Results 151 to 160 of about 1,944,029 (193)

Drug-like Index:  A New Approach To Measure Drug-like Compounds and Their Diversity

Journal of Chemical Information and Computer Sciences, 2000
Combinatorial organic synthesis (combinatorial chemistry or CC) and ultrahigh-throughput screening (UHTS) are speeding up drug discovery by increasing capacity for making and screening large numbers of compounds. However, a key problem is to select the smaller set of "representative" compounds from a virtual library to make or screen.
Jun Xu, James Stevenson
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Definition of Drug-Likeness for Compound Affinity

Journal of Chemical Information and Modeling, 2011
We proposed a new definition of drug-likeness based on protein-compound docking simulation. Active and decoy compounds of 40 target proteins were investigated. These compounds were docked to protein sets consisting of 53-160 proteins. The protein sets did not include the target proteins.
Yoshifumi Fukunishi, Haruki Nakamura
openaire   +3 more sources

Drug-Likeness Analysis of Traditional Chinese Medicines: Prediction of Drug-Likeness Using Machine Learning Approaches

Molecular Pharmaceutics, 2012
Quantitative or qualitative characterization of the drug-like features of known drugs may help medicinal and computational chemists to select higher quality drug leads from a huge pool of compounds and to improve the efficiency of drug design pipelines. For this purpose, the theoretical models for drug-likeness to discriminate between drug-like and non-
Tingjun Hou, Youyong Li, Junmei Wang
exaly   +3 more sources

Recognizing molecules with drug-like properties

Current Opinion in Chemical Biology, 1999
A variety of successful approaches to the problem of recognizing 'drug-like' molecules have been employed. These range from simple counting schemes such as the Lipinski 'rule of five' to the analysis of the multidimensional 'chemistry space' occupied by drugs, to neural network learning systems.
W P, Walters, , Ajay, M A, Murcko
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Selection Criteria for Drug‐Like Compounds

ChemInform, 2003
AbstractFor Abstract see ChemInform Abstract in Full Text.
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Computational methods for the prediction of ‘drug-likeness’

Drug Discovery Today, 2000
Recently, one of the key trends in the pharmaceutical industry has been the integration of what have traditionally been considered 'development' activities into the early phases of drug discovery. The aim of this paradigm shift is the prompt identification and elimination of candidate molecules that are unlikely to survive later stages of discovery and
, Clark, , Pickett
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Assessing drug-likeness – what are we missing?

Drug Discovery Today, 2008
The concept of drug-likeness helps to optimise pharmacokinetic and pharmaceutical properties, for example, solubility, chemical stability, bioavailability and distribution profile. A number of molecular descriptors have emerged as reasonably informative and predictive, for example, the Rule-of-Five. Here, we review some current approaches, then discuss
G. Vistoli, A. Pedretti, B. Testa
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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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Model-Free Drug-Likeness from Fragments

Journal of Chemical Information and Modeling, 2010
We developed a drug-likeness filter (DLF), starting from molecular fragments and molecular weight (MW), a key property relevant in drug design. The molecular fragments were selected from extended connectivity atom environments based on their occurrence ratio in our collection of drugs and "nondrugs".
Oleg Ursu, Tudor I. Oprea
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Predicting Drug-Likeness: Why and How ?

Current Topics in Medicinal Chemistry, 2002
There exists a huge attrition rate of molecules in clinical trials. It was expected that high-throughput screening and combinatorial chemistry would make the task of producing drugs easier. However, the efforts of the past decade have not been an unvarnished success.
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