1.
[Hormone replacement therapy: toxicity of glycol ethers].
Timour, Q, Biggi-Bernard, U, Descotes, J
Journal de gynecologie, obstetrique et biologie de la reproduction. 2007;(1):62-7
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Abstract
Glycol ethers (GE) belong to two main series: series E, which include ethylene glycol ethers (EGE) and series P which include propylene glycol ethers (PGE). GE are widely used as solvents in a large number of industrial, household and cosmetic applications. EGE can be found in water paints, varnishes, inks, household products. Severe adverse effects have been noted with pharmaceutical formulations containing diethylene glycol monoethyl-ethers and this led to withdrawal from the French market. The toxicity of GE depends on the molecular weight and the metabolites generated. It can manifest following acute or chronic exposure by disorders of the nervous system, bone marrow, immune system, kidneys as well as fertility, reproduction and embryofetal development. Several EGE are mutagenic. The carcinogenic risk is not known. The most toxic derivatives EGME, EGMEA, EGEE and EGEEA alter male and female fertility, and induce malformations. Taking these toxic effects into consideration, what is the place of GE as absorption promoting agents? An example is DEGEE, which facilitates estradiol penetration when used as a gel in the treatment of estrogen deficiency. This review is intended to address this issue.
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Predicting peptide binding to MHC pockets via molecular modeling, implicit solvation, and global optimization.
Schafroth, HD, Floudas, CA
Proteins. 2004;(3):534-56
Abstract
Development of a computational prediction method based on molecular modeling, global optimization, and implicit solvation has produced accurate structure and relative binding affinity predictions for peptide amino acids binding to five pockets of the MHC molecule HLA-DRB1*0101. Because peptide binding to MHC molecules is essential to many immune responses, development of such a method for understanding and predicting the forces that drive binding is crucial for pharmaceutical design and disease treatment. Underlying the development of this prediction method are two hypotheses. The first is that pockets formed by the peptide binding groove of MHC molecules are independent, separating the prediction of peptide amino acids that bind within individual pockets from those that bind between pockets. The second hypothesis is that the native state of a system composed of an amino acid bound to a protein pocket corresponds to the system's lowest free energy. The prediction method developed from these hypotheses uses atomistic-level modeling, deterministic global optimization, and three methods of implicit solvation: solvent-accessible area, solvent-accessible volume, and Poisson-Boltzmann electrostatics. The method predicts relative binding affinities of peptide amino acids for pockets of HLA-DRB1*0101 by determining computationally an amino acid's global minimum energy conformation. Prediction results from the method are in agreement with X-ray crystallography data and experimental binding assays.