Jul 2026· Current Opinion in Chemical Biology· Vol 94, pp.
102726
· 0 citations· 34 references
Medicine
TL;DR
It is proposed that systematic integration of NP-inspired scaffolds with modern discovery platforms and computational tools, represents the most productive current framework for targeting disease-relevant complexes previously considered inaccessible, expanding the boundary of druggability across oncology, cardiovascular, and metabolic medicine.
Abstract
Natural product (NP)-inspired scaffolds occupy a privileged position in interface-centric drug discovery, as their preorganised three-dimensional architectures, multivalent contact surfaces, and covalent anchoring potential enable them to engage extended, topographically complex protein-protein and protein-nucleic acid interfaces. This review argues that modern platforms are now making these interactions systematically accessible, shifting NP drug discovery from occupancy-based inhibition toward interface stabilisation and induced proximity at targets previously considered undruggable. We evaluate how trillion-scale DNA-encoded libraries, RaPID-based macrocycle selection, and covalent chemoproteomics interrogate vast chemical spaces to identify compounds with non-classical binding modes relevant to proximity-driven therapeutic discovery, assessing both their demonstrated strengths and current limitations in the context of interface-centric therapeutics. We further discuss how AI-based tools support network prioritisation, interface hotspot prediction, and ternary complex modelling, while noting that computational predictions require independent experimental validation and do not yet replace biochemical evidence. We propose that systematic integration of NP-inspired scaffolds with modern discovery platforms and computational tools, represents the most productive current framework for targeting disease-relevant complexes previously considered inaccessible, expanding the boundary of druggability across oncology, cardiovascular, and metabolic medicine.
The Fragment Molecular Orbital Sygnature Platform (FMO-SP) integrates quantum mechanics with automated workflows and intuitive visual analytics to provide residue-level, quantified energetic insights, supporting more predictive and resource-efficient drug discovery.
Alexander Heifetz, Girinath G. Pillai, Maryamdokht Taimoory et al.· Methods in molecular biology· 0 citations
Natural cyclic peptides have long served as a rich reservoir of bioactivity, occupying a unique region of the drug space that bridges the gap between small molecules and large biologics, and researchers are rationally engineering next-generation macrocycles, positioning them at the frontier of modern drug development.
Greta Bergamaschi, Giulia Lodigiani, Stefano Gandolfi et al.· Current Opinion in Chemical...· 0 citations
The central theme, conformational analysis, links on-target potency via pre-organization of the bioactive conformation with physics-based physicochemical property prediction with physics-based physicochemical property prediction, highlighting neutral polarity as a key determinant of permeability and exposure.
A proposed validation-aware framework aligns claims with the endpoint examined and prevents computational scores, sensor responses, or concentration traces from being interpreted as proof of affinity, mechanism, or clinical utility.
Alexey Podshibiakin, T. Grigoreva· Journal of Advanced Biotechn...· 0 citations
The ndMG modality represents a highly versatile strategy to unlock the undruggable proteome and is systematically highlighted to highlight their evolving capabilities to modulate oncogenic networks, intervene with immune activity, rectify metabolic signaling, control neurodegenerative trafficking and stress networks, a...
Lin-Feng Li, Jia-Jia Li, Li Yang et al.· Pharmaceuticals· 0 citations
A structural database that systematically maps the complete activation trajectories of pharmaceutically relevant targets, encompassing TS, IS, and all connecting conformational ensembles is presented, offering multiple strategic advantages for drug discovery.