Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand-Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors.

Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.

Exploring metalloproteins found in the secretion of venomous species: Biological role and therapeutical applications.

Several species during evolution suffered random mutations in response to various environmental factors, which resulted in the formation of venom in phylogenetically distant species. The composition of the venom of most species is poorly known. Snake venom is well characterized while most species have poorly known composition. In contrast, snake venoms are well characterized which proteins and peptides are the main active and most abundant constituents. 42 protein families have been identified, including metalloproteins known as metalloproteinases. These macromolecules are enzymes with zinc in their active site derived from the disintegrin A and metalloproteinase (ADAM) cellular family and are categorized into three classes (PI, PII and PIII) according to their domain organization. The snake venom metalloproteinases (SVMP) are cytotoxic, neurotoxic, myotoxic and/or hematotoxic with a crucial role in the defense and restraint of prey. In this scenario envenoming represents a danger to human health and has been considered a neglected disease worldwide, particularly in tropical and subtropical countries. Nevertheless, recently advances in "omics" technologies have demonstrated interesting biological activities of SVMPs such as antimicrobial, anticancer, against cardiovascular diseases and nervous system disorders. Metalloproteins have the therapeutic potential to be converted into drugs as other components of the venom have undergone this process (e.g., captopril, tirefiban and eptifibatide). So, this chapter is focused on the metalloproteins found in the secretions of venomous species, highlight some aspects such as structure, biological activity, pharmacological therapeutic potential and on.