Improvement of Virtual Screening Predictions using Computational Intelligence Methods

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of scoring functions used in most VS methods we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, this information being exploited afterwards to improve VS predictions.

Design and synthesis of novel quinolones directed to the Plasmodium falciparum bc1 protein complex

Tese de Doutoramento, Química, Especialização em Química Orgânica, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

Descubrimiento de fármacos basado en cribado virtual refinado con enfoques neuronales paralelos

En el campo de la medicina clínica es crucial poder determinar la seguridad y la eficacia de los fármacos actuales y además acelerar el descubrimiento de nuevos compuestos activos. Para ello se llevan a cabo ensayos de laboratorio, que son métodos muy costosos y que requieren mucho tiempo. Sin embargo, la bioinformática puede facilitar enormemente la investigación clínica para los fines mencionados, ya que proporciona la predicción de la toxicidad de los fármacos y su actividad en enfermedades nuevas, así como la evolución de los compuestos activos descubiertos en ensayos clínicos. Esto se puede lograr gracias a la disponibilidad de herramientas de bioinformática y métodos de cribado virtual por ordenador (CV) que permitan probar todas las hipótesis necesarias antes de realizar los ensayos clínicos, tales como el docking estructural, mediante el programa BINDSURF. Sin embargo, la precisión de la mayoría de los métodos de CV se ve muy restringida a causa de las limitaciones presentes en las funciones de afinidad o scoring que describen las interacciones biomoleculares, e incluso hoy en día estas incertidumbres no se conocen completamente. En este trabajo abordamos este problema, proponiendo un nuevo enfoque en el que las redes neuronales se entrenan con información relativa a bases de datos de compuestos conocidos (proteínas diana y fármacos), y se aprovecha después el método para incrementar la precisión de las predicciones de afinidad del método de CV BINDSURF.

In vitro-in vivo Pharmacokinetic correlation model for quality assurance of antiretroviral drugs

Introduction: The In vitro-in vivo pharmacokinetic correlation models (IVIVC) are a fundamental part of the drug discovery and development process. The ability to accurately predict the in vivo pharmacokinetic profile of a drug based on in vitro observations can have several applications during a successful development process. Objective: To develop a comprehensive model to predict the in vivo absorption of antiretroviral drugs based on permeability studies, in vitro and in vivo solubility and demonstrate its correlation with the pharmacokinetic profile in humans. Methods: Analytical tools to test the biopharmaceutical properties of stavudine, lamivudine y zidovudine were developed. The kinetics of dissolution, permeability in caco-2 cells and pharmacokinetics of absorption in rabbits and healthy volunteers were evaluated. Results: The cumulative areas under the curve (AUC) obtained in the permeability study with Caco-2 cells, the dissolution study and the pharmacokinetics in rabbits correlated with the cumulative AUC values in humans. These results demonstrated a direct relation between in vitro data and absorption, both in humans and in the in vivo model. Conclusions: The analytical methods and procedures applied to the development of an IVIVC model showed a strong correlation among themselves. These IVIVC models are proposed as alternative and cost/effective methods to evaluate the biopharmaceutical properties that determine the bioavailability of a drug and their application includes the development process, quality assurance, bioequivalence studies and pharmacosurveillance.

El efecto de la definición regulatoria de banda ancha sobre la difusión y la competencia del mercado de servicios de Internet fijo en Colombia

A partir de la dinámica evolutiva de la economía de las Tecnologías de la Información y las Comunicaciones y el establecimiento de estándares mínimos de velocidad en distintos contextos regulatorios a nivel mundial, en particular en Colombia, en el presente artículo se presentan diversas aproximaciones empíricas para evaluar los efectos reales que conlleva el establecimiento de definiciones de servicios de banda ancha en el mercado de Internet fijo. Con base en los datos disponibles para Colombia sobre los planes de servicios de Internet fijo ofrecidos durante el periodo 2006-2012, se estima para los segmentos residencial y corporativo el proceso de difusión logístico modificado y el modelo de interacción estratégica para identificar los impactos generados sobre la masificación del servicio a nivel municipal y sobre las decisiones estratégicas que adoptan los operadores, respectivamente. Respecto a los resultados, se encuentra, por una parte, que las dos medidas regulatorias establecidas en Colombia en 2008 y 2010 presentan efectos significativos y positivos sobre el desplazamiento y el crecimiento de los procesos de difusión a nivel municipal. Por otra parte, se observa sustituibilidad estratégica en las decisiones de oferta de velocidad de descarga por parte de los operadores corporativos mientras que, a partir del análisis de distanciamiento de la velocidad ofrecida respecto al estándar mínimo de banda ancha, se demuestra que los proveedores de servicios residenciales tienden a agrupar sus decisiones de velocidad alrededor de los niveles establecidos por regulación.

Anti-proliferative effects of novel hydroxyamides and triazoles

Chemotherapy is a major cancer treatment option. The synthesis of new compounds with anti-proliferative properties and specificity is a current challenge in drug-discovery today. Our goal was to develop compounds, either hydroxyamides derived from D-glucuronic acid or triazole-cinchone hybrids, and to evaluate their anti-proliferative properties. Anti-proliferative activity of the newly synthesized compounds was examined against human breast adenocarcinoma (MCF-7) and human colon carcinoma (MDST8) cell-lines. Cell growth and viability was analysed by the Cell-Counting Kit-8 method. The 5-fluoroacil was used as a positive control. The compounds were studied between 10-9-10-5M. Fifteen compounds from the hydroxyamide family and two triazole compounds were investigated. Most of the compounds from the hydroxyamide family revealed mild (~20%) to moderate (50%) anti-proliferative effects in both cell-lines, with the exception of Hydroxyamide B1 which did not affect MDST8 proliferation, and hydroxyamide B3 where proliferation of MDST8 was inhibited by 90%. Triazoles (A and B) evoked a strong (~100%) anti-proliferative effect of MDST8 cell-lines. Proliferation of MCF-7 was selectively and effectively (~98%) inhibited by triazole B while triazole A had a mild effect. In conclusion, when compared to hydroxyamides, triazoles evoked a stronger anti-proliferative effect and might be promising anti-tumoral drugs.

Action following the discovery of a global association between the whole genome and adverse event risk in a clinical drug-development programme

Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non-sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to? determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright (C) 2008 John Wiley & Sons, Ltd.

Discovery of Phthalimides as Immunomodulatory and Antitumor Drug Prototypes

Brazilian National Council of Research (CNPq)[471834/2006-8]

Building partnership for drug and ag discovery and conservation of the natural resources in Brazil.

2009

Many paths lead to discovery : analogical retrieval of cancer therapies

This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

An analytical method for assessing stage-specific drug activity in Plasmodium vivax malaria : implications for ex vivo drug susceptibility testing

The emergence of highly chloroquine (CQ) resistant P. vivax in Southeast Asia has created an urgent need for an improved understanding of the mechanisms of drug resistance in these parasites, the development of robust tools for defining the spread of resistance, and the discovery of new antimalarial agents. The ex vivo Schizont Maturation Test (SMT), originally developed for the study of P. falciparum, has been modified for P. vivax. We retrospectively analysed the results from 760 parasite isolates assessed by the modified SMT to investigate the relationship between parasite growth dynamics and parasite susceptibility to antimalarial drugs. Previous observations of the stage-specific activity of CQ against P. vivax were confirmed, and shown to have profound consequences for interpretation of the assay. Using a nonlinear model we show increased duration of the assay and a higher proportion of ring stages in the initial blood sample were associated with decreased effective concentration (EC50) values of CQ, and identify a threshold where these associations no longer hold. Thus, starting composition of parasites in the SMT and duration of the assay can have a profound effect on the calculated EC50 for CQ. Our findings indicate that EC50 values from assays with a duration less than 34 hours do not truly reflect the sensitivity of the parasite to CQ, nor an assay where the proportion of ring stage parasites at the start of the assay does not exceed 66%. Application of this threshold modelling approach suggests that similar issues may occur for susceptibility testing of amodiaquine and mefloquine. The statistical methodology which has been developed also provides a novel means of detecting stage-specific drug activity for new antimalarials.

MS-based metabolomics facilitates the discovery of in vivo functional small molecules with a diversity of biological contexts

In vivo small molecules as necessary intermediates are involved in numerous critical metabolic pathways and biological processes associated with many essential biological functions and events. There is growing evidence that MS-based metabolomics is emerging as a powerful tool to facilitate the discovery of functional small molecules that can better our understanding of development, infection, nutrition, disease, toxicity, drug therapeutics, gene modifications and host-pathogen interaction from metabolic perspectives. However, further progress must still be made in MS-based metabolomics because of the shortcomings in the current technologies and knowledge. This technique-driven review aims to explore the discovery of in vivo functional small molecules facilitated by MS-based metabolomics and to highlight the analytic capabilities and promising applications of this discovery strategy. Moreover, the biological significance of the discovery of in vivo functional small molecules with different biological contexts is also interrogated at a metabolic perspective.

Using DNA as a drug : challenges and opportunities for process engineers

The maturing of the biotechnology industry and a focus on productivity has seen a shift from discovery science to small-scale bench-top research to higher productivity, large scale production. Health companies are aggressively expanding their biopharmaceutical interests, an expansion which is facilitated by biochemical and bioprocess engineering. An area of continuous growth is vaccines. Vaccination will be a key intervention in the case of an influenza pandemic. The global manufacturing capacity for fast turn around vaccines is currently woefully inadequate at around 300 million shots. As the prevention of epidemics requires > 80 % vaccination, in theory the world should currently be aiming for the ability to produce around 5.3 billion vaccines. Presented is a production method for the creation of a fast turn around DNA vaccine. A DNA vaccine could have a production time scale of as little as two weeks. This process has been harnessed into a pilot scale production system for the creation of a pre-clinical grade malaria vaccine in a collaborative project with the Coppel Lab, Department of Microbiology, Monash University. In particular, improvements to the fermentation, chromatography and delivery stages will be discussed. Consideration will then be given as to how the fermentation stage affects the mid and downstream processing stages.

Discovery of candidate serum proteomic and metabolomic biomarkers in ankylosing spondylitis

Ankylosing Spondylitis (AS) is a common inflammatory rheumatic disease with a predilection for the axial skeleton, affecting 0.2% of the population. Current diagnostic criteria rely on a composite of clinical and radiological changes, with a mean time to diagnosis of 5 to 10 years. In this study we employed nano liquid-chromatography mass spectrometry analysis to detect and quantify proteins and small compounds including endogenous peptides and metabolites in serum from 18 AS patients and nine healthy individuals. We identified a total of 316 proteins in serum, of which 22 showed significant up- or down-regulation (p < 0.05) in AS patients. Receiver operating characteristic analysis of combined levels of serum amyloid P component and inter-α-trypsin inhibitor heavy chain 1 revealed high diagnostic value for Ankylosing Spondylitis (area under the curve = 0.98). We also depleted individual sera of proteins to analyze endogenous peptides and metabolic compounds. We detected more than 7000 molecular features in patients and healthy individuals. Quantitative MS analysis revealed compound profiles that correlate with the clinical assessment of disease activity. One molecular feature identified as a Vitamin D3 metabolite-(23S,25R)-25-hydroxyvitamin D3 26,23-peroxylactone-was down-regulated in AS. The ratio of this vitamin D metabolite versus vitamin D binding protein serum levels was also altered in AS as compared with controls. These changes may contribute to pathological skeletal changes in AS. Our study is the first example of an integration of proteomic and metabolomic techniques to find new biomarker candidates for the diagnosis of Ankylosing Spondylitis

Computer-Aided Drug Design of Pyranopyrazoles and Related Compounds for Checkpoint Kinase-1

Checkpoint-1 kinase plays an important role in the G(2)M cell cycle control, therefore its inhibition by small molecules is of great therapeutic interest in oncology. In this paper, we have reported the virtual screening of an in-house library of 2499 pyranopyrazole derivatives against the ATP-binding site of Chk1 kinase using Glide 5.0 program, which resulted in six hits. All these ligands were docked into the site forming most crucial interactions with Cys87, Glu91 and Leu15 residues. From the observed results these ligands are suggested to be potent inhibitors of Chk1 kinase with sufficient scope for further elaboration.