Molecular Gating of an Engineered Enzyme Captured in Real Time

Incorporating Prior Knowledge in the Seeds of Adaptive Sampling Molecular Dynamics Simulations of Ligand Transport in Enzymes with Buried Active Sites

Because most proteins have buried active sites, protein tunnels or channels play a crucial role in the transport of small molecules into buried cavities for enzymatic catalysis. Tunnels can critically modulate the biological process of protein-ligand recognition. Various molecular dynamics methods have been developed for exploring and exploiting the protein-ligand conformational space to extract high-resolution details of the binding processes, a recent example being energetically unbiased high-throughput adaptive sampling simulations. The current study systematically contrasted the role of integrating prior knowledge while generating useful initial protein-ligand configurations, called seeds, for these simulations. Using a nontrivial system of a haloalkane dehalogenase mutant with multiple transport tunnels leading to a deeply buried active site, simulations were employed to derive kinetic models describing the process of association and dissociation of the substrate molecule. The most knowledge-based seed generation enabled high-throughput simulations that could more consistently capture the entire transport process, explore the complex network of transport tunnels, and predict equilibrium dissociation constants, koff/kon, on the same order of magnitude as experimental measurements. Overall, the infusion of more knowledge into the initial seeds of adaptive sampling simulations could render analyses of transport mechanisms in enzymes more consistent even for very complex biomolecular systems, thereby promoting drug development efforts and the rational design of enzymes with buried active sites.

A kinetic model reveals the critical gating motifs for donor-substrate loading into Actinobacillus pleuropneumoniae N-glycosyltransferase

Soluble N-glycosyltransferase from Actinobacillus pleuropneumoniae (ApNGT) catalyzes the glycosylation of asparagine residues, and represents one of the most encouraging biocatalysts for N-glycoprotein production. Since the sugar tolerance of ApNGT is restricted to limited monosaccharides (e.g., Glc, GlcN, Gal, Xyl, and Man), tremendous efforts are devoted to expanding the substrate scope of ApNGT via enzyme engineering. However, rational design of novel NGT variants suffers from an elusive understanding of the substrate-binding process from a dynamic point of view. Here, by employing extensive all-atom molecular dynamics (MD) simulations integrated with a kinetic model, we reveal, at the atomic level, the complete donor-substrate binding process from the bulk solvent to the ApNGT active-site, and the key intermediate states of UDP-Glc during its loading dynamics. We are able to determine the critical transition event that limits the overall binding rate, which guides us to pinpoint the key ApNGT residues dictating the donor-substrate entry. The functional roles of several identified gating residues were evaluated through site-directed mutagenesis and enzymatic assays. Two single-point mutations, N471A and S496A, could profoundly enhance the catalytic activity of ApNGT. Our work provides deep mechanistic insights into the structural dynamics of the donor-substrate loading process for ApNGT, which sets a rational basis for design of novel NGT variants with desired substrate specificity.

Water will Find Its Way: Transport through Narrow Tunnels in Hydrolases

An aqueous environment is vital for life as we know it, and water is essential for nearly all biochemical processes at the molecular level. Proteins utilize water molecules in various ways. Consequently, proteins must transport water molecules across their internal network of tunnels to reach the desired action sites, either within them or by functioning as molecular pipes to control cellular osmotic pressure. Despite water playing a crucial role in enzymatic activity and stability, its transport has been largely overlooked, with studies primarily focusing on water transport across membrane proteins. The transport of molecules through a protein's tunnel network is challenging to study experimentally, making molecular dynamics simulations the most popular approach for investigating such events. In this study, we focused on the transport of water molecules across three different α/β-hydrolases: haloalkane dehalogenase, epoxide hydrolase, and lipase. Using a 5 μs adaptive simulation per system, we observed that only a few tunnels were responsible for the majority of water transport in dehalogenase, in contrast to a higher diversity of tunnels in other enzymes. Interestingly, water molecules could traverse narrow tunnels with subangstrom bottlenecks, which is surprising given the commonly accepted water molecule radius of 1.4 Å. Our analysis of the transport events in such narrow tunnels revealed a markedly increased number of hydrogen bonds formed between the water molecules and protein, likely compensating for the steric penalty of the process. Overall, these commonly disregarded narrow tunnels accounted for ∼20% of the total water transport observed, emphasizing the need to surpass the standard geometrical limits on the functional tunnels to properly account for the relevant transport processes. Finally, we demonstrated how the obtained insights could be applied to explain the differences in a mutant of the human soluble epoxide hydrolase associated with a higher incidence of ischemic stroke.

Connecting Biological and Synthetic Approaches for Electrocatalytic CO2 Reduction

Electrocatalytic CO2 reduction has developed into a broad field, spanning fundamental studies of enzymatic 'model' catalysts to synthetic molecular catalysts and heterogeneous gas diffusion electrodes producing commercially relevant quantities of product. This diversification has resulted in apparent differences and a disconnect between seemingly related approaches when using different types of catalysts. Enzymes possess discrete and well understood active sites that can perform reactions with high selectivity and activities at their thermodynamic limit. Synthetic small molecule catalysts can be designed with desired active site composition but do not yet display enzyme-like performance. These properties of the biological and small molecule catalysts contrast with heterogeneous materials, which can contain multiple, often poorly understood active sites with distinct reactivity and therefore introducing significant complexity in understanding their activities. As these systems are being better understood and the continuously improving performance of their heterogeneous active sites closes the gap with enzymatic activity, this performance difference between heterogeneous and enzymatic systems begins to close. This convergence removes the barriers between using different types of catalysts and future challenges can be addressed without multiple efforts as a unified picture for the biological-synthetic catalyst spectrum emerges.

Fluorescent Probes and Quenchers in Studies of Protein Folding and Protein-Lipid Interactions

Fluorescence spectroscopy provides numerous methodological tools for structural and functional studies of biological macromolecules and their complexes. All fluorescence-based approaches require either existence of an intrinsic probe or an introduction of an extrinsic one. Moreover, studies of complex systems often require an additional introduction of a specific quencher molecule acting in combination with a fluorophore to provide structural or thermodynamic information. Here, we review the fundamentals and summarize the latest progress in applications of different classes of fluorescent probes and their specific quenchers, aimed at studies of protein folding and protein-membrane interactions. Specifically, we discuss various environment-sensitive dyes, FRET probes, probes for short-distance measurements, and several probe-quencher pairs for studies of membrane penetration of proteins and peptides. The goals of this review are: (a) to familiarize the readership with the general concept that complex biological systems often require both a probe and a quencher to decipher mechanistic details of functioning and (b) to provide example of the immediate applications of the described methods.

ChannelsDB 2.0: a comprehensive database of protein tunnels and pores in AlphaFold era

ChannelsDB 2.0 is an updated database providing structural information about the position, geometry and physicochemical properties of protein channels-tunnels and pores-within deposited biomacromolecular structures from PDB and AlphaFoldDB databases. The newly deposited information originated from several sources. Firstly, we included data calculated using a popular CAVER tool to complement the data obtained using original MOLE tool for detection and analysis of protein tunnels and pores. Secondly, we added tunnels starting from cofactors within the AlphaFill database to enlarge the scope of the database to protein models based on Uniprot. This has enlarged available channel annotations ∼4.6 times as of 1 September 2023. The database stores information about geometrical features, e.g. length and radius, and physico-chemical properties based on channel-lining amino acids. The stored data are interlinked with the available UniProt mutation annotation data. ChannelsDB 2.0 provides an excellent resource for deep analysis of the role of biomacromolecular tunnels and pores. The database is available free of charge: https://channelsdb2.biodata.ceitec.cz.

sMolBoxes: Dataflow Model for Molecular Dynamics Exploration

We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case studies illustrate that even with relatively few sMolBoxes, it is possible to express complex analytical tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.

Mechanism-Based Strategy for Optimizing HaloTag Protein Labeling

HaloTag labeling technology has introduced unrivaled potential in protein chemistry and molecular and cellular biology. A wide variety of ligands have been developed to meet the specific needs of diverse applications, but only a single protein tag, DhaAHT, is routinely used for their incorporation. Following a systematic kinetic and computational analysis of different reporters, a tetramethylrhodamine- and three 4-stilbazolium-based fluorescent ligands, we showed that the mechanism of incorporating different ligands depends both on the binding step and the efficiency of the chemical reaction. By studying the different haloalkane dehalogenases DhaA, LinB, and DmmA, we found that the architecture of the access tunnels is critical for the kinetics of both steps and the ligand specificity. We showed that highly efficient labeling with specific ligands is achievable with natural dehalogenases. We propose a simple protocol for selecting the optimal protein tag for a specific ligand from the wide pool of available enzymes with diverse access tunnel architectures. The application of this protocol eliminates the need for expensive and laborious protein engineering.

Fast approximative methods for study of ligand transport and rational design of improved enzymes for biotechnologies

Acceleration of chemical reactions by the enzymes optimized using protein engineering represents one of the key pillars of the contribution of biotechnology towards sustainability. Tunnels and channels of enzymes with buried active sites enable the exchange of ligands, ions, and water molecules between the outer environment and active site pockets. The efficient exchange of ligands is a fundamental process of biocatalysis. Therefore, enzymes have evolved a wide range of mechanisms for repetitive conformational changes that enable periodic opening and closing. Protein-ligand interactions are traditionally studied by molecular docking, whereas molecular dynamics is the method of choice for studying conformational changes and ligand transport. However, computational demands make molecular dynamics impractical for screening purposes. Thus, several approximative methods have been recently developed to study interactions between a protein and ligand during the ligand transport process. Apart from identifying the best binding modes, these methods also provide information on the energetics of the transport and identify problematic regions limiting the ligand passage. These methods use approximations to simulate binding or unbinding events rapidly (calculation times from minutes to hours) and provide energy profiles that can be used to rank ligands or pathways. Here we provide a critical comparison of available methods, showcase their results on sample systems, discuss their practical applications in molecular biotechnologies and outline possible future developments.

In Silico Engineering of Enzyme Access Tunnels

Enzyme engineering is a tailoring process that allows the modification of naturally occurring enzymes to provide them with improved catalytic efficiency, stability, or specificity. By introducing partial modifications to their sequence and to their structural features, enzyme engineering can transform natural enzymes into more efficient, specific and resistant biocatalysts and render them suitable for virtually countless industrial processes. Current enzyme engineering methods mostly target the active site of the enzyme, where the catalytic reaction takes place. Nonetheless, the tunnel that often connects the surface of an enzyme with its buried active site plays a key role in the activity of the enzyme as it acts as a gatekeeper and regulates the access of the substrate to the catalytic pocket. Hence, there is an increasing interest in targeting the sequence and the structure of substrate entrance tunnels in order to fine-tune enzymatic activity, regulate substrate specificity, or control reaction promiscuity.In this chapter, we describe the use of a rational in silico design and screening method to engineer the access tunnel of a fructosyl peptide oxidase with the aim to facilitate access to its catalytic site and to expand its substrate range. Our goal is to engineer this class of enzymes in order to utilize them for the direct detection of glycated proteins in diabetes monitoring devices. The design strategy involves remodeling of the backbone structure of the enzyme , a feature that is not possible with conventional enzyme engineering techniques such as single-point mutagenesis and that is highly unlikely to occur using a directed evolution approach.The proposed strategy, which results in a significant reduction in cost and time for the experimental production and characterization of candidate enzyme variants, represents a promising approach to the expedited identification of novel and improved enzymes. Rational enzyme design aims to provide in silico strategies for the fast, accurate, and inexpensive development of biocatalysts that can meet the needs of multiple industrial sectors, thus ultimately promoting the use of green chemistry and improving the efficiency of chemical processes.

Substrate inhibition by the blockage of product release and its control by tunnel engineering

Substrate inhibition is the most common deviation from Michaelis-Menten kinetics, occurring in approximately 25% of known enzymes. It is generally attributed to the formation of an unproductive enzyme-substrate complex after the simultaneous binding of two or more substrate molecules to the active site. Here, we show that a single point mutation (L177W) in the haloalkane dehalogenase LinB causes strong substrate inhibition. Surprisingly, a global kinetic analysis suggested that this inhibition is caused by binding of the substrate to the enzyme-product complex. Molecular dynamics simulations clarified the details of this unusual mechanism of substrate inhibition: Markov state models indicated that the substrate prevents the exit of the halide product by direct blockage and/or restricting conformational flexibility. The contributions of three residues forming the possible substrate inhibition site (W140A, F143L and I211L) to the observed inhibition were studied by mutagenesis. An unusual synergy giving rise to high catalytic efficiency and reduced substrate inhibition was observed between residues L177W and I211L, which are located in different access tunnels of the protein. These results show that substrate inhibition can be caused by substrate binding to the enzyme-product complex and can be controlled rationally by targeted amino acid substitutions in enzyme access tunnels.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering

Computational prediction has become an indispensable aid in the processes of engineering and designing proteins for various biotechnological applications. With the tremendous progress in more powerful computer hardware and more efficient algorithms, some of in silico tools and methods have started to apply the more realistic description of proteins as their conformational ensembles, making protein dynamics an integral part of their prediction workflows. To help protein engineers to harness benefits of considering dynamics in their designs, we surveyed new tools developed for analyses of conformational ensembles in order to select engineering hotspots and design mutations. Next, we discussed the collective evolution towards more flexible protein design methods, including ensemble-based approaches, knowledge-assisted methods, and provable algorithms. Finally, we highlighted apparent challenges that current approaches are facing and provided our perspectives on their further development.

Fluorescent substrates for haloalkane dehalogenases: Novel probes for mechanistic studies and protein labeling

Haloalkane dehalogenases are enzymes that catalyze the cleavage of carbon-halogen bonds in halogenated compounds. They serve as model enzymes for studying structure-function relationships of >100.000 members of the α/β-hydrolase superfamily. Detailed kinetic analysis of their reaction is crucial for understanding the reaction mechanism and developing novel concepts in protein engineering. Fluorescent substrates, which change their fluorescence properties during a catalytic cycle, may serve as attractive molecular probes for studying the mechanism of enzyme catalysis. In this work, we present the development of the first fluorescent substrates for this enzyme family based on coumarin and BODIPY chromophores. Steady-state and pre-steady-state kinetics with two of the most active haloalkane dehalogenases, DmmA and LinB, revealed that both fluorescent substrates provided specificity constant two orders of magnitude higher (0.14-12.6 μM^-1 s^-1) than previously reported representative substrates for the haloalkane dehalogenase family (0.00005-0.014 μM^-1 s^-1). Stopped-flow fluorescence/FRET analysis enabled for the first time monitoring of all individual reaction steps within a single experiment: (i) substrate binding, (ii-iii) two subsequent chemical steps and (iv) product release. The newly introduced fluorescent molecules are potent probes for fast steady-state kinetic profiling. In combination with rapid mixing techniques, they provide highly valuable information about individual kinetic steps and mechanism of haloalkane dehalogenases. Additionally, these molecules offer high specificity and efficiency for protein labeling and can serve as probes for studying protein hydration and dynamics as well as potential markers for cell imaging.

The impact of tunnel mutations on enzymatic catalysis depends on the tunnel-substrate complementarity and the rate-limiting step

Transport of ligands between bulk solvent and the buried active sites is a critical event in the catalytic cycle of many enzymes. The rational design of transport pathways is far from trivial due to the lack of knowledge about the effect of mutations on ligand transport. The main and an auxiliary tunnel of haloalkane dehalogenase LinB have been previously engineered for improved dehalogenation of 1,2-dibromoethane (DBE). The first chemical step of DBE conversion was enhanced by L177W mutation in the main tunnel, but the rate-limiting product release was slowed down because the mutation blocked the main access tunnel and hindered protein dynamics. Three additional mutations W140A + F143L + I211L opened-up the auxiliary tunnel and enhanced the product release, making this four-point variant the most efficient catalyst with DBE. Here we study the impact of these mutations on the catalysis of bulky aromatic substrates, 4-(bromomethyl)-6,7-dimethoxycoumarin (COU) and 8-chloromethyl-4,4'-difluoro-3,5-dimethyl-4-bora-3a,4a-diaza-s-indacene (BDP). The rate-limiting step of DBE conversion is the product release, whereas the catalysis of COU and BDP is limited by the chemical step. The catalysis of COU is mainly impaired by the mutation L177W, whereas the conversion of BDP is affected primarily by the mutations W140A + F143L + I211L. The combined computational and kinetic analyses explain the differences in activities between the enzyme-substrate pairs. The effect of tunnel mutations on catalysis depends on the rate-limiting step, the complementarity of the tunnels with the substrates and is clearly specific for each enzyme-substrate pair.

Engineering enzyme access tunnels

Enzymes are efficient and specific catalysts for many essential reactions in biotechnological and pharmaceutical industries. Many times, the natural enzymes do not display the catalytic efficiency, stability or specificity required for these industrial processes. The current enzyme engineering methods offer solutions to this problem, but they mainly target the buried active site where the chemical reaction takes place. Despite being many times ignored, the tunnels and channels connecting the environment with the active site are equally important for the catalytic properties of enzymes. Changes in the enzymatic tunnels and channels affect enzyme activity, specificity, promiscuity, enantioselectivity and stability. This review provides an overview of the emerging field of enzyme access tunnel engineering with case studies describing design of all the aforementioned properties. The software tools for the analysis of geometry and function of the enzymatic tunnels and channels and for the rational design of tunnel modifications will also be discussed. The combination of new software tools and enzyme engineering strategies will provide enzymes with access tunnels and channels specifically tailored for individual industrial processes.