Monitoring Modulators of Platelet Aggregation in a Microtitre Plate Assay

Moran N, Kiernan A, Dunne E, Edwards RJ, Shields DC & Kenny D (2006): Monitoring Modulators of Platelet Aggregation in a Microtitre Plate Assay. Anal. Biochem. 357(1):77-84.

Abstract

Platelets play a central role in maintaining biological hemostasis. Inappropriate platelet activation is responsible for thrombotic diseases such as myocardial infarction and stroke. Therefore, novel agents that can inhibit platelet activation are necessary. However, assays that monitor platelet aggregation are generally time-consuming and require high volumes of blood and specialized equipment. Therefore, a medium- to high-throughput assay that can monitor platelet aggregation would be considered useful. Such an assay should be sensitive, comparable to the “gold standard” assay of platelet aggregometry, and able to monitor multiple samples simultaneously but with low assay volumes. We have developed such a microtiter assay. It can assay an average of 60 independent treatments per 60 ml blood donation and demonstrates greater sensitivity than the current gold standard assay, namely platelet aggregation in stirring conditions in a platelet aggregometer. The microtiter plate (MTP) assay can detect known inhibitors of platelet function such as indomethacin, aspirin, and ReoPro. It is highly reproducible when using standard doses of agonists such as thrombin receptor-activating peptide (20 microM) and collagen (0.19 mg/ml). Finally, the MTP assay is rapid and sensitive and can detect unknown platelet-modulating agents from a library of compounds.

PMID: 16920064

Absolute Net Charge and the Biological Activity of Oligopeptides

Parthasarathi L, Devocelle M, Søndergaard C, Baran I, O’Dushlaine C, Davey NE, Edwards RJ, Moran N, Kenny D & Shields DC (2006): Absolute Net Charge and the Biological Activity of Oligopeptides. J. Chem. Inf. Model. 46(5):2183-2190.

Abstract

Sequences of human proteins are frequently prepared as synthetic oligopeptides to assess their functional ability to act as compounds modulating pathways involving the parent protein. Our objective was to analyze a set of oligopeptides, to determine if their solubility or activity correlated with features of their primary sequence, or with features of properties inferred from three-dimensional structural models derived by conformational searches. We generated a conformational database for a set of 78 oligopeptides, derived from human proteins, and correlated their 3D structures with solubility and biological assay activity (as measured by platelet activation and inhibition). Parameters of these conformers (frequency of coil, frequency of turns, the degree of packing, and the energy) did not correlate with solubility, which was instead partly predicted by two measures obtained from primary sequence analysis, that is, the hydrophobic moment and the number of charges. The platelet activity of peptides was correlated with a parameter derived from the structural modeling; this was the second virial coefficient (a measure of the tendency for a structure to autoaggregate). This could be explained by an excess among the active peptides of those which had either a large number of positive charges or in some cases a large number of negative charges, with a corresponding deficit of peptides with a mixture of negative and positive charges. We subsequently determined that a panel of 523 commercially available (and biologically active) peptides shared this elevation of absolute net charge: there were significantly lower frequencies of peptides of mixed charges compared to expectations. We conclude that the design of biologically active peptides should consider favoring those with a higher absolute net charge.

PMID: 16995748

SLiMDisc: short, linear motif discovery, correcting for common evolutionary descent

Davey NE, Shields DC & Edwards RJ (2006): SLiMDisc: short, linear motif discovery, correcting for common evolutionary descent. Nucleic Acids Res. 34(12):3546-54.

Abstract

Many important interactions of proteins are facilitated by short, linear motifs (SLiMs) within a protein’s primary sequence. Our aim was to establish robust methods for discovering putative functional motifs. The strongest evidence for such motifs is obtained when the same motifs occur in unrelated proteins, evolving by convergence. In practise, searches for such motifs are often swamped by motifs shared in related proteins that are identical by descent. Prediction of motifs among sets of biologically related proteins, including those both with and without detectable similarity, were made using the TEIRESIAS algorithm. The number of motif occurrences arising through common evolutionary descent were normalized based on treatment of BLAST local alignments. Motifs were ranked according to a score derived from the product of the normalized number of occurrences and the information content. The method was shown to significantly outperform methods that do not discount evolutionary relatedness, when applied to known SLiMs from a subset of the eukaryotic linear motif (ELM) database. An implementation of Multiple Spanning Tree weighting outperformed two other weighting schemes, in a variety of settings.

PMID: 16855291