Human Topoisomerase I (hTop1p) is a ubiquitous enzyme that relaxes supercoiled DNA through a conserved mechanism involving transient breakage, rotation, and binding. Htop1p is the molecular target of the chemotherapeutic drug camptothecin (CPT). It causes the hTop1p-DNA complex to slow down the binding process and clash with the replicative machinery during the S phase of the cell cycle, forcing cells to activate the apoptotic response. This gives hTop1p a central role in cancer therapy. Recently, two artesunic acid derivatives (compounds c6 and c7) have been proposed as promising inhibitors of hTop1p with possible antitumor activity. We used several computational approaches to obtain in silico confirmations of the experimental data and to form a comprehensive dynamic description of the ligand-receptor system. We performed molecular docking analyses to verify the ability of the two new derivatives to access the enzyme-DNA interface, and a classical molecular dynamics simulation was performed to assess the capacity of the two compounds to maintain a stable binding pose over time. Finally, we calculated the noncovalent interactions between the two new derivatives and the hTop1p receptor in order to propose a possible inhibitory mechanism like that adopted by CPT.

Objectives: Anisakis pegreffii is a zoonotic parasite requiring marine organisms to complete its life-history. Human infection (anisakiasis) occurs when the third stage larvae (L3) are accidentally ingested with raw or undercooked infected fish or squids. A new de novo transcriptome of A. pegreffii was here generated aiming to provide a robust bulk of data to be used for a comprehensive "ready-to-use" resource for detecting functional studies on genes and gene products of A. pegreffii involved in the molecular mechanisms of parasite-host interaction. Data description: A RNA-seq library of A. pegreffii L3 was here newly generated by using Illumina TruSeq platform. It was combined with other five RNA-seq datasets previously gathered from L3 of the same species stored in SRA of NCBI. The final dataset was analyzed by launching three assembler programs and two validation tools. The use of a robust pipeline produced a high-confidence protein-coding transcriptome of A. pegreffii. These data represent a more robust and complete transcriptome of this species with respect to the actually existing resources. This is of importance for understanding the involved adaptive and immunomodulatory genes implicated in the “cross talk” between the parasite and its hosts, including the accidental one (humans).