Mixed Quantum Mechanical/Molecular Mechanical Molecular Dynamics Simulations of Biological Systems in Ground and Electronically Excited States

Novel Insights into the Catalytic Mechanism of Collagenolysis by Zn(II)-Dependent Matrix Metalloproteinase-1

Collagen hydrolysis, catalyzed by Zn(II)-dependent matrix metalloproteinases (MMPs), is a critical physiological process. Despite previous computational investigations into the catalytic mechanisms of MMP-mediated collagenolysis, a significant knowledge gap in understanding remains regarding the influence of conformational sampling and entropic contributions at physiological temperature on enzymatic collagenolysis. In our comprehensive multilevel computational study, employing quantum mechanics/molecular mechanics (QM/MM) metadynamics (MetD) simulations, we aimed to bridge this gap and provide valuable insights into the catalytic mechanism of MMP-1. Specifically, we compared the full enzyme-substrate complex in solution, clusters in solution, and gas-phase to elucidate insights into MMP-1-catalyzed collagenolysis. Our findings reveal significant differences in the catalytic mechanism when considering thermal effects and the dynamic evolution of the system, contrasting with conventional static potential energy surface QM/MM reaction path studies. Notably, we observed a significant stabilization of the critical tetrahedral intermediate, attributed to contributions from conformational flexibility and entropy. Moreover, we found that protonation of the scissile bond nitrogen occurs via proton transfer from a Zn(II)-coordinated hydroxide rather than from a solvent water molecule. Following C-N bond cleavage, the C-terminus remains coordinated to the catalytic Zn(II), while the N-terminus forms a hydrogen bond with a solvent water molecule. Subsequently, the release of the C-terminus is facilitated by the coordination of a water molecule. Our study underscores the pivotal role of protein conformational dynamics at physiological temperature in stabilizing the transition state of the rate-limiting step and key intermediates, compared to the corresponding reaction in solution. These fundamental insights into the mechanism of collagen degradation provide valuable guidance for the development of MMP-1-specific inhibitors.

Molecular dynamics simulations for the structure-based drug design: targeting small-GTPases proteins

INTRODUCTION

Molecular Dynamics (MD) simulations can support mechanism-based drug design. Indeed, MD simulations by capturing biomolecule motions at finite temperatures can reveal hidden binding sites, accurately predict drug-binding poses, and estimate the thermodynamics and kinetics, crucial information for drug discovery campaigns. Small-Guanosine Triphosphate Phosphohydrolases (GTPases) regulate a cascade of signaling events, that affect most cellular processes. Their deregulation is linked to several diseases, making them appealing drug targets. The broad roles of small-GTPases in cellular processes and the recent approval of a covalent KRas inhibitor as an anticancer agent renewed the interest in targeting small-GTPase with small molecules.

AREA COVERED

This review emphasizes the role of MD simulations in elucidating small-GTPase mechanisms, assessing the impact of cancer-related variants, and discovering novel inhibitors.

EXPERT OPINION

The application of MD simulations to small-GTPases exemplifies the role of MD simulations in the structure-based drug design process for challenging biomolecular targets. Furthermore, AI and machine learning-enhanced MD simulations, coupled with the upcoming power of quantum computing, are promising instruments to target elusive small-GTPases mutations and splice variants. This powerful synergy will aid in developing innovative therapeutic strategies associated to small-GTPases deregulation, which could potentially be used for personalized therapies and in a tissue-agnostic manner to treat tumors with mutations in small-GTPases.

PyDFT-QMMM: A modular, extensible software framework for DFT-based QM/MM molecular dynamics

PyDFT-QMMM is a Python-based package for performing hybrid quantum mechanics/molecular mechanics (QM/MM) simulations at the density functional level of theory. The program is designed to treat short-range and long-range interactions through user-specified combinations of electrostatic and mechanical embedding procedures within periodic simulation domains, providing necessary interfaces to external quantum chemistry and molecular dynamics software. To enable direct embedding of long-range electrostatics in periodic systems, we have derived and implemented force terms for our previously described QM/MM/PME approach [Pederson and McDaniel, J. Chem. Phys. 156, 174105 (2022)]. Communication with external software packages Psi4 and OpenMM is facilitated through Python application programming interfaces (APIs). The core library contains basic utilities for running QM/MM molecular dynamics simulations, and plug-in entry-points are provided for users to implement custom energy/force calculation and integration routines, within an extensible architecture. The user interacts with PyDFT-QMMM primarily through its Python API, allowing for complex workflow development with Python scripting, for example, interfacing with PLUMED for free energy simulations. We provide benchmarks of forces and energy conservation for the QM/MM/PME and alternative QM/MM electrostatic embedding approaches. We further demonstrate a simple example use case for water solute in a water solvent system, for which radial distribution functions are computed from 100 ps QM/MM simulations; in this example, we highlight how the solvation structure is sensitive to different basis-set choices due to under- or over-polarization of the QM water molecule's electron density.

MiMiC: A high-performance framework for multiscale molecular dynamics simulations

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.g., CPU/GPU), and keep their setup and execution as close as possible to the original. At the moment, MiMiC offers an efficient implementation of electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) that has demonstrated unprecedented parallel scaling in simulations of large biomolecules using CPMD and GROMACS as QM and MM engines, respectively. However, as it is designed for high flexibility with general multiscale models in mind, it can be straightforwardly extended beyond QM/MM. In this article, we illustrate the software design and the features of the framework, which make it a compelling choice for multiscale simulations in the upcoming era of exascale high-performance computing.

Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment

This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.

The development of the QM/MM interface and its application for the on-the-fly QM/MM nonadiabatic dynamics in JADE package: Theory, implementation, and applications

Understanding the nonadiabatic dynamics of complex systems is a challenging task in computational photochemistry. Herein, we present an efficient and user-friendly quantum mechanics/molecular mechanics (QM/MM) interface to run on-the-fly nonadiabatic dynamics. Currently, this interface consists of an independent set of codes designed for general-purpose use. Herein, we demonstrate the ability and feasibility of the QM/MM interface by integrating it with our long-term developed JADE package. Tailored to handle nonadiabatic processes in various complex systems, especially condensed phases and protein environments, we delve into the theories, implementations, and applications of on-the-fly QM/MM nonadiabatic dynamics. The QM/MM approach is established within the framework of the additive QM/MM scheme, employing electrostatic embedding, link-atom inclusion, and charge-redistribution schemes to treat the QM/MM boundary. Trajectory surface-hopping dynamics are facilitated using the fewest switches algorithm, encompassing classical and quantum treatments for nuclear and electronic motions, respectively. Finally, we report simulations of nonadiabatic dynamics for two typical systems: azomethane in water and the retinal chromophore PSB3 in a protein environment. Our results not only illustrate the power of the QM/MM program but also reveal the important roles of environmental factors in nonadiabatic processes.

Resolving Photoinduced Femtosecond Three-Dimensional Solute-Solvent Dynamics through Surface Hopping Simulations

Photoinduced dynamics in solution is governed by mutual solute-solvent interactions, which give rise to phenomena like solvatochromism, the Stokes shift, dual fluorescence, or charge transfer. Understanding these phenomena requires simulating the solute's photoinduced dynamics and simultaneously resolving the three-dimensional solvent distribution dynamics. If using trajectory surface hopping (TSH) to this aim, thousands of trajectories are required to adequately sample the time-dependent three-dimensional solvent distribution functions, and thus resolve the solvent dynamics with sub-Ångstrom and femtosecond accuracy and sufficiently low noise levels. Unfortunately, simulating thousands of trajectories with TSH in the framework of hybrid quantum mechanical/molecular mechanical (QM/MM) can be prohibitively expensive when employing ab initio electronic structure methods. To tackle this challenge, we recently introduced a computationally efficient approach that combines efficient linear vibronic coupling models with molecular mechanics (LVC/MM) via electrostatic embedding [Polonius et al., JCTC 2023, 19, 7171-7186]. This method provides solvent-embedded, nonadiabatically coupled potential energy surfaces while scaling similarly to MM force fields. Here, we employ TSH with LVC/MM to unravel the photoinduced dynamics of two small thiocarbonyl compounds solvated in water. We describe how to estimate the number of trajectories required to produce nearly noise-free three-dimensional solvent distribution functions and present an analysis based on approximately 10,000 trajectories propagated for 3 ps. In the electronic ground state, both molecules exhibit in-plane hydrogen bonds to the sulfur atom. Shortly after excitation, these bonds are broken and reform perpendicular to the molecular plane on timescales that differ by an order of magnitude due to steric effects. We also show that the solvent relaxation dynamics is coupled to the electronic dynamics, including intersystem crossing. These findings are relevant to advance the understanding of the coupled solute-solvent dynamics of solvated photoexcited molecules, e.g., biologically relevant thio-nucleobases.

Multiscale biomolecular simulations in the exascale era

The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. Quantum mechanics/molecular mechanics (QM/MM) molecular 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 mechanisms underlying biological processes. However, 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.

Computational Spectroscopy of Aqueous Solutions: The Underlying Role of Conformational Sampling

Fully atomistic multiscale polarizable quantum mechanics (QM)/molecular mechanics (MM) approaches, combined with techniques to sample the solute-solvent phase space, constitute the most accurate method to compute spectral signals in aqueous solution. Conventional sampling strategies, such as classical molecular dynamics (MD), may encounter drawbacks when the conformational space is particularly complex, and transition barriers between conformers are high. This can lead to inaccurate sampling, which can potentially impact the accuracy of spectral calculations. For this reason, in this work, we compare classical MD with enhanced sampling techniques, i.e., replica exchange MD and metadynamics. In particular, we show how the different sampling techniques affect computed UV, electronic circular dichroism, nuclear magnetic resonance shielding, and optical rotatory dispersion of N-acetylproline-amide in aqueous solution. Such a system is a model peptide characterized by complex conformational variability. Calculated values suggest that spectral properties are influenced by solute conformers, relative population, and solvent effects; therefore, particular care needs to be paid for when choosing the sampling technique.

Unrevealing the Nitrogen Elusive Chirality of 3-Sulfanyl and 3-Sulfinyl N-Tosyl Isoindolinones by ECD Spectra: An Experimental and Theoretical Investigation

The nitrogen-hybridization/pyramidalization of two solvated N-tosylisoindolinone derivatives having chiral residues in adjacent (I) or adjacent and distal (II) position has been investigated by a theoretical-computational procedure based on Molecular Dynamics simulations and Quantum-Chemical calculations. After validation of our methodology in providing a reliable repertory of conformations by modeling the electronic circular dichroism (EDC) spectra, the electronic features associated with N-pyramidalization were further characterized through Natural Bond Order (NBO) analysis. Comparing against the N-geometry observed in crystal structures as a reference, our findings reveal that the presence of neighbouring chiral centers induces a more pronounced N-pyramidalization in solution than in the solid state, both in I and II. Furthermore, NBO analysis confirms that the N-lactam mostly retains the sp2 character but exhibits slight configurational distortion (ξI=13°; ξII=21°), which significantly influences the chiroptical activities observed in ECD spectra of I and II. This substantiates the N-lactams as configurationally stable chiral centers.

Managing Expectations and Imbalanced Training Data in Reactive Force Field Development: An Application to Water Adsorption on Alumina

ReaxFF is a computationally efficient model for reactive molecular dynamics simulations that has been applied to a wide variety of chemical systems. When ReaxFF parameters are not yet available for a chemistry of interest, they must be (re)optimized, for which one defines a set of training data that the new ReaxFF parameters should reproduce. ReaxFF training sets typically contain diverse properties with different units, some of which are more abundant (by orders of magnitude) than others. To find the best parameters, one conventionally minimizes a weighted sum of squared errors over all of the data in the training set. One of the challenges in such numerical optimizations is to assign weights so that the optimized parameters represent a good compromise among all the requirements defined in the training set. This work introduces a new loss function, called Balanced Loss, and a workflow that replaces weight assignment with a more manageable procedure. The training data are divided into categories with corresponding "tolerances", i.e., acceptable root-mean-square errors for the categories, which define the expectations for the optimized ReaxFF parameters. Through the Log-Sum-Exp form of Balanced Loss, the parameter optimization is also a validation of one's expectations, providing meaningful feedback that can be used to reconfigure the tolerances if needed. The new methodology is demonstrated with a nontrivial parametrization of ReaxFF for water adsorption on alumina. This results in a new force field that reproduces both the rare and frequent properties of a validation set not used for training. We also demonstrate the robustness of the new force field with a molecular dynamics simulation of water desorption from a γ-Al2O3 slab model.

Nuclear Quantum Effects on Nonadiabatic Dynamics of a Green Fluorescent Protein Chromophore Analogue: Ring-Polymer Surface-Hopping Simulation

Herein, we have used the "on-the-fly" ring-polymer surface-hopping simulation method with the centroid approximation (RPSH-CA), in combination with the multireference OM2/MRCI electronic structure calculations to study the photoinduced dynamics of a green fluorescent protein (GFP) chromophore analogue in the gas phase, i.e., o-HBI, at 50, 100, and 300 K with 1, 5, 10, and 15 beads (3600 1 ps trajectories). The electronic structure calculations identified five new minimum-energy conical intersection (MECI) structures, which, together with the previous one, play crucial roles in the excited-state decay dynamics of o-HBI. It is also found that the excited-state intramolecular proton transfer (ESIPT) occurs in an ultrafast manner and is completed within 20 fs in all the simulation conditions because there is no barrier associated with this ESIPT process in the S1 state. However, the other excited-state dynamical results are strongly related to the number of beads. At 50 and 100 K, the nuclear quantum effects (NQEs) are very important; therefore, the excited-state dynamical results change significantly with the bead number. For example, the S1 decay time deduced from time-dependent state populations becomes longer as the bead number increases. Nevertheless, an essentially convergent trend is observed when the bead number is close to 10. In contrast, at 300 K, the NQEs become weaker and the above dynamical results converge very quickly even with 1 bead. Most importantly, the NQEs seriously affect the excited-state decay mechanism of o-HBI. At 50 and 100 K, most trajectories decay to the S0 state via perpendicular keto MECIs, whereas, at 300 K, only twisted keto MECIs are responsible for the excited-state decay. The present work not only comprehensively explores the temperature-dependent photoinduced dynamics of o-HBI, but also demonstrates the importance and necessity of NQEs in nonadiabatic dynamics simulations, especially at relatively low temperatures.

Eliminating Imaginary Vibrational Frequencies in Quantum-Chemical Cluster Models of Enzymatic Active Sites

In constructing finite models of enzyme active sites for quantum-chemical calculations, atoms at the periphery of the model must be constrained to prevent unphysical rearrangements during geometry relaxation. A simple fixed-atom or "coordinate-lock" approach is commonly employed but leads to undesirable artifacts in the form of small imaginary frequencies. These preclude evaluation of finite-temperature free-energy corrections, limiting thermochemical calculations to enthalpies only. Full-dimensional vibrational frequency calculations are possible by replacing the fixed-atom constraints with harmonic confining potentials. Here, we compare that approach to an alternative strategy in which fixed-atom contributions to the Hessian are simply omitted. While the latter strategy does eliminate imaginary frequencies, it tends to underestimate both the zero-point energy and the vibrational entropy while introducing artificial rigidity. Harmonic confining potentials eliminate imaginary frequencies and provide a flexible means to construct active-site models that can be used in unconstrained geometry relaxations, affording better convergence of reaction energies and barrier heights with respect to the model size, as compared to models with fixed-atom constraints.

Consistent Analytical Second Derivatives of the Kohn-Sham DFT Energy in the Framework of the Conductor-Like Screening Model through Gaussian Charge Distributions

The use of implicit solvation models such as the conductor-like screening model (COSMO) in quantum chemical calculations is very common, as both a rough estimate of solvation effects as well as a general tool for stabilizing ionic molecular structures. In order to generate a smooth potential energy surface as well as consistent gradients, it is necessary to apply the Gaussian charge model (GCM) for the COSMO charges. This work introduces an efficient implementation for consistent analytical second derivatives of the electronic energy with COSMO-GCM in the framework of the Kohn-Sham density functional theory. This is used to investigate the infrared spectroscopy of amino acids in aqueous solution, where the impact of pH on the molecular structure and vibrational spectra is examined. Furthermore, the structure and stability of selected all-metal aromatic cluster ions are assessed.

Perspective on Integrative Simulations of Bioenergetic Domains

Bioenergetic processes in cells, such as photosynthesis or respiration, integrate many time and length scales, which makes the simulation of energy conversion with a mere single level of theory impossible. Just like the myriad of experimental techniques required to examine each level of organization, an array of overlapping computational techniques is necessary to model energy conversion. Here, a perspective is presented on recent efforts for modeling bioenergetic phenomena with a focus on molecular dynamics simulations and its variants as a primary method. An overview of the various classical, quantum mechanical, enhanced sampling, coarse-grained, Brownian dynamics, and Monte Carlo methods is presented. Example applications discussed include multiscale simulations of membrane-wide electron transport, rate kinetics of ATP turnover from electrochemical gradients, and finally, integrative modeling of the chromatophore, a photosynthetic pseudo-organelle.

Unraveling Water Solvation Effects with Quantum Mechanics/Molecular Mechanics Semiclassical Vibrational Spectroscopy: The Case of Thymidine

We introduce a quantum mechanics/molecular mechanics semiclassical method for studying the solvation process of molecules in water at the nuclear quantum mechanical level with atomistic detail. We employ it in vibrational spectroscopy calculations because this is a tool that is very sensitive to the molecular environment. Specifically, we look at the vibrational spectroscopy of thymidine in liquid water. We find that the C═O frequency red shift and the C═C frequency blue shift, experienced by thymidyne upon solvation, are mainly due to reciprocal polarization effects, that the molecule and the water solvent exert on each other, and nuclear zero-point energy effects. In general, this work provides an accurate and practical tool to study quantum vibrational spectroscopy in solution and condensed phase, incorporating high-level and computationally affordable descriptions of both electronic and nuclear problems.

The catalytic mechanism of the RNA methyltransferase METTL3

The complex of methyltransferase-like proteins 3 and 14 (METTL3-14) is the major enzyme that deposits N6-methyladenosine (m6A) modifications on messenger RNA (mRNA) in humans. METTL3-14 plays key roles in various biological processes through its methyltransferase (MTase) activity. However, little is known about its substrate recognition and methyl transfer mechanism from its cofactor and methyl donor S-adenosylmethionine (SAM). Here, we study the MTase mechanism of METTL3-14 by a combined experimental and multiscale simulation approach using bisubstrate analogues (BAs), conjugates of a SAM-like moiety connected to the N6-atom of adenosine. Molecular dynamics simulations based on crystal structures of METTL3-14 with BAs suggest that the Y406 side chain of METTL3 is involved in the recruitment of adenosine and release of m6A. A crystal structure with a BA representing the transition state of methyl transfer shows a direct involvement of the METTL3 side chains E481 and K513 in adenosine binding which is supported by mutational analysis. Quantum mechanics/molecular mechanics (QM/MM) free energy calculations indicate that methyl transfer occurs without prior deprotonation of adenosine-N6. Furthermore, the QM/MM calculations provide further support for the role of electrostatic contributions of E481 and K513 to catalysis. The multidisciplinary approach used here sheds light on the (co)substrate binding mechanism, catalytic step, and (co)product release, and suggests that the latter step is rate-limiting for METTL3. The atomistic information on the substrate binding and methyl transfer reaction of METTL3 can be useful for understanding the mechanisms of other RNA MTases and for the design of transition state analogues as their inhibitors.

Deciphering Photoreceptors Through Atomistic Modeling from Light Absorption to Conformational Response

In this review, we discuss the successes and challenges of the atomistic modeling of photoreceptors. Throughout our presentation, we integrate explanations of the primary methodological approaches, ranging from quantum mechanical descriptions to classical enhanced sampling methods, all while providing illustrative examples of their practical application to specific systems. To enhance the effectiveness of our analysis, our primary focus has been directed towards the examination of applications across three distinct photoreceptors. These include an example of Blue Light-Using Flavin (BLUF) domains, a bacteriophytochrome, and the orange carotenoid protein (OCP) employed by cyanobacteria for photoprotection. Particular emphasis will be placed on the pivotal role played by the protein matrix in fine-tuning the initial photochemical event within the embedded chromophore. Furthermore, we will investigate how this localized perturbation initiates a cascade of events propagating from the binding pocket throughout the entire protein structure, thanks to the intricate network of interactions between the chromophore and the protein.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Recent developments and applications of reference interaction site model self-consistent field with constrained spatial electron density (RISM-SCF-cSED): A hybrid model of quantum chemistry and integral equation theory of molecular liquids

The significance of solvent effects in electronic structure calculations has long been noted, and various methods have been developed to consider this effect. The reference interaction site model self-consistent field with constrained spatial electron density (RISM-SCF-cSED) is a hybrid model that combines the integral equation theory of molecular liquids with quantum chemistry. This method can consider the statistically convergent solvent distribution at a significantly lower cost than molecular dynamics simulations. Because the RISM theory explicitly considers the solvent structure, it performs well for systems where hydrogen bonds are formed between the solute and solvent molecules, which is a challenge for continuum solvent models. Taking advantage of being founded on the variational principle, theoretical developments have been made in calculating various properties and incorporating electron correlation effects. In this review, we organize the theoretical aspects of RISM-SCF-cSED and its distinctions from other hybrid methods involving integral equation theories. Furthermore, we carefully present its progress in terms of theoretical developments and recent applications.

Investigating the Photodynamics of trans-Azobenzene with Coupled Trajectories

In this work, we present the first implementation of coupled-trajectory Tully surface hopping (CT-TSH) suitable for applications to molecular systems. We combine CT-TSH with the semiempirical floating occupation molecular orbital-configuration interaction electronic structure method to investigate the photoisomerization dynamics of trans-azobenzene. Our study shows that CT-TSH can capture correctly decoherence effects in this system, yielding consistent electronic and nuclear dynamics in agreement with (standard) decoherence-corrected TSH. Specifically, CT-TSH is derived from the exact factorization and the electronic coefficients' evolution is directly influenced by the coupling of trajectories, resulting in the improvement of internal consistency if compared to standard TSH.

Multiscale simulation of fluids: coupling molecular and continuum

Computer simulation is an important tool for scientific progress, especially when lab experiments are either extremely costly and difficult or lack the required resolution. However, all of the simulation methods come with limitations. In molecular dynamics (MD) simulation, the length and time scales that can be captured are limited, while computational fluid dynamics (CFD) methods are built on a range of assumptions, from the continuum hypothesis itself, to a variety of closure assumptions. To address these issues, the coupling of different methodologies provides a way to retain the best of both methods. Here, we provide a perspective on multiscale simulation based on the coupling of MD and CFD with each a distinct part of the same simulation domain. This style of coupling allows molecular detail to be present only where it is needed, so CFD can model larger scales than possible with MD alone. We present a unified perspective of the literature, showing the links between the two main types of coupling, state and flux, and discuss the varying assumptions in their use. A unique challenge in such coupled simulation is obtaining averages and constraining local parts of a molecular simulation. We highlight that incorrect localisation has resulted in an error in the literature. We then finish with some applications, focused on the simulation of fluids. Thus, we hope to motivate further research in this exciting area with applications across the spectrum of scientific disciplines.

Energy transfer from two luteins to chlorophylls in light-harvesting complex II study by using exciton models with phase correction

In light-harvesting complex II of plants, the two lutein pigments (LUT1 and LUT2) are always paired and an energy transfer pathway between them is believed to exist. However, it remains unclear whether this pathway is essential for the energy transfer between carotenoids and chlorophylls. In this work, we performed hybrid quantum mechanics/molecular mechanics simulations with Frenkel exciton models to investigate this energy transfer. The results show that the energy transfer pathways between the S2 state of LUT1 and CLAs are not affected by LUT2 S2. The energy transfer between LUT and chlorophyll-a (CLA) also follows a resonance mechanism. The two LUTs have different energy transfer pathways according to their energy gaps and coupling strengths with each CLA. The present work sheds light on the energy transfer pathways involved in the two LUTs.

The catalytic mechanism of the RNA methyltransferase METTL3

The complex of methyltransferase-like proteins 3 and 14 (METTL3-14) is the major enzyme that deposits N6-methyladenosine (m6A) modifications on mRNA in humans. METTL3-14 plays key roles in various biological processes through its methyltransferase (MTase) activity. However, little is known about its substrate recognition and methyl transfer mechanism from its cofactor and methyl donor S-adenosylmethionine (SAM). Here, we study the MTase mechanism of METTL3-14 by a combined experimental and multiscale simulation approach using bisubstrate analogues (BAs), conjugates of a SAM-like moiety connected to the N6-atom of adenosine. Molecular dynamics simulations based on crystal structures of METTL3-14 with BAs suggest that the Y406 side chain of METTL3 is involved in the recruitment of adenosine and release of m6A. A crystal structure with a bisubstrate analogue representing the transition state of methyl transfer shows a direct involvement of the METTL3 side chains E481 and K513 in adenosine binding which is supported by mutational analysis. Quantum mechanics/molecular mechanics (QM/MM) free energy calculations indicate that methyl transfer occurs without prior deprotonation of adenosine-N6. Furthermore, the QM/MM calculations provide further support for the role of electrostatic contributions of E481 and K513 to catalysis. The multidisciplinary approach used here sheds light on the (co)substrate binding mechanism, catalytic step, and (co)product release catalysed by METTL3, and suggests that the latter step is rate-limiting. The atomistic information on the substrate binding and methyl transfer reaction of METTL3 can be useful for understanding the mechanisms of other RNA MTases and for the design of transition state analogues as their inhibitors.

Simulating Electron Transfer Reactions in Solution: Radical-Polar Crossover

Single-electron transfer (SET) promotes a wide variety of interesting chemical transformations, but modeling of SET requires a careful treatment of electronic and solvent effects to give meaningful insight. Therefore, a combined constrained density functional theory and molecular mechanics (CDFT/MM) tool is introduced specifically for SET-initiated reactions. Mechanisms for two radical-polar crossover reactions involving the organic electron donors tetrakis(dimethylamino)ethylene (TDAE) and tetrathiafulvalene (TTF) were studied with the new tool. An unexpected tertiary radical intermediate within the TDAE system was identified, relationships between kinetics and substitution in the TTF system were explained, and the impact of the solvent environments on the TDAE and TTF reactions were examined. The results highlight the need for including solvent dynamics when quantifying SET kinetics and thermodynamics, as a free energy difference of >20 kcal/mol was observed. Overall, the new method informs mechanistic analysis of SET-initiated reactions and therefore is envisioned to be useful for studying reactions in the condensed phase.

Redox-Based Defect Detection in Packed DNA: Insights from Hybrid Quantum Mechanical/Molecular Mechanics Molecular Dynamics Simulations

The impact of an 8-oxoguanine (8oxoG) defect on the redox properties of DNA within the nucleosome core particle (NCP) was investigated employing hybrid quantum mechanical/molecular mechanics (QM/MM) molecular dynamics simulations of native and 8oxoG-containing NCP systems with an explicit representation of a biologically relevant environment. Two distinct NCP positions with varying solvent accessibility were considered for 8oxoG insertion. In both cases, it is found that the presence of 8oxoG drastically decreases the redox free energy of oxidation by roughly 1 eV, which is very similar to what was recently reported for free native and 8oxoG-containing DNA. In contrast, the effect of 8oxoG on the reorganization free energy is even smaller for packed DNA (decrease of 0.13 and 0.01 eV for defect-free and defect-containing systems, respectively) compared to the one for free DNA (0.25 eV), consistent with the increased rigidity of the NCP as compared to free DNA. Furthermore, the presence of an 8oxoG defect does not yield any significant changes in the packed DNA structure. Such a conclusion favors the idea that in the case of chromatin, defect-induced changes in DNA redox chemistry can also be exploited to detect damaged bases via DNA-mediated hole transfer.

Nonadiabatic Dynamics Simulations for Photoinduced Processes in Molecules and Semiconductors: Methodologies and Applications

Nonadiabatic dynamics (NAMD) simulations have become powerful tools for elucidating complicated photoinduced processes in various systems from molecules to semiconductor materials. In this review, we present an overview of our recent research on photophysics of molecular systems and periodic semiconductor materials with the aid of ab initio NAMD simulation methods implemented in the generalized trajectory surface-hopping (GTSH) package. Both theoretical backgrounds and applications of the developed NAMD methods are presented in detail. For molecular systems, the linear-response time-dependent density functional theory (LR-TDDFT) method is primarily used to model electronic structures in NAMD simulations owing to its balanced efficiency and accuracy. Moreover, the efficient algorithms for calculating nonadiabatic coupling terms (NACTs) and spin-orbit couplings (SOCs) have been coded into the package to increase the simulation efficiency. In combination with various analysis techniques, we can explore the mechanistic details of the photoinduced dynamics of a range of molecular systems, including charge separation and energy transfer processes in organic donor-acceptor structures, ultrafast intersystem crossing (ISC) processes in transition metal complexes (TMCs), and exciton dynamics in molecular aggregates. For semiconductor materials, we developed the NAMD methods for simulating the photoinduced carrier dynamics within the framework of the Kohn-Sham density functional theory (KS-DFT), in which SOC effects are explicitly accounted for using the two-component, noncollinear DFT method. Using this method, we have investigated the photoinduced carrier dynamics at the interface of a variety of van der Waals (vdW) heterojunctions, such as two-dimensional transition metal dichalcogenides (TMDs), carbon nanotubes (CNTs), and perovskites-related systems. Recently, we extended the LR-TDDFT-based NAMD method for semiconductor materials, allowing us to study the excitonic effects in the photoinduced energy transfer process. These results demonstrate that the NAMD simulations are powerful tools for exploring the photodynamics of molecular systems and semiconductor materials. In future studies, the NAMD simulation methods can be employed to elucidate experimental phenomena and reveal microscopic details as well as rationally design novel photofunctional materials with desired properties.

Catalytic Mechanism of Collagen Hydrolysis by Zinc(II)-Dependent Matrix Metalloproteinase-1

Human matrix metalloproteinase-1 (MMP-1) is a zinc(II)-dependent enzyme that catalyzes collagenolysis. Despite the availability of extensive experimental data, the mechanism of MMP-1-catalyzed collagenolysis remains poorly understood due to the lack of experimental structure of a catalytically productive enzyme-substrate complex of MMP-1. In this study, we apply molecular dynamics and combined quantum mechanics/molecular mechanics to reveal the reaction mechanism of MMP-1 based on a computationally modeled structure of the catalytically competent complex of MMP-1 that contains a large triple-helical peptide substrate. Our proposed mechanism involves the participation of an auxiliary (second) water molecule (wat2) in addition to the zinc(II)-coordinated water (wat1). The reaction initiates through a proton transfer to Glu219, followed by a nucleophilic attack by a zinc(II)-coordinated hydroxide anion nucleophile at the carbonyl carbon of the scissile bond, leading to the formation of a tetrahedral intermediate (IM2). The process continues with a hydrogen-bond rearrangement to facilitate proton transfer from wat2 to the amide nitrogen of the scissile bond and, finally, C-N bond cleavage. The calculations indicate that the rate-determining step is the water-mediated nucleophilic attack with an activation energy barrier of 22.3 kcal/mol. Furthermore, the calculations show that the hydrogen-bond rearrangement/proton-transfer step can proceed in a consecutive or concerted manner, depending on the conformation of the tetrahedral intermediate, with the consecutive mechanism being energetically preferable. Overall, the study reveals the crucial role of a second water molecule and the dynamics for effective MMP-1-catalyzed collagenolysis.

Nuclear-Electronic Orbital Quantum Mechanical/Molecular Mechanical Real-Time Dynamics

Simulating the nuclear-electronic quantum dynamics of large-scale molecular systems in the condensed phase is key for studying biologically and chemically important processes such as proton transfer and proton-coupled electron transfer reactions. Herein, the real-time nuclear-electronic orbital time-dependent density functional theory (RT-NEO-TDDFT) approach is combined with a hybrid quantum mechanical/molecular mechanical (QM/MM) strategy to enable the accurate description of coupled nuclear-electronic quantum dynamics in the presence of heterogeneous environments such as solvent or proteins. The densities of the electrons and quantum protons are propagated in real time, while the other nuclei are propagated classically on the instantaneous electron-proton vibronic surface. This approach is applied to phenol bound to lysozyme, intramolecular proton transfer in malonaldehyde, and nonequilibrium excited-state intramolecular proton transfer in o-hydroxybenzaldehyde. These examples illustrate that the RT-NEO-TDDFT framework, coupled with an atomistic representation of the environment, allows the simulation of condensed-phase systems that exhibit significant nuclear quantum effects.

LVC/MM: A Hybrid Linear Vibronic Coupling/Molecular Mechanics Model with Distributed Multipole-Based Electrostatic Embedding for Highly Efficient Surface Hopping Dynamics in Solution

We present a theoretical framework for a hybrid linear vibronic coupling model electrostatically embedded into a molecular mechanics environment, termed the linear vibronic coupling/molecular mechanics (LVC/MM) method, for the surface hopping including arbitrary coupling (SHARC) molecular dynamics package. Electrostatic embedding is realized through the computation of interactions between environment point charges and distributed multipole expansions (DMEs, up to quadrupoles) that represent each electronic state and transition densities in the diabatic basis. The DME parameters are obtained through a restrained electrostatic potential (RESP) fit, which we extended to yield higher-order multipoles. We also implemented in SHARC a scheme for achieving roto-translational invariance of LVC models as well as a general quantum mechanics/molecular mechanics (QM/MM) interface, an OpenMM interface, and restraining potentials for simulating liquid droplets. Using thioformaldehyde in water as a test case, we demonstrate that LVC/MM can accurately reproduce the solvation structure and energetics of rigid solutes, with errors on the order of 1-2 kcal/mol compared to a BP86/MM reference. The implementation in SHARC is shown to be very efficient, enabling the simulation of trajectories on the nanosecond time scale in a matter of days.

Human O-GlcNAcase Uses a Preactivated Boat-skew Substrate Conformation for Catalysis. Evidence from X-ray Crystallography and QM/MM Metadynamics

Human O-linked β-N-acetylglucosaminidase (hOGA) is one of the two enzymes involved in nuclear and cytoplasmic protein O-GlcNAcylation, an essential post-translational modification. The enzyme catalyzes the hydrolysis of the GlcNAc-O-(Ser/Thr) glycosidic bonds via anchimeric assistance through the 2-acetamido group of the GlcNAc sugar. However, the conformational itinerary of the GlcNAc ring during catalysis remains unclear. Here we report the crystal structure of wild type hOGA in complex with a nonhydrolyzable glycopeptide substrate and elucidate the full enzyme catalytic mechanism using QM/MM metadynamics. We show that the enzyme can bind the substrate in either a chair- or a boat-like conformation, but only the latter is catalytically competent, leading to the reaction products via 1,4B/1S3 → [4E]‡ → 4C1 and 4C1 → [4E]‡ → 1,4B/1S3 conformational itineraries for the first and second catalytic reaction steps, respectively. Our results reconcile previous experimental observations for human and bacterial OGA and will aid the development of more effective OGA inhibitors for diseases associated with impaired O-GlcNAcylation.

Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps Including Hydrogen Bonds

Polarizable embedding (PE) refers to classical embedding approaches, such as those used in quantum mechanics/molecular mechanics (QM/MM), that allow mutual polarization between the quantum and classical regions. The quality of the embedding potential is critical to provide accurate results, e.g., for spectroscopic properties and dynamical processes. High-quality embedding-potential parameters can be obtained by dividing the classical region into smaller fragments and deriving the parameters from ab initio calculations on the fragments. For solvents and other systems composed of small molecules, the fragments can be individual molecules, while a more complicated fragmentation procedure is needed for larger molecules, such as proteins and nucleic acids. One such fragmentation strategy is the molecular fractionation with conjugate caps (MFCC) approach. As is widely known, hydrogen bonds play a key role in many biomolecular systems, e.g., in proteins, where they are responsible for the secondary structure. In this work, we assess the effects of including hydrogen-bond fragmentation in the MFCC procedure [MFCC(HB)] for deriving the embedding-potential parameters. The MFCC(HB) extension is evaluated on several molecular systems, ranging from small model systems to proteins, directly in terms of molecular electrostatic potentials and embedding potentials and indirectly in terms of selected properties of chromophores embedded in water and complex protein environments.

Polarizable Embedding without Artificial Boundary Polarization

We present a fully self-consistent polarizable embedding (PE) model that does not suffer from unphysical boundary polarization. This is achieved through the use of the minimum-image convention (MIC) in the induced electrostatics. It is a simple yet effective approach that includes a more physically accurate description of the polarization throughout the molecular system. Using PE with MIC (PE-MIC), we shed new light on the limitations of commonly employed cutoff models, such as the droplet model, when used in PE calculations. Specifically, we investigate the effects of the unphysical polarization at the outer boundary by comparing induced dipoles and the associated electrostatic potentials, as well as some optical properties of solute-solvent and biomolecular systems. We show that the magnitude of the inaccuracies caused by the unphysical polarization depends on multiple parameters: the nature of the quantum subsystem and of the environment, the cutoff model and distance, and the calculated property.

Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations

The initial phases of drug discovery - in silico drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of ∼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.

The confluence of machine learning and multiscale simulations

Multiscale modeling has a long history of use in structural biology, as computational biologists strive to overcome the time- and length-scale limits of atomistic molecular dynamics. Contemporary machine learning techniques, such as deep learning, have promoted advances in virtually every field of science and engineering and are revitalizing the traditional notions of multiscale modeling. Deep learning has found success in various approaches for distilling information from fine-scale models, such as building surrogate models and guiding the development of coarse-grained potentials. However, perhaps its most powerful use in multiscale modeling is in defining latent spaces that enable efficient exploration of conformational space. This confluence of machine learning and multiscale simulation with modern high-performance computing promises a new era of discovery and innovation in structural biology.

Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins

Metal ions are essential cofactors for many proteins and play a crucial role in many applications such as enzyme design or design of protein-protein interactions because they are biologically abundant, tether to the protein using strong interactions, and have favorable catalytic properties. Computational design of metalloproteins is however hampered by the complex electronic structure of many biologically relevant metals such as zinc . In this work, we develop two tools - Metal3D (based on 3D convolutional neural networks) and Metal1D (solely based on geometric criteria) to improve the location prediction of zinc ions in protein structures. Comparison with other currently available tools shows that Metal3D is the most accurate zinc ion location predictor to date with predictions within 0.70 ± 0.64 Å of experimental locations. Metal3D outputs a confidence metric for each predicted site and works on proteins with few homologes in the protein data bank. Metal3D predicts a global zinc density that can be used for annotation of computationally predicted structures and a per residue zinc density that can be used in protein design workflows. Currently trained on zinc, the framework of Metal3D is readily extensible to other metals by modifying the training data.

Hybrid Quantum Mechanical/Molecular Mechanical Methods For Studying Energy Transduction in Biomolecular Machines

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods have become indispensable tools for the study of biomolecules. In this article, we briefly review the basic methodological details of QM/MM approaches and discuss their applications to various energy transduction problems in biomolecular machines, such as long-range proton transports, fast electron transfers, and mechanochemical coupling. We highlight the particular importance for these applications of balancing computational efficiency and accuracy. Using several recent examples, we illustrate the value and limitations of QM/MM methodologies for both ground and excited states, as well as strategies for calibrating them in specific applications. We conclude with brief comments on several areas that can benefit from further efforts to make QM/MM analyses more quantitative and applicable to increasingly complex biological problems.

The Quantum Chemical Cluster Approach in Biocatalysis

ConspectusThe quantum chemical cluster approach has been used for modeling enzyme active sites and reaction mechanisms for more than two decades. In this methodology, a relatively small part of the enzyme around the active site is selected as a model, and quantum chemical methods, typically density functional theory, are used to calculate energies and other properties. The surrounding enzyme is modeled using implicit solvation and atom fixing techniques. Over the years, a large number of enzyme mechanisms have been solved using this method. The models have gradually become larger as a result of the faster computers, and new kinds of questions have been addressed. In this Account, we review how the cluster approach can be utilized in the field of biocatalysis. Examples from our recent work are chosen to illustrate various aspects of the methodology. The use of the cluster model to explore substrate binding is discussed first. It is emphasized that a comprehensive search is necessary in order to identify the lowest-energy binding mode(s). It is also argued that the best binding mode might not be the productive one, and the full reactions for a number of enzyme-substrate complexes have therefore to be considered to find the lowest-energy reaction pathway. Next, examples are given of how the cluster approach can help in the elucidation of detailed reaction mechanisms of biocatalytically interesting enzymes, and how this knowledge can be exploited to develop enzymes with new functions or to understand the reasons for lack of activity toward non-natural substrates. The enzymes discussed in this context are phenolic acid decarboxylase and metal-dependent decarboxylases from the amidohydrolase superfamily. Next, the application of the cluster approach in the investigation of enzymatic enantioselectivity is discussed. The reaction of strictosidine synthase is selected as a case study, where the cluster calculations could reproduce and rationalize the selectivities of both the natural and non-natural substrates. Finally, we discuss how the cluster approach can be used to guide the rational design of enzyme variants with improved activity and selectivity. Acyl transferase from Mycobacterium smegmatis serves as an instructive example here, for which the calculations could pinpoint the factors controlling the reaction specificity and enantioselectivity. The cases discussed in this Account highlight thus the value of the cluster approach as a tool in biocatalysis. It complements experiments and other computational techniques in this field and provides insights that can be used to understand existing enzymes and to develop new variants with tailored properties.

Machines on Genes through the Computational Microscope

Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.

Surface hopping modeling of charge and energy transfer in active environments

An active environment is any atomic or molecular system changing a chromophore's nonadiabatic dynamics compared to the isolated molecule. The action of the environment on the chromophore occurs by changing the potential energy landscape and triggering new energy and charge flows unavailable in the vacuum. Surface hopping is a mixed quantum-classical approach whose extreme flexibility has made it the primary platform for implementing novel methodologies to investigate the nonadiabatic dynamics of a chromophore in active environments. This Perspective paper surveys the latest developments in the field, focusing on charge and energy transfer processes.

Induction effects on the absorption maxima of photoreceptor proteins

Multiscale simulations have been established as a powerful tool to calculate and predict excitation energies in complex systems such as photoreceptor proteins. In these simulations the chromophore is typically treated using quantum mechanical (QM) methods while the protein and surrounding environment are described by a classical molecular mechanics (MM) force field. The electrostatic interactions between these regions are often treated using electrostatic embedding where the point charges in the MM region polarize the QM region. A more sophisticated treatment accounts also for the polarization of the MM region. In this work, the effect of such a polarizable embedding on excitation energies was benchmarked and compared to electrostatic embedding. This was done for two different proteins, the lipid membrane-embedded jumping spider rhodopsin and the soluble cyanobacteriochrome Slr1393g3. It was found that the polarizable embedding scheme produces absorption maxima closer to experimental values. The polarizable embedding scheme was also benchmarked against expanded QM regions and found to be in qualitative agreement. Treating individual residues as polarizable recovered between 50% and 71% of the QM improvement in the excitation energies, depending on the system. A detailed analysis of each amino acid residue in the chromophore binding pocket revealed that aromatic residues result in the largest change in excitation energy compared to the electrostatic embedding. Furthermore, the computational efficiency of polarizable embedding allowed it to go beyond the binding pocket and describe a larger portion of the environment, further improving the results.

Water Maintains the UV-Vis Spectral Features During the Insertion of Anionic Naproxen and Ibuprofen into Model Cell Membranes

UV-vis spectra of anionic ibuprofen and naproxen in a model lipid bilayer of the cell membrane are investigated using computational techniques in combination with a comparative analysis of drug spectra in purely aqueous environments. The simulations aim at elucidating the intricacies behind the negligible changes in the maximum absorption wavelength in the experimental spectra. A set of configurations of the systems constituted by lipid, water, and drugs or just water and drugs are obtained from classical Molecular Dynamics simulations. UV-vis spectra are computed in the framework of atomistic Quantum Mechanical/Molecular Mechanics (QM/MM) approaches together with Time-Dependent Density Functional Theory (TD-DFT). Our results suggest that the molecular orbitals involved in the electronic transitions are the same, regardless of the chemical environment. A thorough analysis of the contacts between the drug and water molecules reveals that no significant changes in UV-vis spectra are a consequence of ibuprofen and naproxen molecules being permanently microsolvated by water molecules, despite the presence of lipid molecules. Water molecules microsolvate the charged carboxylate group as expected but also microsolvate the aromatic regions of the drugs.

MiMiCPy: An Efficient Toolkit for MiMiC-Based QM/MM Simulations

MiMiC is a highly flexible, extremely scalable multiscale modeling framework. It couples the CPMD (quantum mechanics, QM) and GROMACS (molecular mechanics, MM) codes. The code requires preparing separate input files for the two programs with a selection of the QM region. This can be a tedious procedure prone to human error, especially when dealing with large QM regions. Here, we present MiMiCPy, a user-friendly tool that automatizes the preparation of MiMiC input files. It is written in Python 3 with an object-oriented approach. The main subcommand PrepQM can be used to generate MiMiC inputs directly from the command line or through a PyMOL/VMD plugin for visually selecting the QM region. Many other subcommands are also provided for debugging and fixing MiMiC input files. MiMiCPy is designed with a modular structure that allows seamless extensions to new program formats depending on the requirements of MiMiC.

Accelerated Quantum Mechanics/Molecular Mechanics Simulations via Neural Networks Incorporated with Mechanical Embedding Scheme

A powerful tool to study the mechanism of reactions in solutions or enzymes is to perform the ab initio quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations. However, the computational cost is too high due to the explicit electronic structure calculations at every time step of the simulation. A neural network (NN) method can accelerate the QM/MM-MD simulations, but it has long been a problem to accurately describe the QM/MM electrostatic coupling by NN in the electrostatic embedding (EE) scheme. In this work, we developed a new method to accelerate QM/MM calculations in the mechanic embedding (ME) scheme. The potentials and partial point charges of QM atoms are first learned in vacuo by the embedded atom neural networks (EANN) approach. MD simulations are then performed on this EANN/MM potential energy surface (PES) to obtain free energy (FE) profiles for reactions, in which the QM/MM electrostatic coupling is treated in the mechanic embedding (ME) scheme. Finally, a weighted thermodynamic perturbation (wTP) corrects the FE profiles in the ME scheme to the EE scheme. For two reactions in water and one in methanol, our simulations reproduced the B3LYP/MM free energy profiles within 0.5 kcal/mol with a speed-up of 30-60-fold. The results show that the strategy of combining EANN potential in the ME scheme with the wTP correction is efficient and reliable for chemical reaction simulations in liquid. Another advantage of our method is that the QM PES is independent of the MM subsystem, so it can be applied to various MM environments as demonstrated by an S_N2 reaction studied in water and methanol individually, which used the same EANN PES. The free energy profiles are in excellent accordance with the results obtained from B3LYP/MM-MD simulations. In future, this method will be applied to the reactions of enzymes and their variants.

Computational Investigation of a Series of Small Molecules as Potential Compounds for Lysyl Hydroxylase-2 (LH2) Inhibition

The catalytic function of lysyl hydroxylase-2 (LH2), a member of the Fe(II)/αKG-dependent oxygenase superfamily, is to catalyze the hydroxylation of lysine to hydroxylysine in collagen, resulting in stable hydroxylysine aldehyde-derived collagen cross-links (HLCCs). Reports show that high amounts of LH2 lead to the accumulation of HLCCs, causing fibrosis and specific types of cancer metastasis. Some members of the Fe(II)/αKG-dependent family have also been reported to have intramolecular O2 tunnels, which aid in transporting one of the required cosubstrates into the active site. While LH2 can be a promising target to combat these diseases, efficacious inhibitors are still lacking. We have used computational simulations to investigate a series of 44 small molecules as lead compounds for LH2 inhibition. Tunneling analyses indicate the existence of several intramolecular tunnels. The lengths of the calculated O2-transporting tunnels in holoenzymes are relatively longer than those in the apoenzyme, suggesting that the ligands may affect the enzyme's structure and possibly block (at least partially) the tunnels. The sequence alignment analysis between LH enzymes from different organisms shows that all of the amino acid residues with the highest occurrence rate in the oxygen tunnels are conserved. Our results suggest that the enolate form of diketone compounds establishes stronger interactions with the Fe(II) in the active site. Branching the enolate compounds with functional groups such as phenyl and pyridinyl enhances the interaction with various residues around the active site. Our results provide information about possible leads for further LH2 inhibition design and development.

Fast Method for Excited-State Dynamics in Complex Systems and Its Application to the Photoactivation of a Blue Light Using Flavin Photoreceptor

The excited-state dynamics of molecules embedded in complex (bio)matrices is still a challenging goal for quantum chemical models. Hybrid QM/MM models have proven to be an effective strategy, but an optimal combination of accuracy and computational cost still has to be found. Here, we present a method which combines the accuracy of a polarizable embedding QM/MM approach with the computational efficiency of an excited-state self-consistent field method. The newly implemented method is applied to the photoactivation of the blue-light-using flavin (BLUF) domain of the AppA protein. We show that the proton-coupled electron transfer (PCET) process suggested for other BLUF proteins is still valid also for AppA.

Molecular Mechanism of Substrate Oxidation in Lytic Polysaccharide Monooxygenases: Insight from Theoretical Investigations

Lytic polysaccharide monooxygenases (LPMOs) are copper enzymes that today comprise a large enzyme superfamily, grouped into the distinct members AA9-AA17 (with AA12 exempted). The LPMOs have the potential to facilitate the upcycling of biomass waste products by boosting the breakdown of cellulose and other recalcitrant polysaccharides. The cellulose biopolymer is the main component of biomass waste and thus comprises a large, unexploited resource. The LPMOs work through a catalytic, oxidative reaction whose mechanism is still controversial. For instance, the nature of the intermediate performing the oxidative reaction is an open question, and the same holds for the employed co-substrate. Here we review theoretical investigations addressing these questions. The applied theoretical methods are usually based on quantum mechanics (QM), often combined with molecular mechanics (QM/MM). We discuss advantages and disadvantages of the employed theoretical methods and comment on the interplay between theoretical and experimental results.

Mechanism of the Early Catalytic Events in the Collagenolysis by Matrix Metalloproteinase-1

Metalloproteinase-1 (MMP-1) catalyzed collagen degradation is essential for a wide variety of normal physiological processes, while at the same time contributing to several diseases in humans. Therefore, a comprehensive understanding of this process is of great importance. Although crystallographic and spectroscopic studies provided fundamental information about the structure and function of MMP-1, the precise mechanism of collagen degradation especially considering the complex and flexible structure of the substrate, remains poorly understood. In addition, how the protein environment dynamically reorganizes at the atomic scale into a catalytically active state capable of collagen hydrolysis remains unknown. In this study, we applied experimentally-guided multiscale molecular modeling methods including classical molecular dynamics (MD), well-tempered (WT) classical metadynamics (MetD), combined quantum mechanics/molecular mechanics (QM/MM) MD and QM/MM MetD simulations to explore and characterize the early catalytic events of MMP-1 collagenolysis. Importantly the study provided a complete atomic and dynamic description of the transition from the open to the closed form of the MMP-1•THP complex. Notably, the formation of catalytically active Michaelis complex competent for collagen cleavage was characterized. The study identified the changes in the coordination state of the catalytic zinc(II) associated with the conformational transformation and the formation of catalytically productive ES complex. Our results confirm the essential role of the MMP-1 catalytic domain's α-helices (hA, hB and hC) and the linker region in the transition to the catalytically competent ES complex. Overall, the results provide unique mechanistic insight into the conformational transformations and associated changes in the coordination state of the catalytic zinc(II) that would be important for the design of effective MMP-1 inhibitors.