In silico approaches for predicting natural compounds with therapeutic potential and vaccine candidates against Streptococcus equi.

Overview

• This study investigates the genome of Streptococcus equi bacteria to identify natural compounds and vaccine targets that could be effective against infections in horses, particularly equine strangles.
• It uses computational techniques to find proteins common to bacterial strains but absent in horses, aiming to find drug targets and potential vaccine components.

Background and Problem

• Streptococcus equi is a Gram-positive bacterium causing equine strangles, a respiratory disease in horses.
• Other related bacterial subspecies also cause disease and pose zoonotic risks, meaning they can potentially infect other species including humans.
• Effective treatment and preventive vaccines are lacking, and penicillin treatment is complicated by the emergence of multidrug-resistant strains.
• Increasing prevalence of infection worldwide emphasizes the need for novel therapeutic and preventive strategies.

Research Objectives

• To identify candidate bacterial proteins as targets for natural drug-like compounds or as vaccine immunogens using genome data from 18 isolates of Streptococcus equi subspecies.
• To select proteins that are:
• Shared among both subspecies sequenced.
• Absent in the equine host (to avoid targeting horse proteins).
• Essential for bacteria survival and involved in virulence (traits that make good targets to disable bacteria or trigger immune response).

Methods

• Protein Selection: From the whole genome sequences, proteins meeting the criteria were identified.
• Drug Target Candidate Proteins: 4 cytoplasmic proteins were chosen for further study with molecular docking.
• Immunogen Candidate Proteins: 6 proteins predicted to function as adhesins (which help bacteria attach to host cells) were proposed as vaccine targets.
• Molecular Docking: The 4 drug target proteins were tested with a large library (5008 compounds) of natural drug-like molecules to find binding partners that could inhibit the proteins.
• Scoring and Ranking: Docked compounds were scored based on binding affinity and hydrogen bond numbers, markers for the strength and stability of interactions.
• Molecular Dynamics Simulation: Used to further validate and evaluate the stability of the best ligand-protein complex over time under simulated physiological conditions.

Key Findings

• The docking yielded the top ten candidate ligands for each of the 4 drug targets.
• The compound named CHFNO, a natural molecule with a distinctive 5-ring structure, showed the highest stability in interaction with the enzyme UDP-N-acetylenolpyruvoylglucosamine reductase (MurB), a protein critical for bacterial cell wall synthesis.
• The six proposed immunogens based on adhesin prediction highlight promising vaccine candidates targeting bacterial attachment and virulence mechanisms.

Significance and Future Directions

• The study presents potential new natural compounds for therapeutic development against equine strangles, addressing the challenge of drug resistance.
• Identifies vaccine candidate proteins that may elicit protective immune responses to prevent infection.
• The computational approach accelerates the discovery process by narrowing down targets and compounds before experimental validation.
• Offers a foundation for further laboratory and clinical investigations to develop effective treatments and vaccines for Streptococcus equi infections.