Back

Therapeutic Relevance of NLPA Lipoprotein to Combat Biofilm-Associated infection in Acinetobacter baumannii

Brahma, V. U.; Munagalasetty, S.; Bhandari, V.

2026-05-20 bioinformatics
10.64898/2026.05.18.725845 bioRxiv
Show abstract

Acinetobacter baumannii is a leading multidrug-resistant critical priority pathogen in healthcare settings, where biofilm formation confers survival and antibiotic tolerance. Targeting virulence associated proteins offers an alternative to conventional bactericidal strategies. Here, the inner membrane anchored lipoprotein NLPA, implicated in biofilm associated adaptation, was studied as a putative anti-virulence target using an integrated in silico pipeline and complementing the computational findings. The Alpha fold-derived structure of NLPA served as the basis for virtual screening of approximately 1.6 million compounds, with subsequent prioritization guided by MM/GBSA calculated binding free energies to highlight the top promising candidates. Molecular dynamics simulations demonstrated stable NLPA ligand complexes, as indicated by equilibrated RMSD, low residue fluctuations in the binding region, and persistent interaction networks over time. Pharmacokinetic evaluation indicated that the compounds satisfied Lipinskis Rule of Five and had overall acceptable ADMET characteristics. Two compounds, NLPA-6 and NLPA-3, showed the most favourable predicted binding free energies, suggesting strong and stable interactions within the NLPA binding site. NLPA-3 was evaluated in vitro against A. baumannii to validate the computational outcomes. The compound displayed moderate antibacterial activity with a MIC of 125 g/mL and demonstrated 55.75% inhibition of biofilm formation at 4x MIC. In addition, in macrophage infection studies, NLPA-3 decreased intracellular bacterial survival to 19.25% at 50 g/mL, suggesting that it may disrupt virulence pathways linked to persistence. In whole, these findings identify promising NLPA targeting compounds and support the feasibility of NLPA as an anti-virulence target.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Journal of Chemical Information and Modeling
207 papers in training set
Top 0.3%
18.7%
2
Advanced Science
249 papers in training set
Top 2%
7.2%
3
Frontiers in Microbiology
375 papers in training set
Top 1%
6.3%
4
Nature Communications
4913 papers in training set
Top 29%
6.3%
5
Computational and Structural Biotechnology Journal
216 papers in training set
Top 2%
3.6%
6
Scientific Reports
3102 papers in training set
Top 40%
3.3%
7
PLOS Computational Biology
1633 papers in training set
Top 11%
3.1%
8
Microbiology Spectrum
435 papers in training set
Top 1%
2.7%
50% of probability mass above
9
International Journal of Biological Macromolecules
65 papers in training set
Top 1%
2.1%
10
Journal of Medicinal Chemistry
68 papers in training set
Top 0.5%
2.1%
11
eLife
5422 papers in training set
Top 36%
2.1%
12
Antibiotics
32 papers in training set
Top 0.6%
1.9%
13
Communications Biology
886 papers in training set
Top 6%
1.9%
14
PLOS ONE
4510 papers in training set
Top 50%
1.9%
15
RSC Advances
18 papers in training set
Top 0.6%
1.7%
16
ACS Omega
90 papers in training set
Top 2%
1.7%
17
International Journal of Molecular Sciences
453 papers in training set
Top 7%
1.7%
18
mBio
750 papers in training set
Top 8%
1.5%
19
ACS Infectious Diseases
74 papers in training set
Top 0.8%
1.2%
20
Communications Chemistry
39 papers in training set
Top 0.5%
1.2%
21
ACS Synthetic Biology
256 papers in training set
Top 2%
1.1%
22
JACS Au
35 papers in training set
Top 0.9%
0.9%
23
mSystems
361 papers in training set
Top 7%
0.7%
24
ACS Chemical Biology
150 papers in training set
Top 2%
0.7%
25
Frontiers in Molecular Biosciences
100 papers in training set
Top 5%
0.7%
26
BMC Microbiology
35 papers in training set
Top 2%
0.7%
27
PLOS Pathogens
721 papers in training set
Top 9%
0.7%
28
npj Biofilms and Microbiomes
56 papers in training set
Top 2%
0.7%
29
Microbiome
139 papers in training set
Top 3%
0.6%
30
ACS Pharmacology & Translational Science
40 papers in training set
Top 1%
0.6%