Integration of Ligand- and Target-Based Virtual Screening for the Discovery of Cruzain Inhibitors

A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.

2D QSAR and similarity studies on cruzain inhibitors aimed at improving selectivity over cathepsin L

Hologram quantitative structure-activity relationships (HQSAR) were applied to a data set of 41 cruzain inhibitors. The best HQSAR model (Q(2) = 0.77; R-2 = 0.90) employing Surflex-Sim, as training and test sets generator, was obtained using atoms, bonds, and connections as fragment distinctions and 4-7 as fragment size. This model was then used to predict the potencies of 12 test set compounds, giving satisfactory predictive R-2 value of 0,88. The contribution maps obtained from the best HQSAR model are in agreement with the biological activities of the study compounds. The Trypanosoma cruzi cruzain shares high similarity with the mammalian homolog cathepsin L. The selectivity toward cruzam was checked by a database of 123 compounds, which corresponds to the 41 cruzain inhibitors used in the HQSAR model development plus 82 cathepsin L inhibitors. We screened these compounds by ROCS (Rapid Overlay of Chemical Structures), a Gaussian-shape volume overlap filter that can rapidly identify shapes that match the query molecule. Remarkably, ROCS was able to rank the first 37 hits as being only cruzain inhibitors. In addition, the area under the curve (AUC) obtained with ROCS was 0.96, indicating that the method was very efficient to distinguishing between cruzain and cathepsin L inhibitors. (c) 2007 Elsevier Ltd. All rights reserved.

Insights into the Molecular Requirements for the Anti-obesity Activity of a Series of CB1 Ligands

Two-dimensional and 3D quantitative structure-activity relationships studies were performed on a series of diarylpyridines that acts as cannabinoid receptor ligands by means of hologram quantitative structure-activity relationships and comparative molecular field analysis methods. The quantitative structure-activity relationships models were built using a data set of 52 CB1 ligands that can be used as anti-obesity agents. Significant correlation coefficients (hologram quantitative structure-activity relationships: r 2 = 0.91, q 2 = 0.78; comparative molecular field analysis: r 2 = 0.98, q 2 = 0.77) were obtained, indicating the potential of these 2D and 3D models for untested compounds. The models were then used to predict the potency of an external test set, and the predicted (calculated) values are in good agreement with the experimental results. The final quantitative structure-activity relationships models, along with the information obtained from 2D contribution maps and 3D contour maps, obtained in this study are useful tools for the design of novel CB1 ligands with improved anti-obesity potency.

Structure-function relationships of the peptide Paulistine: A novel toxin from the venom of the social wasp Polybia paulista

Background: The peptide Paulistine was isolated from the venom of wasp Polybia paulista. This peptide exists under a natural equilibrium between the forms: oxidised - with an intra-molecular disulphide bridge; and reduced - in which the thiol groups of the cysteine residues do not form the disulphide bridge. The biological activities of both forms of the peptide are unknown up to now. Methods: Both forms of Paulistine were synthesised and the thiol groups of the reduced form were protected with the acetamidemethyl group [Acm-Paulistine] to prevent re-oxidation. The structure/activity relationships of the two forms were investigated, taking into account the importance of the disulphide bridge. Results: Paulistine has a more compact structure, while Acm-Paulistine has a more expanded conformation. Bioassays reported that Paulistine caused hyperalgesia by interacting with the receptors of lipid mediators involved in the cyclooxygenase type II pathway, while Acm-Paullistine also caused hyperalgesia, but mediated by receptors involved in the participation of prostanoids in the cyclooxygenase type II pathway. Conclusion: The acetamidemethylation of the thiol groups of cysteine residues caused small structural changes, which in turn may have affected some physicochemical properties of the Paulistine. Thus, the dissociation of the hyperalgesy from the edematogenic effect when the actions of Paulistine and Acm-Paulistine are compared to each other may be resulting from the influence of the introduction of Acm-group in the structure of Paulistine. General significance: The peptides Paulistine and Acm-Paulistine may be used as interesting tools to investigate the mechanisms of pain and inflammation in future studies. © 2013 Elsevier B.V.

Novel aryl beta-aminocarbonyl derivatives as inhibitors of Trypanosoma cruzi trypanothione reductase: binding mode revised by docking and GRIND2-based 3D-QSAR procedures

Trypanothione reductase has long been investigated as a promising target for chemotherapeutic intervention in Chagas disease, since it is an enzyme of a unique metabolic pathway that is exclusively present in the pathogen but not in the human host, which has the analog Glutathione reductase. In spite of the present data-set includes a small number of compounds, a combined use of flexible docking, pharmacophore perception, ligand binding site prediction, and Grid-Independent Descriptors GRIND2-based 3D-Quantitative Structure-Activity Relationships (QSAR) procedures allowed us to rationalize the different biological activities of a series of 11 aryl beta-aminocarbonyl derivatives, which are inhibitors of Trypanosoma cruzi trypanothione reductase (TcTR). Three QSAR models were built and validated using different alignments, which are based on docking with the TcTR crystal structure, pharmacophore, and molecular interaction fields. The high statistical significance of the models thus obtained assures the robustness of this second generation of GRIND descriptors here used, which were able to detect the most important residues of such enzyme for binding the aryl beta-aminocarbonyl derivatives, besides to rationalize distances among them. Finally, a revised binding mode has been proposed for our inhibitors and independently supported by the different methodologies here used, allowing further optimization of the lead compounds with such combined structure- and ligand-based approaches in the fight against the Chagas disease.

Structure-based drug design studies on a series of aldolase inhibitors

Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.

High yield conversion of doxorubicin to 2-pyrrolinodoxorubicin, an analog 500-1000 times more potent: structure-activity relationship of daunosamine-modified derivatives of doxorubicin.

A convenient, high yield conversion of doxorubicin to 3'-deamino-3'-(2''-pyrroline-1''-yl)doxorubicin is described. This daunosamine-modified analog of doxorubicin is 500-1000 times more active in vitro than doxorubicin. The conversion is effected by using a 30-fold excess of 4-iodobutyraldehyde in anhydrous dimethylformamide. The yield is higher than 85%. A homolog of this compound, 3'-deamino-3'-(1'',3''-tetrahydropyridine-1''-yl)doxorubicin, was also synthesized by using 5-iodovaleraldehyde. In this homolog, the daunosamine nitrogen is incorporated into a six- instead of a five-membered ring. This analog was 30-50 times less active than its counterpart with a five-membered ring. A similar structure-activity relationship was found when 3'-deamino-3'-(3''-pyrrolidone-1''-yl)doxorubicin (containing a five-membered ring) and 3'-deamino-3'-(3''-piperidone-1''-yl)doxorubicin (with a six-membered ring) were tested in vitro, the former being 5 times more potent than the latter. To further elucidate structure-activity relationships, 3'-deamino-3'-(pyrrolidine-1''-yl)doxorubicin, 3'-deamino-3'-(isoindoline-2''-yl)doxorubicin, 3'-deamino-3'-(2''-methyl-2''-pyrroline-1''-yl)doxorubicin, and 3'-deamino-3'-(3''-pyrroline-1''-yl)doxorubicin were also synthesized and tested. All the analogs were prepared by using reactive halogen compounds for incorporating the daunosamine nitrogen of doxorubicin into a five- or six-membered ring. These highly active antineoplastic agents can be used for incorporation into targeted cytotoxic analogs of luteinizing hormone-releasing hormone intended for cancer therapy.

Preliminary structure-activity relationship studies on some novel s-substituted aliphatic analogues of 5-{1-[(4- chlorophenyl) sulfonyl]-3-piperidinyl}-1, 3, 4-oxadiazol-2-yl sulfide

Purpose: To study the structure-activity relationships of synthetic multifunctional sulfides through evaluation of lipoxygenase and anti-bacterial activities. Methods: S-substituted derivatives of the parent compound 5-(1-(4-chlorophenylsulfonyl) piperidin-3- yl)-1, 3, 4-oxadiazole-2-thiol were synthesized through reaction with different saturated and unsaturated alkyl halides in DMF medium, with NaH catalyst. Spectral characterization of each derivative was carried out with respect to IR, 1H - NMR, 13C - NMR and EI - MS. The lipoxygenase inhibitory and antibacterial activities of the derivatives were determined using standard procedures. Results: Compound 5e exhibited higher lipoxygenase inhibitory potential than the standard (Baicalein®), with % inhibition of 94.71 ± 0.45 and IC50 of 20.72 ± 0.34 μmoles/L. Compound 5b showed significant antibacterial potential against all the bacterial strains with % inhibition ranging from 62.04 ± 2.78, 69.49 ± 0.41, 63.38 ± 1.97 and 59.70 ± 3.70 to 78.32 ± 0.41, while MIC ranged from 8.18 ± 2.00, 10.60 ± 1.83, 10.84 ± 3.00, 9.81 ± 1.86 and 11.73 ± 5.00 μmoles/L for S. typhi, E. coli, P. aeruginosa, B. subtilis and S. aureus, respectively. Compounds 5d, 5e and 5g showed good antibacterial activity against S. typhi and B. subtilis bacterial strains. Conclusion: The results suggest that compound 5e bearing n-pentyl group is a potent lipoxygenase inhibitor, while compound 5b with n-propyl substitution is a strong antibacterial agent. In addition, compounds 5d, 5e and 5g bearing n-butyl, n-pentyl and n-octyl groups, respectively, are good antibacterial agents against S. typhi and B. subtilis.

Estudos de relações estrutura-atividade quantitativas (QSAR) de bis-benzamidinas com atividade antifúngica

This paper describes 2D-QSAR and 3D-QSAR studies against Candida albicans and Cryptococcus neofarmans for a set of 20 bisbenzamidines. In the studies of 2D-QSAR with C. albicans it was obtained a correlation between log MIC-1 and lipolo component-Z (r² = 0.68; Q² = 0.51). In the case of C. neofarmans a correlation between log MIC-1 and lipolo component-Z and of Balaban index (r² = 0.85; Q² = 0.6) was obtained. 3D-QSAR studies using CoMFA showed that the steric fields contributed more to the predicted activities for Candida albicans (94.9%) and Cryptococcus neofarmans (97.9%).

Structure-activity studies of conantokins as human N-methyl-D-aspartate receptor modulators

The activities of conantokin-G (con-G), conantokin-T (con-T), and several novel analogues have been studied using polyamine enhancement of [H-3]MK-801 binding to human glutamate-N-methyl-D-aspartate (NMDA) receptors, and their structures have been examined using CD and H-1 NMR spectroscopy. The potencies of con-G[A7], con-G, and con-T as noncompetitive inhibitors of spermine-enhanced [H-3]MK-801 binding to NMDA receptor obtained from human brain tissue are similar to those obtained using rat brain tissue. The secondary structure and activity of con-G are found to be highly sensitive to amino acid substitution and modification. NMR chemical shift data indicate that con-G, con-G[D8,D17], and con-G[A7] have similar conformations in the presence of Ca2+. This consists of a helix for residues 2-16, which is kinked in the vicinity of Gla10. This is confirmed by 3D structure calculations on con-G[A7]. Restraining this helix in a linear form (i.e., con-G[A7,E10-K13]) results in a minor reduction in potency. Incorporation of a 7-10 salt-bridge replacement (con-G[K7-E10]) prevents helix formation in aqueous solution and produces a peptide with low potency. Peptides with the Leu5-Tyr5 substitution also have low potencies (con-G[Y5,A7] and con-G[Y5,K7]) indicating that Leu5 in con-G is important for full antagonist behavior. We have also shown that the Gla-Ala7 substitution increases potency, whereas the Gla-Lys7 substitution has no effect. Con-G and con-G[K7] both exhibit selectivity between NMDA subtypes from mid-frontal and superior temporal gyri, but not between sensorimotor and mid-frontal gyri. Asn8 and/or Asn17 appear to be important for the ability of con-G to function as an inhibitor of polyamine-stimulated [3H]MK-801 binding, but not in maintaining secondary structure. The presence of Ca2+ does not increase the potencies of con-G and con-T for NMDA receptors but does stabilize the helical structures of con-G, con-G[D8,D17], and, to a lesser extent, con-G[A7]. The NMR data support the existence of at least two independent Ca2+-chelating sites in con-G, one involving Gla7 and possibly Gla3 and the other likely to involve Gla10 and/or Gla14.

Obtenció de nous anàlegs amb activitat brassinoesteroide mitjançant modelització molecular i síntesi

Els brassinoesteroides són productes naturals que actuen com a potents reguladors del creixement vegetal. Presenten aplicacions prometedores en l’agricultura degut a que, aplicats exògenament, augmenten la qualitat i la quantitat de les collites. Ara bé, el seu ús s’ha vist restringit degut a la seva costosa obtenció. Aquest fet ha motivat la recerca de nous compostos actius més assequibles. En aquest projecte es planteja el disseny i obtenció de nous anàlegs seguint diferents estratègies que impliquen tant l’ús de mètodes de modelització molecular com de síntesi orgànica. La primera d’aquestes estratègies consisteix en buscar compostos actius en bases de dades de compostos comercials a través de processos de Virtual Screening desenvolupats amb mètodes computacionals basats en Camps d’Interacció Molecular. Així, es van establir i interpretar models de Relacions Quantitatives Estructura-Activitat (QSAR) emprant descriptors independents de l’alineament (GRIND) i, amb col•laboració amb la Universitat de Perugia, aquest criteri de cerca es va ampliar amb l’aplicació de descriptors FLAP de nova generació. Una altra estratègia es va basar en intentar substituir l’esquelet esteroide dels brassinoesteroides per una estructura equivalent, fixant com a cadena lateral el grup (R)-hexahidromandelil. S’han aplicat dos criteris: mètodes computacionals basats en models QSAR establerts amb descriptors GRIND i també en la metodologia SHOP (scaffold hopping), i, per altra banda, anàlegs proposats racionalment a partir d’un estudi efectuat sobre disruptors endocrins no esteroïdals. Sobre les estructures trobades s’hi va unir la cadena lateral comercial esmentada per via sintètica, en la qual s’ha hagut de fer un èmfasi especial en grups protectors. En total, 49 estructures es proposen per a ser obtingudes sintèticament. També s’ha treballat en l’obtenció un agonista derivat de l’hipotètic antagonista KM-01. Totes les molècules candidates, ja siguin comercials o obtingudes sintèticament, estant sent avaluades en el test d’inclinació de la làmina d’arròs (RLIT).

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Molecular modeling of peptide-MHC class I complexes : applications to peptide based immunotherapy

Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.

A web-based tool to aid the identification of chemicals potentially posing a health risk through percutaneous exposure

Occupational hygiene practitioners typically assess the risk posed by occupational exposure by comparing exposure measurements to regulatory occupational exposure limits (OELs). In most jurisdictions, OELs are only available for exposure by the inhalation pathway. Skin notations are used to indicate substances for which dermal exposure may lead to health effects. However, these notations are either present or absent and provide no indication of acceptable levels of exposure. Furthermore, the methodology and framework for assigning skin notation differ widely across jurisdictions resulting in inconsistencies in the substances that carry notations. The UPERCUT tool was developed in response to these limitations. It helps occupational health stakeholders to assess the hazard associated with dermal exposure to chemicals. UPERCUT integrates dermal quantitative structure-activity relationships (QSARs) and toxicological data to provide users with a skin hazard index called the dermal hazard ratio (DHR) for the substance and scenario of interest. The DHR is the ratio between the estimated 'received' dose and the 'acceptable' dose. The 'received' dose is estimated using physico-chemical data and information on the exposure scenario provided by the user (body parts exposure and exposure duration), and the 'acceptable' dose is estimated using inhalation OELs and toxicological data. The uncertainty surrounding the DHR is estimated with Monte Carlo simulation. Additional information on the selected substances includes intrinsic skin permeation potential of the substance and the existence of skin notations. UPERCUT is the only available tool that estimates the absorbed dose and compares this to an acceptable dose. In the absence of dermal OELs it provides a systematic and simple approach for screening dermal exposure scenarios for 1686 substances.

Proposição, validação e análise dos modelos que correlacionam estrutura química e atividade biológica

The present paper aims to bring under discussion some theoretical and practical aspects about the proposition, validation and analysis of QSAR models based on multiple linear regression. A comprehensive approach for the derivation of extrathermodynamic equations is reviewed. Some examples of QSAR models published in the literature are analyzed and criticized.