Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Challenges in the Discovery of Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitors.

Since the discovery of indoleamine 2,3-dioxygenase 1 (IDO1) as an attractive target for anticancer therapy in 2003, the search for inhibitors has been intensely pursued both in academia and in pharmaceutical companies. Many novel IDO1 inhibitor scaffolds have been described, and a few potent compounds have entered clinical trials. However, a significant number of the reported compounds contain problematic functional groups, suggesting that enzyme inhibition could be the result of undesirable side reactions instead of selective binding to IDO1. Here, we describe issues in the employed experimental protocols, review and classify reported IDO1 inhibitors, and suggest different approaches for confirming viable inhibitor scaffolds.

Human disease and drug pharmacology, complex as real life

In the past decades drug discovery practice has escaped from the complexity of the formerly used phenotypic screening in animals to focus on assessing drug effects on isolated protein targets in the search for drugs that exclusively and potently hit one selected target, thought to be critical for a given disease, while not affecting at all any other target to avoid the occurrence of side-effects. However, reality does not conform to these expectations, and, conversely, this approach has been concurrent with increased attrition figures in late-stage clinical trials, precisely due to lack of efficacy and safety. In this context, a network biology perspective of human disease and treatment has burst into the drug discovery scenario to bring it back to the consideration of the complexity of living organisms and particularly of the (patho)physiological environment where protein targets are (mal)functioning and where drugs have to exert their restoring action. Under this perspective, it has been found that usually there is not one but several disease-causing genes and, therefore, not one but several relevant protein targets to be hit, which do not work on isolation but in a highly interconnected manner, and that most known drugs are inherently promiscuous. In this light, the rationale behind the currently prevailing single-target-based drug discovery approach might even seem a Utopia, while, conversely, the notion that the complexity of human disease must be tackled with complex polypharmacological therapeutic interventions constitutes a difficult-torefuse argument that is spurring the development of multitarget therapies.

Dual inhibitors of beta-amyloid aggregation and acetylcholinesterase as multi-target anti-Alzheimer drug candidates

Notwithstanding the functional role that the aggregates of some amyloidogenic proteins can play in different organisms, protein aggregation plays a pivotal role in the pathogenesis of a large number of human diseases. One of such diseases is Alzheimer"s disease (AD), where the overproduction and aggregation of the β-amyloid peptide (Aβ) are regarded as early critical factors. Another protein that seems to occupy a prominent position within the complex pathological network of AD is the enzyme acetylcholinesterase (AChE), with classical and non-classical activities involved at the late (cholinergic deficit) and early (Aβ aggregation) phases of the disease. Dual inhibitors of Aβ aggregation and AChE are thus emerging as promising multi-target agents with potential to efficiently modify the natural course of AD. In the initial phases of the drug discovery process of such compounds, in vitro evaluation of the inhibition of Aβ aggregation is rather troublesome, as it is very sensitive to experimental assay conditions, and requires expensive synthetic Aβ peptides, which makes cost-prohibitive the screening of large compound libraries. Herein, we review recently developed multi-target anti-Alzheimer compounds that exhibit both Aβ aggregation and AChE inhibitory activities, and, in some cases also additional valuable activities such as BACE-1 inhibition or antioxidant properties. We also discuss the development of simplified in vivo methods for the rapid, simple, reliable, unexpensive, and high-throughput amenable screening of Aβ aggregation inhibitors that rely on the overexpression of Aβ42 alone or fused with reporter proteins in Escherichia coli.

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.

A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

A "Trojan horse" strategy to reverse drug-resistance in brain tumors

Los gliomas malignos representan una de las formas más agresivas de los tumores del sistema nervioso central (SNC). De acuerdo con la clasificación de los tumores cerebrales de la Organización Mundial de la Salud (OMS), los astrocitomas han sido categorizados en cuatro grados, determinados por la patología subyacente. Es así como los gliomas malignos (o de alto grado) incluyen el glioma anaplásico (grado III) así como el glioblastoma multiforme (GBM, grado IV),estos últimos los más agresivos con el peor pronóstico (1). El manejo terapéutico de los tumores del SNC se basa en la cirugía, la radioterapia y la quimioterapia, dependiendo de las características del tumor, el estadio clínico y la edad (2),(3), sin embargo ninguno de los tratamientos estándar es completamente seguro y compatible con una calidad de vida aceptable (3), (4). En general, la quimioterapia es la primera opción en los tumores diseminados, como el glioblastoma invasivo y el meduloblastoma de alto riesgo o con metástasis múltiple, pero el pronóstico en estos pacientes es muy pobre (2),(3). Solamente nuevas terapias dirigidas (2) como las terapias anti-angiogénicas (4); o terapias génicas muestran un beneficio real en grupos limitados de pacientes con defectos moleculares específicos conocidos (4). De este modo, se hace necesario el desarrollo de nuevas terapias farmacológicas para atacar los tumores cerebrales. Frente a las terapias los gliomas malignos son con frecuencia quimioresistentes, y esta resistencia parece depender de al menos dos mecanismos: en primer lugar, la pobre penetración de muchas drogas anticáncer a través de la barrera hematoencefálica (BBB: Blood Brain Barrier), la barrera del fluido sangre-cerebroespinal (BCSFB: Blood-cerebrospinal fluid barrier) y la barrera sangre-tumor (BTB: blood-tumor barrier). Dicha resistencia se debe a la interacción de la droga con varios transportadores o bombas de eflujo de droga ABC (ABC: ATP-binding cassette) que se sobre expresan en las células endoteliales o epiteliales de estas barreras. En segundo lugar, estos transportadores de eflujo de drogas ABC propios de las células tumorales confieren un fenotipo conocido como resistencia a multidrogas (MDR: multidrug resistance), el cual es característico de varios tumores sólidos. Este fenotipo también está presente en los tumores del SNC y su papel en gliomas es objeto de investigación (5). Por consiguiente el suministro de medicamentos a través de la BBB es uno de los problemas vitales en los tratamientos de terapia dirigida. Estudios recientes han demostrado que algunas moléculas pequeñas utilizadas en estas terapias son sustratos de la glicoproteína P (Pgp: P-gycoprotein), así como también de otras bombas de eflujo como las proteínas relacionadas con la resistencia a multidrogas (MRPs: multidrug resistance-related proteins (MRPs) o la proteína relacionada con cáncer de seno (BCRP: breast-cancer resistance related protein)) que no permiten que las drogas de este tipo alcancen el tumor (1). Un sustrato de Pgp y BCRP es la DOXOrubicina (DOXO), un fármaco utilizado en la terapia anti cáncer, el cual es muy eficaz para atacar las células del tumor cerebral in vitro, pero con un uso clínico limitado por la poca entrega a través de la barrera hematoencefálica (BBB) y por la resistencia propia de los tumores. Por otra parte las células de BBB y las células del tumor cerebral tienen también proteínas superficiales, como el receptor de la lipoproteína de baja densidad (LDLR), que podría utilizarse como blanco terapéutico en BBB y tumores cerebrales. Es asi como la importancia de este estudio se basa en la generación de estrategias terapéuticas que promuevan el paso de las drogas a través de la barrera hematoencefalica y tumoral, y a su vez, se reconozcan mecanismos celulares que induzcan el incremento en la expresión de los transportadores ABC, de manera que puedan ser utilizados como blancos terapéuticos.Este estudio demostró que el uso de una nueva estrategia basada en el “Caballo de Troya”, donde se combina la droga DOXOrubicina, la cual es introducida dentro de un liposoma, salvaguarda la droga de manera que se evita su reconocimiento por parte de los transportadores ABC tanto de la BBB como de las células del tumor. La construcción del liposoma permitió utilizar el receptor LDLR de las células asegurando la entrada a través de la BBB y hacia las células tumorales a través de un proceso de endocitosis. Este mecanismo fue asociado al uso de estatinas o drogas anticolesterol las cuales favorecieron la expresión de LDLR y disminuyeron la actividad de los transportadores ABC por nitración de los mismos, incrementando la eficiencia de nuestro Caballo de Troya. Por consiguiente demostramos que el uso de una nueva estrategia o formulación denominada ApolipoDOXO más el uso de estatinas favorece la administración de fármacos a través de la BBB, venciendo la resistencia del tumor y reduciendo los efectos colaterales dosis dependiente de la DOXOrubicina. Además esta estrategia del "Caballo de Troya", es un nuevo enfoque terapéutico que puede ser considerado como una nueva estrategia para aumentar la eficacia de diferentes fármacos en varios tumores cerebrales y garantiza una alta eficiencia incluso en un medio hipóxico,característico de las células cancerosas, donde la expresión del transportador Pgp se vió aumentada. Teniendo en cuenta la relación entre algunas vías de señalización reconocidas como moduladores de la actividad de Pgp, este estudio presenta no solo la estrategia del Caballo de Troya, sino también otra propuesta terapéutica relacionada con el uso de Temozolomide más DOXOrubicina. Esta estrategia demostró que el temozolomide logra penetrar la BBB por que interviene en la via de señalización de la Wnt/GSK3/β-catenina, la cual modula la expresión del transportador Pgp. Se demostró que el TMZ disminuye la proteína y el mRNA de Wnt3 permitiendo plantear la hipótesis de que la droga al disminuir la transcripción del gen Wnt3 en células de BBB, incrementa la activación de la vía fosforilando la β-catenina y conduciendo a disminuir la β-catenina nuclear y por tanto su unión al promotor del gen mdr1. Con base en los resultados este estudio permitió el reconocimiento de tres mecanismos básicos relacionados con la expresión de los transportadores ABC y asociados a las estrategias empleadas: el primero fue el uso de las estatinas, el cual condujo a la nitración de los transportadores disminuyendo su actividad por la via del factor de transcripción NFκB; el segundo a partir del uso del temozolomide, el cual metila el gen de Wnt3 reduciendo la actividad de la via de señalización de la la β-catenina, disminuyendo la expresión del transportador Pgp. El tercero consistió en la determinación de la relación entre el eje RhoA/RhoA quinasa como un modulador de la via (no canónica) GSK3/β-catenina. Se demostró que la proteína quinasa RhoA promovió la activación de la proteína PTB1, la cual al fosforilar a GSK3 indujo la fosforilación de la β-catenina, lo cual dio lugar a su destrucción por el proteosoma, evitando su unión al promotor del gen mdr1 y por tanto reduciendo su expresión. En conclusión las estrategias propuestas en este trabajo incrementaron la citotoxicidad de las células tumorales al aumentar la permeabilidad no solo de la barrera hematoencefálica, sino también de la propia barrera tumoral. Igualmente, la estrategia del “Caballo de Troya” podría ser útil para la terapia de otras enfermedades asociadas al sistema nervioso central. Por otra parte estos estudios indican que el reconocimiento de mecanismos asociados a la expresión de los transportadores ABC podría constituir una herramienta clave en el desarrollo de nuevas terapias anticáncer.

A novel Bayesian approach to drug design with simple and complex enzymes: Use with lens aldehyde dehydrogenase and the glyoxalase pathway

Purpose: Acquiring details of kinetic parameters of enzymes is crucial to biochemical understanding, drug development, and clinical diagnosis in ocular diseases. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. Methods: We have developed Bayesian utility functions to minimise kinetic parameter variance involving differentiation of model expressions and matrix inversion. These have been applied to the simple kinetics of the enzymes in the glyoxalase pathway (of importance in posttranslational modification of proteins in cataract), and the complex kinetics of lens aldehyde dehydrogenase (also of relevance to cataract). Results: Our successful application of Bayesian statistics has allowed us to identify a set of rules for designing optimum kinetic experiments iteratively. Most importantly, the distribution of points in the range is critical; it is not simply a matter of even or multiple increases. At least 60 % must be below the KM (or plural if more than one dissociation constant) and 40% above. This choice halves the variance found using a simple even spread across the range.With both the glyoxalase system and lens aldehyde dehydrogenase we have significantly improved the variance of kinetic parameter estimation while reducing the number and costs of experiments. Conclusions: We have developed an optimal and iterative method for selecting features of design such as substrate range, number of measurements and choice of intermediate points. Our novel approach minimises parameter error and costs, and maximises experimental efficiency. It is applicable to many areas of ocular drug design, including receptor-ligand binding and immunoglobulin binding, and should be an important tool in ocular drug discovery.

Discovery of New Inhibitors of Schistosoma mansoni PNP by Pharmacophore-Based Virtual Screening

Schistosomiasis is considered the second most important tropical parasitic disease, with severe socioeconomic consequences for millions of people worldwide. Schistosoma monsoni, one of the causative agents of human schistosomiasis, is unable to synthesize purine nucleotides de novo, which makes the enzymes of the purine salvage pathway important targets for antischistosomal drug development. In the present work, we describe the development of a pharmacophore model for ligands of S. mansoni purine nucleoside phosphorylase (SmPNP) as well as a pharmacophore-based virtual screening approach, which resulted in the identification of three thioxothiazolidinones (1-3) with substantial in vitro inhibitory activity against SmPNP. Synthesis, biochemical evaluation, and structure activity relationship investigations led to the successful development of a small set of thioxothiazolidinone derivatives harboring a novel chemical scaffold as new competitive inhibitors of SmPNP at the low-micromolar range. Seven compounds were identified with IC(50) values below 100 mu M. The most potent inhibitors 7, 10, and 17 with 1050 of 2, 18, and 38 mu M, respectively, could represent new potential lead compounds for further development of the therapy of schistosomiasis.

Novel insights for dihydroorotate dehydrogenase class 1A inhibitors discovery

The enzyme dihydroorotate dehydrogenase (DHODH) has been suggested as a promising target for the design of trypanocidal agents. We report here the discovery of novel inhibitors of Trypanosoma cruzi DHODH identified by a combination of virtual screening and ITC methods. Monitoring of the enzymatic reaction in the presence of selected ligands together with structural information obtained from X-ray crystallography analysis have allowed the identification and validation of a novel site of interaction (S2 site). This has provided important structural insights for the rational design of T cruzi and Leishmania major DHODH inhibitors. The most potent compound (1) in the investigated series inhibits TcDHODH enzyme with K(i)(app) value of 19.28 mu M and possesses a ligand efficiency of 0.54 kcal mol(-1) per non-H atom. The compounds described in this work are promising hits for further development. (C) 2010 Elsevier Masson SAS. All rights reserved.

Chorismate synthase: An attractive target for drug development against orphan diseases

The increase in incidence of infectious diseases worldwide, particularly in developing countries, is worrying. Each year, 14 million people are killed by infectious diseases, mainly HIV/AIDS, respiratory infections, malaria and tuberculosis. Despite the great burden in the poor countries, drug discovery to treat tropical diseases has come to a standstill. There is no interest by the pharmaceutical industry in drug development against the major diseases of the poor countries, since the financial return cannot be guaranteed. This has created an urgent need for new therapeutics to neglected diseases. A possible approach has been the exploitation of the inhibition of unique targets, vital to the pathogen such as the shikimate pathway enzymes, which are present in bacteria, fungi and apicomplexan parasites but are absent in mammals. The chorismate synthase (CS) catalyses the seventh step in this pathway, the conversion of 5-enolpyruvylshikimate-3-phosphate to chorismate. The strict requirement for a reduced flavin mononucleotide and the anti 1,4 elimination are both unusual aspects which make CS reaction unique among flavin-dependent enzymes, representing an important target for the chemotherapeutic agents development. In this review we present the main biochemical features of CS from bacterial and fungal sources and their difference from the apicomplexan CS. The CS mechanisms proposed are discussed and compared with structural data. The CS structures of some organisms are compared and their distinct features analyzed. Some known CS inhibitors are presented and the main characteristics are discussed. The structural and kinetics data reviewed here can be useful for the design of inhibitors. © 2007 Bentham Science Publishers Ltd.

Biotechnology of polyketides: new breath of life for the novel antibiotic genetic pathways discovery through metagenomics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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.

Computational investigation of the Plasmodium falciparum fatty acid biosynthetic pathway toward the discovery of novel antimalarials

The structural peculiarities of a protein are related to its biological function. In the fatty acid elongation cycle, one small carrier protein shuttles and delivers the acyl intermediates from one enzyme to the other. The carrier has to recognize several enzymatic counterparts, specifically interact with each of them, and finally transiently deliver the carried substrate to the active site. Carry out such a complex game requires the players to be flexible and efficiently adapt their structure to the interacting protein or substrate. In a drug discovery effort, the structure-function relationships of a target system should be taken into account to optimistically interfere with its biological function. In this doctoral work, the essential role of structural plasticity in key steps of fatty acid biosynthesis in Plasmodium falciparum is investigated by means of molecular simulations. The key steps considered include the delivery of acyl substrates and the structural rearrangements of catalytic pockets upon ligand binding. The ground-level bases for carrier/enzyme recognition and interaction are also put forward. The structural features of the target have driven the selection of proper drug discovery tools, which captured the dynamics of biological processes and could allow the rational design of novel inhibitors. The model may be perspectively used for the identification of novel pathway-based antimalarial compounds.

Anticancer drug screening from images of zebrafish embryogenesis

During the previous 10 years, global R&D expenditure in the pharmaceuticals and biotechnology sector has steadily increased, without a corresponding increase in output of new medicines. To address this situation, the biopharmaceutical industry's greatest need is to predict the failures at the earliest possible stage of the drug development process. A major key to reducing failures in drug screenings is the development and use of preclinical models that are more predictive of efficacy and safety in clinical trials. Further, relevant animal models are needed to allow a wider testing of novel hypotheses. Key to this is the developing, refining, and validating of complex animal models that directly link therapeutic targets to the phenotype of disease, allowing earlier prediction of human response to medicines and identification of safety biomarkers. Morehover, well-designed animal studies are essential to bridge the gap between test in cell cultures and people. Zebrafish is emerging, complementary to other models, as a powerful system for cancer studies and drugs discovery. We aim to investigate this research area designing a new preclinical cancer model based on the in vivo imaging of zebrafish embryogenesis. Technological advances in imaging have made it feasible to acquire nondestructive in vivo images of fluorescently labeled structures, such as cell nuclei and membranes, throughout early Zebrafishsh embryogenesis. This In vivo image-based investigation provides measurements for a large number of features at cellular level and events including nuclei movements, cells counting, and mitosis detection, thereby enabling the estimation of more significant parameters such as proliferation rate, highly relevant for investigating anticancer drug effects. In this work, we designed a standardized procedure for accessing drug activity at the cellular level in live zebrafish embryos. The procedure includes methodologies and tools that combine imaging and fully automated measurements of embryonic cell proliferation rate. We achieved proliferation rate estimation through the automatic classification and density measurement of epithelial enveloping layer and deep layer cells. Automatic embryonic cells classification provides the bases to measure the variability of relevant parameters, such as cell density, in different classes of cells and is finalized to the estimation of efficacy and selectivity of anticancer drugs. Through these methodologies we were able to evaluate and to measure in vivo the therapeutic potential and overall toxicity of Dbait and Irinotecan anticancer molecules. Results achieved on these anticancer molecules are presented and discussed; furthermore, extensive accuracy measurements are provided to investigate the robustness of the proposed procedure. Altogether, these observations indicate that zebrafish embryo can be a useful and cost-effective alternative to some mammalian models for the preclinical test of anticancer drugs and it might also provides, in the near future, opportunities to accelerate the process of drug discovery.