AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The fragment molecular orbital (FMO) quantum mechanics method offers a comprehensive and computationally inexpensive means of identifying the strength and the chemical nature of the molecular interactions taking place at the protein-protein interface of large biomolecular systems.
A framework for accelerating the development of next-generation PPI therapeutics is provided by connecting interface architecture with optimal inhibitor modality and discovery strategy, revealing clear links between interface topology and inhibitor discovery strategies.
ProtLID2.0 is presented, a residue-specific pharmacophore framework that generates coordinate-based interaction preferences from molecular dynamics simulations of single-residue probes at receptor interfaces and uses these preferences to score docked complexes and identify cognate ligands.
The dysregulation of protein–protein interactions (PPIs) in disease states is well established, yet they are challenging to target, owing to the large surface area and featureless nature of protein binding interfaces. For targeting helix-mediated interactions, α-helix mimetics present a promising strategy. These are versatile small molecule scaffolds, capable of mimicking the hotspot residues on an α-helix. A wide range of such scaffolds have been reported, yet their target protein selectivity in the context of a whole proteome requires further exploration. Here, we report the affinity-based protein profiling of three structurally distinct classes of α-helix mimetics, N-substituted oligobenzamides, pyrrolopyrimidines, and oxopiperazines. This represents the first direct cross-comparison of different helix mimetic scaffolds, revealing significant differences in proteome-wide selectivity.
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