In silico structure-guided fragment-based identification of <i>Klebsiella pneumoniae</i> aspartate semialdehyde dehydrogenase inhibitors
Hospital-acquired infections (HAIs) have been a cause of high global mortality rates. Klebsiella pneumoniae (Kp), a Gram-negative bacterium, is associated with HAIs. The enzyme aspartate β-semialdehyde dehydrogenase (ASADH) participates in the biosynthetic pathway responsible for generating essential amino acids and other key metabolites. Due to the absence of this pathway in mammals, the design of inhibitors to Kp ASADH represents a viable therapeutic approach to prevent HAIs. This study involves developing inhibitors through de novo fragment-based drug discovery. The active site was identified with respect to the binding of the two reported ASADH inhibitors, 4-nitro-2-phosphono benzoic acid and (S)-methyl L-cysteine sulfoxide. Molecular docking followed by Lipinski’s RO5 was utilised in filtering these molecules. The Kp ASADH-screened eleven hit molecular complexes were further studied by molecular dynamics (MD) simulations. Post MD analysis and binding free energy calculations revealed the stability of the four hit molecules (I-IV). These analyses revealed the flexibility of the A188-V197 segment of the helical subdomain. Binding energy calculations revealed Hit- IV to be the best binder, whereas steered MD simulations performed on the final MD structures illustrated the greater stability of Hit-II. The protein-structure network analyses of the minimum energy structures of the apo and complexed Kp ASADH explained the residueresidue interaction networks. A change in the community architecture, metapath, degree and betweenness centrality measures for all the molecular systems illustrated the change in interresidue communication networks within the protein on complexation. These four hit molecules can be identified as potential leads for the treatment of HAIs.
Authors
- B.M. Ganesh
- Lalitha Guruprasad (ORCID: https://orcid.org/0000-0003-1878-6446)
- Adrija Banerjee
Institutions
- Twitter (United States) (US)
Publication Details
- Journal
- Journal of Computational Biophysics and Chemistry
- Published
- 2026-05-08
- DOI
- https://doi.org/10.1142/s2737416526500870
- Primary Topic
- Enzyme Structure and Function
- Type
- article
- Field-Weighted Citation Impact
- 0.00