DOGS: Reaction-Driven de novo Design of Bioactive Compounds

We present a computational method for the reaction-based de novo design of drug-like molecules. The software DOGS (Design of Genuine Structures) features a ligand-based strategy for automated ‘in silico’ assembly of potentially novel bioactive compounds. The quality of the designed compounds is assessed by a graph kernel method measuring their similarity to known bioactive reference ligands in terms of structural and pharmacophoric features. We implemented a deterministic compound construction procedure that explicitly considers compound synthesizability, based on a compilation of 25'144 readily available synthetic building blocks and 58 established reaction principles. This enables the software to suggest a synthesis route for each designed compound. Two prospective case studies are presented together with details on the algorithm and its implementation. De novo designed ligand candidates for the human histamine H4 receptor and γ-secretase were synthesized as suggested by the software. The computational approach proved to be suitable for scaffold-hopping from known ligands to novel chemotypes, and for generating bioactive molecules with drug-like properties

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data

Design, Synthesis, Characterization and Biological Evaluation of Some Novel Isatin Derivatives as Antitubercular Agents.

AIM: The present study to design, synthesis, characterize and evaluate compounds for their potential antitubercular activity .The ability of compounds to inhibit cell wall synthesis by inhibiting Mycolic acid cyclopropane synthase [cmaA1 target (1L1E)] is to be evaluated. OBJECTIVES DESIGN : In-silico design of Mycolic acid cyclopropane synthase [cmaA1 target (1L1E)] inhibitors. SYNTHESIS: Based upon the Docking parameters and synthetic feasibility the following compounds will be synthesized. (3Z)-3-[(3-{[(E)-phenylmethylidene]amino}phenyl)imino]-1,3-dihydro-2H-indol-2- one. (3Z)-3-[(3-{[(E)-(4-methoxyphenyl)methylidene]amino}phenyl)imino]-1,3-dihydro- 2H-indol-2-one. (3Z)-3-[(3-{[(E)-(2-hydroxyphenyl)methylidene]amino}phenyl)imino]-1,3-dihydro- 2H-indol-2-one. CHARACTERIZATION: The above synthesised compounds will be identified and characterized by using Melting point, TLC method, Infrared Spectroscopy, Nuclear Magnetic Spectroscopy, Mass spectroscopy. BIOLOGICAL EVALUATION: The synthesized compounds will be screened for their anti-tubercular activity by in-vitro methods. TOXICOLOGICAL PREDICTION: Toxicological prediction will be carried out for synthesized compounds by in-silico property explorer like OSIRIS. DRUG DESIGN AND DOCKING All the designed molecules were docked to the specific target i.e., cmaA1 target (1L1E) mycolic acid cyclopropane synthase using drug design software (GLIDE Maestro 9.1). Those molecules with the top G-Score molecules which possessed synthetic feasibility were selected and others were ruled out. SYNTHESIS AND CHARACTERIZATION: The chosen compounds were synthesized by the conventional method and checked for purity initially by TLC and melting point methods. The structure of the synthesized compounds was assigned on the basis of spectral studies of IR, H1NMR and Mass spectroscopy method. All the synthesized compounds comply with the spectral requirements. BIOLOGICAL SCREENING Invitro Anti-tubercular activity: The synthesized compound [KB01, KB05 & KB06] showed the anti-tubercular activity. The pathogen tested was susceptible to all the synthesized compounds at 100μg/ml and 50μg/ml concentration. This proved that the docking method with GLIDE [Maestro 9.1] is ideal and fruitful for predicting biological activity. Toxicological prediction: Toxicity prediction was done by the in silico approaches using Osiris property explorer software. It shows for all the synthesized compounds are found to be no risk of undesired effects like tumorigenic, reproductive effective. But it shows some extent of undesired effects like mutagenicity and irritant quality

Електрохімічний синтез метил-2,5-диметокси-2,5-дигідрофуран-2-карбоксилату

В магістерській дисертації проведено літературний пошук існуючих способів створення і розробку ліків. Розглянуто, на прикладі піролу та піридазину, основні будівельні блоки для синтезу ліків. Описано їх властивості, функціоналізація та різні методи синтезу. Проведено дослідження по стабільності продукту реакції в різних умовах електролізу. Обрано параметри електролізу, для максимального спрощення процесу. Продукт електрохімічної реакції – метил-2,5-диметокси-2,5-дигідрофуран-2-карбоксилат, був відновлений до метил-2,5-диметокситетрагідрофуран-2-карбоксилату, для підтвердження гіпотетичних припущень щодо застосування продукту електролізу. Всі продукти реакцій досліджувались за допомогою ЯМР на потужностях ТОВ «НВП «УКРОРГСИНТЕЗ».In the master's dissertation the literary search of existing ways of creation and development of medicines is carried out. The main building blocks for drug synthesis are considered, on the example of pyrrole and pyridazine. Their properties, functionalization and various methods of synthesis are described. A study on the stability of the reaction product in different conditions of electrolysis. Appropriate electrolysis parameters have been selected to maximize process simplification. The product of the electrochemical reaction, methyl 2,5-dimethoxy-2,5-dihydrofuran-2-carboxylate, was reduced to methyl 2,5-dimethoxytetrahydrofuran-2-carboxylate to confirm hypothetical assumptions regarding the use of the electrolysis product. All reaction products were investigated by NMR at the facilities of LLC RPE "UKRORGSYNTEZ"

Optimiertes Design kombinatorischer Verbindungsbibliotheken durch Genetische Algorithmen und deren Bewertung anhand wissensbasierter Protein-Ligand Bindungsprofile

In dieser Arbeit sind die zwei neuen Computer-Methoden DrugScore Fingerprint (DrugScoreFP) und GARLig in ihrer Theorie und Funktionsweise vorgestellt und validiert worden. DrugScoreFP ist ein neuartiger Ansatz zur Bewertung von computergenerierten Bindemodi potentieller Liganden für eine bestimmte Zielstruktur. Das Programm basiert auf der etablierten Bewertungsfunktion DrugScoreCSD und unterscheidet sich darin, dass anhand bereits bekannter Kristallstrukturen für den zu untersuchenden Rezeptor ein Referenzvektor generiert wird, der zu jedem Bindetaschenatom Potentialwerte für alle möglichen Interaktionen enthält. Für jeden neuen, computergenerierten Bindungsmodus eines Liganden lässt sich ein entsprechender Vektor generieren. Dessen Distanz zum Referenzvektor ist ein Maß dafür, wie ähnlich generierte Bindungsmodi zu bereits bekannten sind. Eine experimentelle Validierung der durch DrugScoreFP als ähnlich vorhergesagten Liganden ergab für die in unserem Arbeitskreis untersuchten Proteinstrukturen Trypsin, Thermolysin und tRNA-Guanin Transglykosylase (TGT) sechs Inhibitoren fragmentärer Größe und eine Thermolysin Kristallstruktur in Komplex mit einem der gefundenen Fragmente. Das in dieser Arbeit entwickelte Programm GARLig ist eine auf einem Genetischen Algorithmus basierende Methode, um chemische Seitenkettenmodifikationen niedermolekularer Verbindungen hinsichtlich eines untersuchten Rezeptors effizient durchzuführen. Zielsetzung ist hier die Zusammenstellung einer Verbindungsbibliothek, welche eine benutzerdefiniert große Untermenge aller möglichen chemischen Modifikationen Ligand-ähnlicher Grundgerüste darstellt. Als zentrales Qualitätskriterium einzelner Vertreter der Verbindungsbibliothek dienen durch Docking erzeugte Ligand-Geometrien und deren Bewertungen durch Protein-Ligand-Bewertungsfunktionen. In mehreren Validierungsszenarien an den Proteinen Trypsin, Thrombin, Faktor Xa, Plasmin und Cathepsin D konnte gezeigt werden, dass eine effiziente Zusammenstellung Rezeptor-spezifischer Substrat- oder Ligand-Bibliotheken lediglich eine Durchsuchung von weniger als 8% der vorgegebenen Suchräume erfordert und GARLig dennoch im Stande ist, bekannte Inhibitoren in der Zielbibliothek anzureichern

Crystal structure solution of hydrogen bonded systems : a validation and an investigation using historical methodologies followed by a review of crystal structure prediction methodologies to date

There are many chemicals that crystallize into more than one form. This phenomenon is called polymorphism. In each form or polymorph, inter and intra-molecular binding differ to varying degrees. As a result of this structural variation, the physical properties of the solid phases may also differ. Even the smallest of changes at the molecular level can result in a significant change in the final adopted crystal structure. Polymorphism in crystal structures allows studies of structure-property relationships since it is only the packing motifs that differ between polymorphs. In this thesis, a ‘computationally assisted’ approach to crystal structure solution was taken. X-ray powder diffraction was used to generate unit cell dimensions and space groups while historical in-house molecular modelling methods were used to generate possible trial structures that would be the starting point for refinement. Finally, a review of the latest methodologies for crystal structure prediction and consideration of polymorphism within the pharmaceutical industry completes this work

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

Topology Considerations in Hybrid Electric Vehicle Powertrain Architecture Design.

Optimal system architecture (topology or configuration) design has been a challenging design problem because of its combinatorial nature. Parametric optimization studies make design decisions assuming a given architecture but there has been no general methodology that addresses design decisions on the system architecture itself. Hybrid Electric Vehicle (HEV) powertrains allow various architecture alternatives created by connecting the engine, motor/generators and the output shaft in different ways through planetary gear systems. Addition of clutches to HEV powertrains allows changing the connection arrangement (configuration) among the powertrain components during the vehicle operation. Architectures with this capability are referred to as multi-mode architectures while architectures with fixed configurations are referred to as single-mode architectures. HEV architecture optimization requires designing the powertrain’s configuration and its sizing simultaneously. Additionally, evaluation of an HEV architecture design depends on a power management (control) strategy that distributes the power demand to the engine and motor/generators. Including this control problem increases the complexity of the HEV architecture design problem. This dissertation focuses on a general methodology to make design decisions on HEV powertrain architecture and component sizes. The representation of the architecture design problem is critical to solving this problem. A new general representation capable of describing all architecture alternatives is introduced. Using the representation, all feasible configurations are generated where these feasible configurations are used to create single- and multi-mode HEV architectures. Single-mode and multi-mode architecture design problems considering fuel economy, vehicle performance and architecture complexity are formulated separately and solution strategies are developed. The high complexity of the resulting optimization problem does not allow us to claim true optimality rigorously; therefore, the terms ``promising" or ``near-optimal" are more accurate in characterizing our results. The results show that different architectures must be designed for different applications. The case studies designing architectures for some available vehicles from the market find the architectures already implemented in these vehicles under some design constraints. Alternative architectures that improve these designs under different design constraints are also demonstrated. Architectures for a new application that is not available in the market are also designed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111412/1/bayrak_1.pd

COMBINATORIAL LIBRARY DESIGN OF MUTATION-RESISTANT HIV PROTEASE INHIBITORS.

The emergence of HIV strains that are resistant to current HIV protease inhibitors in the past few years has become a major concern in AIDS treatment. The goal of this project is to design a combinatorial library of potential lead compounds that can bind to both the wild-type and mutant proteases and that can resist further mutations. A recent crystallographic study of complexes of HIV protease with its substrates has provided structural insights into the differential recognition of the substrates and inhibitors. It has been proposed that clinical resistance is a consequence of inhibitors failure to stay within the consensus substrate volume. In this work, we devised a quantitative indicator of the degree to which a candidate ligand falls outside the consensus substrate volume, and determined its correlation with the inhibitor's sensitivity to clinically relevant resistant mutations. The validation of this hypothesis has encouraged us to use this strategy in our design of a combinatorial library of inhibitors. The compounds in a typical combinatorial library are built around a common structural scaffold possessing multiple connection points where substituents can be added by reliable synthetic steps. As the number of compounds encompassed by such a combinatorial scheme frequently exceeds what can actually be synthesized and tested, virtual screening methods are sought to shortlist the compounds. Even though these methods require only seconds to minutes of CPU time per compound, exhaustive screening of an entire virtual combinatorial library is computationally demanding. We therefore implemented a simple algorithm of combining substituents that have been optimized independently for the substituent sites. This method was compared with Genetic Algorithm, a global optimization method and was found equally efficient. This simple method was hence chosen for the design process. A combinatorial library based on these ideas and methods has been synthesized and tested. It includes four compounds with nanomolar inhibition constants. Two of them were shown to have retained affinity against a panel of treatment-resistant mutations