The EVB as a quantitative tool for formulating simulations and analyzing biological and chemical reactions

Prediction of enhanced solvent-induced enantioselectivity for a ring opening with a bifurcating reaction path

A fully atomistic molecular dynamics simulation predicts enhance induction of enantiomeric excess in the products of a reaction with a bifurcating reaction coordinate, when run in a chiral solvent.

Challenges in computational studies of enzyme structure, function and dynamics

In this review we give an overview of the field of Computational enzymology. We start by describing the birth of the field, with emphasis on the work of the 2013 chemistry Nobel Laureates. We then present key features of the state-of-the-art in the field, showing what theory, accompanied by experiments, has taught us so far about enzymes. We also briefly describe computational methods, such as quantum mechanics-molecular mechanics approaches, reaction coordinate treatment, and free energy simulation approaches. We finalize by discussing open questions and challenges.

The mechanism of proton translocation in respiratory complex I from molecular dynamics

Respiratory complex I, the biggest enzyme of respiratory chain, plays a key role in energy production by the mitochondrial respiratory chain and has been implicated in many human neurodegenerative diseases. Recently, the crystal structure of respiratory complex I is reported. We perform 50 ns molecular dynamics simulations on the membrane domain of respiratory complex I under two hypothetical states (oxidized state and reduced state). We find that the density of water molecules in the trans-membrane domain under reduced state is bigger than that under oxidized state. The connecting elements (helix HL and β-hairpins-helix element) fluctuate stronger under reduced state than that under oxidized state, causing more internal water molecules and facilitating the proton conduction. The conformational changes of helix HL and the crucial charged residue Glu in TM5 play key roles in the mechanism of proton translocation. Our results illustrate the dynamic behavior and the potential mechanism of respiratory complex I, which provides the structural basis for drug design of respiratory complex I.

Modeling catalytic promiscuity in the alkaline phosphatase superfamily

In recent years, it has become increasingly clear that promiscuity plays a key role in the evolution of new enzyme function. This finding has helped to elucidate fundamental aspects of molecular evolution. While there has been extensive experimental work on enzyme promiscuity, computational modeling of the chemical details of such promiscuity has traditionally fallen behind the advances in experimental studies, not least due to the nearly prohibitive computational cost involved in examining multiple substrates with multiple potential mechanisms and binding modes in atomic detail with a reasonable degree of accuracy. However, recent advances in both computational methodologies and power have allowed us to reach a stage in the field where we can start to overcome this problem, and molecular simulations can now provide accurate and efficient descriptions of complex biological systems with substantially less computational cost. This has led to significant advances in our understanding of enzyme function and evolution in a broader sense. Here, we will discuss currently available computational approaches that can allow us to probe the underlying molecular basis for enzyme specificity and selectivity, discussing the inherent strengths and weaknesses of each approach. As a case study, we will discuss recent computational work on different members of the alkaline phosphatase superfamily (AP) using a range of different approaches, showing the complementary insights they have provided. We have selected this particular superfamily, as it poses a number of significant challenges for theory, ranging from the complexity of the actual reaction mechanisms involved to the reliable modeling of the catalytic metal centers, as well as the very large system sizes. We will demonstrate that, through current advances in methodologies, computational tools can provide significant insight into the molecular basis for catalytic promiscuity, and, therefore, in turn, the mechanisms of protein functional evolution.

Electrostatic origin of the catalytic effect of a supramolecular host catalyst

The development of enzyme mimetic catalysts as well as the analysis of the catalytic effects of such catalysts has been a major challenge for synthetic chemists. One of the impressive examples of artificial catalysts has been the development of a highly charged host compound that provides a significant acceleration to the hydrolysis of orthoformates and other systems. However, the origin of the catalytic effect has not been quantified, and its origin remains somewhat unclear. The understanding of the corresponding supramolecular catalysis has thus become a major challenge, both in terms of computational modeling and in terms of the analysis of the corresponding acid-catalyzed reaction. Here we present a computer simulation study and kinetic analyses that reproduce the experimentally observed catalytic effect, establishing that this effect is due to electrostatic stabilization of the positively charged transition state (relative to the uncharged bound complex). Our study illustrates the crucial need for careful analysis of the complex kinetics of the catalytic effect and the host system, as well as the need for computational modeling in analyzing the catalytic effect and in the potential design of better catalysts. Finally, our finding of the large stabilization of the bound H(3)O(+) points out the very low "local pH" inside the host system even when the solvent is kept at a high pH.

Computational protein engineering: bridging the gap between rational design and laboratory evolution

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.

Analyzing the molecular basis of enzyme stability in ethanol/water mixtures using molecular dynamics simulations

One of the drawbacks of nonaqueous enzymology is the fact that enzymes tend to be less stable in organic solvents than in water. There are, however, some enzymes that display very high stabilities in nonaqueous media. In order to take full advantage of the use of nonaqueous solvents in enzyme catalysis, it is essential to elucidate the molecular basis of enzyme stability in these media. Toward this end, we performed μs-long molecular dynamics simulations using two homologous proteases, pseudolysin, and thermolysin, which are known to have considerably different stabilities in solutions containing ethanol. The analysis of the simulations indicates that pseudolysin is more stable than thermolysin in ethanol/water mixtures and that the disulfide bridge between C30 and C58 is important for the stability of the former enzyme, which is consistent with previous experimental observations. Our results indicate that thermolysin has a higher tendency to interact with ethanol molecules (especially through van der Waals contacts) than pseudolysin, which can lead to the disruption of intraprotein hydrophobic interactions and ultimately result in protein unfolding. In the absence of the C30-C58 disulfide bridge, pseudolysin undergoes larger conformational changes, becoming more open and more permeable to ethanol molecules which accumulate in its interior and form hydrophobic interactions with the enzyme, destroying its structure. Our observations are not only in good agreement with several previous experimental findings on the stability of the enzymes studied in ethanol/water mixtures but also give an insight on the molecular determinants of this stability. Our findings may, therefore, be useful in the rational development of enzymes with increased stability in these media.

Three ways in, one way out: water dynamics in the trans-membrane domains of the inner membrane translocase AcrB

Powered by proton-motive force, the inner membrane translocase AcrB is the engine of the AcrAB-TolC efflux pump in Escherichia coli. As proton conduction in proteins occurs along hydrogen-bonded networks of polar residues and water molecules, knowledge of the protein-internal water distribution and water-interacting residues allows drawing conclusions to possible pathways of proton conduction. Here, we report a series of 6× 50 ns independent molecular dynamics simulations of asymmetric AcrB embedded in a phospholipid/water environment. Simulating each monomer in its proposed protonation state, we calculated for each trans-membrane domain the average water distribution, identified residues interacting with these waters and quantified each residue's frequency of water hydrogen bond contact. Combining this information we find three possible routes of proton transfer connecting a continuously hydrated region of known key residues in the TMD interior to bulk water by one cytoplasmic and up to three periplasm water channels in monomer B and A. We find that water access of the trans-membrane domains is regulated by four groups of residues in a combination of side chain re-orientations and shifts of trans-membrane helices. Our findings support a proton release event via Arg971 during the C intermediate or in the transition to A, and proton uptake occurring in the A or B state or during a so far unknown intermediate in between B and C where cytoplasmic water access is still possible. Our simulations suggest experimentally testable hypotheses, which have not been investigated so far.

Coarse-grained (multiscale) simulations in studies of biophysical and chemical systems

Recent years have witnessed an explosion in computational power, leading to attempts to model ever more complex systems. Nevertheless, there remain cases for which the use of brute-force computer simulations is clearly not the solution. In such cases, great benefit can be obtained from the use of physically sound simplifications. The introduction of such coarse graining can be traced back to the early usage of a simplified model in studies of proteins. Since then, the field has progressed tremendously. In this review, we cover both key developments in the field and potential future directions. Additionally, particular emphasis is given to two general approaches, namely the renormalization and reference potential approaches, which allow one to move back and forth between the coarse-grained (CG) and full models, as these approaches provide the foundation for CG modeling of complex systems.

Paradynamics: an effective and reliable model for ab initio QM/MM free-energy calculations and related tasks

Recent years have seen tremendous effort in the development of approaches with which to obtain quantum mechanics/molecular mechanics (QM/MM) free energies for reactions in the condensed phase. Nevertheless, there remain significant challenges to address, particularly, the high computational cost involved in performing proper configurational sampling and, in particular, in obtaining ab initio QM/MM (QM(ai)/MM) free-energy surfaces. One increasingly popular approach that seems to offer an ideal way to progress in this direction is the elegant metadynamics (MTD) approach. However, in the current work, we point out the subtle efficiency problems associated with this approach and illustrate that we have at hand what is arguably a more powerful approach. More specifically, we demonstrate the effectiveness of an updated version of our original idea of using a classical reference potential for QM(ai)/MM calculations [J. Phys. Chem. 1995, 99, 17516)], which we refer to as paradynamics (PD). This approach is based on the use of an empirical valence bond (EVB) reference potential, which is already similar to the real ab initio potential. The reference potential is fitted to the ab initio potential by an iterative and, to a great degree, automated refinement procedure. The corresponding free-energy profile is then constructed using the refined EVB potential, and the linear response approximation (LRA) is used to evaluate the QM(ai)/MM activation free-energy barrier. The automated refinement of the EVB surface (and thus the reduction of the difference between the reference and ab initio potentials) is a key factor in accelerating the convergence of the LRA approach. We apply our PD approach to a test reaction, namely, the S(N)2 reaction between a chloride ion and methyl chloride, and demonstrate that, at present, this approach is far more powerful and cost-effective than the metadynamics approach (at least in its current implementation). We also discuss the general features of the PD approach in terms of its ability to explore complex systems and clarify that it is not a specialized approach limited to only accelerating QM(ai)/MM calculations with proper sampling, but rather can be used in a wide variety of applications. In fact, we point out that the use of a reference (CG) potential coupled with its PD refinement, as well as our renormalization approach, provides very general and powerful strategies that can be used very effectively to explore any property that has been studied by the MTD approach.

Multiscale modeling of biological functions

Recent years have witnessed a tremendous explosion in computational power, which in turn has resulted in great progress in the complexity of the biological and chemical problems that can be addressed by means of all-atom simulations. Despite this, however, our computational time is not infinite, and in fact many of the key problems of the field were resolved long before the existence of the current levels of computational power. This review will start by presenting a brief historical overview of the use of multiscale simulations in biology, and then present some key developments in the field, highlighting several cases where the use of a physically sound simplification is clearly superior to a brute-force approach. Finally, some potential future directions will be discussed.

Challenges and advances in validating enzyme design proposals: the case of kemp eliminase catalysis

One of the fundamental challenges in biotechnology and biochemistry is the ability to design effective enzymes. Despite recent progress, most of the advances on this front have been made by placing the reacting fragments in the proper places, rather than by optimizing the preorganization of the environment, which is the key factor in enzyme catalysis. Thus, rational improvement of the preorganization would require approaches capable of evaluating reliably the actual catalytic effect. This work considers the catalytic effects in different Kemp eliminases as a benchmark for a computer-aided enzyme design. It is shown that the empirical valence bond provides a powerful screening tool, with significant advantages over current alternative strategies. The insights provided by the empirical valence bond calculations are discussed with an emphasis on the ability to analyze the difference between the linear free energy relationships obtained in solution and those found in the enzymes. We also point out the trade-off between the reliability and speed of the calculations and try to determine what it takes to realize reliable computer-aided screening.

On catalytic preorganization in oxyanion holes: highlighting the problems with the gas-phase modeling of oxyanion holes and illustrating the need for complete enzyme models

Oxyanion holes play a major role in catalyzing enzymatic reactions, yet the corresponding energetics is frequently misunderstood. The main problem may be associated with the nontrivial nature of the electrostatic preorganization effect, without following the relevant formulation. That is, although the energetics of oxyanion holes have been fully quantified in early studies (which include both the enzymatic and reference solution reactions), the findings of these studies are sometimes overlooked, and, in some cases, it is assumed that gas-phase calculations with a fixed model of an oxyanion hole are sufficient for assessing the corresponding effect in the protein. Herein, we present a systematic analysis of this issue, clarifying the problems associated with modeling oxyanions by means of two fixed water molecules (or related constructs). We then re-emphasize the point that the effect of the oxyanion hole is mainly due to the fact that the relevant dipoles are already set in an orientation that stabilizes the TS charges, whereas the corresponding dipoles in solution are randomly oriented, resulting in the need to pay a very large reorganization energy. Simply calculating interaction energies with relatively fixed species cannot capture this crucial point, and considering it may help in advancing rational enzyme design.