Conformational Changes and ATP Hydrolysis in Zika Helicase: The Molecular Basis of a Biomolecular Motor Unveiled by Multiscale Simulations.

We computationally study the Zika NS3 helicase, a biological motor, using ATP hydrolysis energy for nucleic acid remodeling. Through molecular mechanics and hybrid quantum mechanics/molecular mechanics simulations, we explore the conformational landscape of motif V, a conserved loop connecting the active sites for ATP hydrolysis and nucleic acid binding. ATP hydrolysis, initiated by a meta-phosphate group formation, involves the nucleophilic attack of a water molecule activated by Glu286 proton abstraction. Motif V hydrogen bonds to this water via the Gly415 backbone NH group, assisting hydrolysis. Posthydrolysis, free energy is released when the inorganic phosphate moves away from the coordination shell of the magnesium ion, inducing a significant shift in the conformational landscape of motif V to establish a hydrogen bond between the Gly415 NH group and Glu285. According to our simulations, the Zika NS3 helicase acts as a ratchet biological motor with motif V transitions steered by Gly415's γ-phosphate sensing in the ATPase site.

Tautomer-Specific Deacylation and Ω-Loop Flexibility Explain the Carbapenem-Hydrolyzing Broad-Spectrum Activity of the KPC-2 ß-Lactamase.

KPC-2 (Klebsiella pneumoniae carbapenemase-2) is a globally disseminated serine-ß-lactamase (SBL) responsible for extensive ß-lactam antibiotic resistance in Gram-negative pathogens. SBLs inactivate ß-lactams via a mechanism involving a hydrolytically labile covalent acyl-enzyme intermediate. Carbapenems, the most potent ß-lactams, evade the activity of many SBLs by forming long-lived inhibitory acyl-enzymes; however, carbapenemases such as KPC-2 efficiently deacylate carbapenem acyl-enzymes. We present high-resolution (1.25-1.4 Å) crystal structures of KPC-2 acyl-enzymes with representative penicillins (ampicillin), cephalosporins (cefalothin), and carbapenems (imipenem, meropenem, and ertapenem) obtained utilizing an isosteric deacylation-deficient mutant (E166Q). The mobility of the Ω-loop (residues 165-170) negatively correlates with antibiotic turnover rates (kcat), highlighting the role of this region in positioning catalytic residues for efficient hydrolysis of different ß-lactams. Carbapenem-derived acyl-enzyme structures reveal the predominance of the Δ1-(2R) imine rather than the Δ2 enamine tautomer. Quantum mechanics/molecular mechanics molecular dynamics simulations of KPC-2:meropenem acyl-enzyme deacylation used an adaptive string method to differentiate the reactivity of the two isomers. These identify the Δ1-(2R) isomer as having a significantly (7 kcal/mol) higher barrier than the Δ2 tautomer for the (rate-determining) formation of the tetrahedral deacylation intermediate. Deacylation is therefore likely to proceed predominantly from the Δ2, rather than the Δ1-(2R) acyl-enzyme, facilitated by tautomer-specific differences in hydrogen-bonding networks involving the carbapenem C-3 carboxylate and the deacylating water and stabilization by protonated N-4, accumulating a negative charge on the Δ2 enamine-derived oxyanion. Taken together, our data show how the flexible Ω-loop helps confer broad-spectrum activity upon KPC-2, while carbapenemase activity stems from efficient deacylation of the Δ2-enamine acyl-enzyme tautomer.

Elucidation of the Active Form and Reaction Mechanism in Human Asparaginase Type III Using Multiscale Simulations.

l-asparaginases catalyze the asparagine hydrolysis to aspartate. These enzymes play an important role in the treatment of acute lymphoblastic leukemia because these cells are unable to produce their own asparagine. Due to the immunogenic response and various side effects of enzymes of bacterial origin, many attempts have been made to replace these enzymes with mammalian enzymes such as human asparaginase type III (hASNaseIII). This study investigates the reaction mechanism of hASNaseIII through molecular dynamics simulations, quantum mechanics/molecular mechanics methods, and free energy calculations. Our simulations reveal that the dimeric form of the enzyme plays a vital role in stabilizing the substrate in the active site, despite the active site residues coming from a single protomer. Protomer-protomer interactions are essential to keep the enzyme in an active conformation. Our study of the reaction mechanism indicates that the self-cleavage process that generates an N-terminal residue (Thr168) is required to activate the enzyme. This residue acts as the nucleophile, attacking the electrophilic carbon of the substrate after a proton transfer from its hydroxyl group to the N-terminal amino group. The reaction mechanism proceeds with the formation of an acyl-enzyme complex and its hydrolysis, which turns out to be the rate-determining step. Our proposal of the enzymatic mechanism sheds light on the role of different active site residues and rationalizes the studies on mutations. The insights provided here about hASNaseIII activity could contribute to the comprehension of the disparities among different ASNases and might even guide the design of new variants with improved properties for acute lymphoblastic leukemia treatment.

Enlighten2: molecular dynamics simulations of protein-ligand systems made accessible.

MOTIVATION: Experimental structural data can allow detailed insight into protein structure and protein-ligand interactions, which is crucial for many areas of bioscience, including drug design and enzyme engineering. Typically, however, little more than a static picture of protein-ligand interactions is obtained, whereas dynamical information is often required for deeper understanding and to assess the effect of mutations. Molecular dynamics (MD) simulations can provide such information, but setting up and running these simulations is not straightforward and requires expert knowledge. There is thus a need for a tool that makes protein-ligand simulation easily accessible to non-expert users. RESULTS: We present Enlighten2: efficient simulation protocols for protein-ligand systems alongside a user-friendly plugin to the popular visualization program PyMOL. With Enlighten2, non-expert users can straightforwardly run and visualize MD simulations on protein-ligand models of interest. There is no need to learn new programs and all underlying tools are free and open source. AVAILABILITY AND IMPLEMENTATION: The Enlighten2 Python package and PyMOL plugin are free to use under the GPL3.0 licence and can be found at https://enlighten2.github.io. We also provide a lightweight Docker image via DockerHub that includes Enlighten2 with all the required utilities.

Quantifying the limits of transition state theory in enzymatic catalysis.

While being one of the most popular reaction rate theories, the applicability of transition state theory to the study of enzymatic reactions has been often challenged. The complex dynamic nature of the protein environment raised the question about the validity of the nonrecrossing hypothesis, a cornerstone in this theory. We present a computational strategy to quantify the error associated to transition state theory from the number of recrossings observed at the equicommittor, which is the best possible dividing surface. Application of a direct multidimensional transition state optimization to the hydride transfer step in human dihydrofolate reductase shows that both the participation of the protein degrees of freedom in the reaction coordinate and the error associated to the nonrecrossing hypothesis are small. Thus, the use of transition state theory, even with simplified reaction coordinates, provides a good theoretical framework for the study of enzymatic catalysis.

A first peek into sub-picosecond dynamics of spin energy levels in magnetic biomolecules.

We estimate the time- and temperature-evolution of spin energy levels in a metallopeptide by combining molecular dynamics with crystal field analysis. Fluctuations of tens of cm-1 for spin energy levels at fs times gradually average out at longer times. We confirm that local vibrations are key in spin dynamics.

Adaptive Finite Temperature String Method in Collective Variables.

Here we present a modified version of the on-the-fly string method for the localization of the minimum free energy path in a space of arbitrary collective variables. In the proposed approach the shape of the biasing potential is controlled by only two force constants, defining the width of the potential along the string and orthogonal to it. The force constants and the distribution of the string nodes are optimized during the simulation, improving the convergence. The optimized parameters can be used for umbrella sampling with a path CV along the converged string as the reaction coordinate. We test the new method with three fundamentally different processes: chloride attack to chloromethane in bulk water, alanine dipeptide isomerization, and the enzymatic conversion of isochorismate to piruvate. In each case the same set of parameters resulted in a rapidly converging simulation and a precise estimation of the potential of mean force. Therefore, the default settings can be used for a wide range of processes, making the method essentially parameter free and more user-friendly.

Transition state ensemble optimization for reactions of arbitrary complexity.

In the present work, we use Variational Transition State Theory (VTST) to develop a practical method for transition state ensemble optimization by looking for an optimal hyperplanar dividing surface in a space of meaningful trial collective variables. These might be interatomic distances, angles, electrostatic potentials, etc. Restrained molecular dynamics simulations are used to obtain on-the-fly estimates of ensemble averages that guide the variations of the hyperplane maximizing the transmission coefficient. A central result of our work is an expression that quantitatively estimates the importance of the coordinates used for the localization of the transition state ensemble. Starting from an arbitrarily large set of trial coordinates, one can distinguish those that are indeed essential for the advance of the reaction. This facilitates the use of VTST as a practical theory to study reaction mechanisms of complex processes. The technique was applied to the reaction catalyzed by an isochorismate pyruvate lyase. This reaction involves two simultaneous chemical steps and has a shallow transition state region, making it challenging to define a good reaction coordinate. Nevertheless, the hyperplanar transition state optimized in the space of 18 geometrical coordinates provides a transmission coefficient of 0.8 and a committor histogram well-peaked about 0.5, proving the strength of the method. We have also tested the approach with the study of the NaCl dissociation in aqueous solution, a stringest test for a method based on transition state theory. We were able to find essential degrees of freedom consistent with the previous studies and to improve the transmission coefficient with respect to the value obtained using solely the NaCl distance as the reaction coordinate.

Dynamics and reactivity in Thermus aquaticus N6-adenine methyltransferase.

M.TaqI is a DNA methyltransferase from Thermus aquaticus that catalyzes the transfer of a methyl group from S-adenosyl-L-methionine to the N6 position of an adenine, a process described only in prokaryotes. We have used full atomistic classical molecular dynamics simulations to explore the protein-SAM-DNA ternary complex where the target adenine is flipped out into the active site. Key protein-DNA interactions established by the target adenine in the active site are described in detail. The relaxed structure was used for a combined quantum mechanics/molecular mechanics exploration of the reaction mechanism using the string method. According to our free energy calculations the reaction takes place through a stepwise mechanism where the methyl transfer precedes the abstraction of the proton from the exocyclic amino group. The methyl transfer is the rate-determining step, and the obtained free energy barrier is in good agreement with the value derived from the experimental rate constant. Two possible candidates to extract the leftover proton have been explored: a water molecule found in the active site and Asn105, a residue activated by the hydrogen bonds formed through the amide hydrogens. The barrier for the proton abstraction is smaller when Asn105 acts as a base. The reaction mechanisms can be different in other N6-DNA-methyltransferases, as determined from the exploration of the reaction mechanism in the Asn105Asp M.TaqI mutant.

Exploring chemical reactivity of complex systems with path-based coordinates: role of the distance metric.

Path-based reaction coordinates constitute a valuable tool for free-energy calculations in complex processes. When a reference path is defined by means of collective variables, a nonconstant distance metric that incorporates the nonorthonormality of these variables should be taken into account. In this work, we show that, accounting for the correct metric tensor, these kind of variables can provide iso-hypersurfaces that coincide with the iso-committor surfaces and that activation free energies equal the value that would be obtained if the committor function itself were used as reaction coordinate. The advantages of the incorporation of the variable metric tensor are illustrated with the analysis of the enzymatic reaction catalyzed by isochorismate-pyruvate lyase. Hybrid QM/MM techniques are used to obtain the free energy profile and to analyze reactive trajectories initiated at the transition state. For this example, the committor histogram is peaked at 0.5 only when a variable metric tensor is incorporated in the definition of the path-based coordinate.

4-Thiaproline accelerates the slow folding phase of proteins containing cis prolines in the native state by two orders of magnitude.

The cis/trans isomerization of peptidyl-prolyl peptide bonds is often the bottleneck of the refolding reaction for proteins containing cis proline residues in the native state. Proline (Pro) analogues, especially C4-substituted fluoroprolines, have been widely used in protein engineering to enhance the thermodynamic stability of peptides and proteins and to investigate folding kinetics. 4-thiaproline (Thp) has been shown to bias the ring pucker of Pro, to increase the cis population percentage of model peptides in comparison to Pro, and to diminish the activation energy barrier for the cis/trans isomerization reaction. Despite its intriguing properties, Thp has been seldom incorporated into proteins. Moreover, the impact of Thp on the folding kinetics of globular proteins has never been reported. In this study, we show that upon incorporation of Thp at cisPro76 into the thioredoxin variant Trx1P the half-life of the refolding reaction decreased from ~2 h to ~35 s. A dramatic acceleration of the refolding rate could be observed also for the protein pseudo wild-type barstar upon replacement of cisPro48 with Thp. Quantum chemical calculations suggested that the replacement of the Cγ H2 group by a sulfur atom in the pyrrolidine ring, might lower the barrier for cis/trans rotation due to a weakened peptide bond. The protein variants retained their thermodynamic stability upon incorporation of Thp, while the catalytic and enzymatic activities of the modified Trx1P remained unchanged. Our results show that the Pro isostere Thp might accelerate the rate of the slow refolding reaction for proteins containing cis proline residues in the native state, independent from the local structural environment.

emle-engine: A Flexible Electrostatic Machine Learning Embedding Package for Multiscale Molecular Dynamics Simulations.

We present in this work the emle-engine package (https://github.com/chemle/emle-engine)─the implementation of a new machine learning embedding scheme for hybrid machine learning potential/molecular-mechanics (ML/MM) dynamics simulations. The package is based on an embedding scheme that uses a physics-based model of the electronic density and induction with a handful of tunable parameters derived from in vacuo properties of the subsystem to be embedded. This scheme is completely independent of the in vacuo potential and requires only the positions of the atoms of the machine learning subsystem and the positions and partial charges of the molecular mechanics environment. These characteristics allow emle-engine to be employed in existing QM/MM software. We demonstrate that the implemented electrostatic machine learning embedding scheme (named EMLE) is stable in enhanced sampling molecular dynamics simulations. Through the calculation of free energy surfaces of alanine dipeptide in water with two different ML options for the in vacuo potential and three embedding models, we test the performance of EMLE. When compared to the reference DFT/MM surface, the EMLE embedding is clearly superior to the MM one based on fixed partial charges. The configurational dependence of the electronic density and the inclusion of the induction energy introduced by the EMLE model leads to a systematic reduction in the average error of the free energy surface when compared to MM embedding. By enabling the usage of EMLE embedding in practical ML/MM simulations, emle-engine will make it possible to accurately model systems and processes that feature significant variations in the charge distribution of the ML subsystem and/or the interacting environment.

Activation and friction in enzymatic loop opening and closing dynamics.

Protein loop dynamics have recently been recognized as central to enzymatic activity, specificity and stability. However, the factors controlling loop opening and closing kinetics have remained elusive. Here, we combine molecular dynamics simulations with string-method determination of complex reaction coordinates to elucidate the molecular mechanism and rate-limiting step for WPD-loop dynamics in the PTP1B enzyme. While protein conformational dynamics is often represented as diffusive motion hindered by solvent viscosity and internal friction, we demonstrate that loop opening and closing is activated. It is governed by torsional rearrangement around a single loop peptide group and by significant friction caused by backbone adjustments, which can dynamically trap the loop. Considering both torsional barrier and time-dependent friction, our calculated rate constants exhibit very good agreement with experimental measurements, reproducing the change in loop opening kinetics between proteins. Furthermore, we demonstrate the applicability of our results to other enzymatic loops, including the M20 DHFR loop, thereby offering prospects for loop engineering potentially leading to enhanced designs.

Electrostatic Embedding of Machine Learning Potentials.

This work presents a variant of an electrostatic embedding scheme that allows the embedding of arbitrary machine learned potentials trained on molecular systems in vacuo. The scheme is based on physically motivated models of electronic density and polarizability, resulting in a generic model without relying on an exhaustive training set. The scheme only requires in vacuo single point QM calculations to provide training densities and molecular dipolar polarizabilities. As an example, the scheme is applied to create an embedding model for the QM7 data set using Gaussian Process Regression with only 445 reference atomic environments. The model was tested on the SARS-CoV-2 protease complex with PF-00835231, resulting in a predicted embedding energy RMSE of 2 kcal/mol, compared to explicit DFT/MM calculations.

Unveiling the Mechanistic Singularities of Caspases: A Computational Analysis of the Reaction Mechanism in Human Caspase-1.

Caspases are cysteine proteases in charge of breaking a peptide bond next to an aspartate residue. Caspases constitute an important family of enzymes involved in cell death and inflammatory processes. A plethora of diseases, including neurological and metabolic diseases and cancer, are associated with the poor regulation of caspase-mediated cell death and inflammation. Human caspase-1 in particular carries out the transformation of the pro-inflammatory cytokine pro-interleukin-1ß into its active form, a key process in the inflammatory response and then in many diseases, such as Alzheimer's disease. Despite its importance, the reaction mechanism of caspases has remained elusive. The standard mechanistic proposal valid for other cysteine proteases and that involves the formation of an ion pair in the catalytic dyad is not supported by experimental evidence. Using a combination of classical and hybrid DFT/MM simulations, we propose a reaction mechanism for the human caspase-1 that explains experimental observations, including mutagenesis, kinetic, and structural data. In our mechanistic proposal, the catalytic cysteine, Cys285, is activated after a proton transfer to the amide group of the scissile peptide bond, a process facilitated by hydrogen-bond interactions with Ser339 and His237. The catalytic histidine does not directly participate in any proton transfer during the reaction. After formation of the acylenzyme intermediate, the deacylation step takes place through the activation of a water molecule by the terminal amino group of the peptide fragment formed during the acylation step. The overall activation free energy obtained from our DFT/MM simulations is in excellent agreement with the value derived from the experimental rate constant, 18.7 vs 17.9 kcal·mol-1, respectively. Simulations of the H237A mutant support our conclusions and agree with the reported reduced activity observed for this caspase-1 variant. We propose that this mechanism can explain the reactivity of all cysteine proteases belonging to the CD clan and that differences with respect to other clans could be related to the larger preference showed by enzymes of the CD clan for charged residues at position P1. This mechanism would avoid the free energy penalty associated with the formation of an ion pair. Finally, our structural description of the reaction process can be useful to assist in the design of inhibitors of caspase-1, a target in the treatment of several human diseases.

The impact of SARS-CoV-2 3CL protease mutations on nirmatrelvir inhibitory efficiency. Computational insights into potential resistance mechanisms.

The use of antiviral drugs can promote the appearance of mutations in the target protein that increase the resistance of the virus to the treatment. This is also the case of nirmatrelvir, a covalent inhibitor of the 3CL protease, or main protease, of SARS-CoV-2. In this work we show how the by-residue decomposition of noncovalent interactions established between the drug and the enzyme, in combination with an analysis of naturally occurring mutations, can be used to detect potential mutations in the 3CL protease conferring resistance to nirmatrelvir. We also investigate the consequences of these mutations on the reaction mechanism to form the covalent enzyme-inhibitor complex using QM/MM methods. In particular, we show that the E166V variant of the protease displays smaller binding affinity to nirmatrelvir and larger activation free energy for the formation of the covalent complex, both factors contributing to the observed resistance to the treatment with this drug. The conclusions derived from our work can be used to anticipate the consequences of the introduction of nirmatrelvir in the fitness landscape of the virus and to design new inhibitors adapted to some of the possible resistance mechanisms.

Free energy along drug-protein binding pathways interactively sampled in virtual reality.

We describe a two-step approach for combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculation to explore the dynamics of biological processes at the molecular level. We refer to this combined approach as iMD-VR-FE. Stage one involves using a state-of-the-art 'human-in-the-loop' iMD-VR framework to generate a diverse range of protein-ligand unbinding pathways, benefitting from the sophistication of human spatial and chemical intuition. Stage two involves using the iMD-VR-sampled pathways as initial guesses for defining a path-based reaction coordinate from which we can obtain a corresponding free energy profile using FE methods. To investigate the performance of the method, we apply iMD-VR-FE to investigate the unbinding of a benzamidine ligand from a trypsin protein. The binding free energy calculated using iMD-VR-FE is similar for each pathway, indicating internal consistency. Moreover, the resulting free energy profiles can distinguish energetic differences between pathways corresponding to various protein-ligand conformations (e.g., helping to identify pathways that are more favourable) and enable identification of metastable states along the pathways. The two-step iMD-VR-FE approach offers an intuitive way for researchers to test hypotheses for candidate pathways in biomolecular systems, quickly obtaining both qualitative and quantitative insight.

Modeling caspase-1 inhibition: Implications for catalytic mechanism and drug design.

The metabolic product of caspase-1, IL-1ß, is an important mediator in inflammation and pyroptosis cell death process. Alzheimer's disease, septic shock and rheumatoid arthritis are IL-1ß mediated diseases, making the caspase-1 an interesting target of pharmacological value. Many inhibitors have been developed until now, most of them are peptidomimetic with improved potency. In the present study, all-atom molecular dynamics simulations and the MM/GBSA method were employed to reproduce and interpret the results obtained by in vitro experiments for a series of inhibitors. The analysis shows that the tautomeric state of the catalytic His237 impact significantly the performance of the prediction protocol, providing evidence for a His237 tautomeric state different to the proposed in the putative mechanism. Additionally, analysis of inhibitor-enzyme interactions indicates that the differences in the inhibitory potency of the tested ligands can be explained mainly by the interaction of the inhibitors with the S2-S4 protein region. These results provide guidelines for subsequent studies of caspase-1 catalytic reaction mechanism and for the design of novel inhibitors.