Since its discovery in 1882, the so-called Koch's bacillus (Mycobacterium tuberculosis, Mtb)
has never ceased to affect humanity. In 2020, tuberculosis (TB) became the second leading cause of
death in the world from a single pathological agent, Mycobacterium tuberculosis (Mtb), second only to
COVID-19. With the COVID-19 pandemic, there was an increase in the number of deaths from
tuberculosis due a lack of access to diagnosis and treatment, a fact that occurred for the first time in ten
years. Furthermore, the emergence of drug-resistant strains of TB makes urgent the search for less
toxic drugs and efforts to improve current treatment and bypass Mtb resistance mechanisms.
The shikimate pathway, which is present in bacteria, fungi and plants but absent in humans, has
been important for the development of new anti-TB therapeutic agents. The enzyme shikimate
kinase (SK) is a member of the Nucleoside Monophosphate Kinase (NMP) family, an important group
of enzymes that catalyze the reversible transfer of a phosphate from a nucleoside triphosphate to a
specific nucleoside diphosphate. This enzyme catalyzes the fifth step of the shikimate pathway, which
is shikimate phosphorylation (SKM), using ATP as a phosphate donor to form shikimate-3-phosphate
(S3P) and adenosine diphosphate (ADP). Based on the determination of the SKM binding site in a
crystallographic structure of SK complexed with ADP:SKM and the structure ATP:shikimate 3-
phosphotransferase, it was possible to have a better understanding of the intermolecular interactions
between the ligands and the enzyme.
In order to assist in the development of new drugs, computational tools can be used, as they
facilitate the detailed understanding of protein-ligand interactions. Therefore, in this work, we used
docking simulations to identify potential MtSK inhibitors from the library of molecules synthesized by
the Research Center for Molecular and Functional Biology (CPBMF), Brazil. Compounds that showed
the best binding energy predicted by docking simulations were subjected to in silico prediction of
toxicity and hepatotoxicity using pkCSM. Thus, the results obtained serve as a basis for further
efforts aimed at designing new anti-TB agents, as well as potential MtSK inhibitors.