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

Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.

Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach

Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.

In vitro and in silico evaluations of actinomycin X2and actinomycin D as potent anti-tuberculosis agents

Background

Multidrug-resistant tuberculosis (MDR-TB) is one of the world's most devastating contagious diseases and is caused by the MDR-Mycobacterium tuberculosis (MDR-Mtb) bacteria. It is therefore essential to identify novel anti-TB drug candidates and target proteins to treat MDR-TB. Here, in vitro and in silico studies were used to investigate the anti-TB potential of two newly sourced actinomycins, actinomycin-X₂ (act-X₂) and actinomycin-D (act-D), from the Streptomyces smyrnaeus strain UKAQ_23 (isolated from the Jubail industrial city of Saudi Arabia).

Methods

The anti-TB activity of the isolated actinomycins was assessed in vitro using the Mtb H37Ra, Mycobacterium bovis (BCG), and Mtb H37Rv bacterial strains, using the Microplate Alamar Blue Assay (MABA) method. In silico molecular docking studies were conducted using sixteen anti-TB drug target proteins using the AutoDock Vina 1.1.2 tool. The molecular dynamics (MD) simulations for both actinomycins were then performed with the most suitable target proteins, using the GROningen MAchine For Chemical Simulations (GROMACS) simulation software (GROMACS 2020.4), with the Chemistry at HARvard Macromolecular Mechanics 36m (CHARMM36m) forcefield for proteins and the CHARMM General Force Field (CGenFF) for ligands.

Results

In vitro results for the Mtb H37Ra, BCG, and Mtb H37Rv strains showed that act-X₂ had minimum inhibitory concentration (MIC) values of 1.56 ± 0.0, 1.56 ± 0.0, and 2.64 ± 0.07 µg/mL and act-D had MIC values of 1.56 ± 0.0, 1.56 ± 0.0, and 1.80 ± 0.24 µg/mL respectively. The in silico molecular docking results showed that protein kinase PknB was the preferred target for both actinomycins, while KasA and pantothenate synthetase were the least preferred targets for act-X₂and act-D respectively. The molecular dynamics (MD) results demonstrated that act-X₂ and act-D remained stable inside the binding region of PknB throughout the simulation period. The MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) binding energy calculations showed that act-X₂ was more potent than act-D.

Conclusion

In conclusion, our results suggest that both actinomycins X₂ and D are highly potent anti-TB drug candidates. We show that act-X₂is better able to antagonistically interact with the protein kinase PknB target than act-D, and thus has more potential as a new anti-TB drug candidate.

In silico structure-based designers of therapeutic targets for diabetes mellitus or obesity: A protocol for systematic review

Obesity is a significant risk factor for several chronic non-communicable diseases, being closely related to Diabetes Mellitus. Computer modeling techniques favor the understanding of interaction mechanisms between specific targets and substances of interest, optimizing drug development. In this article, the protocol of two protocols of systematic reviews are described for identifying therapeutic targets and models for treating obesity or diabetes mellitus investigated in silico. The protocol is by the guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes Protocols (PRISMA-P) and was published in the International Prospective Register of Systematic Reviews database (PROSPERO: CRD42022353808). Search strategies will be developed based on the combination of descriptors and executed in the following databases: PubMed; ScienceDirect; Scopus; Web of Science; Virtual Health Library; EMBASE. Only original in silico studies with molecular dynamics, molecular docking, or both will be inserted. Two trained researchers will independently select the articles, extract the data, and assess the risk of bias. The quality will be assessed through an adapted version of the Strengthening the Reporting of Empirical Simulation Studies (STRESS) and the risk of bias using a checklist obtained from separate literature sources. The implementation of this protocol will result in the elaboration of two systematic reviews identifying the therapeutic targets for treating obesity (review 1) or diabetes mellitus (review 2) used in computer simulation studies and their models. The systematization of knowledge about these treatment targets and their in silico structures is fundamental, primarily because computer simulation contributes to more accurate planning of future either in vitro or in vivo studies. Therefore, the reviews developed from this protocol will guide decision-making regarding the choice of targets/models in future research focused on therapeutics of obesity or Diabetes Mellitus contributing to mitigate of factors such as costs, time, and necessity of in vitro and/or in vivo assays.

Discovery of novel DprE1 inhibitors via computational bioactivity fingerprints and structure-based virtual screening

Decaprenylphosphoryl-β-D-ribose oxidase (DprE1) plays important roles in the biosynthesis of mycobacterium cell wall. DprE1 inhibitors have shown great potentials in the development of new regimens for tuberculosis (TB) treatment. In this study, an integrated molecular modeling strategy, which combined computational bioactivity fingerprints and structure-based virtual screening, was employed to identify potential DprE1 inhibitors. Two lead compounds (B2 and H3) that could inhibit DprE1 and thus kill Mycobacterium smegmatis in vitro were identified. Moreover, compound H3 showed potent inhibitory activity against Mycobacterium tuberculosis in vitro (MIC_Mtb = 1.25 μM) and low cytotoxicity against mouse embryo fibroblast NIH-3T3 cells. Our research provided an effective strategy to discover novel anti-TB lead compounds.

(R)-(+)-Lasiodiplodin isolated from the endophytic fungus Sordaria tamaensis exhibits potent antimycobacterial and anti-inflammatory activities in vitro and in vivo: a dual approach for the treatment of severe pulmonary tuberculosis

OBJECTIVES

This study aimed to evaluate endophytic fungi isolated from Tocoyena bullata and Humiria balsamifera plant species for their antimycobacterial and anti-inflammatory activities, focusing on severe pulmonary tuberculosis cases which are often associated with exacerbated inflammation.

METHODS

Mycobacterium suspensions were incubated with the samples for 5 days. RAW 264.7 macrophages stimulated with LPS were also incubated with them for 24 h to assess the inhibition of inflammatory mediator production and cytotoxicity. C57BL/6 mice were infected with Mtb M299 and treated for 15 days with lasiodiplodin (Lasio).

KEY FINDINGS

Endophytic fungus Sordaria tamaensis, obtained from T. bullata, was the most promising. Its ethanolic extract impaired mycobacterial growth with MIC50 (µg/ml): 1.5 ± 0.6 (BCG), 66.8 ± 0.1 (H37Rv) and 80.0 ± 0.1 (M299). (R)-(+)-Lasio showed MIC50 92.2 ± 1.8 µg/ml (M299). In addition, Lasio was able to inhibit NO, IL-1β and TNF-α production and was not cytotoxic for macrophages. M. tuberculosis-infected C57BL/6 animals treated by Lasio reduced the number of acid-fast bacilli, lung pathology, leucocyte influx and proinflammatory cytokine production in the lungs. The class IIa fructose 1,6-bisphosphate aldolase was the predicted hypothetical target of Lasio.

CONCLUSIONS

(R)-(+)-Lasio stood out as a promising anti-TB compound, exhibiting anti-inflammatory and antimycobacterial effects, as well as low cytotoxicity.

Pangenome Analysis of Mycobacterium tuberculosis Reveals Core-Drug Targets and Screening of Promising Lead Compounds for Drug Discovery

Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), is one of the leading causes of human deaths globally according to the WHO TB 2019 report. The continuous rise in multi- and extensive-drug resistance in M. tuberculosis broadens the challenges to control tuberculosis. The availability of a large number of completely sequenced genomes of M. tuberculosis has provided an opportunity to explore the pangenome of the species along with the pan-phylogeny and to identify potential novel drug targets leading to drug discovery. We attempt to calculate the pangenome of M. tuberculosis that comprises a total of 150 complete genomes and performed the phylo-genomic classification and analysis. Further, the conserved core genome (1251 proteins) is subjected to various sequential filters (non-human homology, essentiality, virulence, physicochemical parameters, and pathway analysis) resulted in identification of eight putative broad-spectrum drug targets. Upon molecular docking analyses of these targets with ligands available at the DrugBank database shortlisted a total of five promising ligands with projected inhibitory potential; namely, 2′deoxy-thymidine-5′-diphospho-alpha-d-glucose, uridine diphosphate glucose, 2′-deoxy-thymidine-beta-l-rhamnose, thymidine-5′-triphosphate, and citicoline. We are confident that with further lead optimization and experimental validation, these lead compounds may provide a sound basis to develop safe and effective drugs against tuberculosis disease in humans.

In silico Prediction of New Drug Candidates Against the Multidrug-Resistant and Potentially Zoonotic Fish Pathogen Serotype III Streptococcus agalactiae

Streptococcus agalactiae is an invasive multi-host pathogen that causes invasive diseases mainly in newborns, elderly, and individuals with underlying health complications. In fish, S. agalactiae causes streptococcosis, which is characterized by septicemia and neurological signs, and leads to great economic losses to the fish farming industry worldwide. These bacteria can be classified into different serotypes based on capsular antigens, and into different sequence types (ST) based on multilocus sequence typing (MLST). In 2015, serotype III ST283 was identified to be associated with a foodborne invasive disease in non-pregnant immunocompetent humans in Singapore, and the infection was related to raw fish consumption. In addition, a serotype III strain isolated from tilapia in Brazil has been reported to be resistant to five antibiotic classes. This specific serotype can serve as a reservoir of resistance genes and pose a serious threat to public health. Thus, new approaches for the control and treatment of S. agalactiae infections are needed. In the present study, 24 S. agalactiae serotype III complete genomes, isolated from human and fish hosts, were compared. The core genome was identified, and, using bioinformatics tools and subtractive criteria, five proteins were identified as potential drug targets. Furthermore, 5,008 drug-like natural compounds were virtually screened against the identified targets. The ligands with the best binding properties are suggested for further in vitro and in vivo analysis.

Identification of novel scaffold using ligand and structure based approach targeting shikimate kinase

Tuberculosis (TB) remains a major global health problem. It causes ill-health among millions of people each year and rank as the second leading cause of death from an infectious disease worldwide, after the human immunodeficiency virus (HIV). Shikimate kinase is one of the major enzymes targeted for TB. Most approaches to overcome TB were based on synthesis and screening of a known compounds to obtain a few representatives with desired potency. In this study, we have applied a virtual screening approach which combines ligand- and structure-based approaches to screen a large library of compounds as a starting point for the identification of new scaffolds for the development of shikimate kinase inhibitors. The combined approach has identified 2 new scaffolds as potential inhibitors of shikimate kinase. To prove the approach, few of the molecules and their derivatives, a total of 17 compounds, were synthesized. The compounds were tested for biological activity and shows moderate activity against shikimate kinase. The shikimate kinase enzyme inhibition study reveals that the compounds showed inhibition (IC₅₀) at concentrations of 50 µg/mL (Compounds 21, 22, 24, 25, 26, 27, 30, 32, 34) and 25 µg/mL (14, 19, 23, 31, 33).