Computational Method for Drug Target Search and Application in Drug Discovery

Chen, Yu Zong; Li, Zerong; Ung, Choong Yong

doi:10.1142/s0219633602000166

Cited by 6 publications

(4 citation statements)

References 45 publications

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“…[26][27][28] Thus the ligand-protein docking method can be readily extended to identify protein targets of MP ingredients as well as synthetic chemicals based on structural and molecular mechanical analysis of the binding between this molecule and its potential target proteins. 29 So far, an extended ligandprotein docking method, INVDOCK, has been specifically used for automated drug target identification of several MP ingredients 30 and synthetic compounds. 31…”

Section: In Silico Methods For Identification Of Mp Ingredientsmentioning

confidence: 99%

Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?

2003

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Medicinal plants have been explored therapeutically in traditional medicines and are a valuable source for drug discovery. Insufficient knowledge about the molecular mechanism of these medicinal plants limits the scope of their application and hinders the effort to design new drugs using the therapeutic principles of herbal medicines. This problem can be partially alleviated if efficient methods for rapid identification of protein targets of herbal ingredients can be introduced. Efforts have been directed at developing efficient computer methods for facilitating target identification. Various methods being explored or under investigation are reviewed here. So far, one computer method, INVDOCK, has been specifically used for automated drug target identification. Its usefulness in the identification of therapeutic targets of medicinal herbal ingredients as well as synthetic chemicals is reviewed. The majority of INVDOCK identified therapeutic targets of several well-known medicinal herbal ingredients have been found to be confirmed or implicated by experiments, which suggests the potential of in silico methods in facilitating the study of molecular mechanism of medicinal plants.

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Section: In Silico Methods For Identification Of Mp Ingredientsmentioning

confidence: 99%

Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?

2003

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“…Entre las ventajas y posibles aplicaciones del método de acoplamiento inverso dirigidas al descubrimiento de fármacos, existen varias contribuciones importantes, incluyendo la detección de blancos terapéuticos desconocidos, la identificación de blancos potenciales responsables de la toxicidad y/o efectos secundarios de un medicamento, así como la exploración de mecanismos moleculares de compuestos bioactivos a base de plantas, en particular aquellas provenientes de las medicinas tradicionales (Mandal et al, 2010;tang et al, 2006;Chen & Ung, 2002).…”

Section: Acoplamiento Inverso Proteína-ligandounclassified

“…En la actualidad hay varios servidores y softwares utilizados para el acoplamiento inverso, tales como INVDOCK (Chen & Ung, 2002), EM-Dique 3 (harriman et al, 2007), y Tar-FisDock (li et al, 2006), entre otros.…”

Section: Acoplamiento Inverso Proteína-ligandounclassified

Acoplamiento Inverso Y Mapeo De Farmacóforo Como Herramientas Para Encontrar Nuevos Blancos Farmacológicos De Compuestos Naturales

Maldonado rojas,

Noguera Oviedo,

Olivero Verbel

2023

Rev. Acad. Colomb. Cienc. Ex. Fis. Nat.

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El resurgimiento de los productos naturales en el ámbito de descubrimiento de fármacos tiene su base en la introducción de nuevos enfoques, tecnologías y metodologías, incluyendo el diseño de moléculas bioactivas asistido por ordenador. Los servidores TarFisDock y PharmMapper son herramientas computacionales empleadas para la búsqueda de potenciales blancos farmacológicos para ligandos orgánicos. Este trabajo muestra un ejemplo de aplicación de estos servidores. Los resultados obtenidos sugirieron que moléculas de origen natural, tales como la ascididemina (Didemnum sp. Tunicado), el peyssonol B (Peyssonnelia sp), el ácido asiático (Centella asiatica) y el ácido docosahexaenoico (aceite de pescado), tienen como blancos la dihidroorotato deshidrogenasa, la mieloperoxidasa, el receptor beta del ácido retinoico, y la aldosa reductasa, respectivamente.Estas proteínas han sido relacionadas con diversas enfermedades y ofrecen una explicación teórica de algunosde los efectos benéficos reportados para las moléculas evaluadas

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“…aspirin), which is an objective of drug repositioning strategy. Lack of this knowledge holds back the efforts to completely explore the novel mechanism of these therapeutic agents in the design of new drugs (Chen et al, 2003). Because the molecular mechanism and clinical pharmacology are known for only a relatively small number of medicinal herbs (Gupta and Jasrai, 2005), the efforts required to initiate a new drug discovery program for herbal medicines will be enormous, while an alternative approach like inverse docking can be effectively utilized to reduce the target list.…”

Section: Introductionmentioning

confidence: 99%

Compound prioritization from inverse docking experiment using receptor‐centric and ligand‐centric methods: a case study on Plasmodium falciparum Fab enzymes

Kumar

Pandya

Desai

et al. 2014

J of Molecular Recognition

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Prioritization of compounds using inverse docking approach is limited owing to potential drawbacks in its scoring functions. Classically, molecules ranked by best or lowest binding energies and clustering methods have been considered as probable hits. Mining probable hits from an inverse docking approach is very complicated given the closely related protein targets and the chemically similar ligand data set. To overcome this problem, we present here a computational approach using receptor-centric and ligand-centric methods to infer the reliability of the inverse docking approach and to recognize probable hits. This knowledge-driven approach takes advantage of experimentally identified inhibitors against a particular protein target of interest to delineate shape and molecular field properties and use a multilayer perceptron model to predict the biological activity of the test molecules. The approach was validated using flavone derivatives possessing inhibitory activities against principal antimalarial molecular targets of fatty acid biosynthetic pathway, FabG, FabI and FabZ, respectively. We propose that probable hits can be retrieved by comparing the rank list of docking, quantitative-structure activity relationship and multilayer perceptron models.

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Computational Method for Drug Target Search and Application in Drug Discovery

Cited by 6 publications

References 45 publications

Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?

Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?

Acoplamiento Inverso Y Mapeo De Farmacóforo Como Herramientas Para Encontrar Nuevos Blancos Farmacológicos De Compuestos Naturales

Compound prioritization from inverse docking experiment using receptor‐centric and ligand‐centric methods: a case study on Plasmodium falciparum Fab enzymes

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