The increasing availability of genomic data for pathogens that cause tropical diseases has created new opportunities for drug discovery and development. However, if the potential of such data is to be fully exploited, the data must be effectively integrated and be easy to interrogate. Here, we discuss the development of the TDRtargets.org database (http://tdrtargets.org), which encompasses extensive genetic, biochemical and pharmacological data related to tropical disease pathogens, as well as computationally predicted druggability for potential targets and compound desirability information. By allowing the integration and weighting of this information, this database aims to facilitate the identification and prioritisation of candidate drug targets for pathogens.

We have identified a novel cDNA encoding a protein (named TX) with > 50% overall sequence identity with the interleukin‐1 beta converting enzyme (ICE) and approximately 30% sequence identity with the ICE homologs NEDD‐2/ICH‐1L and CED‐3. A computer homology model of TX was constructed based on the X‐ray coordinates of the ICE crystal recently published. This model suggests that TX is a cysteine protease, with the P1 aspartic acid substrate specificity retained. Transfection experiments demonstrate that TX is a protease which is able to cleave itself and the p30 ICE precursor, but not to generate mature IL‐1 beta from pro‐IL‐1 beta. In addition, this protein induces apoptosis in transfected COS cells. TX therefore delineates a new member of the growing Ice/ced‐3 gene family coding for proteases with cytokine processing activity or involved in programmed cell death.

Using small, flat aromatic rings as components of fragments or molecules is a common practice in fragment-based drug discovery and lead optimization. With an increasing focus on the exploration of novel biological and chemical space, and their improved synthetic accessibility, 3D fragments are attracting increasing interest. This study presents a detailed analysis of 3D and 2D ring fragments in marketed drugs. Several measures of properties were used, such as the type of ring assemblies and molecular shapes. The study also took into account the relationship between protein classes targeted by each ring fragment, providing target-specific information. The analysis shows the high structural and shape diversity of 3D ring systems and their importance in bioactive compounds. Major differences in 2D and 3D fragments are apparent in ligands that bind to the major drug targets such as GPCRs, ion channels, and enzymes.

A @-bulge is a region of irregularity in a &sheet involving two @-strands. It usually involves two or more residues in the bulged strand opposite to a single residue on the adjacent strand. These irregularities in 0-sheets were iden- A set of 182 protein chains (170 proteins) was used, and a total of 362 bulges were extracted. Five types of @-bulges were found: classic, G1, wide, bent, and special. Their characteristic amino acid preferences were found for most classes of bulges.Basically, bulges occur frequently in proteins; on average there are more than two bulges per protein. In general, @-bulges produce two main changes in the structure of a @-sheet: (1) disrupt the normal alternation of side-chain direction; (2) accentuate the twist of the sheet, altering the direction of the surrounding strands.