Periodic Reporting for period 2 - ELNANO (Charge transport in nanochannels)
Okres sprawozdawczy: 2021-12-01 do 2022-11-30
Accurate prediction of macromolecular structure and function is a key challenge in many fields, from designing new nanomaterials to drug discovery. Nanoparticles, nanochannels, proteins, and other biomolecules are typically charged, and this charge dictates their interactions and function. It is intuitively expected that two identical particles will contain the same charge. However, we find that when multiple particles aggregate, a spontaneous and global redistribution of charge can cause initially identical particles to take on different roles.
Molecules and particles commonly attain charge via dissociation or association of ions – the same process that governs acid and base reactions. However, this process of charge transfer between the molecules and the solution is perturbed when other charged entities are present in the vicinity, for example, a DNA molecule can alter the charge distribution of a nearby protein. We have wondered to what extent these perturbations could add up, leading to possible new modes of interactions and new structures.
To find out, we implemented a simulation method that dynamically resolves these “charge regulation” effects. We expected that the charge will redistribute within individual particles, which has been proposed using theoretical arguments already in the 1950s. Surprisingly, however, the simulations predict that initially, identical nanoparticles will spontaneously exchange charge among themselves, resulting in disparate charging and the corresponding formation of asymmetric aggregates. Following this result, we conclude that charge regulation must be accounted for to accurately predict the structure formation of molecular and nano-scale systems. Our simulation method should significantly improve the accuracy of calculations used for drug discovery and the design of nanomaterials.
The computational method that dynamically simulates charge-regulation effects has been made freely accessible as a module for the LAMMPS molecular dynamics simulation package at "https://docs.lammps.org/fix_charge_regulation.html". Moreover, the simulation method is currently being implemented within Ludwig Lattice-Boltzmann software to enable accurate predictions of charge transport in nano-channels.
Molecules and particles commonly attain charge via dissociation or association of ions – the same process that governs acid and base reactions. However, this process of charge transfer between the molecules and the solution is perturbed when other charged entities are present in the vicinity, for example, a DNA molecule can alter the charge distribution of a nearby protein. We have wondered to what extent these perturbations could add up, leading to possible new modes of interactions and new structures.
To find out, we implemented a simulation method that dynamically resolves these “charge regulation” effects. We expected that the charge will redistribute within individual particles, which has been proposed using theoretical arguments already in the 1950s. Surprisingly, however, the simulations predict that initially, identical nanoparticles will spontaneously exchange charge among themselves, resulting in disparate charging and the corresponding formation of asymmetric aggregates. Following this result, we conclude that charge regulation must be accounted for to accurately predict the structure formation of molecular and nano-scale systems. Our simulation method should significantly improve the accuracy of calculations used for drug discovery and the design of nanomaterials.
The computational method that dynamically simulates charge-regulation effects has been made freely accessible as a module for the LAMMPS molecular dynamics simulation package at "https://docs.lammps.org/fix_charge_regulation.html". Moreover, the simulation method is currently being implemented within Ludwig Lattice-Boltzmann software to enable accurate predictions of charge transport in nano-channels.
We have developed and implemented a hybrid Monte Carlo–molecular dynamics computational method that simulates the charge-regulation effects of particles and molecules in aqueous solutions.
Incorporation of charge regulation in theoretical and computational models requires dynamic, configuration-dependent recalculation of surface charges and is therefore typically approximated by assuming constant net charge on particles. Various computational methods exist that address this. We presented an alternative, particularly efficient charge regulation Monte Carlo method (CR-MC), which explicitly models the redistribution of individual charges and accurately samples the correct grand-canonical charge distribution. In addition, we provided an open-source implementation in the LAMMPS molecular dynamics (MD) simulation package, resulting in a hybrid MD/CR-MC simulation method. This implementation is designed to handle a wide range of implicit-solvent systems that model discreet ionizable groups or surface sites. The computational cost of the method scales linearly with the number of ionizable groups, thereby allowing accurate simulations of systems containing thousands of individual ionizable sites. We use the CR-MC method to quantify the effects of charge regulation on the nature of the polyelectrolyte coil–globule transition and on the effective interaction between oppositely charged nanoparticles. The method is freely available for download at "https://docs.lammps.org".
In addition, we worked on multiple other interesting projects that led to high-profile publications: (i) Self-assembly of hybrid nanocrystals, (ii) Controlling Superselectivity of Multivalent Interactions with Cofactors and Competitors, (iii) Amplification free detection of SARS-COV-2, (iv) Predicting nanoscale crystallization.
Moreover, we worked on additional topics that are going to be published within the next year: (i) Phase Separation and Ripening in a Viscoelastic Material, (ii) Thermodynamics stability of self-assembled Moire patterns, (iii) phase transitions in nano-channel flow.
Incorporation of charge regulation in theoretical and computational models requires dynamic, configuration-dependent recalculation of surface charges and is therefore typically approximated by assuming constant net charge on particles. Various computational methods exist that address this. We presented an alternative, particularly efficient charge regulation Monte Carlo method (CR-MC), which explicitly models the redistribution of individual charges and accurately samples the correct grand-canonical charge distribution. In addition, we provided an open-source implementation in the LAMMPS molecular dynamics (MD) simulation package, resulting in a hybrid MD/CR-MC simulation method. This implementation is designed to handle a wide range of implicit-solvent systems that model discreet ionizable groups or surface sites. The computational cost of the method scales linearly with the number of ionizable groups, thereby allowing accurate simulations of systems containing thousands of individual ionizable sites. We use the CR-MC method to quantify the effects of charge regulation on the nature of the polyelectrolyte coil–globule transition and on the effective interaction between oppositely charged nanoparticles. The method is freely available for download at "https://docs.lammps.org".
In addition, we worked on multiple other interesting projects that led to high-profile publications: (i) Self-assembly of hybrid nanocrystals, (ii) Controlling Superselectivity of Multivalent Interactions with Cofactors and Competitors, (iii) Amplification free detection of SARS-COV-2, (iv) Predicting nanoscale crystallization.
Moreover, we worked on additional topics that are going to be published within the next year: (i) Phase Separation and Ripening in a Viscoelastic Material, (ii) Thermodynamics stability of self-assembled Moire patterns, (iii) phase transitions in nano-channel flow.
Accurate prediction of macromolecular structure and function is a key challenge in many fields, from designing new nanomaterials to drug discovery. Nanoparticles, proteins, and other biomolecules typically carry electrostatic charges, and this charge controls what types of structures nanoparticles form to create new materials and how proteins function in biological environments. By developing a charge-regulation method we found that when two or more identical nanoparticles, proteins, or other biomolecules come together, there’s a spontaneous and global redistribution of charge that can cause initially matching particles to take on different charges in a cluster. The collective effect can qualitatively change the structure of nanoscale systems.
Importantly, this finding shows that charge regulation – the mechanism responsible for the change in particle charge – cannot be ignored when making predictions about how the structure will react.
The changing of charges is a complicated, often erratic process. When one particle approaches a second particle the surface charges on both particles change. That then modifies how the new item attracts or repels a third particle, which in turn changes the charge of the first two particles, and so on.
Often, molecules and particles attain charge through the dissociation or association of ionic groups on their surface – the same process that governs acid and base reactions. However, this process is perturbed when other charged entities are in the vicinity, such as a DNA molecule that can alter the charge distribution on a nearby protein. Luijten and Curk wondered to what extent these perturbations could add up, leading to possible new modes of interactions and new structures.
We implemented a new computer simulation method that dynamically resolves these charge regulation effects and found that initially identical nanoparticles spontaneously exchange charge among each other, resulting in disparate charging and the corresponding formation of asymmetrically shaped clusters. Our simulation method has the potential to significantly improve the accuracy of calculations used for drug discovery and the design of new nanomaterials.
We made the simulation method freely available in widely used open-source software [https://github.com/lammps/lammps] to make it easily accessible to other scientists.
Moreover, due to the covid pandemic, we focused on understanding super selectivity and detection of pathogen DNA. This work led to the development of a new method for amplification-free multivalent detection of viral DNA, which could enable faster detection of pathogen DNA compared to current methods that rely on PCR amplification.
Importantly, this finding shows that charge regulation – the mechanism responsible for the change in particle charge – cannot be ignored when making predictions about how the structure will react.
The changing of charges is a complicated, often erratic process. When one particle approaches a second particle the surface charges on both particles change. That then modifies how the new item attracts or repels a third particle, which in turn changes the charge of the first two particles, and so on.
Often, molecules and particles attain charge through the dissociation or association of ionic groups on their surface – the same process that governs acid and base reactions. However, this process is perturbed when other charged entities are in the vicinity, such as a DNA molecule that can alter the charge distribution on a nearby protein. Luijten and Curk wondered to what extent these perturbations could add up, leading to possible new modes of interactions and new structures.
We implemented a new computer simulation method that dynamically resolves these charge regulation effects and found that initially identical nanoparticles spontaneously exchange charge among each other, resulting in disparate charging and the corresponding formation of asymmetrically shaped clusters. Our simulation method has the potential to significantly improve the accuracy of calculations used for drug discovery and the design of new nanomaterials.
We made the simulation method freely available in widely used open-source software [https://github.com/lammps/lammps] to make it easily accessible to other scientists.
Moreover, due to the covid pandemic, we focused on understanding super selectivity and detection of pathogen DNA. This work led to the development of a new method for amplification-free multivalent detection of viral DNA, which could enable faster detection of pathogen DNA compared to current methods that rely on PCR amplification.