A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide-resistant Mycobacterium tuberculosis.

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.

An in silico approach to identify novel and potential Akt1 (protein kinase B-alpha) inhibitors as anticancer drugs.

Akt1 (protein kinase B) has become a major focus of attention due to its significant functionality in a variety of cellular processes and the inhibition of Akt1 could lead to a decrease in tumour growth effectively in cancer cells. In the present work, we discovered a set of novel Akt1 inhibitors by using multiple computational techniques, i.e. pharmacophore-based virtual screening, molecular docking, binding free energy calculations, and ADME properties. A five-point pharmacophore hypothesis was implemented and validated with AADRR38. The obtained R2 and Q2 values are in the acceptable region with the values of 0.90 and 0.64, respectively. The generated pharmacophore model was employed for virtual screening to find out the potential Akt1 inhibitors. Further, the selected hits were subjected to molecular docking, binding free energy analysis, and refined using ADME properties. Also, we designed a series of 6-methoxybenzo[b]oxazole analogues by comprising the structural characteristics of the hits acquired from the database. Molecules D1-D10 were found to have strong binding interactions and higher binding free energy values. In addition, Molecular dynamic simulation was performed to understand the conformational changes of protein-ligand complex.

Unveiling Novel Urease Inhibitors for Helicobacter pylori: A Multi-Methodological Approach from Virtual Screening and ADME to Molecular Dynamics Simulations.

Helicobacter pylori (Hp) infections pose a global health challenge demanding innovative therapeutic strategies by which to eradicate them. Urease, a key Hp virulence factor hydrolyzes urea, facilitating bacterial survival in the acidic gastric environment. In this study, a multi-methodological approach combining pharmacophore- and structure-based virtual screening, molecular dynamics simulations, and MM-GBSA calculations was employed to identify novel inhibitors for Hp urease (HpU). A refined dataset of 8,271,505 small molecules from the ZINC15 database underwent pharmacokinetic and physicochemical filtering, resulting in 16% of compounds for pharmacophore-based virtual screening. Molecular docking simulations were performed in successive stages, utilizing HTVS, SP, and XP algorithms. Subsequent energetic re-scoring with MM-GBSA identified promising candidates interacting with distinct urease variants. Lys219, a residue critical for urea catalysis at the urease binding site, can manifest in two forms, neutral (LYN) or carbamylated (KCX). Notably, the evaluated molecules demonstrated different interaction and energetic patterns in both protein variants. Further evaluation through ADMET predictions highlighted compounds with favorable pharmacological profiles, leading to the identification of 15 candidates. Molecular dynamics simulations revealed comparable structural stability to the control DJM, with candidates 5, 8 and 12 (CA5, CA8, and CA12, respectively) exhibiting the lowest binding free energies. These inhibitors suggest a chelating capacity that is crucial for urease inhibition. The analysis underscores the potential of CA5, CA8, and CA12 as novel HpU inhibitors. Finally, we compare our candidates with the chemical space of urease inhibitors finding physicochemical similarities with potent agents such as thiourea.

Pharmacophore-based virtual screening of commercial databases against ß-secretase 1 for drug development against Alzheimer's disease.

ß-secretase 1, one of the most important proteins, is an aspartate protease. This membrane-associated protein is used for treating Alzheimer's disease (AD). Several inhibitors have been pursued against ß-secretase 1, but they still have not resulted effectively. Virtual screening based on pharmacophores has been shown to be useful for lead optimization and hit identification in the preliminary phase of developing a new drug. Here, we screen the commercially available databases to find the hits against ß-secretase 1 for drug discovery against AD. Virtual screening for 200,000 compounds was done using the database from the Vitas-M Laboratory. The phase screen score was utilized to assess the screened hits. Molecular docking was performed on compounds with phase scores >1.9. According to the study, the 66H ligand of the crystal structure has the maximum performance against ß-secretase 1. The redocking of the co-crystal ligand showed that the docked ligand was seamlessly united with the crystal structure. The reference complex had three hydrogen bonds with Asp93, Asp289, and Gly291; one van der Waals interaction with Gly74; and three hydrophobic interactions. After equilibration, the RMSD of the reference compound sustained a value of ∼1.5 Å until 30 ns and then boosted to 2.5 Å. On comparison, the RMSD of the S1 complex steadily increased to ∼2.5 Å at 15 ns, displayed slight aberrations at approximately ∼2.5-3 Å until 80 ns, and then achieved steadiness toward the end of the simulation. The arrangements of proteins stayed condensed during the mockup when bonded to these complexes as stable Rg values showed. Furthermore, the MM/GBSA technique was employed to analyze both compounds' total binding free energies (ΔGtotal). Our research study provides a new understanding of using 66H as anti-ß-secretase 1 for drug development against AD.