Metadynamics as a tool for exploring free energy landscapes of chemical reactions

Efficient acceleration of the convergence of the minimum free energy path via a path-planning generated initial guess

We demonstrate that combining a shifted clustering algorithm with a fast-marching-based algorithm can generate accurate approximations of the minimum energy path (MEP) given a free energy landscape (FEL). Using this approximation as the initial guess for the MEP, followed by further refinement with the string method (referred to as the fast marching tree (FMT)-string combined approach), significantly reduces the number of iterations required for MEP convergence. This approach saves substantial time compared to using linear interpolation (LI) for the initial guess. Our method offers a viable solution for obtaining an effective initial guess of the MEP when an approximate or converged FEL is available. This work highlights the potential of applying FMT-based approaches to extract the MEP in chemical reactions.

Navigating the landscape of enzyme design: from molecular simulations to machine learning

Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.

Mechanisms of isomerization and hydration reactions of typical β-diketone at the air-droplet interface

Acetylacetone (AcAc) is a typical class of β-diketones with broad industrial applications due to the property of the keto-enol isomers, but its isomerization and chemical reactions at the air-droplet interface are still unclear. Hence, using combined molecular dynamics and quantum chemistry methods, the heterogeneous chemistry of AcAc at the air-droplet interface was investigated, including the attraction of AcAc isomers by the droplets, the distribution of isomers at the air-droplet interface, and the hydration reactions of isomers at the air-droplet interface. The results reveal that the preferential orientation of two AcAc isomers (keto- and enol-AcAc) to accumulate and accommodate at the acidic air-droplet interface. The isomerization of two AcAc isomers at the acidic air-droplet interface is more favorable than that at the neutral air-droplet interface because the "water bridge" structure is destroyed by H3O+, especially for the isomerization from keto-AcAc to enol-AcAc. At the acidic air-droplet interface, the carbonyl or hydroxyl O-atoms of two AcAc isomers display an energetical preference to hydration. Keto-diol is the dominant products to accumulate at the air-droplet interface, and excessive keto-diol can enter the droplet interior to engage in the oligomerization. The photooxidation reaction of AcAc will increase the acidity of the air-droplet interface, which indirectly facilitate the uptake and formation of more keto-diol. Our results provide an insight into the heterogeneous chemistry of β-diketones and their influence on the environment.

Stereospecific alkenylidene homologation of organoboronates by SNV reaction

Concerted nucleophilic substitution, known as SN2 reaction, is a fundamental organic transformation used in synthesis to introduce new functional groups and construct carbon-carbon and carbon-heteroatom bonds1. SN2 reactions typically involve backside attack of a nucleophile to the σ* orbital of a C(sp3)-X bond (X = halogen or other leaving group), resulting in complete inversion of a stereocentre2. By contrast, the corresponding stereoinvertive nucleophilic substitution on electronically unbiased sp2 vinyl electrophiles, namely concerted SNV(σ) reaction, is much rarer, and so far limited to carefully designed substrates mostly in ring-forming processes3,4. Here we show that concerted SNV reactions can be accelerated by a proposed strain-release mechanism in metallated complexes, leading to the development of a general and stereospecific alkenylidene homologation of diverse organoboronates. This method enables the iterative incorporation of multiple alkenylidene units, giving cross-conjugated polyenes that are challenging to prepare otherwise. Further application to the synthesis of bioactive compounds containing multi-substituted alkenes is also demonstrated. Computational studies suggest an unusual SN2-like concerted pathway promoted by diminishing steric strain in the square planar transition state, which explains the high efficiency and stereoinversive feature of this metallate SNV reaction.

Assessing the role of residue Phe108 of cytochrome P450 3A4 in allosteric effects of midazolam metabolism

Cytochrome P450 3A4 (CYP3A4) is involved in the metabolism of more drugs in clinical use than any other xenobiotic-metabolizing enzyme. CYP3A4-mediated drug metabolism is usually allosterically modulated by substrate concentration (homotropic allostery) and other drugs (heterotropic allostery), exhibiting unusual kinetic profiles and regiospecific metabolism. Recent studies suggest that residue Phe108 (F108) of CYP3A4 may have an important role in drug metabolism. In this work, residue mutations were coupled with well-tempered metadynamics simulations to assess the importance of F108 in the allosteric effects of midazolam metabolism. Comparing the simulation results of the wild-type and mutation systems, we identify that the π-π interaction and steric effect between the F108 side chain and midazolam is favorable for the stable binding of substrate in the active site. F108 also plays an important role in the transition of substrate binding mode, which mainly induces the transition of substrate binding mode by forming π-π interactions with multiple aromatic rings of the substrate. Moreover, the side chain of F108 is closely related to the radius and depth of the 2a and 2f channels, and F108 may further regulate drug metabolism by affecting the pathway, orientation, or time of substrate entry into the CYP3A4 active site or product egress from the active site. Altogether, we suggest that F108 affects drug metabolism and regulatory mechanisms by affecting substrate binding stability, binding mode transition, and channel characteristics of CYP3A4. Our findings could promote the understanding of complicated allosteric mechanisms in CYP3A4-mediated drug metabolism, and the knowledge could be used for drug development and disease treatment.

Stability of Cytoplasmic Membrane of Escherichia coli Bacteria in Aqueous and Ethanolic Environment

The mechanism of action of any antibacterial agent or disinfectant depends largely on their interaction with the bacterial membrane. Herein, we use the SPICA (surface property fitting coarse graining) force-field and develop a coarse-grained (CG) model for the structure of the cytoplasmic membrane of Escherichia coli (E. coli) and its interaction with water and ethanol. We elucidate the impact of different concentrations of ethanol on the cytoplasmic membrane bilayers and vesicles of E. coli using the CG molecular dynamics (CG MD) simulations. Our modeling approach first focuses on the parametrization of the required force-field for POPG lipid and its interaction with water, ethanol, and POPE lipid. Subsequently, the structural stability of the E. coli bacterial membrane in the presence of high and low concentrations of ethanol is delineated. Both flat bilayers as well as vesicles of E. coli membrane were considered for the CG MD. Our results reveal that, at low ethanol concentrations (<30 mol %), the size of the E. coli vesicles increases with discernible deformations in their shapes. Because of ethanol-induced interdigitation, thinning of the E. coli vesicular membrane is also observed. However, at higher ethanol concentrations (>30 mol %), the integrity of the vesicles is lost because of deteriorating invasion of ethanol molecules into the vesicle bilayer and significant weakening of lipid-lipid interactions. At higher ethanol concentrations (40 and 70 mol %), both the multivesicle and single-vesicle bacterial membranes exhibit a similar rupturing pattern wherein the extraction of lipids from the membrane and formation of aggregates of the component lipids are observed. These aggregates consist of polar head groups of 3-5 POPE/POPG lipids with intertwined nonpolar tails.

Revealing the Unique Role of Water in the Formation of Benzothiazoles: an Experimental and Computational Study

We present here a joint experimental and computational study on the formation of benzothiazoles. Our investigation reveals a green protocol for accessing benzothiazoles from acyl chlorides using either water alongside a reducing agent as the reaction medium or in combination with stoichiometric amounts of a weak acid, instead of the harsh conditions and catalysts previously reported. Specifically, we show that a protic solvent, particularly water, enables the formation of 2-substituted benzothiazoles from N-acyl 1,2-aminothiophenols already at room temperature, without the need for strong acids or metal catalysts. DFT Molecular Dynamics simulations coupled with advanced enhanced sampling techniques provide a clear understanding of the catalytic role of water. We demonstrate how bulk water - due to its extended network of hydrogen bonds and an efficient Grotthuss mechanism - provides a reaction path that strongly reduces the reaction barriers compared to aprotic environments, namely more than 80 kJ/mol for the first reaction step and 250 kJ/mol for the second. Finally, we discuss the influence of different aliphatic and aromatic substituents with varying electronic properties on chemical reactivity. Besides providing in-depth mechanistic insights, we believe that our findings pave the way for a greener route toward an important class of bioactive molecules.

Automated Exploration of Reaction Networks and Mechanisms Based on Metadynamics Nanoreactor Simulations

We developed an automated approach to construct a complex reaction network and explore the reaction mechanisms for numerous reactant molecules by integrating several theoretical approaches. Nanoreactor-type molecular dynamics was used to generate possible chemical reactions, in which the metadynamics was used to overcome the reaction barriers, and the semiempirical GFN2-xTB method was used to reduce the computational cost. Reaction events were identified from trajectories using the hidden Markov model based on the evolution of the molecular connectivity. This provided the starting points for further transition-state searches at the electronic structure levels of density functional theory to obtain the reaction mechanism. Finally, the entire reaction network containing multiple pathways was built. The feasibility and efficiency of the automated construction of the reaction network were investigated using the HCHO and NH3 biomolecular reaction and the reaction network for a multispecies system comprising dozens of HCN and H2O molecules. The results indicated that the proposed approach provides a valuable and effective tool for the automated exploration of the reaction networks.

Modern Alchemical Free Energy Methods for Drug Discovery Explained

This Perspective provides a contextual explanation of the current state-of-the-art alchemical free energy methods and their role in drug discovery as well as highlights select emerging technologies. The narrative attempts to answer basic questions about what goes on "under the hood" in free energy simulations and provide general guidelines for how to run simulations and analyze the results. It is the hope that this work will provide a valuable introduction to students and scientists in the field.

Agglomeration Drives the Reversed Fractionation of Aqueous Carbonate and Bicarbonate at the Air-Water Interface

In the course of our investigations of the adsorption of ions to the air-water interface, we previously reported the surprising result that doubly charged carbonate anions exhibit a stronger surface affinity than singly charged bicarbonate anions. In contrast to monovalent, weakly hydrated anions, which generally show enhanced concentrations in the interfacial region, multivalent (and strongly hydrated) anions are expected to show a much weaker surface propensity. In the present work, we use resonantly enhanced deep-UV second-harmonic generation spectroscopy to measure the Gibbs free energy of adsorption of both carbonate (CO32-) and bicarbonate (HCO3-) anions to the air-water interface. Contrasting the predictions of classical electrostatic theory and in support of our previous findings from X-ray photoelectron spectroscopy, we find that carbonate anions do indeed exhibit much stronger surface affinity than do the bicarbonate anions. Extensive computer simulations reveal that strong ion pairing of CO32- with the Na+ countercation in the interfacial region results in the formation of near-neutral agglomerate clusters, consistent with a theory of interfacial ion adsorption based on hydration free energy and capillary waves. Simulated X-ray photoelectron spectra predict a 1 eV shift in the carbonate spectra compared to that of bicarbonate, further confirming our experiments. These findings not only advance our fundamental understanding of ion adsorption chemistry but also impact important practical processes such as ocean acidification, sea-spray aerosol chemistry, and mammalian respiration physiology.

Thermodynamics and kinetics of DNA and RNA dinucleotide hybridization to gaps and overhangs

Hybridization of short nucleic acid segments (<4 nt) to single-strand templates occurs as a critical intermediate in processes such as nonenzymatic nucleic acid replication and toehold-mediated strand displacement. These templates often contain adjacent duplex segments that stabilize base pairing with single-strand gaps or overhangs, but the thermodynamics and kinetics of hybridization in such contexts are poorly understood because of the experimental challenges of probing weak binding and rapid structural dynamics. Here we develop an approach to directly measure the thermodynamics and kinetics of DNA and RNA dinucleotide dehybridization using steady-state and temperature-jump infrared spectroscopy. Our results suggest that dinucleotide binding is stabilized through coaxial stacking interactions with the adjacent duplex segments as well as from potential noncanonical base-pairing configurations and structural dynamics of gap and overhang templates revealed using molecular dynamics simulations. We measure timescales for dissociation ranging from 0.2-40 μs depending on the template and temperature. Dinucleotide hybridization and dehybridization involve a significant free energy barrier with characteristics resembling that of canonical oligonucleotides. Together, our work provides an initial step for predicting the stability and kinetics of hybridization between short nucleic acid segments and various templates.

Machine-learning based prediction of small molecule-surface interaction potentials

Predicting the adsorption affinity of a small molecule to a target surface is of importance to a range of fields, from catalysis to drug delivery and human safety, but a complex task to perform computationally when taking into account the effects of the surrounding medium. We present a flexible machine-learning approach to predict potentials of mean force (PMFs) and adsorption energies for chemical-surface pairs from the separate interaction potentials of each partner with a set of probe atoms. We use a pre-existing library of PMFs obtained via atomistic molecular dynamics simulations for a variety of inorganic materials and molecules to train the model. We find good agreement between original and predicted PMFs in both training and validation groups, confirming the predictive power of this approach, and demonstrate the flexibility of the model by producing PMFs for molecules and surfaces outside the training set.

Probing the general base for DNA polymerization in telomerase: a molecular dynamics investigation

Telomerase is an RNA-dependent DNA polymerase that plays a role in the maintenance of the 3' end of the eukaryotic chromosome, known as a telomere, by catalyzing the DNA polymerization reaction in cancer and embryonic stem cells. The detailed molecular details of the DNA polymerization by telomerase, especially the general base for deprotonating the terminal 3'-hydroxyl, which triggers the chemical reaction, remain elusive. We conducted a computational investigation using hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations to probe the detailed mechanism of the reaction. Our simulations started with the telomerase:RNA:DNA:dNTP ternary complex, and by using enhanced sampling QM/MM MD simulations, we probed the general base involved directly in the polymerization. We report the participation of an aspartate (Asp344) coordinated to Mg and an active site water molecule, jointly acting as a base during nucleic acid addition. The Asp344 residue remains transiently protonated during the course of the reaction, and later it deprotonates by transferring its proton to the water at the end of the reaction.

Mechanistic Modeling of Lys745 Sulfonylation in EGFR C797S Reveals Chemical Determinants for Inhibitor Activity and Discriminates Reversible from Irreversible Agents

Targeted covalent inhibitors hold promise for drug discovery, particularly for kinases. Targeting the catalytic lysine of epidermal growth factor receptor (EGFR) has attracted attention as a new strategy to overcome resistance due to the emergence of C797S mutation. Sulfonyl fluoride derivatives able to inhibit EGFR^{L858R/T790M/C797S} by sulfonylation of Lys745 have been reported. However, atomistic details of this process are still poorly understood. Here, we describe the mechanism of inhibition of an innovative class of compounds that covalently engage the catalytic lysine of EGFR, through a sulfur(VI) fluoride exchange (SuFEx) process, with the help of hybrid quantum mechanics/molecular mechanics (QM/MM) and path collective variables (PCVs) approaches. Our simulations identify the chemical determinants accounting for the irreversible activity of agents targeting Lys745 and provide hints for the further optimization of sulfonyl fluoride agents.

ReNeGate: A Reaction Network Graph-Theoretical Tool for Automated Mechanistic Studies in Computational Homogeneous Catalysis

Exploration of the chemical reaction space of chemical transformations in multicomponent mixtures is one of the main challenges in contemporary computational chemistry. To remove expert bias from mechanistic studies and to discover new chemistries, an automated graph-theoretical methodology is proposed, which puts forward a network formalism of homogeneous catalysis reactions and utilizes a network analysis tool for mechanistic studies. The method can be used for analyzing trajectories with single and multiple catalytic species and can provide unique conformers of catalysts including multinuclear catalyst clusters along with other catalytic mixture components. The presented three-step approach has the integrated ability to handle multicomponent catalytic systems of arbitrary complexity (mixtures of reactants, catalyst precursors, ligands, additives, and solvents). It is not limited to predefined chemical rules, does not require prealignment of reaction mixture components consistent with a reaction coordinate, and is not agnostic to the chemical nature of transformations. Conformer exploration, reactive event identification, and reaction network analysis are the main steps taken for identifying the pathways in catalytic systems given the starting precatalytic reaction mixture as the input. Such a methodology allows us to efficiently explore catalytic systems in realistic conditions for either previously observed or completely unknown reactive events in the context of a network representing different intermediates. Our workflow for the catalytic reaction space exploration exclusively focuses on the identification of thermodynamically feasible conversion channels, representative of the (secondary) catalyst deactivation or inhibition paths, which are usually most difficult to anticipate based solely on expert chemical knowledge. Thus, the expert bias is sought to be removed at all steps, and the chemical intuition is limited to the choice of the thermodynamic constraint imposed by the applicable experimental conditions in terms of threshold energy values for allowed transformations. The capabilities of the proposed methodology have been tested by exploring the reactivity of Mn complexes relevant for catalytic hydrogenation chemistry to verify previously postulated activation mechanisms and unravel unexpected reaction channels relevant to rare deactivation events.

Molecular Mechanisms of Phosphoester Bond Formation in Water Using Tight-Binding Ab Initio Molecular Dynamics

Phosphate groups are ubiquitous in biomolecules and are usually incorporated through phosphoester bonds between alcohol groups and orthophosphate. The formation of this bond is exceptionally difficult, with associated barriers of 30-45 kcal/mol in the absence of catalysts. In abiotic conditions, polymerizing nucleic acids without enzymes remains very challenging and is still a partly unsolved problem that severely questions the RNA World hypothesis for the origins of life. Offering a solution to this problem would involve a detailed knowledge of the reaction energetics and mechanisms, yet these remain not fully understood at a molecular level, especially because of the very slow reaction rates that represent a significant challenge for the experiments. The number of involved reaction coordinates and the possible role of the solvent in assisting the reaction are challenging for computational studies. Here, we use extensive ab initio molecular dynamics simulations using semiempirical tight-binding methods and enhanced sampling to address these issues. We first show that the choice of the tight-binding method is greatly limited by the instability of the water liquid phase for most DFTB generations and parameter sets that are widely available. We then focus on a model reaction involving methanol and orthophosphate, for which the two protonation states (mono- and dianionic) that are dominant around neutral pH are considered. We compare different proton coordinates that enable (or not) the participation of solvent water molecules. Our simulations suggest that in all cases, a dissociative associative mechanism, with an intermediate metaphosphate, is favored. The main difference between the two phosphate species is that reaction with the monoanion is assisted by the substrate, while that with the dianion involves solvent water molecules. Our results are in agreement with early experimental measurements, but the reaction barriers are underestimated in our framework. We believe that our approach provides an interesting perspective on how to sample the reaction phase space efficiently, but it calls for future studies using more accurate descriptions of chemical reactivity.

Reconstructing reactivity in dynamic host-guest systems at atomistic resolution: amide hydrolysis under confinement in the cavity of a coordination cage

Spatial confinement is widely employed by nature to attain unique efficiency in controlling chemical reactions. Notable examples are enzymes, which selectively bind reactants and exquisitely regulate their conversion into products. In an attempt to mimic natural catalytic systems, supramolecular metal-organic cages capable of encapsulating guests in their cavity and of controlling/accelerating chemical reactions under confinement are attracting increasing interest. However, the complex nature of these systems, where reactants/products continuously exchange in-and-out of the host, makes it often difficult to elucidate the factors controlling the reactivity in dynamic regimes. As a case study, here we focus on a coordination cage that can encapsulate amide guests and enhance their hydrolysis by favoring their mechanical twisting towards reactive molecular configurations under confinement. We designed an advanced multiscale simulation approach that allows us to reconstruct the reactivity in such host-guest systems in dynamic regimes. In this way, we can characterize amide encapsulation/expulsion in/out of the cage cavity (thermodynamics and kinetics), coupling such host-guest dynamic equilibrium with characteristic hydrolysis reaction constants. All computed kinetic/thermodynamic data are then combined, obtaining a statistical estimation of reaction acceleration in the host-guest system that is found in optimal agreement with the available experimental trends. This shows how, to understand the key factors controlling accelerations/variations in the reaction under confinement, it is necessary to take into account all dynamic processes that occur as intimately entangled in such host-guest systems. This also provides us with a flexible computational framework, useful to build structure-dynamics-property relationships for a variety of reactive host-guest systems.

Engineered P450 Atom-Transfer Radical Cyclases are Bifunctional Biocatalysts: Reaction Mechanism and Origin of Enantioselectivity

New-to-nature radical biocatalysis has recently emerged as a powerful strategy to tame fleeting open-shell intermediates for stereoselective transformations. In 2021, we introduced a novel metalloredox biocatalysis strategy that leverages the innate redox properties of the heme cofactor of P450 enzymes, furnishing new-to-nature atom-transfer radical cyclases (ATRCases) with excellent activity and stereoselectivity. Herein, we report a combined computational and experimental study to shed light on the mechanism and origins of enantioselectivity for this system. Molecular dynamics and quantum mechanics/molecular mechanics (QM/MM) calculations revealed an unexpected role of the key beneficial mutation I263Q. The glutamine residue serves as an essential hydrogen bond donor that engages with the carbonyl moiety of the substrate to promote bromine atom abstraction and enhance the enantioselectivity of radical cyclization. Therefore, the evolved ATRCase is a bifunctional biocatalyst, wherein the heme cofactor enables atom-transfer radical biocatalysis, while the hydrogen bond donor residue further enhances the activity and enantioselectivity. Unlike many enzymatic stereocontrol rationales based on a rigid substrate binding model, our computations demonstrate a high degree of rotational flexibility of the allyl moiety in an enzyme-substrate complex and succeeding intermediates. Therefore, the enantioselectivity is controlled by the radical cyclization transition states rather than the substrate orientation in ground-state complexes in the preceding steps. During radical cyclization, anchoring effects of the Q263 residue and steric interactions with the heme cofactor concurrently control the π-facial selectivity, allowing for highly enantioselective C-C bond formation. Our computational findings are corroborated by experiments with ATRCase mutants generated from site-directed mutagenesis.

Exploration of high dimensional free energy landscapes by a combination of temperature-accelerated sliced sampling and parallel biasing

Temperature-accelerated sliced sampling (TASS) is an enhanced sampling method for achieving accelerated and controlled exploration of high-dimensional free energy landscapes in molecular dynamics simulations. With the aid of umbrella bias potentials, the TASS method realizes a controlled exploration and divide-and-conquer strategy for computing high-dimensional free energy surfaces. In TASS, diffusion of the system in the collective variable (CV) space is enhanced with the help of metadynamics bias and elevated-temperature of the auxiliary degrees of freedom (DOF) that are coupled to the CVs. Usually, a low-dimensional metadynamics bias is applied in TASS. In order to further improve the performance of TASS, we propose here to use a highdimensional metadynamics bias, in the same form as in a parallel bias metadynamics scheme. Here, a modified reweighting scheme, in combination with artificial neural network is used for computing unbiased probability distribution of CVs and projections of high-dimensional free energy surfaces. We first validate the accuracy and efficiency of our method in computing the four-dimensional free energy landscape for alanine tripeptide in vacuo. Subsequently, we employ the approach to calculate the eight-dimensional free energy landscape of alanine pentapeptide in vacuo. Finally, the method is applied to a more realistic problem wherein we compute the broad four-dimensional free energy surface corresponding to the deacylation of a drug molecule which is covalently complexed with a β-lactamase enzyme. We demonstrate that using parallel bias in TASS improves the efficiency of exploration of high-dimensional free energy landscapes.

Adsorption Free Energy of Cellulose Nanocrystal on Water-Oil Interface

To investigate the amphiphilicity of cellulose, a series of molecular dynamics simulations were performed with a cellulose nanocrystal and a water-octane interfacial system. Assuming that the axis of cellulose is parallel to the water-octane interface, the freedoms of motion of the nanocrystal were restricted to two, the distance from the interface and the orientation around the axis. The mean force and the mean torque on the nanocrystal were evaluated with sufficiently long simulation at each crystal configuration, and their numerical integration gave a smooth free energy surface as the potential of mean force. The cellulose sample used here was found to be much more hydrophilic than oleophilic with the free energy difference ΔFw→o=318 kcal/mol. Three adsorption states with local minimum of adsorption free energy are distinguished in the free energy surface-the direct contact type which is similar to previously reported one, the hydrophilic-surface/water/octane type where a thin water layer is sandwiched between the surface and the octane phase, and the oleophilic/water/octane type where a thin water layer also exists. Water molecules in these water layers contribute to stabilize the adsorption states by taking a special orientational order and slow self-diffusion.

Deciphering Ethanol-Driven Swelling, Rupturing, Aggregation, and Fusion of Lipid Vesicles Using Coarse-Grained Molecular Dynamics Simulations

Traditionally, liquid ethanol is known to enhance the permeability of lipid membranes and causes vesicle aggregation and fusion. However, how the amphiphilic ethanol molecules perturb the lipid vesicles to facilitate their aggregation or fusion has not been addressed at any level of molecular simulations. Herein, not only have we developed a coarse-grained (CG) model for liquid ethanol, its aqueous mixture, and hydrated lipid membranes for molecular dynamics (MD) simulations, but also utilized it to delineate the aggregation and fusion of lipid vesicles using CG-MD simulations with multimillion particles. We have systematically parametrized the force-field for pure ethanol and its interactions with hydrated POPC and POPE model lipid membranes. In this process, we have successfully reproduced the bulk ethanol structure and concentration-dependent density of aqueous ethanol. To quantify the interaction of ethanol with lipid membranes, we have reproduced the transfer free energy of the ethanol molecule across the hydrated bilayers, and the concentration-dependent distribution of ethanol molecules across the lipid bilayers. After having acceptable force-field parameters for ethanol-membrane interactions, we have checked the effect of ethanol toward the vesicles comprising POPC lipids. We observe a rapid increase in the size of the POPC lipid vesicles with increasing amounts of ethanol up to 30 mol %. We unambiguously observe swelling and decrease in the thickness of the POPC vesicles with increasing amounts of ethanol up to 30 mol %, beyond which the vesicles begin to lose their integrity and rupture at higher mol % of ethanol. The fusion study of two vesicles demonstrates that fused vesicles can be obtained from 20 to 30 mol % of ethanol provided that they are brought closer than a critical distance at a particular mol %. The multivesicle simulations show that along with the increase in the sizes of vesicles the propensity of vesicle aggregation increases as the mol % of ethanol increases.

Complete inhibition of a polyol nucleation by a micromolar biopolymer additive

Preventing spontaneous crystallization of supersaturated solutions by additives is of critical interest to successful process design and implementation, with numerous applications in chemical, pharmaceutical, medical, pigment, and food industries, but challenges remain in laboratory and industry settings and fundamental understanding is lacking. When copresented with antifreeze proteins (AFPs), otherwise spontaneously crystallizing osmolytes are maintained at high supersaturations for months in over-wintering organisms. Thus, we here explore the inhibition phenomenon by AFPs, using persistent crystallization of a common sugar alcohol, D-mannitol, as a case study. We report experimentally that DAFP1, an insect AFP, completely inhibits D-mannitol nucleation. Computer simulations reveal a new mechanism for crystallization inhibition where the population of the crystal-forming conformers are selectively bound and randomized in solution by hydrogen bonding to the protein surface. These results highlight the advantages of using natural polymers to address crystallization inhibition challenges and suggest new strategies in controlling the nucleation processes.

Discovering surface reaction pathways using accelerated molecular dynamics and network analysis tools

We present an automated method that maps surface reaction pathways with no experimental data and with minimal human interventions. In this method, bias potentials promoting surface reactions are applied to enable statistical samplings of the surface reaction within the timescale of ab initio molecular dynamics (MD) simulations, and elementary reactions are extracted automatically using an extension of the method constructed for gas- or liquid-phase reactions. By converting the extracted elementary reaction data to directed graph data, MD trajectories can be efficiently mapped onto reaction pathways using a network analysis tool. To demonstrate the power of the method, it was applied to the steam reforming of methane on the Rh(111) surface and to propane reforming on the Pt(111) and Pt₃Sn(111) surfaces. We discover new energetically favorable pathways for both reactions and reproduce the experimentally-observed materials-dependence of the surface reaction activity and the selectivity for the propane reforming reactions.

We present an automated method that maps surface reaction pathways with no experimental data and with minimal human interventions.

Free Energy Surfaces and Barriers for Vacancy Diffusion on Al(100), Al(110), Al(111) Reconstructed Surfaces

Metadynamics is a popular enhanced sampling method based on the recurrent application of a history-dependent adaptive bias potential that is a function of a selected number of appropriately chosen collective variables. In this work, using metadynamics simulations, we performed a computational study for the diffusion of vacancies on three different Al surfaces [reconstructed Al(100), Al(110), and Al(111) surfaces]. We explored the free energy landscape of diffusion and estimated the barriers associated with this process on each surface. It is found that the surfaces are unique regarding vacancy diffusion. More specically, the reconstructed Al(110) surface presents four metastable states on the free energy surface having sizable and connected passage-ways with an energy barrier of height 0.55 eV. On the other hand, the reconstructed Al(100)/Al(111) surfaces exhibit two/three metastable states, respectively, with an energy barrier of height 0.33 eV. The findings in this study can help to understand surface vacancy diffusion in technologically relevant Al surfaces.

Water-Assisted Chemical Route Towards the Oxygen Evolution Reaction at the Hydrated (110) Ruthenium Oxide Surface: Heterogeneous Catalysis via DFT-MD and Metadynamics Simulations

Notwithstanding that RuO2 is a promising catalyst for the oxygen evolution reaction (OER), a plethora of fundamental details on its catalytic properties are still elusive, severely limiting its large-scale deployment. It is also established experimentally that corrosion and wettability of metal oxides can, in fact, enhance the catalytic activity for OER owing to the formation of a hydrated surface layer. However, the mechanistic interplay between surface wettability, interfacial water dynamics and OER across RuO2 , and what degree these processes are correlated are still debated. Herein, spin-polarized Density Functional Theory Molecular Dynamics (DFT-MD) simulations, coupled with advanced enhanced sampling methods in the well-tempered metadynamics framework, are applied to gain a global understanding of RuO2 aqueous interface (explicit water solvent) in catalyzing the OER, and hence possibly help in the design of novel catalysts in the context of photochemical water oxidation. The present study quantitatively assesses the free-energy barriers behind the OER at the (110)-RuO2 catalyst surface revealing plausible pathways composing the reaction network of the O2 evolution. In particular, OER is investigated at room temperature when such a surface is exposed to both gas-phase and liquid-phase water. Albeit a unique efficient pathway has been identified in the gas-phase OER, a surprisingly lowest-free-energy-requiring reaction route is possible when (110)-RuO2 is in contact with explicit liquid water. By estimating the free-energy surfaces associated to these processes, we reveal a noticeable water-assisted OER mechanism which involves a crucial proton-transfer-step assisted by the local water environment. These findings pave the way toward the systematic usage of DFT-MD coupled with metadynamics techniques for the fine assessment of the activity of catalysts, considering finite-temperature and explicit-solvent effects.

On-Surface Synthesis of Porphyrin-Complex Multi-Block Co-Oligomers by Defluorinative Coupling

On-surface chemical reaction has become a very powerful technique to synthesize nanostructures by linking small molecules in the bottom-up approach. Given the fact that most reactants are simultaneously activated at certain temperatures, a sequential reaction in a controlled way has remained challenging. Here, we present an on-surface synthesis of multi-block co-oligomers from trifluoromethyl (CF₃ ) substituted porphyrin metal complexes. The oligomerization on Au(111) is demonstrated with a combination of bond-resolved scanning probe microscopy and density functional theory (DFT) calculations. Even after the first oligomerization of single monomer unit, the termini of the oligomer keep the CF₃ group, which can be used as a reactant for further coupling in a sequential order. Consequently, copper, cobalt, and palladium complexes of bisanthracene-fused porphyrin oligomers were linked with each other in a designed order.

Mechanistic Insight on BioIL-Induced Structural Alterations in DMPC Lipid Bilayer

The emerging application risks of traditional ionic liquids (ILs) toward the ecosystem have changed the perception regarding their greenness. This resulted in the exploration of their more biocompatible alternatives known as biocompatible ILs (BioILs). Here, we have investigated the impact of two such biocompatible cholinium amino acid-based ILs on the structural behavior of model homogeneous DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) lipid bilayer using all-atom molecular dynamics simulation technique. Two classic cholinium-amino acid-based ILs, cholinium glycinate ([Ch][Gly]) and cholinium phenylalaninate ([Ch][Phe]), which differ only by the side chain lengths and hydrophobicity of the anions, have been utilized in the present work. Simultaneous analysis of the bilayer structural properties reveals that the existence of [Ch][Gly] BioIL above a particular concentration induces phase transition from fluid phase to gel phase in the DMPC lipid bilayer. Such a freezing of lipid bilayer upon the exposure to concentrated aqueous solution of [Ch][Gly] BioIL indicates the harmfulness of this BioIL toward the cell membranes majorly containing DMPC lipids, as the cell freezing can negatively affect its stability and functionality. Despite having a more hydrophobic amino acid side chain of [Phe]^- anion in [Ch][Phe], in the case of bilayer-[Ch][Phe] systems we observe the minimal impact of [Ch][Phe] BioIL on the DMPC bilayer properties up to 10 mol % concentration. In the presence of these BioIL, we observe the thickening of the bilayer and accumulation of the cations and anions of the BioILs at the interface of DMPC lipid heads and tails. The transfer free-energy profile of a [Phe]^- anion from aqueous phase to membrane center also indicates the anion partitioning at lipid head-tail interface and its inability to penetrate in the lipid membrane tail region. In contrast, the free-energy profile for a [Gly]^- anion offers a very high energy barrier to the insertion of [Gly]^- into the membrane interior, leading to accumulation of [Gly]^- anions at the lipid head-water region.

Closer Look at Inverse Electron Demand Diels–Alder and Nucleophilic Addition Reactions on s-Tetrazines Using Enhanced Sampling Methods

Inverse electron demand [4+2] Diels–Alder (iEDDA) reactions as well as unprecedented nucleophilic (azaphilic) additions of R-substituted silyl-enol ethers (where R is Phenyl, Methyl, and Hydrogen) to 1,2,4,5-tetrazine (s-tetrazine) catalyzed by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {BF}_{3}$$\end{document}BF3 have recently been discovered (Simon et al. in Org Lett 23(7):2426–2430, 2021), where static calculations were employed for calculation of activation energies. In order to have a more realistic dynamic description of these reactions in explicit solution at ambient conditions, in this work we use a semiempirical tight-binding method combined with enhanced sampling techniques to calculate free energy surfaces (FESs) of the iEDDA and azaphilic addition reactions. Relevant products of not only s-tetrazine but also its derivatives such as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {BF}_{3}$$\end{document}BF3-mediated s-tetrazine adducts are investigated. We reconstruct the FESs of the iEDDA and azaphilic addition reactions using metadynamics and blue moon ensemble, and compare the ability of different collective variables (CVs) including bond distances, Social PeRmutation INvarianT (SPRINT) coordinates, and path-CV to describe the reaction pathway. We find that when a bulky Phenyl is used as a substituent at the dienophile the azaphilic addition is preferred over the iEDDA reaction. In addition, we also investigate the effect of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {BF}_{3}$$\end{document}BF3 in the diene and steric hindrance in the dienophile on the competition between the iEDDA and azaphilic addition reactions, providing chemical insight for reaction design.

Dynamics and Site Isolation: Keys to High Propane Dehydrogenation Performance of Silica-Supported PtGa Nanoparticles

Nonoxidative dehydrogenation of light alkanes has seen a renewed interest in recent years. While PtGa systems appear among the most efficient catalyst for this reaction and are now implemented in production plants, the origin of the high catalytic performance in terms of activity, selectivity, and stability in PtGa-based catalysts is largely unknown. Here we use molecular modeling at the DFT level on three different models: (i) periodic surfaces, (ii) clusters using static calculations, and (iii) realistic size silica-supported nanoparticles (1 nm) using molecular dynamics and metadynamics. The combination of the models with experimental data (XAS, TEM) allowed the refinement of the structure of silica-supported PtGa nanoparticles synthesized via surface organometallic chemistry and provided a structure-activity relationship at the molecular level. Using this approach, the key interaction between Pt and Ga was evidenced and analyzed: the presence of Ga increases (i) the interaction between the oxide surface and the nanoparticles, which reduces sintering, (ii) the Pt site isolation, and (iii) the mobility of surface atoms which promotes the high activity, selectivity, and stability of this catalyst. Considering the complete system for modeling that includes the silica support as well as the dynamics of the PtGa nanoparticle is essential to understand the catalytic performances.

Side-Chain Polarity Modulates the Intrinsic Conformational Landscape of Model Dipeptides

The intrinsic conformational preferences of small peptides may provide additional insight into the thermodynamics and kinetics of protein folding. In this study, we explore the underlying energy landscapes of two model peptides, namely, Ac-Ala-NH₂ and Ac-Ser-NH₂, using geometry-optimization-based tools developed within the context of energy landscape theory. We analyze not only how side-chain polarity influences the structural preferences of the dipeptides, but also other emergent properties of the landscape, including heat capacity profiles, and kinetics of conformational rearrangements. The contrasting topographies of the free energy landscape agree with recent results from Fourier transform microwave spectroscopy experiments, where Ac-Ala-NH₂ was found to exist as a mixture of two conformers, while Ac-Ser-NH₂ remained structurally locked, despite exhibiting an apparently rich conformational landscape.

High Temperature Accelerated Stone-Wales Transformation and the Threshold Temperature of IPR-C60 Formation

The Stone-Wales bond rotation isomerization of nonicosahedral C₆₀ (C_2v-C₆₀) into isolated-pentagon rule following icosahedral C₆₀ (I_h-C₆₀ or IPR-C₆₀) is a limiting step in the synthesis of I_h-C₆₀. However, extensive previous studies indicate that the potential energy barrier of the Stone-Wales bond rotation is between 6 and 8 eV, extremely high to allow for bond rotation at the temperatures used to produce fullerenes conventionally. This is also despite data indicating a possible fullerene road mechanism that necessitates low-temperature annealing. However, these previous investigations often have limiting factors, such as using the harmonic approximation to determine free energies at high temperatures or considering only the reverse I_h-C₆₀ to C_2v-C₆₀ transition as a basis. Indeed, when the difference in energy between I_h-C₆₀ and C_2v-C₆₀ is accounted for, this barrier is generally reduced by ∼1.5 eV. Thus, utilizing the recently developed density functional tight binding metadynamics (DFTB-MTD) interface, the effects of temperature on the bond rotation in the conversion of C_2v-C₆₀ to I_h-C₆₀ have been investigated. We found that Stone-Wales bond rotations are complex processes with both in-plane and out-of-plane transition states, and which transition path dominates depends on temperature. Our results clearly show that at temperatures of 2000 K, the free energy for a C_2v-C₆₀ to I_h-C₆₀ transition is only ∼4.21 eV and further reduces to ∼3.77 eV at 3000 K. This translates to transition times of ∼971 μs at 2000 K and ∼34 ns at 3000 K, indicating that defect healing is a fast process at temperatures typical of arc jet or laser ablation experiments. Conversely, below ∼2000 K, bond rotation becomes prohibitively slow, putting a lower threshold limit on the temperature of fullerene formation and subsequent annealing.

Carbonation Reaction Mechanisms of Portlandite Predicted from Enhanced Ab Initio Molecular Dynamics Simulations

Geological carbon capture and sequestration (CCS) is a promising technology for curbing the global warming crisis by reduction of the overall carbon footprint. Degradation of cement wellbore casings due to carbonation reactions in the underground CO2 storage environment is one of the central issues in assessing the long-term success of the CCS operations. However, the complexity of hydrated cement coupled with extreme subsurface environmental conditions makes it difficult to understand the carbonation reaction mechanisms leading to the loss of well integrity. In this work, we use biased ab initio molecular dynamics (AIMD) simulations to explore the reactivity of supercritical CO2 with the basal and edge surfaces of a model hydrated cement phase—portlandite—in dry scCO2 and water-rich conditions. Our simulations show that in dry scCO2 conditions, the undercoordinated edge surfaces of portlandite experience a fast barrierless reaction with CO2, while the fully hydroxylated basal surfaces suppress the formation of carbonate ions, resulting in a higher reactivity barrier. We deduce that the rate-limiting step in scCO2 conditions is the formation of the surface carbonate barrier which controls the diffusion of CO2 through the layer. The presence of water hinders direct interaction of CO2 with portlandite as H2O molecules form well-structured surface layers. In the water-rich environment, CO2 undergoes a concerted reaction with H2O and surface hydroxyl groups to form bicarbonate complexes. We relate the variation of the free-energy barriers in the formation of the bicarbonate complexes to the structure of the water layer at the interface which is, in turn, dictated by the surface chemistry and the degree of nanoconfinement.

Classical MD and metadynamics simulations on back-pocket binders of CDK2 and VEGFR2: a guidepost to design novel small-molecule dual inhibitors

Cyclin-Dependent Kinase 2 (CDK2) and Vascular-Endothelial Growth Factor Receptor 2 (VEGFR2) are promising targets for the design of novel inhibitors in anticancer therapeutics. In a recent work, our group designed a set of potential dual inhibitors predicted to occupy an allosteric back pocket near the active site of both enzymes, but their dynamic and unbinding behavior was unclear. Here, we used molecular dynamics (MD) and metadynamics (meta-D) simulations to study two of these virtual candidates (herein called IQ2 and IQ3). Their binding mode was predicted to be similar to that observed in LQ5 and BAX, well-known back-pocket binders of CDK2 and VEGFR2, respectively, including H-bonding with critical residues such as Leu83/Cys113 and Asp145/Asp190 (but excepting H-bonding with Glu51/Glu111) in CDK2/VEGFR2, correspondingly. Likewise, while LQ5 and BAX unbound through the allosteric channel as expected for type-IIA inhibitors, IQ2 and IQ3 unbound via the ATP channel (except for CDK2-IQ2) as expected for type-I½A inhibitors. Interestingly, a C-C single/double bond difference between IQ2/IQ3, respectively, resulted associated with differences in the AS/T loop flexibility observed for CDK2. These insights will help developing scaffold modifications during an optimization stage, serving as a starting point to develop dual kinase inhibitors in challenging biological targets with a promising anticancer potential.Communicated by Ramaswamy H. Sarma.

First-principles molecular dynamics study on the surface chemistry and nanotribological properties of MgAl layered double hydroxides

Layered double hydroxides (LDHs) are promising materials for lubrication. However, the underlying mechanism that leads to the low friction of the material is not well-understood. In this study, density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations have been used to study the reduced friction mechanism of MgAl-LDH. Our results indicate that the introduction of trivalent cations has a significant impact on the friction reduction of the LDH. Besides, the lateral force shows a strong correlation with the coverage of the hydroxyl group on the surface. By using AIMD simulation, we show that the water/hydroxide molecules interact with the surface through strong hydrogen bonds that confine the movement and the orientation of the intercalated molecules on the surface. Furthermore, the friction is reduced when the water thickness is increased. The reaction pathways of water with the LDH surface has been investigated using well-tempered metadynamics simulation. We found that the LDH can promote proton transfer, leading to the formation of hydroxide intermediates (OH), which then chemically adsorb on the surface. The chemical adsorption of the hydroxide intermediates can cleave the O-H bonds on the LDH surface.

Ab Initio Molecular Dynamics Simulations of the SN1/SN2 Mechanistic Continuum in Glycosylation Reactions

We report a computational approach to evaluate the reaction mechanisms of glycosylation using ab initio molecular dynamics (AIMD) simulations in explicit solvent. The reaction pathways are simulated via free energy calculations based on metadynamics and trajectory simulations using Born-Oppenheimer molecular dynamics. We applied this approach to investigate the mechanisms of the glycosylation of glucosyl α-trichloroacetimidate with three acceptors (EtOH, i-PrOH, and t-BuOH) in three solvents (ACN, DCM, and MTBE). The reactants and the solvents are treated explicitly using density functional theory. We show that the profile of the free energy surface, the synchronicity of the transition state structure, and the time gap between leaving group dissociation and nucleophile association can be used as three complementary indicators to describe the glycosylation mechanism within the SN1/SN2 continuum for a given reaction. This approach provides a reliable means to rationalize and predict reaction mechanisms and to estimate lifetimes of oxocarbenium intermediates and their dependence on the glycosyl donor, acceptor, and solvent environment.

Reaction prediction via atomistic simulation: from quantum mechanics to machine learning

It is an ultimate goal in chemistry to predict reaction without recourse to experiment. Reaction prediction is not just the reaction rate determination of known reactions but, more broadly, the reaction exploration to identify new reaction routes. This review briefly overviews the theory on chemical reaction and the current methods for computing/estimating reaction rate and exploring reaction space. We particularly focus on the atomistic simulation methods for reaction exploration, which are benefited significantly by recently emerged machine learning potentials. We elaborate the stochastic surface walking global pathway sampling based on the global neural network (SSW-NN) potential, developed in our group since 2013, which can explore complex reactions systems unbiasedly and automatedly. Two examples, molecular reaction and heterogeneous catalytic reactions, are presented to illustrate the current status for reaction prediction using SSW-NN.

Molecular dynamics simulation of the adsorption of per- and polyfluoroalkyl substances (PFASs) on smectite clay

Molecular dynamics (MD) simulations are used to predict the partitioning of per- and polyfluoroalkyl substances (PFASs) to smectite clay, a high surface area adsorbent ubiquitous in temperate soils. Simulated systems model a stack of flexible smectite lamellae in contact with a bulk aqueous reservoir containing PFAS molecules. Perfluorobutanesulfonic acid (PFBS), perfluorohexanesulfonic acid (PFHxS), and perfluorooctanesulfonic acid (PFOS) are simulated at various aqueous chemistry conditions to examine the effect of PFAS size, salinity, and coordinating cation type (K⁺, Na⁺, and Ca²⁺) on adsorption. The metadynamics technique is employed to facilitate the exploration of the simulation cell and to reconstruct the underlying free energy landscape. Adsorption is favorable on the hydrophobic domains of the external basal surfaces with the fluorinated chain adopting a flat orientation on the surface. Analysis of the adsorption energetics reveals large favorable entropic contributions to adsorption. The enthalpy of adsorption is unfavorable, though much less so in the presence of Ca²⁺ due to stabilizing 'lateral cation bridging' interactions between divalent cations and PFAS sulfonate head groups. Overall, this research advances the mechanistic understanding of PFAS-smectite interactions and provides new insights that could help inform fate and transport models and the development of adsorbents and remediation techniques.

Accessing slow diffusion in solids by employing metadynamics simulation

Molecular dynamics (MD) is a powerful tool to investigate microscopic transport of atoms and molecules in condensed matter. However, there lies a large class of systems wherein atomic diffusion is too slow a process relative to the feasible time scales of typical atomistic simulations. Here, we demonstrate that with judicial implementation of a metadynamics (MTD) technique, the microscopic mechanism of atomic transport in solids can be accessed within a reasonable computational time. The calculations are carried out on the two end members of the true NASICON solid solutions, namely NaZr2(PO4)3 and Na4Zr2(SiO4)3, wherein Na+ diffusion is too slow to be accessed through standard MD simulations. The study also provides fresh insights on correlated ion hops and their implications on the effective diffusion barrier. The results are compared with climbing image nudged elastic band (CI-NEB) calculation, and available experimental results.