Polymorphisms in alternative oxidase genes from ecotypes of Arabidopsis and rice revealed an environment-induced linkage to altitude and rainfall.

We investigated SNPs in alternative oxidase (AOX) genes and their connection to ecotype origins (climate, altitude, and rainfall) by using genomic data sets of Arabidopsis and rice populations from 1190 and 90 ecotypes, respectively. Parameters were defined to detect non-synonymous SNPs in the AOX ORF, which revealed amino acid (AA) changes in AOX1c, AOX1d, and AOX2 from Arabidopsis and AOX1c from rice in comparison to AOX references from Columbia-0 and Japonica ecotypes, respectively. Among these AA changes, Arabidopsis AOX1c_A161E&G165R and AOX1c_R242S revealed a link to high rainfall and high altitude, respectively, while all other changes in Arabidopsis and rice AOX was connected to high altitude and rainfall. Comparative 3D modeling showed that all mutant AOX presented structural differences in relation to the respective references. Molecular docking analysis uncovered lower binding affinity values between AOX and the substrate ubiquinol for most of the identified structures compared to their reference, indicating better enzyme-substrate binding affinities. Thus, our in silico data suggest that the majority of the AA changes found in the available ecotypes will confer better enzyme-subtract interactions and thus indicate environment-related, more efficient AOX activity.

Development of New Potential Inhibitors of ß1 Integrins through In Silico Methods-Screening and Computational Validation.

Integrins are transmembrane receptors that play a critical role in many biological processes which can be therapeutically modulated using integrin blockers, such as peptidomimetic ligands. This work aimed to develop new potential ß1 integrin antagonists using modeled receptors based on the aligned crystallographic structures and docked with three lead compounds (BIO1211, BIO5192, and TCS2314), widely known as α4ß1 antagonists. Lead-compound complex optimization was performed by keeping intact the carboxylate moiety of the ligand, adding substituents in two other regions of the molecule to increase the affinity with the target. Additionally, pharmacokinetic predictions were performed for the ten best ligands generated, with the lowest docking interaction energy obtained for α4ß1 and BIO5192. Results revealed an essential salt bridge between the BIO5192 carboxylate group and the Mg2+ MIDAS ion of the integrin. We then generated more than 200 new BIO5192 derivatives, some with a greater predicted affinity to α4ß1. Furthermore, the significance of retaining the pyrrolidine core of the ligand and increasing the therapeutic potential of the new compounds is emphasized. Finally, one novel molecule (1592) was identified as a potential drug candidate, with appropriate pharmacokinetic profiles, similar dynamic behavior at the integrin interaction site compared with BIO5192, and a higher predicted affinity to VLA-4.

Investigation of Unprecedented Sites and Proposition of New Ligands for Programmed Cell Death Protein I through Molecular Dynamics with Probes and Virtual Screening.

Cancer immunotherapy has attracted increasing attention over the last few years. Programmed cell death protein 1 (PD-1) promotes self-tolerance and inhibits immune responses by modulating the T-cell function. The interaction between PD-1 and programmed cell death ligand-1 (PD-L1) leads to immune exhaustion, protecting cancer cells from destruction. Here, we computationally designed a novel ligand named 1508 that binds to an unprecedented PD-1 cavity identified by MixMD and defined by amino acid residues Lys78 to Val97. We showed through a set of MD simulations totaling 12.5 µs that ligand 1508 establishes frequent cation-π and hydrogen bonding interactions with amino acid residues Lys78 and Arg86, respectively, and stabilizes the PD-1 C'D loop in a conformation that does not favor PD-1-PD-L1 complex formation. This study highlights the power of MixMD in exposing new cavities prone to protein-protein complex inhibition and establishes the basis for the design of new molecules that target the PD-1 C'D cavity as an alternative for exploring the modulation of the PD-1-PD-L1 complex in cancer therapy.

Guidelines To Predict Binding Poses of Antibody-Integrin Complexes.

Integrins are cell adhesion receptors that transmit bidirectional signals across the plasma membrane. They are noncovalently linked heterodimeric molecules consisting of two subunits and act as biomarkers in several pathologies. Thus, according to the increase of therapeutic antibody production, some efforts have been applied to produce anti-integrin antibodies. Here, we purposed to evaluate methods of generation and identification of the binding pose of integrin-antibody complexes, through protein-protein docking and molecular dynamics simulations, and propose a strategy to assure the confidence of the final model and avoid false-positive poses. The results show that ClusPro and GRAMM-X were the best programs to generate the native pose of integrin-antibody complexes. Furthermore, we were able to recover and to ensure that the selected pose is the native one by using a simple rule. All complexes from ClusPro in which the first model had the lowest energy, at least 5% more negative than the second one, were correctly predicted. Therefore, our methodology seems to be efficient to avoid misranking of wrong poses for integrin-antibody complexes. In cases where the rule is inconclusive, we proposed the use of heated molecular dynamics to identify the native pose characterized by RMSDi <0.5 nm. We believe that the set of methods presented here helps in the rational design of anti-integrin antibodies, giving some insights on the development of new biopharmaceuticals.