Results 261 to 270 of about 27,194 (296)

Diving for drugs: tunicate anticancer compounds

Drug Discovery Today, 2012
The marine biosphere boasts tremendous biodiversity replete with structurally unique, active and selective secondary metabolites. Bioprospecting for antitumor compounds has been rewarding, and tunicates have been especially successful in yielding prospective cancer therapies.
Edwin L, Cooper, David, Yao
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Defining and characterizing drug/compound function

Biochemical Pharmacology, 2014
The receptor concept, now more than century old, remains the core concept in understanding the mechanisms of disease causality and drug action. Originally formulated in the early 1900s, receptor theory has evolved in both detail and complexity as the tools of molecular biology and increasingly sophisticated research technologies have facilitated the ...
Terry, Kenakin, Michael, Williams
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Compound Immobilization and Drug-Affinity Chromatography

2011
Bioactive small molecules act through modulating a yet unpredictable number of targets. It is therefore of critical importance to define the cellular target proteins of a compound as an entry point to understanding its mechanism of action. Often, this can be achieved in a direct fashion by chemical proteomics.
Uwe, Rix, Manuela, Gridling, Giulio, Superti-Furga   +2 more
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Cyclodepsipeptides - Potential Drugs and Lead Compounds in the Drug Development Process

Current Medicinal Chemistry, 2009
Cyclodepsipeptides show an interesting spectrum of biological activity. Members of this new class of potential drugs may also serve as lead compounds for more pharmacologically potent and toxicologically safe derivatives. Some of these natural products and (semi-)synthetic derivatives have already been evaluated in clinical trials.
Lemmens, Rosa, Kamyar, Majid-Reza, Dornetshuber-Fleiss, Rita   +2 more
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Prediction of the Corneal Permeability of Drug-Like Compounds

Pharmaceutical Research, 2010
To develop a computational model for optimisation of low corneal permeability, which is a key feature in ocular drug development.We have used multivariate analysis to build corneal permeability models based on a structurally diverse set of 58 drug-like compounds.According to the models, the most important parameters for permeability are logD at ...
Kidron, Heidi, Vellonen, Kati Sisko, Del Amo, Eva M., Tissari, Anita, Urtti, Arto   +4 more
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Natural Compounds as Drugs

2008
Activation of fungal silent gene clusters: A new avenue to drug discovery.- Total synthesis studies on macrocyclic pipecolic acid natural products: FK506, the antascomicins and rapamycin.- Application of natural product-inspired diversity-oriented synthesis to drug discovery.- Cheminformatics analysis of natural products: Lessons from nature inspiring ...
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Using Ensembles to Classify Compounds for Drug Discovery.

ChemInform, 2003
This paper introduces Signal, a novel method for classifying activity against a small molecule drug target. Signal creates an ensemble, or collection, of meaningful descriptors chosen from a much larger property space. The method works with a variety of descriptor types, including fingerprints that represent four-point pharmacophores or shape ...
J. Kevin Lanctôt, Santosh Putta, Christian Lemmen, Jonathan Greene   +3 more
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Compounding Intrathecal Drugs

2009
Publisher Summary This chapter focuses on various issues related to the compounding of intrathecal drugs. For the majority of practitioners who use intrathecal drugs for chronic pain management, compounding represents the only mechanism to obtain the drugs and drug combinations necessary for some of their patients.
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Comments on Drugs Difficult to Compound and the Quality of Chemicals to Be Used in Compounding

Drug Development and Industrial Pharmacy, 1999
These comments are minor modifications to the material submitted by the author to the docket for the FDA Pharmacy Compounding Committee that met on October 15 and 16, 1998.
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Compound Data Mining for Drug Discovery

2016
In recent years, there has been unprecedented growth in compound activity data in the public domain. These compound data provide an indispensable resource for drug discovery in academic environments as well as in the pharmaceutical industry. To handle large volumes of heterogeneous and complex compound data and extract discovery-relevant knowledge from
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