Treatment of dementia with neurotransmission modulation

The prevalence of dementia is growing in developed countries where elderly patients are increasing in numbers. Neurotransmission modulation is one approach to the treatment of dementia. Cholinergic precursors, anticholinesterases, nicotine receptor agonists and muscarinic M-2 receptor antagonists are agents that enhance cholinergic neurotransmission and that depend on having some intact cholinergic innervation to be effective in the treatment of dementia. The cholinergic precursor choline alfoscerate may be emerging as a potential useful drug in the treatment of dementia, with few adverse effects. Of the anticholinesterases, donepezil, in addition to having a similar efficacy to tacrine in mild-to-moderate Alzheimer's disease (AD), appears to have major advantages; its use is associated with lower drop-out rates in clinical trials, a lower incidence of cholinergic-like side effects and no liver toxicity. Rivastigmine is efficacious in the treatment in dementia with Lewy bodies, a condition in which the other anticholinesterases have not been tested extensively to date. Galantamine is an anticholinesterase and also acts as an allosteric potentiating modulator at nicotinic receptors to increase the release of acetylcholine. Pooled data from clinical trials of patients with mild-to-moderate AD suggest that the benefits and safety profile of galantamine are similar to those of the anticholinesterases. Selective nicotine receptor agonists are being developed that enhance cognitive performance without influencing autonomic and skeletal muscle function, but these have not yet entered clinical trial for dementia. Unlike the cholinergic enhancers, the M, receptor agonists do not depend upon intact cholinergic nerves but on intact M, receptors for their action, which are mainly preserved in AD and dementia with Lewy bodies. The M, receptor-selective agonists developed to date have shown limited efficacy in clinical trials and have a high incidence of side effects. A major recent advancement in the treatment of dementia is memantine, a non-competitive antagonist at NMDA receptors. Memantine is beneficial in the treatment of severe and moderate to-severe AD and may also be of some benefit in the treatment of mild-to-moderate vascular dementia. Drugs that modulate 5-HT, somatostatin and noradrenergic neurotransmission are also being considered for the treatment of dementia.

A safety catch linker for Fmoc-based assembly of constrained cyclic peptides

A new safety-catch linker for Fmoc solid-phase peptide synthesis of cyclic peptides is reported. The linear precursors were assembled on a tert-butyl protected catechol derivative using optimized conditions for Fmoc-removal. After activation of the linker using TFA, neutralization of the N-terminal amine induced cyclization with concomitant cleavage from the resin yielding the cyclic peptides in DMF solution. Several constrained cyclic peptides were synthesized in excellent yields and purities. Copyright (c) 2005 European Peptide Society and John Wiley & Sons, Ltd.

Topological side-chain classification of beta-turns: Ideal motifs for peptidomimetic development

beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi 2, psi 2, phi 3 and psi 3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C-alpha-C-beta vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C-alpha-C-beta vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

A gradient descent algorithm for minimizing amino acid coupling reactions when synthesizing cyclic-peptide libraries

Combinatorial chemistry has become an invaluable tool in medicinal chemistry for the identification of new drug leads. For example, libraries of predetermined sequences and head-to-tail cyclized peptides are routinely synthesized in our laboratory using the IRORI approach. Such libraries are used as molecular toolkits that enable the development of pharmacophores that define activity and specificity at receptor targets. These libraries can be quite large and difficult to handle, due to physical and chemical constraints imposed by their size. Therefore, smaller sub-libraries are often targeted for synthesis. The number of coupling reactions required can be greatly reduced if the peptides having common amino acids are grouped into the same sub-library (batching). This paper describes a schedule optimizer to minimize the number of coupling reactions by rotating and aligning sequences while simultaneously batching. The gradient descent method thereby reduces the number of coupling reactions required for synthesizing cyclic peptide libraries. We show that the algorithm results in a 75% reduction in the number of coupling reactions for a typical cyclic peptide library.

Carbohydrate-based scaffolds in drug discovery

Carbohydrates have been proven as valuable scaffolds to display pharmocophores and the resulting molecules have demonstrated useful biological activity towards various targets including the somatostatin receptors (SSTR), integrins, HIV-1 protease, matrix metalloproteinases (MMP), multidrug resistance-associated protein (MRP), and as RNA binders. Carbohydrate-based compounds have also shown antibacterial and herbicidal activity.