Exploring protein flexibility during docking to investigate ligand-target recognition

Ligand-protein binding models have experienced an evolution during time: from the lock-key model to induced-fit and conformational selection, the role of protein flexibility has become more and more relevant. Understanding binding mechanism is of great importance in drug-discovery, because it could help to rationalize the activity of known binders and to optimize them. The application of computational techniques to drug-discovery has been reported since the 1980s, with the advent computer-aided drug design. During the years several techniques have been developed to address the protein flexibility issue. The present work proposes a strategy to consider protein structure variability in molecular docking, through a ligand-based/structure-based integrated approach and through the development of a fully automatic cross-docking benchmark pipeline. Moreover, a full exploration of protein flexibility during the binding process is proposed through the Supervised Molecular Dynamics. The application of a tabu-like algorithm to classical molecular dynamics accelerates the binding process from the micro-millisecond to the nanosecond timescales. In the present work, an implementation of this algorithm has been performed to study peptide-protein recognition processes

In silico studies of the effect of phenolic compounds from grape seed extracts on the activity of phosphoinositide 3-kinase (PI3K) and the farnesoid x receptor (FXR)

In silico studies of the effect of phenolic compounds from grape seed extracts on the activity of phosphoinositide 3-kinase (PI3K) and farnesoid X receptor (FXR)Montserrat Vaqué Marquès En aquesta tesis es pretén aplicar metodologies computacionals (generació de farmacòfors i docking proteïna lligand) en l'àmbit de la nutigenòmica (ciència que pretén entendre, a nivell molecular, com els nutrients afecten la salut). S'aplicaran metodologies in silico per entendre a nivell molecular com productes naturals com els compostos fenòlics presents en la nostra dieta, poden modular la funció d'una diana comportant un efect en la salut. Aquest efecte es creu que podria ser degut a la seva interacció directa amb proteïnes de vies de senyalització molecular o bé a la modificació indirecta de l'expressió gènica. Donat que el coneixement de l'estructura del complex lligand-receptor és bàsic per entendre el mecanisme d'acció d'aquests lligands s'aplica la metodologia docking per predir l'estructura tridimensional del complex. En aquest sentit, un dels programes de docking és AutoGrid/AutoDock (un dels més citats). No obstant, l'automatització d'AutoGrid/AutoDock no és trivial tan per (a) la cerca virtual en una llibreria de lligands contra un grup de possibles receptors, (b) l'ús de flexibilitat, i (c) realitzar un docking a cegues utilitzant tota la superfície del receptor. Per aquest motiu, es dissenya una interfície gràfica de fàcil ús per utilitzar AutoGrid/AutoDock. Blind Docking Tester (BDT) és una aplicació gràfica que s'executa sobre quatre programes escrits en Fortran i que controla les condicions de les execucions d'AutoGrid i AutoDock. BDT pot ser utilitzat per equips d'investigadors en el camp de la química i de ciències de la vida interessats en dur a terme aquest tipus d'experiments però que no tenen suficient habilitats en programació. En la modulació del metabolisme de la glucosa, treballs in vivio i in vitro en el nostre grup de recerca s'han atribuït els efectes beneficiosos de l'extracte de pinyol de raïm en induir captació de glucosa (punt crític pel manteniment de l'homeostasis de la glucosa). No obstant alguns compostos fenòlics no tenen efecte en la captació de la glucosa, d'altres l'inhibeixen reversiblement. En alguns casos aquesta inhibició és el resultat de la competició dels compostos fenòlics amb ATP pel lloc d'unió de l'ATP de la subunitat catalítica de la fosfatidil inositol 3-kinasa (PI3K). Estudis recents amb inhibidors específics d'isoforma han identificat la p110α (la subunitat catalítica de PI3Kα) com la isoforma crucial per la captació de glucosa estimulada per insulina en algunes línies cel·lulars. Els programes computacionals han estat aplicats per tal de correlacionar l'activitat biològica dels compostos fenòlics amb informació estructural per obtenir una relació quantitativa estructura-activitat (3D-QSAR) i obtenir informació dels requeriments estructura-lligand per augmentar l'afinitat i/o selectivitat amb la diana (proteïna). Tot hi haver-se demostrat que l'adició d'extractes de compostos fenòlics en l'aliment pot tenir en general un benefici per la salut, s'ha de tenir en compte que l'estudi 3D-QSAR (construït a partir d'inhibidors sintètics de p110α) prediu que algunes d'aquestes molècules poden agreujar la resistència a la insulina en individus susceptibles dificultant la capatació de glucosa en múscul i teixit adipós i, per tant, produir un efecte secundari indesitjat. Resultats en el nostre grup de recerca han demostrat que compostos fenòlics presents en extractes de llavor de raïm incrementen l'activitat del receptor "farnesoid x receptor" (FXR) de manera dosi depenent quan el lligand natural de FXR (CDCA) és present. Les metodologies in silico, docking i 3D-QSAR, han estat aplicades juntament amb dades biològiques d'agonistes no esteroidals de FXR que s'uneixen a un lloc d'unió proper però diferent al lligand esteroidal 6CDCA. Els resultats han mostrat que els compostos fenòlics no són capaços d'activar FXR per ells mateixos però poden afegir noves interaccions que estabilitzarien la conformació activa de FXR en presència del lligand natural CDCA. Els compostos fenòlics podrien induir canvis conformacionals específics que augmentarien l'activitat de FXR. In silico studies of the effect of phenolic compounds from grape seed extracts on the activity of phosphoinositide 3-kinase (PI3K) and farnesoid X receptor (FXR)Montserrat Vaqué Marquès This thesis was written with the aim of applying computational methods that have already been developed for molecular design and simulation (i.e. pharmacophore generation and protein-ligand docking) to nutrigenomics. So, in silico tools that are routinely used by the pharmaceutical industry to develop drugs have been used to understand, at the molecular level, how natural products such as phenolic compounds (i.e. molecules that are commonly found in fruits and vegetables) can improve health and prevent diseases. Therefore, we first focused on predicting the structure of protein-ligand complexes. The docking algorithms can use the individual structures from receptor and ligand to predict (1) whether they can form a complex and (2) if so, the structure of the resulting complex. This prediction can be made, for instance, with AutoGrid/AutoDock, the most cited docking software in the literature. The automation of AutoGrid/AutoDock is not trivial for tasks such as (1) the virtual screening of a library of ligands against a set of possible receptors; (2) the use of receptor flexibility and (3) making a blind-docking experiment with the whole receptor surface. Therefore, in order to circumvent these limitations, we have designed BDT (i.e. blind-docking tester; http://www.quimica.urv.cat/~pujadas/BDT), an easy-to-use graphic interface for using AutoGrid/AutoDock. BDT is a Tcl/Tk graphic front-end application that runs on top of four Fortran programs and which controls the conditions of the AutoGrid and AutoDock runs. As far as the modulation of the glucose metabolism is concerned, several in vivo and in vitro results obtained by our group have shown that grape seed procyanidin extracts (GSPE) stimulate glucose uptake in 3T3-L1 adipocytes and thus help to maintain their glucose homeostasis. In contrast, it is also well known that although some phenolic compounds do not affect glucose uptake, others reversibly inhibit it in several cell lines. Moreover, for at least some of these phenolic compounds, this inhibition is the result of their competition with ATP for the ATP-binding site in p110α (i.e. the α isoform of the catalytic subunit of phosphoinositide 3-kinase or PI3Kα). Furthermore, recent studies with isoform-specific inhibitors have identified p110α as the crucial isoform for insulin-stimulated glucose-uptake in some cell lines. Therefore, although it has been proved that the addition of phenolic compound extracts to food can have an overall benefit on health, it should be taken into account that some of these molecules may exacerbate insulin resistance in susceptible individuals via impaired glucose uptake in muscle and adipose tissues and, therefore, produce an undesirable side effect. In this context, we have applied computational approaches (i.e. protein-ligand docking and 3D-QSAR) to predict the IC50 (i.e. the concentration that reduces the p110α activity to 50%). Our results agree with previous experimental results and predict that some compounds are potential inhibitors of this enzyme. Recent results in our research group have demonstrated that the phenolic compounds in GSPE increase the activity of the farnesoid X receptor (i.e. FXR) in a dose-dependent way when the natural ligand of FXR (i.e. CDCA) is also present. The phenolic compounds might induce specific conformational changes that increase FXR activity and then contribute to cardioprotection through mechanisms that are independent of their intrinsic antioxidant capacities but that involve direct interaction with FXR to modulate gene expression. Taking into account this hypothesis a 3D-QSAR analysis was made in an attempt to understand how phenolic compounds activate FXR. So, our results explain why phenolic compounds cannot activate FXR by themselves and how they can add new interactions to stabilize the active conformation of FXR when its natural ligand (i.e. CDCA) is present. Therefore, we proposed a mechanism of FXR activation by dietary phenolic compounds in which they may enhance bile acid-bound FXR activity

Chemistry and Pharmacology of Steroidal and Non-steroidal Modulators of Human Receptors

Metabolic and inflammatory diseases, affecting the liver and gastrointestinal system, are very widespread and often their pathogenesis is still unknown. Because these disorders represent a growing global public health problem and the present therapies expose the patients to several side effects, there is increased interest in the development of new pharmacological tools that could provide new opportunities in the treatment of complex metabolic disorders in which several target pathways are involved. The main liver manifestation of metabolic disorders are: NASH (Non-Alcoholic SteatoHepatitis), caused by the accumulation of fat in the liver, and PBC (Primary Biliary Cholangitis) an autoimmune disease that causes damage to the small bile ducts. In these pathologies, alterations of bile acid pool regulation have revealed a link between bile acid and metabolic homeostasis. The bile acid receptors farnesoid X receptor (FXR) and GPBAR1 both regulating lipid, glucose and energy metabolism, are today recognized promising targets for NASH and PBC. My research project was mainly focused on the design, synthesis and biological evaluation of small molecules as new modulators of human receptors involved in hepatic and metabolic diseases. Specifically, my research activity was addressed to the investigation of three major targets: the bile acids receptors (FXR and GPBAR1) and the cysteinyl leukotriene receptor 1 (CysLT1R). The obtained results can be summarized in the three main sections reported below according to the target of interest: Discovery of 6-ethylcholane derivatives as potent bile acid receptor agonists with improved pharmacokinetic properties The nuclear receptor FXR has been proposed as a potential target for the treatment of various pathologies, such as cholestasis, hepatic steatosis, atherosclerosis, dyslipidaemias, type 2 diabetes, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). Based on the previous results, extensive ligand/receptor binding studies, using the hGPBAR1 homology model and FXR crystal structure, allowed to elucidate the structural requirements for GPBAR1 and FXR recognition. These outcomes have paved the way for the rational design of a new generation of potent FXR ligands. GPBAR1 has been recently demonstrated the physiological mediator of itching, a common symptom observed in cholestasis and the severity of this side effect limits the pharmacological utility of dual FXR/GPBAR1 agonists in the treatment of different cholestatic disorders. In this context, the discovery of new chemical entities endowed with selective agonistic activity on FXR represents a promising approach in the identification of new pharmacological protocols for the treatment of metabolic disorders. My project concerned the synthesis, starting from the 6-ethylcholane scaffold, of new small molecules as modulators of the nuclear receptor FXR. These studies led us to identify compound 6 as a selective FXR agonist even if with reduced potency respect to 6-ECDCA (EC50=0.5 M) and compounds 1 and 3 which showed a dual activity (FXR/GPBAR1) but with improved pharmacodynamic and pharmacokinetic capabilities. Synthesis of novel isoxazole derivatives with FXR agonistic activity In vivo acetaminophen (APAP) is one of the most prescribed drugs worldwide, but the misuse causes acute liver failure. Since FXR ligands have shown effective in reducing liver injury in some experimental, I have decided to elaborate the chemical structure of GW4064, the first non-steroidal agonist for FXR, in order to obtain a new library of isoxazoles endowed with FXR agonistic activity. Compound 28 was the most effective FXR agonist of the library (EC50 = 0.30 ± 0.006 M). This compound was orally active and rescued mice from acute liver toxicity caused by APAP overdose. Development of dual CysLT1R and GPBAR1 modulators In order to develop multitarget drugs for the treatment of various metabolic diseases such as type 2 diabetes, fatty liver disease, dyslipidemia and inflammatory states affecting the enterohepatic system, we have decided to explore if there is a possible cross-talk between CysLT1R antagonists and the two bile acid receptors FXR and GPBAR1. New evidence suggests that cysteinyl leukotriene receptor type 1 (CysLT1R) is a critical signaling molecules implicated in the immune response, cell proliferation, inflammation regulation and intestinal barrier maintenance. Recently, a selected group of CysLT1R antagonists was tested on FXR and GPBAR1 by my research group. Results showed that REV5901 was effective as GPBAR1 agonist attenuating inflammation and immune dysfunction with an EC50 of 2.5 µM. None of the tested compounds exhibited activity on FXR. Therefore, in order to obtain a new library of compounds with improving CysLT1R antagonist/GPBAR1 agonist dual modulation, we have decided to synthetize a new library of compounds preserving the quinoline ring of REV5901 and modifying the substituents on the benzene ring. In vitro and in vivo assays showed that the most effective in modulating the two receptors, were compounds 44 (IC50 = 2.8M and EC50 = 3M, respectively) and 45 (IC50 = 1.2M and EC50 = 7.4M, respectively). These results could be a starting point for the development of new drugs for the treatment of metabolic and inflammatory diseases

Design, virtual screening and structural studies of new molecules with potential antitumor and antiinflammatory activity

2010 - 2011Computational methodologies in combination with experimental techniques as Nuclear Magnetic Resonance (NMR) have become a crucial component in drug discovery process, from hit identification to lead optimization. The study of ligand-macromolecule interactions, in fact, has a crucial role for the design and the development of new and more powerful drugs. In this project, different aspects of interaction and recognition processes between ligand and macromolecule, and streostructure assignment has been studied through this kind of combined approach with the aim to identify novel potential antitumor and/or antiinflammatory molecules. In particular, because the strong interconnection between the tumoral and inflammatory pathology has led to the identification of new target utilizable for the therapy, in this project will be described proteins (Histone deacetilase, HDAC; Nicotinamide Phosphoribosyltransferase, NMPRTase or Nampt; microsomal prostaglandin E2 synthase, mPGES-1; human synovial Phospholipases A2, hsPLA2; human Farnesoid-X-Receptor, FXR; human Pregnane-X-Receptor, PXR; Bile Acid Receptor GPBAR-1, TGR5) involved in essential cellular processes and acting at diverse levels and phases of the tumor and inflammation diseases. The results obtained can be summarized in three main areas of activity, whose relative weight was varied according to the development of the overall project: a) Support in the design of original scaffolds for the generation of libraries potentially utilizable in therapy. This work was exclusively conducted in silico by a molecular docking technique in order to direct the design of the new molecules basing on the analysis of ligand-target interactions and the synthetic possibilities. This kind of approach was successfully applied leading to the identification of new potential inhibitors for HDAC enzymes with ciclic (mono and bis amides, paragraph 2.2; conformationally locked calixarenes, paragraph 2.4), and linear (hydroxamic tertiary amines, paragraph 2.3) structures, and isoform selective (paragraph 2.6), and of ligands for microsomal prostaglandin E2 synthase (mPGES)-1 (two series of triazole-based compounds; paragraphs 4.2 and 4.3). For each of this described studied, the good qualitative accordance between the calculated and experimental data has made possible the identifications of new lead compounds, rationalizing in this way the key features to the target inhibition. b) Rationalization of the biological activity of compounds by the study of the drug-receptor interactions. Molecular docking was used for the detailed study of antiinflammatory and antitumoral compounds whose activities are known a priori. In fact, thanks to this procedure, in this thesis several rationalizations of binding modes were reported related to Ugi products derivatives of CHAP 1 (HDAC inhibitors, paragraph 2.5), new and potent inhibitor of NMPRTAse analogs of FK866 and CHS 828 (chapter 3), marine natural products as inhibitors of hsPLA2 (BLQ and CLDA, chapter 5), 4-methylen sterols extracted from Theonella swinhoei as ligands of FXR and PXR (chapter 6), and known compounds as taurolitholic acid and ciprofloxacin (chapter 7), agonists of TGR5. Through the in silico methodology the putative binding modes for the reported molecules was described offering a complete rationalization of docking results, evaluating the influence of the ligand target interactions (e.g. hydrophobic, hydrophilic, electrostatic contacts) on the biological activity. c) Determination of relative configuration of natural products. The complete comprehension of the three dimensional structure of synthetic or isolated molecules is fundamental to design and characterize new platform potentially utilizable in therapy. On this basis, the combined approach between the quantum mechanical (QM) calculation of NMR parameters and NMR spectroscopy was revealed a very useful mean to lead the total synthesis of natural product toward the right isomer avoiding waste of time and resources (paragraph 8.1). Moreover, the stereostructure assignment of marine natural products conicasterol F and its analog thonellasterol I was reported in the paragraph 8.2. by a novel combined approach between the quantitative interproton distance determinations by ROE and quantum mechanical calculations of chemical shifts. (edited by author)X n.s

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

Molecular similarity is a key concept in drug discovery. It is based on the assumption that structurally similar molecules frequently have similar properties. Assessment of similarity between small molecules has been highly effective in the discovery and development of various drugs. Especially, two-dimensional (2D) similarity approaches have been quite popular due to their simplicity, accuracy and efficiency. Recently, the focus has been shifted toward the development of methods involving the representation and comparison of three-dimensional (3D) conformation of small molecules. Among the 3D similarity methods, evaluation of shape similarity is now gaining attention for its application not only in virtual screening but also in molecular target prediction, drug repurposing and scaffold hopping. A wide range of methods have been developed to describe molecular shape and to determine the shape similarity between small molecules. The most widely used methods include atom distance-based methods, surface-based approaches such as spherical harmonics and 3D Zernike descriptors, atom-centered Gaussian overlay based representations. Several of these methods demonstrated excellent virtual screening performance not only retrospectively but also prospectively. In addition to methods assessing the similarity between small molecules, shape similarity approaches have been developed to compare shapes of protein structures and binding pockets. Additionally, shape comparisons between atomic models and 3D density maps allowed the fitting of atomic models into cryo-electron microscopy maps. This review aims to summarize the methodological advances in shape similarity assessment highlighting advantages, disadvantages and their application in drug discovery

New techniques of molecular modelling and structural chemistry for the development of bioactive compounds

2011 - 2012Computational chemistry represents today a valid and fast tool for the research of new compounds with potential biological activity. The analysis of ligand-macromolecule interactions and the evaluation of possible “binding modes” have a crucial role for the design and the development of new and more powerful drugs. In silico Virtual Screening campaigns of large libraries compounds (fragments or drug-like) on a specific target allow the selection of promising compounds, leading the identification of new scaffolds. The accurate analysis and the comparison of different bioactive compounds clarify the molecular basis of their interaction and the construction of pharmacoforic models. In parallel, another crucial aspect of pharmacological research is the identification of targets of interaction of bioactive molecules, and this is particularly true for compounds from natural sources. In fact, a wide range of drug tests on a large number of biological targets can represent a useful approach for the study of natural products, but often one of the main problems is their limited availability. Starting from these assumptions, a new computational method named Inverse Virtual Screening is described in details in this thesis. The different works based on this approach were performed considering panels of targets involved in the cancer events, determining the identification of the specific antitumor activity of the natural compounds investigated. Inverse Virtual Screening studies were performed by means of molecular docking experiments on different natural compounds, organized in small libraries or as single compounds. Firstly, a mathematical method for the exclusion of false positive and false negative results was proposed applying a normalization of the predicted binding energies (expressed in kcal/mol) obtained from the docking calculations. Then this approach was applied on a library of 10 compounds extracted from natural sources, obtaining a good validation through in vitro biological tests. Afterwards, another study was performed on the cyclopeptide namalide. Its biological inhibitory activity and selectivity on Carboxipeptidase A target was in accordance with Inverse Virtual Screening results. Virtual Screening topic was also inspected analyzing the efficacy of Molecular Dynamics-based methods for the accurate calculations of the binding affinities. This work was conducted on a library of 1588 compounds (44 ligands + 1544 decoys) extracted from the DUD database on trypsin target, using the Linear Interaction Energy (LIE) method by means of extensive Molecular Dynamics simulations. Four different LIE results obtained combining different scaling factors were compared with docking results, evaluating and comparing ROC and enrichment curves for each of the considered methods. Poor results were obtained with LIE, and further analysis with MM-GBSA and MM-PBSA approaches are under investigation. Moreover, in silico screenings were performed for the detailed study of natural compounds whose activities are known a priori. With this procedure, several binding modes were reported for a library of compounds on PXR target, whose activity or inactivity were rationalized comparing their binding poses with that of Solomonsterol A, used as a reference compound on this receptor. The presence/absence of biological activity of another library of compounds extracted from the marine sponge Plakinastrella Mamillaris on PPAR-γ and for the diterpene oridonin on HSP70 1A are described at a molecular level with molecular docking and Molecular Dynamics simulations. The putative binding modes for the reported molecules was described offering a complete rationalization of docking results, evaluating how ligand target specific interactions (e.g. hydrophobic, hydrophilic, electrostatic contacts) can influence their biological activity. [edited by author]La chimica computazionale rappresenata un valido e rapido strumento per l’identificazione di nuovi potenziali composti bioattivi. L’analisi delle interazioni ligando-target macromolecolare e la valutazione di un possibile “binding mode” sono cruciali per il design e lo sviluppo di nuovi potenziali farmaci. Il Virtual Screening di grandi librerie di composti (fragments o drug-like) condotto in silico su uno specifico recettore può permettere la selezione di composti dalla promettente attività, e parallelamente l’identificazione di nuovi scaffolds molecolari. L’analisi accurata dei modelli di interazione ligando-recettore e il confronto di tali modelli con quelli di composti dalla già nota attività permette la costruzione di un modello farmacoforico, punto di partenza per successivi studi di potenziamento dell’attività farmacologica. Parallelamente, un altro aspetto fondamentale della ricerca farmacologica è rappresentato dall’identificazione dei targets di interazione per composti dalla nota bioattività, e questo risulta particolarmente interessante per i composti di origine naturale. Infatti, per tale classe di molecole sarebbe molto utile effettuare tests biologici su un elevato numero di recettori, ma ciò risulta spesso proibitivo a causa della scarsa quantità di composto disponibile. Partendo da tali presupposti, nella presente tesi è descritto approfonditamente un nuovo metodo computazionale definito Inverse Virtual Screening. I vari lavori basati su questo nuovo tipo di approccio sono stati effettuati considerando pannelli composti da diversi targets coinvolti nello sviluppo del cancro, portando all’identificazione della specifica attività antitumorale dei vari composti naturali investigati. Gli studi basati sull’Inverse Virtual Screening sono stati effettuati attraverso calcoli di Molecular Docking utilizzando diversi composti naturali, raggruppati in piccole librerie o studiati singolarmente. In primo luogo, è stato proposto un metodo matematico con l’obiettivo di escludere i falsi positivi e i falsi negativi applicando una normalizzazione delle affinità di legame predette (espresse in kcal/mol). Successivamente, tale approccio è stato applicato su una libreria di 10 composti di origine naturale, validando l’applicabilità di tale metodo attraverso tests biologici in vitro. Successivamente, un ulteriore studio è stato incentrato su un ciclopeptide definito namalide, la cui attività biologica su Carbossipeptidasi A era in totale accordo con i dati provenienti dallo studio di Inverse Virtual Screening condotto. Il Virtual Screening è stato inoltre studiato anche analizzando l’efficacia dei metodi per il calcolo accurato delle affinità di legame basati su simulazioni di Dinamica Molecolare. Tale studio è stato condotto su una libreria di 1588 composti (44 ligandi + 1544 decoys, estratti dal DUD database) sul target tripsina, utilizzando il metodo LIE (Linear Interaction Energy) attraverso un elevato numero di simulazioni di Dinamica Molecolare. Sono stati ottenuti quattro differenti scale di affinità predetta (attraverso quattro combinazioni di differenti scaling factors) e sono stati confrontati con i risultati derivanti dai calcoli di Molecular Docking, valutando e confrontando curve ROC e di enrichment. Attraverso il metodo LIE sono stati ottenuti risultati non incoraggianti, e quindi ulteriori analisi attraverso metodi MM-GBSA e MM-PBSA sono in corso di studio. Inoltre, screenings in silico sono stati effettuati anche per lo studio dettagliato di altri composti naturali la cui attività era nota a priori. Attraverso questa procedura, sono stati proposti diversi modelli di binding di una libreria di composti sul target PXR, e per tali composti è stata razionalizzata l’attività/inattività confrontando il loro binding mode con quello del Solomonsterol A, utilizzato come composto di riferimento su tale target. La presenza/assenza di attività biologica è stata è stata descritto a livello molecolare per un’altra classe di composti estratti dalla spugna Plakinastrella Mamillaris sul target PPAR-γ e sul diterpene oridonina sul target HSP70 1A attraverso esperimenti combinati di Molecular Docking e Molecular Dynamics. Sono stati proposti e descritti approfonditamente modelli di binding di tali composti, valutando come specifiche interazioni ligando-target macromolecolare (di natura idrofobica, elettrostatica o caratterizzata dalla presenza di specifici legami ad idrogeno) possano influenzare l’attività biologica. [a cura dell'autore]XI n.s

A novel graph-based method for targeted ligand-protein fitting

A thesis submitted to the Faculty of Creative Arts, Technologies & Science, University of Bedfordshire, in partial & fulfilment of the requirements for the degree of Master of Philosophy.The determination of protein binding sites and ligand -protein fitting are key to understanding the functionality of proteins, from revealing which ligand classes can bind or the optimal ligand for a given protein, such as protein/ drug interactions. There is a need for novel generic computational approaches for representation of protein-ligand interactions and the subsequent prediction of hitherto unknown interactions in proteins where the ligand binding sites are experimentally uncharacterised. The TMSite algorithms read in existing PDB structural data and isolate binding sites regions and identifies conserved features in functionally related proteins (proteins that bind the same ligand). The Boundary Cubes method for surface representation was applied to the modified PDB file allowing the creation of graphs for proteins and ligands that could be compared and caused no loss of geometric data. A method is included for describing binding site features of individual ligands conserved in terms of spatial relationships allowed identification of 3D motifs, named fingerprints, which could be searched for in other protein structures. This method combine with a modification of the pocket algorithm allows reduced search areas for graph matching. The methods allow isolation of the binding site from a complexed protein PDB file, identification of conserved features among the binding sites of individual ligand types, and search for these features in sequence data. In terms of spatial conservation create a fingerprint ofthe binding site that can be sought in other proteins of/mown structure, identifYing putative binding sites. The approach offers a novel and generic method for the identification of putative ligand binding sites for proteins for which there is no prior detailed structural characterisation of protein/ ligand interactions. It is unique in being able to convert PDB data into graphs, ready for comparison and thus fitting of ligand to protein with consideration of chemical charge and in the future other chemica! properties

Application of computer-aided drug design for identification of P. falciparum inhibitors

Malaria is a millennia-old disease with the first recorded cases dating back to 2700 BC found in Chinese medical records, and later in other civilizations. It has claimed human lives to such an extent that there are a notable associated socio-economic consequences. Currently, according to the World Health Organization (WHO), Africa holds the highest disease burden with 94% of deaths and 82% of cases with P. falciparum having ~100% prevalence. Chemotherapy, such as artemisinin combination therapy, has been and continues to be the work horse in the fight against the disease, together with seasonal malaria chemoprevention and the use of insecticides. Natural products such as quinine and artemisinin are particularly important in terms of their antimalarial activity. The emphasis in current chemotherapy research is the need for time and cost-effective workflows focussed on new mechanisms of action (MoAs) covering the target candidate profiles (TCPs). Despite a decline in cases over the past decades with, countries increasingly becoming certified malaria free, a stalling trend has been observed in the past five years resulting in missing the 2020 Global Technical Strategy (GTS) milestones. With no effective vaccine, a reduction in funding, slower drug approval than resistance emergence from resistant and invasive vectors, and threats in diagnosis with the pfhrp2/3 gene deletion, malaria remains a major health concern. Motivated by these reasons, the primary aim of this work was a contribution to the antimalarial pipeline through in silico approaches focusing on P. falciparum. We first intended an exploration of malarial targets through a proteome scale screening on 36 targets using multiple metrics to account for the multi-objective nature of drug discovery. The continuous growth of structural data offers the ideal scenario for mining new MoAs covering antimalarials TCPs. This was combined with a repurposing strategy using a set of orally available FDA approved drugs. Further, use was made of time- and cost-effective strategies combining QVina-W efficiency metrics that integrate molecular properties, GRIM rescoring for molecular interactions and a hydrogen mass repartitioning (HMR) molecular dynamics (MD) scheme for accelerated development of antimalarials in the context of resistance. This pipeline further integrates a complex ranking for better drug-target selectivity, and normalization strategies to overcome docking scoring function bias. The different metrics, ranking, normalization strategies and their combinations were first assessed using their mean ranking error (MRE). A version combining all metrics was used to select 36 unique protein-ligand complexes, assessed in MD, with the final retention of 25. From the 16 in vitro tested hits of the 25, fingolimod, abiraterone, prazosin, and terazosin showed antiplasmodial activity with IC50 2.21, 3.37, 16.67 and 34.72 μM respectively and of these, only fingolimod was found to be not safe with respect to human cell viability. These compounds were predicted active on different molecular targets, abiraterone was predicted to interact with a putative liver-stage essential target, hence promising as a transmission-blocking agent. The pipeline had a promising 25% hit rate considering the proteome-scale and use of cost-effective approaches. Secondly, we focused on Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (PfDXR) using a more extensive screening pipeline to overcome some of the current in silico screening limitations. Starting from the ZINC lead-like library of ~3M, hierarchical ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches with molecular docking and re-scoring using eleven scoring functions (SFs) were used. Later ranking with an exponential consensus strategy was included. Selected hits were further assessed through Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), advanced MD sampling in a ligand pulling simulations and (Weighted Histogram Analysis Method) WHAM analysis for umbrella sampling (US) to derive binding free energies. Four leads had better predicted affinities in US than LC5, a 280 nM potent PfDXR inhibitor with ZINC000050633276 showing a promising binding of -20.43 kcal/mol. As shown with fosmidomycin, DXR inhibition offers fast acting compounds fulfilling antimalarials TCP1. Yet, fosmidomycin has a high polarity causing its short half-life and hampering its clinical use. These leads scaffolds are different from fosmidomycin and hence may offer better pharmacokinetic and pharmacodynamic properties and may also be promising for lead optimization. A combined analysis of residues’ contributions to the free energy of binding in MM-PBSA and to steered molecular dynamics (SMD) Fmax indicated GLU233, CYS268, SER270, TRP296, and HIS341 as exploitable for compound optimization. Finally, we updated the SANCDB library with new NPs and their commercially available analogs as a solution to NP availability. The library is extended to 1005 compounds from its initial 600 compounds and the database is integrated to Mcule and Molport APIs for analogs automatic update. The new set may contribute to virtual screening and to antimalarials as the most effective ones have NP origin.Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 202

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

Development and optimisation of computational tools for drug discovery

The aim of my PhD project was the development, optimisation, and implementation of new in silico virtual screening protocols. Specifically, this thesis manuscript is divided into three main parts, presenting some of the papers published during my doctoral work. The first one, here named CHEMOMETRIC PROTOCOLS IN DRUG DISCOVERY, is about the optimisation and application of an in house developed chemometric protocol. This part has been entirely developed at the University of Palermo - STEBICEF Department - under the guide of my supervisors. During the development of this part I have personally worked on the tuning and optimisation of the algorithm and on the docking campaigns to obtain molecule conformaitons. The second part, THE APPLICATION OF MOLECULAR DYNAMICS TO VIRTUAL SCREENING, presents a new approach to virtual screening, in particular the attention is focused on different approaches to the application of protein flexibility and dynamics to virtual screening. This part, has been carried out in cooperation with the University of Vienna - Department of Pharmaceutical Chemistry. For these works I have worked in the development of the general workflow, to a lesser extent to the programming (coding) part of the applications used and I mainly focused on the realisation of the screening campaigns and results interpretation. The third and last part, COMPUTATIONAL CHEMISTRY IN POLY-PHARMACOLOGY AND DRUG REPURPOSING, concerns the study of the in silico methods applied to two main topics of the drug discovery process, such as the drug repurposing and the polypharmacology. In this part I will briefly describe what published in two reviews dealing to the above mentioned topics. In conclusion during this doctoral project, I have demonstrated how the use of in silico tools can be useful in the drug discovery process. The Chemometric protocols developed and optimised represent in fact a helpful strategy to use for target fishing. Whereas, the application of molecular dynamics to virtual screening, especially for pharmacophore modelling, is a new way to deepen crucial features to be adopted in the search of new putative active compounds.The aim of my PhD project was the development, optimisation, and implementation of new in silico virtual screening protocols. Specifically, this thesis manuscript is divided into three main parts, presenting some of the papers published during my doctoral work. The first one, here named CHEMOMETRIC PROTOCOLS IN DRUG DISCOVERY, is about the optimisation and application of an in house developed chemometric protocol. This part has been entirely developed at the University of Palermo - STEBICEF Department - under the guide of my supervisors. During the development of this part I have personally worked on the tuning and optimisation of the algorithm and on the docking campaigns to obtain molecule conformaitons. The second part, THE APPLICATION OF MOLECULAR DYNAMICS TO VIRTUAL SCREENING, presents a new approach to virtual screening, in particular the attention is focused on different approaches to the application of protein flexibility and dynamics to virtual screening. This part, has been carried out in cooperation with the University of Vienna - Department of Pharmaceutical Chemistry. For these works I have worked in the development of the general workflow, to a lesser extent to the programming (coding) part of the applications used and I mainly focused on the realisation of the screening campaigns and results interpretation. The third and last part, COMPUTATIONAL CHEMISTRY IN POLY-PHARMACOLOGY AND DRUG REPURPOSING, concerns the study of the in silico methods applied to two main topics of the drug discovery process, such as the drug repurposing and the polypharmacology. In this part I will briefly describe what published in two reviews dealing to the above mentioned topics. In conclusion during this doctoral project, I have demonstrated how the use of in silico tools can be useful in the drug discovery process. The Chemometric protocols developed and optimised represent in fact a helpful strategy to use for target fishing. Whereas, the application of molecular dynamics to virtual screening, especially for pharmacophore modelling, is a new way to deepen crucial features to be adopted in the search of new putative active compounds