Molecular descriptor data explain market prices of a large commercial chemical compound library

The relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry

NATURAL ISOTHIOCYANATE ANTI-MALARIA: MOLECULAR DOCKING, PHYSICOCHEMICAL, ADME, TOXICITY AND SYNTHETIC ACCESSIBILITY STUDY OF EUGENOL AND CINNAMALDEHYDE

Objective: This study aims to evaluate novel compounds of isothiocyanate (ITC) based on eugenol and cinnamaldehyde derivatives as the drug candidate of Plasmodium falciparum anti-malaria using in silico method, physicochemical, pharmacokinetics, toxicity, and synthetic accessibility prediction. This present study also describes molecular docking and pharmacoinformatics of natural ITC in Moringa oleifera leaves. Methods: A series of novel ITC compounds (3, 5, and 6) were designed and analyzed with a series of natural ITC compounds (7, 8, 9, 10) for P. falciparum anti-malaria. This research is descriptive qualitative and uses the reverse molecular docking method, proving the biological activity of compounds theoretically using software and database information. Results: Molecular docking study showed that compound 6 exhibits binding affinity (-5.3 Kcal/mol) on Van der Waals interaction with the residual active site (His159, Cys25) of cysteine protease. All designed ITC compounds are obeyed the Lipinski and Veber Rule, have a well-brain penetrant character and have a medium risk for mutagenic, tumorigenic, and reproductive prediction. They are also in the simple rate of synthetic accessibility (SA) estimation. In regards to natural ITCs, they all have better assay characteristics except the SA. Conclusion: Molecular docking, physicochemical, pharmacokinetic, and toxicity studies show that methyl eugenol isothiocyanate and cinnamaldehyde isothiocyanate are promising anti-malaria compounds. Substituents of hydroxy, acetate and tetrahydropyran groups in the building block ring are suggested for better in silico profiles enhancement

The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation.

In the European Union, medicines are authorised for some rare disease only if they are judged to be dissimilar to authorised orphan drugs for that disease. This paper describes the use of 2D fingerprints to show the extent of the relationship between computed levels of structural similarity for pairs of molecules and expert judgments of the similarities of those pairs. The resulting relationship can be used to provide input to the assessment of new active compounds for which orphan drug authorisation is being sought

Identification of Potential Insect Growth Inhibitor against Aedes aegypti: A Bioinformatics Approach

Aedes aegypti is the main vector that transmits viral diseases such as dengue, hemorrhagic dengue, urban yellow fever, zika, and chikungunya. Worldwide, many cases of dengue have been reported in recent years, showing significant growth. The best way to manage diseases transmitted by Aedes aegypti is to control the vector with insecticides, which have already been shown to be toxic to humans; moreover, insects have developed resistance. Thus, the development of new insecticides is considered an emergency. One way to achieve this goal is to apply computational methods based on ligands and target information. In this study, sixteen compounds with acceptable insecticidal activities, with 100% larvicidal activity at low concentrations (2.0 to 0.001 mg center dot L-1), were selected from the literature. These compounds were used to build up and validate pharmacophore models. Pharmacophore model 6 (AUC = 0.78; BEDROC = 0.6) was used to filter 4793 compounds from the subset of lead-like compounds from the ZINC database; 4142 compounds (dG < 0 kcal/mol) were then aligned to the active site of the juvenile hormone receptor Aedes aegypti (PDB: 5V13), 2240 compounds (LE < -0.40 kcal/mol) were prioritized for molecular docking from the construction of a chitin deacetylase model of Aedes aegypti by the homology modeling of the Bombyx mori species (PDB: 5ZNT), which aligned 1959 compounds (dG < 0 kcal/mol), and 20 compounds (LE < -0.4 kcal/mol) were predicted for pharmacokinetic and toxicological prediction in silico (Preadmet, SwissADMET, and eMolTox programs). Finally, the theoretical routes of compounds M01, M02, M03, M04, and M05 were proposed. Compounds M01-M05 were selected, showing significant differences in pharmacokinetic and toxicological parameters in relation to positive controls and interaction with catalytic residues among key protein sites reported in the literature. For this reason, the molecules investigated here are dual inhibitors of the enzymes chitin synthase and juvenile hormonal protein from insects and humans, characterizing them as potential insecticides against the Aedes aegypti mosquito.Laboratory of Cellular Immunology Applied to Health of the Oswaldo Cruz Foundation (FIOCRUZ)Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy of the University of Granada (Spain)Researcher Assistance Program-PAPESQ/UNIFA

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

Analizy QSPR wielkich bibliotek związków chemicznych na przykładzie bazy danych Abamachem

Structure-activity relationship is an essential concept in chemistry guiding, for example, drug design. However, we need economics to fully understand the fate of drugs on the market. Quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals have been modeled and analyzed for the first time. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry. The modeled molecular statistics shows that on average what we are paying for is the quantity of matter. The influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive

Metody eksploracji baz danych w poszukiwaniu nowych reguł projektowania leków

The pharmaceutical industry has been one of the most lucrative business areas of all time. However, faced with numerous problems in recent years, it appears to be declining. Despite the use of the latest technology, there has been no significant improvement which would result in the implementation of new, better, and more innovative pharmaceuticals. The aim of this study was to optimize the database exploration and analysis methods in terms of determining trends in pharma R&D and to propose strategies to facilitate the process of drug development. This study shows the synergy between the numerous research methods in several scientific fields, such as chemistry, computer science, economics and pharmacy. Thus, the calculated chemical descriptors and economic parameters were used in statistical analysis. Moreover, comparative analysis of trends and developments, both in science and the pharmaceutical industry, has been presented. Thus, an effort was made to explain the role and impact of the market for the trends in pharma which could encourage changes in the drug structure. A population of FDA drugs were collected, characterized by drug-like and drug-age properties and additional implementation of the fragmentation algorithms helped to understand the topology of the investigated drug population. In summary, the analysis revealed many interesting trends in drug development in recent years. The study shed new light on the known methods for the design of active compounds

Structure generation and de novo design using reaction networks

This project is concerned with de novo molecular design whereby novel molecules are built in silico and evaluated against properties relevant to biological activity, such as physicochemical properties and structural similarity to active compounds. The aim is to encourage cost-effective compound design by reducing the number of molecules requiring synthesis and analysis. One of the main issues in de novo design is ensuring that the molecules generated are synthesisable. In this project, a method is developed that enables virtual synthesis using rules derived from reaction sequences. Individual reactions taken from reaction databases were connected to form reaction networks. Reaction sequences were then extracted by tracing paths through the network and used to create ‘reaction sequence vectors’ (RSVs) which encode the differences between the start and end points of th esequences. RSVs can be applied to molecules to generate virtual products which are based on literature precedents. The RSVs were applied to structure-activity relationship (SAR) exploration using examples taken from the literature. They were shown to be effective in expanding the chemical space that is accessible from the given starting materials. Furthermore, each virtual product is associated with a potential synthetic route. They were then applied in de novo design scenarios with the aim of generating molecules that are predicted to be active using SAR models. Using a collection of RSVs with a set of small molecules as starting materials for de novo design proved that the method was capable of producing many useful, synthesisable compounds worthy of future study. The RSV method was then compared with a previously published method that is based on individual reactions (reaction vectors or RVs). The RSV approach was shown to be considerably faster than de novo design using RVs, however, the diversity of products was more limited

Polifarmakologiczna analiza leków aktywnych względem wirusa HIV

Moje zainteresowania dotyczyły głównie potencjalnych celów przeciw HIV, których kierunkiem działania jest integraza HIV. Najczęściej jednak dostępne dane opisują polifarmakologię tych potencjalnych leków, czyli układ, w którym interesuje nas wiele celów (enzymów, receptorów) działania leku. Także praktycznie przeprowadzone testy aktywności zaprojektowanej biblioteki potencjalnych leków wykonane zostały w układzie, w którym potencjalnym celem działania niekoniecznie jest wyłącznie integraza HIV. Tak więc centralnym problemem mojej pracy stała się polifarmakologia leków przeciw HIV. Zakres prowadzonych przeze mnie badań obejmuje projektowanie i poszukiwanie związków biologicznie aktywnych z wykorzystaniem metod obliczeniowych i technologii informatycznych ze szczególnym uwzględnieniem eksploracji baz danych molekularno-strukturalnych