound state but only include the T-R degrees of freedom. This approximation significantly speeds up entropy calculations because only 6 x 6 matrices need to be treated, which makes it easier to be used in computer-aided drug design for studying many ligands. The methodological connection with other methods is discussed as well. We tested this approximation by applying it to study the binding of ATP, peptide inhibitor (PKI), and several bound water molecules to protein kinase A (PKA). These ligands span a wide range in size. The model gave reasonable estimates of the residual T-R entropy of bound ligands or water molecules. The residual T-R entropy demonstrated a wide range of values, e.g., 4 to 16 cal/K.mol for the bound water molecules of PKA.
Adenosine Triphosphate↗
Molecular docking of balanol to dynamics snapshots of protein kinase A.
Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.
Azepines↗
Relative contributions of desolvation, inter- and intramolecular interactions to binding affinity in protein kinase systems.
In several previous studies, we performed sensitivity analysis to gauge the relative importance of different atomic partial charges in determining protein-ligand binding. In this work, we gain further insights by decomposing these results into three contributions: desolvation, intramolecular interactions, and intermolecular interactions, again based on a Poisson continuum electrostatics model. Three protein kinase-inhibitor systems have been analyzed: CDK2-deschloroflavopiridol, PKA-PKI, and LCK-PP2. Although our results point out the importance of specific intermolecular interactions to the binding affinity, they also reveal the remarkable contributions from the solvent-mediated intramolecular interactions in some cases. Thus, it is necessary to look beyond analyzing protein-ligand interactions to understand protein-ligand recognition or to gain insights into designing ligands and proteins. In analyzing the contributions of the three components to the overall binding free energy, the PKA-PKI system with a much larger ligand was found to behave differently from the other two systems with smaller ligands. In the former case, the intermolecular interactions are very favorable, and together with the favorable solvent-mediated intramolecular interactions, they overcome the large desolvation penalties to give a favorable electrostatics contribution to the overall binding affinity. On the other hand, the other two systems with smaller ligands only present modest intermolecular interactions and they are not or are only barely sufficient to overcome the desolvation penalty even with the aid of the favorable intramolecular contributions. As a result, the binding affinity of these two systems do not or only barely benefit from electrostatics contributions.
Algorithms↗
Release of ADP from the catalytic subunit of protein kinase A: a molecular dynamics simulation study.
Substrate phosphorylation by cAMP-dependent-protein kinase A (protein kinase A, PKA) has been studied extensively. Phosphoryl transfer was found to be fast, whereas ADP release was found to be the slow, rate-limiting step. There is also evidence that ADP release may be preceded by a partially rate-limiting conformational change. However, the atomic details of the conformational change and the mode of ADP release are difficult to obtain experimentally. In this work, we studied ADP release from PKA by carrying out molecular dynamics simulations with different pulling forces applied to the ligand. The detailed ADP release pathway and the associated conformational changes were analyzed. The ADP release process was found to involve a swinging motion with the phosphate of ADP anchored to the Gly-rich loop, so that the more buried adenine base and ribose ring came out before the phosphate. In contrast to the common belief that a hinge-bending motion was responsible for the opening of the ligand-binding cleft, our simulations showed that the small lobe exhibited a large amplitude "rocking" motion when the ligand came out. The largest conformational change of the protein was observed at about the first quarter time point along the release pathway. Two prominent intermediate states were observed in the release process.
Adenosine Diphosphate↗
Finite concentration effects on diffusion-controlled reactions.
The algorithm by Northrup, Allison, and McCammon [J. Chem. Phys. 80, 1517 (1984)] has been used for two decades for calculating the diffusion-influenced rate-constants of enzymatic reactions. Although many interesting results have been obtained, the algorithm is based on the assumption that substrate-substrate interactions can be neglected. This approximation may not be valid when the concentration of the ligand is high. In this work, we constructed a simulation model that can take substrate-substrate interactions into account. We first validated the model by carrying out simulations in ways that could be compared to analytical theories. We then carried out simulations to examine the possible effects of substrate-substrate interactions on diffusion-controlled reaction rates. For a substrate concentration of 0.1 mM, we found that the diffusion-controlled reaction rates were not sensitive to whether substrate-substrate interactions were included. On the other hand, we observed significant influence of substrate-substrate interactions on calculated reaction rates at a substrate concentration of 0.1M. Therefore, a simulation model that takes substrate-substrate interactions into account is essential for reliably predicting diffusion-controlled reaction rates at high substrate concentrations, and one such simulation model is presented here.
Computer Simulation↗
Charge optimization of the interface between protein kinases and their ligands.
Examining the potential for electrostatic complementarity between a ligand and a receptor is a useful technique for rational drug design, and can demonstrate how a system prioritizes interactions when allowed to optimize its charge distribution. In this computational study, we implemented the previously developed, continuum solvent-based charge optimization theory with a simple, quadratic programming algorithm and the UHBD Poisson-Boltzmann solver. This method allows one to compute the best set of point charges for a ligand or ligand region based on the ligand and receptor shape, and the receptor partial charges, by optimizing the binding free energy obtained from a continuum-solvent model. We applied charge optimization to a fragment of the heat-stable protein kinase inhibitor (PKI) of protein kinase A (PKA), to three flavopiridol inhibitors of CDK2, and to cyclin A which interacts with CDK2 to regulate the cell cycle. We found that a combination of global (involving every charge) and local (involving only charges in a local region) optimization can give useful hints for designing better inhibitors. Although some parts of an inhibitor may already contribute significantly to binding, we found that they could still be the most important targets for modifications to obtain stronger binders. In studying the binding of flavopiridol inhibitors to CDK2, comparable binding affinity could be obtained regardless of whether the net charges of the inhibitors were constrained to -2, -1, 0, 1, or 2 during the optimization. This provides flexibility in inhibitor design when a certain net charge of the inhibitor is desired in addition to strong binding affinity. For the study of the PKA-PKI and CDK2-cyclin A interfaces, we identified residues whose charge distributions are already close to optimal and those whose charge distributions could be refined to further improve binding.
Algorithms↗
AP-2 transcription factor family member expression, activity, and regulation in human epidermal keratinocytes in vitro.
The AP-2 transcription factor family is presumed to play an important role in the regulation of the keratinocyte squamous differentiation program; however, limited functional data are available to support this. In the present study, the activity and regulation of AP-2 were examined in differentiating human epidermal keratinocytes. We report that (1) AP-2 transcriptional activity decreases in differentiated keratinocytes but remains unchanged in differentiation-insensitive squamous cell carcinoma cell lines, (2) diminished AP-2 transcriptional activity is associated with a loss of specific DNA-bound AP-2 complexes, and (3) there is an increase in the ability of cytoplasmic extracts, derived from differentiated keratinocytes, to phosphorylate AP-2 alpha and AP-2 beta when cells differentiate. In contrast, extracts from differentiation-insensitive squamous cell carcinoma cells are unable to phosphorylate AP-2 proteins. Finally, the phosphorylation of recombinant AP-2 alpha by cytosolic extracts from differentiated keratinocytes is associated with decreased AP-2 DNA-binding activity. Combined, these data indicate that AP-2 trans-activation and DNA-binding activity decrease as keratinocytes differentiate, and that this decreased activity is associated with an enhanced ability to phosphorylate AP-2 alpha and beta.
Blotting, Western↗
A computational model of binding thermodynamics: the design of cyclin-dependent kinase 2 inhibitors.
The cyclin-dependent protein kinases are important targets in drug discovery because of their role in cell cycle regulation. In this computational study, we have applied a continuum solvent model to study the interactions between cyclin-dependent kinase 2 (CDK2) and analogues of the clinically tested anticancer agent flavopiridol. The continuum solvent model uses Coulomb's law to account for direct electrostatic interactions, solves the Poisson equation to obtain the electrostatic contributions to solvation energy, and calculates scaled solvent-accessible surface area to account for hydrophobic interactions. The computed free energy of binding gauges the strength of protein-ligand interactions. Our model was first validated through a study on the binding of a number of flavopiridol derivatives to CDK2, and its ability to identify potent inhibitors was observed. The model was then used to aid in the design of novel CDK2 inhibitors with the aid of a computational sensitivity analysis. Some of these hypothetical structures could be significantly more potent than the lead compound flavopiridol. We applied two approaches to gain insights into designing selective inhibitors. One relied on the comparative analysis of the binding pocket for several hundred protein kinases to identify the parts of a lead compound whose modifications might lead to selective compounds. The other was based on building and using homology models for energy calculations. The homology models appear to be able to classify ligand potency into groups but cannot yet give reliable quantitative results.
Binding Sites↗
Brownian dynamics simulation of helix-capping motifs.
Helix-capping motifs are believed to play an important role in stabilizing alpha-helices and defining helix start and stop signals. We performed microsecond scale Brownian dynamics simulations to study ten XAAD sequences, with X = (A,E,I,L,N,Q,S,T,V,Y), to examine their propensity to form helix capping motifs and correlate these results with those obtained from analyzing a structural database of proteins. For the widely studied capping box motif S**D, where the asterisk can be any amino acid residue, the simulations suggested that one of the two hydrogen bonds proposed earlier as a stabilizing factor might not be as important. On the other hand, side-chain interactions between the capping residue and the third residue downstream on the polypeptide chain might also play a role in stabilizing this motif. These results are consistent with explicit-solvent molecular dynamics simulations of two capping box motifs found in the proteins BPTI and alpha-dendrotoxin. Principal component analysis of the SAAD trajectory showed that the first three principal components, after those corresponding to translational-rotational motion were removed, accounted for more than half of the conformational fluctuations. The first component separated the conformational space into two parts with the all-helical conformation and the capping box motif lying largely in one part. The second component, on the other hand, could be used to describe conformational transitions between the all-helical form and the capping box motif.
Amino Acid Motifs↗
Brownian dynamics simulations of ion atmospheres around polyalanine and B-DNA: effects of biomolecular dielectric.
We have extended an earlier Brownian dynamics simulation algorithm for simulating the structural dynamics of ions around biomolecules to accommodate dielectric inhomogeneity. The electrostatic environment of a biomolecule immersed in water was obtained by numerically solving the Poisson equation with the biomolecule treated as a low dielectric region and the solvent treated as a high dielectric region. Instead of using the mean-field type approximations of ion interactions as in the Poisson-Boltzmann model, the ions were treated explicitly by allowing them to evolve dynamically under the electrostatic field of the biomolecule. This model thus accounts for ion-ion correlations and the finite-size effects of the ions. For a 13-residue alpha-helical polyalanine and a 12-base-pair bp B-form DNA, we found that the choice of the dielectric constant of the biomolecule has much larger effects on the mean ionic structure around the biomolecule than on the fluctuational and dynamical properties of the ions surrounding the biomolecule.
Algorithms↗
Protein simulation and drug design.
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Computer Simulation↗
Protein flexibility and computer-aided drug design.
Although computational techniques are increasingly being used in computer-aided drug design, the effects due to protein flexibility are still ignored in many applications. This review revisits rigorous statistical mechanical methods for predicting binding affinity, discusses some recent developments for improving their speed and reliability, and examines faster approximate models for facilitating virtual screening and lead optimization.
Computational Biology↗
Designing specific protein kinase inhibitors: insights from computer simulations and comparative sequence/structure analysis.
Protein kinases are important targets for designing therapeutic drugs. We describe here a computational approach to extend the usefulness of a single protein-inhibitor structure in aiding the design of protein kinase inhibitors. This approach is based on using sensitivity analysis to identify the most significant functional groups of a lead compound in accounting for binding affinity and on using comparative sequence/structure analysis to examine whether these functional groups would present specificity. A sensitivity analysis study is similar to genetic or chemical modification experiments in which specific features of a lead compound are modified to examine whether they affect properties such as binding affinity. In this study, the binding affinity was estimated by using an implicit-solvent model in which the electrostatic contributions were obtained by solving the Poisson equation, and the hydrophobic effects were accounted for by using surface-area-dependent terms. The comparative sequence/structure analysis involves the study of the amino acid distributions of a large number of protein kinases (384 in this study) near the ligand-binding sites. This analysis provides useful guiding principles for designing specific inhibitors targeted towards a particular kinase. Here, we illustrate the utility of these computational approaches by applying them to identify the determinants of the recognition between the protein kinase A and two of its inhibitors. One inhibitor, balanol, binds to the ATP-binding pocket. The other, protein kinase inhibitor, binds to the substrate-binding site. These analyses have helped to construct pharmacophore models for mining new drug leads from small-molecule libraries and for suggesting how a lead compound or a peptide inhibitor may be modified to generate selective inhibitors.
Azepines↗