Computational Design of Small-Molecule AtlA Activators to Trigger Self-Lysis in MRSA

Overview

Antibiotic resistance is recognized by the World Health Organization as one of the most globally significant health threats of the 21st century and is estimated to cause about 10 million deaths annually by 2050. Autolysins, such as AtlA, play a crucial role in bacterial cell wall remodeling and division. While traditionally studied as virulence factors, autolysins represent an unexplored class of antibiotic targets—compounds that activate these enzymes could trigger self-degradation of bacterial cells, bypassing resistance mechanisms that inactivate traditional antibiotics. This study employs computational approaches to design and optimize small-molecule activators that enhance AtlA activity in methicillin-resistant Staphylococcus aureus (MRSA). Structural characterization was performed using Protein Data Bank structures and homology modeling via SwissModel, followed by binding site identification with ProFunc and InterProScan, which displayed 4 essential targets on the AtlA Autolysin: ALA 302, ASN 316 and SER 373 residues and the Center of a Regulatory Pocket previously identified by ProFunc. De novo drug design using LEA3D generated a library of activator candidates using user-generated parameters adhering to drug-likeness rules like Lipinski's Rule of Five and Pfizer's MPO Algorithm. Molecular dynamics (MD) simulations using GROMACS assessed binding stability, with energy minimization curves ensuring structural optimization. The system underwent equilibration under NVT and NPT ensembles before a 1 ns production run, analyzing Root Mean Square Deviation (RMSD) and Fluctuation (RMSF) to track structural stability between AtlA and each of the designed ligands. Gibbs free energy values were obtained using MM/PBSA calculations, determining an binding average of -80 kcal/mol for all the designed activators, and ADMET analyses (Absorption, distribution, metabolism, excretion, and toxicity) on SwissADMET were conducted, identifying high-affinity and drug-like activators. This study presents autolysin activation as a groundbreaking strategy for combating MRSA, leveraging bacterial self-destruction to bypass conventional resistance mechanisms and introduce a novel class of antibiotic alternatives.