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As a member of the class I PI3K family, phosphoinositide 3-kinase δ (PI3Kδ) is an important signaling biomolecule that controls immune cell differentiation, proliferation, migration, and survival. It also represents a potential and promising therapeutic approach for the management of numerous inflammatory and autoimmune diseases. We designed and assessed the biological activity of new fluorinated analogues of CPL302415, taking into account the therapeutic potential of our selective PI3K inhibitor and fluorine introduction as one of the most frequently used modifications of a lead compound to further improve its biological activity. In this paper, we compare and evaluate the accuracy of our previously described and validated in silico workflow with that of the standard (rigid) molecular docking approach. The findings demonstrated that a properly fitted catalytic (binding) pocket for our chemical cores at the induced-fit docking (IFD) and molecular dynamics (MD) stages, along with QM-derived atomic charges, can be used for activity prediction to better distinguish between active and inactive molecules. Moreover, the standard approach seems to be insufficient to score the halogenated derivatives due to the fixed atomic charges, which do not consider the response and indictive effects caused by fluorine. The proposed computational workflow provides a computational tool for the rational design of novel halogenated drugs. [ABSTRACT FROM AUTHOR]

Currently, G protein-coupled receptors (GPCRs) constitute a significant group of membrane-bound receptors representing more than 30% of therapeutic targets. Fluorine is commonly used in designing highly active biological compounds, as evidenced by the steadily increasing number of drugs by the Food and Drug Administration (FDA). Herein, we identified and analyzed 898 target-based F-containing isomeric analog sets for SAR analysis in the ChEMBL database—FiSAR sets active against 33 different aminergic GPCRs comprising a total of 2163 fluorinated (1201 unique) compounds. We found 30 FiSAR sets contain activity cliffs (ACs), defined as pairs of structurally similar compounds showing significant differences in affinity (≥50-fold change), where the change of fluorine position may lead up to a 1300-fold change in potency. The analysis of matched molecular pair (MMP) networks indicated that the fluorination of aromatic rings showed no clear trend toward a positive or negative effect on affinity. Additionally, we propose an in silico workflow (including induced-fit docking, molecular dynamics, quantum polarized ligand docking, and binding free energy calculations based on the Generalized-Born Surface-Area (GBSA) model) to score the fluorine positions in the molecule. [ABSTRACT FROM AUTHOR]

Ciprofloxacin (CFX), a widely used fluoroquinolone antibiotic, is critical in healthcare settings for treating patients. However, improper treatment of wastewater from these facilities can lead to environmental contamination with CFX. This underscores the need for an efficient, straightforward method for early detection. In this study, a DNA aptamer was selected through a hierarchical docking workflow, and the stability and interactions were assessed by Molecular Dynamics (MD) simulation. The aptamer-CFX complex that showed the most promise had a docking score of −8.596 kcal/mol and was further analyzed using MD simulation and MM/PBSA. Based on the overall results, the identified ssDNA sequence length of 60 nt (CAGCGCTAGGGCTTTTAGCGTAATGGGTAGGGTGGTGCGGTGCAGATATCGGAATTGGTG) was immobilized over a gold transducer surface through the self-assembled monolayer (SAM; Au–S-ssDNA) method. The ssDNA-modified surface has demonstrated a high affinity towards CFX, which is confirmed by cyclic voltammogram (CV) and electrochemical impedance spectroscopy measurements (EIS). The DNA-aptamer modified electrode demonstrated a good linear range (10 × 10−9 – 200 × 10−9 M), detection limit (1.0 × 10−9 M), selectivity, reproducibility, and stability. The optimized DNA-aptamer-based CFX sensor was further utilized for the accurate determination of CFX with good recoveries in real samples. [Display omitted] • 238 ssDNA nucleotide 3D structures were predicted through a standard bioinformatics workflow. • Top 5 ciprofloxacin specific DNA aptamers were screened using standard precision (SP) docking and QPLD docking. • Using Aptamer5099 and ciprofloxacin interaction data, electrochemical measurements were performed. • The aptamer showed a linear range (10 × 10−9 – 200 × 10−9 M), detection limit (1.0 × 10−9), and good recoveries in real samples. [ABSTRACT FROM AUTHOR]

As a member of the class I PI3K family, phosphoinositide 3-kinase δ (PI3Kδ) is an important signaling biomolecule that controls immune cell differentiation, proliferation, migration, and survival. It also represents a potential and promising therapeutic approach for the management of numerous inflammatory and autoimmune diseases. We designed and assessed the biological activity of new fluorinated analogues of CPL302415, taking into account the therapeutic potential of our selective PI3K inhibitor and fluorine introduction as one of the most frequently used modifications of a lead compound to further improve its biological activity. In this paper, we compare and evaluate the accuracy of our previously described and validated in silico workflow with that of the standard (rigid) molecular docking approach. The findings demonstrated that a properly fitted catalytic (binding) pocket for our chemical cores at the induced-fit docking (IFD) and molecular dynamics (MD) stages, along with QM-derived atomic charges, can be used for activity prediction to better distinguish between active and inactive molecules. Moreover, the standard approach seems to be insufficient to score the halogenated derivatives due to the fixed atomic charges, which do not consider the response and indictive effects caused by fluorine. The proposed computational workflow provides a computational tool for the rational design of novel halogenated drugs.

The high rate of drug resistance as well as the complex biochemical process of the parasite reproduction cycle makes development of new drugs for malaria a very important but challenging task. Falcipain 2 (FL2) and Falcipain 3 (FL3) are the major cysteine protease enzymes that play a central role in providing essential amino acids for the parasite’s protein biosynthesis through the hemoglobin hydrolysis process. Selective inhibition of these enzymes is considered as a promising chemotherapeutic target. In the present investigation, the highly efficient linear interaction energy (LIE) method has been parameterized for binding affinity predictions and assessed with a set of 244 compounds for FL2 and FL3 inhibition. The results revealed that the van der Waals energy is very important for ligands binding to Falcipain proteins and that, overall, the electrostatic energy contribution is minor. The best models obtained for FL2 and FL3 give root mean square errors (RMSE) of 1.82 and 1.33 kcal/mol respectively, for the test set. In this study, we also investigate how the choice of initial protein-ligand confirmation ( pose ) impacts the overall quality of the LIE models. Moreover, the transferability of LIE parameters is further discussed. [ABSTRACT FROM AUTHOR]

HIV-1 integrase (IN) is an essential enzyme in the viral replication cycle and represents a promising target for anti-HIV drug design. In the present study, pharmacophore modeling and atom-based 3D-QSAR studies were carried out on a series of compounds belonging to dihydroxy isoindole derivatives as HIV-1 IN strand transfer inhibitors. The best pharmacophore model generated consists of six features AADHRR: two hydrogen bond acceptors (A), a hydrogen bond donor (D), a hydrophobic group (H) and two aromatic rings (R). Based on the best pharmacophore model, a statistically valid atom-based 3D-QSAR model was developed. The obtained atom-based 3D-QSAR model has an excellent correlation coefficient value (R²=0.87) and also exhibited good predictive power (Q²=0.72). The best pharmacophore model was further validated through enrichment calculations and it shows strong predictive power with a high performance in identifying active ligands from the total hits (actives+decoys). QM-polarized ligand docking and molecular dynamics simulations of selected active compounds in the active site of prototype foamy virus intasome gave important insights into the chemical and structural basis involved in the molecular recognition process. The O,O,O donor atom triad of compounds show metal chelation with divalent Mg2+ ions bound to the three catalytic amino acids in the enzyme's active site and π-stacking interaction with the viral DNA residue DA17. The results might have implications for rational design of specific HIV-1 integrase strand transfer inhibitors with improved affinity and selectivity. [ABSTRACT FROM AUTHOR]