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.

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.

Physical Chemistry of Chloroquine Permeation through the Cell Membrane with Atomistic Detail.

We provide a molecular-level description of the thermodynamics and mechanistic aspects of drug permeation through the cell membrane. As a case study, we considered the antimalaria FDA approved drug chloroquine. Molecular dynamics simulations of the molecule (in its neutral and protonated form) were performed in the presence of different lipid bilayers, with the aim of uncovering key aspects of the permeation process, a fundamental step for the drug's action. Free energy values obtained by well-tempered metadynamics simulations suggest that the neutral form is the only permeating protomer, consistent with experimental data. H-bond interactions of the drug with water molecules and membrane headgroups play a crucial role for permeation. The presence of the transmembrane potential, investigated here for the first time in a drug permeation study, does not qualitatively affect these conclusions.

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.

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.

Molecular Dynamics and Structural Studies of Zinc Chloroquine Complexes.

Chloroquine (CQ) is a first-choice drug against malaria and autoimmune diseases. It has been co-administered with zinc against SARS-CoV-2 and soon dismissed because of safety issues. The structural features of Zn-CQ complexes and the effect of CQ on zinc distribution in cells are poorly known. In this study, state-of-the-art computations combined with experiments were leveraged to solve the structural determinants of zinc-CQ interactions in solution and the solid state. NMR, ESI-MS, and X-ray absorption and diffraction methods were combined with ab initio molecular dynamics calculations to address the kinetic lability of this complex. Within the physiological pH range, CQ binds Zn2+ through the quinoline ring nitrogen, forming [Zn(CQH)Clx(H2O)3-x](3+)-x (x = 0, 1, 2, and 3) tetrahedral complexes. The Zn(CQH)Cl3 species is stable at neutral pH and at high chloride concentrations typical of the extracellular medium, but metal coordination is lost at a moderately low pH as in the lysosomal lumen. The pentacoordinate complex [Zn(CQH)(H2O)4]3+ may exist in the absence of chloride. This in vitro/in silico approach can be extended to other metal-targeting drugs and bioinorganic systems.

Proton Transfers to DNA in Native Electrospray Ionization Mass Spectrometry: A Quantum Mechanics/Molecular Mechanics Study.

Native electrospray ionization-ion mobility mass spectrometry (N-ESI/IM-MS) is a powerful approach for low-resolution structural studies of DNAs in the free state and in complex with ligands. Solvent vaporization is coupled with proton transfers from ammonium ions to the DNA, resulting in a reduction of the DNA charge. Here we provide insight into these processes by classical molecular dynamics and quantum mechanics/molecular mechanics free energy calculations on the d(GpCpGpApApGpC) heptamer, for which a wealth of experiments is available. Our multiscale simulations, consistent with experimental data, reveal a highly complex scenario. The proton either sits on one of the molecules or is fully delocalized on both, depending on the level of hydration of the analytes and the size of the droplets formed during the electrospray experiments. This work complements our previous study of the intramolecular proton transfer on the same heptamer occurring after the processes studied here, and together, they provide a first molecular view of proton transfer in N-ESI/IM-MS.

Wavefunction-Based Electrostatic-Embedding QM/MM Using CFOUR through MiMiC.

We present an interface of the wavefunction-based quantum chemical software CFOUR to the multiscale modeling framework MiMiC. Electrostatic embedding of the quantum mechanical (QM) part is achieved by analytic evaluation of one-electron integrals in CFOUR, while the rest of the QM/molecular mechanical (MM) operations are treated according to the previous MiMiC-based QM/MM implementation. Long-range electrostatic interactions are treated by a multipole expansion of the potential from the QM electron density to reduce the computational cost without loss of accuracy. Testing on model water/water systems, we verified that the CFOUR interface to MiMiC is robust, guaranteeing fast convergence of the self-consistent field cycles and optimal conservation of the energy during the integration of the equations of motion. Finally, we verified that the CFOUR interface to MiMiC is compatible with the use of a QM/QM multiple time-step algorithm, which effectively reduces the cost of ab initio MD (AIMD) or QM/MM-MD simulations using higher level wavefunction-based approaches compared to cheaper density functional theory-based ones. The new wavefunction-based AIMD and QM/MM-MD implementations were tested and validated for a large number of wavefunction approaches, including Hartree-Fock and post-Hartree-Fock methods like Møller-Plesset, coupled-cluster, and complete active space self-consistent field.

Mechanisms Underlying Proton Release in CLC-type F-/H+ Antiporters.

The CLC family of anion channels and transporters includes Cl-/H+ exchangers (blocked by F-) and F-/H+ exchangers (or CLCFs). CLCFs contain a glutamate (E318) in the central anion-binding site that is absent in CLC Cl-/H+ exchangers. The X-ray structure of the protein from Enterococcus casseliflavus (CLCF-eca) shows that E318 tightly binds to F- when the gating glutamate (E118; highly conserved in the CLC family) faces the extracellular medium. Here, we use classical and DFT-based QM/MM metadynamics simulations to investigate proton transfer and release by CLCF-eca. After up to down movement of protonated E118, both glutamates combine with F- to form a triad, from which protons and F- anions are released as HF. Our results illustrate how glutamate insertion into the central anion-binding site of CLCF-eca permits the release of H+ to the cytosol as HF, thus enabling a net 1:1 F-/H+ stoichiometry.

Machine Learning of Allosteric Effects: The Analysis of Ligand-Induced Dynamics to Predict Functional Effects in TRAP1.

Allosteric molecules provide a powerful means to modulate protein function. However, the effect of such ligands on distal orthosteric sites cannot be easily described by classical docking methods. Here, we applied machine learning (ML) approaches to expose the links between local dynamic patterns and different degrees of allosteric inhibition of the ATPase function in the molecular chaperone TRAP1. We focused on 11 novel allosteric modulators with similar affinities to the target but with inhibitory efficacy between the 26.3 and 76%. Using a set of experimentally related local descriptors, ML enabled us to connect the molecular dynamics (MD) accessible to ligand-bound (perturbed) and unbound (unperturbed) systems to the degree of ATPase allosteric inhibition. The ML analysis of the comparative perturbed ensembles revealed a redistribution of dynamic states in the inhibitor-bound versus inhibitor-free systems following allosteric binding. Linear regression models were built to quantify the percentage of experimental variance explained by the predicted inhibitor-bound TRAP1 states. Our strategy provides a comparative MD-ML framework to infer allosteric ligand functionality. Alleviating the time scale issues which prevent the routine use of MD, a combination of MD and ML represents a promising strategy to support in silico mechanistic studies and drug design.

Molecular Basis of CLC Antiporter Inhibition by Fluoride.

CLC channels and transporters conduct or transport various kinds of anions, with the exception of fluoride, which acts as an effective inhibitor. Here, we performed sub-nanosecond DFT-based QM/MM simulations of the E. coli anion/proton exchanger ClC-ec1 and observed that fluoride binds incoming protons within the selectivity filter, with excess protons shared with the gating glutamate E148. Depending on E148 conformation, the competition for the proton can involve either a direct F-/E148 interaction or the modulation of water molecules bridging the two anions. The direct interaction locks E148 in a conformation that does not allow for proton transport, and thus inhibits protein function.

All-Atom Simulations Disclose How Cytochrome Reductase Reshapes the Substrate Access/Egress Routes of Its Partner CYP450s.

Cytochromes P450 enzymes (CYP450s) promote the oxidative metabolism of a variety of substrates via the electrons supplied by the cytochrome P450 reductase (CPR) and upon formation of a CPR/CYP450 adduct. In spite of the pivotal regulatory importance of this process, the impact of CPR binding on the functional properties of its partner CYP450 remains elusive. By performing multiple microsecond-long all-atom molecular dynamics simulations of a 520 000-atom model of a CPR/CYP450 adduct embedded in a membrane mimic, we disclose the molecular terms for their interactions, considering the aromatase (HA) enzyme as a proxy of the CYP450 family. Our study strikingly unveils that CPR binding alters HA's functional motions, bolstering a change in the shape and type of the channels traveled by substrates/products during their access/egress to/from the enzyme's active site. Our outcomes unprecedentedly contribute to extricate the many entangled facets of the CYP450 metabolon, redrafting its intricate panorama from an atomic-level perspective.

Extreme Scalability of DFT-Based QM/MM MD Simulations Using MiMiC.

We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computation of electrostatic QM/MM interactions is parallelized exploiting both distributed- and shared-memory strategies. Here, we use the efficient CPMD and GROMACS programs as QM and MM engines, respectively. The scalability is demonstrated through large-scale benchmark simulations of realistic biomolecular systems employing non-hybrid and hybrid GGA exchange-correlation functionals. We show that the loose-coupling strategy adopted in MiMiC, with its inherent high flexibility, does not carry any significant computational overhead compared to a tight-coupling scheme. Furthermore, we demonstrate that the adopted parallelization strategy enables scaling up to 13,000 CPU cores with efficiency above 70%, thus making DFT-based QM/MM MD simulations using hybrid functionals at the nanosecond scale accessible.

MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry.

We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through the use of MPI intercommunicators. This allows exploiting the existing parallelization strategies used by the coupled programs while maintaining a high degree of flexibility. MiMiC has been used in a new electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) implementation coupling the highly efficient CPMD and GROMACS programs, but it can also be extended to use other programs. The framework can also be utilized to extend the partitioning of the system into several domains that can be treated using different models, such as models based on wave function or density functional theory as well as coarse-graining and continuum models. The new QM/MM implementation treats long-range electrostatic QM-MM interactions through the multipoles of the QM subsystem which substantially reduces the computational cost without loss of accuracy compared to an exact treatment. This enables QM/MM molecular dynamics (MD) simulations of very large systems.

Post-Translational Regulation of CYP450s Metabolism As Revealed by All-Atoms Simulations of the Aromatase Enzyme.

Phosphorylation by kinases enzymes is a widespread regulatory mechanism able of rapidly altering the function of target proteins. Among these are cytochrome P450s (CYP450), a superfamily of enzymes performing the oxidation of endogenous and exogenous substrates thanks to the electron supply of a redox partner. In spite of its pivotal role, the molecular mechanism by which phosphorylation modulates CYP450s metabolism remains elusive. Here by performing microsecond-long all-atom molecular dynamics simulations, we disclose how phosphorylation regulates estrogen biosynthesis, catalyzed by the Human Aromatase (HA) enzyme. Namely, we unprecedentedly propose that HA phosphorylation at Y361 markedly stabilizes its adduct with the flavin mononucleotide domain of CYP450s reductase (CPR), the redox partner of microsomal CYP450s, and a variety of other proteins. With CPR present at physiological conditions in a limiting ratio with respect to its multiple oxidative partners, the enhanced stability of the CPR/HA adduct may favor HA in the competition with the other proteins requiring CPR's electron supply, ultimately facilitating the electron transfer and estrogen biosynthesis. As a result, our work elucidates at atomic-level the post-translational regulation of CYP450s catalysis. Given the potential for rational clinical management of diseases associated with steroid metabolism disorders, unraveling this mechanism is of utmost importance, and raises the intriguing perspective of exploiting this knowledge to devise novel therapies.

Designing the Sniper: Improving Targeted Human Cytolytic Fusion Proteins for Anti-Cancer Therapy via Molecular Simulation.

Targeted human cytolytic fusion proteins (hCFPs) are humanized immunotoxins for selective treatment of different diseases including cancer. They are composed of a ligand specifically binding to target cells genetically linked to a human apoptosis-inducing enzyme. hCFPs target cancer cells via an antibody or derivative (scFv) specifically binding to e.g., tumor associated antigens (TAAs). After internalization and translocation of the enzyme from endocytosed endosomes, the human enzymes introduced into the cytosol are efficiently inducing apoptosis. Under in vivo conditions such enzymes are subject to tight regulation by native inhibitors in order to prevent inappropriate induction of cell death in healthy cells. Tumor cells are known to upregulate these inhibitors as a survival mechanism resulting in escape of malignant cells from elimination by immune effector cells. Cytosolic inhibitors of Granzyme B and Angiogenin (Serpin P9 and RNH1, respectively), reduce the efficacy of hCFPs with these enzymes as effector domains, requiring detrimentally high doses in order to saturate inhibitor binding and rescue cytolytic activity. Variants of Granzyme B and Angiogenin might feature reduced affinity for their respective inhibitors, while retaining or even enhancing their catalytic activity. A powerful tool to design hCFPs mutants with improved potency is given by in silico methods. These include molecular dynamics (MD) simulations and enhanced sampling methods (ESM). MD and ESM allow predicting the enzyme-protein inhibitor binding stability and the associated conformational changes, provided that structural information is available. Such "high-resolution" detailed description enables the elucidation of interaction domains and the identification of sites where particular point mutations may modify those interactions. This review discusses recent advances in the use of MD and ESM for hCFP development from the viewpoints of scientists involved in both fields.

Proton Dynamics in Protein Mass Spectrometry.

Native electrospray ionization/ion mobility-mass spectrometry (ESI/IM-MS) allows an accurate determination of low-resolution structural features of proteins. Yet, the presence of proton dynamics, observed already by us for DNA in the gas phase, and its impact on protein structural determinants, have not been investigated so far. Here, we address this issue by a multistep simulation strategy on a pharmacologically relevant peptide, the N-terminal residues of amyloid-ß peptide (Aß(1-16)). Our calculations reproduce the experimental maximum charge state from ESI-MS and are also in fair agreement with collision cross section (CCS) data measured here by ESI/IM-MS. Although the main structural features are preserved, subtle conformational changes do take place in the first ∼0.1 ms of dynamics. In addition, intramolecular proton dynamics processes occur on the picosecond-time scale in the gas phase as emerging from quantum mechanics/molecular mechanics (QM/MM) simulations at the B3LYP level of theory. We conclude that proton transfer phenomena do occur frequently during fly time in ESI-MS experiments (typically on the millisecond time scale). However, the structural changes associated with the process do not significantly affect the structural determinants.

A Self-Activated Mechanism for Nucleic Acid Polymerization Catalyzed by DNA/RNA Polymerases.

The enzymatic polymerization of DNA and RNA is the basis for genetic inheritance for all living organisms. It is catalyzed by the DNA/RNA polymerase (Pol) superfamily. Here, bioinformatics analysis reveals that the incoming nucleotide substrate always forms an H-bond between its 3'-OH and ß-phosphate moieties upon formation of the Michaelis complex. This previously unrecognized H-bond implies a novel self-activated mechanism (SAM), which synergistically connects the in situ nucleophile formation with subsequent nucleotide addition and, importantly, nucleic acid translocation. Thus, SAM allows an elegant and efficient closed-loop sequence of chemical and physical steps for Pol catalysis. This is markedly different from previous mechanistic hypotheses. Our proposed mechanism is corroborated via ab initio QM/MM simulations on a specific Pol, the human DNA polymerase-η, an enzyme involved in repairing damaged DNA. The structural conservation of DNA and RNA Pols supports the possible extension of SAM to Pol enzymes from the three domains of life.

Structure and dynamics of oligonucleotides in the gas phase.

By combining ion-mobility mass spectrometry experiments with sub-millisecond classical and ab initio molecular dynamics we fully characterized, for the first time, the dynamic ensemble of a model nucleic acid in the gas phase under electrospray ionization conditions. The studied oligonucleotide unfolds upon vaporization, loses memory of the solution structure, and explores true gas-phase conformational space. Contrary to our original expectations, the oligonucleotide shows very rich dynamics in three different timescales (multi-picosecond, nanosecond, and sub-millisecond). The shorter timescale dynamics has a quantum mechanical nature and leads to changes in the covalent structure, whereas the other two are of classical origin. Overall, this study suggests that a re-evaluation on our view of the physics of nucleic acids upon vaporization is needed.