Physiological modeling of the metaverse of the Mycobacterium tuberculosis β-CA inhibition mechanism

Tuberculosis (TB) is an infectious disease that primarily affects the lungs of humans and accounts for Mycobacterium tuberculosis (Mtb) bacteria as the etiologic agent. In this study, we introduce a computational framework designed to identify the important chemical features crucial for the effective inhibition of Mtb β-CAs. Through applying a mechanistic model, we elucidated the essential features pivotal for robust inhibition. Using this model, we engineered molecules that exhibit potent inhibitory activity and introduce relevant novel chemistry. The designed molecules were prioritized for synthesis based on their predicted pKi values via the QSAR (Quantitative Structure-Activity Relationship) model. All the rationally designed and synthesized compounds were evaluated in vitro against different carbonic anhydrase isoforms expressed from the pathogen Mtb; moreover, the off-target and widely human-expressed CA I and II were also evaluated. Among the reported derivatives, 2, 4, and 5 demonstrated the most valuable in vitro activity, resulting in promising candidates for the treatment of TB infection. All the synthesized molecules exhibited favorable pharmacokinetic and toxicological profiles based on in silico predictions. Docking analysis confirmed that the zinc-binding groups bind effectively into the catalytic triad of the Mtb β-Cas, supporting the in vitro outcomes with these binding interactions. Furthermore, molecules with good prediction accuracies according to previously established mechanistic and QSAR models were utilized to delve deeper into the realm of systems biology to understand their mechanism in combating tuberculotic pathogenesis. The results pointed to the key involvement of the compounds in modulating immune responses via NF-κβ1, SRC kinase, and TNF-α to modulate granuloma formation and clearance via T cells. This dual action, in which the pathogen's enzyme is inhibited while modulating the human immune machinery, represents a paradigm shift toward more effective and comprehensive treatment approaches for combating tuberculosis.

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Publication Details

Journal
Computers in Biology and Medicine
Published
2024-08-22
DOI
https://doi.org/10.1016/j.compbiomed.2024.109029
Citations
4
Primary Topic
Enzyme function and inhibition
Type
article
Field-Weighted Citation Impact
0.94

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article

Physiological modeling of the metaverse of the Mycobacterium tuberculosis β-CA inhibition mechanism

Ashok Aspatwar, Simone Giovannuzzi, Rajarshi Ray, Claudiu T. Supuran et al.
4 citations
Computers in Biology and Medicine
Enzyme function and inhibition
0.94
article

Physiological modeling of the metaverse of the Mycobacterium tuberculosis β-CA inhibition mechanism

Ashok Aspatwar, Simone Giovannuzzi, Rajarshi Ray, Claudiu T. Supuran, Ratul Bhowmik, Ajay Manaithiya, Fabrizio Carta, Sagar Singh Shyamal, Seppo Parrkila
article en
4 citations

Abstract

Tuberculosis (TB) is an infectious disease that primarily affects the lungs of humans and accounts for Mycobacterium tuberculosis (Mtb) bacteria as the etiologic agent. In this study, we introduce a computational framework designed to identify the important chemical features crucial for the effective inhibition of Mtb β-CAs. Through applying a mechanistic model, we elucidated the essential features pivotal for robust inhibition. Using this model, we engineered molecules that exhibit potent inhibitory activity and introduce relevant novel chemistry. The designed molecules were prioritized for synthesis based on their predicted pKi values via the QSAR (Quantitative Structure-Activity Relationship) model. All the rationally designed and synthesized compounds were evaluated in vitro against different carbonic anhydrase isoforms expressed from the pathogen Mtb; moreover, the off-target and widely human-expressed CA I and II were also evaluated. Among the reported derivatives, 2, 4, and 5 demonstrated the most valuable in vitro activity, resulting in promising candidates for the treatment of TB infection. All the synthesized molecules exhibited favorable pharmacokinetic and toxicological profiles based on in silico predictions. Docking analysis confirmed that the zinc-binding groups bind effectively into the catalytic triad of the Mtb β-Cas, supporting the in vitro outcomes with these binding interactions. Furthermore, molecules with good prediction accuracies according to previously established mechanistic and QSAR models were utilized to delve deeper into the realm of systems biology to understand their mechanism in combating tuberculotic pathogenesis. The results pointed to the key involvement of the compounds in modulating immune responses via NF-κβ1, SRC kinase, and TNF-α to modulate granuloma formation and clearance via T cells. This dual action, in which the pathogen's enzyme is inhibited while modulating the human immune machinery, represents a paradigm shift toward more effective and comprehensive treatment approaches for combating tuberculosis.

Computers in Biology and MedicineVol. 181
Tampere University of Applied Sciences (FI), Tampere University (FI), Tampere University Hospital (FI), Tampere University (FI), University of Florence (IT), Banaras Hindu University (IN)
Academy of Finland, Suomen Kulttuurirahasto, Jane ja Aatos Erkon Säätiö, Tampereen Tuberkuloosisäätiö
Good health and well-being
Openalex Percentile: Top 26%
Enzyme function and inhibition
0.94
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