Global ETD Search

1	Use and Development of Computational Tools in Drug Discovery: From Small Molecules to Cyclic Peptides Santiago, Daniel Navarrete 01 January 2012 (has links) The scope of this work focuses on computationally modeling compounds with protein structures. While the impetus of drug discovery is the innovation of new therapeutic molecules, it also involves distinguishing molecules that would not be an effective drug. This can be achieved by inventing new tools or by refining old tools. Virtual screening (VS, also called docking), the computational modeling of a molecule in a receptor structure, is a staple in predicting a molecule's affinity for an intended target. In our Virtual Target Screening system (also called inverse-docking), VS is used to find high-affinity targets, which can potentially explain absorption, distribution, metabolism, and excretion (ADME) of a molecule of interest in the human body. The next project, low-mode docking (LD), attempts to improve VS by incorporating protein flexibility into traditional docking where a static receptor structure has potential to produce poor results due to incorrectly predicted ligand poses. Finally, VS, performed mostly on small molecules, is scaled up to cyclic peptides by employing Monte Carlo simulations and molecular dynamics to mimic the steps of small molecule VS. The first project discussed is Virtual Target Screening (also called inverse-docking) where a small molecule is virtually screened against a library of protein structures. Predicting receptors to which a synthesized compound may bind would give insights to drug repurposing, metabolism, toxicity, and lead optimization. Our protocol calibrates each protein entry with a diverse set of small molecule structures, the NCI Diversity Set I. Our test set, 20 kinase inhibitors, was predicted to have a high percentage of kinase "hits" among approximately 1500 protein structures. Further, approved drugs within the test set generally had better rates of kinase hits. Next, normal mode analysis (NMA), which can computationally describe the fundamental motions of a receptor structure, is utilized to approach the rigid body bias problem in traditional docking techniques. Traditional docking involves the selection of a static receptor structure for VS; however, protein structures are dynamic. Simulation of the induced fit effect in protein-ligand binding events is modeled by full articulation of the approximated large-scale low-frequency normal modes of vibration, or "low-modes," coupled with the docking of a ligand structure. Low-mode dockings of 40 cyclin dependent 2 (CDK2) inhibitors into 54 low-modes of CDK2 yielded minimum root-mean-square deviation (RMSD) values of 1.82 – 1.20 Å when compared to known coordinate data. The choice of pose is currently limited to docking score, however, with ligand pose RMSD values of 3.87 – 2.07 Å. When compared to corresponding traditional dockings with RMSD values of 5.89 – 2.33 Å, low-mode docking was more accurate. The last discussion involves the rational docking of a cyclic peptide to the murine double minute 2 (MDM2) oncoprotein. The affinity for a cyclic peptide (synthesized by Priyesh Jain, McLaughin Lab, University of South Florida), PJ-8-73, in MDM2 was found to be within an order of magnitude of a cyclic peptide from the Robinson Lab at the University of Zurich in Switzerland. Both are Β-hairpin cyclic peptides with IC50 values of 650 nm and 140 nm, respectively. Using the co-crystalized structure of the Robinson peptide (PDB 2AXI), we modeled the McLaughlin peptide based on an important interaction of the 6-chloro-tryptophan residue of the Robinson peptide occupying the same pocket in MDM2 as the tryptophan residue by the native p53 transactivation helical domain. By preserving this interaction in initial cyclic peptide poses, the resulting pose of PJ-8-73 structure in MDM2 possessed comparable active site residue contacts and surface area. These protocols will aid medical research by using computer technology to reduce cost and time. VTS utilizes a unique structural and statistical calibration to virtually assay thousands of protein structures to predict high affinity binding. Determining unintended protein targets aids in creating more effective drugs. In low-mode docking, the accuracy of virtual screening was increased by including the fundamental motions of proteins. This newfound accuracy can decrease false negative results common in virtual screening. Lastly, docking techniques, usually for small molecules, were applied to larger peptide molecules. These modifications allow for the prediction of peptide therapeutics in protein-protein interaction modulation, a growing interest in medicine. Impactful in their own ways, these procedures contribute to the discovery of drugs, whether they are small molecules or cyclic peptides. Low-mode Normal Mode Analysis Peptide Docking Protein Flexibility Virtual Target Screening Chemistry Other Chemistry Pharmacology
2	Computational modeling of protein-protein and protein-peptide interactions Porter, Kathryn 30 August 2019 (has links) Protein-protein and protein-peptide interactions play a central role in various aspects of the structural and functional organization of the cell. While the most complete structural characterization is provided by X-ray crystallography, many biological interactions occur in complexes that will not be amenable to direct experimental analysis. Therefore, it is important to develop computational docking methods that start from the structures of component proteins and predict the structure of their complexes, preferably with accuracy close to that provided by X-ray crystallography. This thesis details three applications of computational protein modeling, including the study of antibody maturation mechanisms, and the development of protocols for peptide-protein interaction prediction and template-based modeling of protein complexes. The first project, a comparative analysis of docking an antigen structure to antibodies across a lineage, reveals insights into antibody maturation mechanisms. A linear relationship between near-native docking results and changes in binding free energy is established, and used to investigate changes in binding affinity following mutation across two antibody-antigen systems: influenza and anthrax. The second project demonstrates that a motif-based search of available protein crystal structures is sufficient to adequately represent the conformational space sampled by a flexible peptide, compared to that of a rigid globular protein. This observation forms the basis for a global peptide-protein docking protocol that has since been implemented into the Structural Bioinformatics Laboratory’s docking web server, ClusPro. Finally, as structure availability remains a roadblock to many studies, researchers turn to homology modeling, in which the desired protein sequence is modeled onto a related structure. This is particularly challenging when the target is a protein complex, further restricting template availability. To address this problem, the third project details the development of a new template-based modeling protocol to be integrated into the ClusPro server. The implementation of a novel template-based search enables users to model both homomeric and heteromeric complexes, greatly expanding ClusPro server functionality. / 2020-08-30T00:00:00Z Biomedical engineering Antibody maturation Computational biology Homology modeling Peptide docking Protein docking Protein-protein interaction
3	The Structural Basis of Peptide Binding at Class A G Protein-Coupled Receptors Vu, Oanh, Bender, Brian Joseph, Pankewitz, Lisa, Huster, Daniel, Beck-Sickinger, Annette G., Meiler, Jens 05 May 2023 (has links) G protein-coupled receptors (GPCRs) represent the largest membrane protein family and a significant target class for therapeutics. Receptors from GPCRs’ largest class, class A, influence virtually every aspect of human physiology. About 45% of the members of this family endogenously bind flexible peptides or peptides segments within larger protein ligands. While many of these peptides have been structurally characterized in their solution state, the few studies of peptides in their receptor-bound state suggest that these peptides interact with a shared set of residues and undergo significant conformational changes. For the purpose of understanding binding dynamics and the development of peptidomimetic drug compounds, further studies should investigate the peptide ligands that are complexed to their cognate receptor. info:eu-repo/classification/ddc/540 ddc:540
4	The Allosteric Activation of α7 nAChR by α-Conotoxin MrIC Is Modified by Mutations at the Vestibular Site Gulsevin, Alican, Papke, Roger L., Stokes, Clare, Tran, Hue N. T., Jin, Aihua H., Vetter, Irina, Meiler, Jens 08 May 2023 (has links) α-conotoxins are 13–19 amino acid toxin peptides that bind various nicotinic acetylcholine receptor (nAChR) subtypes. α-conotoxin Mr1.7c (MrIC) is a 17 amino acid peptide that targets α7 nAChR. Although MrIC has no activating effect on α7 nAChR when applied by itself, it evokes a large response when co-applied with the type II positive allosteric modulator PNU-120596, which potentiates the α7 nAChR response by recovering it from a desensitized state. A lack of standalone activity, despite activation upon co-application with a positive allosteric modulator, was previously observed for molecules that bind to an extracellular domain allosteric activation (AA) site at the vestibule of the receptor. We hypothesized that MrIC may activate α7 nAChR allosterically through this site. We ran voltage-clamp electrophysiology experiments and in silico peptide docking calculations in order to gather evidence in support of α7 nAChR activation by MrIC through the AA site. The experiments with the wild-type α7 nAChR supported an allosteric mode of action, which was confirmed by the significantly increased MrIC + PNU-120596 responses of three α7 nAChR AA site mutants that were designed in silico to improve MrIC binding. Overall, our results shed light on the allosteric activation of α7 nAChR by MrIC and suggest the involvement of the AA site. info:eu-repo/classification/ddc/610 ddc:610
5	Entwicklung und Charakterisierung von Komplexen aus Cetrorelix und biophilen Trägermaterialien Rattei, Thomas 20 July 2002 (has links) (PDF) Die Dissertation beschreibt Arbeiten zur Herstellung neuer Cetrorelixkomplexe, zur Kinetik der dynamischen Liberation, zur Struktur von Aggregaten und Komplexen von Cetrorelix und zur Berechnung von Komplexeigenschaften mit Molecular Modeling. / Presented are results about new complexes of cetrorelix, the kinetics of dynamical liberations, the structure of Cetrorelix aggregates and complexes and the computation of properties of complexes by molecular modeling. Biochemie Dissertation Peptiddocking Peptidkomplex Biochemistry Peptide complex Peptide docking PhD-Thesis ddc:30 rvk:VX 8557 Bioverfügbarkeit Cetrorelix Depotpräparat Komplexbildungsreaktion Molekulardesign Pharmakokinetik Wirkstofffreisetzung
6	Entwicklung und Charakterisierung von Komplexen aus Cetrorelix und biophilen Trägermaterialien Rattei, Thomas 12 August 2002 (has links) Die Dissertation beschreibt Arbeiten zur Herstellung neuer Cetrorelixkomplexe, zur Kinetik der dynamischen Liberation, zur Struktur von Aggregaten und Komplexen von Cetrorelix und zur Berechnung von Komplexeigenschaften mit Molecular Modeling. / Presented are results about new complexes of cetrorelix, the kinetics of dynamical liberations, the structure of Cetrorelix aggregates and complexes and the computation of properties of complexes by molecular modeling. info:eu-repo/classification/ddc/30 ddc:30
7	Modellierung und Visualisierung von Systemen zur Beschreibung der intra- und intermolekularen Wechselwirkungen in hydrophoben Peptiden Schneider, Alexander 11 November 2014 (has links) (PDF) Die vorliegende Arbeit beschäftigt sich mit der Untersuchung und Beschreibung der Eigenschaften der synthetischen Dekapeptide Cetrorelix und Ozarelix durch analytische Methoden und computergestützte Modellierung. Diese Moleküle sind hydrophobe, aggregierende Antagonisten des Gonadotropin-Releasing-Hormons (GnRH). Zusätzlich wurden amyloidbildende Peptidstrukturen als Modelle für die Assoziationsprozesse in hydrophoben Peptiden untersucht und visualisiert. Die intrinsische Fluoreszenz der GnRH-Antagonisten und zusätzlich der Peptide Teverelix und D-Phe6-GnRH sowie von verkürzten Fragmenten des Cetrorelix wurde untersucht. Ein Strukturmodell für die Beschreibung der Aggregation der Dekapeptide wurde erarbeitet. Der Aufbau eines Rechenclusters durch das Einbinden der Computer am Lehrstuhl in ein Linux-System zur Verteilung von Rechenprozessen über das Netzwerk ermöglichte die Bereitstellung der notwendigen Leistung zur Realisierung der Berechnungen. Es wurden Werkzeuge zur Modellierung der solvatisierten Aggregate von Peptiden ohne eindeutige Vorzugsstruktur programmiert und in ein Docking-System für beliebige Moleküle eingebunden. Verwendet wurde das Kraftfeld MMFF94 mit einer Erweiterung durch ein Verfahren zur dynamischen Berechnung von Partialladungen in Molekülstrukturen. Solvatisierte Aggregate der Dekapeptide und von bekannten amyloidbildenden Strukturen wurden modelliert (Docking). Berechnet wurden als aggregierend beschriebene Sequenzen und entsprechende Vergleichsstrukturen des Calcitonins, des Insel-Amyloid-Polypeptides, des beta2-Mikroglobulins, des Amyloid-beta-Proteins, des Lactoferrins und weitere Modellpeptide. Die wesentlichen Wechselwirkungen während der Aggregation konnten schließlich anhand von Dynamik-Simulationen der faltblattartigen Dimere des Cetrorelix und Ozarelix beschrieben werden. So wurden die Prozesse der hydrophoben Assoziation und Stabilisierung durch Wasserstoffbrücken von Peptiden veranschaulicht und auf molekularer Ebene erfolgreich analysiert. Die Visualisierung der erhaltenen Modellierungsergebnisse erfolgt durch die Darstellung der Strukturen und Dynamik-Simulationen als interaktive 3D-Modelle in einem für diese Arbeit aufgebauten Internetauftritt. / This work discusses the analysis of the aggregation properties of the gonadotropin releasing hormone antagonists Cetrorelix, Teverelix, Ozarelix and of small amyloid forming model peptides by analytical fluorescence spectroscopy and molecular modelling. A high performance linux compute cluster was developed for calculation of molecular structures. Solvated aggregate clusters of peptides without defined secondary structure were modelled by molecular mechanics methods (forcefield mmff94) in combination with an advanced charge equilibration and docking technique. Molecular dynamics of solvated peptide dimers were implemented and the role of hydrophic association and hydrogen bond formation in hydrophobic peptide aggregates was explained. Finally, an aggregation model for the directed association of hydrophobic peptides is presented. The modelling results, 3d structures and dynamic simulations are visualized in an interactive web material. Aggregation GnRH-Antagonist Peptidaggregation Gonadotropin-Releasinghormon-Analoga Cetrorelix Ozarelix Teverelix Fluoreszenzspektroskopie LINUX-Rechencluster Molekulardynamik Molekülmechanik Docking Solvatation Kraftfeldberechnung MMFF94 Naphthylalanin Tyrosin Tyrosinat Hydropathie Wasserstoffbrücken aggregation peptide aggregation peptide docking fluorescence spectroscopy amyloid molecular modelling molecular dynamics force field hydrogen bonds hydropathy hydrophobicity hydrophobic effect secondary structure beta sheet compute cluster ddc:540 rvk:WD 5250 Aggregation Aggregat <Chemie> Assoziation <Chemie> Gonadotropin-Releasinghormon-Analoga Cetrorelix Fluoreszenzspektroskopie Amyloid Gel Aminosäuren Nichtproteinogene Aminosäuren Peptide Strukturanalyse Faltblatt Sekundärstruktur Wasserstoffbrückenbindung Hydrophobe Wechselwirkung Hydrophobie Van-der-Waals-Kraft Aromaten LINUX Cluster <Rechnernetz> Hochleistungsrechnen Kraftfeld Kraftfeld-Rechnung Modellierung Molekulardesign Molekulardynamik Docking <Chemie> Solvatation Tyrosin Calcitonin Amylin Mikroglobulin <beta-2-> Amyloid <beta-> Amyloid-Peptid <beta-> Lactoferrin Visualisierung VRML Virtualisierung Visuelle Wahrnehmung
8	Modellierung und Visualisierung von Systemen zur Beschreibung der intra- und intermolekularen Wechselwirkungen in hydrophoben Peptiden Schneider, Alexander 08 October 2014 (has links) Die vorliegende Arbeit beschäftigt sich mit der Untersuchung und Beschreibung der Eigenschaften der synthetischen Dekapeptide Cetrorelix und Ozarelix durch analytische Methoden und computergestützte Modellierung. Diese Moleküle sind hydrophobe, aggregierende Antagonisten des Gonadotropin-Releasing-Hormons (GnRH). Zusätzlich wurden amyloidbildende Peptidstrukturen als Modelle für die Assoziationsprozesse in hydrophoben Peptiden untersucht und visualisiert. Die intrinsische Fluoreszenz der GnRH-Antagonisten und zusätzlich der Peptide Teverelix und D-Phe6-GnRH sowie von verkürzten Fragmenten des Cetrorelix wurde untersucht. Ein Strukturmodell für die Beschreibung der Aggregation der Dekapeptide wurde erarbeitet. Der Aufbau eines Rechenclusters durch das Einbinden der Computer am Lehrstuhl in ein Linux-System zur Verteilung von Rechenprozessen über das Netzwerk ermöglichte die Bereitstellung der notwendigen Leistung zur Realisierung der Berechnungen. Es wurden Werkzeuge zur Modellierung der solvatisierten Aggregate von Peptiden ohne eindeutige Vorzugsstruktur programmiert und in ein Docking-System für beliebige Moleküle eingebunden. Verwendet wurde das Kraftfeld MMFF94 mit einer Erweiterung durch ein Verfahren zur dynamischen Berechnung von Partialladungen in Molekülstrukturen. Solvatisierte Aggregate der Dekapeptide und von bekannten amyloidbildenden Strukturen wurden modelliert (Docking). Berechnet wurden als aggregierend beschriebene Sequenzen und entsprechende Vergleichsstrukturen des Calcitonins, des Insel-Amyloid-Polypeptides, des beta2-Mikroglobulins, des Amyloid-beta-Proteins, des Lactoferrins und weitere Modellpeptide. Die wesentlichen Wechselwirkungen während der Aggregation konnten schließlich anhand von Dynamik-Simulationen der faltblattartigen Dimere des Cetrorelix und Ozarelix beschrieben werden. So wurden die Prozesse der hydrophoben Assoziation und Stabilisierung durch Wasserstoffbrücken von Peptiden veranschaulicht und auf molekularer Ebene erfolgreich analysiert. Die Visualisierung der erhaltenen Modellierungsergebnisse erfolgt durch die Darstellung der Strukturen und Dynamik-Simulationen als interaktive 3D-Modelle in einem für diese Arbeit aufgebauten Internetauftritt. / This work discusses the analysis of the aggregation properties of the gonadotropin releasing hormone antagonists Cetrorelix, Teverelix, Ozarelix and of small amyloid forming model peptides by analytical fluorescence spectroscopy and molecular modelling. A high performance linux compute cluster was developed for calculation of molecular structures. Solvated aggregate clusters of peptides without defined secondary structure were modelled by molecular mechanics methods (forcefield mmff94) in combination with an advanced charge equilibration and docking technique. Molecular dynamics of solvated peptide dimers were implemented and the role of hydrophic association and hydrogen bond formation in hydrophobic peptide aggregates was explained. Finally, an aggregation model for the directed association of hydrophobic peptides is presented. The modelling results, 3d structures and dynamic simulations are visualized in an interactive web material. info:eu-repo/classification/ddc/540 ddc:540

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