ArticleMolecular diversity2021
Molecular modeling of a series of dehydroquinate dehydratase type II inhibitors of Mycobacterium tuberculosis and design of new binders.
Article in Molecular diversity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Amino Acid Biosynthesis Inhibitors in Tuberculosis Drug Discovery.Pharmaceutics · 2024Review
- Advances in computational frameworks in the fight against TB: The way forward.Frontiers in pharmacology · 2023Review
- In Silico Study, Physicochemical, and In Vitro Lipase Inhibitory Activity ofInternational journal of molecular sciences · 2021Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), is still responsible for a large number of fatal cases, especially in developing countries with alarming rates of incidence and prevalence worldwide. Mycobacterium tuberculosis has a remarkable ability to develop new resistance mechanisms to the conventional antimicrobials treatment. Because of this, there is an urgent need for novel bioactive compounds for its treatment. The dehydroquinate dehydratase II (DHQase II) is considered a key enzyme of shikimate pathway, and it can be used as a promising target for the design of new bioactive compounds with antibacterial action. The aim of this work was the construction of QSAR models to aid the design of new potential DHQase II inhibitors. For that purpose, various molecular modeling approaches, such as activity cliff, QSAR models and computer-aided ligand design were utilized. A predictive in silico 4D-QSAR model was built using a database comprising 86 inhibitors of DHQase II, and the model was used to predict the activity of the designed ligands. The obtained model proved to predict well the DHQase II inhibition for an external validation dataset ([Formula: see text] = 0.72). Also, the Activity Cliff analysis shed light on important structural features applied to the ligand design.
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