Discovery of new Mycobacterium tuberculosis proteasome inhibitors using a knowledge-based computational screening approach

Computational Insight into Substrate-Induced Conformational Changes in Methionyl-tRNA Synthetase of Mycobacterium Tuberculosis

Tuberculosis caused by Mycobacterium tuberculosis (M.tb) has killed millions worldwide. Antibiotic resistance leads to the ineffectiveness of the current therapies. Aminoacyl tRNA synthetase (aaRS) class of proteins involved in protein synthesis are promising bacterial targets for developing new therapies. Here, we carried out a systematic comparative study on the aaRS sequences from M.tb and human. We listed important M.tb aaRS that could be explored as potential M.tb targets alongside the detailed conformational space analysis of methionyl-tRNA synthetase (MetRS) in apo- and substrate-bound form, which is among the proposed targets. Understanding the conformational dynamics is central to the mechanistic understanding of MetRS, as the substrate binding leads to the conformational changes causing the reaction to proceed. We performed the most complete simulation study of M.tb MetRS for 6 microseconds (2 systems × 3 runs × 1 microsecond) in the apo and substrate-bound states. Interestingly, we observed differential features, showing comparatively large dynamics for the holo simulations, whereas the apo structures became slightly compact with reduced solvent exposed area. In contrast, the ligand size decreased significantly in holo structures possibly to relax ligand conformation. Our findings correlate with experimental studies, thus validating our protocol. Adenosine monophosphate moiety of the substrate exhibited quite higher fluctuations than the methionine. His21 and Lys54 were found to be the important residues forming prominent hydrogen bond and salt-bridge interactions with the ligand. The ligand-protein affinity decreased during simulations as computed by MMGBSA analysis over the last 500 ns trajectories, which indicates the conformational changes upon ligand binding. These differential features could be further explored for designing new M.tb inhibitors.

Identification of New Mycobacterium tuberculosis Proteasome Inhibitors Using a Knowledge-Based Computational Screening Approach

Mycobacterium tuberculosis (Mtb) is a deadly tuberculosis (TB)-causing pathogen. The proteasome is vital to the survival of Mtb and is therefore validated as a potential target for anti-TB therapy. Mtb resistance to existing antibacterial agents has enhanced drastically, becoming a worldwide health issue. Therefore, new potential therapeutic agents need to be developed that can overcome the complications of TB. With this purpose, in the present study, 224,205 natural compounds from the ZINC database have been screened against the catalytic site of Mtb proteasome by the computational approach. The best scoring hits, ZINC3875469, ZINC4076131, and ZINC1883067, demonstrated robust interaction with Mtb proteasome with binding energy values of −7.19, −7.95, and −7.21 kcal/mol for the monomer (K-chain) and −8.05, −9.10, and −7.07 kcal/mol for the dimer (both K and L chains) of the beta subunit, which is relatively higher than that of reference compound HT1171 (−5.83 kcal/mol (monomer) and −5.97 kcal/mol (dimer)). In-depth molecular docking of top-scoring compounds with Mtb proteasome reveals that amino acid residues Thr1, Arg19, Ser20, Thr21, Gln22, Gly23, Asn24, Lys33, Gly47, Asp124, Ala126, Trp129, and Ala180 are crucial in binding. Furthermore, a molecular dynamics study showed steady-state interaction of hit compounds with Mtb proteasome. Computational prediction of physicochemical property assessment showed that these hits are non-toxic and possess good drug-likeness properties. This study proposed that these compounds could be utilized as potential inhibitors of Mtb proteasome to combat TB infection. However, there is a need for further bench work experiments for their validation as inhibitors of Mtb proteasome.

Predictive Power of In Silico Approach to Evaluate Chemicals against M. tuberculosis: A Systematic Review

Mycobacterium tuberculosis (Mtb) is an endemic bacterium worldwide that causes tuberculosis (TB) and involves long-term treatment that is not always effective. In this context, several studies are trying to develop and evaluate new substances active against Mtb. In silico techniques are often used to predict the effects on some known target. We used a systematic approach to find and evaluate manuscripts that applied an in silico technique to find antimycobacterial molecules and tried to prove its predictive potential by testing them in vitro or in vivo. After searching three different databases and applying exclusion criteria, we were able to retrieve 46 documents. We found that they all follow a similar screening procedure, but few studies exploited equal targets, exploring the interaction of multiple ligands to 29 distinct enzymes. The following in vitro/vivo analysis showed that, although the virtual assays were able to decrease the number of molecules tested, saving time and money, virtual screening procedures still need to develop the correlation to more favorable in vitro outcomes. We find that the in silico approach has a good predictive power for in vitro results, but call for more studies to evaluate its clinical predictive possibilities.

Advancement of the 5-Amino-1-(Carbamoylmethyl)-1H-1,2,3-Triazole-4-Carboxamide Scaffold to Disarm the Bacterial SOS Response

Many antibiotics, either directly or indirectly, cause DNA damage thereby activating the bacterial DNA damage (SOS) response. SOS activation results in expression of genes involved in DNA repair and mutagenesis, and the regulation of the SOS response relies on two key proteins, LexA and RecA. Genetic studies have indicated that inactivating the regulatory proteins of this response sensitizes bacteria to antibiotics and slows the appearance of resistance. However, advancement of small molecule inhibitors of the SOS response has lagged, despite their clear promise in addressing the threat of antibiotic resistance. Previously, we had addressed this deficit by performing a high throughput screen of ∼1.8 million compounds that monitored for inhibition of RecA-mediated auto-proteolysis of Escherichia coli LexA, the reaction that initiates the SOS response. In this report, the refinement of the 5-amino-1-(carbamoylmethyl)-1H-1,2,3-triazole-4-carboxamide scaffold identified in the screen is detailed. After development of a modular synthesis, a survey of key activity determinants led to the identification of an analog with improved potency and increased breadth, targeting auto-proteolysis of LexA from both E. coli and Pseudomonas aeruginosa. Comparison of the structure of this compound to those of others in the series suggests structural features that may be required for activity and cross-species breadth. In addition, the feasibility of small molecule modulation of the SOS response was demonstrated in vivo by the suppression of the appearance of resistance. These structure activity relationships thus represent an important step toward producing Drugs that Inhibit SOS Activation to Repress Mechanisms Enabling Resistance (DISARMERs).

A structural-chemical explanation of fungal laccase activity

Fungal laccases (EC 1.10.3.2) are multi-copper oxidases that oxidize a wide variety of substrates. Despite extensive studies, the molecular basis for their diverse activity is unclear. Notably, there is no current way to rationally predict the activity of a laccase toward a given substrate. Such knowledge would greatly facilitate the rational design of new laccases for technological purposes. We report a study of three datasets of experimental K_m values and activities for Trametes versicolor and Cerrena unicolor laccase, using a range of protein modeling techniques. We identify diverse binding modes of the various substrates and confirm an important role of Asp-206 and His-458 (T. versicolor laccase numbering) in guiding substrate recognition. Importantly, we demonstrate that experimental K_m values correlate with binding affinities computed by MMGBSA. This confirms the common assumption that the protein-substrate affinity is a major contributor to observed K_m. From quantitative structure-activity relations (QSAR) we identify physicochemical properties that correlate with observed K_m and activities. In particular, the ionization potential, shape, and binding affinity of the substrate largely determine the enzyme’s K_m for the particular substrate. Our results suggest that K_m is not just a binding constant but also contains features of the enzymatic activity. In addition, we identify QSAR models with only a few descriptors showing that phenolic substrates employ optimal hydrophobic packing to reach the T1 site, but then require additional electronic properties to engage in the subsequent electron transfer. Our results advance our ability to model laccase activity and lend promise to future rational optimization of laccases toward phenolic substrates.

Anti-tubercular drug discovery: in silico implications and challenges

Tuberculosis (TB) has been reported as a major public health concern, especially in the developing countries. WHO report on tuberculosis 2016 shows a high mortality rate caused by TB leading to 1.8 million deaths worldwide (including deaths due to TB in HIV positive individuals), which is one of the top 10 causes of mortality in 2015. However, the main therapy used for the treatment of TB is still the Direct Observed Therapy Short-course (DOTS) that consists of four main first-line drugs. Due to the prolonged and unorganized use of these drugs, Mycobacterium tuberculosis (Mtb) has developed drug-resistance against them. To overcome this drug-resistance, efforts are continuously being made to develop new therapeutics. New drug-targets of Mtb are pursued by the researchers to develop their inhibitors. For this, new methodologies that comprise of the computational drug designing techniques are vigorously applied. A major limitation that is found with these techniques is the inability of the newly identified target-based inhibitors to inhibit the whole cell bacteria. A foremost factor for this limitation is the inability of these inhibitors to penetrate the bacterial cell wall. In this regard, various strategies to overcome this limitation have been discussed in detail in this review, along with new targets and new methodologies. A bunch of in silico tools available for the prediction of physicochemical properties that need to be explored to deal with the permeability issue of the Mtb inhibitors has also been discussed.

Targeting proteasomes in infectious organisms to combat disease

Proteasomes are multisubunit, energy-dependent, proteolytic complexes that play an essential role in intracellular protein turnover. They are present in eukaryotes, archaea, and in some actinobacteria species. Inhibition of proteasome activity has emerged as a powerful strategy for anticancer therapy and three drugs have been approved for treatment of multiple myeloma. These compounds react covalently with a threonine residue located in the active site of a proteasome subunit to block protein degradation. Proteasomes in pathogenic organisms such as Mycobacterium tuberculosis and Plasmodium falciparum also have a nucleophilic threonine residue in the proteasome active site and are therefore sensitive to these anticancer drugs. This review summarizes efforts to validate the proteasome in pathogenic organisms as a therapeutic target. We describe several strategies that have been used to develop inhibitors with increased potency and selectivity for the pathogen proteasome relative to the human proteasome. In addition, we highlight a cell-based chemical screening approach that identified a potent, allosteric inhibitor of proteasomes found in Leishmania and Trypanosoma species. Finally, we discuss the development of proteasome inhibitors as anti-infective agents.