Biomedical subjects

M Adenot

Publications and source records attributed to M Adenot.

4 recordsLinked to original sources

PubMed2007

Applications of a blood-brain barrier technology platform to predict CNS penetration of various chemotherapeutic agents. 1. Anti-infective drugs.

Except for a few well-documented CNS therapeutics, quantitative data on blood-brain barrier (BBB) permeation is incomplete, unreliable or nonexistent and this is a major impediment in BBB modeling. Furthermore, only the passive diffusion component is generally taken into account. Three techniques of modeling (in vivo, in vitro and in silico) were set up and compared. The in silico predicted permeation of 287 anti-infective drugs has been faced to clinical observations. Good correlations were observed between in vitro permeability coefficients, influx transfer coefficients from in vivo studies and Pe scores from the computational model. High Pe score values are associated with an increase of reported CNS side effects.

Animals↗

PubMed2007

Applications of a blood-brain barrier technology platform to predict CNS penetration of various chemotherapeutic agents. 2. Cationic peptide vectors for brain delivery.

BACKGROUND: SynB family peptides conjugated to several drugs have been shown to increase the brain uptake and in vivo activities of these drugs via an adsorptive-mediated transcytosis mechanism. Based on both in vivo and in vitro experimental data, a cell uptake component has been added to our computational model of blood-brain barrier. METHODS: In situ brain perfusion, in vitro cell model and a computational cell uptake model have been used to discover brain-penetrating properties of SynB peptides and to screen libraries of new rationally designed peptide vectors suitable for brain drug delivery. RESULTS AND CONCLUSION: Starting from small peptide vectors that enhance the brain transport coefficient, the BBB platform has made it possible to design libraries of peptide vectors with enhanced transport properties.

Amino Acid Sequence↗

PubMed2005

Peptide dynamic fingerprints: a tool for investigating the role of conformational flexibility for GLP-1 analogs affinity.

Glucagon-like peptide-1 (GLP-1) is a 30-residue peptide implicated in short-term appetite regulation. Its analogs are presumed to be potential drugs against obesity and non-insulin dependent diabetes mellitus (NIDDM or type 2 diabetes). This study examined how the dynamic fingerprints can be used for establishing dynamics-activity relationships in a series of peptides for which the mechanism of action is unknown and in which mutations can cause an increase or decrease in biological activity. The 3D autocorrelation method was used to generate maps of both active and inactive analogs. As the active conformation of GLP-1 is not yet clearly defined, the dynamic fingerprints of peptides in an aqueous environment were compared to explain the high affinity of the peptide for its receptor. The suggestion that the peptide could bind to the receptor in a folded conformation has been examined. In the case of the GLP-1 analogs, it was shown that the folding tendency cannot be directly related to affinity values and the results do not favor a folded active conformation model of GLP-1.

Animals↗

PubMedDate not supplied

Peptides quantitative structure-function relationships: an automated mutation strategy to design peptides and pseudopeptides from substitution matrices.

The process by which analogs in peptide chemistry are currently designed does not include any quantitative basis for amino acid substitutions from pharmacological leads. Here, we show that substitution matrices such as PAM 250 can provide quantitative constraints compatible with biological activity. This article describes its use in a strategy of rational amino acid substitution in peptides and proteins: we have computed a chemically derived matrix equivalent to the well-known PAM 250 matrix, reflecting the natural mutability rates of amino acids in protein evolutions but that can be extended to all the noncoded amino acids. Some of these noncoded amino acids are widely used to mimic secondary structure, to constrain backbone conformation, or to evade protease degradation. An automated sequence mutation (ASM) strategy has been defined to generate mutations within constraints. Application of such a substitution matrix to quantitative structure-function relationship studies will be of use in the design of proteins and peptides destined to become pharmaceutical drugs. In particular, issues such as which functionally conserved substitutions are able to satisfy conformational restrictions, oral bioavailability, or formulation demands can be quantitatively addressed.

Amino Acid Substitution↗