Dynamic and multi-pharmacophore modeling for designing polo-box domain inhibitors.

The polo-like kinase 1 (Plk1) is a critical regulator of cell division that is overexpressed in many types of tumors. Thus, a strategy in the treatment of cancer has been to target the kinase activity (ATPase domain) or substrate-binding domain (Polo-box Domain, PBD) of Plk1. However, only few synthetic small molecules have been identified that target the Plk1-PBD. Here, we have applied an integrative approach that combines pharmacophore modeling, molecular docking, virtual screening, and in vitro testing to discover novel Plk1-PBD inhibitors. Nine Plk1-PBD crystal structures were used to generate structure-based hypotheses. A common pharmacophore model (Hypo1) composed of five chemical features was selected from the 9 structure-based hypotheses and used for virtual screening of a drug-like database consisting of 159,757 compounds to identify novel Plk1-PBD inhibitors. The virtual screening technique revealed 9,327 compounds with a maximum fit value of 3 or greater, which were selected and subjected to molecular docking analyses. This approach yielded 93 compounds that made good interactions with critical residues within the Plk1-PBD active site. The testing of these 93 compounds in vitro for their ability to inhibit the Plk1-PBD, showed that many of these compounds had Plk1-PBD inhibitory activity and that compound Chemistry_28272 was the most potent Plk1-PBD inhibitor. Thus Chemistry_28272 and the other top compounds are novel Plk1-PBD inhibitors and could be used for the development of cancer therapeutics

E3 Ubiquitin Ligases in Cancer and Their Pharmacological Targeting

Ubiquitination plays many critical roles in protein function and regulation. Consequently, mutation and aberrant expression of E3 ubiquitin ligases can drive cancer progression. Identifying key ligase-substrate relationships is crucial to understanding the molecular basis and pathways behind cancer and toward identifying novel targets for cancer therapeutics. Here, we review the importance of E3 ligases in the regulating the hallmarks of cancer, discuss some of the key and novel E3 ubiquitin ligases that drive tumor formation and angiogenesis, and review the clinical development of inhibitors that antagonize their function. We conclude with perspectives on the field and future directions toward understanding ubiquitination and cancer progression

Chemical Similarity Networks for Drug Discovery

Chemical similarity networks are an emerging area of interest in medicinal chemistry, chemical biology, and systems chemoinformatics that are currently being applied to drug target prediction, drug repurposing, and drug discovery in the new paradigm of poly-pharmacology and systems biology. In this chapter, we discuss the network-based drug target identification and discovery framework called chemical similarity network analysis pull-down (CSNAP) and its applications. We highlight the utility of CSNAP in identifying novel antimitotic drugs and their targets through practical case studies

Políticas alternativas para el Perú en la década 1980

El propósito de este ensayo es evaluar la tasa y dirección del crecimiento económico que se conseguiría bajo dos tipos de estrategias alternativas para la economía del Perú, bajo la presente estructura socioeconómica. Los cálculos se referirán a la evolución de la estructura del producto, inversión, y comercio para la década de 1980. Estos cálculos requerirán el uso de un modelo económico, con el cual se calculará los resultados numéricos de políticas alternativas sobre variables económicas concretas tales como producción, inversión, exportaciones e importaciones para los diferentes sectores de la economía peruana

Quantitative Methods in System-Based Drug Discovery

Modern pharmaceutical industries have faced significant challenges to deliver safe and effective medicines because of significant toxicity and severe side effects of discovered drugs. On the other hand, recent developments and advances in system-based pharmacology aim to address these challenges. In this chapter, we provide an overview of quantitative methods for system-based drug discovery. System-based drug discovery integrates chemical, molecular, and systematic information and applies this knowledge to the designing of small molecules with controlled toxicity and minimized side effects. First, we discuss current approaches for drug discovery and outline their advantages and disadvantages. Next, we introduce basic concepts of systems pharmacology with an emphasis on ligand-based drug discovery and target identification. This is followed by a discussion on structure-based drug design and statistical tools for pharmaceutical research. Finally, we provide an overview of future directions in systems pharmacology that will guide further developments

Computer-Aided Biosensor Design

Amperometric biosensors are widely used in point-of-care medical devices that help patients control blood glucose and cholesterol levels in an effective and convenient way. On the other hand, computer-aided technologies for biosensor design remain an actively developing field. In this chapter, we present a computational model for biosensor design that uses a reaction-diffusion equation. We have successfully applied this model to simulate cholesterol analysis based on a multienzyme system. Furthermore, we show that this computer-aided approach can be used to optimize biosensor performance. This model can be applied to industry-grade biosensor development and can be easily extended to model multiple types of biosensors for a wide array of clinical applications

Diets containing sea cucumber (Isostichopus badionotus) meals are hypocholesterolemic in young rats

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