Current Drug Discovery Technologies - Volume 1, Issue 3, 2004

Oxazolomycin, first isolated in 1985, is a novel bioactive compound, exhibiting potent antiviral, antibacterial and cytotoxic activity, and is now known to be the parent of a wider class of compounds. The broad-spectrum activity of oxazolomycin has been attributed to its protonophoric properties. This review outlines the isolation, structural determination, biosynthesis, bioactivity, biological mode of action and synthesis of all members of this compound class. Significantly, the oxazolomycins appear to offer not only a completely novel chemotype as a bioactive lead structure, but also a chemotype, which also exhibits an unusual biological mode of action.

Primary high-throughput screening of commercially available small molecules collections often results in hit compounds with unfavorable ADME / Tox properties and low IP potential. These issues are addressed empirically at follow-up lead development and optimization stages. In this work, we describe a rational approach to the optimization of hit compounds discovered during screening of a kinase focused library against abl tyrosine kinase. The optimization strategy involved application of modern chemoinformatics techniques, such as automatic bioisosteric transformation of the initial hits, efficient solution-phase combinatorial synthesis, and advanced methods of knowledge-based libraries design.

In-house pharmaceutical collections are no longer sufficient for sampling chemical spaces. As novel bioactive chemotypes are successfully identified by virtual and high -throughput screening, the ability to rapidly sift through large numbers of chemicals prior to acquisition or experiment is required. Strategies for compound selection include some of the following steps: 1.) database assembly ('in silico' inventory); 2a.) structural integrity verification (keep unique structures only); 2b.) limited exploration of alternative chemical representations for the uniques (stereoisomers, tautomers, ionization states); 3.) property and structural filtering (remove unwanted structures); 4.) 3D-structure generation (for virtual screening or 3D-based similarity); 5a.) clustering or statistical design for selection; 5b.) similarity-based selection (if bioactives are known); 5c.) receptor-based selection (if target binding site is known); 6.) add a random subset to the final list.

The gold standards for the measurement of glomerular filtration rate (GFR) are inulin clearance and radioisotopic methods. However, creatinine clearance is the most used test to evaluate GFR in clinical practice. Its adequacy is questionable, since its repeatability is quite poor, mainly due to errors in the collection of urine. The aim of this study was to evaluate a new method to predict GFR from the body cell mass (BCM) and plasma creatinine (Pcr), avoiding urine collection. The values of BCM were obtained in 275 adult renal patients with different renal function, ranging from normality to advanced renal failure. The relationship of GFR (clearance of 99mTc-DTPA) with BCM and Pcr was calculated in the first 85 patients. A highly significant linear correlation was found between GFR and the ratio BCM / Pcr. Thereafter, GFR was predicted from BCM and Pcr (BCM GFR) with formulas derived from the relationships found between GFR and the ratio BCM / Pcr. For comparison, GFR was predicted also according to other prediction formulas: Cockcroft and Gault (CG GFR), and the simplified MDRD formula (MDRD GFR). BCM GFR gave a more precise estimate of GFR than CG GFR and MDRD GFR. In fact, BCM GFR had the best correlation and agreement with true GFR (99mTc-DTPA). Furthermore, CG GFR and MDRD GFR markedly overestimated true GFR. Finally, the error of prediction of BCM GFR was definitely lower than that of the two other estimates of GFR. GFR can be predicted from BCM and plasma creatinine. This method, which is very simple and accurate, seems suitable to establish the adequate dosage of drugs cleared by the kidneys.

The proliferation of new peptides and proteins requiring characterisation is a direct result of recent advances in genomics and proteomics, but protein aggregation is particular problem in the biotechnology industry, where aggregation is encountered throughout the lifetime of a therapeutic protein, including during refolding, purification, sterilization, shipping, and storage process. To ensure that it meets quality standards, the size, molecular weight and / or molecular weight distribution, and aggregate state must be accurately determined. Traditional analytical methods for determining molecular weight include size-exclusion chromatography (SEC), gel electrophoresis, analytical ultracentrifugation and time-of-flight mass spectrometry. These technologies are time-consuming (some take days), provide data based on relative standards, or cannot characterise very high molecular weight aggregates. Laser light-scattering (LS) detection coupled with SEC system have been used for over a decade to determine the size and molecular weight of bio-molecules such as proteins, peptides, polysaccharides, oligonucleotides, and antibodies, the method of choice being for molar mass determinations and the study of self-association and heterogeneous interaction under native, equilibrium conditions in solution. The purpose of the current review is to describe and discuss the capability of the SEC / LS system to determine absolute molecular weight of proteins and their complexes and the association state of the conjugate, either with itself or with protein receptor / ligands. For this, the “two or three detector” methods, each with its advantages and limitations, can be used to calculate the molecular weight of a simple protein or glycoprotein, and the stoichiometry of their complexes. Also, some alternative techniques for determining the molecular weight are discussed in this review. Applications of all these methodologies are described.