ABCG2 is an ABC membrane protein reverse transport pump, which removes toxic substances such as medicines out of cells. As a result, drug bioavailability is an unexpected change and negatively influences the ADMET (absorption, distribution, metabolism, excretion, and toxicity), leading to multi-drug resistance (MDR). Currently, in spite of promising studies, screening for ABCG2 inhibitors showed modest results. The aim of this study was to search for small molecules that could inhibit the ABCG2 pump. We first used the WISS MODEL automatic server to build up ABCG2 homology protein from 655 amino acids. Pharmacophore models, which were con-structed based on strong ABCG2 inhibitors (IC₅₀ < 1 μM), consist of two hydrophobic (Hyd) groups, two hydrogen bonding acceptors (Acc2), and an aromatic or conjugated ring (Aro|PiR). Using molecular docking method, 714 substances from the DrugBank and 837 substances from the TCM with potential to inhibit the ABCG2 were obtained. These chemicals maybe favor synthesized or extracted and bioactivity testing.

The human P‐glycoprotein (P‐gp) and the NorA transporter are the major culprits of multidrug resistance observed in various bacterial strains and cancer cell lines, by extruding drug molecules out of the targeted cells, leading to treatment failures in clinical settings. Inhibiting the activity of these efflux pumps has been a well‐known strategy of drug design studies in this regard. In this manuscript, our earlier published machine learning models and homology structures of P‐gp and NorA were utilized to screen a chemolibrary of 95 in‐house chalcone derivatives, identifying two hit compounds, namely, F88 and F90, as potential modulators of both transporters, whose activity on Staphylococcus aureus strains overexpressing NorA and resistant to ciprofloxacin was subsequently confirmed. The findings of this study are expected to guide future research towards developing novel potent chalconic inhibitors of P‐gp and/or NorA.

Antibiotic resistance has been becoming more and more critical due to bacteria’s evolving hydrolysis enzymes. The NDM-1 enzyme could hydrolyze not only carbapenems but also most of β-lactam’s antibiotics and inhibitors. In fact, variant strains could impose a high impact on the resistance of bacteria producing NDM-1. Although previous studies showed the effect of some variants toward antibiotics and inhibitors binding, there has been no research systematically evaluating the effects of alternative one-point mutations on the hydrolysis capacity of NDM-1. This study aims to identify which mutants could increase or decrease the effectiveness of antibiotics and β-lactamase inhibitors toward bacteria. Firstly, 35 different variants with a high probability of emergence based on the PAM-1 matrix were constructed and then docked with 5 ligands, namely d-captopril, l-captopril, thiorphan, imipenem, and meropenem. The selected complexes underwent molecular dynamics simulation and free energy binding estimation, with the results showing that the substitutions at residues 122 and 124 most influenced the binding ability of NDM-1 toward inhibitors and antibiotics. The H122R mutant decreases the binding ability between d-captopril and NDM-1 and diminishes the effectiveness of this antibiotic toward Enterobacteriaceae. However, the H122R mutant has a contrary impact on thiorphan, which should be tested in vitro and in vivo in further experiments.

Monoamine oxidase B (MAO-B) is a key target in Parkinson's disease treatment due to its role in dopamine metabolism. This study applied a multi-stage in silico workflow - combining 3D-pharmacophore modelling, 2D-QSAR, ADMET filtering, docking, molecular dynamics (MD), and MM/PBSA analysis - to identify selective MAO-B inhibitors. From four datasets including ZINC, DrugBank, TCM, and UNPD, 22 top candidates were selected based on docking scores and predicted selectivity over MAO-A. MD simulations (200 ns) and binding free energy calculations identified four promising compounds - ZINC21285023, ZINC79651118, ZINC58283019, and UNPD89644 (crotafuran E)- that exhibited stable binding and favourable interactions with key residues such as Cys172 and Tyr435. These compounds demonstrated performance comparable to or better than safinamide and are strong candidates for further experimental validation as selective MAO-B inhibitors.

The COVID-19 pandemic posed a threat to global society. Delta and Omicron are concerning variants due to the risk of increasing human-to-human transmissibility and immune evasion. This study aims to evaluate the binding ability of these variants toward the angiotensin-converting enzyme 2 receptor and antibodies using a computational approach. The receptor-binding domain (RBD) of the two variants was created by CHARMM-GUI and then docked to the hACE2 receptor and two antibodies (REGN10933 and REGN10987). These complexes were also subjected to molecular dynamics simulation within 100 ns. As a result, the two variants, Omicron and Delta, exhibited stronger interaction with the hACE2 receptor than the wild type. The mutations in the RBD region also facilitated the virus's escape from antibody neutralization.