In summary, we utilized the strengths of existing network/pathway tools and databases to gain insight into processes related to childhood leukemia subtypes; T-ALL and B-ALL have distinct molecular interaction patterns visible from various systems levels, including gene, gene set, molecular pathway, and gene networks.
Finally, computational studies allowed clarifying at molecular level the interaction pattern established by the compounds with KDR, highlighting key stable cation-π interactions, and thus providing the basis for further designing novel inhibitors.
The number of rotatable bonds (#RotB) was chosen as the main descriptor for the ligand classification, since variation of dihedral angles along rotatable bonds allows a compound to adopt distinct molecular shapes and spatial distribution of its functional groups, which play the key role for molecular recognition (compound selectivity) and interaction pattern with macromolecular targets.
Advances in biomolecular research, coupled with rapidly increasing availability of information from multiple genome sequencing initiatives, global gene expression patterns, large scale molecular interaction experiments and genome wide association studies, have led to an exponential increase in biological data.
Here, we report the identification of a synthetic chalcone in our in vitro assays with promastigote cells from Leishmania amazonensis, its biological activity in animal models, and docking followed by molecular dynamics simulation to investigate the molecular interactions and structural patterns that are crucial to achieve the inhibition complex between this compound and G3PDH.
The focus is on mining the expert knowledge of individual enzymes studies by different laboratories from the literature to identify molecular interactions and regulatory patterns of each enzyme (e.g. feedback and allosteric regulation).
Multiple studies have observed the hourglass pattern across diverse biological processes, including transcriptome divergence, transcriptome age, molecular interaction, and evolutionary selective constraints.
Despite their apparent universality, it proved difficult to derive biological conclusions from the patterns discovered in these initial global statistical analyses of molecular interaction networks.
