Protein Energy Landscape Exploration Research Articles

Exploiting cyclodextrins as artificial chaperones to enhance enzyme protection through supramolecular engineering.

We report a method of enzyme stabilisation exploiting the artificial protein chaperone properties of β-cyclodextrin (β-CD) covalently embedded in an ultrathin organosilica layer. Putative interaction points of this artificial chaperone system with the surface of the selected enzyme were studied in silico using a protein energy landscape exploration simulation algorithm. We show that this enzyme shielding method allows for drastic enhancement of enzyme stability under thermal and chemical stress conditions, along with broadening the optimal temperature range of the biocatalyst. The presence of the β-CD macrocycle within the protective layer supports protein refolding after treatment with a surfactant.

Enzyme Access Tunnel Engineering in Baeyer‐Villiger Monooxygenases to Improve Oxidative Stability and Biocatalyst Performance

AbstractHydrogen peroxide is involved in a variety of enzyme catalysis as an oxidant or toxic by‐product. Thereby, attenuation of the H2O2‐driven oxidative stress is one of the key issues for preparative biocatalysis. Here, a rational approach to improve the robustness of enzymes, in particular, Baeyer‐Villiger monooxygenases (BVMOs) against H2O2 was investigated. The enzyme access tunnels, which may serve as exit paths for H2O2 from the active site to the bulk, were predicted by using the CAVER and/or protein energy landscape exploration (PELE) software for the phenylacetone monooxygenase variant (PAMO_C65D) from Thermobifida fusca and the BVMO from Pseudomonas putida KT2440. The amino acid residues, which are susceptible to oxidation by H2O2 (e. g., methionine and tyrosine) and located in vicinity of the predicted H2O2 migration paths, were substituted with less reactive or inert amino acids (e. g., leucine and isoleucine). This led to design of the H2O2‐resistant enzyme variants, which became robust biocatalysts for synthetic applications. For instance, the H2O2‐resistant P. putida BVMO reached turnover numbers of 4,100 for the BV oxygenation of 4‐decanone, which is 2.8‐fold greater than the parent enzyme. Moreover, the H2O2‐resistant P. putida BVMO allowed 2‐fold enhancement in titer of 9‐(nonanoyloxy)nonanoic acid (8) formation in a cascade fatty acid biotransformation. Therefore, it was assumed that the CAVER/PELE‐based H2O2 migration path engineering represents an efficient rational design approach to improve not only oxidative stability but also biotransformation performance of the H2O2‐forming or utilizing enzymes (e. g., BVMOs, oxidases, and peroxidases).magnified image

Known Evolutionary Paths Are Accessible to Engineered ß-Lactamases Having Altered Protein Motions at the Timescale of Catalytic Turnover.

The evolution of new protein functions is dependent upon inherent biophysical features of proteins. Whereas, it has been shown that changes in protein dynamics can occur in the course of directed molecular evolution trajectories and contribute to new function, it is not known whether varying protein dynamics modify the course of evolution. We investigate this question using three related ß-lactamases displaying dynamics that differ broadly at the slow timescale that corresponds to catalytic turnover yet have similar fast dynamics, thermal stability, catalytic, and substrate recognition profiles. Introduction of substitutions E104K and G238S, that are known to have a synergistic effect on function in the parent ß-lactamase, showed similar increases in catalytic efficiency toward cefotaxime in the related ß-lactamases. Molecular simulations using Protein Energy Landscape Exploration reveal that this results from stabilizing the catalytically-productive conformations, demonstrating the dominance of the synergistic effect of the E014K and G238S substitutions in vitro in contexts that vary in terms of sequence and dynamics. Furthermore, three rounds of directed molecular evolution demonstrated that known cefotaximase-enhancing mutations were accessible regardless of the differences in dynamics. Interestingly, specific sequence differences between the related ß-lactamases were shown to have a higher effect in evolutionary outcomes than did differences in dynamics. Overall, these ß-lactamase models show tolerance to protein dynamics at the timescale of catalytic turnover in the evolution of a new function.

AquaPELE: A Monte Carlo-Based Algorithm to Sample the Effects of Buried Water Molecules in Proteins

Water is frequently found inside proteins, carrying out important roles in catalytic reactions or molecular recognition tasks. Therefore, computational models that aim to study protein-ligand interactions usually have to include water effects through explicit or implicit approaches to obtain reliable results. While full explicit models might be too computationally daunting for some applications, implicit models are normally faster but omit some of the most important contributions of water. This is the case of our in-house software, called protein energy landscape exploration (PELE), which uses implicit models to speed up conformational explorations as much as possible; the lack of explicit water sampling, however, limits its model. In this work, we confront this problem with the development of aquaPELE. It is a new algorithm that extends the exploration capabilities while keeping efficiency as it employs a mixed implicit/explicit approach to also take into account the effects of buried water molecules. With an additional Monte Carlo (MC) routine, a set of explicit water molecules is perturbed inside protein cavities and their effects are dynamically adjusted to the current state of the system. As a result, this implementation can be used to predict the principal hydration sites or the rearrangement and displacement of conserved water molecules upon the binding of a ligand. We benchmarked this new tool focusing on estimating ligand binding modes and hydration sites in cavities with important interfacial water molecules, according to crystallographic structures. Results suggest that aquaPELE sets a fast and reliable alternative for molecular recognition studies in systems with a strong water-dependency.

Predicting Antibody Neutralization Efficacy in Hypermutated Epitopes Using Monte Carlo Simulations.

Human Immunodeficiency Virus 1 (HIV-1) evades adaptive immunity by means of its extremely high mutation rate, which allows the HIV envelope glycoprotein to continuously escape from the action of antibodies. However, some broadly neutralizing antibodies (bNAbs) targeting specific viral regions show the ability to block the infectivity of a large number of viral variants. The discovery of these antibodies opens new avenues in anti-HIV therapy; however, they are still suboptimal tools as their amplitude of action ranges between 50% and 90% of viral variants. In this context, being able to discriminate between sensitive and resistant strains to an antibody would be of great interest for the design of optimal clinical antibody treatments and to engineer potent bNAbs for clinical use. Here, we describe a hierarchical procedure to predict the antibody neutralization efficacy of multiple viral isolates to three well-known anti-CD4bs bNAbs: VRC01, NIH45-46 and 3BNC117. Our method consists of simulating the three-dimensional binding process between the gp120 and the antibody by using Protein Energy Landscape Exploration (PELE), a Monte Carlo stochastic approach. Our results clearly indicate that the binding profiles of sensitive and resistant strains to a bNAb behave differently, showing the latter’s weaker binding profiles, that can be exploited for predicting antibody neutralization efficacy in hypermutated HIV-1 strains.

PELE-MSM: A Monte Carlo Based Protocol for the Estimation of Absolute Binding Free Energies.

In this study, we present a fully automatic platform based on our Monte Carlo algorithm, the Protein Energy Landscape Exploration method (PELE), for the estimation of absolute protein-ligand binding free energies, one of the most significant challenges in computer aided drug design. Based on a ligand pathway approach, an initial short enhanced sampling simulation is performed to identify reasonable starting positions for more extended sampling. This stepwise approach allows for a significant faster convergence of the free energy estimation using the Markov State Model (MSM) technique. PELE-MSM was applied on four diverse protein and ligand systems, successfully ranking compounds for two systems. Based on the results, current limitations and challenges with physics-based methods in computational structural biology are discussed. Overall, PELE-MSM constitutes a promising step toward computing absolute binding free energies and in their application into drug discovery projects.

Rational Engineering of Multiple Active Sites in an Ester Hydrolase.

Effects of altering the properties of an active site in an enzymatic homogeneous catalyst have been extensively reported. However, the possibility of increasing the number of such sites, as commonly done in heterogeneous catalytic materials, remains unexplored, particularly because those have to accommodate appropriate residues in specific configurations. This possibility was investigated by using a serine ester hydrolase as the target enzyme. By using the Protein Energy Landscape Exploration software, which maps ligand diffusion and binding, we found a potential binding pocket capable of holding an extra catalytic triad and oxyanion hole contacts. By introducing two mutations, this binding pocket became a catalytic site. Its substrate specificity, substrate preference, and catalytic activity were different from those of the native site of the wild type ester hydrolase and other hydrolases, due to the differences in the active site architecture. Converting the binding pocket into an extra catalytic active site was proven to be a successful approach to create a serine ester hydrolase with two functional reactive groups. Our results illustrate the accuracy and predictive nature of modern modeling techniques, opening novel catalytic opportunities coming from the presence of different catalytic environments in single enzymes.

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.

Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein-ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD < 1.0 Å) can be obtained by the PELE method within a few hours of simulation, positioning PELE as a tool applicable for rapid drug design cycles.

In Silico Characterization of P-Glycoprotein Substrate Entrance Pathways

Due to the wide variety of substrates it extrudes, P-glycoprotein is one of the main causes of multidrug resistance. Although the chemical structure of a ligand is likely to dictate interactions within the binding site, it is equally important to understand how access to the binding site itself is controlled. Access to the binding site is via an aqueous cavity formed in the main by transmembrane helices (TMHs). These TMHs also have helical structure that extends into the cytoplasm, but the hydrophobic vacuum cleaner model suggests that access to the aqueous cavity is via gates between the membranous regions of TMHs 4 and 6 or between TMHs 10 and 12.Previously, we observed that the intra-membrane sections of these gates tend to close while cytoplasmic regions remain open. We have explored this further via the use of steered MD with substrates initially positioned in the cytoplasmic leaflet of the bilayer. Rather unexpectedly, the simulations show that entrance through the intra-membrane gate requires a significantly larger amount of work compared to the cytoplasmic entrance and with a preference for the cavity between TMH 4 and 6 compared to that between TMH 10 and 12.Once the compound has reached the aqueous cavity, it can freely diffuse towards its binding site. The binding mode was independently assessed through the use of consensus docking and appears to be similar to the so-called “R-site”. The docked conformations were then used to calculate possible unbinding pathways of amitriptyline with the Protein Energy Landscape Exploration (PELE) method.Taken together, these combined approaches suggest that a likely access route to the binding site for many compounds is through a cytoplasmic gate formed by TMHs 4 and 6.

Steroid hydroxylation by basidiomycete peroxygenases: a combined experimental and computational study.

The goal of this study is the selective oxyfunctionalization of steroids under mild and environmentally friendly conditions using fungal enzymes. With this purpose, peroxygenases from three basidiomycete species were tested for the hydroxylation of a variety of steroidal compounds, using H2O2 as the only cosubstrate. Two of them are wild-type enzymes from Agrocybe aegerita and Marasmius rotula, and the third one is a recombinant enzyme from Coprinopsis cinerea. The enzymatic reactions on free and esterified sterols, steroid hydrocarbons, and ketones were monitored by gas chromatography, and the products were identified by mass spectrometry. Hydroxylation at the side chain over the steroidal rings was preferred, with the 25-hydroxyderivatives predominating. Interestingly, antiviral and other biological activities of 25-hydroxycholesterol have been reported recently (M. Blanc et al., Immunity 38:106-118, 2013, http://dx.doi.org/10.1016/j.immuni.2012.11.004). However, hydroxylation in the ring moiety and terminal hydroxylation at the side chain also was observed in some steroids, the former favored by the absence of oxygenated groups at C-3 and by the presence of conjugated double bonds in the rings. To understand the yield and selectivity differences between the different steroids, a computational study was performed using Protein Energy Landscape Exploration (PELE) software for dynamic ligand diffusion. These simulations showed that the active-site geometry and hydrophobicity favors the entrance of the steroid side chain, while the entrance of the ring is energetically penalized. Also, a direct correlation between the conversion rate and the side chain entrance ratio could be established that explains the various reaction yields observed.

Catalytic surface radical in dye-decolorizing peroxidase: a computational, spectroscopic and site-directed mutagenesis study.

Dye-decolorizing peroxidase (DyP) of Auricularia auricula-judae has been expressed in Escherichia coli as a representative of a new DyP family, and subjected to mutagenic, spectroscopic, crystallographic and computational studies. The crystal structure of DyP shows a buried haem cofactor, and surface tryptophan and tyrosine residues potentially involved in long-range electron transfer from bulky dyes. Simulations using PELE (Protein Energy Landscape Exploration) software provided several binding-energy optima for the anthraquinone-type RB19 (Reactive Blue 19) near the above aromatic residues and the haem access-channel. Subsequent QM/MM (quantum mechanics/molecular mechanics) calculations showed a higher tendency of Trp-377 than other exposed haem-neighbouring residues to harbour a catalytic protein radical, and identified the electron-transfer pathway. The existence of such a radical in H2O2-activated DyP was shown by low-temperature EPR, being identified as a mixed tryptophanyl/tyrosyl radical in multifrequency experiments. The signal was dominated by the Trp-377 neutral radical contribution, which disappeared in the W377S variant, and included a tyrosyl contribution assigned to Tyr-337 after analysing the W377S spectra. Kinetics of substrate oxidation by DyP suggests the existence of high- and low-turnover sites. The high-turnover site for oxidation of RB19 (kcat> 200 s−1) and other DyP substrates was assigned to Trp-377 since it was absent from the W377S variant. The low-turnover site/s (RB19 kcat ~20 s−1) could correspond to the haem access-channel, since activity was decreased when the haem channel was occluded by the G169L mutation. If a tyrosine residue is also involved, it will be different from Tyr-337 since all activities are largely unaffected in the Y337S variant.

Unveiling Prolyl Oligopeptidase Ligand Migration by Comprehensive Computational Techniques

Prolyl oligopeptidase (POP) is a large 80 kDa protease, which cleaves oligopeptides at the C-terminal side of proline residues and constitutes an important pharmaceutical target. Despite the existence of several crystallographic structures, there is an open debate about migration (entrance and exit) pathways for ligands, and their coupling with protein dynamics. Recent studies have shown the capabilities of molecular dynamics and classical force fields in describing spontaneous binding events and nonbiased ligand migration pathways. Due to POP’s size and to the buried nature of its active site, an exhaustive sampling by means of conventional long enough molecular dynamics trajectories is still a nearly impossible task. Such a level of sampling, however, is possible with the breakthrough protein energy landscape exploration technique. Here, we present an exhaustive sampling of POP with a known inhibitor, Z-pro-prolinal. In >3000 trajectories Z-pro-prolinal explores all the accessible surface area, showing multiple entrance events into the large internal cavity through the pore in the β-propeller domain. Moreover, we modeled a natural substrate binding and product release by predicting the entrance of an undecapeptide substrate, followed by manual active site cleavage and nonbiased exit of one of the products (a dipeptide). The product exit shows preference from a flexible 18-amino acid residues loop, pointing to an overall mechanism where entrance and exit occur in different sites.

PELE web server: atomistic study of biomolecular systems at your fingertips

PELE, Protein Energy Landscape Exploration, our novel technology based on protein structure prediction algorithms and a Monte Carlo sampling, is capable of modelling the all-atom protein–ligand dynamical interactions in an efficient and fast manner, with two orders of magnitude reduced computational cost when compared with traditional molecular dynamics techniques. PELE’s heuristic approach generates trial moves based on protein and ligand perturbations followed by side chain sampling and global/local minimization. The collection of accepted steps forms a stochastic trajectory. Furthermore, several processors may be run in parallel towards a collective goal or defining several independent trajectories; the whole procedure has been parallelized using the Message Passing Interface. Here, we introduce the PELE web server, designed to make the whole process of running simulations easier and more practical by minimizing input file demand, providing user-friendly interface and producing abstract outputs (e.g. interactive graphs and tables). The web server has been implemented in C++ using Wt (http://www.webtoolkit.eu) and MySQL (http://www.mysql.com). The PELE web server, accessible at http://pele.bsc.es, is free and open to all users with no login requirement.

PELE: Protein Energy Landscape Exploration. A Novel Monte Carlo Based Technique.

Combining protein structure prediction algorithms and Metropolis Monte Carlo techniques, we provide a novel method to explore all-atom energy landscapes. The core of the technique is based on a steered localized perturbation followed by side-chain sampling as well as minimization cycles. The algorithm and its application to ligand diffusion are presented here. Ligand exit pathways are successfully modeled for different systems containing ligands of various sizes: carbon monoxide in myoglobin, camphor in cytochrome P450cam, and palmitic acid in the intestinal fatty-acid-binding protein. These initial applications reveal the potential of this new technique in mapping millisecond-time-scale processes. The computational cost associated with the exploration is significantly less than that of conventional MD simulations.