Human serum albumin binding

Hollosy, F., Valko, K., Hersey, A., Nunhuck, S., Keri, G., Bevan, C. Estimation of volume of distribution in humans from high throughput HPLC-based measurements of human serum albumin binding and immobilized artificial membrane partitioning. J. Med. Chem. 2006, 49, 6958-6971. 

This section will provide an overview on ADME models from our group to illustrate our approach for building predictive models on structurally diverse training sets. Datasets for intestinal human absorption and human serum albumin binding are discussed, while models for other relevant ADME properties have also been obtained. Those models, however, do not stand alone but are used in combination with those models tailored for affinity and selectivity in the frame of multidimensional lead optimization. 

Fig. 14.7 Correlation ofVolSurf descriptors with human serum albumin binding affinity. Two submodels indicate their predictive ability to external test sets. Ten compounds were removed by either experimental design on PCA scores (A) or literature proposals (B). Model A 0.558,...

In 2007, Wichmann et al. [47] applied several COSMO-RS cr-moments as descriptors to model PPB. Unlike the above-mentioned PPB models, which predicted %PPB directly, Wichmann et al. built up a QSAR model to predict human serum albumin binding, log Kt SA (logarithm of %bound/%free), instead. The performance of the log K isa model was reasonable given only four... 

Wichmann, K., Diedenhofen, M., Klamt, A. Prediction of blood-brain partitioning and human serum albumin binding based on COSMO-RS sigma-moments. J. Chem. Inf. Model. 2007, 47,... 

Y Ding, X Zhu, B Lin. Capillary electrophoresis study of human serum albumin binding to basic drugs. Chromatographia 49 343-346, 1999. 

Gunturi, S.B., Narayanan, R. and Khandelwal, A. (2006) In silico ADME modelling 2 Computational models to predict human serum albumin binding affinity using ant colony systems. Bioorganic and Medicinal Chemistry, 14, 4118 129. 

Erostell-Karlsson, A., Remaeus, A., Roos, H., Andersson, K, Borg, P., Hiimalainen, M. and Karlsson, R. (2000) Biosensor analysis of the interaction between immobilized human serum albumin and drug compounds for prediction of human serum albumin binding levels. Journal of Medicinal Chemistry, 43, 1986-1992. 

Correlating 3D Structure to Human Serum Albumin Binding... 

Fig. 6. Correlation of VolSurf descriptors with human serum albumin binding affinity for 93 drug-like molecules. Left. Predicted versus experimental -log(K(HSA)) from the final 6 component PLS model. Right PLS loadings showing the importance of VolSurf descriptors to the prediction of human serum albumin binding.

B. Subfile and N. Thuaud, Determination of tryptophan-human serum albumin binding from retention data and separation of tryptophan enantiomers by high-performance liquid chromatography, J. Litj. Chromatogr., 3 299 (1980). 

General regression neural network (GRNN) was introduced by Donald Specht in 1991 [33], and it has been successfully used in pharmacokinetic studies, including human intestinal absorption [34], blood-brain barrier prediction [35], human serum albumin binding [35], milk-plasma ratio [35], and drug clearance [36], Recently it has been applied for the prediction of Tetrahymenapyriformis toxicity [37],... 

Estimation of voliune of distribution in humans from high-throughput HPLC-based measiuements of human serum albumin binding and immobilised artificial membrane partitioning. Journal of Medicinal Chemistry, 49, 6958-6971. 

Correlation ranking and stepwise regression procedures in principal components artificial neural networks modeling with application to predict toxic activity and human serum albumin binding affinity... 

Artali, R., Bombieri, G Calabi, L. and Del Pra, A. (2005) A molecular dynamics study of human serum albumin binding sites. IL Farmaco, 60,485-495. 

Gu,C. Nikolic,D. Lai,J. Xu,X. VanBreemen,R.B. Assays of ligand-human serum albumin binding using pulsed ultrafiltration and liquid chromatography-mass spectrometry. Comb. Chem. High Throughput Screen. 1999,2, 353-359. 

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