In Silico Target Druggability Assessment: From Structural to Systemic Approaches

Epoxy-a-lapachone in nanosystem: a prototype drug for leishmaniasis assessed in the binomial BALB/c - Leishmania (Leishmania) amazonensis

This perspective presents and supports arguments for a new formulation of epoxy-α-lapachone loaded microemulsion (ELAP-ME), a nanosystem, as a prototype drug for the treatment of leishmaniasis. The benefits of ELAP as a multitarget compound, with properties that affect key physiological pathways of Leishmania spp. are discussed. ELAP-ME demonstrated efficacy in murine infection models, particularly with the binomial BALB/c-Leishmania (Leishmania) amazonensis. Furthermore, it is proposed that the technological maturity of ELAP-ME be classified as Technology Readiness Level 4 (TLR 4) within the context of innovative drugs for American Cutaneous Leishmaniasis (ACL).

Druggable hot spots in trypanothione reductase: novel insights and opportunities for drug discovery revealed by DRUGpy

Assessment of target druggability guided by search and characterization of hot spots is a pivotal step in early stages of drug-discovery. The raw output of FTMap provides the data to perform this task, but it relies on manual intervention to properly combine different sets of consensus sites, therefore allowing identification of hot spots and evaluation of strength, shape and distance among them. Thus, the user's previous experience on the target and the software has a direct impact on how data generated by FTMap server can be explored. DRUGpy plugin was developed to overcome this limitation. By automatically assembling and scoring all possible combinations of consensus sites, DRUGpy plugin provides FTMap users a straight-forward method to identify and characterize hot spots in protein targets. DRUGpy is available in all operating systems that support PyMOL software. DRUGpy promptly identifies and characterizes pockets that are predicted by FTMap to bind druglike molecules with high-affinity (druggable sites) or low-affinity (borderline sites) and reveals how protein conformational flexibility impacts on the target's druggability. The use of DRUGpy on the analysis of trypanothione reductases (TR), a validated drug target against trypanosomatids, showcases the usefulness of the plugin, and led to the identification of a druggable pocket in the conserved dimer interface present in this class of proteins, opening new perspectives to the design of selective inhibitors.

Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace

The interplay between life sciences and advancing technology drives a continuous cycle of chemical data growth; these data are most often stored in open or partially open databases. In parallel, many different types of algorithms are being developed to manipulate these chemical objects and associated bioactivity data. Virtual screening methods are among the most popular computational approaches in pharmaceutical research. Today, user-friendly web-based tools are available to help scientists perform virtual screening experiments. This article provides an overview of internet resources enabling and supporting chemical biology and early drug discovery with a main emphasis on web servers dedicated to virtual ligand screening and small-molecule docking. This survey first introduces some key concepts and then presents recent and easily accessible virtual screening and related target-fishing tools as well as briefly discusses case studies enabled by some of these web services. Notwithstanding further improvements, already available web-based tools not only contribute to the design of bioactive molecules and assist drug repositioning but also help to generate new ideas and explore different hypotheses in a timely fashion while contributing to teaching in the field of drug development.