The coarse-grained Martini force field is widely used in biomolecular simulations. Here, we present the refined model, Martini 3 (http://cgmartini.nl), with an improved interaction balance, new bead types, and expanded ability to include specific interactions representing, e.g. hydrogen bonding and electronic polarizability. The new model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.

The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein-ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the wellcharacterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model.

The RNA nucleobase uracil can suffer from photodamage when exposed to UV light, which may lead to severe biological defects. To prevent this from happening in most cases, uracil exhibits an ultrafast relaxation mechanism from the electronically excited state back to the ground state. In our theoretical work, we demonstrate how this process can be significantly influenced using shaped laser pulses. This not only sheds new light on how efficient nature is in preventing biologically momentous photodamage. We also show a way to entirely prevent photorelaxation by preparing a long-living wave packet in the excited state. This can enable new experiments dedicated to finding the photochemical pathways leading to uracil photodamage. The optimized laser pulses we present fulfill all requirements to be experimentally accessible.

Optimal control theory and optimal control experiments are state of the art tools to control quantum systems. Both methods have been demonstrated successfully for numerous applications in molecular physics, chemistry and biology. Modulated light pulses could be realized, driving these various control processes. Next to the control efficiency, a key issue is the understanding of the control mechanism. An obvious way is to seek support from theory. However, the underlying search strategies in theory and experiment towards the optimal laser field differ. While the optimal control theory operates in the time domain, optimal control experiments optimize the laser fields in the frequency domain. This also implies that both search procedures experience a different bias and follow different pathways on the search landscape. In this perspective we review our recent developments in optimal control theory and their applications. Especially, we focus on approaches, which close the gap between theory and experiment. To this extent we followed two ways. One uses sophisticated optimization algorithms, which enhance the capabilities of optimal control experiments. The other is to extend and modify the optimal control theory formalism in order to mimic the experimental conditions.

<div> <div> <div> <p>The computational and conceptual simplifications realized by coarse-grain (CG) models make them an ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field. </p> </div> </div> </div>

Bond cleavage and bond formation are central to organic chemistry. Carbocations play a key role in our understanding of nucleophilic substitution reactions that involve both processes. The precise understanding of the mechanism and dynamics of the photogeneration of carbocations and carbon radicals is therefore an important quest. In particular, the role of electron transfer for the generation of carbocations from the radical pair is still unclear. A quantitative femtosecond absorption study is presented, with ultrabroad probing on selected donor and acceptor substituted benzhydryl chlorides irradiated with 270 nm (35 fs) pulses. The ultrafast bond cleavage within 300 fs is almost exclusively homolytic, thus leading to a radical pair. The carbocations observable in the nanosecond regime are generated from these radicals by electron transfer from the benzhydryl to the chlorine radical within the first tens of picoseconds. Their concentration is reduced by geminate recombination within hundreds of picoseconds. In moderately polar solvents this depletion almost extinguishes the cation population; in highly polar solvents free ions are still observable on the nanosecond timescale. The explanation of the experimental findings requires the microscopic realm of the intermediates to be accounted for, including their spatial and environmental distributions. The distance dependent electron transfer described by Marcus theory is combined with Smoluchowski diffusion. The depletion of the radical pair distribution at small distances causes a temporal increase of the mean distance and the observed stretched exponential electron transfer. A close accord with experiment can only be reached for a broad distribution of the nascent radical pairs. The increase in the inter-radical and inter-ion pair distance is measured directly as a shift of the UV/Vis absorption of the products. The results demonstrate that, at least for aprotic solvents, traditional descriptions of reaction mechanisms based on the concept of contact and solvent-separated pairs have to be reassessed.

Artificial rotary molecular motors convert energy into controlled motion and drive a system out of equilibrium with molecular precision. The molecular motion is harnessed to mediate the adsorbed protein layer and then ultimately to direct the fate of human bone marrow–derived mesenchymal stem cells (hBM-MSCs). When influenced by the rotary motion of light-driven molecular motors grafted on surfaces, the adsorbed protein layer primes hBM-MSCs to differentiate into osteoblasts, while without rotation, multipotency is better maintained. We have shown that the signaling effects of the molecular motion are mediated by the adsorbed cell-instructing protein layer, influencing the focal adhesion–cytoskeleton actin transduction pathway and regulating the protein and gene expression of hBM-MSCs. This unique molecular-based platform paves the way for implementation of dynamic interfaces for stem cell control and provides an opportunity for novel dynamic biomaterial engineering for clinical applications.