Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterial infection that has become resistant to most of the antibiotics used to treat conventional staphylococcal infections. Bruce Donald, a computer scientist at Duke University, and a collaborator at the University of Connecticut are working on a new enzyme inhibitor to combat MRSA.In the study published in PLOS Computational BiologyThe team discovered how a single small mutation can make a big difference in efficacy.
They investigated dihydrofolate reductase (DHFR), an enzyme targeted by antibiotics to fight MRSA. Drugs that block DHFR act like tablets and keys. They bind to MRSA enzymes. MRSA has a specific three-dimensional structure that allows only exactly matching molecules to attach to them.
Mutations change the structure of bacterial enzymes and can cause the drug to lose its effectiveness. The F98Y mutation is a well-known resistance mutation. A slight change in the 98th amino acid of the DHFR enzyme changes phenylalanine to tyrosine. “These two amino acids are structurally similar, but mutations have a significant impact on the effectiveness of the inhibitor,” said Graham Holt, a graduate student at Donald Labs. In essence, it changes the lock.
Dr. Pablo Gainsa, a former graduate student in Donald’s lab, said that OSPREY, a series of programs developed in Donald’s lab for computational structure-based protein design, should be able to predict this mutation. I thought. But he couldn’t. After knocking down the hypothesis after the hypothesis and understanding why this mutation could not be predicted, he returned to investigate the initial structure.
“When we looked at the electron density data from crystallographers, we found something strange,” said Donald. In determining the structure of the F98Y variant, crystallographers used computer programs to invert or mirror the chirality of the NADPH cofactor to better adapt it. The “inverted” species they discovered through analysis are present in laboratory experimental conditions and probably in vivo.
“We used OSPREY to discover this inverted chirality, which we believe was caused by the F98Y mutation,” says Donald. As with two-factor authentication, single enzyme mutations and inverted cofactors appear to collude to avoid inhibitors.
This “chiral avoidance” changes the structural basis of resistance. But now, Donald and his colleagues know not only how a single small mutation changed the lock, but also the structure needed to make a better key, a better drug inhibitor.
“this is, Enzyme It utilizes the chirality of cofactors to avoid inhibitors. Seeing this happening helps to inform computational strategies for developing better inhibitors. “
Donald Lab showed it by taking a flip Chirality When taken into account, OSPREY’s predictions are in close agreement with experimental measurements of inhibitor efficacy. They collaborated with collaborators at the University of Connecticut to conduct biochemical experiments, test theories, and provide structural evidence.
“This is just the beginning of the story,” said Donald. “The discovery of chiral avoidance should be more resilient. Inhibitor: Better drug design. Currently, most drug designs are responsive and awaiting resistance. medicine We use our algorithms to predict resistance for proactive design, “says Donald.
Siyu Wang et al, Chiral Avoidance and Stereospecific Antimetabolite Resistance in Staphylococcus aureus, PLOS Computational Biology (2022). DOI: 10.1371 / journal.pcbi.1009855
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How Super Bugs Use Mirror Images to Create Antibiotic Resistance
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