In silico-Design, Synthese und Evaluation von Kinase- und Proteasom-Inhibitoren sowie Fluoreszenzsonden.

Übergeordnetes Ziel dieser Arbeit war die systematische Anwendung interdisziplinärer Methoden des modernen Wirkstoffdesigns sowie deren Weiter- und Neuentwicklung. Mit Bortezomib und Carfilzomib sind bereits zwei Inhibitoren des 20S-Proteasoms zur Behandlung schwerer Tumorerkrankungen des blutbildenden Systems zugelassen, die jedoch aufgrund ihres (pseudo)-irreversiblen Bindungsmodus nicht zur Behandlung solider Tumoren geeignet sind. alpha-Ketophenylamide, allen voran die Leitstruktur BSc2189, binden nicht nur nachweislich reversibel, sondern bieten durch den Kontakt mit der gestrichenen Seite der ß5-Untereinheit völlig neue Möglichkeiten, um Aktivität und Selektivität zu optimieren. Eine solche Optimierung ist mit dem in dieser Arbeit entwickelten Wirkstoff BSc4999 gelungen, der mit einem IC50-Wert von 38 nM doppelt so aktiv ist wie die ursprüngliche Leitstruktur. Mit der Software DOCKTITE konnte im Rahmen dieser Arbeit eine Methode zum kovalenten Docking entwickelt werden, die keinerlei Restriktionen bezüglich elektrophiler Kopfgruppen, Proteinklassen oder nukleophiler Seitenketten zeigt und deren Präzision und Schnelligkeit in einer umfangreichen Validierungsstudie belegt wurde. Neben der Entwicklung von Antitumorwirkstoffen befanden sich die Alzheimer-Demenz und die Entwicklung potentieller diagnostischer Sonden und Wirkstoffe im Fokus dieser Arbeit

Validation and Applications of Protein-Ligand Docking Approaches Improved for Metalloligands with Multiple Vacant Sites

Altres ajuts: COST Action CM1306Decoding the interaction between coordination compounds and proteins is of fundamental importance in biology, pharmacy, and medicine. In this context, protein-ligand docking represents a particularly interesting asset to predict how small compounds could interact with biomolecules, but to date, very little information is available to adapt these methodologies to metal-containing ligands. Here, we assessed the predictive capability of a metal-compatible parameter set for the docking program GOLD for metalloligands with multiple vacant sites and different geometries. The study first presents a benchmark of 25 well-characterized X-ray metalloligand-protein adducts. In 100% of the cases, the docking solutions are superimposable to the X-ray determination, and in 92% the value of the root-mean-square deviation between the experimental and calculated structures is lower than 1.5 Å. After the validation step, we applied these methods to five case studies for the prediction of the binding of pharmacological active metal species to proteins: (i) the anticancer copper(II) complex [Cu II (Br)(2-hydroxy-1-naphthaldehyde benzoyl hydrazine)(indazole)] to human serum albumin (HSA); (ii) one of the active species of antidiabetic and antitumor vanadium compounds, V IV O 2+ ion, to carboxypeptidase; (iii) the antiarthritic species [Au I (PEt 3 )] + to HSA; (iv) the antitumor oxaliplatin to ubiquitin; (v) the antitumor ruthenium(II) compound RAPTA-PentaOH to cathepsin B. The calculations suggested that the binding modes are in good agreement with the partial information retrieved from spectroscopic and spectrometric analysis and allowed us, in certain cases, to propose additional hypotheses. This method is an important update in protein-metalloligand docking, which could have a wide field of application, from biology and inorganic biochemistry to medicinal chemistry and pharmacology

In silico investigation of hepatitis c virus: a novel perspective into targeted viral inhibition of NS3 helicase, NS 3/4a protease and NS5b RNA dependent RNA polymerase.

Doctoral Degrees (Pharmaceutical Sciences). University of KwaZulu-Natal. Westville, 2019.Hepatitis C Virus (HCV) is an escalating global healthcare and economic burden that requires extensive intervention to alleviate its control. Over the years, drug design efforts have produced many anti-HCV drugs; however, due to drug resistance brought on by numerous genetic variations of the virus and lack of specificity and stability, current drugs are rendered ineffective. The situation has been further intensified by the absence of a viable vaccine. For these reasons, continuous HCV research is imperative for the design and development of promising inhibitors that address the challenges faced by present antiviral therapies. Moreover, exposure of previously neglected viral protein targets can offer another potentially valuable therapeutic route in drug design research. Structure-based drug design approaches accentuate the development of small inhibitor molecules that interact with therapeutic targets through non-covalent interactions. The unexpected discovery of covalent inhibitors and their distinctive nature of instigating complete and irreversible inhibition of targets have shifted attention away from the use of non-covalent drugs in antiviral treatment. This has led to significant progress in understanding covalent inhibition regarding their underlying mechanism of action and in the design of novel covalent inhibitors that work against biological targets. However, due to difficulties arising in its application and resultant safety, the pharmaceutical industry were reluctant to pursue this strategy. With the use of rational drug design, a novel strategy was then proposed known as selective covalent inhibition. Due to the lack of competent protocols and information, little is known regarding selective covalent inhibition This study investigates three biological HCV targets, NS3 protease, RNA helicase and NS5B RNAdependent RNA polymerase. With constantly evolving viruses like HCV, computational methods including molecular modelling and docking, virtual screening and molecular dynamic simulations have allowed chemists to screen millions of compounds to filter out potential lead drugs. These in silico approaches have allowed Computer-Aided Drug Design as a cost-effective strategy to accelerate the process of drug discovery. The above techniques, with numerous other computational tools were employed in this study to fill the gap in HCV drug research by providing insights into the structural and dynamic changes that describe the mechanism of selective covalent inhibition and pharmacophoric features that lead to unearthing of potential small inhibitor molecules against Hepatitis C. v The first study (Chapter 4) provides a comprehensive review on HCV NS3/4A protein, current therapies and covalent inhibition as well as introduces a technical guideline that provides a systematic approach for the design and development of potent, selective HCV inhibitors. The second study (Chapter 5) provides a comprehensive understanding concerning the implications of selective covalent inhibition on the activity of HCV NS5B RNA-dependent RNA polymerase, with respect to key components required for viral replication, when bound to a target-specific small inhibitor molecule. The third study (Chapter 6) is preliminary investigation that uses Pharmacophore-based virtual screening as an efficient tool for the discovery of improved potential HCV NS3 helicase inhibitors. The pharmacophoric features were created based on the highly contributing amino acid residues that bind with highest affinity to the weak inhibitor, quercetin. These residues were identified based on free energy footprints obtained from molecular dynamic and thermodynamic calculations. Post molecular dynamic analysis and appropriate drug-likeness properties of the three top-hit compounds revealed that ZINC02495613 could be a more effective potential HCV helicase inhibitor; however, further validation steps are still required. This study offers a comprehensive in silico perspective to fill the gap in rational drug design research against HCV, thus providing an insight into the mechanism of selective covalent inhibition, uncovering a previously neglected viral target and identifying possible antiviral drugs. To this end, the work presented in this report is considered a fundamental platform to advance research toward the design and development of novel and selective anti-HCV drugs

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions

Rapid Covalent-Probe Discovery by Electrophile-Fragment Screening

Covalent probes can display unmatched potency, selectivity, and duration of action; however, their discovery is challenging. In principle, fragments that can irreversibly bind their target can overcome the low affinity that limits reversible fragment screening, but such electrophilic fragments were considered nonselective and were rarely screened. We hypothesized that mild electrophiles might overcome the selectivity challenge and constructed a library of 993 mildly electrophilic fragments. We characterized this library by a new high-throughput thiol-reactivity assay and screened them against 10 cysteine-containing proteins. Highly reactive and promiscuous fragments were rare and could be easily eliminated. In contrast, we found hits for most targets. Combining our approach with high-throughput crystallography allowed rapid progression to potent and selective probes for two enzymes, the deubiquitinase OTUB2 and the pyrophosphatase NUDT7. No inhibitors were previously known for either. This study highlights the potential of electrophile-fragment screening as a practical and efficient tool for covalent-ligand discovery

Structure-based approaches applied to the study of pharmaceutical relevant targets

Computer Aided Drug Design/Discovery methods became complementary to traditional and modern drug discovery approaches. Indeed CADD is useful to improve and speed up the detection and the optimization of bioactive molecules. The present study is focused on the application of structure-based approaches to the study of pharmaceutical relevant targets. The introduction provides a quick overview on the fundamentals of computational chemistry and structure-based methods, while in the successive chapters the main targets investigated through these methods are treated. In particular we focused our attention on Reverse Transcriptase of HIV-1, Monoamine oxidase B and VP35 of Ebola virus. The last chapter is dedicated to the validation of covalent docking performed with Autodock

DOCKTITEA Highly Versatile Step-by-Step Workflow for Covalent Docking and Virtual Screening in the Molecular Operating Environment

The formation of a covalent bond with the target is essential for a number of successful drugs, yet tools for covalent docking without significant restrictions regarding warhead or receptor classes are rare and limited in use. In this work we present DOCKTITE, a highly versatile workflow for covalent docking in the Molecular Operating Environment (MOE) combining automated warhead screening, nucleophilic side chain attachment, pharmacophore-based docking, and a novel consensus scoring approach. The comprehensive validation study includes pose predictions of 35 protein/ligand complexes which resulted in a mean RMSD of 1.74 Å and a prediction rate of 71.4% with an RMSD below 2 Å, a virtual screening with an area under the curve (AUC) for the receiver operating characteristics (ROC) of 0.81, and a significant correlation between predicted and experimental binding affinities (ρ = 0.806, <i>R</i>² = 0.649, <i>p</i> < 0.005)