There is emergence of multidrug-resistant Salmonella enterica serotype typhi in pandemic proportions throughout the world, and therefore, there is a necessity to speed up the discovery of novel molecules having different modes of action and also less influenced by the resistance formation that would be used as drug for the treatment of salmonellosis particularly typhoid fever. The PhoP regulon is well studied and has now been shown to be a critical regulator of number of gene expressions which are required for intracellular survival of S. enterica and pathophysiology of disease like typhoid. The evident roles of two-component PhoP-/PhoQ-regulated products in salmonella virulence have motivated attempts to target them therapeutically. Although the discovery process of biologically active compounds for the treatment of typhoid relies on hit-finding procedure, using high-throughput screening technology alone is very expensive, as well as time consuming when performed on large scales. With the recent advancement in combinatorial chemistry and contemporary technique for compounds synthesis, there are more and more compounds available which give ample growth of diverse compound library, but the time and endeavor required to screen these unfocused massive and diverse library have been slightly reduced in the past years. Hence, there is demand to improve the high-quality hits and success rate for high-throughput screening that required focused and biased compound library toward the particular target. Therefore, we still need an advantageous and expedient method to prioritize the molecules that will be utilized for biological screens, which saves time and is also inexpensive. In this concept, in silico methods like machine learning are widely applicable technique used to build computational model for high-throughput virtual screens to prioritize molecules for advance study. Furthermore, in computational analysis, we extended our study to identify the common enriched structural entities among the biologically active compound toward finding out the privileged scaffold.
Streptococcus pyogenes ST4547 is an opacity factor negative strain, which has been recently reported as a new emm type from Malaysia. Nucleotide sequencing of the mga regulon of this strain showed the existence of two emm-like genes. The emm gene located upstream of the scpA gene comprises 1305 nucleotides encoding the putative precursor M protein of 435 amino acids in length with an M(r) of 49 kDa. or a predicted mature protein of 394 amino acids with an M(r) of 44.8 kDa. Another gene mrpST4547 was located upstream of the emm gene and downstream of the mga gene. The sequence of this mrp gene comprises 1167 nucleotides encoding a predicted protein of 388 amino acids in length with an M(r) of 42.2 kDa. or a predicted mature protein of 347 amino acids with an M(r) of 37.9 kDa. The mga regulon of strain ST4547 has a mosaic structure comprising segments, which originated from different OF positive and OF negative strains. The sequences flanking the hyper-variable and C repeats of the emmST4547 gene showed high similarity to corresponding regions in the mga regulon of OF positive strains notably M15, M4, M22 and M50. In contrast, the sequence within the hyper-variable and C repeat regions of the emmST4547 gene revealed high similarity to equivalent regions in the OF negative strains. These data indicates that horizontal transfer of emm-like gene could have occurred between OF positive and OF negative strains resulting in architectural divergence in the mga regulon.
Pseudomonads typically carry multiple non-identical alleles of the post-transcriptional regulator rsmA. In Pseudomonas aeruginosa, RsmN is notable in that its structural rearrangement confers distinct and overlapping functions with RsmA. However, little is known about the specificities of RsmN for its target RNAs and overall impact on the biology of this pathogen. We purified and mapped 503 transcripts directly bound by RsmN in P. aeruginosa. About 200 of the mRNAs identified encode proteins of demonstrated function including some determining acute and chronic virulence traits. For example, RsmN reduces biofilm development both directly and indirectly via multiple pathways, involving control of Pel exopolysaccharide biosynthesis and c-di-GMP levels. The RsmN targets identified are also shared with RsmA, although deletion of rsmN generally results in less pronounced phenotypes than those observed for ΔrsmA or ΔrsmArsmNind mutants, probably as a consequence of different binding affinities. Targets newly identified for the Rsm system include the small non-coding RNA CrcZ involved in carbon catabolite repression, for which differential binding of RsmN and RsmA to specific CrcZ regions is demonstrated. The results presented here provide new insights into the intricacy of riboregulatory networks involving multiple but distinct RsmA homologues.