A breakthrough on Amanita phalloides poisoning: an effective antidotal effect by polymyxin B

Amanita phalloides is responsible for more than 90 % of mushroom-related fatalities, and no effective antidote is available. a-Amanitin, the main toxin of A. phalloides, inhibits RNA polymerase II (RNAP II), causing hepatic and kidney failure. In silico studies included docking and molecular dynamics simulation coupled to molecular mechanics with generalized Born and surface area method energy decomposition on RNAP II. They were performed with a clinical drug that shares chemical similarities to a-amanitin, polymyxin B. The results show that polymyxin B potentially binds to RNAP II in the same interface of a-amanitin, preventing the toxin from binding to RNAP II. In vivo, the inhibition of the mRNA transcripts elicited by a-amanitin was efficiently reverted by polymyxin B in the kidneys. Moreover, polymyxin B significantly decreased the hepatic and renal a-amanitin-induced injury as seen by the histology and hepatic aminotransferases plasma data. In the survival assay, all animals exposed to a-amanitin died within 5 days, whereas 50 % survived up to 30 days when polymyxin B was administered 4, 8, and 12 h post-a-amanitin. Moreover, a single dose of polymyxin B administered concomitantly with a-amanitin was able to guarantee 100 % survival. Polymyxin B protects RNAP II from inactivation leading to an effective prevention of organ damage and increasing survival in a-amanitin-treated animals. The present use of clinically relevant concentrations of an already human-use-approved drug prompts the use of polymyxin B as an antidote for A. phalloides poisoning in humans.

Protein-based nanodevices for therapeutic applications

Tese de Doutoramento em Biologia Molecular e Ambiental (área de especialização em Biologia Celular e Saúde).

Single molecule simulation of diffusion and enzyme kinetics

This work presents a molecular-scale agent-based model for the simulation of enzymatic reactions at experimentally measured concentrations. The model incorporates stochasticity and spatial dependence, using diffusing and reacting particles with physical dimensions. We developed strategies to adjust and validate the enzymatic rates and diffusion coefficients to the information required by the computational agents, i.e., collision efficiency, interaction logic between agents, the time scale associated with interactions (e.g., kinetics), and agent velocity. Also, we tested the impact of molecular location (a source of biological noise) in the speed at which the reactions take place. Simulations were conducted for experimental data on the 2-hydroxymuconate tautomerase (EC 5.3.2.6, UniProt ID Q01468) and the Steroid Delta-isomerase (EC 5.3.3.1, UniProt ID P07445). Obtained results demonstrate that our approach is in accordance to existing experimental data and long-term biophysical and biochemical assumptions.