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The GT99 domain of the membrane‐anchored WbbB glycosyltransferase (WbbBGT99) catalyzes the transfer of 3‐deoxy‐D‐manno‐oct‐2‐acid (β‐Kdo) to an O‐antigen saccharide acceptor with retention of stereochemistry. It has been proposed that the enzyme follows an unprecedented double‐displacement mechanism involving the formation of covalent adduct between the Kdo sugar and an active site residue (Asp232) that is properly oriented for nucleophilic attack. Here we use QM/MM metadynamics simulations on recently reported crystal structures to provide theoretical evidence for the formation of such adduct and unveil the atomic details of the chemical reaction. Our results support the interpretation made on the basis of X‐ray and mass spectrometry analyses. Moreover, we show that the formation of the β‐Kdo‐Asp232 adduct is assisted by the sugar Kdo‐carboxylate group, which mediates the transfer of a proton from Asp232 towards the phosphate leaving group, alleviating electrostatic repulsion between the two negatively charged carboxylate groups. The computed mechanism also explains why His265, previously proposed to act as a general acid, does not impair catalysis. This mechanism can be extended to other related enzymes, expanding the repertoire of GT mechanisms in Nature. [ABSTRACT FROM AUTHOR]

This study employs ab initio molecular dynamics simulations to investigate the impact of solvent and noncovalent interactions on the structure‐reactivity relationship of both strain‐free and strained macrocyclic disulfides. Our findings reveal that interactions with water as a solvent significantly influence the minimum energy geometry structures of both conformers of the studied macrocycle. In particular, our simulations identify short contacts, specifically S⋅⋅⋅π‐aromatic interactions, which suppress reactivity for the strained isomer by obstructing the reaction cone at the minimum free energy. Surprisingly, the free energy barriers for the disulfide reaction with a simple nucleophile (OH− anion) remain very similar, despite one conformer having a markedly more strained disulfide bond than the other. Enhanced molecular dynamics simulations in an explicit solution elucidate this apparent contradiction by revealing different solvent exposures of the two sulfur atoms in the macrocycles. [ABSTRACT FROM AUTHOR]

This article provides an overview of various methods for calculating free energy in the interactions between biomolecules and nanomaterials. The authors discuss the advantages and limitations of these methods and their applicability to different systems. The article aims to guide future research in this field and emphasizes the need for further improvements in force fields, software, and the use of machine learning. The document also includes a list of references to scientific articles related to drug discovery, computational methods, and the calculation of free energy in molecular systems. These articles provide valuable insights and techniques for researchers in these fields. Additionally, there are references to two specific articles that discuss the use of machine learning in drug discovery and the computational characterization of membrane proteins as potential targets for anticancer treatments. [Extracted from the article]

The low‐temperature liquid metals Ga‐In and Ga‐Sn have previously showcased >95 % selectivity towards the electrochemical reduction of CO2 to formate, occuring only when the alloys are melted, not solid. Here, density functional theory molecular dynamics and metadynamics simulations reveal that CO2 does not directly adsorb to the Ga‐alloy surface, but instead is reduced indirectly by reaction with an adsorbed hydrogen. The reaction barrier is vastly more favourable when this process occurs at In or Sn sites (average: 0.26 eV), than when it occurs on Ga (average: 0.47 eV). However, there is no difference in barrier between solid and liquid surfaces. Instead, we find that Hads is mobile only on the liquid surface, travelling due to the motion of the liquid beneath. This process drives Hads to In/Sn sites, allowing low‐barrier CO2 reduction to occur only on the liquid. Therefore, the dynamic motion of liquid metal catalysts can underpin their unique reactivity. The result has far reaching implications for any protonation reaction conducted with a liquid metal catalyst. [ABSTRACT FROM AUTHOR]

The self-assembly of Aβ peptides into toxic oligomers and fibrils is the primary cause of Alzheimer's disease. Moreover, the conformational transition from helix to sheet is considered a crucial step in the aggregation of Aβ peptides. However, the structural details of this process still remain unclear due to the heterogeneity and transient nature of the Aβ peptides. In this study, we developed an enhanced sampling strategy that combines artificial neural networks (ANN) with metadynamics to explore the conformational space of the Aβ42 peptides. The strategy consists of two parts: applying ANN to optimize CVs and conducting metadynamics based on the resulting CVs to sample conformations. The results showed that this strategy achieved better sampling performance in terms of the distribution of sampled conformations. The sampling efficiency is increased by 10-fold compared to our previous Hamiltonian Exchange Molecular Dynamics (MD) and by 1000-fold compared to ordinary MD. Based on the sampled conformations, we constructed a Markov state model to understand the detailed transition process. The intermediate states in this process are identified, and the connecting paths are analyzed. The conformational transitions in D23-K28 and M35-V40 are proven to be crucial for aggregation. These results are helpful in clarifying the mechanism and process of Aβ42 peptide aggregation. D23-K28 and M35-V40 can be identified as potential targets for screening and designing inhibitors of Aβ peptide aggregation.

Antimicrobial peptides (AMPs) are increasingly recognized as potent therapeutic agents, with their selective affinity for pathological membranes, low toxicity profile, and minimal resistance development making them particularly attractive in the pharmaceutical landscape. This study offers a comprehensive analysis of the interaction between specific AMPs, including magainin-2, pleurocidin, CM15, LL37, and clavanin, with lipid bilayer models of very different compositions that have been ordinarily used as biological membrane models of healthy mammal, cancerous, and bacterial cells. Employing unbiased molecular dynamics simulations and metadynamics techniques, we have deciphered the intricate mechanisms by which these peptides recognize pathogenic and pathologic lipid patterns and integrate into lipid assemblies. Our findings reveal that the transverse component of the peptide's hydrophobic dipole moment is critical for membrane interaction, decisively influencing the molecule's orientation and expected therapeutic efficacy. Our approach also provides insight on the kinetic and dynamic dependence on the peptide orientation in the axial and azimuthal angles when coming close to the membrane. The aim is to establish a robust framework for the rational design of peptide-based, membrane-targeted therapies, as well as effective quantitative descriptors that can facilitate the automated design of novel AMPs for these therapies using machine learning methods.

Cyclodextrins (CDs) are cyclic carbohydrate polymers that hold significant promise for drug delivery and industrial applications. Their effectiveness depends on their ability to encapsulate target molecules with strong affinity and specificity, but quantifying affinities in these systems accurately is challenging for a variety of reasons. Computational methods represent an exceptional complement to in vitro assays because they can be employed for existing and hypothetical molecules, providing high resolution structures in addition to a mechanistic, dynamic, kinetic, and thermodynamic characterization. Here, we employ potential of mean force (PMF) calculations obtained from guided metadynamics simulations to characterize the 1:1 inclusion complexes between four different modified βCDs, with different type, number, and location of substitutions, and two sterol molecules (cholesterol and 7-ketocholesterol). Our methods, validated for reproducibility through four independent repeated simulations per system and different post processing techniques, offer new insights into the formation and stability of CD-sterol inclusion complexes. A systematic distinct orientation preference where the sterol tail projects from the CD's larger face and significant impacts of CD substitutions on binding are observed. Notably, sampling only the CD cavity's wide face during simulations yielded comparable binding energies to full-cavity sampling, but in less time and with reduced statistical uncertainty, suggesting a more efficient approach. Bridging computational methods with complex molecular interactions, our research enables predictive CD designs for diverse applications. Moreover, the high reproducibility, sensitivity, and cost-effectiveness of the studied methods pave the way for extensive studies of massive CD-ligand combinations, enabling AI algorithm training and automated molecular design.

Self-assembly of colloidal particles into 3D lattices, with potential applications as single crystals with promising optical properties, has received considerable attention. The superior bandgap properties of open colloidal lattices over their more easily self-assembling close-packed counterparts make them more demanding for this purpose. However, due to the mechanical instability of low-coordination open lattices, their self-assembly has proven to be challenging. Here, we employ a model of triblock Janus nanoparticles, which includes their surface chemistry (hydrophobic patches at the poles and surface charges in the equator) to simulate their self-assembly to three-dimensional nanocrystals. The solvent is explicitly included in the simulation, and hydrodynamic interactions are taken into account by dissipative particle dynamics. Biased sampling simulations are conducted to drive the simulations between different phases. The phase diagrams represent a competition between the liquid phase, open (pyrochlore, perovskite, and diamond), and close-packed [body-centered cubic (bcc) and face-centered cubic (fcc)] nanocrystals, whose stabilities depend on the patch width, temperature, and density. Patch widths allowing for three contacts per patch stabilize the pyrochlore nanocrystal at low densities and the fcc phase at high densities, and those allowing four contacts per patch stabilize the perovskite nanocrystal at low densities, the bcc lattice at higher densities, and upon further compression, the fcc lattice. The diamond nanocrystal is stabilized by wide enough patches that provide strong enough bonding between nanoparticles. Increasing the density converts the diamond nanocrystal to bcc and, subsequently, to a higher-density fcc lattice. The calculated free energies for conversion of liquid to crystalline phases reveal that the barrier height for nucleation of open lattices (within their stability domains) is lower than that for denser lattices. [ABSTRACT FROM AUTHOR]

The oligomeric ruthenium‐based water oxidation catalyst, Ru(bda), is known to be experimentally anchored on graphitic surfaces through CH‐π stacking interactions between the auxiliary bda ([2,2′‐bipyridine]‐6,6′‐dicarboxylate) ligand bonded to ruthenium and the hexagonal rings of the surface. This anchoring provides control over their molecular coverage and enables efficient catalysis of water oxidation to dioxygen. The oligomeric nature of the molecule offers multiple anchoring sites at the surface, greatly enhancing the overall stability of the hybrid catalyst‐graphitic surface anode through dynamic bonding. However, the impact of this dynamic anchoring on the overall catalytic mechanism is still a topic of debate. In this study, a crucial proton‐coupled electron transfer event in the catalytic cycle is investigated using DFT‐based molecular dynamics simulations plus metadynamics. The CH‐π stacking anchoring plays a critical role not only in stabilizing this hybrid system but also in facilitating the proton‐coupled electron transfer event with possible vibronic couplings between the anchoring bonds motion and charge fluctuations at the catalyst – graphitic surface interface. Furthermore, this computational investigation displays the presence of a quartet spin state intermediate that can lead to the experimentally observed and thermodynamically more stable doublet spin state. [ABSTRACT FROM AUTHOR]

[Display omitted] Understanding the mechanisms of proton transfer on quartz surfaces in water is critical for a range of processes in geochemical, environmental, and materials sciences. The wide range of surface acidities (>9 p K a units) found on the ubiquitous mineral quartz is caused by the structural variations of surface silanol groups. Molecular scale simulations provide essential tools for elucidating the origin of site-specific surface acidities. We used density-functional tight-binding-based molecular dynamics combined with rare-event metadynamics simulations to probe the mechanisms of deprotonation reactions from ten representative surface silanol groups found on both pristine and defect-rich quartz (1 0 1) surfaces with Si vacancies. The results show that deprotonation is a highly dynamic process where both the surface hydroxyls and bridging oxygen atoms serve as the proton acceptors, in addition to water. Deprotonation of embedded silanols through intrasurface proton transfer exhibited lower p K a values with less H-bond participation and higher energy barriers, suggesting a new mechanism to explain the bimodal acidity observed on quartz surface. Defect sites, recently shown to comprise a significant portion of the quartz (1 0 1) surface, diversify the coordination and local H-bonding environments of the surface silanols, changing both the deprotonation pathways and energetics, leading to a wider range of p K a values (2.4 to 11.5) than that observed on pristine quartz surface (10.4 and 12.1). [ABSTRACT FROM AUTHOR]

Poly(ADP-ribose) polymerase 1 (PARP1) plays a major role in the DNA damage repair and transcriptional regulation, and is targeted by a number of clinical inhibitors. Despite this, catalytic mechanism of PARP1 remains largely underexplored because of the complex substrate/product structure. Using molecular modeling and metadynamics simulations we have described in detail elongation of poly(ADP-ribose) chain in the PARP1 active site. It was shown that elongation reaction proceeds via the SN1-like mechanism involving formation of the intermediate furanosyl oxocarbenium ion. Intriguingly, nucleophilic 2′A-OH group of the acceptor substrate can be activated by the general base Glu988 not directly but through the proton relay system including the adjacent 3′A-OH group. [ABSTRACT FROM AUTHOR]

Computational target fishing plays an important role in target identification, particularly in drug discovery campaigns utilizing phenotypic screening. Numerous approaches exist to predict potential targets for a given ligand, but true targets may be inconsistently ranked. More advanced simulation methods may provide benefit in such cases by reranking these initial predictions. We evaluated the ability of binding pose metadynamics to improve the predicted rankings for three diverse ligands and their six true targets. Initial predictions using pharmacophore mapping showed no true targets ranked in the top 50 and two targets each ranked within the 50–100, 100–150, and 250–300 ranges respectively. Following binding pose metadynamics, ranking of true targets improved for four out of the six targets and included the highest ranked predictions overall, while rankings deteriorated for two targets. The revised rankings predicted two true targets ranked within the top 50, and one target each within the 50–100, 100–150, 150–200, and 200–250 ranges respectively. The findings of this study demonstrate that binding pose metadynamics may be of benefit in refining initial predictions from structure‐based target fishing algorithms, thereby improving the efficiency of the target identification process in drug discovery efforts. [ABSTRACT FROM AUTHOR]

Integrin αIIbβ3 mediates platelet aggregation by binding the Arginyl-Glycyl-Aspartic acid (RGD) sequence of fibrinogen. RGD binding occurs at a site topographically proximal to the αIIb and β3 subunits, promoting the conformational activation of the receptor from bent to extended states. While several experimental approaches have characterized RGD binding to αIIbβ3 integrin, applying computational methods has been significantly more challenging due to limited sampling and the need for a priori information regarding the interactions between the RGD peptide and integrin. In this study, we employed all-atom simulations using funnel metadynamics (FM) to evaluate the interactions of an RGD peptide with the αIIb and β3 subunits of integrin. FM incorporates an external history-dependent potential on selected degrees of freedom while applying a funnel-shaped restraint potential to limit RGD exploration of the unbound state. Furthermore, it does not require a priori information about the interactions, enhancing the sampling at a low computational cost. Our FM simulations reveal significant molecular changes in the β3 subunit of integrin upon RGD binding and provide a free-energy landscape with a low-energy binding mode surrounded by higher-energy prebinding states. The strong agreement between previous experimental and computational data and our results highlights the reliability of FM as a method for studying dynamic interactions of complex systems such as integrin. [ABSTRACT FROM AUTHOR]

For a detailed understanding of chemical processes in nature and industry, we need accurate models of chemical reactions in complex environments. While Eyring transition state theory is commonly used for modeling chemical reactions, it is most accurate for small molecules in the gas phase. A wide range of alternative rate theories exist that can better capture reactions involving complex molecules and environmental effects. However, they require that the chemical reaction is sampled by molecular dynamics simulations. This is a formidable challenge since the accessible simulation timescales are many orders of magnitude smaller than typical timescales of chemical reactions. To overcome these limitations, rare event methods involving enhanced molecular dynamics sampling are employed. In this work, thermal isomerization of retinal is studied using tight‐binding density functional theory. Results from transition state theory are compared to those obtained from enhanced sampling. Rates obtained from dynamical reweighting using infrequent metadynamics simulations were in close agreement with those from transition state theory. Meanwhile, rates obtained from application of Kramers' rate equation to a sampled free energy profile along a torsional dihedral reaction coordinate were found to be up to three orders of magnitude higher. This discrepancy raises concerns about applying rate methods to one‐dimensional reaction coordinates in chemical reactions. [ABSTRACT FROM AUTHOR]

Dynein, a motor protein, harnesses chemical energy from ATP hydrolysis to generate mechanical output as it travels along microtubular tracks. Essential to this process is the microtubule-binding domain (MTBD), which facilitates the interaction with and detachment from microtubules. Previous studies have proposed that the mechanism governing this interaction is primarily driven by the coiled-coil stalk attached to the MTBD. However, conflicting arguments suggest the presence of two-way communications, where the binding and unbinding mechanisms may also influence the nucleotide state of dynein. In this study, we employed all-atom explicit solvent simulations, enhanced sampling techniques, and coarse-grained methodologies to systematically investigate the effects of stalk and MT on the structural stabilities of different conformations of MTBD and their sequence of events during the transition from one to another. We found that the globular MTBD domain without stalk and MT predominantly resides in its weak binding configuration. Upon introduction of a limited length of stalk and interaction with MT, a balance between the strong and weak binding configurations is restored. Further introduction of the full-length stalk and interaction with MT strengthen the kinetic stability of these two configurations. We have also explored the sequence of events of the relevant transition between these two states using coarse-grained simulation protocols both in the presence and absence of interaction with MT. In the absence of MT interactions, we found a mixed conformational state of the system that corresponds to the already published crystal structure of Dynein. In the presence of MT, the conformational change of the stalk precedes the conformational change of the MTBD globular domain. Our findings support the view that the nucleotide state of the AAA+ ring determines the state of the MTBD domain through stalk, shedding light on the intricate mechanisms governing dynein's interaction with microtubules.

In the current study, we designed, synthesized, and characterized a series of substituted pyrazolo[4,3-c]pyrazoles. These novel compounds were evaluated in vitro for their inhibitory activity over a panel of protein kinases to determine their potential therapeutic applications against Alzheimer's disease. To gain deeper insight into the binding interactions between the most potent analogues and their respective kinase targets, advanced molecular simulations were performed. In parallel, the ability of pyrazolo[4,3-c]pyrazoles to inhibit Aβ40 aggregation was assessed using biophysical techniques such as circular dichroism and Thioflavin T assays. Our results highlight the specific heterocycle as a highly promising and synthetically versatile scaffold for developing inhibitors of both AD-relevant kinases and amyloid-β aggregation. Although more effort is needed to assess the possibility of developing multi-target inhibitors, pyrazolo[4,3-c]pyrazole analogues demonstrated significant activities against their individual targets, indicating substantial capacity of the heterocyclic scaffold for further optimization toward both directions. Overall, our findings emphasize the potential of properly substituted pyrazolo[4,3-c]pyrazoles as multifunctional agents targeting key processes in Alzheimer's disease pathology.

Metadynamics calculations of large chemical systems with ab initio methods are computationally prohibitive due to the extensive sampling required to simulate the large degrees of freedom in these systems. To address this computational bottleneck, we utilized a GPU-enhanced density functional tight binding (DFTB) approach on a massively parallelized cloud computing platform to efficiently calculate the thermodynamics and metadynamics of biochemical systems. To first validate our approach, we calculated the free-energy surfaces of alanine dipeptide and showed that our GPU-enhanced DFTB calculations qualitatively agree with computationally-intensive hybrid DFT benchmarks, whereas classical force fields give significant errors. Most importantly, we show that our GPU-accelerated DFTB calculations are significantly faster than previous approaches by up to two orders of magnitude. To further extend our GPU-enhanced DFTB approach, we also carried out a 10 ns metadynamics simulation of remdesivir, which is prohibitively out of reach for routine DFT-based metadynamics calculations. We find that the free-energy surfaces of remdesivir obtained from DFTB and classical force fields differ significantly, where the latter overestimates the internal energy contribution of high free-energy states. Taken together, our benchmark tests, analyses, and extensions to large biochemical systems highlight the use of GPU-enhanced DFTB simulations for efficiently predicting the free-energy surfaces/thermodynamics of large biochemical systems.

The amino acid substitutions in Klebsiella pneumoniae carbapenemase 2 (KPC‐2) that have arisen in the clinic are observed to lead to the development of resistance to ceftazidime‐avibactam, a preferred treatment for KPC bearing Gram‐negative bacteria. Specific substitutions in the omega loop (R164‐D179) result in changes in the structure and function of the enzyme, leading to alterations in substrate specificity, decreased stability, and more recently observed, increased resistance to ceftazidime/avibactam. Using accelerated rare‐event sampling well‐tempered metadynamics simulations, we explored in detail the structural role of R164 and D179 variants that are described to confer ceftazidime/avibactam resistance. The buried conformation of D179 substitutions produce a pronounced structural disorder in the omega loop ‐ more than R164 mutants, where the crystallographic omega loop structure remains mostly intact. Our findings also reveal that the conformation of N170 plays an underappreciated role impacting drug binding and restricting deacylation. The results further support the hypothesis that KPC‐2 D179 variants employ substrate‐assisted catalysis for ceftazidime hydrolysis, involving the ring amine of the aminothiazole group to promote deacylation and catalytic turnover. Moreover, the shift in the WT conformation of N170 contributes to reduced deacylation and an altered spectrum of enzymatic activity. [ABSTRACT FROM AUTHOR]

Sampling rare events in metastable dynamical systems is often a computationally expensive task and one needs to resort to enhanced sampling methods such as importance sampling. Since we can formulate the problem of finding optimal importance sampling controls as a stochastic optimization problem, this then brings additional numerical challenges and the convergence of corresponding algorithms might suffer from metastabilty. In this article, we address this issue by combining systematic control approaches with the heuristic adaptive metadynamics method. Crucially, we approximate the importance sampling control by a neural network, which makes the algorithm in principle feasible for high-dimensional applications. We can numerically demonstrate in relevant metastable problems that our algorithm is more effective than previous attempts and that only the combination of the two approaches leads to a satisfying convergence and therefore to an efficient sampling in certain metastable settings. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) simulations can provide detailed insights into complex molecular systems, such as DNA, at high resolution in space and time. Using current computer architectures, time scales of tens of microseconds are feasible with contemporary all-atom force fields. However, these timescales are insufficient to accurately characterize large conformational transitions in DNA and compare calculations to experimental data. This review discusses the advantages and draw-backs of two simulation approaches to overcome the timescale challenge. The first approach is based on adding biasing potentials to the system to drive transitions. Umbrella sampling, steered MD, and metadynamics are examples of these methods. A key challenge of such methods is the necessity of selecting one or a few efficient coordinates, commonly referred to as collective variables (CVs), along which to apply the biasing potential. The path-metadynamics methodology addresses this issue by finding the optimal route(s) between states in a multi-dimensional CV space. The second strategy is path sampling, which focuses MD simulations on the transitions. The assumption is that even though transitions between states are rare, they are generally fast. Stopping the simulations as soon as they reach a stable state can significantly increase simulation efficiency. We introduce these methods on the two-dimensional Müller--Brown potential. DNA applications are featured for two different processes: the Watson--Crick--Franklin to Hoogsteen transition in adenine--thymine base pairs and the binding of a DNA-binding protein domain to DNA. This article is categorized under: Molecular and Statistical Mechanics Molecular Dynamics and Monte-Carlo Methods Molecular and Statistical Mechanics Free Energy Methods Software Simulation Methods [ABSTRACT FROM AUTHOR]

Abstract Cosolvent molecular dynamics (MD) simulations are molecular dynamics simulations used to identify preferable locations of small organic fragments on a protein target. Most cosolvent molecular dynamics workflows make use of only water-soluble fragments, as hydrophobic fragments would cause lipophilic aggregation. To date the two approaches that allow usage of hydrophobic cosolvent molecules are to use a low (0.2 M) concentration of hydrophobic probes, with the disadvantage of a lower sampling speed, or to use force field modifications, with the disadvantage of a difficult and inflexible setup procedure. Here we present a third alternative, that does not suffer from low sampling speed nor from cumbersome preparation procedures. We have built an easy-to-use open source command line tool PART (Plumed Automatic Restraining Tool) to generate a PLUMED file handling all intermolecular restraints to prevent lipophilic aggregation. We have compared restrained and unrestrained cosolvent MD simulations, showing that restraints are necessary to prevent lipophilic aggregation at hydrophobic probe concentrations of 0.5 M. Furthermore, we benchmarked PART generated restraints on a test set of four proteins (Factor-Xa, HIV protease, P38 MAP kinase and RNase A), showing that cosolvent MD with PART generated restraints qualitatively reproduces binding features of cocrystallised ligands.

Cosolvent molecular dynamics (MD) simulations are molecular dynamics simulations used to identify preferable locations of small organic fragments on a protein target. Most cosolvent molecular dynamics workflows make use of only water-soluble fragments, as hydrophobic fragments would cause lipophilic aggregation. To date the two approaches that allow usage of hydrophobic cosolvent molecules are to use a low (0.2 M) concentration of hydrophobic probes, with the disadvantage of a lower sampling speed, or to use force field modifications, with the disadvantage of a difficult and inflexible setup procedure. Here we present a third alternative, that does not suffer from low sampling speed nor from cumbersome preparation procedures. We have built an easy-to-use open source command line tool PART (Plumed Automatic Restraining Tool) to generate a PLUMED file handling all intermolecular restraints to prevent lipophilic aggregation. We have compared restrained and unrestrained cosolvent MD simulations, showing that restraints are necessary to prevent lipophilic aggregation at hydrophobic probe concentrations of 0.5 M. Furthermore, we benchmarked PART generated restraints on a test set of four proteins (Factor-Xa, HIV protease, P38 MAP kinase and RNase A), showing that cosolvent MD with PART generated restraints qualitatively reproduces binding features of cocrystallised ligands. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Enediyne antibiotics are a class of potent DNA-cleaving antitumor agents. Searching for promising analogs of enediyne antibiotics, the features of interaction with the DNA of enediynes fused with heterocycles have been studied using molecular modeling methods. Depending on their structure, 10-membered heteroenediynes can exhibit both intercalator properties and bind to the minor groove of DNA. Variation of the heterocyclic part annulated with the enediyne cycle as well as the attachment of substituents at the enediyne core makes it possible to change the DNA method of binding mode, from intercalation to minor groove-binding. [ABSTRACT FROM AUTHOR]

Stochastic systems often exhibit multiple viable metastable states that are long-lived. Over very long timescales, fluctuations may push the system to transition between them, drastically changing its macroscopic configuration. In realistic systems, these transitions can happen via multiple physical mechanisms, corresponding to multiple distinct transition channels for a pair of states. In this paper, we use the fact that the transition path ensemble is equivalent to the invariant measure of a gradient flow in pathspace, which can be efficiently sampled via metadynamics. We demonstrate how this pathspace metadynamics, previously restricted to reversible molecular dynamics, is in fact very generally applicable to metastable stochastic systems, including irreversible and time-dependent ones, and allows rigorous estimation of the relative probability of competing transition paths. We showcase this approach on the study of a stochastic partial differential equation describing magnetic field reversal in the presence of advection. [ABSTRACT FROM AUTHOR]

Investigations of the synthesis of amino acids are crucial to the understanding of the chemical evolution of life and are of applied interest in biochemistry and pharmaceutical industry. Focus is here on extending the comprehension of their formation, studying by theoretical and computational procedures potential pathways for the synthesis of precursors of alanine. Amino acid is second in simplicity only to glycine and the simplest exhibiting chirality. Eight reaction paths were designed based on known experimental features and on theoretical grounds. For their study, stationary and dynamical quantum mechanical methods were used. For the first set of four reactions examined, E-ethanimine and Z-ethanimine reacted with carbon monoxide forming R- and S-alanine precursors, each process considered as evolving upon two planes of approach. For the other set of four reactions, the ethanimine isomers reacted with carbon dioxide. For all reactions, the chirality of the alanine precursors was also analyzed. Calculations of geometries and energies of the stationary points (reactants, products, van der Waals complexes and transition states) for all reactions were processed, as well as their thermodynamical state functions. The Z-ethanimine and CO reactions were found to be favored. Preferential channels for the chiral center formation were not identified. Biased first-principle molecular dynamics simulations (metadynamics) were carried out to provide the enantiomeric control of the reactions and the formation of other possible remarkable structures: initially 80 metadynamics simulations were performed. They confirmed the precursors of alanine found in the static calculations, but also found additional ones. In general, the last steps of the simulation culminated in simpler and less reactive substances. Our results individuated feasible reaction pathways to precursors of alanine synthesis, although no evidence was obtained of favoring homochiral selectivity. However, insertion of CO and CO2 into ethanimines was considered, with these molecules being of primordial interest, and both were shown to be orientable in gaseous flow, so arguably relevant to the emergence of chirality by a stereodynamic mechanism. [ABSTRACT FROM AUTHOR]

Integrin αIIbβ3 mediates platelet aggregation by binding the Arginyl-Glycyl-Aspartic acid (RGD) sequence of fibrinogen. RGD binding occurs at a site topographically proximal to the αIIb and β3 subunits, promoting the conformational activation of the receptor from bent to extended states. While several experimental approaches have characterized RGD binding to αIIbβ3 integrin, applying computational methods has been significantly more challenging due to limited sampling and the need for a priori information regarding the interactions between the RGD peptide and integrin. In this study, we employed all-atom simulations using funnel metadynamics (FM) to evaluate the interactions of an RGD peptide with the αIIb and β3 subunits of integrin. FM incorporates an external history-dependent potential on selected degrees of freedom while applying a funnel-shaped restraint potential to limit RGD exploration of the unbound state. Furthermore, it does not require a priori information about the interactions, enhancing the sampling at a low computational cost. Our FM simulations reveal significant molecular changes in the β3 subunit of integrin upon RGD binding and provide a free-energy landscape with a low-energy binding mode surrounded by higher-energy prebinding states. The strong agreement between previous experimental and computational data and our results highlights the reliability of FM as a method for studying dynamic interactions of complex systems such as integrin.

Metadynamics electron microscopy metaInference (MEMMI) is an integrative structural biology method that enables a rapid and accurate characterization of protein structural dynamics at the atomic level and the error in the cryo‐EM experimental data, even in cases where conformations are separated by high energy barriers. It achieves this by incorporating (a) cryo‐electron microscopy electron density maps with (b) metadynamic‐enhanced‐sampling molecular dynamics. Here, I showcase the setup and analysis protocol of MEMMI, used to discover the atomistic structural ensemble and error in the cryo‐EM electron density map of the fuzzy coat of IAPP, a fibril implicated in type II diabetes.

The coronavirus SARS-CoV-2 protects its RNA from being recognized by host immune responses by methylation of its 5’ end, also known as capping. This process is carried out by two enzymes, non-structural protein 16 (NSP16) containing 2’-O-methyltransferase and NSP14 through its N7 methyltransferase activity, which are essential for the replication of the viral genome as well as evading the host’s innate immunity. NSP10 acts as a crucial cofactor and stimulator of NSP14 and NSP16. To further understand the role of NSP10, we carried out a comprehensive analysis of >13 million globally collected whole-genome sequences (WGS) of SARS-CoV-2 obtained from the Global Initiative Sharing All Influenza Data (GISAID) and compared it with the reference genome Wuhan/WIV04/2019 to identify all currently known variants in NSP10. T12I, T102I, and A104V in NSP10 have been identified as the three most frequent variants and characterized using X-ray crystallography, biophysical assays, and enhanced sampling simulations. In contrast to other proteins such as spike and NSP6, NSP10 is significantly less prone to mutation due to its crucial role in replication. The functional effects of the variants were examined for their impact on the binding affinity and stability of both NSP14-NSP10 and NSP16-NSP10 complexes. These results highlight the limited changes induced by variant evolution in NSP10 and reflect on the critical roles NSP10 plays during the SARS-CoV-2 life cycle. These results also indicate that there is limited capacity for the virus to overcome inhibitors targeting NSP10 via the generation of variants in inhibitor binding pockets.

Various force fields and water model potentials influence significantly RNA conformations. The polyanionic nature of RNA attracts the water molecules and the counter ions which in turn affects their stability. The interfacial water's structural and dynamic aspects affect the RNA's base-pair opening and denaturation by breaking or making inter/intra-hydrogen bonds. Herein, we employed an MD simulations study using SPC/E and modified TIP3P water models in combination with different force fields CHARMM and AMBER to find their influence on the hydration shell of the SARS-CoV-2 RNA genome at different temperatures. AMBER-mTIP3P model was found to give more dynamic and transient conformations for RNA. The lower dielectric constant of the SPC/E model helps in the formation of the ion-contact pair near the negatively charged phosphate group (Na+-PO4−) leading to strong RNA-ion interaction and strong hydration shells having higher hydrogen bond lifetime. The Na+ ion survival probability at the interface was found to be more in the SPC/E model. At lower temperatures, the water molecules inside these hydration shells were found to be inhomogeneous, with lower void space, higher-coordinated, and non-tetrahedral. The higher dielectric constant of the mTIP3P model screened out the attraction between the ion pairs leading to a more homogenous solvation shell having a lesser hydrogen bond lifetime and more diffusive water. The distribution of the ions near the RNA structure is confirmed by metadynamics simulations. Both water models were found to disrupt the base pair orientation due to the formation of water bridges between the O2ʹ group of RNA and the water molecules.

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases. [ABSTRACT FROM AUTHOR]

In the context of drug discovery, computational methods were able to accelerate the challenging process of designing and optimizing a new drug candidate. Amongst the possible atomistic simulation approaches, metadynamics (metaD) has proven very powerful. However, the choice of collective variables (CVs) is not trivial for complex systems. To automate the process of CVs identification, two different machine learning algorithms were applied in this study, namely DeepLDA and Autoencoder, to the metaD simulation of a well‐researched drug/target complex, consisting in a pharmacologically relevant non‐canonical DNA secondary structure (G‐quadruplex) and a metallodrug acting as its stabilizer, as well as solvent molecules. [ABSTRACT FROM AUTHOR]

Electrochemical methods can detect trace amounts of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in the environment to help their management. PFAS adsorption on electrodes is an essential step in these methods, but is poorly understood. Here, we study the adsorption of perfluorooctanoic acid (PFOA), a model PFAS molecule, on gold substrates using metadynamics and equilibrium molecular dynamics simulations. The two‐dimensional free energy landscape obtained from metadynamics reveals that a PFOA molecule can adsorb on a neutral gold surface with the lowest free energy of −83.9 kJ/mol by adopting a co‐planar orientation, indicating a strong enrichment of PFOA occurs near the electrode. Spontaneous adsorption in other configurations, e. g. only a PFOA molecule's head attaches to the electrode, also occurs. However, a PFOA molecule generally must overcome energy barriers to become adsorbed. We show that energetic effects, particularly those associated with van der Waals PFOA‐gold interactions, are the primary driver for PFOA adsorption, and entropic effects associated with interfacial water molecules are the secondary driver. The implications of these results for the electrochemical detection and analysis of PFAS molecules are discussed. [ABSTRACT FROM AUTHOR]

Car–Parrinello molecular dynamics and metadynamics were carried out for salt-free Wittig reaction of non-stabilized, semi-stabilized and stabilized ylides and correlated to static quantum calculation at PBE/6-31G(d, p), including continuum solvation. The Grimme's dispersion correction approach (DFT-D) was employed throughout the study for both methods. The aim of the present investigations is to reformulate in details than has been possible hitherto, the reaction path and introduce all the stable and metastable states in the Wittig reaction, using ab-initio molecular dynamics tools. In what follows, we show that in the calculated free energy surface, betaine appears at the beginning of the reaction followed by oxaphosphetane for all ylides. The betaine has a higher energy and short life time than oxaphosphetane. It is found that increasing the ylide stability extends the reaction onset time and reduces the overall reaction time. The metadynamics trajectory (metatrajectory) shows the early formation of the C–C bond followed by the P–O bonding formation and simultaneous breaking of the P–C and C–O bond. Within this process, a high E selectivity for all ylides is observed. The metadynamics analysis encompasses all possible energy reaction coordinates; this property provides a more detailed mechanistic picture. Comparison with static calculations demonstrates the potential of the metadynamics approach in the conformational and geometric analysis of the cycloaddition and the cycloelimination processes. [ABSTRACT FROM AUTHOR]

Interactions between DNA and graphene are paramount for a wide range of applications, such as biosensing and nanoelectronics; nonetheless, the molecular details of such interactions remain largely unexplored. We employ atomically detailed molecular dynamics simulations with an enhanced sampling technique to investigate the adsorption and mobility of double-stranded DNA along the basal plane of graphene, in an electrolytic aqueous medium. The study focuses on physiologically relevant conditions, using a buffer of [NaCl] = 134 mM. DNA physisorption is shown to be fast and irreversible, leading to deformation and partial melting of the double helix as a result of π–π stacking between the terminal nucleobases and graphene. Denaturation occurs primarily at the termini, with ensemble averaged H-bond ratios of 47.8–62%; these can, however, reach a minimum of 15%. Transition between free-energy minima occurs via a thermodynamical pathway driving the nucleic acid from a radius of gyration of 1.5 nm to 1.35 nm. Mobility along the basal plane of graphene is dominant, accounting for ~90% of all centre-of-mass translation and revealing that the DNA’s apparent diffusivity is similar to diffusion along the endohedral volume of carbon nanotubes, but one order of magnitude faster than in other 2D materials, such as BC3 and C3N.

Abstract Electrochemical methods can detect trace amounts of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in the environment to help their management. PFAS adsorption on electrodes is an essential step in these methods, but is poorly understood. Here, we study the adsorption of perfluorooctanoic acid (PFOA), a model PFAS molecule, on gold substrates using metadynamics and equilibrium molecular dynamics simulations. The two‐dimensional free energy landscape obtained from metadynamics reveals that a PFOA molecule can adsorb on a neutral gold surface with the lowest free energy of −83.9 kJ/mol by adopting a co‐planar orientation, indicating a strong enrichment of PFOA occurs near the electrode. Spontaneous adsorption in other configurations, e. g., only a PFOA molecule‘s head attaches to the electrode, also occurs. However, a PFOA molecule generally must overcome energy barriers to become adsorbed. We show that energetic effects, particularly those associated with van der Waals PFOA‐gold interactions, are the primary driver for PFOA adsorption, and entropic effects associated with interfacial water molecules are the secondary driver. The implications of these results for the electrochemical detection and analysis of PFAS molecules are discussed.

Here, we present a parametrization of the metadynamics simulations for reactions involving breaking the chemical bonds along a single collective variable coordinate. The parameterization is based on the similarity between the bias potential in metadynamics and the quantum potential in the de Broglie–Bohm formalism. We derive the method and test it on two prototypical reaction types: proton transfer and breaking of the cyclohexene cycle (reversed Diels–Alder reaction). [ABSTRACT FROM AUTHOR]

The results are presented of a theoretical study on assessment of the stereoselectivity of processes aimed at increasing the enantiomeric excess of chiral pyrimidinones, products of the Biginelli reaction. The effects of hydroxyproline-containing podands used as chiral inductors, viz., the influence of the base or salt forms and of the oxyethylene chain length in the stage of formation of iminium intermediates of the Biginelli reaction are considered. A methodology is proposed for modeling a multicomponent reaction mixture by the molecular dynamics method. The strategy proved itself in quantitative assessment of the stereoselectivity of the approach of urea molecule to the iminium stereoisomers under the conditions of a simulated diffusion stage of the reaction. The energy maps constructed in the polar coordinates make it possible to visually assess the preference of the reagent approach to the different diastereotopic sides. [ABSTRACT FROM AUTHOR]

Metadynamics electron microscopy metaInference (MEMMI) is an integrative structural biology method that enables a rapid and accurate characterization of protein structural dynamics at the atomic level and the error in the cryo‐EM experimental data, even in cases where conformations are separated by high energy barriers. It achieves this by incorporating (a) cryo‐electron microscopy electron density maps with (b) metadynamic‐enhanced‐sampling molecular dynamics. Here, I showcase the setup and analysis protocol of MEMMI, used to discover the atomistic structural ensemble and error in the cryo‐EM electron density map of the fuzzy coat of IAPP, a fibril implicated in type II diabetes. [ABSTRACT FROM AUTHOR]