Ligand-based pharmacophore model of N-Aryl and N-Heteroaryl piperazine alpha 1A-adrenoceptors antagonists using GALAHAD

Computational Approaches to Designing Antiviral Drugs against COVID-19: A Comprehensive Review

The global impact of the COVID-19 pandemic caused by SARS-CoV-2 necessitates innovative strategies for the rapid development of effective treatments. Computational methodologies, such as molecular modelling, molecular dynamics simulations, and artificial intelligence, have emerged as indispensable tools in the drug discovery process. This review aimed to provide a comprehensive overview of these computational approaches and their application in the design of antiviral agents for COVID-19. Starting with an examination of ligand-based and structure-based drug discovery, the review has delved into the intricate ways through which molecular modelling can accelerate the identification of potential therapies. Additionally, the investigation extends to phytochemicals sourced from nature, which have shown promise as potential antiviral agents. Noteworthy compounds, including gallic acid, naringin, hesperidin, Tinospora cordifolia, curcumin, nimbin, azadironic acid, nimbionone, nimbionol, and nimocinol, have exhibited high affinity for COVID-19 Mpro and favourable binding energy profiles compared to current drugs. Although these compounds hold potential, their further validation through in vitro and in vivo experimentation is imperative. Throughout this exploration, the review has emphasized the pivotal role of computational biologists, bioinformaticians, and biotechnologists in driving rapid advancements in clinical research and therapeutic development. By combining state-of-the-art computational techniques with insights from structural and molecular biology, the search for potent antiviral agents has been accelerated. The collaboration between these disciplines holds immense promise in addressing the transmissibility and virulence of SARS-CoV-2.

Identification of novel Aedes aegypti odorant-binding protein 1 modulators by ligand and structure-based approaches and bioassays

Arboviruses are a group of viruses (e.g. Dengue, Chikungunya and Yellow fever virus) that are transmitted by arthropod vectors, which Aedes aegipty is the vector of main viruses in Americas. This vector is responsible to 2.4 millions of arboviruses cases in Brazil with less than a thousand deaths annually. Despite of epidemiological data, arboviruses treatment is symptomatic and the vaccine control is not effective, which makes the vector control against A. aegipty a promising strategy to diseases control. One way to achieve this goal is to development of A. aegipty sensitive olfactory modulators. Odorant binding protein 1 from A. aegypti (AaegOBP1) is essential in sensory communication, and is the first filter in odorant selection, which makes this target promising to development of new repellents. For this reason, hierarchical virtual screening (ligand-based pharmacophore model and molecular docking) together volatility filter was applied at Sigma-Aldrich database (n = 126.851) to prioritize potential molecules to repellency assays. Three compounds showed adequate stereo-electronic requirements (QFIT> 81.53), score to AaegOBP1 binding site (Score > 36.0) and volatile properties and it was chosen for repellency assays. ZINC00170981 and ZINC00131924 showed a dose-response behavior, while ZINC01621824 did not showed activity in repellency assays. Finally, Molecular Dynamics (MD) was employed to hypothesize the stability of protein-ligand complexes. According to RMSD, RMSF and binding free energy data, ZINC00170981 and ZINC00131924 were able to stabilize AaegOBP1 binding-site during the trajectory by interactions with key residues such as His77, Leu89 and Trp114). Communicated by Ramaswamy H. Sarma.

Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening

The Protein Kinase Receptor type 2 (RIPK2) plays an important role in the pathogenesis of inflammatory diseases; it signals downstream of the NOD1 and NOD2 intracellular sensors and promotes a productive inflammatory response. However, excessive NOD2 signaling has been associated with various diseases, including sarcoidosis and inflammatory arthritis; the pharmacological inhibition of RIPK2 is an affinity strategy that demonstrates an increased expression of pro-inflammatory secretion activity. In this study, a pharmacophoric model based on the crystallographic pose of ponatinib, a potent RIPK2 inhibitor, and 30 other ones selected from the BindingDB repository database, was built. Compounds were selected based on the available ZINC compounds database and in silico predictions of their pharmacokinetic, toxicity and potential biological activity. Molecular docking was performed to identify the probable interactions of the compounds as well as their binding affinity with RIPK2. The compounds were analyzed to ponatinib and WEHI-345, which also used as a control. At least one of the compounds exhibited suitable pharmacokinetic properties, low toxicity and an interesting binding affinity and high fitness compared with the crystallographic pose of WEHI-345 in complex with RIPK2. This compound also possessed suitable synthetic accessibility, rendering it a potential and very promising RIPK2 inhibitor to be further investigated in regards to different diseases, particularly inflammatory ones.

Synthesis, biological evaluation and in silico molecular modeling of pyrrolyl benzohydrazide derivatives as enoyl ACP reductase inhibitors

In efforts to develop lead anti-TB compounds, a novel series of 19 pyrrolyl benzohydrazides were synthesized and screened to target enoyl-ACP reductase enzyme, which is one of the important enzymes involved in type II fatty acid biosynthetic pathway of M. tuberculosis. Pharmacophores were constructed using GALAHAD to generate alignment of data sets and calculated by Pareto ranking. The pharmacophore features were then filtered by Surflex-dock study using enoyl ACP reductase from M. tuberculosis. Compounds 5b and 5d showed H-bonding interactions with Tyr158, Thr196 and co-factor NAD⁺ that fitted well within the binding pocket of InhA. All the synthesized compounds were screened for preliminary antibacterial activities against Gram-positive S. aureus and Gram-negative E. coli and M. tuberculosis H₃₇Rv to evaluate their antitubercular activities. Some representative compounds were further tested for mammalian cell toxicity using human lung cancer cell-line (A549) that was found to be nontoxic. These compounds exhibited moderate inhibition activities against InhA.

Design and synthesis of potent N-phenylpyrimidine derivatives for the treatment of skin cancer

The development of novel synthetic compounds for the treatment of skin cancer is much needed, as there is a sudden rise in the incidence of skin cancer throughout the world and the available chemotherapy is facing problems of resistance.

Synthesis and cytotoxic activity evaluation of novel arylpiperazine derivatives on human prostate cancer cell lines

A series of novel arylpiperazine derivatives was synthesized. The in vitro cytotoxic activities of all synthesized compounds against three human prostate cancer cell lines (PC-3, LNCaP, and DU145) were evaluated by a CCK-8 assay. Compounds 9 and 15 exhibited strong cytotoxic activities against LNCaP cells (IC₅₀ < 5 μM), and compound 8 (IC₅₀ = 8.25 μM) possessed the most potent activity against DU145 cells. However, these compounds also exhibited cytotoxicity towards human epithelial prostate normal cells RWPE-1. The structure–activity relationship (SAR) of these arylpiperazine derivatives was also discussed based on the obtained experimental data.

The discovery of potentially selective human neuronal nitric oxide synthase (nNOS) Inhibitors: a combination of pharmacophore modelling, CoMFA, virtual screening and molecular docking studies

Neuronal nitric oxide synthase (nNOS) plays an important role in neurotransmission and smooth muscle relaxation. Selective inhibition of nNOS over its other isozymes is highly desirable for the treatment of neurodegenerative diseases to avoid undesirable effects. In this study, we present a workflow for the identification and prioritization of compounds as potentially selective human nNOS inhibitors. Three-dimensional pharmacophore models were constructed based on a set of known nNOS inhibitors. The pharmacophore models were evaluated by Pareto surface and CoMFA (Comparative Molecular Field Analysis) analyses. The best pharmacophore model, which included 7 pharmacophore features, was used as a search query in the SPECS database (SPECS^®, Delft, The Netherlands). The hit compounds were further filtered by scoring and docking. Ten hits were identified as potential selective nNOS inhibitors.

Pharmacophore and QSAR studies to design novel histone deacetylase 2 inhibitors

One pharmacophore model and three quantitative structure-activity relationship models were developed on a series of benzimidazole and imidazole inhibitors of histone deacetylase 2. The goodness of hit score value of the best pharmacophore model was 0.756, which indicated that it is reliable to be used for virtual screening. The built pharmacophore model was used to search the NCI database. The hit compounds were subjected to molecular docking. The results showed that 25 compounds had high scores and strong interactions with histone deacetylase 2. In three-dimensional quantitative structure-activity relationship studies, good predictive models were obtained using comparative molecular field analysis, comparative molecular similarity indices analysis, and Topomer comparative molecular field analysis. Some putative active compounds were proposed based on compound no. 41. Twenty-six compounds had high scores and good interactions when they were docking into histone deacetylase 2.

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies on α(1A)-adrenergic receptor antagonists based on pharmacophore molecular alignment

The α_1A-adrenergic receptor (α_1A-AR) antagonist is useful in treating benign prostatic hyperplasia, lower urinary tract symptoms, and cardiac arrhythmia. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a set of α_1A-AR antagonists of N-aryl and N-nitrogen class. Statistically significant models constructed from comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established based on a training set of 32 ligands using pharmacophore-based molecular alignment. The leave-oneout cross-validation correlation coefficients were q²_CoMFA = 0.840 and q²_CoMSIA = 0.840. The high correlation between the cross-validated/predicted and experimental activities of a test set of 12 ligands revealed that the CoMFA and CoMSIA models were robust (r²_pred/CoMFA = 0.694; r²_pred/CoMSIA = 0.671). The generated models suggested that electrostatic, hydrophobic, and hydrogen bonding interactions play important roles between ligands and receptors in the active site. Our study serves as a guide for further experimental investigations on the synthesis of new compounds. Structural modifications based on the present 3D-QSAR results may lead to the discovery of other α_1A-AR antagonists.