Diseases caused by protozoan parasites represent a huge challenge to global health care, due to the lack of selective and efficient treatments for the management and spreading of such complex pathologies. The protozoans Trypanosoma cruzi (T. cruzi) and Leishmania spp. are the etiological agents of the so‐called neglected tropical diseases (NTDs), that is, Chagas disease (CD) and leishmaniasis, respectively. In such a context, the metalloenzymes carbonic anhydrases (CAs; EC 4.2.1.1) emerged as potential protozoan druggable enzymes, being involved in the parasites’ life cycle. Several studies suggested the relevance of the protozoan‐expressed CAs as future candidates for the management of NTDs.

Integration of a desossiribonucleic acid (DNA) copy of the viral ribonucleic acid (RNA) into host genomes is a fundamental step in the replication cycle of all retroviruses. The highly conserved virus-encoded Integrase enzyme (IN; EC 2.7.7.49) catalyzes such a process by means of two consecutive reactions named 3′-processing (3-P) and strand transfer (ST). The Authors report and discuss the major discoveries and advances which mainly contributed to the development of Human Immunodeficiency Virus (HIV) -IN targeted inhibitors for therapeutic applications. All the knowledge accumulated over the years continues to serve as a valuable resource for the design and development of effective antiretroviral drugs.

Background/Objectives: Human carbonic anhydrases (hCAs) are metalloenzymes involved in essential physiological processes, and their selective inhibition holds therapeutic potential across a wide range of disorders. However, the high degree of structural similarity among isoforms poses a significant challenge for the design of selective inhibitors. In this work, we present a machine learning (ML)-based platform for the isoform-specific prediction and profiling of small molecules targeting hCA I, II, IX, and XII. Methods: By integrating four molecular representations with four ML algorithms, we built 64 classification models, each extensively optimized and validated. The best-performing models for each isoform were applied in a virtual screening campaign for ~2 million compounds. Results: Following a multi-step refinement process, 12 candidates were identified, purchased, and experimentally tested. Several compounds showed potent inhibitory activity in the nanomolar to submicromolar range, with selectivity profiles across the isoforms. To gain mechanistic insights, SHAP-based feature importance analysis and molecular docking supported by molecular dynamics simulations were employed, highlighting the structural determinants of the predicted activity. Conclusions: This study demonstrates the effectiveness of integrating ML, cheminformatics, and experimental validation to accelerate the discovery of selective carbonic anhydrase inhibitors and provides a generalizable framework for activity profiling across enzyme isoforms.

A novel series of compounds was designed and synthesized by combining the distal piperazine nitrogen of the antifungal ketoconazole (KTZ) with primary arylsulfonamides. The aim of this study is to present the basis for a new generation of Malassezia antifungal agents able to inhibit the enzyme lanosterol‐14α‐demethylase (CYP51; EC 1.14.13.70) as well as a newly emergent therapeutic target: carbonic anhydrases (CAs; EC 4.2.1.1). The final compounds showed effective interactions with the intended targets in vitro, as well as KTZ comparable minimum inhibitory concentrations on yeast strains of the Malassezia genus: Malassezia furfur ATCC 14521; Malassezia globosa ATCC MYA 4612; and Malassezia pachydermatis DSM 6172. Overall, the data obtained account for the reported compounds as promising antifungal candidates with high safety profiles for the management of fungal infections.