# Design of Highly Specific Antimicrobial Peptides Targeting the BamA Protein of Candidatus Liberibacter Asiaticus

## TL;DR

This study uses computer modeling to design antimicrobial peptides that target a key protein in a citrus greening disease-causing bacterium.

## Contribution

A novel in silico method for designing peptides with high affinity for the BamA protein of CLas is introduced.

## Key findings

- Three peptides with high affinity for BamA were identified through docking and simulations.
- Two peptides showed antimicrobial activity against a CLas surrogate in vitro.
- Amino acid clusters on BamA were identified as key binding sites for peptide design.

## Abstract

Candidatus Liberibacter asiaticus (CLas)
is a
putative causative agent of Huanglongbing (citrus greening). The unculturable
nature of CLas poses a significant challenge in discovering drugs
against citrus greening. This study presents a novel in silico technique
to design peptides with a high affinity toward the β-barrel
assembly machinery A (BamA) protein, a critical outer membrane component
of CLas vital for bacterial functionality. The technique used in this
study is based on identifying the strongest binding amino acids at
different sites in BamA and linking them using peptide linkers. Initially,
amino acid probes that can emulate amino acid activity in peptide
form were docked using Schrodinger Glide on the target domain of BamA.
Docking results of amino acid probes showed three closely located
clusters on BamA. Peptides were designed by selecting the strongest
binding probes in each cluster and linking them using short peptide
linkers. Initially, 15 peptides were designed, and based on molecular
docking, molecular dynamics simulations, and BioLayer Interferometry,
three peptides with a high affinity toward BamA were identified. Two
of the peptides effectively inhibited Rhizobium grahamii, a CLas surrogate, in in vitro assays, suggesting potential antimicrobial
activity against CLas.