Channelrhodopsin-2 (ChR2) is a light-gated ion channel widely used in optogenetics, a technique that enables precise control of neuronal activity by genetically engineering light-sensitive proteins into cell membranes. This protein exists in dimeric form, with each monomer containing a retinal Schiff base (RSB) moiety covalently bonded that undergoes trans-cis isomerization upon light absorption. However, the limited penetration depth of visible light in biological tissues motivates the use of multiphoton-absorption techniques, which enhance tissue penetration, improve focality, and reduce phototoxicity, thereby offering a promising alternative for optogenetic applications. In this paper, we present a fully atomistic multiscale methodology for computing the one-, two-, and three-photon absorption spectra of ChR2, where the protein, lipid bilayer, and solvent are explicitly considered throughout the workflow. This methodology integrates classical molecular mechanics (MM) molecular dynamics (MD), quantum mechanics/molecular mechanics (QM/MM)-MD, and fragment-based polarizable embedding (PE) to derive environment-specific PE potentials from the explicit protein-lipid-solvent environment. The final step in the methodology is to use these potentials to compute accurate spectra via PE-time-dependent density functional theory (PE-TD-DFT). Validation against experimental one-photon absorption spectra demonstrates excellent agreement. For the first time, we report the theoretical two- and three-photon absorption in ChR2, albeit without direct experimental comparison. We compare the multiphoton absorption (MPA) spectra where the two RSB moieties are sampled using classical MD and QM/MM-MD, respectively. The resulting spectral differences are attributed to variations in key structural parameters that we analyze and document.

Targeting the Frizzled family (FZD1-10) of WNT receptors pharmacologically has, despite substantial therapeutic potential, proven difficult. Given an almost complete lack of validated, effective small molecules targeting FZDs, no putative ligand binding site has so far been identified. In order to target FZD7, a potential target for the treatment of intestinal tumors, we combine an approach of adapted docking setups and large molecular library docking screens, identifying compound C407. Applying pharmacological assays, genetically-encoded biosensors, site-directed mutagenesis, cryo-electron microscopy and molecular dynamics simulations, the compound binding site in the core of the seven transmembrane bundle is validated and C407 is confirmed as a negative allosteric modulator of WNT-induced and FZD-mediated WNT/beta-catenin signaling. In summary, we provide here the proof-of-principle that targeting FZDs with small molecule compounds is possible and effective. Future hit optimization and functional validation in disease-relevant in vitro and in vivo models will pave the way towards clinical exploration.

Oceans are essentially an electrolyte solution. The experimental study of physical and chemical processes occurring in oceans remains challenging, so molecular dynamics simulations may be of great help. We have recently demonstrated that simulations using a state-of-the-art force field can accurately describe the thermophysical properties of seawater by employing a detailed chemical model of the solution. Here, we extend our previous work by investigating additional properties that require simulations on larger samples and time length scales. First, the extended time and size scales of our simulations allow for a relatively precise determination of the electrical conductivity, a fundamental property of seawater for which accurate experimental data are available, serving as a further test of the employed force field. Second, the incorporation of CO2 into the sample enables us to evaluate its diffusion coefficient . No experimental measurements or computational simulations have yet provided estimates of carbon dioxide diffusivity at salinity levels and compositions representative of actual oceanic environments. To validate our results, we have also determined in pure water. Our simulation results show excellent agreement with experimental data in pure water, which reinforces our confidence in the predicted CO2 diffusivity in seawater. This study provides a rigorous test of the reliability of the Madrid-2019 force field (together with TraPPE for CO2) in saline environments. From this perspective, relevant challenges can be addressed, such as the sink of atmospheric carbon dioxide into the deeper ocean, CO2 sequestration in deep saline aquifers, and seawater freezing (for desalination purposes).

Protein deposits are common hallmarks of several neurodegenerative diseases, including Alzheimer’s disease (AD), and ligands that selectively detect specific protein aggregates are crucial. Herein, we investigated the molecular requirements of a thiophene-based ligand, denoted HS-276, for selective detection of Aβ deposits in human brain tissue sections with AD pathology. The staining of Aβ deposits was altered when replacing the terminal thiophene moiety with other heterocyclic moieties. In addition, when changing the central thiophene moiety of the ligand to a phenylene, a quinoxaline, or a benzothiadiazole moiety, the staining of Aβ aggregates was completely abolished, verifying that specific molecular interactions between these ligands and the aggregates were required. The experimental observations were also verified by theoretical calculations of the ligands’ binding mode towards Aβ filaments. Our findings provide chemical insights for developing ligands that selectively target Aβ deposits and highlight the importance of certain chemical requirements for achieving a selective ligand, such as HS-276, for detecting Aβ deposits in sporadic AD. We foresee that these findings might aid in creating novel agents for clinical imaging of Aβ aggregates in AD.

Being a program written primarily in Python that strictly adheres to modern object-oriented software engineering and parallel programming practices, VeloxChem is shown to be suitable for the development of (semi)automatized workflows that extend its scope from first-principles quantum chemical purism to hybrid quantum-classical interoperability and some degree of semiempiricism. Methods are presented for building complex systems such as metal-organic frameworks, constructing molecular mechanics and interpolation mechanics force fields, conformer searches, system solvation, determining free energies of solvation, and determining free energy profiles of reaction pathways using the empirical valence bond method. The implementations are made intuitive with opportunities for interactive plotting and 3D molecular structure illustrations through the use of Jupyter notebooks.

We present a workflow, benchmarks, and applications to provide a roadmap for simulating harmonic IR and Raman spectra for solute-solvent systems by employing a polarizable-embedding quantum-mechanics (PE-QM) approach. This multiscale modeling scheme divides the system into a central core region described by quantum-mechanical methods and an environment region described through the fragment-based polarizable embedding (PE) model. The workflow involves generating representative structures, calculating properties, and postprocessing data. Benchmark calculations quantify errors introduced by some of the key approximations used in our approach and discuss its strengths and weaknesses. Finally, we apply the workflow to acetone in three different solvents, comparing simulated spectra to experimental results to further evaluate our approach and identify potential weaknesses. Accurate simulations of solute-solvent systems are an important step toward modeling more complex molecular systems with a fragment-based PE approach.

The effect of nuclear vibrations on the electronic eigenvalues and the HOMO-LUMO gap is known for several kinds of carbon-based materials, like diamond, diamondoids, carbon nanoclusters, carbon nanotubes and others, like hydrogen-terminated oligoynes and polyyne. However, it has not been widely analysed in another remarkable kind which presents both theoretical and technological interest: fullerenes. In this article we present the study of the HOMO, LUMO and gap renormalizations due to zero-point motion of a relatively large number (163) of fullerenes and fullerene derivatives. We have calculated this renormalization using density-functional theory with the frozen-phonon method, finding that it is non-negligible (above 0.1 eV) for systems with relevant technological applications in photovoltaics and that the strength of the renormalization increases with the size of the gap. In addition, we have applied machine learning methods for classification and regression of the renormalizations, finding that they can be approximately predicted using the output of a computationally cheap ground state calculation. Our conclusions are supported by recent research in other systems.

The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. lar dynamics (MD) simulations are crucial for capturing processes beyond the reach of classical MD simulations. The advent of exascale computing offers unprecedented opportunities for scientific exploration, not least within life sciences, where simulations are essential to unravel intricate molecular leveraging the immense computational power of exascale computing requires innovative algorithms and software designs. In this context, we discuss the current status and future prospects of multiscale biomolecular simulations on exascale supercomputers with a focus on QM/MM MD. We highlight our own efforts in developing a versatile and high-performance multiscale simulation framework with the aim of efficient utilization of state-of-the-art supercomputers. We showcase its application in uncovering complex biological mechanisms and its potential for leveraging exascale computing.