Fighting Antimicrobial Resistance: Insights on How the Staphylococcus aureus NorA Efflux Pump Recognizes 2-Phenylquinoline Inhibitors by Supervised Molecular Dynamics (SuMD) and Molecular Docking Simulations.

The superbug Staphylococcus aureus (S. aureus) exhibits several resistance mechanisms, including efflux pumps, that strongly contribute to antimicrobial resistance. In particular, the NorA efflux pump activity is associated with S. aureus resistance to fluoroquinolone antibiotics (e.g., ciprofloxacin) by promoting their active extrusion from cells. Thus, since efflux pump inhibitors (EPIs) are able to increase antibiotic concentrations in bacteria as well as restore their susceptibility to these agents, they represent a promising strategy to counteract bacterial resistance. Additionally, the very recent release of two NorA efflux pump cryo-electron microscopy (cryo-EM) structures in complex with synthetic antigen-binding fragments (Fabs) represents a real breakthrough in the study of S. aureus antibiotic resistance. In this scenario, supervised molecular dynamics (SuMD) and molecular docking experiments were combined to investigate for the first time the molecular mechanisms driving the interaction between NorA and efflux pump inhibitors (EPIs), with the ultimate goal of elucidating how the NorA efflux pump recognizes its inhibitors. The findings provide insights into the dynamic NorA-EPI intermolecular interactions and lay the groundwork for future drug discovery efforts aimed at the identification of novel molecules to fight antimicrobial resistance.

Q-raKtion: A Semiautomated KNIME Workflow for Bioactivity Data Points Curation.

The recent increase of bioactivity data freely available to the scientific community and stored as activity data points in chemogenomic repositories provides a huge amount of ready-to-use information to support the development of predictive models. However, the benefits provided by the availability of such a vast amount of accessible information are strongly counteracted by the lack of uniformity and consistency of data from multiple sources, requiring a process of integration and harmonization. While different automated pipelines for processing and assessing chemical data have emerged in the last years, the curation of bioactivity data points is a less investigated topic, with useful concepts provided but no tangible tools available. In this context, the present work represents a first step toward the filling of this gap, by providing a tool to meet the needs of end-user in building proprietary high-quality data sets for further studies. Specifically, we herein describe Q-raKtion, a systematic, semiautomated, flexible, and, above all, customizable KNIME workflow that effectively aggregates information on biological activities of compounds retrieved by two of the most comprehensive and widely used repositories, PubChem and ChEMBL.

1,2,4-Triazolo[1,5-a]pyrimidines as a Novel Class of Inhibitors of the HIV-1 Reverse Transcriptase-Associated Ribonuclease H Activity.

Despite great efforts have been made in the prevention and therapy of human immunodeficiency virus (HIV-1) infection, however the difficulty to eradicate latent viral reservoirs together with the emergence of multi-drug-resistant strains require the search for innovative agents, possibly exploiting novel mechanisms of action. In this context, the HIV-1 reverse transcriptase (RT)-associated ribonuclease H (RNase H), which is one of the few HIV-1 encoded enzymatic function still not targeted by any current drug, can be considered as an appealing target. In this work, we repurposed in-house anti-influenza derivatives based on the 1,2,4-triazolo[1,5-a]-pyrimidine (TZP) scaffold for their ability to inhibit HIV-1 RNase H function. Based on the results, a successive multi-step structural exploration around the TZP core was performed leading to identify catechol derivatives that inhibited RNase H in the low micromolar range without showing RT-associated polymerase inhibitory activity. The antiviral evaluation of the compounds in the MT4 cells showed any activity against HIV-1 (IIIB strain). Molecular modelling and mutagenesis analysis suggested key interactions with an unexplored allosteric site providing insights for the future optimization of this class of RNase H inhibitors.

Deciphering the Molecular Recognition Mechanism of Multidrug Resistance Staphylococcus aureus NorA Efflux Pump Using a Supervised Molecular Dynamics Approach.

The use and misuse of antibiotics has resulted in critical conditions for drug-resistant bacteria emergency, accelerating the development of antimicrobial resistance (AMR). In this context, the co-administration of an antibiotic with a compound able to restore sufficient antibacterial activity may be a successful strategy. In particular, the identification of efflux pump inhibitors (EPIs) holds promise for new antibiotic resistance breakers (ARBs). Indeed, bacterial efflux pumps have a key role in AMR development; for instance, NorA efflux pump contributes to Staphylococcus aureus (S. aureus) resistance against fluoroquinolone antibiotics (e.g., ciprofloxacin) by promoting their active extrusion from the cells. Even though NorA efflux pump is known to be a potential target for EPIs development, the absence of structural information about this protein and the little knowledge available on its mechanism of action have strongly hampered rational drug discovery efforts in this area. In the present work, we investigated at the molecular level the substrate recognition pathway of NorA through a Supervised Molecular Dynamics (SuMD) approach, using a NorA homology model. Specific amino acids were identified as playing a key role in the efflux pump-mediated extrusion of its substrate, paving the way for a deeper understanding of both the mechanisms of action and the inhibition of such efflux pumps.

Small Molecule Drugs Targeting Viral Polymerases.

Small molecules that specifically target viral polymerases-crucial enzymes governing viral genome transcription and replication-play a pivotal role in combating viral infections. Presently, approved polymerase inhibitors cover nine human viruses, spanning both DNA and RNA viruses. This review provides a comprehensive analysis of these licensed drugs, encompassing nucleoside/nucleotide inhibitors (NIs), non-nucleoside inhibitors (NNIs), and mutagenic agents. For each compound, we describe the specific targeted virus and related polymerase enzyme, the mechanism of action, and the relevant bioactivity data. This wealth of information serves as a valuable resource for researchers actively engaged in antiviral drug discovery efforts, offering a complete overview of established strategies as well as insights for shaping the development of next-generation antiviral therapeutics.

Computer-Aided Identification of Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein.

AKT (also known as PKB) is a serine/threonine kinase that plays a pivotal regulatory role in the PI3K/AKT/mTOR signaling pathway. Dysregulation of AKT activity, especially its hyperactivation, is closely associated with the development of various human cancers and resistance to chemotherapy. Over the years, a wide array of AKT inhibitors has been discovered through experimental and computational approaches. In this regard, herein we present a comprehensive overview of AKT inhibitors identified using computer-assisted drug design methodologies (including docking-based and pharmacophore-based virtual screening, machine learning, and quantitative structure-activity relationships) and successfully validated small molecules endowed with anticancer activity. Thus, this review provides valuable insights to support scientists focused on AKT inhibition for cancer treatment and suggests untapped directions for future computer-aided drug discovery efforts.

From Serendipity to Rational Identification of the 5,6,7,8-Tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidin-4(3H)-one Core as a New Chemotype of AKT1 Inhibitors for Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a heterogeneous hematopoietic malignancy whose prognosis is globally poor. In more than 60% of AML patients, the PI3K/AKTs/mTOR signaling pathway is aberrantly activated because of oncogenic driver alterations and further enhanced by chemotherapy as a mechanism of drug resistance. Against this backdrop, very recently we have started a multidisciplinary research project focused on AKT1 as a pharmacological target to identify novel anti-AML agents. Indeed, the serendipitous finding of the in-house compound T187 as an AKT1 inhibitor has paved the way to the rational identification of new active small molecules, among which T126 has emerged as the most interesting compound with IC50 = 1.99 ± 0.11 µM, ligand efficiency of 0.35, and a clear effect at low micromolar concentrations on growth inhibition and induction of apoptosis in AML cells. The collected results together with preliminary SAR data strongly indicate that the 5,6,7,8-tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidin-4(3H)-one derivative T126 is worthy of future biological experiments and medicinal chemistry efforts aimed at developing a novel chemical class of AKT1 inhibitors as anti-AML agents.

Discovery of potent p38α MAPK inhibitors through a funnel like workflow combining in silico screening and in vitro validation.

This work describes the rational discovery of novel chemotypes of p38α MAPK inhibitors using a funnel approach consisting of several computer-aided drug discovery methods and biological experiments. Among the identified hits, four compounds belonging to different chemical families showed IC50 values lower than 10 µM. In particular, the 1,4-benzodioxane derivative 5 turned out to be a potent and efficient p38α MAPK inhibitor having IC50 = 0.07 µM, and LEexp and LipE values of 0.38 and 4.8, respectively; noteworthy, the compound had also a promising kinase selectivity profile and the capability to suppress p38α MAPK effects in human immune cells. Overall, the collected findings highlight that the applied strategy has been successful in generating chemical novelty in the inhibitor kinase field, providing suitable chemical candidates for further inhibitor optimization.