Compound Optimization in Early and Late Phase Drug Discovery: Acceptable Pharmacokinetic Properties Utilizing Combined Physicochemical, In Vitro and In Vivo Screens

Caldwell, Gary W.

doi:10.2174/1567204043396677

Cited by 9 publications

(10 citation statements)

References 25 publications

(33 reference statements)

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“…2) or channel, the influence of molecular bulkiness should not be obvious. When the size of a molecule is larger than a threshold, the influence of molecular bulkiness begins to go into effect.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

ADME Evaluation in Drug Discovery. 3. Modeling Blood-Brain Barrier Partitioning Using Simple Molecular Descriptors

Hou

2003

J. Chem. Inf. Comput. Sci.

112

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In this paper, QSPR models were developed for in vivo blood-brain partitioning data (logBB) of a large data set consisting of 115 diverse organic compounds. The best model is based on three descriptors: n-octanol/ water partition coefficient calculated using the SLOGP approach, logP; high-charged polar surface areas based on the Gasteiger partial charges, HCPSA, and the excessive molecular weight larger than 360, MW 360 . The model bears good statistical significance, n ) 78, r ) 0.88, q ) 0.86, s ) 0.36, F ) 81.5. The actual prediction potential of the model was validated through two external validation sets of 37 diverse compounds. The predicted results demonstrate that the model bears better prediction potential than many other models and can be used for logBB estimations for drug and drug-like molecules. Comparison of several logP calculation approaches suggests that logP calculated by SLOGP can be used as a significant descriptor for the prediction of molecular transport properties because SLOGP gives the most similar results with CLOGP. The QSPR model indicates that larger polar surface areas have a more negative contribution to logBB, but the absolute partial charges on the atoms surrounded by the polar surfaces should be larger than 0.10|e|. Meanwhile, tight junction membranes limit the size of hydrophilic molecules that can cross the membrane with a molecular weight of approximately 360, because when a molecule's weight is larger than 360 it shows a negative contribution to logBB. The computations of molecular surface, partial charges, logP, and logBB have been accomplished using a program called Drug-BB. Moreover, to improve the efficiency of the computations of logP, we made an extensive reparametrization of SLOGP, and the newly developed SLOGP model is only based on simple atomic addition. Further, we developed a set of parameters to calculate the topological polar surface area (TPSA), thus the high-charged topological polar surface area (HCTPSA) could be estimated from the 2D connection information of a molecule. Adopting the new strategies, the estimations of logP, HCTPSA, and logBB are only based on the topological structure of a molecule and therefore, can be used for fast screening of virtual libraries having millions of molecules.

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Section: Resultsmentioning

confidence: 99%

“…It has been estimated that about 50% of such failures are caused by ADME/Tox deficiencies. 2 Apparently developing effective computational models to screen ADME properties is very promising as an early screen for potential drug candidates and for the design of combinatorial libraries.…”

Section: Introductionmentioning

confidence: 99%

ADME Evaluation in Drug Discovery. 3. Modeling Blood-Brain Barrier Partitioning Using Simple Molecular Descriptors

Hou

2003

J. Chem. Inf. Comput. Sci.

112

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“…26,27 Screening for ADME properties of new chemical entities, and in particular, identifying compounds that are potent CYP3A4 inhibitors, is now a widely accepted part of the modern drug discovery process that is commonly employed by the pharmaceutical industry at different stages of drug discovery and development. 28,29 At the same time, the ability to identify compounds that are potent inducers of CYP3A4 activity remains less investigated, partially due to the lack of mature technology.…”

Section: Discussionmentioning

confidence: 99%

A simultaneous assessment of CYP3A4 metabolism and induction in the DPX-2 cell line

Trubetskoy¹,

Marks²,

Zielinski³

et al. 2005

AAPS J

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The DPX-2 cell line, a derivative of HepG2 cells, harbors human PXR and a luciferase-linked CYP3A4 promoter. These cells were used in a panel of cell-based assays for a parallel assessment of CYP3A4 induction, metabolism, and inhibition at the cellular level. CYP3A4 induction in the DPX-2 cell line by various agents was monitored in 96-well plates by a luciferase-based transcriptional activation assay. Of the prototypical CYP3A4 inducers examined, all exhibited elevated luciferase activity in DPX-2 cells. CYP3A4 enzyme activity in noninduced and rifampicin-induced DPX-2 cells was also assessed using Vivid fluorogenic substrates. Significantly elevated CYP3A4 activity levels (2.8-fold ± 0.2-fold above DMSO-treated cells) were found in DPX-2 cells after 48 hours of exposure to rifampicin, but were undetectable in parental HepG2 cells. Rifampicin-induced activity levels were found to be suitable for assessing the inhibitory potential of new chemical entities in downstream CYP3A4 inhibition assays. The elevated CYP3A4 activity was inhibited 85% by 10 µM ketoconazole. In addition, a cytotoxicity assay to correct for possible toxic effects of compounds at the cellular level was applied. The comparative data obtained with a combination of the above assays suggests that the application of several independent in vitro technologies used in DPX-2 cells is the best possible strategy for the assessment of the complex phenomena of CYP3A4 induction and inhibition.

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“…It is believed that over 50% of the candidates failed due to ADME/Tox deficiencies during development. 1,2 To avoid this failure at the development stage, a set of in vitro ADME screens has been implemented in many pharmaceutical companies with the aim of discarding compounds in early stage of drug discovery process. Even though the early stage in vitro ADME reduces the probability of the failure at the development stage, it is still time-consuming and resourceintensive.…”

Section: Introductionmentioning

confidence: 99%

ADME Evaluation in Drug Discovery. 5. Correlation of Caco-2 Permeation with Simple Molecular Properties

Hou

Zhang

Xia

et al. 2004

J. Chem. Inf. Comput. Sci.

173

153

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The correlations between Caco-2 permeability (logP app ) and molecular properties have been investigated. A training set of 77 structurally diverse organic molecules was used to construct significant QSAR models for Caco-2 cell permeation. Cellular permeation was found to depend primarily upon experimental distribution coefficient (logD) at pH ) 7.4, high charged polar surface area (HCPSA), and radius of gyration (rgyr). Among these three descriptors, logD may have the largest impact on diffusion through Caco-2 cell because logD shows obvious linear correlation with logP app (r)0.703) when logD is smaller than 2.0. High polar surface area will be unfavorable to achieve good Caco-2 permeability because higher polar surface area will introduce stronger H-bonding interactions between Caco-2 cells and drugs. The comparison among HCPSA, PSA (polar surface area), and TPSA (topological polar surface area) implies that high-charged atoms may be more important to the interactions between Caco-2 cell and drugs. Besides logD and HCPSA, rgyr is also closely connected with Caco-2 permeabilities. The molecules with larger rgyr are more difficult to cross Caco-2 monolayers than those with smaller rgyr. The descriptors included in the prediction models permit the interpretation in structural terms of the passive permeability process, evidencing the main role of lipholiphicity, H-bonding, and bulk properties. Besides these three molecular descriptors, the influence of other molecular descriptors was also investigated. From the calculated results, it can be found that introducing descriptors concerned with molecular flexibility can improve the linear correlation. The resulting model with four descriptors bears good statistical significance, n ) 77, r ) 0.82, q ) 0.79, s ) 0.45, F ) 35.7. The actual predictive abilities of the QSAR model were validated through an external validation test set of 23 diverse compounds. The predictions for the tested compounds are as the same accuracy as the compounds of the training set and significantly better than those predicted by using the model reported. The good predictive ability suggests that the proposed model may be a good tool for fast screening of logP app for compound libraries or large sets of new chemical entities via combinatorial chemistry synthesis.

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Compound Optimization in Early and Late Phase Drug Discovery: Acceptable Pharmacokinetic Properties Utilizing Combined Physicochemical, In Vitro and In Vivo Screens

Cited by 9 publications

References 25 publications

ADME Evaluation in Drug Discovery. 3. Modeling Blood-Brain Barrier Partitioning Using Simple Molecular Descriptors

ADME Evaluation in Drug Discovery. 3. Modeling Blood-Brain Barrier Partitioning Using Simple Molecular Descriptors

A simultaneous assessment of CYP3A4 metabolism and induction in the DPX-2 cell line

ADME Evaluation in Drug Discovery. 5. Correlation of Caco-2 Permeation with Simple Molecular Properties

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