NAMD goes quantum: an integrative suite for hybrid simulations

Machine Learning Approach to Vertical Energy Gap in Redox Processes

A straightforward approach to calculating the free energy change (ΔG) and reorganization energy of a redox process is linear response approximation (LRA). However, accurate prediction of redox properties is still challenging due to difficulties in conformational sampling and vertical energy-gap sampling. Expensive hybrid quantum mechanical/molecular mechanical (QM/MM) calculations are typically employed in sampling energy gaps using conformations from simulations. To alleviate the computational cost associated with the expensive QM method in the QM/MM calculation, we propose machine learning (ML) methods to predict the vertical energy gaps (VEGs). We tested several ML models to predict the VEGs and observed that simple models like linear regression show excellent performance (mean absolute error ∼0.1 eV) in predicting VEGs in all test systems, even when using features extracted from cheaper semiempirical methods. Our best ML model (extra trees regressor) shows a mean absolute error of around 0.1 eV while using features from the cheapest QM method. We anticipate our approach can be generalized to larger macromolecular systems with more complex redox centers.

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.

GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models

GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.

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.

Simulations predict preferred Mg2+ coordination in a nonenzymatic primer-extension reaction center

The mechanism by which genetic information was copied prior to the evolution of ribozymes is of great interest because of its importance to the origin of life. The most effective known process for the nonenzymatic copying of an RNA template is primer extension by a two-step pathway in which 2-aminoimidazole-activated nucleotides first react with each other to form an imidazolium-bridged intermediate that subsequently reacts with the primer. Reaction kinetics, structure-activity relationships, and X-ray crystallography have provided insight into the overall reaction mechanism, but many puzzles remain. In particular, high concentrations of Mg2+ are required for efficient primer extension, but the mechanism by which Mg2+ accelerates primer extension remains unknown. By analogy with the mechanism of DNA and RNA polymerases, a role for Mg2+ in facilitating the deprotonation of the primer 3'-hydroxyl is often assumed, but no catalytic metal ion is seen in crystal structures of the primer-extension complex. To explore the potential effects of Mg2+ binding in the reaction center, we performed atomistic molecular dynamics simulations of a series of modeled complexes in which a Mg2+ ion was placed in the reaction center with inner-sphere coordination with different sets of functional groups. Our simulations suggest that coordination of a Mg2+ ion with both O3' of the terminal primer nucleotide and the pro-Sp nonbridging oxygen of the reactive phosphate of an imidazolium-bridged dinucleotide would help to pre-organize the structure of the primer/template substrate complex to favor the primer-extension reaction. Our results suggest that the catalytic metal ion may play an important role in overcoming electrostatic repulsion between a deprotonated O3' and the reactive phosphate of the bridged dinucleotide and lead to testable predictions of the mode of Mg2+ binding that is most relevant to catalysis of primer extension.

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.

Revisiting Textbook Azide-Clock Reactions: A "Propeller-Crawling" Mechanism Explains Differences in Rates

An ongoing challenge to chemists is the analysis of pathways and kinetics for chemical reactions in solution, including transient structures between the reactants and products that are difficult to resolve using laboratory experiments. Here, we enabled direct molecular dynamics simulations of a textbook series of chemical reactions on the hundreds of ns to μs time scale using the weighted ensemble (WE) path sampling strategy with hybrid quantum mechanical/molecular mechanical (QM/MM) models. We focused on azide-clock reactions involving addition of an azide anion to each of three long-lived trityl cations in an acetonitrile-water solvent mixture. Results reveal a two-step mechanism: (1) diffusional collision of reactants to form an ion-pair intermediate; (2) "activation" or rearrangement of the intermediate to the product. Our simulations yield not only reaction rates that are within error of experiment but also rates for individual steps, indicating the activation step as rate-limiting for all three cations. Further, the trend in reaction rates is due to dynamical effects, i.e., differing extents of the azide anion "crawling" along the cation's phenyl-ring "propellers" during the activation step. Our study demonstrates the power of analyzing pathways and kinetics to gain insights on reaction mechanisms, underscoring the value of including WE and other related path sampling strategies in the modern toolbox for chemists.

Proton Coulomb Blockade Effect Involving Covalent Oxygen-Hydrogen Bond Switching

Instead of the canonical Grotthuss mechanism, we show that a knock-on proton transport process is preferred between organic functional groups (e.g., -COOH and -OH) and adjacent water molecules in biological proton channel and synthetic nanopores through comprehensive quantum and classical molecular dynamics simulations. The knock-on process is accomplished by the switching of covalent O─H bonds of the functional group under externally applied electric fields. The proton transport through the synthetic nanopore exhibits nonlinear current-voltage characteristics, suggesting an unprecedented proton Coulomb blockade effect. These findings not only enhance the understanding of proton transport in nanoconfined systems but also pave the way for the design of a variety of proton-based nanofluidic devices.

Computational Investigation of the Covalent Inhibition Mechanism of Bruton's Tyrosine Kinase by Ibrutinib

Covalent inhibitors represent a promising class of therapeutic compounds. Nonetheless, rationally designing covalent inhibitors to achieve a right balance between selectivity and reactivity remains extremely challenging. To better understand the covalent binding mechanism, a computational study is carried out using the irreversible covalent inhibitor of Bruton tyrosine kinase (BTK) ibrutinib as an example. A multi-μs classical molecular dynamics trajectory of the unlinked inhibitor is generated to explore the fluctuations of the compound associated with the kinase binding pocket. Then, the reaction pathway leading to the formation of the covalent bond with the cysteine residue at position 481 via a Michael addition is determined using the string method in collective variables on the basis of hybrid quantum mechanical-molecular mechanical (QM/MM) simulations. The reaction pathway shows a strong correlation between the covalent bond formation and the protonation/deprotonation events taking place sequentially in the covalent inhibition reaction, consistent with a 3-step reaction with transient thiolate and enolates intermediate states. Two possible atomistic mechanisms affecting deprotonation/protonation events from the thiolate to the enolate intermediate were observed: a highly correlated direct pathway involving proton transfer to the Cα of the acrylamide warhead from the cysteine involving one or a few water molecules and a more indirect pathway involving a long-lived enolate intermediate state following the escape of the proton to the bulk solution. The results are compared with experiments by simulating the long-time kinetics of the reaction using kinetic modeling.

Low-Barrier Hydrogen Bond Determines Target-Binding Affinity and Specificity of the Antitubercular Drug Bedaquiline

The role of short strong hydrogen bonds (SSHBs) in ligand-target binding remains largely unexplored, thereby hindering a potentially important avenue in rational drug design. Here we investigate the interaction between the antituberculosis drug bedaquiline (Bq) and the mycobacterial ATP synthase to unravel the role of a specific hydrogen bond to a conserved acidic residue in the target affinity and specificity. Our ab initio molecular dynamics simulations reveal that this bond belongs to the SSHB category and accounts for a substantial fraction of the target binding free energy. We also demonstrate that the presence of an extra acidic residue, i.e., aspartic acid at position 32 (D32), found exclusively in mycobacteria, cooperatively enhances the HB strength, ensuring specificity for the mycobacterial target. Consistently, we show that the removal of D32 markedly weakens the affinity, leading to Bq resistance associated with mutations of D32 to nonacidic residues. By designing simple Bq analogs, we then explore the possibility to overcome the resistance and potentially broaden the Bq antimicrobial spectrum by making the SSHB independent of the presence of the extra acidic residue.

Molecular docking, 3D-QASR and molecular dynamics simulations of benzimidazole Pin1 inhibitors

Pin1 (protein interacting with never-in-mitosis akinase-1) is a member of the family of peptidylprolyl cis-trans isomerases (PPIases) that specifically recognize and isomerize substrates containing phosphorylated Ser/Thr-Pro sequences. Pin1 is involved in many cellular processes and plays a key role in the cell cycle, transcriptional regulation, cell metabolism, proliferation and differentiation, and its abnormalities lead to degenerative and neoplastic diseases. Pin1 is highly expressed in human cancers and promotes the development of tumors by activating multiple oncogenes and inactivating multiple tumor suppressor genes, making it an attractive target for cancer therapy. In this study, we investigated the binding mechanism and conformational relationship between benzimidazole Pin1 inhibitors and Pin1 proteins by molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, binding free energy calculations and decomposition, and molecular dynamics simulations. Molecular docking and molecular dynamics simulations disclosed the most likely binding pose of benzimidazoles with the Pin1 protein. The results of 3D-QSAR modeling indicated that electrostatic fields, hydrophobic fields and hydrogen bonding play important roles in the binding process of inhibitors to proteins. The binding free energy calculations and energy decomposition indicated that Lys63, Arg69, Cys113, Leu122, Met130, and Ser154 may be key residues in the binding of benzimidazole-based inhibitors to the Pin1 protein. This study provides an important theoretical basis for the design and optimization of benzimidazole compounds.

Structural basis of respiratory complexes adaptation to cold temperatures

In response to cold, mammals activate brown fat for respiratory-dependent thermogenesis reliant on the electron transport chain (1, 2). Yet, the structural basis of respiratory complex adaptation to cold remains elusive. Herein we combined thermoregulatory physiology and cryo-EM to study endogenous respiratory supercomplexes exposed to different temperatures. A cold-induced conformation of CI:III 2 (termed type 2) was identified with a ∼25° rotation of CIII 2 around its inter-dimer axis, shortening inter-complex Q exchange space, and exhibiting different catalytic states which favor electron transfer. Large-scale supercomplex simulations in lipid membrane reveal how unique lipid-protein arrangements stabilize type 2 complexes to enhance catalytic activity. Together, our cryo-EM studies, multiscale simulations and biochemical analyses unveil the mechanisms and dynamics of respiratory adaptation at the structural and energetic level.

Histidine-assisted reduction of arylnitrenes upon photo-activation of phenyl azide chromophores in GFP-like fluorescent proteins

The photochemically active sites of the proteins sfGFP66azF and Venus66azF, members of the green fluorescent protein (GFP) family, contain a non-canonical amino acid residue p-azidophenylalanine (azF) instead of Tyr66. The light-induced decomposition of azF at these sites leads to the formation of reactive arylnitrene (nF) intermediates followed by the formation of phenylamine-containing chromophores. We report the first study of the reaction mechanism of the reduction of the arylnitrene intermediates in sfGFP66nF and Venus66nF using molecular modeling methods. The Gibbs energy profiles for the elementary steps of the chemical reaction in sfGFP66nF are computed using molecular dynamics simulations with quantum mechanics/molecular mechanics (QM/MM) potentials. Structures and energies along the reaction pathway in Venus66nF are evaluated using a QM/MM approach. According to the results of the simulations, arylnitrene reduction is coupled with oxidation of the histidine side chain on the His148 residue located near the chromophore.

Do Naturally Modified Nucleotides Contribute to Stabilizing Complexes between Ribosomes and Small Molecules? A Case Study with the Antitumor Drug Homoharringtonine

Modified nucleotides are ubiquitous with RNAs, also in contact with drugs that target the ribosome. Whether this represents a stabilization of the drug-ribosome complex, thus affecting the drug's affinity and possibly also intrinsic efficacy, remains an open question, however. The challenge of answering this question has been taken here with the only human-ribosome-targeting small-molecule currently in clinical use, the antitumor plant alkaloid homoharringtonine (HHT). The approach consisted in dissecting HHT-nucleotide interaction energies from QM-MM simulations in explicit water. What emerged is a network of mostly weak interactions of the large, branched HHT with standard nucleotides and a single modified nucleotide, out of the four ones present at PCT's A site. This is unlike the case of the small, compact marine antitumor alkaloid agelastatin A, which displays only a few, albeit strong, interactions with site-A ribosome nucleotides. This should aid tailoring drugs targeting the ribosome.

In silico prediction of mutation sites for anthranilate synthase from Serratia marcesens to deregulate tryptophan feedback inhibition

Allosteric feedback inhibition of the committed step in amino acid biosynthetic pathways is a major concern for production of amino acids at industrial scale. Anthranilate synthase (AS) catalyzes the first reaction of tryptophan biosynthetic pathway found in microorganisms and is feedback inhibited by its own product i.e. tryptophan. Here, we identified new mutant sites in AS using computational mutagenesis approach. MD simulations (20 ns) followed by MMPBSA and per residue decomposition energy analysis identified seven amino acid residues with best binding affinity for tryptophan. All 19 mutant structures were generated for each identified amino acid residue followed by simulation to evaluate effect of mutation on protein stability. Later, molecular docking studies were employed to generate mutant-tryptophan complex and structures with binding energies (kcal/mol) much higher than wild-type AS were selected. Finally, two mutants i.e., S37W and S37H were identified on the basis of positive binding scores and loss of tryptophan binding inside pocket. Further, MD simulations run for 200 ns were performed over these mutant-tryptophan complexes followed by RMSD, RMSF, radius of gyration , solvent accessible surface area , intra-protein hydrogen bond numbers, principal component analysis, free energy landscape (FEL) and secondary structure analysis to rationale effect of mutations on stability of protein. Cross correlation analysis of mutant site amino acids (S37W) with key residues of catalytic site (G325, T326, H395 and G482) was done to evaluate the effect of mutations on catalytic site conformation. Current computational mutagenesis approach predicted two mutants S37W and S37H with proposed deregulated feedback inhibition by tryptophan and retained catalytic activity.Communicated by Ramaswamy H. Sarma.

Multiscale QM/MM modelling of catalytic systems with ChemShell

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods are a powerful computational tool for the investigation of all forms of catalysis, as they allow for an accurate description of reactions occurring at catalytic sites in the context of a complicated electrostatic environment. The scriptable computational chemistry environment ChemShell is a leading software package for QM/MM calculations, providing a flexible, high performance framework for modelling both biomolecular and materials catalysis. We present an overview of recent applications of ChemShell to problems in catalysis and review new functionality introduced into the redeveloped Python-based version of ChemShell to support catalytic modelling. These include a fully guided workflow for biomolecular QM/MM modelling, starting from an experimental structure, a periodic QM/MM embedding scheme to support modelling of metallic materials, and a comprehensive set of tutorials for biomolecular and materials modelling.

VMD as a Platform for Interactive Small Molecule Preparation and Visualization in Quantum and Classical Simulations

Modeling and simulation of small molecules such as drugs and biological cofactors have been both a major focus of computational chemistry for decades and a growing need among computational biophysicists who seek to investigate the interaction of different types of ligands with biomolecules. Of particular interest in this regard are quantum mechanical (QM) calculations that are used to more accurately describe such small molecules, which can be of heterogeneous structures and chemistry, either in purely QM calculations or in hybrid QM/molecular mechanics (MM) simulations. QM programs are also used to develop MM force field parameters for small molecules to be used along with established force fields for biomolecules in classical simulations. With this growing need in mind, here we report a set of software tools developed and closely integrated within the broadly used molecular visualization/analysis program, VMD, that allow the user to construct, modify, and parametrize small molecules and prepare them for QM, hybrid QM/MM, or classical simulations. The tools also provide interactive analysis and visualization capabilities in an easy-to-use and integrated environment. In this paper, we briefly report on these tools and their major features and capabilities, along with examples of how they can facilitate molecular research in computational biophysics that might be otherwise prohibitively complex.

Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike

Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.

Multiscale Simulations of the Covalent Inhibition of the SARS-CoV-2 Main Protease: Four Compounds and Three Reaction Mechanisms

We report the results of computational modeling of the reactions of the SARS-CoV-2 main protease (MPro) with four potential covalent inhibitors. Two of them, carmofur and nirmatrelvir, have shown experimentally the ability to inhibit MPro. Two other compounds, X77A and X77C, were designed computationally in this work. They were derived from the structure of X77, a non-covalent inhibitor forming a tight surface complex with MPro. We modified the X77 structure by introducing warheads capable of reacting with the catalytic cysteine residue in the MPro active site. The reaction mechanisms of the four molecules with MPro were investigated by quantum mechanics/molecular mechanics (QM/MM) simulations. The results show that all four compounds form covalent adducts with the catalytic cysteine Cys 145 of MPro. From the chemical perspective, the reactions of these four molecules with MPro follow three distinct mechanisms. The reactions are initiated by a nucleophilic attack of the thiolate group of the deprotonated cysteine residue from the catalytic dyad Cys145-His41 of MPro. In the case of carmofur and X77A, the covalent binding of the thiolate to the ligand is accompanied by the formation of the fluoro-uracil leaving group. The reaction with X77C follows the nucleophilic aromatic substitution SNAr mechanism. The reaction of MPro with nirmatrelvir (which has a reactive nitrile group) leads to the formation of a covalent thioimidate adduct with the thiolate of the Cys145 residue in the enzyme active site. Our results contribute to the ongoing search for efficient inhibitors of the SARS-CoV-2 enzymes.

Horizontal proton transfer across the antiporter-like subunits in mitochondrial respiratory complex I

Respiratory complex I is a redox-driven proton pump contributing to about 40% of total proton motive force required for mitochondrial ATP generation. Recent high-resolution cryo-EM structural data revealed the positions of several water molecules in the membrane domain of the large enzyme complex. However, it remains unclear how protons flow in the membrane-bound antiporter-like subunits of complex I. Here, we performed multiscale computer simulations on high-resolution structural data to model explicit proton transfer processes in the ND2 subunit of complex I. Our results show protons can travel the entire width of antiporter-like subunits, including at the subunit-subunit interface, parallel to the membrane. We identify a previously unrecognized role of conserved tyrosine residues in catalyzing horizontal proton transfer, and that long-range electrostatic effects assist in reducing energetic barriers of proton transfer dynamics. Results from our simulations warrant a revision in several prevailing proton pumping models of respiratory complex I.

Combined Structural and Computational Study of the mRubyFT Fluorescent Timer Locked in Its Blue Form

The mRubyFT is a monomeric genetically encoded fluorescent timer based on the mRuby2 fluorescent protein, which is characterized by the complete maturation of the blue form with the subsequent conversion to the red one. It has higher brightness in mammalian cells and higher photostability compared with other fluorescent timers. A high-resolution structure is a known characteristic of the mRubyFT with the red form chromophore, but structural details of its blue form remain obscure. In order to obtain insight into this, we obtained an S148I variant of the mRubyFT (mRubyFT^S148I) with the blocked over time blue form of the chromophore. X-ray data at a 1.8 Å resolution allowed us to propose a chromophore conformation and its interactions with the neighboring residues. The imidazolidinone moiety of the chromophore is completely matured, being a conjugated π-system. The methine bridge is not oxidized in the blue form bringing flexibility to the phenolic moiety that manifests itself in poor electron density. Integration of these data with the results of molecular dynamic simulation disclosed that the OH group of the phenolic moiety forms a hydrogen bond with the side chain of the T163 residue. A detailed comparison of mRubyFT^S148I with other available structures of the blue form of fluorescent proteins, Blue102 and mTagBFP, revealed a number of characteristic differences. Molecular dynamic simulations with the combined quantum mechanic/molecular mechanic potentials demonstrated that the blue form exists in two protonation states, anion and zwitterion, both sharing enolate tautomeric forms of the C=C-O^- fragment. These two forms have similar excitation energies, as evaluated by calculations. Finally, excited state molecular dynamic simulations showed that excitation of the chromophore in both protonation states leads to the same anionic fluorescent state. The data obtained shed light on the structural features and spectral properties of the blue form of the mRubyFT timer.

Computational Modeling of the Interaction of Molecular Oxygen with the miniSOG Protein—A Light Induced Source of Singlet Oxygen

Interaction of molecular oxygen 3O2 with the flavin-dependent protein miniSOG after light illumination results in creation of singlet oxygen 1O2 and superoxide O2●−. Despite the recently resolved crystal structures of miniSOG variants, oxygen-binding sites near the flavin chromophore are poorly characterized. We report the results of computational studies of the protein−oxygen systems using molecular dynamics (MD) simulations with force-field interaction potentials and quantum mechanics/molecular mechanics (QM/MM) potentials for the original miniSOG and the mutated protein. We found several oxygen-binding pockets and pointed out possible tunnels bridging the bulk solvent and the isoalloxazine ring of the chromophore. These findings provide an essential step toward understanding photophysical properties of miniSOG—an important singlet oxygen photosensitizer.

Unraveling Binding Mechanism and Stability of Urease Inhibitors: A QM/MM MD Study

Soil bacteria can produce urease, which catalyzes the hydrolysis of urea to ammonia (NH3) and carbamate. A variety of urease inhibitors have been proposed to reduce NH3 volatilization by interfering with the urease activity. We report a quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) study on the mechanism employed for the inhibition of urease by three representative competitive inhibitors; namely, acetohydroxamic acid (AHA), hydroxyurea (HU), and N-(n-butyl)phosphorictriamide (NBPTO). The possible connections between the structural and thermodynamical properties and the experimentally observed inhibition efficiency were evaluated and characterized. We demonstrate that the binding affinity decreases in the order NBPTO >> AHA > HU in terms of the computed activation and reaction free energies. This trend also indicates that NBPTO shows the highest inhibitory activity and the lowest IC50 value of 2.1 nM, followed by AHA (42 μM) and HU (100 μM). It was also found that the X=O moiety (X = carbon or phosphorous) plays a crucial role in the inhibitor binding process. These findings not only elucidate why the potent urease inhibitors are effective but also have implications for the design of new inhibitors.

Long-time-step molecular dynamics can retard simulation of protein-ligand recognition process

Molecular dynamics (MD) simulation of biologically relevant processes at realistic time scale and atomistic precision is generally limited by prohibitively large computational cost, due to its restriction of using an ultrashort integration time step (1-2 fs). A popular numerical recipe to reduce the associated computational burden is adopting schemes that would allow relatively longer-time-step for MD propagation. Here, we explore the perceived potential of one of the most frequently used long-time-step protocols, namely the hydrogen mass repartitioning (HMR) approach, in alleviating the computational overhead associated with simulation of the kinetic process of protein-ligand recognition events. By repartitioning the mass of heavier atoms to their linked hydrogen atoms, HMR leverages around twofold longer time step than regular simulation, holding promise of significant performance boost. However, our probe into direct simulation of the protein-ligand recognition event, one of the computationally most challenging processes, shows that long-time-step HMR MD simulations do not necessarily translate to a computationally affordable solution. Our investigations spanning cumulative 176 μs in three independent proteins (T4 lysozyme, sensor domain of MopR, and galectin-3) show that long-time-step HMR-based MD simulations can catch the ligand in its act of recognizing the native cavity. But, as a major caveat, the ligand is found to require significantly longer time to identify buried native protein cavity in an HMR MD simulation than regular simulation, thereby defeating the purpose of its usage for performance upgrade. A molecular analysis shows that the longer time required by a ligand to recognize the protein in HMR is rooted in faster diffusion of the ligand, which reduces the survival probability of decisive on-pathway metastable intermediates, thereby slowing down the eventual recognition process at the native cavity. Together, the investigation stresses careful assessment of pitfalls of long-time-step algorithms before attempting to utilize them for higher performance for biomolecular recognition simulations.

The Electronic Structure of Genome Editors from the First Principles

Genome editing based on the CRISPR-Cas9 system has paved new avenues for medicine, pharmaceutics, biotechnology, and beyond. This article reports the role of first-principles (ab-initio) molecular dynamics (MD) in the CRISPR-Cas9 revolution, achieving a profound understanding of the enzymatic function and offering valuable insights for enzyme engineering. We introduce the methodologies and explain the use of ab-initio MD simulations to characterize the two-metal dependent mechanism of DNA cleavage in the RuvC domain of the Cas9 enzyme, and how a second catalytic domain, HNH, cleaves the target DNA with the aid of a single metal ion. A detailed description of how ab-initio MD is combined with free-energy methods - i.e., thermodynamic integration and metadynamics - to break and form chemical bonds is given, explaining the use of these methods to determine the chemical landscape and establish the catalytic mechanism in CRISPR-Cas9. The critical role of classical methods is also discussed, explaining theory and application of constant pH MD simulations, used to accurately predict the catalytic residues' protonation states. Overall, first-principles methods are shown to unravel the electronic structure of the Cas9 enzyme, providing valuable insights that can serve for the design of genome editing tools with improved catalytic efficiency or controllable activity.

The application of QM/MM simulations in heterogeneous catalysis

The QM/MM simulation method is provenly efficient for the simulation of biological systems, where an interplay of extensive environment and delicate local interactions drives a process of interest through a funnel on a complex energy landscape. Recent advances in quantum chemistry and force-field methods present opportunities for the adoption of QM/MM to simulate heterogeneous catalytic processes, and their related systems, where similar intricacies exist on the energy landscape. Herein, the fundamental theoretical considerations for performing QM/MM simulations, and the practical considerations for setting up QM/MM simulations of catalytic systems, are introduced; then, areas of heterogeneous catalysis are explored where QM/MM methods have been most fruitfully applied. The discussion includes simulations performed for adsorption processes in solvent at metallic interfaces, reaction mechanisms within zeolitic systems, nanoparticles, and defect chemistry within ionic solids. We conclude with a perspective on the current state of the field and areas where future opportunities for development and application exist.

To the Understanding of Catalysis by D-Amino Acid Transaminases: A Case Study of the Enzyme from Aminobacterium colombiense

Pyridoxal-5'-phosphate (PLP)-dependent transaminases are highly efficient biocatalysts for stereoselective amination. D-amino acid transaminases can catalyze stereoselective transamination producing optically pure D-amino acids. The knowledge of substrate binding mode and substrate differentiation mechanism in D-amino acid transaminases comes down to the analysis of the transaminase from Bacillus subtilis. However, at least two groups of D-amino acid transaminases differing in the active site organization are known today. Here, we present a detailed study of D-amino acid transaminase from the gram-negative bacterium Aminobacterium colombiense with a substrate binding mode different from that for the transaminase from B. subtilis. We study the enzyme using kinetic analysis, molecular modeling, and structural analysis of holoenzyme and its complex with D-glutamate. We compare the multipoint binding of D-glutamate with the binding of other substrates, D-aspartate and D-ornithine. QM/MM MD simulation reveals that the substrate can act as a base and its proton can be transferred from the amino group to the α-carboxylate group. This process occurs simultaneously with the nucleophilic attack of the PLP carbon atom by the nitrogen atom of the substrate forming gem-diamine at the transimination step. This explains the absence of the catalytic activity toward (R)-amines that lack an α-carboxylate group. The obtained results clarify another substrate binding mode in D-amino acid transaminases and underpinned the substrate activation mechanism.

Quantum-based Modeling of Protein-ligand Interaction: The Complex of RutA with Uracil and Molecular Oxygen

Modern quantum-based methods are employed to model interaction of the flavin-dependent enzyme RutA with the uracil and oxygen molecules. This complex presents the structure of reactants for the chain of chemical reactions of monooxygenation in the enzyme active site, which is important in drug metabolism. In this case, application of quantum-based approaches is an essential issue, unlike conventional modeling of protein-ligand interaction with force fields using molecular mechanics and classical molecular dynamics methods. We focus on two difficult problems to characterize the structure of reactants in the RutA-FMN-O₂ -uracil complex, where FMN stands for the flavin mononucleotide species. First, location of a small O₂ molecule in the triplet spin state in the protein cavities is required. Second, positions of both ligands, O₂ and uracil, must be specified in the active site with a comparable accuracy. We show that the methods of molecular dynamics with the interaction potentials of quantum mechanics/molecular mechanics theory (QM/MM MD) allow us to characterize this complex and, in addition, to surmise possible reaction mechanism of uracil oxygenation by RutA.

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed

This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.

Extending multi-layer energy-based fragment method for excited-state calculations of large covalently bonded fragment systems

Recently, we developed a low-scaling Multi-Layer Energy-Based Fragment (MLEBF) method for accurate excited-state calculations and nonadiabatic dynamics simulations of nonbonded fragment systems. In this work, we extend the MLEBF method to treat covalently bonded fragment ones. The main idea is cutting a target system into many fragments according to chemical properties. Fragments with dangling bonds are first saturated by chemical groups; then, saturated fragments, together with the original fragments without dangling bonds, are grouped into different layers. The accurate total energy expression is formulated with the many-body energy expansion theory, in combination with the inclusion-exclusion principle that is used to delete the contribution of chemical groups introduced to saturate dangling bonds. Specifically, in a two-layer MLEBF model, the photochemically active and inert layers are calculated with high-level and efficient electronic structure methods, respectively. Intralayer and interlayer energies can be truncated at the two- or three-body interaction level. Subsequently, through several systems, including neutral and charged covalently bonded fragment systems, we demonstrate that MLEBF can provide accurate ground- and excited-state energies and gradients. Finally, we realize the structure, conical intersection, and path optimizations by combining our MLEBF program with commercial and free packages, e.g., ASE and SciPy. These developments make MLEBF a practical and reliable tool for studying complex photochemical and photophysical processes of large nonbonded and bonded fragment systems.

Challenges in Protein QM/MM Simulations with Intra-Backbone Link Atoms

Hybrid quantum mechanical/molecular mechanical (QM/MM) simulations fuel discoveries in many fields of science including computational biochemistry and enzymology. Development of more convenient tools leads to an increase in the number of works in which mechanical insights into enzymes' mode of operation are obtained. Most commonly, these tools feature hydrogen-capping (link atom) approach to provide coupling between QM and MM subsystems across a covalent bond. Extensive studies were conducted to provide a solid foundation for the correctness of such an approach when a bond to a nonpolar MM atom is considered. However, not every task may be accomplished this way. Certain scenarios of using QM/MM in computational enzymology encourage or even necessitate the incorporation of backbone atoms into the QM region. Two out of three backbone atoms are polar, and in QM/MM with electrostatic embedding, a neighboring link atom will be hyperpolarized. Several schemes to mitigate this effect were previously proposed alongside a rigorous assessment of quantitative effects on model systems. However, it was not clear whether they may translate into qualitatively different results and how link atom hyperpolarization may manifest itself in a real-life enzymological scenario. Here, we show that the consequences of such an artifact may be severe and may completely overturn the conclusions drawn from the simulations. Our case advocates for the use of charge redistribution schemes whenever intra-backbone QM/MM boundaries are considered. Moreover, we addressed how different boundary types and charge redistribution schemes influence backbone dynamics. We showed that the results are heavily dependent on which boundary MM terms are retained, with charge alteration being of secondary importance. In the worst case, only three intra-backbone boundaries may be used with relative confidence in the adequacy of resulting simulations, irrespective of the hyperpolarization mitigation scheme. Thus, advances in the field are certainly needed to fuel new discoveries. As of now, we believe that issues raised in this work might encourage authors in the field to report what boundaries, boundary MM terms, and charge redistribution schemes they are using, so their results may be correctly interpreted.

How acidic amino acid residues facilitate DNA target site selection

Despite the negative charge of the DNA backbone, acidic residues (Asp/Glu) commonly participate in the base readout, with a strong preference for cytosine. In fact, in the solved DNA/protein structures, cytosine is recognized almost exclusively by Asp/Glu through a direct hydrogen bond, while at the same time, adenine, regardless of its amino group, shows no propensity for Asp/Glu. Here, we analyzed the contribution of Asp/Glu to sequence-specific DNA binding using classical and ab initio simulations of selected transcription factors and found that it is governed by a fine balance between the repulsion from backbone phosphates and attractive interactions with cytosine. Specifically, Asp/Glu lower the affinity for noncytosine sites and thus act as negative selectors preventing off-target binding. At cytosine-containing sites, the favorable contribution does not merely rely on the formation of a single H-bond but usually requires the presence of positive potential generated by multiple cytosines, consistently with the observed excess of cytosine in the target sites. Finally, we show that the preference of Asp/Glu for cytosine over adenine is a result of the repulsion from the adenine imidazole ring and a tendency of purine-purine dinucleotides to adopt the BII conformation.

G-quadruplex-mediated specific recognition, stabilization and transcriptional repression of bcl-2 by small molecule

The presence of the G-quadruplex (G4) structure in the promoter region of the human bcl-2 oncogenes makes it a promising target for developing anti-cancer therapeutics. Bcl-2 inhibits apoptosis, and its frequent overexpression in cancer cells contributes to tumor initiation, progression, and resistance to therapy. Small molecules that can specifically bind to bcl-2 G4 with high affinity and selectivity are remaining elusive. Here, we report that small molecule 1,3-bis-) furane-2yl-methylidene-amino) guanidine (BiGh) binds to bcl-2 G4 DNA structure with very high affinity and selectivity over other genomic G4 DNA structures and duplex DNA. BiGh stabilizes folded parallel conformation of bcl-2 G4 via non-covalent and electrostatic interactions and increases the thermal stabilization up to 15 °C. The ligand significantly suppresses the bcl-2 transcription in HeLa cells by a G4-dependent mechanism and induces cell cycle arrest which promotes apoptosis. The in silico ADME profiling confirms the potential 'drug-likeness' of BiGh. Our results showed that BiGh stabilizes the bcl-2 G-quadruplex motif, downregulates the bcl-2 gene transcription as well as translation process in cervical cancer cells, and exhibits potential anti-cancer activity. This work provides a potential platform for the development of lead compound(s) as G4 stabilizers with drug-like properties of BiGh for cancer therapeutics.

Molecular docking, 3D-QASR and molecular dynamics simulations of thiazoles Pin1 inhibitors

Pin1 (protein interacting with never-in-mitosis akinase-1) is a member of the PPIase (peptidylprolyl cis-trans isomerase) family. It can interact with a variety of carcinogenic or tumor suppressive phosphorylated proteins. The interaction results in the conformational changes of target proteins, and ultimately regulates the activity of these proteins. These activity changes play a key role in tumorigenesis. Pin1 is an attractive target for cancer therapy due to its over-expression and/or activation in various types of cancer and the disorder of Proline directed phosphorylation. In this study, molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular dynamics (MD) simulations were performed to investigate the structure-activity relationship and binding mechanism of 45 thiazole-class Pin1 inhibitors. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. The results of the 3 D-QSAR model show that electrostatic field, hydrophobic field and hydrogen bond play important roles in the binding process of inhibitors to protein. Molecular dynamics simulation results reveal that the complex of the ligand and the receptor protein are stable at 300 K. The binding free energy calculation and energy decomposition results show that His59, Cys113, Ser114, Ser115, Leu122, Met130, Gln131, Phe134, Ser154 and His157 may be the key to the inhibitor binding to Pin1 protein. This study provides an important theoretical basis for further development of the new Pin1 inhibitor design. These results can provide more useful information for our further drug design. Communicated by Ramaswamy H. Sarma.

Interplay between the Enamine and Imine Forms of the Hydrolyzed Imipenem in the Active Sites of Metallo-β-lactamases and in Water Solution

Deactivation of the β-lactam antibiotics in the active sites of the β-lactamases is among the main mechanisms of bacterial antibiotic resistance. As drugs of last resort, carbapenems are efficiently hydrolyzed by metallo-β-lactamases, presenting a serious threat to human health. Our study reveals mechanistic aspects of the imipenem hydrolysis by bizinc metallo-β-lactamases, NDM-1 and L1, belonging to the B1 and the B3 subclasses, respectively. The results of QM(PBE0-D3/6-31G**)/MM simulations show that the enamine product with the protonated nitrogen atom is formed as the major product in NDM-1 and as the only product in the L1 active site. In NDM-1, there is also another reaction pathway that leads to the formation of the (S)-enantiomer of the imine form of the hydrolyzed imipenem; this process occurs with the higher energy barriers. The absence of the second pathway in L1 is due to the different amino acid composition of the active site loop. In L1, the hydrophobic Pro226 residue is located above the pyrroline ring of imipenem that blocks protonation of the carbon atom. Electron density analysis is performed at the stationary points to compare reaction pathways in L1 and NDM-1. Tautomerization from the enamine to the imine form likely happens in solution after the dissociation of the hydrolyzed imipenem from the active site of the enzyme. Classical molecular dynamics simulations of the hydrolyzed imipenem in solution, both with the neutral enamine and the negatively charged N-C₂-C₃ fragment, demonstrate a huge diversity of conformations. The vast majority of conformations blocks the C₃-atom from the side required for the (S)-imine formation upon tautomerization. Thus, according to our calculations, formation of the (R)-imine is more likely. QM(PBE0-D3/6-31G**)/MM molecular dynamics simulations of the hydrolyzed imipenem with the negatively charged N-C₂-C₃ fragment followed by the Laplacian bond order analysis demonstrate that the N═C₂-C₃^- resonance structure is the most pronounced that facilitates formation of the imine form. The proposed mechanism of the enzymatic enamine formation and its subsequent tautomerization to the imine form in solution is in agreement with the recent spectroscopic and NMR studies.

Evolution of Ceftriaxone Resistance of Penicillin-Binding Proteins 2 Revealed by Molecular Modeling

Penicillin-binding proteins 2 (PBP2) are critically important enzymes in the formation of the bacterial cell wall. Inhibition of PBP2 is utilized in the treatment of various diseases, including gonorrhea. Ceftriaxone is the only drug used to treat gonorrhea currently, and recent growth in PBP2 resistance to this antibiotic is a serious threat to human health. Our study reveals mechanistic aspects of the inhibition reaction of PBP2 from the wild-type FA19 strain and mutant 35/02 and H041 strains of Neisseria Gonorrhoeae by ceftriaxone. QM(PBE0-D3/6-31G**)/MM MD simulations show that the reaction mechanism for the wild-type PBP2 consists of three elementary steps including nucleophilic attack, C-N bond cleavage in the β-lactam ring and elimination of the leaving group in ceftriaxone. In PBP2 from the mutant strains, the second and third steps occur simultaneously. For all considered systems, the acylation rate is determined by the energy barrier of the first step that increases in the order of PBP2 from FA19, 35/02 and H041 strains. Dynamic behavior of ES complexes is analyzed using geometry and electron density features including Fukui electrophilicity index and Laplacian of electron density maps. It reveals that more efficient activation of the carbonyl group of the antibiotic leads to the lower energy barrier of nucleophilic attack and larger stabilization of the first reaction intermediate. Dynamical network analysis of MD trajectories explains the differences in ceftriaxone binding affinity: in PBP2 from the wild-type strain, the β₃-β₄ loop conformation facilitates substrate binding, whereas in PBP2 from the mutant strains, it exists in the conformation that is unfavorable for complex formation. Thus, we clarify that the experimentally observed decrease in the second-order rate constant of acylation (k₂/K_S) in PBP2 from the mutant strains is due to both a decrease in the acylation rate constant k₂ and an increase in the dissociation constant K_S.

Predicting Solvent Effects on SN2 Reaction Rates: Comparison of QM/MM, Implicit, and MM Explicit Solvent Models

Solvents are one of the key variables in the optimization of a synthesis yield or properties of a synthesis product. In this paper, contemporary solvent models are applied to predict the rates of S_N2 reactions in a range of aqueous and non-aqueous solvents. High-level CCSD(T)/CBS//M06-2X/6-31+G(d) gas phase energies were combined with solvation free energies from SMD, SM12, and ADF-COSMO-RS continuum solvent models, as well as molecular mechanics (MM) explicit solvent models with different atomic charge schemes to predict the rate constants of three S_N2 reactions in eight protic and aprotic solvents. It is revealed that the prediction of rate constants in organic solvents is not necessarily less challenging than in water and popular solvent models struggle to predict their rate constants to within 3 log units of experimental values. Among the continuum solvent models, the ADF-COSMO-RS model performed the best in predicting absolute rate contants while the SM12 model was best at predicting relative rate constants with an average accuracy of about 1.5 and 0.8 log units, respectively. The use of computationally more demanding MM explicit solvent models did not translate to improvements in absolute rate constants but was quite effective at predicting relative rate constants due to systematic error cancellation. Free energy barriers obtained from umbrella sampling with explicit solvent QM/MM simulations led to excellent agreement with experimental values, provided that a validated level of theory is used to treat the QM region.

An understanding of coronavirus and exploring the molecular dynamics simulations to find promising candidates against the Mpro of nCoV to combat the COVID-19: A systematic review

The first infection case of new coronavirus was reported at the end of 2019 and after then, the cases are reported in all nations across the world in a very short period. Further, the regular news of mutations in the virus has made life restricted with appropriate behavior. To date, a new strain (Omicron and its new subvariant Omicron XE) has brought fear amongst us due to a higher trajectory of increase in the number of cases. The researchers thus started giving attention to this viral infection and discovering drug-like candidates to cure the infections. Finding a drug for any viral infection is not an easy task and takes plenty of time. Therefore, computational chemistry/bioinformatics is followed to get promising molecules against viral infection. Molecular dynamics (MD) simulations are being explored to get drug candidates in a short period. The molecules are screened via molecular docking, which provides preliminary information which can be further verified by molecular dynamics (MD) simulations. To understand the change in structure, MD simulations generated several trajectories such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonding, and radius of gyration for the main protease (Mpro) of the new coronavirus (nCoV) in the presence of small molecules. Additionally, change in free energy for the formation of complex of Mpro of nCoV with the small molecule can be determined by applying molecular mechanics with generalized born and surface area solvation (MM-GBSA). Thus, the promising molecules can be further explored for clinical trials to combat coronavirus disease-19 (COVID-19).

Discovery of potent Guanidine derivative that selectively binds and stabilizes the human BCL-2 G-quadruplex DNA and downregulates the transcription

Small molecules that interact with quadruplexes offer a wide range of potential applications, including not just as medications but also as sensors for quadruplexes structures. The BCL-2 is a proto-oncogene that often gets mutated in lethal cancer and could be an interesting target for developing an anti-cancer drug. In the present study, we have employed various biophysical techniques such as fluorescence, CD, Isothermal calorimeter, gel retardation, and PCR stop assay, indicating that Guanidine derivatives GD-1 and GD-2 selectively interact with high affinity with BCL-2 G-quadruplex over other G-quadruplex DNA and duplex DNA. The most promising small molecule GD-1 increases the thermostability of the BCL-2 GQ structure by 12°C. Our biological experiments such as ROS generation, qRT-PCR, western blot, TFP based Reporter assay, show that the GD-1 ligand causes a synthetic lethal interaction by suppressing the expression BCL-2 genes via interaction and stabilization of its the promoter G-quadruplexes in HeLa cells and act as a potential anti-cancer agent.

Protein structure prediction in the era of AI: Challenges and limitations when applying to in silico force spectroscopy

Mechanoactive proteins are essential for a myriad of physiological and pathological processes. Guided by the advances in single-molecule force spectroscopy (SMFS), we have reached a molecular-level understanding of how mechanoactive proteins sense and respond to mechanical forces. However, even SMFS has its limitations, including the lack of detailed structural information during force-loading experiments. That is where molecular dynamics (MD) methods shine, bringing atomistic details with femtosecond time-resolution. However, MD heavily relies on the availability of high-resolution structural data, which is not available for most proteins. For instance, the Protein Data Bank currently has 192K structures deposited, against 231M protein sequences available on Uniprot. But many are betting that this gap might become much smaller soon. Over the past year, the AI-based AlphaFold created a buzz on the structural biology field by being able to predict near-native protein folds from their sequences. For some, AlphaFold is causing the merge of structural biology with bioinformatics. Here, using an in silico SMFS approach pioneered by our group, we investigate how reliable AlphaFold structure predictions are to investigate mechanical properties of Staphylococcus bacteria adhesins proteins. Our results show that AlphaFold produce extremally reliable protein folds, but in many cases is unable to predict high-resolution protein complexes accurately. Nonetheless, the results show that AlphaFold can revolutionize the investigation of these proteins, particularly by allowing high-throughput scanning of protein structures. Meanwhile, we show that the AlphaFold results need to be validated and should not be employed blindly, with the risk of obtaining an erroneous protein mechanism.

Intermolecular Interactions of Nucleoside Antibiotic Tunicamycin with On-Target MraYCB-TUN and Off-Target DPAGT1-TUN in the Active Sites Delineated by Quantum Mechanics/Molecular Mechanics Calculations

Tunicamycin (TUN) is a nucleoside antibiotic with a complex structure comprising uracil, tunicamine sugar, N-acetylglucosamine (GlcNAc), and fatty acyl tail moieties. TUN, known as a canonical inhibitor, blocks vital functions of certain transmembrane protein families, for example, the insect enzyme dolichyl phosphate α-N-acetylglucosaminylphosphotransferase (DPAGT1) of Spodoptera frugiperda and the bacterial enzyme phospho-N-acetylmuramoylpentapeptide translocase (MraY_CB) of Clostridium bolteae. Accurate description of protein-drug interactions has an immense impact on structure-based drug design, while the main challenge is to create proper topology and parameter entries for TUN in modeling protein-TUN interactions given the structural complexity. Starting from DPAGT1-TUN and MraY_CB-TUN crystal structures, we first sketched these structural complexes on the basis of the CHARMM36 force field and optimized each of them using quantum mechanics/molecular mechanics (QM/MM) calculations. By continuing calculations on the active site (QM region) of each optimized structure, we specified the characteristics of intermolecular interactions contributing to the binding of TUN to each active site by quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) analyses at the M06-2X/6-31G** level. The results outlined that TUN insertion into each active site requires multiple weak, moderate, and strong hydrogen bonds accompanying charge-dipole, dipole-dipole, and hydrophobic interactions among different TUN moieties and adjacent residues. The water-mediated interactions also play central roles in situating the uracil and tunicamine moieties of TUN within the DPAGT1 active site as well as in preserving the uracil-binding pocket in the MraY_CB active site. The TUN binds more strongly to DPAGT1 than to MraY_CB. The information garnered here is valuable particularly for better understanding mode of action at the molecular level, as it is conducive to developing next generations of nucleoside antibiotics.

INAQS, a Generic Interface for Nonadiabatic QM/MM Dynamics: Design, Implementation, and Validation for GROMACS/Q-CHEM simulations

The accurate description of large molecular systems in complex environments remains an ongoing challenge for the field of computational chemistry. This problem is even more pronounced for photoinduced processes, as multiple excited electronic states and their corresponding nonadiabatic couplings must be taken into account. Multiscale approaches such as hybrid quantum mechanics/molecular mechanics (QM/MM) offer a balanced compromise between accuracy and computational burden. Here, we introduce an open-source software package (INAQS) for nonadiabatic QM/MM simulations that bridges the sampling capabilities of the GROMACS MD package and the excited-state infrastructure of the Q-CHEM electronic structure software. The interface is simple and can be adapted easily to other MD codes. The code supports a variety of different trajectory-based molecular dynamics, ranging from Born-Oppenheimer to surface hopping dynamics. To illustrate the power of this combination, we simulate electronic absorption spectra, free-energy surfaces along a reaction coordinate, and the excited-state dynamics of 1,3-cyclohexadiene in solution.

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India

Background

The massive increase in COVID-19 infection had generated a second wave in India during May–June 2021 with a critical pandemic situation. The Delta variant (B.1.617.2) was a significant factor during the second wave. Conversely, the UK had passed through the crucial phase of the pandemic from November to December 2020 due to B.1.1.7. The study tried to comprehend the pandemic response in the UK and India to the spread of the B.1.1.7 (Alpha, UK) variant and B.1.617.2 (Delta, India) variant.

Methods

This study was performed in three directions to understand the pandemic response of the two emerging variants. First, we served comparative genomics, such as genome sequence submission patterns, mutational landscapes, and structural landscapes of significant mutations (N501Y, D614G, L452R, E484Q, and P681R). Second, we performed evolutionary epidemiology using molecular phylogenetics, scatter plots of the cluster evaluation, country-wise transmission pattern, and frequency pattern. Third, the receptor binding pattern was analyzed using the Wuhan reference strain and the other two variants.

Results

The study analyzed the country-wise and region-wise genome sequences and their submission pattern, molecular phylogenetics, scatter plot of the cluster evaluation, country-wise geographical distribution and transmission pattern, frequency pattern, entropy diversity, and mutational landscape of the two variants. The structural pattern was analyzed in the N501Y, D614G L452R, E484Q, and P681R mutations. The study found increased molecular interactivity between hACE2-RBD binding of B.1.1.7 and B.1.617.2 compared to the Wuhan reference strain. Our receptor binding analysis showed a similar indication pattern for hACE2-RBD of these two variants. However, B.1.617.2 offers slightly better stability in the hACE2-RBD binding pattern through MD simulation than B.1.1.7.

Conclusion

The increased hACE2-RBD binding pattern of B.1.1.7 and B.1.617.2 might help to increase the infectivity compared to the Wuhan reference strain.

Multistructural microiteration combined with QM/MM-ONIOM electrostatic embedding

Multistructural microiteration (MSM) is a method to take account of contributions of multiple surrounding structures in a geometrical optimization or reaction path calculation using the quantum mechanics/molecular mechanics (QM/MM) ONIOM method. In this study, we combined MSM with the electrostatic embedding (EE) scheme of the QM/MM-ONIOM method by extending its original formulation for mechanical embedding (ME). MSM-EE takes account of the polarization in the QM region induced by point charges assigned to atoms in the multiple surrounding structures, where the point charges are scaled by the weight factor of each surrounding structure determined through MSM. The performance of MSM-EE was compared with that of the other methods, i.e., ONIOM-ME, ONIOM-EE, and MSM-ME, by applying them to three chemical processes: (1) chorismate-to-prephenate transformation in aqueous solution, (2) the same transformation as (1) in an enzyme, and (3) hydroxylation in p-hydroxybenzoate hydroxylase. These numerical tests of MSM-EE yielded barriers and reaction energies close to experimental values with computational costs comparable to those of the other three methods.