Predicting Protein Binding Research Articles

Computational prediction of the plasma protein‐binding percent of diverse pharmaceutical compounds

A nonlinear regression analysis has been applied to develop a new method to predict the plasma protein‐binding percent of structurally diverse pharmaceutical compounds. The analysis included over 300 launched drugs with experimental human plasma protein binding percent data. These drugs were classified according to protonation state and pharmacophore features. The correlation formula for each class is a simple sigmoidal function of variable LogP or LogD. A correlation formula of variable LogD at pH 7.4 with a good correlation coefficient (R‐squared = 0.803) was obtained for neutral and basic drugs, with the exception of zwitterions. A correlation formula using LogP as variable for acidic drugs with one of the specific pharmacophore features gave a good correlation coefficient (R‐squared = 0.786). The method was verified using the protein binding data of 20 compounds that had not been included in the data set to configure the formulas. The correlation coefficient (R‐squared) between the experimental and predicted protein binding percents was 0.830. In conclusion, the method developed and described in this report can provide precise and useful prediction of plasma protein binding percent for new drug candidates. © 2004 Wiley‐Liss, Inc. and the American Pharmacists Association J Pharm Sci 93:1480–1494, 2004

Predicting Protein Binding Site Presence/Absence in SNP-Related Alleles by Accounting Gel Mobility Shift Assay

Predicting Protein Binding Site Presence/Absence in SNP-Related Alleles by Accounting Gel Mobility Shift Assay

Prediction of Protein Binding to DNA in the Presence of Water-Mediated Hydrogen Bonds

We extend our previous analysis of binding specificity of DNA-protein complexes to com- plexes containing water-mediated bridges. Inclusion of water bridges between phosphate and base, phosphate and sugar, as well as proteins and DNA, improves the prediction of specificity; six data sets studied in this paper yield correct predictions for all base pairs that have two or more hydrogen-bonds. Beside massive computation, our approach relies highly on experimental da ta. After deriving protein structures from DNA-protein complexes in which coordinates were established by X-ray diffraction techniques, we analysed all possible DNA sequences to which these proteins might bind, ranking them in terms of Lennard-Jones potential for the optimal docking configuration. Our prediction algorithm rests on the following assumptions: (1) specificity comes mainly from direct hydrogen bonding; (2) electrostatic forces stabilise DNA-protein complexes and contribute only weakly to specificity since they occur at the charged phosphate gr oups; (3) Van der Waals forces and electrostatic interactions between positively charged groups on the protein and phosphates on DNA can be neglected as they contribute primarily to the free energy of stabilisation as opposed to specificity.

Characteristics of ceftriaxone binding to immunoglobulin G and potential clinical significance

The interaction between immunoglobulin G (IgG) and ceftriaxone was studied. Using an ultrafiltration method, we performed dose ranging studies at a ceftriaxone concentration range of 1 to 720 micrograms/ml in the presence of various concentrations of human IgG, human serum albumin (HSA), and combinations of IgG and HSA at pH 7.4 and 37 degrees C. The results showed that ceftriaxone binding to IgG was nonlinear and was consistent with the presence of two binding sites that possess different binding capacities and affinities. Except for increased peak percent binding as the IgG concentration increased, the binding characteristics did not change with IgG concentration. Binding to HSA was consistent, with the presence of only one high-affinity binding site. A mathematical model based on the observed data was constructed; this model was used to predict protein binding at various concentrations of drug, IgG, HSA, or combinations of IgG and HSA in buffer and in plasma medium. Correlations between the observed versus the predicted values were excellent in both media. Simulations with the model indicated that patients with hypergammaglobulinemia have an increased potential of being exposed to prolonged subinhibitory concentrations of ceftriaxone if the drug is given once every 24 h.