Development of Inhibitors of SAICAR Synthetase (PurC) from Mycobacterium abscessus Using a Fragment-Based Approach

Mycobacterium abscessus (Mab) has emerged as a challenging threat to individuals with cystic fibrosis. Infections caused by this pathogen are often impossible to treat due to the intrinsic antibiotic resistance leading to lung malfunction and eventually death. Therefore, there is an urgent need to develop new drugs against novel targets in Mab to overcome drug resistance and subsequent treatment failure. In this study, SAICAR synthetase (PurC) from Mab was identified as a promising target for novel antibiotics. An in-house fragment library screen and a high-throughput X-ray crystallographic screen of diverse fragment libraries were explored to provide crucial starting points for fragment elaboration. A series of compounds developed from fragment growing and merging strategies, guided by crystallographic information and careful hit-to-lead optimization, have achieved potent nanomolar binding affinity against the enzyme. Some compounds also show a promising inhibitory effect against Mab and Mtb. This work utilizes a fragment-based design and demonstrates for the first time the potential to develop inhibitors against PurC from Mab.

Discovery of Novel Inhibitors of Uridine Diphosphate-N-Acetylenolpyruvylglucosamine Reductase (MurB) from Pseudomonas aeruginosa, an Opportunistic Infectious Agent Causing Death in Cystic Fibrosis Patients

Pseudomonas aeruginosa is of major concern for cystic fibrosis patients where this infection can be fatal. With the emergence of drug-resistant strains, there is an urgent need to develop novel antibiotics against P. aeruginosa. MurB is a promising target for novel antibiotic development as it is involved in the cell wall biosynthesis. MurB has been shown to be essential in P. aeruginosa, and importantly, no MurB homologue exists in eukaryotic cells. A fragment-based drug discovery approach was used to target Pa MurB. This led to the identification of a number of fragments, which were shown to bind to MurB. One fragment, a phenylpyrazole scaffold, was shown by ITC to bind with an affinity of K_d = 2.88 mM (LE 0.23). Using a structure guided approach, different substitutions were synthesized and the initial fragment was optimized to obtain a small molecule with K_d = 3.57 μM (LE 0.35).

Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae

Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps.