243 research outputs found

    Developing and validating Fuzzy-Border continuum solvation model with POlarizable Simulations Second order Interaction Model (POSSIM) force field for proteins

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    The accurate, fast and low cost computational tools are indispensable for studying the structure and dynamics of biological macromolecules in aqueous solution. The goal of this thesis is development and validation of continuum Fuzzy-Border (FB) solvation model to work with the Polarizable Simulations Second-order Interaction Model (POSSIM) force field for proteins developed by Professor G A Kaminski. The implicit FB model has advantages over the popularly used Poisson Boltzmann (PB) solvation model. The FB continuum model attenuates the noise and convergence issues commonly present in numerical treatments of the PB model by employing fixed position cubic grid to compute interactions. It also uses either second or first-order approximation for the solvent polarization which is similar to the second-order explicit polarization applied in POSSIM force field. The FB model was first developed and parameterized with nonpolarizable OPLS-AA force field for small molecules which are not only important in themselves but also building blocks of proteins and peptide side chains. The hydration parameters are fitted to reproduce the experimental or quantum mechanical hydration energies of the molecules with the overall average unsigned error of ca. 0.076kcal/mol. It was further validated by computing the absolute pKa values of 11 substituted phenols with the average unsigned error of 0.41pH units in comparison with the quantum mechanical error of 0.38pH units for this set of molecules. There was a good transferability of hydration parameters and the results were produced only with fitting of the specific atoms to the hydration energy and pKa targets. This clearly demonstrates the numerical and physical basis of the model is good enough and with proper fitting can reproduce the acidity constants for other systems as well. After the successful development of FB model with the fixed charges OPLS-AA force field, it was expanded to permit simulations with Polarizable Simulations Second-order Interaction Model (POSSIM) force field. The hydration parameters of the small molecules representing analogues of protein side chains were fitted to their solvation energies at 298.15K with an average error of ca.0.136kcal/mol. Second, the resulting parameters were used to reproduce the pKa values of the reference systems and the carboxylic (Asp7, Glu10, Glu19, Asp27 and Glu43) and basic residues (Lys13, Lys29, Lys34, His52 and Lys55) of the turkey ovomucoid third domain (OMTKY3) protein. The overall average unsigned error in the pKa values of the acid residues was found to be 0.37pH units and the basic residues was 0.38 pH units compared to 0.58pH units and 0.72 pH units calculated previously using polarizable force field (PFF) and Poisson Boltzmann formalism (PBF) continuum solvation model. These results are produced with fitting of specific atoms of the reference systems and carboxylic and basic residues of the OMTKY3 protein. Since FB model has produced improved pKa shifts of carboxylic residues and basic protein residues in OMTKY3 protein compared to PBF/PFF, it suggests the methodology of first-order FB continuum solvation model works well in such calculations. In this study the importance of explicit treatment of the electrostatic polarization in calculating pKa of both acid and basic protein residues is also emphasized. Moreover, the presented results demonstrate not only the consistently good degree of accuracy of protein pKa calculations with the second-degree POSSIM approximation of the polarizable calculations and the first-order approximation used in the Fuzzy-Border model for the continuum solvation energy, but also a high degree of transferability of both the POSSIM and continuum solvent Fuzzy Border parameters. Therefore, the FB model of solvation combined with the POSSIM force field can be successfully applied to study the protein and protein-ligand systems in water

    SMARTS Approach to Chemical Data Mining and Physicochemical Property Prediction.

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    The calculation of physicochemical and biological properties is essential in order to facilitate modern drug discovery. Chemical spaces dimensionalized by these descriptors have been used to scaffold-hop in order to discover new lead and drug-like molecules. Broadening the boundaries of structure based drug design, these molecules are expected to share the same physiological target and have similar efficacy, as do known drug molecules sharing the same region in chemical property space. In the past few decades physicochemical and ADMET (absorption, distribution, metabolism, elimination, and toxicity) property predictors have been the subject of increased focus in academia and the pharmaceutical industry. Due to the ever increasing attention given to data mining and property predictions, we first discuss the sources of experimental pKa values and current methodologies used for pKa prediction in proteins and small molecules. Of particular concern is an analysis of the scope, statistical validity, overall accuracy, and predictive power of these methods. The expressed concerns are not limited to predicting pKa, but apply to all empirical predictive methodologies. In a bottom-up approach, we explored the influence of freely generated SMARTS string representations of molecular fragments on chelation and cytotoxicity. Later investigations, involving the derivation of predictive models, use stepwise regression to determine the optimal pool of SMARTS strings having the greatest influence over the property of interest. By applying a unique scoring system to sets of highly generalized SMARTS strings, we have constructed well balanced regression trees with predictive accuracy exceeding that of many published and commercially available models for cytotoxicity, pKa, and aqueous solubility. The methodology is robust, extremely adaptable, and can handle any molecular dataset with experimental data. This story details our struggles of data gathering, curation, and the development of a machine learning methodology able to derive and validate highly accurate regression trees capable of extremely fast property predictions. Regression trees created by our method are well suited to calculate descriptors for large in silico molecular libraries, facilitating data mining of chemical spaces in search of new lead molecules in drug discovery.Ph.D.Medicinal ChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64627/1/adamclee_1.pd

    THERMODYNAMIC AND KINETIC PROPERTIES OF CYTOCHROMES C AND C’ IN THE DENATURED STATE: PROPENSITY FOR RESIDUAL STRUCTURE

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    To expand our understanding of helical propensity and residual structure in the denatured state, two approaches have been taken. In the first project, we have engineered serine in place of alanine near the center of the third helix (positions 83 and 87) in cytochrome c’ (Cytc’) and have measured histidine-heme loop formation in 3 M gdnHCl. A series of thirteen variants that include the A83S/A87S substitutions have been engineered with single surface histidine substitutions to provide a range of His-heme loop sizes from 10 to 111 residues and to provide direct comparison to previous studies with pWT Cytc’ . We observe decreased global stability for most variants and an average decrease of the midpoint of gdnHCl unfolding for A83S/A87S variants compared to pWT. Loop stability versus loop size data yields a scaling exponent of 2.24 ± 0.24, similar to the pWT value of 2.5 ± 0.3, but with a crossover point and values that suggest that loop flexibility and stability increase in loops that contain the A83S/A87S substitutions. Kinetic data shows nonrandom behavior in the denatured state similar to pWT, and also supports the suggestion of helical propensity only being important if the helical segment is contained within the loop, as kf values are slightly faster for loops containing A83S/A87S. Molecular dynamic simulations of the thermal unfolding of Cytc’ show a perhaps surprising amount of structure retention in the third helix, even with the helical propensity lowering A83S/A87S substitutions. In the second project, we combine NMR methods with chemical shift secondary structure analysis on the iso-1 cytochrome c K54H variant in 3 and 6 M gdnHCl. We consider two pH conditions, pH 6.3 where the His54-heme loop is formed and pH 3.6 where the His54-heme loop is broken. A method designed to estimate the secondary structure propensities quantitatively was used to process chemical shift data obtained for each residue. Regions of residual structure were identified in 3 M gdnHCl, a condition at which the protein is fully denatured, as well as in the very harsh denaturant condition of 6 M gdnHCl. The data presented here may contribute to the identification of residues and structural behavior involved in early folding which could lead to better understanding of protein folding pathways

    Prediction of protonation states in ligand-protein complexes upon ligand binding

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    Die ständige Weiterentwicklung der Computer-Hardware und die daraus resultierende Steigerung der Rechenleistung ermöglicht heutzutage eine erfolgreiche Modellierung von chemischen und biologischen Prozessen, die vor 20 Jahren noch undenkbar war. Als Beispiele sind Molekulardynamik-Simulationen grosser Biomoleküle, die Berechnung freier Bindungsenergien von Protein-Ligand-Komplexen oder auch Untersuchungen von Reaktionswegen in Enzymen zu nennen. In einem Bereich mangelt es jedoch weiterhin an akkuraten Methoden: die Abschätzung von Protonierungszuständen in Protein-Ligand-Komplexen. In der vorliegenden Arbeit zeigen wir die Entwicklung einer neuen Methode der Ladungszuweisung, genannt PEOE_PB (Partial Equalisation of Orbital Electronegativities - optimiert für Poisson-Boltzmann Rechnungen). Diese Methode stellt eine konsistente Ladungszuweisung sowohl für Proteine als auch für kleine organische Moleküle dar. Die Ladungen sind entscheidende Parameter bei Poisson-Boltzmann (PB)- Rechnungen. PB-Rechnungen stellen eine etablierte Methode bei der Bestimmung von pKa-Werten in Proteinen dar. Die Entwicklung von PEOE_PB-Ladungen ist notwendig geworden, da es keine generische Methode gibt, PB-basierte pKa-Berechnungen in Protein-Ligand-Komplexen durchzufÃ�hren. Der PEOE-Ansatz wurde gewählt, um zunächst die freien Solvatationsenergien kleiner organischer Moleküle bestmöglich vorherzusagen. Modifikationen wurden heuristisch, d.h. ergebnisorientiert vorgenommen, wobei Änderungen lediglich den Parameter a des PEOE-Polynoms betreffen. Bei unserer Optimierung versuchten wir zunächst, die experimentell bestimmten freien Solvatationsenergien polarer AminosÃ�uren (r2 = 0.94, RMSD = 0.84) und anschliessend eines Datensatzes von 80 kleinen organischen MolekÃ�ulen (r2 = 0.78, RMSD = 1.57) zu reproduzieren. Die Verwendung des letztgenannten Datensatzes zeigt den generischen Charakter unserer PEOE_PB-Ladungen. Abschliessend führten wir Rechnungen an einem Datensatz von neun (apo-)Proteinen mit 132 experimentell bestimmten pKa-Werten durch und erzielten einen RMSD von 0.88. Die Dielektrizitätskonstante im Protein war hierbei auf 20 gesetzt. Aminosäurereste in Bindetaschen mit stark verschobenen pKa-Werten lagen bei zwei Enzymen des Datensatzes vor, in diesen FÃ�llen wurden folgende Beobachtungen gemacht: * Die Dielektrizitätskonstante wurde von 20 auf 4 gesenkt, was teilweise durch die Vergrabenheit der Bindetasche erklärt werden kann. * Die Orientierung der Hydroxylgruppe des Tyrosins hatte einen beachtlichen Einfluss auf den pKa-Wert eines Aminosäurerestes in der Bindetasche (ein Glutamat mit einem stark erhöhten pKa-Wert). Diese Tatsache unterstreicht den entscheidenden Einfluss der Orientierung polarer Wasserstoffatome. Im letzten Schritt unserer PEOE_PB-Validierung führten wir pKa-Berechnungen für drei Protein-Ligand-Komplexe (die im Experiment einen Protonentransfer zeigten) durch: in allen Fällen stimmten unsere Berechnungen mit dem Experiment überein. In einer folgenden reinen Anwendungstudie führten wir pKa-Berechnungen für eine Serie von Liganden, die an die Serin-Proteasen Trypsin und Thrombin binden, durch. An diesen Komplexen waren bereits ausführliche ITC- und Kristallographie-Studien gemacht worden und für vier dieser Komplexe konnten Ã�nderungen in den ProtonierungszustÃ�nden detektiert werden [Dullweber et al., J. Mol. Biol. 313 (2001), 593] . Da ITC-Experimente jedoch nur gesamtheitliche Ã�nderungen in der Protonierung messen, konnten diese Experimente keinen Aufschluss darüber geben, welche funktionellen Gruppen tatsächlich am Protonentransfer beteiligt sind. Um diese Gruppen identifizieren zu können, führten wir Poisson-Boltzmann-Rechnungen, basierend auf unseren PEOE_PB-Ladungen, durch. Die resultierenden pKa-Werte zeigen, dass His57 (einer der drei katalytisch aktiven Reste) für die wichtigsten pKa-Änderungen, die sich im Experiment als Ã�nderungen im Protonierungszustand zeigen, verantwortlich ist. Dies steht im Widerspruch zu unserer frÃ�heren Annahme, dass die Ã�nderungen im Protonierugszustand an der Carboxylgruppe der Liganden ablaufen. Der neuentdeckte Protonenakzeptor wurde für die Refaktorisierung der ITC-Daten eingesetzt; dies ist wichtig für Fälle, in denen sich die Protonierung während der Komplexbildung ändert. Die pKa-Werte von Komplexen, die im ITC-Experiment keine Änderung im Protonierungszustand zeigen, werden in den meisten Fällen verlässlich vorhergesagt, während dies in Fällen stark koppelnder Systeme schwierig bleibt. Solche Fälle treten auf, wenn zwei (oder mehr) interagierende titrierbare Gruppen räumlich nahe beiander liegen. Die HIV-Protease (HIVP) ist ein bekanntes Beispiel für erfolgreiches strukturbasiertes Wirkstoffdesign und ist ein gut untersuchtes System, bei dem Änderungen des Protonierungszustandes während der Ligandenbindung auftreten, wie im Experiment gezeigt wurde. Das System der HIVP stellt einen Ausgangspunkt für eine weitere Anwendungsstudie unserer PEOE_PB-Ladungen dar. Bei dem Apo-Enzym befindet sich die zwei katalytisch aktiven Reste (Aspartate) im monoprotonierten Zustand. Dieser kann sich ändern, wenn Liganden binden, die eine cylische Harnstoff-Gruppe enthalten. Unser PEOE_PB-Modell reproduziert den experimentell bestimmten Protonierungszustand. Ferner führten wir pKa-Berechnungen für zwei HIVP-Komplexe mit neuartigen Inhibitoren, die unserer Gruppe entwickelt und synthetisiert wurden [Specket et al, J. Med. Chem., 48 (2005) 6607], durch. In diesen Fällen gibt es keinerlei experimentelle Daten für die Protonierungszustände. Einer der Inhibitoren enthält ein Pyrrolidin-Ring: hier sagten die Berechnungen voraus, dass beide katalytisch aktiven Aspartate nach Ligandenbindung deprotoniert vorliegen. Solch ein Protonierungsmuster wurde bisher in keinem HIVP-Komplex beobachtet, weder experimentell noch mittels einer Berechnungsmethode. Neben den experimentellen Trypsin/Thrombin-Studien wurden auch kombinierte kristallographische und thermodynamische Untersuchungen der Ligandenbindung an humaner Aldose-Reduktase (hAR) in unserer Gruppe vorgenommen [Steuber, Doktorarbeit in Vorbereitung]. Die ITC-Messungen zeigten einen durch die Ligandenbindung induzierten Protonentransfer. Unsere Berechnungen lassen darauf schliessen, dass ein Tyrosin-Rest der Bindetasche (Tyr48) als Protonenakzeptor fungiert, was bedeutet, dass das Tyrosin im Holo-Enzym deprotoniert vorliegt. Dies ist im Einklang mit den Ergebnissen von ITC-Messungen an Tyr48Phe-Mutanten. Während bei hAR-Komplexen von Inhibitoren mit einer Carboxyl-Kopfgruppe die Berechnungen gut im Einklang mit den ITC-Experimenten waren, zeigten sich Ungenauigkeiten bei der Vorhersage von Inhibitoren mit einer cyclischen Hydantoin-Gruppe. Eine mögliche Erklärung hierfür ist die starke elektrostatische Wechselwirkung zwischen Ligand und den Tyrosin bzw. Lysin-Resten der Bindetasche. Ferner liegen die pKa-Werte in wässriger LÃ�sung nahe dem physiologischen pH-Bereich, was das System sehr anfälig für kleine Ã�nderungen des pKa-Wertes macht. Ein limitierender Faktor für die breite Anwendung unserer PEOE_PB Ladungsmethode bei pKa-Rechnungen stellt die vorangehende Prozessierung der Liganden dar. Zu diesem Zweck implementierten wir den PEOE_PB-Algorithmus in das PDB2PQR-Programm (dieses erzeugt Input-Dateien für das Poisson-Boltzmann-Programm APBS). Liganden wurden in der PDB2PQR-Umgebung als voll flexibel betrachtet, und es wurde eine Suchprozedur für gemeinsame Substrukturen eingeführt. Mit dieser Technik ist es möglich, titrierbare Gruppen des Liganden automatisch zu erkennen und ihnen pKa-Werte zuzuweisen. Diese pKa-Werte stammen aus einer Datenbank, die momentan 348 Moleküle mit experimentell bestimmten pKa-Werten enthält

    A Computational Methodology to Screen Activities of Enzyme Variants

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    We present a fast computational method to efficiently screen enzyme activity. In the presented method, the effect of mutations on the barrier height of an enzyme-catalysed reaction can be computed within 24 hours on roughly 10 processors. The methodology is based on the PM6 and MOZYME methods as implemented in MOPAC2009, and is tested on the first step of the amide hydrolysis reaction catalyzed by Candida Antarctica lipase B (CalB) enzyme. The barrier heights are estimated using adiabatic mapping and are shown to give barrier heights to within 3kcal/mol of B3LYP/6-31G(d)//RHF/3-21G results for a small model system. Relatively strict convergence criteria (0.5kcal/(mol{\AA})), long NDDO cutoff distances within the MOZYME method (15{\AA}) and single point evaluations using conventional PM6 are needed for reliable results. The generation of mutant structure and subsequent setup of the semiempirical calculations are automated so that the effect on barrier heights can be estimated for hundreds of mutants in a matter of weeks using high performance computing

    The Exploration of Protein Electrostatics Through NMR Chemical Shift Perturbations

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    Understanding the relationship between protein structure and function is paramount to gaining insight into important biological mechanisms. In this context, pH often plays a significant role. The organization of charge within a protein prepares it to form intra-/inter-molecular interactions as the environmental pH changes. Studying the pKa values of titratable groups in a protein allows us to understand its electrostatic network. Computational pKa values are influenced by a microscopic environment and are often compared to macroscopic pKa values derived from NMR experiments. In this work we aim to understand the impact of pH on NMR chemical shift perturbations such that we can bridge the gap between computational and experimental observables. Peptide model systems have historically been used in NMR spectroscopy to detangle the many contributions which compose the observable NMR chemical shift. Utilizing molecular dynamics simulations, we sampled the conformational preferences of model tripeptides each containing one of the four titratable groups (aspartic acid, glutamic acid, histidine or lysine) in either a protonated or deprotonated state. The conformational ensembles obtained during the simulations were then used to compute pH-dependent NMR chemical shift perturbations for each nucleus in the tripeptides. The perturbations agree well with experimental findings and elucidate the relationship between charge and chemical shift. Furthermore, these results allow for better interpretation of NMR spectra and the possible integration of pH in chemical shift prediction paradigms. Although random coil chemical shifts serve as the basis for chemical shift prediction and interpretation, the complexity of the protein environment can produce drastically different behaviors. In the second study, we investigate the ability to utilize peptide derived chemical shift perturbations along with through-space electrostatic and conformational effects to compute pH-dependent NMR chemical shifts of the dynamic ensembles produced by constant pH molecular dynamics (CpHMD). Hen egg white lysozyme (HEWL) is an appropriate benchmark protein to probe the efficacy of a new protocol which fortifies the microscopic pKa values from simulation with macroscopic influences. The inclusion of the pH-dependent chemical shift contribution improved the results from the empirical chemical shift predictor for both 15N and 1H atoms and added dimensionality to the CpHMD simulations informing pH-dependent conformational fluctuations in HEWL. The newly derived macroscopic pKa values from simulation were directly compared to the experimental pKa values. Lastly, hisactophilin, a highly charged protein, is studied in order to identify critical residues that trigger the pH-dependent switching behavior of a post-translational modification. Hisactophilin has an N-terminal myristoyl group which is buried inside the beta-trefoil cavity in pH values greater than 7.5. However, at pH values lower than 6.5, the myristoyl group is accessible and may incorporate itself into an external lipid membrane. The small pH range where this switching behavior occurs likely corresponds with the protonation event of one or a few titratable residues. Implicit and explicit solvent CpHMD simulations allow us to explore the residues involved in the pH-dependent mechanism and formulate conclusions about charge redistribution.PHDBiophysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163051/1/eartikis_1.pd

    Investigations of Protein-Lipid Interactions in Model Membranes: Influence of Aromatic Anchoring Residues and Buried Polar Residues

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    To investigate in detail the interactions between transmembrane proteins and the lipid bilayers in which they are constituted, designed model peptides with selective isotopic labels were synthesized and analyzed by means of solid-state deuterium NMR spectroscopy. Starting from the well-characterized model peptide GWALP23, acetyl-GGALW(LA)6LWLAGA-amide, several Trp to Tyr mutations were compared to evaluate their respective interfacial anchoring abilities. It was found that Tyr, substituted on either or both termini, can effectively anchor the transmembrane alpha-helix, which then adopts a similar transmembrane topology in a range of bilayer thicknesses. Nevertheless, a consistent ~10° shift in tilt direction (helix rotation) is observed when a Tyr is substituted for Trp and found to be terminal-dependent (i.e. in opposite direction on each end). The fluorescence emission spectra from the single remaining Trp residue in Y5GWALP23 and Y19GWALP23 indicate that W5 is buried more deeply in the bilayer than is W19. Using Y5GWALP23 as a host, the influence of Lys was examined at positions 12 and 14 in various lipid bilayer thicknesses. Y5GWALP23-K14 incorporates well into both thin and thick bilayers. It influences the peptide\u27s orientation by increasing the tilt magnitude (4-9°) and altering the tilt direction (60-95°). In contrast, the L12K mutant yields multiple low-intensity peaks in 2H NMR spectra, recorded in DOPC, indicative of multi-state behavior. Nevertheless, the peptide orients well and adopts a large tilt angle (30°) in the thinner bilayers of DLPC. Y5GWALP23-K12 in DOPC is observed to titrate at high pH to a neutral form that is well aligned in an orientation that is very similar to that of the host peptide without lysine. Titration of Y5GWALP23-K14 reveals a pKa of 6.2 in DOPC at 50 °C and different transmembrane orientations when the peptides charged lysine, neutral lysine or no lysine are compared. When Glu is added adjacent to a lysine, significantly improved NMR spectra and a stable transmembrane orientation are observed for Y5GWALP23-(K12, E13). Y5GWALP23-K14 experiences a small change in orientation with Glu-15 addition, but interestingly titrates much like the peptide with K14 alone. Placement of a Glu residue (E13) near R12 also improves spectra quality, especially at higher pH. It appears a stabilizing ion-pair may in some instances rescue the K12 or R12 peptide from its multi-state behavior in DOPC. The individual ionization states of paired ionizable residues have yet to be determined
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