The aim of this article is to show how thevpower of statistics and cheminformatics can be combined, in R, using two packages: rcdk and cluster.We describe the role of clustering methods for identifying similar structures in a group of 23 molecules according to their fingerprints. The most commonly used method is to group the molecules using a “score” obtained by measuring the average distance between them. This score reflects the similarity/non-similarity between compounds and helps us identify active or potentially toxic substances through predictive studies.Clustering is the process by which the common characteristics of a particular class of compounds are identified. For clustering applications, we are generally measure the molecular fingerprint similarity with the Tanimoto coefficient. Based on the molecular fingerprints, we calculated the molecular distances between the methotrexate molecule and the other 23 molecules in the group, and organized them into a matrix. According to the molecular distances and Ward ’s method, the molecules were grouped into 3 clusters. We can presume structural similarity between the compounds and their locations in the cluster map. Because only 5 molecules were included in the methotrexate cluster, we considered that they might have similar properties and might be further tested as potential drug candidates.

Over the past two decades, the use of tumor necrosis factor alpha (TNF-α) inhibitors has significantly improved the treatment of patients with immune-mediated inflammatory diseases. Firstly, introduced for rheumatoid arthritis, these inhibitors are currently approved and used for a variety of conditions, including ankylosing spondylitis, Crohn’s disease, juvenile idiopathic arthritis, psoriasis, psoriatic arthritis, ulcerative colitis, and chronic uveitis. Despite their immense therapeutic efficacy, TNF-α inhibitors have been associated with neurological adverse effects that bring new clinical challenges. The present review collects data from multiple studies to evaluate the incidence and the relationship between TNF-α inhibitors and neurological side effects and to explore the potential underlying mechanisms of this association. Moreover, it highlights the importance of patient selection, particularly in the case of individuals with a history of demyelinating diseases, raises awareness for clinicians, and calls for ongoing research that will improve TNF-α targeting strategies and offer safer and more effective therapeutic options.

Cancer persists as a global challenge due to the extent to which conventional anticancer therapies pose high risks counterbalanced with their therapeutic benefit. Naturally occurring substances stand as an important safer alternative source for anticancer drug development. In the current study, a series of modified lupane and ursane derivatives was subjected to in vitro screening on the NCI-60 cancer cell line panel. Compounds 6 and 7 have been identified as highly active with GI₅₀ values ranging from 0.03 µM to 5.9 µM (compound 6) and 0.18–1.53 µM (compound 7). Thus, these two compounds were further assessed in detail in order to identify a possible antiproliferative mechanism of action. DAPI (4′,6-diamidino-2-phenylindole) staining revealed that both compounds induced nuclei condensation and overall cell morphological changes consistent with apoptotic cell death. rtPCR analysis showed that both compounds induced upregulation of proapoptotic Bak and Bad genes while downregulating Bcl-XL and Bcl-2 antiapoptotic genes. Molecular docking analysis revealed that both compounds exhibited high scores for Bcl-XL inhibition, while compound 7 showed higher in silico Bcl-XL inhibition potential as compared to the native inhibitor ATB-737, suggesting that compounds may induce apoptotic cell death through targeted antiapoptotic protein inhibition, as well.

Twenty lupane type A-ring azepano-triterpenoids were synthesized from betulin and its related derivatives and their antitubercular activity against Mycobacterium tuberculosis, mono-resistant MTB strains, and nontuberculous strains Mycobacterium abscessus and Mycobacterium avium were investigated in the framework of AToMIc (Anti-mycobacterial Target or Mechanism Identification Contract) realized by the Division of Microbiology and Infectious Diseases, NIAID, National Institute of Health. Of all the tested triterpenoids, 17 compounds showed antitubercular activity and 6 compounds were highly active on the H37Rv wild strain (with MIC 0.5 µM for compound 7), out of which 4 derivatives also emerged as highly active compounds on the three mono-resistant MTB strains. Molecular docking corroborated with a machine learning drug-drug similarity algorithm revealed that azepano-triterpenoids have a rifampicin-like antitubercular activity, with compound 7 scoring the highest as a potential M. tuberculosis RNAP potential inhibitor. FIC testing demonstrated an additive effect of compound 7 when combined with rifampin, isoniazid and ethambutol. Most compounds were highly active against M. avium with compound 14 recording the same MIC value as the control rifampicin (0.0625 µM). The antitubercular ex vivo effectiveness of the tested compounds on THP-1 infected macrophages is correlated with their increased cell permeability. The tested triterpenoids also exhibit low cytotoxicity and do not induce antibacterial resistance in MTB strains.

A series of novel hybrid chalcone N-ethyl-piperazinyl amide derivatives of oleanonic and ursonic acids were synthesized, and their cytotoxic potential was evaluated in vitro against the NCI-60 cancer cell line panel. Compounds 4 and 6 exhibited the highest overall anticancer activity, with GI₅₀ values in some cases reaching nanomolar values. Thus, the two compounds were further assessed in detail in order to identify a possible apoptosis- and antiangiogenic-based mechanism of action induced by the assessed compounds. DAPI staining revealed that both compounds induced nuclei condensation and overall cell morphological changes consistent with apoptotic cell death. rtPCR analysis showed that up-regulation of pro-apoptotic Bak gene combined with the down-regulation of the pro-survival Bcl-XL and Bcl-2 genes caused altered ratios between the pro-apoptotic and anti-apoptotic proteins’ levels, leading to overall induced apoptosis. Molecular docking analysis revealed that both compounds exhibited high scores for Bcl-XL inhibition, suggesting that compounds may induce apoptotic cell death through targeted anti-apoptotic protein inhibition, as well. Ex vivo determinations showed that both compounds did not significantly alter the angiogenesis process on the tested cell lines.