Bioactive glass material of the type CaO--P(2)O(5)--SiO(2)--ZnO was obtained by the sol-gel processing method. This material was produced both in powder and in disks form by compression of the powder. The obtained material was characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and surface electron micrograph (SEM). The bioactivity was examined in vitro with respect to the ability of hydroxyapatite layer to form on the surface as a result of contact with simulated body fluid (SBF). The XRD and FTIR studies were conducted before and after contact of the material with SBF. The gel-derived materials were amorphous as shown by XRD, but were able to crystallize calcium phosphates on their surfaces when exposed to SBF. We also examined the alkaline phosphatase (AP) activity of osteoblasts, using human fetal osteoblastic cells (hFOB 1.19) cultured on the zinc bioglass, and compared it with the polystyrene plates. The bone cells consistently expressed higher AP activity in the zinc bioglass materials compared with the polystyrene plates, which indicates the zinc containing composition stimulates bone cells production of AP.

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Molecular docking simulation of thirty-five (35) molecules of N-(2-phenoxy)ethyl imidazo[1,2-a]pyridine-3-carboxamide (IPA) with Mycobacterium tuberculosis target (DNA gyrase) was carried out so as to evaluate their theoretical binding affinities. The chemical structure of the molecules was accurately drawn using ChemDraw Ultra software, then optimized at density functional theory (DFT) using Becke’s three-parameter Lee–Yang–Parr hybrid functional (B3LYP/6-311**) basis set in a vacuum of Spartan 14 software. Subsequently, the docking operation was carried out using PyRx virtual screening software. Molecule 35 (M35) with the highest binding affinity of − 7.2 kcal/mol was selected as the lead molecule for structural modification which led to the development of four (4) newly hypothetical molecules D1, D2, D3 and D4. In addition, the D4 molecule with the highest binding affinity value of − 9.4 kcal/mol formed more H-bond interactions signifying better orientation of the ligand in the binding site compared to M35 and isoniazid standard drug. In-silico ADME and drug-likeness prediction of the molecules showed good pharmacokinetic properties having high gastrointestinal absorption, orally bioavailable, and less toxic. The outcome of the present research strengthens the relevance of these compounds as promising lead candidates for the treatment of multidrug-resistant tuberculosis which could help the medicinal chemists and pharmaceutical professionals in further designing and synthesis of more potent drug candidates. Moreover, the research also encouraged the in vivo and in vitro evaluation study for the proposed designed compounds to validate the computational findings.

Development of more potent antituberculosis agents is as a result of emergence of multidrug resistant strains of M. tuberculosis. Novel compounds are usually synthesized by trial approach with a lot of errors, which is time consuming and expensive. QSAR is a theoretical approach, which has the potential to reduce the aforementioned problem in discovering new potent drugs against M. tuberculosis. This approach was employed to develop multivariate QSAR model to correlate the chemical structures of the 2,4-disubstituted quinoline analogues with their observed activities using a theoretical approach. In order to build the robust QSAR model, Genetic Function Approximation (GFA) was employed as a tool for selecting the best descriptors that could efficiently predict the activities of the inhibitory agents. The developed model was influenced by molecular descriptors: AATS5e, VR1_Dzs, SpMin7_Bhe, TDB9e, and RDF110s. The internal validation test for the derived model was found to have correlation coefficient (R2) of 0.9265, adjusted correlation coefficient (R2 adj) value of 0.9045, and leave-one-out cross-validation coefficient (Q_cv∧2) value of 0.8512, while the external validation test was found to have (R2 test) of 0.8034 and Y-randomization coefficient (cR_p∧2) of 0.6633. The proposed QSAR model provides a valuable approach for modification of the lead compound and design and synthesis of more potent antitubercular agents.

A quantitative structure-activity relationship (QSAR) study was performed to develop a model that relates the structures of 50 compounds to their activities against M. tuberculosis. The compounds were optimized by employing density functional theory (DFT) with B3LYP/6-31G⁎. The Genetic Function Algorithm (GFA) was used to select the descriptors and to generate the correlation model that relates the structural features of the compounds to their biological activities. The optimum model has squared correlation coefficient (R2) of 0.9202, adjusted squared correlation coefficient (Radj) of 0.91012, and leave-one-out (LOO) cross-validation coefficient (Qcv2) value of 0.8954. The external validation test used for confirming the predictive power of the built model has R2pred value of 0.8842. These parameters confirm the stability and robustness of the model. Docking analysis showed the best compound with high docking affinity of −14.6 kcal/mol which formed hydrophobic interaction and hydrogen bond with amino acid residues of M. tuberculosis cytochromes (Mtb CYP121). QSAR and molecular docking studies provide valuable approach for pharmaceutical and medicinal chemists to design and synthesize new anti-Mycobacterium tuberculosis compounds.