The identification of novel Mycobacterium tuberculosis DHFR inhibitors and the investigation of their binding preferences by using molecular modelling
نویسندگان
چکیده
It is an urgent need to develop new drugs for Mycobacterium tuberculosis (Mtb), and the enzyme, dihydrofolate reductase (DHFR) is a recognised drug target. The crystal structures of methotrexate binding to mt- and h-DHFR separately indicate that the glycerol (GOL) binding site is likely to be critical for the function of mt-DHFR selective inhibitors. We have used in silico methods to screen NCI small molecule database and a group of related compounds were obtained that inhibit mt-DHFR activity and showed bactericidal effects against a test Mtb strain. The binding poses were then analysed and the influence of GOL binding site was studied by using molecular modelling. By comparing the chemical structures, 4 compounds that might be able to occupy the GOL binding site were identified. However, these compounds contain large hydrophobic side chains. As the GOL binding site is more hydrophilic, molecular modelling indicated that these compounds were failed to occupy the GOL site. The most potent inhibitor (compound 6) demonstrated limited selectivity for mt-DHFR, but did contain a novel central core (7H-pyrrolo[3,2-f]quinazoline-1,3-diamine), which may significantly expand the chemical space of novel mt-DHFR inhibitors. Collectively, these observations will inform future medicinal chemistry efforts to improve the selectivity of compounds against mt-DHFR.
منابع مشابه
Structural and Dynamics Perspectives on the Binding of Substrate and Inhibitors in Mycobacterium tuberculosis DHFR
Dihydrofolate reductase (DHFR), an essential enzyme in the folate pathway, is a potential target for new anti-tuberculosis drugs. Fifteen crystal structures of Mycobacterium tuberculosis DHFR complexed with NADPH and various inhibitors are available in the RCSB Protein Data Bank, but none of them is a substrate binding structure. Therefore, we performed molecular dynamics simulations on ternary...
متن کاملBiochemical characterization of PE_PGRS61 family protein of Mycobacterium tuberculosis H37Rv reveals the binding ability to fibronectin
Objective(s): The periodic binding of protein expressed by Mycobacterium tuberculosis H37Rv with the host cell receptor molecules i.e. fibronectin (Fn) is gaining significance because of its adhesive properties. The genome sequencing of M. tuberculosis H37Rv revealed that the proline-glutamic (PE) proteins contain polymorphic GC-rich repetitive sequences (PGRS) which have clinical importance i...
متن کاملIdentification of Mycobacterium tuberculosis adherence-mediating components: a review of key methods to confirm adhesin function
Anti-adhesion therapy represents a potentially promising avenue for the treatment and prevention of tuberculosis in a post-antibiotic era. Adhesins are surface-exposed microbial structures or molecules that enable pathogenic organisms to adhere to host surfaces, a fundamental step towards host infection. Although several Mycobacterium tuberculosis adhesins have been identified, it is predicted ...
متن کاملIdentification of Mycobacterium Tuberculosis Complex, Using Molecular Methods
Abstract Background and Objective: A high level of homogeneity observed within all bacteria in the Mycobacterium tuberculosis complex makes a property that seriously challenges traditional biochemical-based identification methods of these pathogens in the laboratory. The work presented here was conducted to characterize Mycobacterium tuberculosis complex isolates in Golestan, Northern Iran. ...
متن کاملA Novel QSAR Model for the Evaluation and Prediction of (E)-N’-Benzylideneisonicotinohydrazide Derivatives as the Potent Anti-mycobacterium Tuberculosis Antibodies Using Genetic Function Approach
Abstract A dataset of (E)-N’-benzylideneisonicotinohydrazide derivatives as a potent anti-mycobacterium tuberculosis has been investigated utilizing Quantitative Structure-Activity Relationship (QSAR) techniques. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors and to generate the correlation QSAR models that relate the Mi...
متن کامل