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.

Suitability of GRIND-based principal properties for the description of molecular similarity and ligand-based virtual screening

The information provided by the alignment-independent GRid Independent Descriptors (GRIND) can be condensed by the application of principal component analysis, obtaining a small number of principal properties (GRIND-PP), which is more suitable for describing molecular similarity. The objective of the present study is to optimize diverse parameters involved in the obtention of the GRIND-PP and validate their suitability for applications, requiring a biologically relevant description of the molecular similarity. With this aim, GRIND-PP computed with a collection of diverse settings were used to carry out ligand-based virtual screening (LBVS) on standard conditions. The quality of the results obtained was remarkable and comparable with other LBVS methods, and their detailed statistical analysis allowed to identify the method settings more determinant for the quality of the results and their optimum. Remarkably, some of these optimum settings differ significantly from those used in previously published applications, revealing their unexplored potential. Their applicability in large compound database was also explored by comparing the equivalence of the results obtained using either computed or projected principal properties. In general, the results of the study confirm the suitability of the GRIND-PP for practical applications and provide useful hints about how they should be computed for obtaining optimum results.

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.

Natural products biological screening and ligand-based virtual screening for the discovery of new antileishmanial agents

In the course of our research program to discover novel antileishmanial agents, a biological screening of natural products against Leishmania major promastigotes allowed the identification of a furoquinoline alkaloid (1) and a furanocoumarin (2) as new hits. Subsequently, an integrated ligand-based virtual screening approach was employed to search for new antileishmanial compounds using these naturally occurring molecules as templates. Fourteen out of 40 compounds selected from a database of about 800,000 compounds (extracted from ZINC, a free database for virtual screening) were experimentally confirmed to possess significant in vitro antileishmanial properties. The application of ligand-based virtual screening as a complementary approach to experimental natural product screening was a useful strategy to facilitate the identification of new promising lead candidates.

Structure- and ligand-based drug design approaches for neglected tropical diseases

Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.

A Combined Study Using Ligand-Based Design, Synthesis, and Pharmacological Evaluation of Analogues of the Acetaminophen Ortho-Regioisomer with Potent Analgesic Activity

A ligand-based drug design study was performed to acetaminophen regioisomers as analgesic candidates employing quantum chemical calculations at the DFT/B3LYP level of theory and the 6-31G* basis set. To do so, many molecular descriptors were used such as highest occupied molecular orbital, ionization potential, HO bond dissociation energies, and spin densities, which might be related to quench reactivity of the tyrosyl radical to give N-acetyl-p-benzosemiquinone-imine through an initial electron withdrawing or hydrogen atom abstraction. Based on this in silico work, the most promising molecule, orthobenzamol, was synthesized and tested. The results expected from the theoretical prediction were confirmed in vivo using mouse models of nociception such as writhing, paw licking, and hot plate tests. All biological results suggested an antinociceptive activity mediated by opioid receptors. Furthermore, at 90 and 120 min, this new compound had an effect that was comparable to morphine, the standard drug for this test. Finally, the pharmacophore model is discussed according to the electronic properties derived from quantum chemistry calculations.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.

Optimization of TRPV6 Calcium Channel Inhibitors Using a 3D Ligand-Based Virtual Screening Method

Herein, we report the discovery of the first potent and selective inhibitor of TRPV6, a calcium channel overexpressed in breast and prostate cancer, and its use to test the effect of blocking TRPV6-mediated Ca2+-influx on cell growth. The inhibitor was discovered through a computational method, xLOS, a 3D-shape and pharmacophore similarity algorithm, a type of ligand-based virtual screening (LBVS) method described briefly here. Starting with a single weakly active seed molecule, two successive rounds of LBVS followed by optimization by chemical synthesis led to a selective molecule with 0.3 μM inhibition of TRPV6. The ability of xLOS to identify different scaffolds early in LBVS was essential to success. The xLOS method may be generally useful to develop tool compounds for poorly characterized targets.

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.

Extracting Urban Food Potential: design-based methods for digital and bodily cartography

Sweden’s recent report on Urban Sustainable Development calls out a missing link between the urban design process and citizens. This paper investigates if engaging citizens as design agents by providing a platform for alternate participation can bridge this gap, through the transfer of spatial agency and new modes of critical cartography. To assess whether this is the case, the approaches are applied to Stockholm’s urban agriculture movement in a staged intervention. The aim of the intervention was to engage citizens in locating existing and potential places for growing food and in gathering information from these sites to inform design in urban agriculture. The design-based methodologies incorporated digital and bodily interfaces for this cartography to take place. The Urban CoMapper, a smartphone digital app, captured real-time perspectives through crowd-sourced mapping. In the bodily cartography, participant’s used their bodies to trace the site and reveal their sensorial perceptions. The data gathered from these approaches gave way to a mode of artistic research for exploring urban agriculture, along with inviting artists to be engaged in the dialogues. In sum, results showed that a combination of digital and bodily approaches was necessary for a critical cartography if we want to engage citizens holistically into the urban design process as spatial agents informing urban policy. Such methodologies formed a reflective interrogation and encouraged a new intimacy with nature, in this instance, one that can transform our urban conduct by questioning our eating habits: where we get our food from and how we eat it seasonally.