Bioinformatic analysis of bacterial and eukaryotic amino- terminal signal peptides

Ph.DDOCTOR OF PHILOSOPH

Alfaviiruse mittestruktuurne proteaas ja tema liitvalgust substraat: täiuslikult korraldatud kooselu reeglid

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Alfaviirused (sugukond Togaviridae) on artriiti ja entsefaliiti põhjustavad RNA genoomsed viirused. Nende paljunemise strateegia aluseks on viiruse replikaasi valkude süntees ühe nn. mittestruktuurse eelvalgu P1234 kujul ning selle ajaliselt reguleeritud lõikamine valmis valkudeks nsP2 proteaasi abil. Käesoleva väitekirja aluseks olevad uurimistööd viisid nsP2 substraat-spetsiifilisust tagavate mehhanismide väljaselgitamiseni; muu hulgas kirjeldati uudset proteolüütiliste lõikamiste regulatsioonimehhanismi, mis põhineb liitvalgu erinevate regioonide vahelisel „suhtlemisel“ viiruse replikatsiooni kompleksi moodustamise käigus. Sellest saab järeldada, et P1234 lõikamise ajaline regulatsioon sõltub otseselt replikatsioonikompleksi konfiguratsioonidest, millised omakorda on määratud selle komponentide vaheliste interaktsioonide poolt. Seega tõuseb viiruse nsP2 proteaas esile kui keerulise signaalvõrgustiku keskne element, mille roll viirus infektsiooni regulatsioonis seisneb replikatsiooniga kaasnevate sündmuste „jälgimises“ ja nendele reageerimises. Viimane põhineb sellel, et kui viiruse paljunemine jõuab kindla vahe-etapini, siis kaasneb sellega lõikamiskohtade ja/või muude oluliste struktuuride „esitlemine“ proteaasile, mis reageerib toimunud muudatustele lokaalse signaalülekande, mis lõppkokkuvõttes viib replikaasi kompleksi struktuuri järjestikulistele muudatustele, käivitamisega. Kokkuvõttes, tõid läbiviidud uurimised välja asjaolu, et lisaks varem teada olnud lõikamisjärjestuste äratundmisele, omab ka makromolekulaarsete struktuuride moodustamine viiruse valkude poolt olulist (ja mitmel juhul isegi määravat) rolli viiruse proteaasi töö reguleerimisel. Veel enam, eeldati, et seesugune mitmetahuline regulatsioon võib olla paljukomponentsete proteolüütiliste süsteemide üldine omadus. Kirjeldatud avastused ja nende lahtimõtestamine omavad olulist rolli uurimistöödele, mille eesmärgiks on alfaviiruste paljunemist takistavate lähenemiste väljatöötamine. Nii võib saadud tulemuste põhjal järeldada, et lisaks proteaasi aktiivsuse otsesele mõjutamisele võib viiruse replikatsiooni takistada ka mõjutades proteolüüsi regulatsiooni tagavaid molekulide vahelised seoseid.Alphaviruses from the Togaviridae family are RNA viruses that may cause arthritic syndroms and encephalitis. The alphavirus replication strategy relies on the production of replicase proteins initially in the form of non-structural (ns) polyprotein precursor P1234, which during the course of replication becomes proteolytically processed by the virus-encoded nsP2 protease in a temporally regulated manner. The studies that constitute the basis of this thesis led to identification of the requirements for substrate specificity of nsP2 protease and revealed novel mechanism for the regulation of processing based on the specific communication between distant parts of the viral polyprotein brought together during assembly of replication complex. It was concluded that the order of alphaviral ns-polyprotein processing is mostly dependent on the configuration of the replication complex imposed by intermolecular interactions meant to guarantee timely cleavages. The alphaviral protease therefore emerges as an integral part of the sophisticated signaling mechanism, in which the regulatory task of the protease consists of monitoring the succession and completion of the events of viral infection. Once the respective replication status-induced conformational changes within replicase allow the presentation of the scissile bond and/or other essential determinants of substrate recognition like exosites, the local protease signaling is initiated, which apparently leads to further reconfiguration of the viral replication complex. Combined, the studies unveiled the decisive role played by the macromolecular assembly-dependent component of substrate recognition in addition to the sequence-dependent component, the combination of which may be expected to constitute the basis of regulation in multi-site proteolytic systems in general. Described findings and their interpretations are expected to provide with essential grounds and directions for further studies on the restriction of alphaviral replication through affecting the center of viral proteolytic activity or via intervention with its regulation by targeting intramolecular interactions

INTEGRATED MOLECULAR PROFILING FOR ANALYZING AND PREDICTING THERAPEUTIC MECHANISM, RESPONSE, BIOMARKER AND TARGET

Ph.DDOCTOR OF PHILOSOPH

Entwicklung einer computergestützten Methode zum reaktionsbasierten De-Novo-Design wirkstoffartiger Verbindungen

A new method for computer-based de novo design of drug candidate structures is proposed. DOGS (Design of Genuine Structures) features a ligand-based strategy to suggest new molecular structures. The quality of designed compounds is assessed by a graph kernel method measuring the distance of designed molecules to a known reference ligand. Two graph representations of molecules (molecular graph and reduced graph) are implemented to feature different levels of abstraction from the molecular structure. A fully deterministic construction procedure explicitly designed to facilitate synthesizability of proposed structures is realized: DOGS uses readily available synthesis building blocks and established reaction schemes to assemble new molecules. This approach enables the software to propose not only the final compounds, but also to give suggestions for synthesis routes to generate them at the bench. The set of synthesis schemes comprises about 83 chemical reactions. Special focus was put on ring closure reactions forming drug-like substructures. The library of building blocks consists of about 25,000 readily available synthesis building blocks. DOGS builds up new structures in a stepwise process. Each virtual synthesis step adds a fragment to the growing molecule until a stop criterion (upper threshold for molecular mass or number of synthesis steps) is fulfilled. In a theoretical evaluation, a set of ~1,800 molecules proposed by DOGS is analyzed for critical properties of de novo designed compounds. The software is able to suggest drug-like molecules (79% violate less than two of Lipinski’s ‘rule of five’). In addition, a trained classifier for drug-likeness assigns a score >0.8 to 51% of the designed molecules (with 1.0 being the top score). In addition, most of the DOGS molecules are deemed to be synthesizable by a retro-synthesis descriptor (77% of molecules score in the top 10% of the decriptor’s value range). Calculated logP(o/w) values of constructed molecules resemble a unimodal distribution centred close to the mean of logP(o/w) values calculated for the reference compounds. A structural analysis of selected designs reveals that DOGS is capable of constructing molecules reflecting the overall topological arrangement of pharmacophoric features found in the reference ligands. At the same time, the DOGS designs represent innovative compounds being structurally distinct from the references. Synthesis routes for these examples are short and seem feasible in most cases. Some reaction steps might need modification by using protecting groups to avoid unwanted side reactions. Plausible bioisosters for known privileged fragments addressing the S1 pocket of trypsin were proposed by DOGS in a case study. Three of them can be found in known trypsin inhibitors as S1-adressing side chains. The software was also tested in two prospective case studies to design bioactive compounds. DOGS was applied to design ligands for human gamma-secretase and human histamine receptor subtype 4 (hH4R). Two selected designs for gamma-secretase were readily synthesizable as suggested by the software in one-step reactions. Both compounds represent inverse modulators of the target molecule. In a second case study, a ligand candidate selected for hH4R was synthesized exactly following the three-step synthesis plan suggested by DOGS. This compound showed low activity on the target structure. The concept of DOGS is able to deliver synthesizable and bioactive compounds. Suggested synthesis plans of selected compounds were readily pursuable. DOGS can therefore serve as a valuable idea generator for the design of new pharmacological active compounds.Im Rahmen der vorliegenden Arbeit wird eine neue Methode zum computergestützten de novo Design von wirkstoffartigen Molekülen vorgestellt. Ziel ist es, automatisiert und zielgerichtet neuartige Moleküle mit biologischer Aktivität zu entwerfen. Das entwickelte Programm DOGS (Design of Genuine Structures) schlägt zusätzlich zu den chemischen Verbindungen mögliche Strategien zu deren Synthese vor. Ein vollständig deterministischer Konstruktionsalgorithmus verwendet verfügbare Synthesebausteine und etablierte chemische Reaktionen zum Aufbau der neuen Moleküle. Die Bibliothek der Synthesebausteine umfasst etwa 25.000 Moleküle mit einer molekularen Masse zwischen 30 und 300 Da. Die Sammlung der Reaktionen zur Verknüpfung der Bausteine besteht aus 83 literaturbeschriebenen chemischen Reaktionen. Ein Großteil stellt Syntheseschritte zur Generierung neuer Ringsysteme dar. DOGS baut neue Moleküle schrittweise auf: In jedem virtuellen Syntheseschritt wird ein neues Fragment an das wachsende Molekül angefügt, bis eines der Stoppkriterien (Überschreitung einer maximalen molekulare Masse oder Anzahl Syntheseschritte) erfüllt ist. Zur Bewertung der Qualität der Zischen- und Endprodukte wird eine ligandenbasierte Strategie verwendet. Die entstehenden Moleküle werden mit einem bekannten Referenzliganden verglichen, welcher die gewünschte biologische Aktivität aufweist. Das Verfahren zielt dabei auf die Maximierung der Ähnlichkeit der neu konstruierten Moleküle zur Referenz ab. Eine Graphkernmethode berechnet die Ähnlichkeit zum Referenzliganden anhand des Vergleichs ihrer zweidimensionalen molekularen Struktur. In einer theoretischen Auswertung des Programms werden ca. 1.800 generierte potentielle Trypsin-Inhibitoren hinsichtlich solcher Eigenschaften analysiert, welche für neu entworfene Verbindungen kritisch sind: DOGS ist in der Lage wirkstoffartige Moleküle zu entwerfen (79% verletzen weniger als zwei von Lipinskis 'rule of five' Kriterien zur Abschätzung der oralen Bioverfügbarkeit). Zusätzlich wurde die Wirkstoffartigkeit der DOGS-Moleküle durch einen trainierten Klassifizieralgorithmus bewertet. Hierbei erhielten 51% der Verbindungen einen Wert in den oberen 20% des Wertebereichs des Klassifizierers. Weiterhin wird die synthetische Zugänglichkeit für den Großteil der computergenerierten Moleküle als hoch eingeschätzt (77% erhalten einen Wert in den oberen 10% des Wertebereichs eines Deskriptors zur Abschätzung der Synthetisierbarkeit). Die berechneten logP(o/w) Werte der konstruierten Moleküle entsprechen in ihrer Verteilung denen der Referenzliganden. Die Untersuchung der vorgeschlagenen Trypsin-Inhibitoren auf Bioisostere zur Adressierung der S1-Bindetasche zeigt, dass hierfür plausible Vorschläge von DOGS generiert werden. Der Großteil ist potentiell in der Lage eine kritische ladungsvermittelte Interaktion mit dem Protein in der S1-Bindetasche einzugehen. Unter den Vorschlägen befinden sich unter anderem auch drei Seitenketten, für die Interaktionen mit der S1-Bindetasche von Trypsin experimentell bestätigt sind. Eine Analyse ausgewählter Beispiele aus verschiedenen Läufen zum Ligandenentwurf für unterschiedliche biologische Zielmoleküle zeigt, dass das Programm in der Lage ist, die generelle topologische Anordnung potentieller Interaktionspunkte der Referenzliganden in den neu erzeugten Molekülen beizubehalten. Gleichzeitig sind diese Moleküle strukturell verschieden im Vergleich zu den Referenzliganden. Die generierten Synthesewege sind kurz und erscheinen in den meisten Fällen plausibel. Für einige der Syntheseschritte wird bei der praktischen Umsetzung der ergänzende Einsatz von Schutzgruppen notwendig sein, um unerwünschte Nebenreaktionen zu vermeiden. Die Software wurde zusätzlich zu den theoretischen Analysen in prospektiven Studien zum Ligandenentwurf praktisch evaluiert. Hierzu wurde DOGS zur Generierung von Liganden des humanen Histaminrezeptors 4 (hH4R) sowie der humanen gamma-Sekretase eingesetzt. Für hH4R wurde einer der entworfenen potentiellen Liganden synthetisiert, wobei der vorgeschlagene Syntheseweg exakt nachvollzogen werden konnte. Der Ligand weist eine geringfügige Affinität zum Histaminrezeptor auf. Für die gamma-Sekretase wurden zwei der entworfenen Moleküle zur Synthese und Testung ausgewählt. In beiden Fällen konnte auch hier die von DOGS vorgeschlagene Synthesestrategie nachvollzogen werden. Anschließende in vitro Analysen wiesen beide Verbindungen als inverse Modulatoren der gamma-Sekretase aus. Das Konstruktionskonzept von DOGS ist in der Lage, bioaktive Substanzen vorzuschlagen. Diese sind synthetisch zugänglich und können nach der vorgeschlagenen Strategie synthetisiert werden. Somit kann das Programm als Ideengenerator für den Entwurf neuer bioaktiver Moleküle dienen

HIV-1 proteaz enziminin kesme konumlarının tespitinde yeni öznitelik vektörleri

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Canlıların vücudunda bulunan proteaz enzimleri, pek çok yararlı biyolojik işlevi yerine getirirler. Bununla beraber, virüsler, parazitler gibi pek çok bulaşıcı mikroorganizmalar, proteazları enfekte olabilmek için kullanırlar. Proteazların temel görevi yeni sentezlenmiş çoklu proteinleri uygun yerlerinden keserek yapısal hale gelmelerini sağlamaktır. Böylece, ait oldukları mikroorganizmanın olgunlaşması ve çoğalmasında rol alırlar. Bu nedenle proteazların özgünlüklerini çözmek ilaç ve aşı geliştimek için çok önemlidir. Bununla beraber, proteaz enzimlerinin özgünlükleri konusunda yetersiz bilgi bulunmaktadır. Bu nedenle laboratuvar ortamlarında, proteaz verileri elde etmek ve proteazların özgünlüklerini karakterize etmek için uygun biyobilişim öznitelik kodlama yöntemleri ve algoritmaları geliştirmek hayati derecede önemlidir. Bu tezde, Human Immunodeficiency Virüs Tip 1 (HIV-1) proteazının proteinleri kesme konumlarının tespiti üzerine çalışılmıştır.Proteinlerle çalışırken göz önününde bulundurulması gereken iki temel bilgi bulunmaktadır: kalıntıların birbirleri ile olan fizikokimyasal etkileşimleri ve protein dizilimi içindeki konumları. Bu iki temel bilgi, proteinin işlevini anlamada nirengi noktalarıdır ve HIV-1 proteazının çoklu proteinleri nereden keseceğinin tahmin edilmesinde kullanılabilir. Bu varsayımdan yola çıkarak, HIV-1 proteaz enzimi özgünlüğünün modellenmesinde Fizikokimyasal Tabanlı Kodlama Yöntemi (FTKY), Birimdik Taylor Venn Diyagramı (BirTVD ) ve Birimdik BOOL (BirBOOL) olarak isimledirilen üç öznitelik kodlama yöntemi geliştirilmiştir.HIV-1 proteazın kesme konumlarını tespit etmek için güncel iki HIV-1 proteaz veri setlerine ait peptit örüntüleri, öznitelik çıkarım yöntemleri ile kodlanmıştır. Bu kodlanan örneklerin öznitelikleri Temel Bileşenler Analizi (TBA) ve Doğrusal Ayırıcı Analiz (DAA) ile çıkarılmıştır. Ardından doğrusal Destek Vektör Makineleri (DVM) algoritması ile sınıflandırılmıştır. Elde edilen deneysel sonuçlara göre; BirTVD ve BirBOOL öznitelik çıkarım kodlama yöntemlerinde, başarım mevcut yöntemlere göre daha yüksek elde edilmiştir.Protease enzymes which are inside the living organisms, implement many useful biological functions. However, many infectious microorganisms such as viruses and parasites use proteases to be infected as virulence factors. The main task of proteases is to cleave the polyproteins synthesized newly at the appropriate places to make them structural components. In this way, virulent proteases take role in maturation and replication of microorganisms. Hence, unravelling the specificities of proteases is of great importance to develop drugs and vaccines. However, little is known about the cleavage specificities of these proteases. It is therefore, an important challenge to collect experimental protease data and to develop appropriate bioinformatics feature encoding schemes, algorithms to characterize the specificities for all proteases. In this thesis, human immunodeficiency virus type 1 (HIV-1) protease site prediction has been studied.When studying on proteins, there are two basic points considered: physicochemical relationships and the positions of the residues in protein sequnces. These two references are the keys to understand the functions of the proteins and can be used to predict where HIV-1 protease cleave the polyproteins. This hypothesis leads us to develop three feature encoding schemes namely FTKY, BirTVD and BirBOOL to model specificity of HIV-1 protease.For the prediction of HIV-1 protease cleavage sites, peptide samples of two up-to-date HIV-1 protease datasets have been encoded with feature encoding techniques and extracted their features with Principal Components Analysis and Linear Discriminant Anaysis. Subsequently, they have been classified by Linear Support Vector Machines algorithm. According to empirical results obtained, BirTVD and BirBOOL methods have achieved better performance compared to hitherto methods

Molecular dynamics simulations of HIV-1 protease complexed with saquinavir

Inhibition of the Human Immunode�ficiency virus type-1 (HIV-1) protease enzyme blocks HIV-1 replication. Protease inhibitor drugs have successfully been used as a therapy for HIV-infected individuals to reduce their viral loads and slow the progression to Acquired Immune Defi�ciency Syndrome (AIDS). However, mutations readily and rapidly accrue in the protease gene resulting in a reduced sensitivity of the protein to the inhibitor. In this thesis, molecular dynamics simulations (MDS) were run on HIV proteases complexed with the protease inhibitor saquinavir, and the strength of affinity calculated through MMPBSA and normal mode analysis. We show in this thesis that at least 13 residues can be computationally mutated in the proteases sequence without adversely aff�ecting its structure or dynamics, and can still replicate the change in binding affinity to saquinavir caused by said mutations. Using 6 protease genotypes with an ordered decrease in saquinavir sensitivity we use MDS to calculate drug binding affinity. Our results show that single 10ns simulations of the systems resulted in good concurrence for the wild-type (WT) system, but an overall strong anti-correlation to biochemically derived results. Extension of the WT and multi-drug resistant (MDR) systems to 50ns yielded no improvement in the correlation to experimental. However, expansion of these systems to a 10-repetition ensemble MDS considerably improved the MDR binding affinity compared to the biochemical result. Principle components analysis on the simulations revealed that a much greater confi�gurational sampling was achieved through ensemble MD than simulation extension. These data suggest a possible mechanism for saquinavir resistance in the MDR system, where a transitioning to a lower binding-affinity configuration than WT occurs. Furthermore, we show that ensembles of 1ns in length sample a significant proportion of the con�figurations adopted over 10ns, and generate sufficiently similar binding affinities

Translocation of protein cargo into Candida albicans using cell-penetrating peptides

Fungal infections caused by Candida albicans pose a serious threat to public health. The rising drug resistance towards azoles, the current first-line antifungal treatment, warrants novel approaches to designing and delivering new antifungal agents that target C. albicans cells. To increase the intracellular delivery of bioactive molecular cargo, we studied the use of cell-penetrating peptides (CPPs) as delivery vehicles. CPPs have been extensively used to deliver different cargoes into mammalian cells, but limited work has focused on delivery into fungal cells. To improve understanding of CPP-mediated delivery to C. albicans, we studied their ability to deliver green fluorescent protein (GFP) intracellularly. For our work, we chose the CPPs, MPG and Hst5, that have previously shown translocation into fungal cells without cargo and recombinantly produced these CPP fusions to GFP in Escherichia coli. We investigated the CPP-mediated translocation of GFP using flow cytometry. Fusion of GFP to MPG resulted in translocation into 40% of C. albicans cells, which was significantly higher than 13% cells that demonstrate translocation of GFP without a CPP. However, Hst5 did not translocate GFP into cells, with only 5% of cells exhibiting Hst5-GFP translocation. Our results demonstrate that MPG can deliver GFP, while Hst5 is not as promising. These results are consistent with molecular dynamics simulations that show MPG enters a model membrane preferentially with the N-terminal residues, whereas Hst5 fails to enter the membrane. Our results emphasize the potential of CPPs in delivering large cargo to C. albicans cells and the advantage of using both experiments and simulations to study the translocation of CPPs into C. albicans. To explore factors affecting translocation efficacy, we evaluated the aggregation of CPP-GFP fusion constructs. Using dynamic light scattering and interference scattering microscopy, our results identified aggregation of our fusions at high concentration as a possible limitation to translocation, motivating future studies of the causes of aggregation and its relationship to translocation efficiency. Our work has shown that CPPs can deliver large biomolecular cargo into fungal cells and has laid the foundation for further studies to design better CPPs and to explore mechanisms limiting translocation of CPPs into fungal pathogens