Desenvolvimento de novos medicamentos para doenças negligenciadas: uma análise bibliométrica / New drug development for neglected diseases: a bibliometric analysis / Desarrollo de nuevos fármacos para enfermedades desatendidas: un análisis bibliométrico

Doenças negligenciadas impõem um fardo humano, social e econômico devastador a mais de um bilhão de pessoas em todo o mundo. Embora existam ferramentas para controlar e até mesmo eliminar muitas dessas doenças, novos produtos terapêuticos precisam urgentemente ser desenvolvidos. Este artigo se baseia em um estudo que buscou quantificar e caracterizar a produção científica global sobre desenvolvimento de novos medicamentos para doenças negligenciadas, por meio de uma análise bibliométrica. De modo a investigar a pesquisa relacionada ao desenvolvimento de novos medicamentos para as doenças negligenciadas em âmbito global na última década, foi utilizada a base de dados Scopus. Observou-se aumento da produção de conhecimento sobre o tema, com relevante participação de autores, instituições e financiamento brasileiros, sobretudo de instituições públicas. Contudo, os esforços realizados têm sido insuficientes, sendo necessária a implementação de estratégias futuras de pesquisa e de financiamento que propiciem maior produção científica e uma tradução da pesquisa básica para a prática clínica.

Neglected diseases impose a devastating human, social, and economic burden on more than one billion people worldwide. While tools exist to control and even eliminate many of these diseases, new therapeutic products urgently need to be developed. This article is based on a study that sought to quantify and characterize the global scientific production on new drug development for neglected diseases through a bibliometric analysis. The Scopus database was used to investigate the research related to the development of new drugs for neglected diseases globally in the last decade. An increase in the production of knowledge about the theme and the relevant participation of Brazilian authors, institutions and funding, especially from public institutions were observed. However, their efforts have been insufficient, and the implementation of future research and funding strategies that provide greater scientific production and a translation of basic research into clinical practice is necessary.

Las enfermedades desatendidas imponen una carga humana, social y económica devastadora a más de mil millones de personas en todo el mundo. A pesar de haber herramientas para controlar y incluso eliminar muchas de estas enfermedades, es necesario desarrollar con urgencia nuevos productos terapéuticos. Este artículo se basa en un estudio lo cual ha buscado cuantificar y caracterizar la producción científica global sobre el desarrollo de nuevos fármacos para enfermedades desatendidas, a través de un análisis bibliométrico. Para inspeccionar investigaciones relacionadas con el desarrollo de nuevos medicamentos para enfermedades desatendidas en ámbito mundial durante la última década se utilizó la base de datos Scopus. Hubo un aumento de la producción de conocimiento sobre el tema, con una participación relevante de autores, instituciones y financiamiento brasileños, especialmente de instituciones públicas. Sin embargo, los esfuerzos realizados siguen siendo insuficientes, requiriendo la implementación de futuras estrategias de investigación y financiamiento que propicien una mayor producción científica y una traducción de la investigación básica a la práctica clínica.

Application of computational methods for anticancer drug discovery, design, and optimization / Aplicación de métodos computacionales para el descubrimiento, diseño y optimización de fármacos contra el cáncer

Abstract: Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.

Resumen: El desarrollo de un nuevo fármaco es un proceso complejo y arriesgado que requiere una enorme cantidad de tiempo y dinero. Se estima que el proceso estándar para producir un nuevo fármaco, desde su descubrimiento hasta que acaba en el mercado, puede tardar hasta 15 años y tener un costo de mil millones de dólares (USD). Por fortuna, este escenario ha cambiado recientemente con la llegada de nuevas tecnologías y metodologías. Entre ellas, los métodos computacionales se han convertido en un componente determinante en muchos programas de descubrimiento de fármacos. En un esfuerzo por incrementar las posibilidades de encontrar nuevas moléculas con potencial farmacológico, se utilizan técnicas como el cribado virtual de quimiotecas construidas con base en ligandos o estructuras para la identificación de hits y hasta para la optimización de compuestos líder. En lo que respecta al diseño y descubrimiento de nuevos candidatos a fármacos contra el cáncer, estos enfoques tienen, a la fecha, un impacto importante y aportan nuevas posibilidades terapéuticas. En este artículo se revisa el concepto del diseño racional de moléculas con potencial farmacológico, ilustrando los principios clave con algunos de los ejemplos más representativos y exitosos de moléculas identificadas mediante estas aproximaciones. Se incluyen casos desarrollados en el campo del diseño de fármacos contra el cáncer con la finalidad de mostrar cómo, con la ayuda del diseño asistido por computadora, se pueden generar nuevos fármacos que den esperanza a millones de pacientes.

New perspectives on the computational characterization of the kinetics of binding-unbinding in drug design: implications for novel therapies / Nuevas perspectivas sobre la caracterización computacional de la cinética de unión-desunión en el diseño de fármacos: implicaciones para terapias de vanguardia

Abstract: The efficiency and the propensity of a drug to be bound to its target protein have been inseparable concepts for decades now. The correlation between the pharmacological activity and the binding affinity has been the first rule to design and optimize a new drug rationally. However, this argument does not prove to be infallible when the results of in vivo assays have to be confronted. Only recently, we understand that other magnitudes as the kinetic rates of binding and unbinding, or the mean residence time of the complex drug-protein, are equally relevant to draw a more accurate model of the mechanism of action of a drug. It is in this scenario where new computational techniques to simulate the all-atom dynamics of the biomolecular system find its valuable place on the challenge of designing new molecules for more effective and less toxic therapies.

Resumen: La eficiencia de un fármaco se ha relacionado habitualmente con su constante de afinidad, magnitud que puede ser medida experimentalmente in vitro y que cuantifica la propensión mostrada por la molécula ligando para interaccionar con su proteína diana. Este modo de entender el mecanismo de acción ha guiado durante años el desarrollo de nuevas moléculas con potencial farmacológico. Sin embargo, dicho modelo o criterio no es infalible cuando se confronta con los resultados de ensayos in vivo. Otras magnitudes, como las constantes cinéticas de asociación o disociación o el tiempo de residencia del ligando acoplado a su proteína diana, demuestran ser igualmente necesarias para comprender y predecir la capacidad farmacológica del compuesto químico. En este nuevo escenario, con ayuda de las técnicas computacionales de simulación molecular, la correcta caracterización del proceso dinámico de unión y desunión del ligando y receptor resulta imprescindible para poder diseñar racionalmente nuevas moléculas que permitan terapias más eficaces y menos tóxicas.

New perspectives on the computational characterization of the kinetics of binding-unbinding in drug design: implications for novel therapies.

The efficiency and the propensity of a drug to be bound to its target protein have been inseparable concepts for decades now. The correlation between the pharmacological activity and the binding affinity has been the first rule to design and optimize a new drug rationally. However, this argument does not prove to be infallible when the results of in vivo assays have to be confronted. Only recently, we understand that other magnitudes as the kinetic rates of binding and unbinding, or the mean residence time of the complex drug-protein, are equally relevant to draw a more accurate model of the mechanism of action of a drug. It is in this scenario where new computational techniques to simulate the all-atom dynamics of the biomolecular system find its valuable place on the challenge of designing new molecules for more effective and less toxic therapies.

Application of computational methods for anticancer drug discovery, design, and optimization.

Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.