@phdthesis{Le2020, author = {Le, Thien Anh}, title = {Theoretical investigations of proton transfer and interactions or reactions of covalent and non-covalent inhibitors in different proteins}, doi = {10.25972/OPUS-17051}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-170511}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Nowadays, computational-aided investigations become an essential part in the chemical, biochemical or pharmaceutical research. With increasing computing power, the calculation of larger biological systems becomes feasible. In this work molecular mechanical (MM) and quantum mechanical approaches (QM) and the combination of both (QM/MM) have been applied to study several questions which arose from different working groups. Thus, this work comprises eight different subjects which deals with chemical reactions or proton transfer in enzymes, conformational changes of ligands or proteins and verification of experimental data. This work firstly deals with reaction mechanisms of aromatic inhibitors of cysteine proteases which can be found in many organisms. These enzymes are responsible for various cancer or diseases as for example Human African Trypanosomiasis (HAT) or the Chagas disease. Aromatic SNAr-type electrophiles might offer a new possibility to covalently modify these proteases. Quantum mechanical calculations have been performed to gain insights into the energetics and possible mechanisms. The next chapter also deals with Trypanosomiasis but the focus was set on a different enzyme. The particularity of Trypanosomiasis is the thiol metabolism which can also be modified by covalent inhibitors. In this context, the wild type and point mutations of the enzyme tryparedoxin have been investigated via molecular dynamic (MD) simulations to examine the influence of specific amino acids in regard to the inhibitor. Experimental data showed that a dimerization of the enzyme occurs if the inhibitor is present. Simulations revealed that the stability of the dimer decreases in absence of the inhibitor and thus confirms these experiments. Further investigations concerning cysteine proteases such as cruzain and rhodesain have been conducted with respect to experimental kinetic data of covalent vinylsulfone inhibitors. Several approaches such as QM or QM/MM calculations and docking, MD or MMPBSA/MMGBSA simulations have been applied to reproduce these data. The utilization of force field approaches resulted in a qualitatively accurate prediction. The kinase AKT is involved in a range of diseases and plays an important role in the formation of cancer. Novel covalent-allosteric inhibitors have been developed and crystallized in complex with AKT. It was shown that depending on the inhibitor a different cysteine residue is modified. To investigate these differences in covalent modification computational simulations have been applied. Enoyl-(acyl carrier) (ENR) proteins are essential in the last step of the fatty acid biosynthesis II (FAS) and represent a good target for inhibition. The diphenylether inhibitor SKTS1 which was originally designed to target the ENR's of Staphylococcus aureus was also crystallized in InhA, the ENR of Mycobacterium tuberculosis (TB). Crystal structures indicate a change of the inhibitor's tautomeric form. This subject was investigated via MD simulations. Results of these simulations confirmed the tautomerization of the inhibitor. This work also deals with the development of a covalent inhibitor originating from a non-covalent ligand. The target FadA5 is an essential enzyme for the degradation of steroids in TB and is responsible for chronic tuberculosis. This enzyme was crystallized in complex with a non-covalent ligand which served as starting point for this study. Computations on QM or QM/MM level and docking and MD simulations have been applied to evaluate potential candidates. The next chapter focuses on the modification of the product spectrum of Bacillus megaterium levansucrase, a polymerase which catalyzes the biosynthesis of fructans. The covalent modification of the wild type or mutants of the enzyme lead to an accumulation of oligosaccharides but also to polymers with higher polymerization degree. To understand these changes in product spectra MD simulations have been performed. Finally, the proton transfer in catalytic cysteine histidine dyads was investigated. The focus was set on the influence of the relaxation of the protein environment to the reaction. Calculations of the enzymes FadA5 and rhodesain revealed that the preferred protonation state of the dyade depends on the protein environment and has an impact on the reaction barrier. Furthermore, the adaptation of the environment to a fixed protonation state was analyzed via MD simulations.}, subject = {Computational chemistry}, language = {en} } @phdthesis{Merget2015, author = {Merget, Benjamin}, title = {Computational methods for assessing drug-target residence times in bacterial enoyl-ACP reductases and predicting small-molecule permeability for the \(Mycobacterium\) \(tuberculosis\) cell wall}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-127386}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2015}, abstract = {\textbf{Molecular Determinants of Drug-Target Residence Times of Bacterial Enoyl-ACP Reductases.} Whereas optimization processes of early drug discovery campaigns are often affinity-driven, the drug-target residence time \$t_R\$ should also be considered due to an often strong correlation with \textit{in vivo} efficacy of compounds. However, rational optimization of \$t_R\$ is not straightforward and generally hampered by the lack of structural information about the transition states of ligand association and dissociation. The enoyl-ACP reductase FabI of the fatty acid synthesis (FAS) type II is an important drug-target in antibiotic research. InhA is the FabI enzyme of \textit{Mycobacterium tuberculosis}, which is known to be inhibited by various compound classes. Slow-onset inhibition of InhA is assumed to be associated with the ordering of the most flexible protein region, the substrate binding loop (SBL). Diphenylethers are one class of InhA inhibitors that can promote such SBL ordering, resulting in long drug-target residence times. Although these inhibitors are energetically and kinetically well characterized, it is still unclear how the structural features of a ligand affect \$t_R\$. Using classical molecular dynamics (MD) simulations, recurring conformational families of InhA protein-ligand complexes were detected and structural determinants of drug-target residence time of diphenyl\-ethers with different kinetic profiles were described. This information was used to deduce guidelines for efficacy improvement of InhA inhibitors, including 5'-substitution on the diphenylether B-ring. The validity of this suggestion was then analyzed by means of MD simulations. Moreover, Steered MD (SMD) simulations were employed to analyze ligand dissociation of diphenylethers from the FabI enzyme of \textit{Staphylococcus aureus}. This approach resulted in a very accurate and quantitative linear regression model of the experimental \$ln(t_R)\$ of these inhibitors as a function of the calculated maximum free energy change of induced ligand extraction. This model can be used to predict the residence times of new potential inhibitors from crystal structures or valid docking poses. Since correct structural characterization of the intermediate enzyme-inhibitor state (EI) and the final state (EI*) of two-step slow-onset inhibition is crucial for rational residence time optimization, the current view of the EI and EI* states of InhA was revisited by means of crystal structure analysis, MD and SMD simulations. Overall, the analyses affirmed that the EI* state is a conformation resembling the 2X23 crystal structure (with slow-onset inhibitor \textbf{PT70}), whereas a twist of residues Ile202 and Val203 with a further opened helix \$\alpha 6\$ corresponds to the EI state. Furthermore, MD simulations emphasized the influence of close contacts to symmetry mates in the SBL region on SBL stability, underlined by the observation that an MD simulation of \textbf{PT155} chain A with chain B' of a symmetry mate in close proximity of the SBL region showed significantly more stable loops, than a simulation of the tetrameric assembly. Closing Part I, SMD simulations were employed which allow the delimitation of slow-onset InhA inhibitors from rapid reversible ligands. \textbf{Prediction of \textit{Mycobacterium tuberculosis} Cell Wall Permeability.} The cell wall of \textit{M. tuberculosis} hampers antimycobacterial drug design due to its unique composition, providing intrinsic antibiotic resistance against lipophilic and hydrophilic compounds. To assess the druggability space of this pathogen, a large-scale data mining endeavor was conducted, based on multivariate statistical analysis of differences in the physico-chemical composition of a normally distributed drug-like chemical space and a database of antimycobacterial--and thus very likely permeable--compounds. The approach resulted in the logistic regression model MycPermCheck, which is able to predict the permeability probability of small organic molecules based on their physico-chemical properties. Evaluation of MycPermCheck suggests a high predictive power. The model was implemented as a freely accessible online service and as a local stand-alone command-line version. Methodologies and findings from both parts of this thesis were combined to conduct a virtual screening for antimycobacterial substances. MycPermCheck was employed to screen the chemical permeability space of \textit{M. tuberculosis} from the entire ZINC12 drug-like database. After subsequent filtering steps regarding ADMET properties, InhA was chosen as an exemplary target. Docking to InhA led to a principal hit compound, which was further optimized. The quality of the interaction of selected derivatives with InhA was subsequently evaluated using MD and SMD simulations in terms of protein and ligand stability, as well as maximum free energy change of induced ligand egress. The results of the presented computational experiments suggest that compounds with an indole-3-acethydrazide scaffold might constitute a novel class of InhA inhibitors, worthwhile of further investigation.}, subject = {Computational chemistry}, language = {en} } @phdthesis{Paasche2013, author = {Paasche, Alexander}, title = {Mechanistic Insights into SARS Coronavirus Main Protease by Computational Chemistry Methods}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-79029}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2013}, abstract = {The SARS virus is the etiological agent of the severe acute respiratory syndrome, a deadly disease that caused more than 700 causalities in 2003. One of its viral proteins, the SARS coronavirus main protease, is considered as a potential drug target and represents an important model system for other coronaviruses. Despite extensive knowledge about this enzyme, it still lacks an effective anti-viral drug. Furthermore, it possesses some unusual features related to its active-site region. This work gives atomistic insights into the SARS coronavirus main protease and tries to reveal mechanistic aspects that control catalysis and inhibition. Thereby, it applies state-of-the-art computational methods to develop models for this enzyme that are capable to reproduce and interpreting the experimental observations. The theoretical investigations are elaborated over four main fields that assess the accuracy of the used methods, and employ them to understand the function of the active-site region, the inhibition mechanism, and the ligand binding. The testing of different quantum chemical methods reveals that their performance depends partly on the employed model. This can be a gas phase description, a continuum solvent model, or a hybrid QM/MM approach. The latter represents the preferred method for the atomistic modeling of biochemical reactions. A benchmarking uncovers some serious problems for semi-empirical methods when applied in proton transfer reactions. To understand substrate cleavage and inhibition of SARS coronavirus main protease, proton transfer reactions between the Cys/His catalytic dyad are calculated. Results show that the switching between neutral and zwitterionic state plays a central role for both mechanisms. It is demonstrated that this electrostatic trigger is remarkably influenced by substrate binding. Whereas the occupation of the active-site by the substrate leads to a fostered zwitterion formation, the inhibitor binding does not mimic this effect for the employed example. The underlying reason is related to the coverage of the active-site by the ligand, which gives new implications for rational improvements of inhibitors. More detailed insights into reversible and irreversible inhibition are derived from in silico screenings for the class of Michael acceptors that follow a conjugated addition reaction. From the comparison of several substitution patterns it becomes obvious that different inhibitor warheads follow different mechanisms. Nevertheless, the initial formation of a zwitterionic catalytic dyad is found as a common precondition for all inhibition reactions. Finally, non-covalent inhibitor binding is investigated for the case of SARS coranavirus main protease in complex with the inhibitor TS174. A novel workflow is developed that includes an interplay between theory and experiment in terms of molecular dynamic simulation, tabu search, and X-ray structure refinement. The results show that inhibitor binding is possible for multiple poses and stereoisomers of TS174.}, subject = {SARS}, language = {en} } @phdthesis{Grebner2012, author = {Grebner, Christoph}, title = {New Tabu-Search Algorithms for the Exploration of Energy Landscapes of Molecular Systems}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75591}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2012}, abstract = {The visualization of energy functions is based on the possibility of separating different degrees of freedom. The most important one is the Born-Oppenheimer-approximation, which separates nucleus and electron movements. This allows the illustration of the potential energy as a function of the nuclei coordinates. Minima of the surface correspond to stable points like isomers or conformers. They are important for predicting the stability or thermodynamical of a system. Stationary points of first order correspond to transition points. They describe phase transitions, chemical reaction, or conformational changes. Furthermore, the partition function connects the potential hypersurface to the free energy of the system. The aim of the present work is the development and application of new approaches for the efficient exploration of multidimensional hypersurfaces. Initially, the Conformational Analysis and Search Tool (CAST) program was developed to create a basis for the new methods and algorithms. The development of CAST in object oriented C++ included, among other things, the implementation of a force field, different interfaces to external programs, analysis tools, and optimization libraries. Descriptions of an energy landscape require knowledge about the most stable minima. The Gradient Only Tabu Search (GOTS) has been shown to be very efficient in the optimization of mathematical test functions. Therefore, GOTS was taken as a starting point. Tabu-Search is based on the steepest descent - modest ascent strategy. The steepest descent is used for finding local minima, while the modest ascent is taken for leaving a minimum quickly. Furthermore, Tabu-Search is combined with an adaptive memory design to avoid cycling or returning. The highly accurate exploration of the phase space by Tabu-Search is often too expensive for complex optimization problems. Therefore, an algorithm for diversification of the search is required. After exploration of the proximity of the search space, the algorithm would guide the search to new and hopefully promising parts of the phase space. First application of GOTS to conformational search revealed weaknesses in the diversification search and the modest ascent part. On the one hand, the original methodology for diversification is insufficiently diverse. The algorithm is considerably improved by combining the more local GOTS with the wider searching Basin Hopping (BH) approach. The second weak point is a too inaccurate and inefficient modest ascent strategy. Analysis of common transition state search algorithms lead to the adaption of the Dimer-method to the Tabu-Search approach. The Dimer-method only requires the first derivatives for locating the closest transition state. For conformational search, dihedral angles are usually the most flexible degrees of freedom. Therefore, only those are used in the Dimer-method for leaving a local minimum. Furthermore, the exact localization of the reaction pathway and the transition state is not necessary as the local minimum position should only be departed as fast as possible. This allows for larger step sizes during the Dimer-search. In the following optimization step, all coordinates are relaxed to remove possible strains in the system. The new Tabu-Search method with Dimer-search delivers more and improved minima. Furthermore, the approach is faster for larger systems. For a system with approximately 1200 atoms, an acceleration of 40 was measured. The new approach was compared to Molecular Dynamics with optimization (MD), Simulated Annealing (SA), and BH with the help of conformational search problems of bio-organic systems. In all cases, a better performance was found. A comparison to the Monte Carlo Multiple Minima/Low Mode Sampling (MCMM/LM) method proved the outstanding performance of the new Tabu-Search approach. The solvation of the chignolin protein further revealed the possibility of uncovering discrepancies between the employed theoretical model and the experimental starting structure. Ligand optimization for improvement of x-ray structures was one further new application field. Besides the global optimization, the search for transition states and reaction pathways is also of paramount importance. These points describe different transitions of stable states. Therefore, a new approach for the exploration of such cases was developed. The new approach is based on a global minimization of a hyperplane being perpendicular to the reaction coordinate. Minima of this reduced phase space belong to traces of transition states between reactant and product states on the unchanged hypersurface. Optimization to the closest transition state using the Dimer-method delivers paths lying between the initial and the final state. An iterative approach finally yields complex reaction pathways with many intermediate local minima. The PathOpt algorithm was tested by means of rearrangements of argon clusters showing very promising results.}, subject = {Globale Optimierung}, language = {en} }