Противовирусные органические соединения : учебное пособие

В учебном пособии описаны основные органические классы соединений, обладающих противовирусным действием. Материал пособия является дополнением к читаемым курсам лекций и предназначен для самостоятельного освоения студентами. Для студентов, изучающих дисциплины «Химия биологически активных веществ», «Химия гетероциклических соединений», «Готовые лекарственные средства», «Химия химфармпрепаратов»

Computational Estimation of Biliary Excretion of Compounds and the Role of Transporters

Biliary excretion is one of the main elimination pathways for drugs and/or their metabolites. Therefore, an insight into the structural profile of cholephilic compounds through accurate modelling of the biliary excretion is important for the estimation of clinical pharmacokinetics in early stages of drug discovery. The aim of this project was to develop Quantitative Structure-Activity Relationships(QSAR) as computational tools for the estimation of biliary excretion. In addition, the structural requirements for biliary excretion were investigated in relation to the structural requirements for binding to uptake and efflux transporter proteins that are involved in hepatobiliary elimination. The study used three datasets; 1. percentage of dose excreted intact into bile in rat for 217 compounds, 2. P-gp inhibition constants for 219 compound, 3. percentage inhibition of OATP transporters, OATP1B1, OATP1B3 and OATP2B1. Statistical techniques were stepwise regression analysis, Classification and Regression Trees (C&RT), Chi-square Automatic Interaction Detector (CHAID), Boosted trees (BT), Random Forest (RF) and Multivariate Adaptive Regression Splines (MARS) models. The study resulted in QSARs for the prediction of biliary excretion, P-gp binding constants and percentage inhibition of OATPs, along with QSARs incorporating predicted P-gp and OATP inhibition values for the prediction of biliary excretion. Simple regression tree models were of similar accuracy to the boosted trees model in the estimation of the percentage of bile excretion of compounds. Molecular descriptors selected by these models indicated a higher biliary excretion for relatively hydrophilic compounds especially if they have acid/base dissociation, and a large molecular size above 348 Da. The major role of OATPs in biliary excretion was indicated using interactive decision tree models with OATP1B1 binding being the most successful predictor of biliary excretion amongst the three OATP subfamilies. In contrast, predicted P-gp binding parameters were not successful in the prediction of biliary excretion. This may be due to problems in extrapolating the in vitro P-gp binding data to the in vivo situation, or due to the difference in the chemical spaces of the P-gp and biliary excretion datasets which may lead to the compounds in biliary excretion dataset to fall outside the applicability domain of the P-gp models

The application of the Multi-Component Reaction (MCR) strategy in the design and synthesis of new antiplasmodial and antimycobacterial agents

Includes bibliographical references.Malaria and tuberculosis are ancient diseases that continue to have a profound impact on mankind, 5 millennia after their first documentation. Malaria is endemic in more than 100 countries and about 50% of the world's population is at risk of infection. Sub-Saharan Africa accounts for nearly 91% of malaria-related deaths annually. Tuberculosis on the other hand infects about one third of the word's population and is the second major cause of death in adults worldwide, with about 1.8 million deaths reported annually. The major challenge to the control of these diseases has been the rapid emergence of multi-drug resistant strains to the currently administered drugs, as such, these exert an enormous pressure on health care systems, especially in resource-limited areas. Alleviation of this pressure requires the development of highly efficacious new chemical entities (NCEs) to curb or manage these pathogens. The main aim of this study was to design NCEs based on quinoline-, PA-824-, and tetrazole-scaffolds, which exhibit in vitro antiplasmodial and antimycobacterial activity

Data mining methods for the prediction of intestinal absorption using QSAR

Oral administration is the most common route for administration of drugs. With the growing cost of drug discovery, the development of Quantitative Structure-Activity Relationships (QSAR) as computational methods to predict oral absorption is highly desirable for cost effective reasons. The aim of this research was to develop QSAR models that are highly accurate and interpretable for the prediction of oral absorption. In this investigation the problems addressed were datasets with unbalanced class distributions, feature selection and the effects of solubility and permeability towards oral absorption prediction. Firstly, oral absorption models were obtained by overcoming the problem of unbalanced class distributions in datasets using two techniques, under-sampling of compounds belonging to the majority class and the use of different misclassification costs for different types of misclassifications. Using these methods, models with higher accuracy were produced using regression and linear/non-linear classification techniques. Secondly, the use of several pre-processing feature selection methods in tandem with decision tree classification analysis – including misclassification costs – were found to produce models with better interpretability and higher predictive accuracy. These methods were successful to select the most important molecular descriptors and to overcome the problem of unbalanced classes. Thirdly, the roles of solubility and permeability in oral absorption were also investigated. This involved expansion of oral absorption datasets and collection of in vitro and aqueous solubility data. This work found that the inclusion of predicted and experimental solubility in permeability models can improve model accuracy. However, the impact of solubility on oral absorption prediction was not as influential as expected. Finally, predictive models of permeability and solubility were built to predict a provisional Biopharmaceutic Classification System (BCS) class using two multi-label classification techniques, binary relevance and classifier chain. The classifier chain method was shown to have higher predictive accuracy by using predicted solubility as a molecular descriptor for permeability models, and hence better final provisional BCS prediction. Overall, this research has resulted in predictive and interpretable models that could be useful in a drug discovery context

Estudios computacionales del receptor Toll-like 4

Tesis de la Universidad Complutense de Madrid, Facultad de Farmacia, Departamento de Química Orgánica y Farmacéutica, leída el 11/10/2017This Thesis is focused on the molecular modeling and computational study of the molecular recognition processes involving Pattern Recognition Receptors (PRRs), in particular, Toll-like receptors (TLRs). TLRs are the main actors in innate immunity and are specialized in the recognition of pathogen associated molecular patterns (PAMPs). In particular, TLR4 is located in the plasma membrane where, together with the MD-2 protein, it binds to lipopolysaccharides, membrane constituents of Gramnegative bacteria, forming a heterodimeric complex. TLR4 agonists can be used as adjuvants in vaccine development and in cancer immunotherapy. TLR4 antagonists have also been studied for their promising application in septic shock, chronic inflammation and autoimmunity. However, the mechanism at atomic level for such activation/inactivation process remains unknown. Our research has been focused on the study of the mechanism of the TLR4/MD-2 system by means of computational approaches. In order to carry out our research objectives, we use a combination of several computational tools: geometry optimization, charges calculations, docking, virtual screening, and molecular dynamics simulations of protein complexes and membranes. The main objective of this Thesis is to elucidate the ligand-protein interactions of TLR4 at atomic detail through computational techniques. Computational methodologies will be applied to the study of the molecular mechanisms involved in the TLRs functionality, and in the recognition of PAMPs. Ligand-protein docking and virtual screening will be used as a source of new compounds able to modulate the TLRs behavior with possible therapeutic applications, and also as biological probes...En esta Tesis Doctoral se han empleado técnicas de modelado molecular y se ha llevado a cabo el estudio computacional de los procesos de reconocimiento molecular que implican Receptores de Reconocimiento de Patrones (PRRs), en particular, los receptores Toll-like (TLRs). Los TLRs son los principales actores en la inmunidad innata y se especializan en el reconocimiento de patrones moleculares asociados a patógenos (PAMPs). En particular, el receptor TLR4 se localiza en la membrana plasmática donde, junto con la proteína MD-2, se une a lipopolisacáridos, constituyentes de membrana de bacterias Gram-negativas, que forman un complejo heterodimérico. Los agonistas de TLR4 pueden ser útiles como coadyuvantes en el desarrollo de la vacuna y en la inmunoterapia contra el cáncer. Los antagonistas de TLR4 también han sido estudiados por su prometedora aplicación en choque séptico, inflamación crónica y autoinmunidad. Sin embargo, el mecanismo a nivel atómico para tal proceso de activación/inactivación sigue siendo desconocido. Nuestra investigación se ha centrado en el estudio del mecanismo del sistema TLR4/MD-2 mediante métodos computacionales. Con el fin de llevar a cabo nuestros objetivos de investigación, hemos utilizado una combinación de varias herramientas computacionales: optimización de la geometría, cálculos de carga, docking, cribado virtual y simulaciones de dinámica molecular de complejos y membranas de proteínas. El objetivo principal de esta Tesis es elucidar las interacciones ligando-proteína del receptor TLR4 a nivel atómico a través de técnicas computacionales. Metodologías computacionales se aplicarán para el estudio de los mecanismos moleculares involucrados en la funcionalidad de los receptores Toll-like, y en el reconocimiento de los PAMPs. Técnicas de acoplamiento ligando-proteína y cribado virtual serán utilizadas, dando lugar a una fuente de nuevos compuestos capaces de modular el comportamiento de los TLRs con posibles aplicaciones terapéuticas, y también como sondas biológicas...Depto. de Química en Ciencias FarmacéuticasFac. de FarmaciaTRUEunpu

Non-covalent interactions in organotin(IV) derivatives of 5,7-ditertbutyl- and 5,7-diphenyl-1,2,4-triazolo[1,5-a]pyrimidine as recognition motifs in crystalline self- assembly and their in vitro antistaphylococcal activity

Non-covalent interactions are known to play a key role in biological compounds due to their stabilization of the tertiary and quaternary structure of proteins [1]. Ligands similar to purine rings, such as triazolo pyrimidine ones, are very versatile in their interactions with metals and can act as model systems for natural bio-inorganic compounds [2]. A considerable series (twelve novel compounds are reported) of 5,7-ditertbutyl-1,2,4-triazolo[1,5-a]pyrimidine (dbtp) and 5,7-diphenyl- 1,2,4-triazolo[1,5-a]pyrimidine (dptp) were synthesized and investigated by FT-IR and 119Sn M\uf6ssbauer in the solid state and by 1H and 13C NMR spectroscopy, in solution [3]. The X-ray crystal and molecular structures of Et2SnCl2(dbtp)2 and Ph2SnCl2(EtOH)2(dptp)2 were described, in this latter pyrimidine molecules are not directly bound to the metal center but strictly H-bonded, through N(3), to the -OH group of the ethanol moieties. The network of hydrogen bonding and aromatic interactions involving pyrimidine and phenyl rings in both complexes drives their self-assembly. Noncovalent interactions involving aromatic rings are key processes in both chemical and biological recognition, contributing to overall complex stability and forming recognition motifs. It is noteworthy that in Ph2SnCl2(EtOH)2(dptp)2 \u3c0\u2013\u3c0 stacking interactions between pairs of antiparallel triazolopyrimidine rings mimick basepair interactions physiologically occurring in DNA (Fig.1). M\uf6ssbauer spectra suggest for Et2SnCl2(dbtp)2 a distorted octahedral structure, with C-Sn-C bond angles lower than 180\ub0. The estimated angle for Et2SnCl2(dbtp)2 is virtually identical to that determined by X-ray diffraction. Ph2SnCl2(EtOH)2(dptp)2 is characterized by an essentially linear C-Sn-C fragment according to the X-ray all-trans structure. The compounds were screened for their in vitro antibacterial activity on a group of reference staphylococcal strains susceptible or resistant to methicillin and against two reference Gramnegative pathogens [4] . We tested the biological activity of all the specimen against a group of staphylococcal reference strains (S. aureus ATCC 25923, S. aureus ATCC 29213, methicillin resistant S. aureus 43866 and S. epidermidis RP62A) along with Gram-negative pathogens (P. aeruginosa ATCC9027 and E. coli ATCC25922). Ph2SnCl2(EtOH)2(dptp)2 showed good antibacterial activity with a MIC value of 5 \u3bcg mL-1 against S. aureus ATCC29213 and also resulted active against methicillin resistant S. epidermidis RP62A

Development of synthetic methodologies for N- to C-terminal cyclization of peptidomimetic small molecules and in silico and in vitro studies of the role of cyclization on antibacterial and antiviral activities

Among the different mechanisms of resistance in Gram-negative bacteria, the permeability barrier of the outer membrane and efflux pumps represent a significant challenge to address as they synergize to reduce accumulation of most antibiotics. As no predictive model of the structural and physicochemical properties governing efflux susceptibility and outer membrane permeability has been developed, there is a pressing need for strategies to enhance the accumulation of small molecules in Gram-negative bacteria. The Small-molecule Penetration & Efflux in Antibiotic-Resistant Gram-Negatives (SPEAR-GN) project takes a multidisciplinary approach to develop a class- and activity-independent model for antibiotic permeability by building small-molecule libraries. For my contribution to this project, I conducted the synthesis of a library centered around a piperazinone scaffold which is derived from the natural product acyldepsipeptide (ADEP), a potent activator of bacterial caseinolytic protease P (ClpP). The N- to C-terminal cyclization of the ADEP pharmacophore, N-heptenoyl 3,5-difluorophenylalanine, was hypothesized to constraint the conformation of the scaffold and improve its metabolic stability. From an optimized three-step synthetic route to produce the piperazinone core, I generated a library of 48 chemically diverse piperazinone analogs, for which I investigated and optimized different methodologies such as N-alkylation of secondary amides with inactivated alkyl halides using phase-transfer catalysis, photoinduced copper catalysis and synthetic handles. In parallel to the piperazinone library, Quentin Gibault and Katelyn Stevens generated a set of uncyclized or seco analogs to examine the role of the cyclization on antibacterial activity and accumulation in Gram-negatives. The Zgurskaya lab evaluated the antibacterial activity of the library by the measuring the minimum inhibitory concentration (MIC) in isogenic strain sets of wild-type, hyperporinated, efflux-deficient, and doubly compromised (i.e., hyperporinated and efflux-deficient) E. coli, P. aeruginosa, and A. baumannii. The promising biological results set the stage for future LC/MS accumulation studies and will lead to the identification of physicochemical properties or motifs governing efflux susceptibility and outer membrane permeability in the seco and piperazinone libraries. The persistent emergence of antimicrobial-resistant bacteria, paired with a dwindling pipeline of therapeutic treatments amplifies the urgency for novel antibacterials. However, antibiotics that exploit new mechanisms of action provide modern challenges to bacteria; and thus, require the development of a completely new resistance regime, potentially lengthening the duration of action. One promising target departing from traditional antibacterial discovery paradigm is caseinolytic protease P (ClpP). Essential in bacterial homeostasis and virulence, this protease can be chemo-activated by natural products such as acyldepsipeptide (ADEP), resulting in uncontrolled protein degradation and subsequent bacterial cell death. Although ADEP exhibit impressive potency against Gram-positive pathogens, its overall low stability and the synthetic challenge that represents the peptidolactone prevent further development as an antibacterial. To structurally simplify ADEP and maintain its potency associated with the peptidolactone, I investigated the introduction of structural constraint to the ADEP bioactive fragment, N-heptenoyl-3,5-difluorophenylalanine, via N- to C-terminal cyclization. To understand the conformational behavior of the cyclized ClpP activators ranging from six- to eight-membered ring, I conducted computational studies on the conformational space of each analog. The synthetic work I performed provided methodologies to access the six-membered rings (piperazinones and pyrazinones), the seven-membered ring (1,4-diazepan-2-one), and the eight-membered ring (1,4-diazecan-2-one), and the generation of the corresponding small-molecule ADEP analogs. To evaluate the capacity of this series to activate ClpP, I employed a fluorescence-based peptide degradation assay. Although all the cyclized analogs were inactive against Bacillus subtilis ClpP, the biological results demonstrated that, in conjunction with docking studies, a hydrogen bonding with ADEP and Tyr62 is essential for the chemo-activation of ClpP and conformational alteration of the scaffold cannot overcome the loss of this interaction. The COVID-19 pandemic culminated in more than 470 million cases and six million deaths worldwide since the outbreak of SARS-CoV-2 in December 2020. These numbers along with our individual experience during the last two years make the need for antiviral treatments for coronaviruses indisputable. As the pandemic was taking hold, Jessi Gardner, Katelyn Stevens and I investigated four structurally diverse scaffolds for potential non-covalent SARS-CoV-2 Main protease (Mpro) inhibitors. Among these four scaffolds I designed by leveraging existing literature on Mpro inhibitors and hits from a large-scale crystallographic fragment screen by Diamond Light Source, I conducted docking studies to validate a piperazine scaffold. Although the piperazine scaffold was not pursued because of its poor binding to Mpro, it informed the design of a substituted piperazinone scaffold. Docking studies indicated that this scaffold engaged in multiple protein-ligand interactions with Mpro resulting in good docking scores. Since the piperazinone ring is the result of a N- to C-terminal cyclization of a “peptidic” scaffold, I also conducted docking studies of an “uncyclized” peptidic series of analogs to compare the impact of the cyclization on the binding. Although the docking score of these analogs was weaker, I synthesized a preliminary library of piperazinone and peptidic potential Mpro inhibitors setting the stage for biochemical evaluation against SARS-CoV-2 Mpro