Computer-assisted rational design of immunosuppressive compounds.

We describe the rational design of immunosuppressive peptides without relying on information regarding their receptors or mechanisms of action. The design strategy uses a variety of topological and shape descriptors in combination with an analysis of molecular dynamics trajectories for the identification of potential drug candidates. This strategy was applied to the development of immunosuppressive peptides with enhanced potency. The lead compounds were peptides, derived from the heavy chain of HLA class I, that modulate immune responses in vitro and in vivo. In particular, a peptide derived from HLA-B2702, amino acids 75-84 (2702.75-84) prolonged skin and heart allograft survival in mice. The biological activity of the rationally designed peptides was tested in a heterotopic mouse heart allograft model. The molecule predicted to be most potent displayed an immunosuppressive activity approximately 100 times higher than the lead compound.

Functional diversity of compound libraries.

The ideal designed screening library should contain compounds with a variety of structural shapes and molecular properties, while avoiding redundancies. Other requirements involve the need to find structurally distinct leads and to recognise drug-like molecules. Functional diversity analysis is one way in which these objectives can be achieved. For this, molecular descriptions that relate to both structure and properties of molecules are needed, as well as their evaluation in terms of biological relevance.

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.

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.

Computational approaches in the post-genomic era - how will we cope?

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Molecular diversity and its analysis.

We have recently developed a novel strategy for the rational design of compounds. This 'in silico screening' approach is based on the design and screening of virtual combinatorial libraries. Screening is performed using defined rules derived from a comprehensive description of active and inactive molecules in a relevant learning set. This strategy allows the development of potential ligands without the necessity of any knowledge of the 3D-structure of the target receptor. Key to the success of such methods is the quality of the information being processed, in particular, the diversity of the data in the context of the molecular population in the libraries concerned. Here, we review the problem of data diversity, its definition and its analysis using a new software tool, named Diverser.