Identification of Serine 119 as an Effective Inhibitor Binding Site of M. tuberculosis Ubiquitin-like Protein Ligase PafA Using Purified Proteins and M. smegmatis.

Owing to the spread of multidrug resistance (MDR) and extensive drug resistance (XDR), there is a pressing need to identify potential targets for the development of more-effective anti-M. tuberculosis (Mtb) drugs. PafA, as the sole Prokaryotic Ubiquitin-like Protein ligase in the Pup-proteasome System (PPS) of Mtb, is an attractive drug target. Here, we show that the activity of purified Mtb PafA is significantly inhibited upon the association of AEBSF (4-(2-aminoethyl) benzenesulfonyl fluoride) to PafA residue Serine 119 (S119). Mutation of S119 to amino acids that resemble AEBSF has similar inhibitory effects on the activity of purified Mtb PafA. Structural analysis reveals that although S119 is distant from the PafA catalytic site, it is located at a critical position in the groove where PafA binds the C-terminal region of Pup. Phenotypic studies demonstrate that S119 plays critical roles in the function of Mtb PafA when tested in M. smegmatis. Our study suggests that targeting S119 is a promising direction for developing an inhibitor of M. tuberculosis PafA.

3D-QSAR studies on tripeptide aldehyde inhibitors of proteasome using CoMFA and CoMSIA methods.

The ubiquitin-proteasome pathway plays a crucial role in the regulation of many physiological processes and in the development of a number of major human diseases, such as cancer, Alzheimer's, Parkinson's, diabetes, etc. As a new target, the study on the proteasome inhibitors has received much attention recently. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using comparative molecule field analysis (CoMFA) and comparative molecule similarity indices analysis (CoMSIA) techniques were applied to analyze the binding affinity of a set of tripeptide aldehyde inhibitors of 20S proteasome. The optimal CoMFA and CoMSIA models obtained for the training set were all statistically significant with cross-validated coefficients (q(2)) of 0.615, 0.591 and conventional coefficients (r(2)) of 0.901, 0.894, respectively. These models were validated by a test set of eight molecules that were not included in the training set. The predicted correlation coefficients (r(2)) of CoMFA and CoMSIA are 0.944 and 0.861, respectively. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of beta5 subunit of 20S proteasome, which suggests that the 3D-QSAR models built in this paper can be used to guide the development of novel inhibitors of 20S proteasome.