Periodic Reporting for period 2 - PREDACTED (Predictive computational models for Enzyme Dynamics, Antimicrobial resistance, Catalysis and Thermoadaptation for Evolution and Design)
Berichtszeitraum: 2023-04-01 bis 2024-09-30
The aim of PREDACTED is to use molecular simulations to understand and predict enzyme catalytic activity, ranging from how it depends on temperature (relevant for developing ‘green’ biocatalysts for sustainable industry) to analysing the ability of bacterial enzymes to breakdown antibiotics (to help combat antimicrobial resistance). Bacterial antibiotic resistance is a serious and growing global problem. It threatens to make some infections untreatable. Resistance to carbapenems, so-called last resort antibiotics, is a particular concern as recognised e.g. by the World Health Organisation. Carbapenems are widely used to treat infections by bacteria that resist other beta-actam antibiotics (such as penicillin), but increasingly bacteria have developed the ability to resist carbapenems. Enzymes (called carbapenemases) that break down carbapenems are a primary cause of this resistance. Use of antibiotics drives the evolution of these enzymes. We model carbapenemases to understand how they break down carbapenems. We investigate the structure and motions of these enzymes, and model the chemical reactions that destroy carbapenems within them. By comparing carbapenemases with similar enzymes that do not have this ability, we identify and analyse, at the atomic level, the features that cause this resistance. This will help in the design of new antibiotics and of new drugs to block carbapenemases. We combine simulations with experiments to test our findings. We investigate the effects of evolution at the level of individual proteins, to understand how it alters enzyme structure and dynamics to achieve the ability to catalyse a specific chemical reaction. The role of dynamics in catalysis is central: evolution changes the way that enzymes fluctuate, but how this affects catalysis is not clear. Enzymes do not behave like simple chemical catalysts: instead of becoming more and more active as temperature increases, they lose activity at higher temperatures. It used to be thought this was because they lost their functional shape, but it is now clear that the loss of activity is for more subtle reasons. Small changes enzyme can significantly change an enzyme’s optimum temperature for reasons that are not well understood. Being able to design such changes opens a route to developing catalysts that work at low temperatures, potentially saving energy in industrial processes. Simulations allow us to probe these questions and to test fundamental theories of enzyme evolution.
We have studied a wide range of enzymes. In the antibiotic resistance area, we began by modelling the breakdown of meropenem (a carbapenem) by 8 different bacterial enzymes. We showed that modelling of the reactions in these enzymes gave results that agree well with experiment: our models correctly show which enzymes break down the antibiotic quickly (causing resistance to carbapenems) and which do not. This shows that our methods can accurately predict the activity of different enzymes. By analysing the chemical reactions in the enzyme, we identified the molecular features that allow the reaction to happen quickly. We showed that several factors combined are needed for an enzyme to be able to break down carbapenems quickly. We then focused on one carbapenemase enzyme, KPC-2, which causes resistance to many beta-lactam antibiotics. Working with experiment, we determined the structure of this enzyme with several different beta-lactam antibiotics. We showed that the mobility of a particular part of the enzyme correlates with its ability to break down different antibiotics. We also found that antibiotics can bind to the enzyme in different chemical forms. Modelling showed that these different chemical forms react at very different rates. This combination of experiments and simulations reveal the factors that allow this enzyme to break down a wide range of different antibiotics. The multiscale modelling methods that we use in PREDACTED allow us to see how chemical bonds are broken and formed. We can create detailed models of unstable species that are formed during a chemical reaction in an enzyme, such as reaction intermediates and transition states. These unstable structures cannot be studied directly by experiment because of their very short lifetimes. Modelling not only reveals their structures but allows us to calculate their properties and interactions in enzyme active sites where reactions happen. We showed that the electric field during the reaction is a crucial physical factor in determining how quickly the antibiotic is broken down. This detailed insight should help in the design of enzyme inhibitors to block breakdown and protect antibiotics. In the area of temperature dependence, working with experiments we showed that the temperature dependence of enzyme activity is more complex than previously realised. This fundamental insight has important implications for understanding enzyme catalysis generally and in the engineering of biocatalysts.
We have shown that molecular simulations can predict the ability of enzymes to break down different antibiotics, distinguishing enzymes that destroy carbapenems rapidly (and so cause bacterial resistance to these ‘last resort’ antibiotics) from enzymes that do not. By analysing the chemical reactions of carbapenem breakdown in different bacterial enzymes, we showed that a fundamental physical property, the electric field, is a crucial factor in determining how fast the breakdown reaction happens. This insight will help in predicting and combating bacterial antibiotic resistance, e.g. in the development of new antibiotics and of inhibitors to block the enzymes that break down antibiotics. We have made these tools freely available. Combining simulations with experiments, we also showed what factors are responsible for the antibiotic breakdown ability of an enzyme that is a globally significant cause of antibiotic resistance.
Another focus of PREDACTED is the temperature dependence of enzyme-catalysed reactions. We have shown (combining simulations with experiments) that the factors that make enzymes different from simple chemical catalysts (in particular, the non-linearity of their temperature dependence) are complex, but can be understood and modelled. Our models explain previously puzzling experimental observations. They provide a new conceptual framework for understanding how enzymes evolve to function at different temperatures. This is fundamentally important in how organisms adapt to ecological niches, and how they may respond to climate change. Our framework also provides a route to engineering enzymes for activity at low temperatures, as biocatalysts for low temperature, less energy-intensive processes for biotechnology and industry.
We have also applied the simulation tools we are developing (including non-equilibrium molecular dynamics simulations) to proteins from the SARS-CoV-2 virus. With experimental collaborators, and as part of an international consortium, we investigated the virus spike protein and identified new features relating to function and infectivity. For the SARS-CoV-2 main protease, we found features relevant to drug resistance. We apply high performance and cloud computing. We have developed new approaches to combine simulation and interactive virtual reality to investigate binding to proteins. We are applying all of these methods to understand, predict and design enzyme activity and are testing these predictions experimentally.
Another focus of PREDACTED is the temperature dependence of enzyme-catalysed reactions. We have shown (combining simulations with experiments) that the factors that make enzymes different from simple chemical catalysts (in particular, the non-linearity of their temperature dependence) are complex, but can be understood and modelled. Our models explain previously puzzling experimental observations. They provide a new conceptual framework for understanding how enzymes evolve to function at different temperatures. This is fundamentally important in how organisms adapt to ecological niches, and how they may respond to climate change. Our framework also provides a route to engineering enzymes for activity at low temperatures, as biocatalysts for low temperature, less energy-intensive processes for biotechnology and industry.
We have also applied the simulation tools we are developing (including non-equilibrium molecular dynamics simulations) to proteins from the SARS-CoV-2 virus. With experimental collaborators, and as part of an international consortium, we investigated the virus spike protein and identified new features relating to function and infectivity. For the SARS-CoV-2 main protease, we found features relevant to drug resistance. We apply high performance and cloud computing. We have developed new approaches to combine simulation and interactive virtual reality to investigate binding to proteins. We are applying all of these methods to understand, predict and design enzyme activity and are testing these predictions experimentally.