Prediction of pKa shifts in proteins using a combination of molecular mechanical and continuum solvent calculations

Identification of potential JNK3 inhibitors through virtual screening, molecular docking and molecular dynamics simulation as therapeutics for Alzheimer's disease

Alzheimer's disease (AD) is a complex neurological disorder and no effective drug is available for its treatment. Numerous pathological conditions are believed to be responsible for the initiation and development of AD including c-Jun N-terminal kinases (JNKs). The JNKs are one of the enzymes from the mitogen-activated protein kinase (MAPK) family that controls the phosphorylation of various transcription factors on serine and threonine residues, and hold significant responsibilities in tasks like gene expression, cell proliferation, differentiation, and apoptosis. Since, JNK3 is primarily expressed in the brain hence its increased levels in the brain are associated with the AD pathology promoting neurofibrillary tangles, senile plaques, neuroinflammation, and nerve cell apoptosis. The current research work is focused on the development of novel JNK inhibitors as therapeutics for AD employing a structure-based virtual screening (SBVS) approach. The ZINC database (14634052 compounds) was investigated after employing pan assay interference (PAINs), drug-likeness, and diversity picking filter to distinguish molecules interacting with JNK3 by following three docking precision criteria: High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP) & MMGBSA. Five lead molecules showed a better docking score in the range of -13.091 to -14.051 kcal/mol better than the reference compound (- 11.828 kcal/mol). The lead compounds displayed acceptable pharmacokinetic properties and were subjected to molecular dynamic simulations of 100 ns and binding free energy calculations. All the lead molecules showed stable RMSD and hydrogen bond interactions throughout the trajectory. The ∆GMM/PBSA_total score for the lead compounds ZINC220382956, ZINC147071339, ZINC207081127, ZINC205151456, ZINC1228819126, and CC-930 was calculated and found to be - 31.39, - 42.8, - 37.04, - 39.01, - 36.5, - 34.16 kcal/mol, respectively. Thus, it was concluded that the lead molecules identified in these studies have the potential to be explored as potent JNK3 inhibitors.

Recent Progress in the Endosomal Escape Mechanism and Chemical Structures of Polycations for Nucleic Acid Delivery

Nucleic acid-based therapies are seeing a spiralling surge. Stimuli-responsive polymers, especially pH-responsive ones, are gaining widespread attention because of their ability to efficiently deliver nucleic acids. These polymers can be synthesized and modified according to target requirements, such as delivery sites and the nature of nucleic acids. In this regard, the endosomal escape mechanism of polymer-nucleic acid complexes (polyplexes) remains a topic of considerable interest owing to various plausible escape mechanisms. This review describes current progress in the endosomal escape mechanism of polyplexes and state-of-the-art chemical designs for pH-responsive polymers. The importance is also discussed of the acid dissociation constant (i.e., pKa) in designing the new generation of pH-responsive polymers, along with assays to monitor and quantify the endosomal escape behavior. Further, the use of machine learning is addressed in pKa prediction and polymer design to find novel chemical structures for pH responsiveness. This review will facilitate the design of new pH-responsive polymers for advanced and efficient nucleic acid delivery.

Targeted Covalent Inhibition of Telomerase

Telomerase is a ribonuceloprotein complex responsible for maintaining telomeres and protecting chromosomal integrity. The human telomerase reverse transcriptase (hTERT) is expressed in ∼90% of cancer cells where it confers the capacity for limitless proliferation. Along with its established role in telomere lengthening, telomerase also serves noncanonical extra-telomeric roles in oncogenic signaling, resistance to apoptosis, and enhanced DNA damage response. We report a new class of natural-product-inspired covalent inhibitors of telomerase that target the catalytic active site.

Design and development of high affinity dual anticancer peptide-inhibitors against p53-MDM2/X interaction

AIMS

Inhibition of P53-MDM2/X interaction is known as an effective cancer therapy strategy. In this regard, pDI peptide was introduced previously with the potential of targeting MDM2. In this research, the large-scale peptide mutation screening was used to achieve the best sequence of pDI with the highest affinity for inhibition activity against MDM2/X.

MAIN METHODS

Three mutant peptides of pDI as dual inhibitor peptides including single mutations of pDIm/4W, pDIm/11M and double mutations of pDIdm/4W11M were presented with the high affinities to inhibit both MDM2/X. The selected mutants were then evaluated comprehensively to confirm their ability as potent MDM2/X inhibitors, using a theoretical simulation approach.

KEY FINDINGS

MD simulations analyses confirmed their dual inhibition potential against both MDM2/X interactions with p53 protein. The developed pDIm and mainly pDIdm peptides showed stable conformations over the simulation time with conserved secondary structure and effective interaction with MDM2/X by physical binding such as hydrogen bonding. Besides, umbrella sampling free energy calculation indicated higher binding energy, ΔG_binding, of pDIm-MDM2/X and pDIdm-MDM2/X compared to pDI-MDM2/X.

SIGNIFICANCE

The optimized and improved mutant pDI, pDIdm, with more effective ΔG_binding values of -30 and -25 kcal/mol to MDMX and MDM2, respectively, is recommended as a promising anticancer agent and suitable candidate for experimental evaluations.

pKa values in proteins determined by electrostatics applied to molecular dynamics trajectories

For a benchmark set of 194 measured pKa values in 13 proteins, electrostatic energy computations are performed in which pKa values are computed by solving the Poisson-Boltzmann equation. In contrast to the previous approach of Karlsberg(+) (KB(+)) that essentially used protein crystal structures with variations in their side chain conformations, the present approach (KB2(+)MD) uses protein conformations from four molecular dynamics (MD) simulations of 10 ns each. These MD simulations are performed with different specific but fixed protonation patterns, selected to sample the conformational space for the different protonation patterns faithfully. The root-mean-square deviation between computed and measured pKa values (pKa RMSD) is shown to be reduced from 1.17 pH units using KB(+) to 0.96 pH units using KB2(+)MD. The pKa RMSD can be further reduced to 0.79 pH units, if each conformation is energy-minimized with a dielectric constant of εmin = 4 prior to calculating the electrostatic energy. The electrostatic energy expressions upon which the computations are based have been reformulated such that they do not involve terms that mix protein and solvent environment contributions and no thermodynamic cycle is needed. As a consequence, conformations of the titratable residues can be treated independently in the protein and solvent environments. In addition, the energy terms used here avoid the so-called intrinsic pKa and can therefore be interpreted without reference to arbitrary protonation states and conformations.

Underlying thermodynamics of pH-dependent allostery

Understanding the effects of coupling protein protonation and conformational states is critical to the development of drugs targeting pH sensors and to the rational engineering of pH switches. In this work, we address this issue by performing a comprehensive study of the pH-regulated switch from the closed to the open conformation in nitrophorin 4 (NP4) that determines its pH-dependent activity. Our calculations show that D30 is the only amino acid that has two significantly different pKas in the open and closed conformations, confirming its critical role in regulating pH-dependent behavior. In addition, we describe the free-energy landscape of the conformational change as a function of pH, obtaining accurate estimations of free-energy barriers and equilibrium constants using different methods. The underlying thermodynamic model of the switch workings suggests the possibility of tuning the observed pKa only through the conformational equilibria, keeping the same conformation-specific pKas, as evidenced by the proposed K125L mutant. Moreover, coupling between the protonation and conformational equilibria results in efficient regulation and pH-sensing around physiological pH values only for some combinations of protonation and conformational equilibrium constants, placing constraints on their possible values and leaving a narrow space for protein molecular evolution. The calculations and analysis presented here are of general applicability and provide a guide as to how more complex systems can be studied, offering insight into how pH-regulated allostery works of great value for designing drugs that target pH sensors and for rational engineering of pH switches beyond the common histidine trigger.

What stabilizes close arginine pairing in proteins?

Close stacking of arginine residues are often observed in protein structures despite the highly repulsive nature of the close like-charged groups. Physical factors stabilizing the close guanidinium ions of arginine side-chains have been previously studied in water and in protein-like environments, and the hydration free energy has been emphasized to be an important factor. However, how close arginine pairs are stabilized in real proteins has not been fully understood yet. In this paper, we show that arginine pairs are more frequently found in the protein interior than expected from the frequency of unpaired arginines buried inside protein through a statistical analysis of the protein structure database. We then confirm that 4 selected arginine pairs buried in the protein are indeed positively charged rather than neutralized, by molecular dynamics simulations and pKa estimation with molecular mechanics-Poisson-Boltzmann calculations. Further energy decomposition analysis shows that the hydration free energy may not be strong enough to overcome the repulsive Coulomb interaction between the positively charged arginine residues buried inside the protein. Instead, a highly polar interaction network is identified around each buried arginine pair, and the electrostatic interactions within such network are strong enough to stabilize the repulsive interaction of the buried arginine pair for the 4 selected cases. The polar interaction network is highly conserved evolutionarily in some proteins, implicating their roles in protein stabilization or biochemical function.

Rapid calculation of protein pKa values using Rosetta

We developed a Rosetta-based Monte Carlo method to calculate the pK(a) values of protein residues that commonly exhibit variable protonation states (Asp, Glu, Lys, His, and Tyr). We tested the technique by calculating pK(a) values for 264 residues from 34 proteins. The standard Rosetta score function, which is independent of any environmental conditions, failed to capture pK(a) shifts. After incorporating a Coulomb electrostatic potential and optimizing the solvation reference energies for pK(a) calculations, we employed a method that allowed side-chain flexibility and achieved a root mean-square deviation (RMSD) of 0.83 from experimental values (0.68 after discounting 11 predictions with an error over 2 pH units). Additional degrees of side-chain conformational freedom for the proximal residues facilitated the capture of charge-charge interactions in a few cases, resulting in an overall RMSD of 0.85 pH units. The addition of backbone flexibility increased the overall RMSD to 0.93 pH units but improved relative pK(a) predictions for proximal catalytic residues. The method also captures large pK(a) shifts of lysine and some glutamate point mutations in staphylococcal nuclease. Thus, a simple and fast method based on the Rosetta score function and limited conformational sampling produces pK(a) values that will be useful when rapid estimation is essential, such as in docking, design, and folding.

Binding affinity prediction for ligands and receptors forming tautomers and ionization species: inhibition of mitogen-activated protein kinase-activated protein kinase 2 (MK2)

Treatment of ionization and tautomerism of ligands and receptors is one of the unresolved issues in structure-based prediction of binding affinities. Our solution utilizes the thermodynamic master equation, expressing the experimentally observed association constant as the sum of products, each valid for a specific ligand–receptor species pair, consisting of the association microconstant and the fractions of the involved ligand and receptor species. The microconstants are characterized by structure-based simulations, which are run for individual species pairs. Here we incorporated the multispecies approach into the QM/MM linear response method and used it for structural correlation of published inhibition data on mitogen-activated protein kinase (MAPK)-activated protein kinase (MK2) by 66 benzothiophene and pyrrolopyridine analogues, forming up to five tautomers and seven ionization species under experimental conditions. Extensive cross-validation showed that the resulting models were stable and predictive. Inclusion of all tautomers and ionization ligand species was essential: the explained variance increased to 90% from 66% for the single-species model.

Computational studies of difference in binding modes of peptide and non-peptide inhibitors to MDM2/MDMX based on molecular dynamics simulations

Inhibition of p53-MDM2/MDMX interaction is considered to be a promising strategy for anticancer drug design to activate wild-type p53 in tumors. We carry out molecular dynamics (MD) simulations to study the binding mechanisms of peptide and non-peptide inhibitors to MDM2/MDMX. The rank of binding free energies calculated by molecular mechanics generalized Born surface area (MM-GBSA) method agrees with one of the experimental values. The results suggest that van der Waals energy drives two kinds of inhibitors to MDM2/MDMX. We also find that the peptide inhibitors can produce more interaction contacts with MDM2/MDMX than the non-peptide inhibitors. Binding mode predictions based on the inhibitor-residue interactions show that the π–π, CH–π and CH–CH interactions dominated by shape complimentarity, govern the binding of the inhibitors in the hydrophobic cleft of MDM2/MDMX. Our studies confirm the residue Tyr99 in MDMX can generate a steric clash with the inhibitors due to energy and structure. This finding may theoretically provide help to develop potent dual-specific or MDMX inhibitors.

14-3-3ζ interacts with stat3 and regulates its constitutive activation in multiple myeloma cells

The 14-3-3 proteins are a family of regulatory signaling molecules that interact with other proteins in a phosphorylation-dependent manner and function as adapter or scaffold proteins in signal transduction pathways. One family member, 14-3-3ζ, is believed to function in cell signaling, cycle control, and apoptotic death. A systematic proteomic analysis done in our laboratory has identified signal transducers and activators of transcription 3 (Stat3) as a novel 14-3-3ζ interacting protein. Following our initial finding, in this study, we provide evidence that 14-3-3ζ interacts physically with Stat3. We further demonstrate that phosphorylation of Stat3 at Ser727 is vital for 14-3-3ζ interaction and mutation of Ser727 to Alanine abolished 14-3-3ζ/Stat3 association. Inhibition of 14-3-3ζ protein expression in U266 cells inhibited Stat3 Ser727 phosphorylation and nuclear translocation, and decreased both Stat3 DNA binding and transcriptional activity. Moreover, 14-3-3ζ is involved in the regulation of protein kinase C (PKC) activity and 14-3-3ζ binding to Stat3 protects Ser727 dephosphorylation from protein phosphatase 2A (PP2A). Taken together, our findings support the model that multiple signaling events impinge on Stat3 and that 14-3-3ζ serves as an essential coordinator for different pathways to regulate Stat3 activation and function in MM cells.

Quantitative, directional measurement of electric field heterogeneity in the active site of ketosteroid isomerase

Understanding the electrostatic forces and features within highly heterogeneous, anisotropic, and chemically complex enzyme active sites and their connection to biological catalysis remains a longstanding challenge, in part due to the paucity of incisive experimental probes of electrostatic properties within proteins. To quantitatively assess the landscape of electrostatic fields at discrete locations and orientations within an enzyme active site, we have incorporated site-specific thiocyanate vibrational probes into multiple positions within bacterial ketosteroid isomerase. A battery of X-ray crystallographic, vibrational Stark spectroscopy, and NMR studies revealed electrostatic field heterogeneity of 8 MV/cm between active site probe locations and widely differing sensitivities of discrete probes to common electrostatic perturbations from mutation, ligand binding, and pH changes. Electrostatic calculations based on active site ionization states assigned by literature precedent and computational pK(a) prediction were unable to quantitatively account for the observed vibrational band shifts. However, electrostatic models of the D40N mutant gave qualitative agreement with the observed vibrational effects when an unusual ionization of an active site tyrosine with a pK(a) near 7 was included. UV-absorbance and (13)C NMR experiments confirmed the presence of a tyrosinate in the active site, in agreement with electrostatic models. This work provides the most direct measure of the heterogeneous and anisotropic nature of the electrostatic environment within an enzyme active site, and these measurements provide incisive benchmarks for further developing accurate computational models and a foundation for future tests of electrostatics in enzymatic catalysis.

Progress in the prediction of pKa values in proteins

The pK(a) -cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pK(a) values and protein electrostatics in general. The first round of the pK(a) -cooperative, which challenged computational labs to carry out blind predictions against pK(a) s experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6-10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pK(a) calculations, emphasizing methods that were used by the participants in calculating the blind pK(a) values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pK(a) calculations.

Predicting pKa values with continuous constant pH molecular dynamics

Knowledge of pK(a) values is important for understanding structure and function relationships in proteins. Over the past two decades, theoretical methods for pK(a) calculations have been mainly based on macroscopic models, in which the protein is considered as a low-dielectric cavity embedded in a high-dielectric continuum. In recent years, constant pH molecular dynamics methods have been developed based on a microscopic description of the protein. We describe here the methodology of continuous constant pH molecular dynamics (CPHMD), which has emerged as one of the most robust and accurate tools for predicting protein pK(a)s and for the study of pH-modulated conformational dynamics. We illustrate the utility of CPHMD by the calculation of pK(a)s for surface residues in ribonuclease A, buried residues in staphylococcal nuclease, and titratable groups in the intrinsically flexible protein α-lactalbumin. We will compare the CPHMD results with experimental data as well as calculations from PB-based and empirical methods. These examples demonstrate the accuracy and robustness of the CPHMD method and its ability to capture the correlation between ionization equilibria and conformational dynamics as well as the local dielectric response to structural rearrangement. Finally, we discuss future improvement of the CPHMD method.

Empirical prediction of protein pKa values with residue mutation

A fast, empirical method, Mut-pKa, is presented for predicting the pKa values of ionizable residues in proteins based on mutation. The method compares the effect of mutating each residue that may act as a hydrogen bond donor or acceptor for the ionizable residue. The energetic effect of each type of mutation, along with a desolvation measure and the overall background charge, is fit against pKa data for histidine and carboxyl residues. A total of 214 residues from 35 different proteins were used in the dataset. Using 11 parameters for each type of ionizable residue, a root mean squared error (RMSE) of 0.78 and 1.12 pH units were obtained for carboxyl and histidines residues, respectively, using leave one out cross validation (LOOCV). The results were particularly promising for buried residues, which had RMSE values of 0.99 and 1.13 for carboxyl and histidine residues, respectively. A number of desolvation measures were tested. The simplest measure, the number of atoms surrounding the residue, was found to work best. The effect of using dynamics was also studied using short molecular dynamics runs, followed by minimization of the structures. Mut-pKa has significantly fewer parameters than, but similar performance to, other empirical methods. Because of this and the LOOCV results, we believe the model is robust and that overfitting is not a problem.

On the role of electrostatics in protein-protein interactions

The role of electrostatics in protein-protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity.

A parameterized, continuum electrostatic model for predicting protein pKa values

Recognizing the limits of trying to achieve chemical accuracy for pK(a) calculations with a purely electrostatic model, we include empirical corrections into the Poisson-Boltzmann solver macroscopic electrostatics with atomic detail (Bashford, Biochemistry 1990;29:10219-10225), to improve the reliability and accuracy of the model. The total number of parameters is kept to a minimum to maximize the robustness of the model for compounds outside of the fitting dataset. The parameters are based on: (a) the electrostatic interaction between functional groups close to the titratable site, (b) the electrostatic work required to desolvate the residue, and (c) the site-to-site interactions. These interactions are straightforward to calculate once the electrostatic field has been solved for each residue using the linearized Poisson-Boltzmann equation and are assumed to be linearly related to the intrinsic pK(a). Two hundred and eighty-six residues from 30 proteins are used to determine the empirical parameters, which result in a root mean square error (RMSE) of 0.70 for the entire set. Eight proteins with 46 experimentally known values were excluded from the parameterization to test the model. This test set had a RMSE of 1.08. We show that the parameterized model improves the results over other models, although like other models the error is strongly correlated with the degree to which a residue is buried. The parameters themselves indicate that local effects are most important for determining the pK(a), whereas site-to-site interactions are found to be less significant.

Brownian dynamics simulation of protein solutions: structural and dynamical properties

The study of solutions of biomacromolecules provides an important basis for understanding the behavior of many fundamental cellular processes, such as protein folding, self-assembly, biochemical reactions, and signal transduction. Here, we describe a Brownian dynamics simulation procedure and its validation for the study of the dynamic and structural properties of protein solutions. In the model used, the proteins are treated as atomically detailed rigid bodies moving in a continuum solvent. The protein-protein interaction forces are described by the sum of electrostatic interaction, electrostatic desolvation, nonpolar desolvation, and soft-core repulsion terms. The linearized Poisson-Boltzmann equation is solved to compute electrostatic terms. Simulations of homogeneous solutions of three different proteins with varying concentrations, pH, and ionic strength were performed. The results were compared to experimental data and theoretical values in terms of long-time self-diffusion coefficients, second virial coefficients, and structure factors. The results agree with the experimental trends and, in many cases, experimental values are reproduced quantitatively. There are no parameters specific to certain protein types in the interaction model, and hence the model should be applicable to the simulation of the behavior of mixtures of macromolecules in cell-like crowded environments.

Conformational consequences of ionization of Lys, Asp, and Glu buried at position 66 in staphylococcal nuclease

The pK(a) values measured previously for the internal Lys-66, Asp-66, and Glu-66 in variants of a highly stable form of staphylococcal nuclease are shifted by as many as 5 pK(a) units relative to normal pK(a) values in water. These shifts cannot be reproduced with continuum electrostatics calculations with static structures unless the protein is treated with high dielectric constants near 10. These high apparent dielectric constants are inconsistent with the highly hydrophobic microenvironments of the ionizable moieties in crystal structures. To examine the origins of these high apparent dielectric constants, we showed that the pK(a) values of these internal residues are sensitive to the global stability of the protein; the shifts tend to be smaller in less stable forms of nuclease. This implies that the apparent dielectric constants reported by these internal ionizable groups are high because they reflect conformational reorganization coupled to their ionization. To detect this directly, acid-base titrations monitored with Trp fluorescence and near-UV and far-UV CD spectroscopy were performed on variants with Lys-66, Glu-66, or Asp-66 in background proteins with different stabilities. Conformational reorganization coupled to the ionization of the internal groups was spectroscopically detectable, especially in the less stable background proteins. The data show that to improve the accuracy of structure-based pK(a) calculations of internal groups the calculations will have to treat explicitly all structural reorganization coupled to ionization. The data also suggest a novel approach to mapping the folding free energy landscape of proteins by using internal ionizable groups to stabilize partially unfolded states.

Continuum electrostatic calculations of the pKa of ionizable residues in an ion channel: dynamic vs. static input structure

We have computed the pK(a)'s of the ionizable residues of a protein ion channel, the Staphylococcus aureus toxin alpha-hemolysin, by using two types of input structures, namely the crystal structure of the heptameric alpha-hemolysin and a set of over four hundred snapshots from a 4.38 ns Molecular Dynamics simulation of the protein inserted in a phospholipid planar bilayer. The comparison of the dynamic picture provided by the Molecular Simulation with the static one based on the X-ray crystal structure of the protein embedded in a lipid membrane allows analyzing the influence of the fluctuations in the protein structure on its ionization properties. We find that the use of the dynamic structure provides interesting information about the sensitivity of the computed pK(a) of a given residue to small changes in the local structure. The calculated pK(a) are consistent with previous indirect estimations obtained from single-channel conductance and selectivity measurements.

Predicting pKa

One of the most important physicochemical properties of small molecules and macromolecules are the dissociation constants for any weakly acidic or basic groups, generally expressed as the pK(a) of each group. This is a major factor in the pharmacokinetics of drugs and in the interactions of proteins with other molecules. For both the protein and small molecule cases, we survey the sources of experimental pK(a) values and then focus on current methods for predicting them. Of particular concern is an analysis of the scope, statistical validity, and predictive power of methods as well as their accuracy.

High-throughput pKa screening and prediction amenable for ADME profiling

Recent technological advances have made it possible for several new pK(a) assays to be used in drug screening. In this review, a critical overview is provided of current new methodologies for high-throughput screening and prediction of pK(a). Typical applications of using pK(a )constants and charge state for absorption, distribution, metabolism and excretion (ADME) profiling and quantitative structure-activity relationship modelling complements the methodological comparisons and discussions. The experimental methods discussed include high-throughput screening of pK(a) by multiplexed capillary with ultraviolet absorbance detection on a 96-capillary format instrument, capillary electrophoresis and mass spectrometry (CEMS) based on sample pooling, determination of pK(a) by pH gradient high-performance liquid chromatography, and measurement of pK(a) by a mixed-buffer liner pH gradient system. Comparisons of the different experimental assays are made with emphasis on the newly developed CEMS method. The current status and recent progress in computational approaches to pK(a) prediction are also discussed. In particular, the accuracy limits of simple fragment-based approaches as well as quantum mechanical methods are addressed. Examples of pK(a) prediction from in-house drug candidates as well as commercially available drug molecules are shown and an outline is provided for how drug discovery companies can integrate experiments with computational approaches for increased applications for ADME profiling.

Web application for studying the free energy of binding and protonation states of protein-ligand complexes based on HINT

A public web server performing computational titration at the active site in a protein-ligand complex has been implemented. This calculation is based on the Hydropathic interaction noncovalent force field. From 3D coordinate data for the protein, ligand and bridging waters (if available), the server predicts the best combination of protonation states for each ionizable residue and/or ligand functional group as well as the Gibbs free energy of binding for the ionization-optimized protein-ligand complex. The 3D structure for the modified molecules is available as output. In addition, a graph depicting how this energy changes with acidity, i.e., as a function of added protons, can be obtained. This data may prove to be of use in preparing models for virtual screening and molecular docking. A few illustrative examples are presented. In beta secretase (2va7) computational titration flipped the amide groups of Gln12 and Asn37 and protonated a ligand amine yielding an improvement of 6.37 kcal mol(-1) in the protein-ligand binding score. Protonation of Glu139 in mutant HIV-1 reverse transcriptase (2opq) allows a water bridge between the protein and inhibitor that increases the protein-ligand interaction score by 0.16 kcal mol(-1). In human sialidase NEU2 complexed with an isobutyl ether mimetic inhibitor (2f11) computational titration suggested that protonating Glu218, deprotonating Arg237, flipping the amide bond on Tyr334, and optimizing the positions of several other polar protons would increase the protein-ligand interaction score by 0.71 kcal mol(-1).

Improved pK(a) prediction: combining empirical and semimicroscopic methods

Using three different methods we tried to compute 171 experimentally known pK(a) values of ionizable residues from 15 different proteins and compared the accuracies of computed pK(a) values in terms of the root mean square deviation (RMSD) from experiment. One method is based on a continuum electrostatic model of the protein including conformational flexibility (KBPLUS). The others are empirical approaches with PROPKA deploying physically motivated energy terms with adjustable parameters and PKAcal using an empirical function with no physical basis. PROPKA reproduced the pK(a) values with highest overall accuracy. Differentiating the data set into weakly and strongly shifted experimental pK(a) values, however, we found that PROPKA's accuracy is better if the pK(a) values are weakly shifted but on equal footing with that of KBPLUS for more strongly shifted values. On the other hand, PKAcal reproduces strongly shifted pK(a) values badly but weakly shifted values with the same accuracy as PROPKA. We tested different consensus approaches combining data from all three methods to find a general procedure for most accurate pK(a) predictions. In most of the cases we found that the consensus approach reproduced experimental data with better accuracy than any of the individual methods alone.

Optimizing pKa computation in proteins with pH adapted conformations

pK(A) in proteins are determined by electrostatic energy computations using a small number of optimized protein conformations derived from crystal structures. In these protein conformations hydrogen positions and geometries of salt bridges on the protein surface were determined self-consistently with the protonation pattern at three pHs (low, ambient, and high). Considering salt bridges at protein surfaces is most relevant, since they open at low and high pH. In the absence of these conformational changes, computed pK(A)(comp) of acidic (basic) groups in salt bridges underestimate (overestimate) experimental pK(A)(exp), dramatically. The pK(A)(comp) for 15 different proteins with 185 known pK(A)(exp) yield an RMSD of 1.12, comparable with two other methods. One of these methods is fully empirical with many adjustable parameters. The other is also based on electrostatic energy computations using many non-optimized side chain conformers but employs larger dielectric constants at short distances of charge pairs that diminish their electrostatic interactions. These empirical corrections that account implicitly for additional conformational flexibility were needed to describe the energetics of salt bridges appropriately. This is not needed in the present approach. The RMSD of the present approach improves if one considers only strongly shifted pK(A)(exp) in contrast to the other methods under these conditions. Our method allows interpreting pK(A)(comp) in terms of pH dependent hydrogen bonding pattern and salt bridge geometries. A web service is provided to perform pK(A) computations.

Calculated reaction cycle of cytochrome c oxidase

The catalytic cycle of cytochrome c oxidase has been simulated by means of quantum mechanical calculations. The experimental energetics of the catalytic cycle is nearly reproduced. The atomic structures of the intermediates are suggested. In particular, the structures of nonactive "resting" intermediates are proposed.

A statistical approach to the prediction of pK(a) values in proteins

We propose a simple model for the calculation of pK(a) values of ionizable residues in proteins. It is based on the premise that the pK(a) shift of ionizable residues is linearly correlated to the interaction between a particular residue and the local environment created by the surrounding residues. Despite its simplicity, the model displays good prediction performance. Under the sixfold cross test prediction over a data set of 405 experimental pK(a) values in 73 protein chains with known structures, the root-mean-square deviation (RMSD) between the experimental and calculated pK(a) was found to be 0.77. The accuracy of this model increases with increasing size of the data set: the RMSD is 0.609 for glutamate (the largest data set with 141 sites) and approximately 1 pH unit for lysine, with a data set containing 45 sites.

Screening of the active site from water by the incoming ligand triggers catalysis and inhibition in serine proteases

The pKa of the catalytic His57 N(epsilon)H in the tetrahedral complex (TC) of chymotrypsin with trifluoromethyl ketone inhibitors is 4-5 units higher relative to the free enzyme (FE). Such stable TC's, formed with transition state (TS) analog inhibitors, are topologically similar to the catalytic TS. Thus, analysis of this pKa shift may shed light on the role of water solvation in the general base catalysis by histidine. We applied our QM/SCRF(VS) approach to study this shift. The method enables explicit quantum mechanical DFT calculations of large molecular clusters that simulate chemical reactions at the active site (AS) of water solvated enzymes. We derived an analytical expression for the pKa dependence on the degree of water exposure of the ionizable group, and on the total charge in the enzyme AS, Q(A) and Q(B), when the target ionizable functional group (His57 in this study) is in the acidic (A) and basic (B) forms, respectively. Q2(B) > Q2(A) both in the FE and in the TC of chymotrypsin. Therefore, water solvation decreases the relative stability of the protonated histidine in both. Ligand binding reduces the degree of water solvation of the imidazole ring, and consequently elevates the histidine pKa. Thus, the binding of the ligand plays a triggering role that switches on the cascade of catalytic reactions in serine proteases.

The impact of dyskeratosis congenita mutations on the structure and dynamics of the human telomerase RNA pseudoknot domain

The pseudoknot domain is a functionally crucial part of telomerase RNA and influences the activity and stability of the ribonucleoprotein complex. Autosomal dominant dyskeratosis congenita (DKC) is an inherited disease that is linked to mutations in telomerase RNA and impairs telomerase function. In this paper, we present a computational prediction of the influence of two base DKC mutations on the structure, dynamics, and stability of the pseudoknot domain. We use molecular dynamics simulations, MM-GBSA free energy calculations, static analysis, and melting simulations analysis. Our results show that the DKC mutations stabilize the hairpin form and destabilize the pseudoknot form of telomerase RNA. Moreover, the P3 region of the predicted DKC-mutated pseudoknot structure is unstable and fails to form as a defined helical stem. We directly compare our predictions with experimental observations by calculating the enthalpy of folding and melting profiles for each structure. The enthalpy values are in very good agreement with values determined by thermal denaturation experiments. The melting simulations and simulations at elevated temperatures show the existence of an intermediate structure, which involves the formation of two UU base pairs observed in the hairpin form of the pseudoknot domain.

High apparent dielectric constant inside a protein reflects structural reorganization coupled to the ionization of an internal Asp

The dielectric properties of proteins are poorly understood and difficult to describe quantitatively. This limits the accuracy of methods for structure-based calculation of electrostatic energies and pK(a) values. The pK(a) values of many internal groups report apparent protein dielectric constants of 10 or higher. These values are substantially higher than the dielectric constants of 2-4 measured experimentally with dry proteins. The structural origins of these high apparent dielectric constants are not well understood. Here we report on structural and equilibrium thermodynamic studies of the effects of pH on the V66D variant of staphylococcal nuclease. In a crystal structure of this protein the neutral side chain of Asp-66 is buried in the hydrophobic core of the protein and hydrated by internal water molecules. Asp-66 titrates with a pK(a) value near 9. A decrease in the far UV-CD signal was observed, concomitant with ionization of this aspartic acid, and consistent with the loss of 1.5 turns of alpha-helix. These data suggest that the protein dielectric constant needed to reproduce the pK(a) value of Asp-66 with continuum electrostatics calculations is high because the dielectric constant has to capture, implicitly, the energetic consequences of the structural reorganization that are not treated explicitly in continuum calculations with static structures.

Electronic structure, bonding, spectroscopy and energetics of Fe-dependent nitrile hydratase active-site models

Fe-type nitrile hydratase (NHase) is a non-heme Fe(III)-dependent enzyme that catalyzes the hydration of nitriles to the corresponding amides. Despite experimental studies of the enzyme and model Fe(III)-containing complexes, many questions concerning the electronic structure and spectroscopic transitions of the metal center remain unanswered. In addition, the catalytic mechanism of nitrile hydration has not yet been determined. We now report density functional theory (B3LYP/6-31G) calculations on three models of the Fe(III) center in the active site of NHase corresponding to hypothetical intermediates in the enzyme-catalyzed hydration of acetonitrile. Together with natural bond orbital (NBO) analysis of the chemical bonding in these active-site models and INDO/S CIS calculations of their electronic spectra, this theoretical investigation gives new insight into the molecular origin of the unusual low-spin preference and spectroscopic properties of the Fe(III) center. In addition, the low-energy electronic transition observed for the active form of NHase is assigned to a dd transition that is coupled with charge-transfer transitions involving the metal and its sulfur ligands. Calculations of isodesmic ligand-exchange reaction energies provide support for coordination of the Fe(III) center in free NHase by a water molecule rather than a hydroxide ion and suggest that the activation of the nitrile substrate by binding to the metal in the sixth coordination site during catalytic turnover cannot yet be definitively ruled out.

Factors influencing the energetics of electron and proton transfers in proteins. What can be learned from calculations

A protein structure should provide the information needed to understand its observed properties. Significant progress has been made in developing accurate calculations of acid/base and oxidation/reduction reactions in proteins. Current methods and their strengths and weaknesses are discussed. The distribution and calculated ionization states in a survey of proteins is described, showing that a significant minority of acidic and basic residues are buried in the protein and that most of these remain ionized. The electrochemistry of heme and quinones are considered. Proton transfers in bacteriorhodopsin and coupled electron and proton transfers in photosynthetic reaction centers, 5-coordinate heme binding proteins and cytochrome c oxidase are highlighted as systems where calculations have provided insight into the reaction mechanism.

Probing biological interfaces by tracing proton passage across them

The properties of water at the surface, especially at an electrically charged one, differ essentially from those in the bulk phase. Here we survey the traits of surface water as inferred from proton pulse experiments with membrane enzymes. In such experiments, protons that are ejected (or captured) by light-triggered enzymes are traced on their way between the membrane surface and the bulk aqueous phase. In several laboratories it has been shown that proton exchange between the membrane surface and the bulk aqueous phase takes as much as about 1 ms, but could be accelerated by added mobile pH-buffers. Since the accelerating capacity of the latter decreased with increase in their electric charge, it was suggested that the membrane surface is separated from the bulk aqueous phase by a barrier of electrostatic nature. In terms of ordinary electrostatics, the barrier could be ascribed to dielectric saturation of water at a charged surface. In terms of nonlocal electrostatics, the barrier could result from the dielectric overscreening in the surface water layers. It is discussed how the interfacial potential barrier can affect the reactions at interface, especially those coupled with biological energy conversion and membrane transport.

Assessment of two theoretical methods to estimate potentiometric titration curves of peptides: comparison with experiment

We compared the ability of two theoretical methods of pH-dependent conformational calculations to reproduce experimental potentiometric titration curves of two models of peptides: Ac-K5-NHMe in 95% methanol (MeOH)/5% water mixture and Ac-XX(A)7OO-NH2 (XAO) (where X is diaminobutyric acid, A is alanine, and O is ornithine) in water, methanol (MeOH), and dimethyl sulfoxide (DMSO), respectively. The titration curve of the former was taken from the literature, and the curve of the latter was determined in this work. The first theoretical method involves a conformational search using the electrostatically driven Monte Carlo (EDMC) method with a low-cost energy function (ECEPP/3 plus the SRFOPT surface-solvation model, assumming that all titratable groups are uncharged) and subsequent reevaluation of the free energy at a given pH with the Poisson-Boltzmann equation, considering variable protonation states. In the second procedure, molecular dynamics (MD) simulations are run with the AMBER force field and the generalized Born model of electrostatic solvation, and the protonation states are sampled during constant-pH MD runs. In all three solvents, the first pKa of XAO is strongly downshifted compared to the value for the reference compounds (ethylamine and propylamine, respectively); the water and methanol curves have one, and the DMSO curve has two jumps characteristic of remarkable differences in the dissociation constants of acidic groups. The predicted titration curves of Ac-K5-NHMe are in good agreement with the experimental ones; better agreement is achieved with the MD-based method. The titration curves of XAO in methanol and DMSO, calculated using the MD-based approach, trace the shape of the experimental curves, reproducing the pH jump, while those calculated with the EDMC-based approach and the titration curve in water calculated using the MD-based approach have smooth shapes characteristic of the titration of weak multifunctional acids with small differences between the dissociation constants. Nevertheless, quantitative agreement between theoretically predicted and experimental titration curves is not achieved in all three solvents even with the MD-based approach, which is manifested by a smaller pH range of the calculated titration curves with respect to the experimental curves. The poorer agreement obtained for water than for the nonaqueous solvents suggests a significant role of specific solvation in water, which cannot be accounted for by the mean-field solvation models.

Design of improved protein inhibitors of HIV-1 cell entry: Optimization of electrostatic interactions at the binding interface

Continuum electrostatic methods are a powerful tool for the analysis and design of biomolecular complexes, with methodologies that allow for the detailed analysis of the electrostatic contributions to binding affinities and procedures for computing the properties of electrostatically optimal ligands. We have applied these methods to the design of improved inhibitors of HIV-1 cell entry. HIV infection of a cell requires viral-cell membrane fusion, an event partially driven by a large-scale conformational change in the viral membrane glycoprotein gp41. This transformation involves the docking of a helix from the C-terminal region of three gp41 chains against a pre-formed trimeric-coiled coil; several protein constructs that inhibit membrane fusion act by binding to an isolated C-terminal helix and blocking the formation of the fusogenic structure. A detailed analysis of the electrostatic contributions to the binding of one such inhibitor (5-Helix) to a C-terminal helix was performed using the X-ray crystal structure of the core of the HIV-1 gp41 ectodomain as a structural model, and several residues on 5-Helix that make substantial contributions to binding, both favorable and unfavorable, were identified. An electrostatic affinity optimization methodology was applied to the side chains of 5-Helix, with the results showing that significant improvements in binding affinity are possible if the electrostatic contributions to the binding free energy are optimized. Several mutations accessible by experimental methods are suggested, with calculated improvements in binding affinity of as much as 500-fold and greater.

Are acidic and basic groups in buried proteins predicted to be ionized?

Ionizable residues play essential roles in proteins, modulating protein stability, fold and function. Asp, Glu, Arg, and Lys make up about a quarter of the residues in an average protein. Multi-conformation continuum electrostatic (MCCE) calculations were used to predict the ionization states of all acidic and basic residues in 490 proteins. Of all 36,192 ionizable residues, 93.5% were predicted to be ionized. Thirty-five percent have lost 4.08 kcal/mol solvation energy (DeltaDeltaG(rxn)) sufficient to shift a pK(a) by three pH units in the absence of other interactions and 17% have DeltaDeltaG(rxn) sufficient to shift pK(a) by five pH units. Overall 85% of these buried residues (DeltaDeltaG(rxn)>5DeltapK units) are ionized, including 92% of the Arg, 86% of the Asp, 77% of the Glu, and 75% of the Lys. Ion-pair interactions stabilize the ionization of both acids and bases. The backbone dipoles stabilize anions more than cations. The interactions with polar side-chains are also different for acids and bases. Asn and Gln stabilize all charges, Ser and Thr stabilize only acids while Tyr rarely stabilize Lys. Thus, hydroxyls are better hydrogen bond donors than acceptors. Buried ionized residues are more likely to be conserved than those on the surface. There are 3.95 residues buried per 100 residues in an average protein.