Tunnel engineering of gas-converting enzymes for inhibitor retardation and substrate acceleration

Carbon monoxide dehydrogenase (CODH), formate dehydrogenase (FDH), hydrogenase (H2ase), and nitrogenase (N2ase) are crucial enzymatic catalysts that facilitate the conversion of industrially significant gases such as CO, CO2, H2, and N2. The tunnels in the gas-converting enzymes serve as conduits for these low molecular weight gases to access deeply buried catalytic sites. The identification of the substrate tunnels is imperative for comprehending the substrate selectivity mechanism underlying these gas-converting enzymes. This knowledge also holds substantial value for industrial applications, particularly in addressing the challenges associated with separation and utilization of byproduct gases. In this comprehensive review, we delve into the emerging field of tunnel engineering, presenting a range of approaches and analyses. Additionally, we propose methodologies for the systematic design of enzymes, with the ultimate goal of advancing protein engineering strategies.

Genome-Wide Identification, Characterization and Expression Profiling of Potato (Solanum tuberosum) Frataxin (FH) Gene

Frataxin (FH) plays a crucial role in the biogenesis of mitochondria and the regulation of iron in the cells of various organisms. However, there has been very little research on FH in plants. In this study, the potato FH gene (StFH) was identified and characterized using a genome-wide approach, and its sequence was compared to those of FH genes from Arabidopsis, rice, and maize. The FH genes were found to have a lineage-specific distribution and were more conserved in monocots than in dicots. While multiple copies of FH genes have been reported in some species, including plants, only one isoform of FH was found in potato. The expression of StFH in leaves and roots was analyzed under two different abiotic stress conditions, and the results showed that StFH was upregulated more in leaves and that its expression levels increased with the severity of the stress. This is the first study to examine the expression of an FH gene under abiotic stress conditions.

A Method for Assessing the Robustness of Protein Structures by Randomizing Packing Interactions

Many single-domain proteins are not only stable and water-soluble, but they also populate few to no intermediates during folding. This reduces interactions between partially folded proteins, misfolding, and aggregation, and makes the proteins tractable in biotechnological applications. Natural proteins fold thus, not necessarily only because their structures are well-suited for folding, but because their sequences optimize packing and fit their structures well. In contrast, folding experiments on the de novo designed Top7 suggest that it populates several intermediates. Additionally, in de novo protein design, where sequences are designed for natural and new non-natural structures, tens of sequences still need to be tested before success is achieved. Both these issues may be caused by the specific scaffolds used in design, i.e., some protein scaffolds may be more tolerant to packing perturbations and varied sequences. Here, we report a computational method for assessing the response of protein structures to packing perturbations. We then benchmark this method using designed proteins and find that it can identify scaffolds whose folding gets disrupted upon perturbing packing, leading to the population of intermediates. The method can also isolate regions of both natural and designed scaffolds that are sensitive to such perturbations and identify contacts which when present can rescue folding. Overall, this method can be used to identify protein scaffolds that are more amenable to whole protein design as well as to identify protein regions which are sensitive to perturbations and where further mutations should be avoided during protein engineering.

A biomimetic metal–organic framework with cuboid inner cavities for enantioselective separation

A biomimetic metal–organic framework with cuboid inner cavities and multiple recognition sites was constructed from a phenylalanine-derived ligand. It can enantioselectively separate various racemic alcohols, diols and epoxides with ee up to 99.5%.

Molecular dynamics: a powerful tool for studying the medicinal chemistry of ion channel modulators

Molecular dynamics (MD) simulations allow researchers to investigate the behavior of desired biological targets at ever-decreasing costs with ever-increasing precision. Among the biological macromolecules, ion channels are remarkable transmembrane proteins, capable of performing special biological processes and revealing a complex regulatory matrix, including modulation by small molecules, either endogenous or exogenous. Recently, given the developments in ion channel structure determination and accessibility of bio-computational techniques, MD and related tools are becoming increasingly popular in the intense research area regarding ligand-channel interactions. This review synthesizes and presents the most important fields of MD involvement in investigating channel-molecule interactions, including, but not limited to, deciphering the binding modes of ligands to their ion channel targets and the mechanisms through which chemical compounds exert their effect on channel function. Special attention is devoted to the importance of more elaborate methods, such as free energy calculations, while principles regarding drug design and discovery are highlighted. Several technical aspects involving the creation and simulation of channel-molecule MD systems (ligand parameterization, proper membrane setup, system building, etc.) are also presented.

ProPores2: Web Service and Stand-Alone Tool for Identifying, Manipulating, and Visualizing Pores in Protein Structures

Surface pockets, cavities, and tunnels in the 3D structures of proteins play integral functional roles such as enabling enzymatic catalysis, ligand binding, or transport of ions or small molecules across biomembranes. ProPores2 facilitates understanding and analysis of these processes by identifying pores and lining residues, determining their axes, and opening closed connections via side-chain rotation. The fast stand-alone tool introduces a novel mode for pore identification, improved axis determination, and additional features such as parallel batch processing and a graphical user interface. The new web service features an integrated and customizable protein viewer with an option to analyze and view more than one structure at once. This feature facilitates side-by-side comparisons of pores in different conformations of the same protein or of identified pores before and after opening gates within the same protein. ProPores2 is freely and publicly available at https://service.bioinformatik.uni-saarland.de/propores.

Tunnel engineering for modulating the substrate preference in cytochrome P450BsβHI

An active site is normally located inside enzymes, hence substrates should go through a tunnel to access the active site. Tunnel engineering is a powerful strategy for refining the catalytic properties of enzymes. Here, P450BsβHI (Q85H/V170I) derived from hydroxylase P450Bsβ from Bacillus subtilis was chosen as the study model, which is reported as a potential decarboxylase. However, this enzyme showed low decarboxylase activity towards long-chain fatty acids. Here, a tunnel engineering campaign was performed for modulating the substrate preference and improving the decarboxylation activity of P450BsβHI. The finally obtained BsβHI-F79A variant had a 15.2-fold improved conversion for palmitic acid; BsβHI-F173V variant had a 3.9-fold improved conversion for pentadecanoic acid. The study demonstrates how the substrate preference can be modulated by tunnel engineering strategy.

Properties of Cavities in Biological Structures-A Survey of the Protein Data Bank

We performed a PDB-wide survey of proteins to assess their cavity content, using the SPACEBALL algorithm to calculate the cavity volumes. In addition, we determined the hydropathy character of the cavities. We demonstrate that the cavities of most proteins are hydrophilic, but smaller proteins tend to have cavities with hydrophobic walls. We propose criteria for distinguishing between cavities and pockets, and single out proteins with the largest cavities.

Comparative Dynamics and Functional Mechanisms of the CYP17A1 Tunnels Regulated by Ligand Binding

As an important member of cytochrome P450 (CYP) enzymes, CYP17A1 is a dual-function monooxygenase with a critical role in the synthesis of many human steroid hormones, making it an attractive therapeutic target. The emerging structural information about CYP17A1 and the growing number of inhibitors for these enzymes call for a systematic strategy to delineate and classify mechanisms of ligand transport through tunnels that control catalytic activity. In this work, we applied an integrated computational strategy to different CYP17A1 systems with a panel of ligands to systematically study at the atomic level the mechanism of ligand-binding and tunneling dynamics. Atomistic simulations and binding free energy computations identify the dynamics of dominant tunnels and characterize energetic properties of critical residues responsible for ligand binding. The common transporting pathways including S, 3, and 2c tunnels were identified in CYP17A1 binding systems, while the 2c tunnel is a newly formed pathway upon ligand binding. We employed and integrated several computational approaches including the analysis of functional motions and sequence conservation, atomistic modeling of dynamic residue interaction networks, and perturbation response scanning analysis to dissect ligand tunneling mechanisms. The results revealed the hinge-binding and sliding motions as main functional modes of the tunnel dynamic, and a group of mediating residues as key regulators of tunnel conformational dynamics and allosteric communications. We have also examined and quantified the mutational effects on the tunnel composition, conformational dynamics, and long-range allosteric behavior. The results of this investigation are fully consistent with the experimental data, providing novel rationale to the experiments and offering valuable insights into the relationships between the structure and function of the channel networks and a robust atomistic model of activation mechanisms and allosteric interactions in CYP enzymes.

Applications of water molecules for analysis of macromolecule properties

Water molecules maintain proteins' structures, functions, stabilities and dynamics. They can occupy certain positions or pass quickly via a protein's interior. Regardless of their behaviour, water molecules can be used for the analysis of proteins' structural features and biochemical properties. Here, we present a list of several software programs that use the information provided by water molecules to: i) analyse protein structures and provide the optimal positions of water molecules for protein hydration, ii) identify high-occupancy water sites in order to analyse ligand binding modes, and iii) detect and describe tunnels and cavities. The analysis of water molecules' distribution and trajectories sheds a light on proteins' interactions with small molecules, on the dynamics of tunnels and cavities, on protein composition and also on the functionality, transportation network and location of functionally relevant residues. Finally, the correct placement of water molecules in protein crystal structures can significantly improve the reliability of molecular dynamics simulations.

Voronoi-based detection of pockets in proteins defined by large and small probes

The function of enzymatic proteins is given by their ability to bind specific small molecules into their active sites. These sites can often be found in pockets on a hypothetical boundary between the protein and its environment. Detection, analysis, and visualization of pockets find its use in protein engineering and drug discovery. Many definitions of pockets and algorithms for their computation have been proposed. Kawabata and Go defined them as the regions of empty space into which a small spherical probe can enter but a large probe cannot and developed programs that can compute their approximate shape. In this article, this definition was slightly modified in order to capture the existence of large internal holes, and a Voronoi-based method for the computation of the exact shape of these modified regions is introduced. The method first puts a finite number of large probes on the protein exterior surface and then, considering both large probes and atomic balls as obstacles for the small probe, the method computes the exact shape of the regions for the small probe. This is all achieved with Voronoi diagrams, which help with the safe navigation of spherical probes among spherical obstacles. Detected regions are internally represented as graphs of vertices and edges describing possible movements of the center of the small probe on Voronoi edges. The surface bounding each region is obtained from this representation and used for visualization, volume estimation, and comparison with other approaches. © 2019 Wiley Periodicals, Inc.

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.

Four Major Channels Detected in the Cytochrome P450 3A4: A Step toward Understanding Its Multispecificity

We computed the network of channels of the 3A4 isoform of the cytochrome P450 (CYP) on the basis of 16 crystal structures extracted from the Protein Data Bank (PDB). The calculations were performed with version 2 of the CCCPP software that we developed for this research project. We identified the minimal cost paths (MCPs) output by CCCPP as probable ways to access to the buried active site. The algorithm of calculation of the MCPs is presented in this paper, with its original method of visualization of the channels. We found that these MCPs constitute four major channels in CYP3A4. Among the many channels proposed by Cojocaru et al. in 2007, we found that only four of them open in 3A4. We provide a refined description of these channels together with associated quantitative data.

Ligand Access Channels in Cytochrome P450 Enzymes: A Review

Quantitative structure-activity relationships may bring invaluable information on structural elements of both enzymes and substrates that, together, govern substrate specificity. Buried active sites in cytochrome P450 enzymes are connected to the solvent by a network of channels exiting at the distal surface of the protein. This review presents different in silico tools that were developed to uncover such channels in P450 crystal structures. It also lists some of the experimental evidence that actually suggest that these predicted channels might indeed play a critical role in modulating P450 functions. Amino acid residues at the entrance of the channels may participate to a first global ligand recognition of ligands by P450 enzymes before they reach the buried active site. Moreover, different P450 enzymes show different networks of predicted channels. The plasticity of P450 structures is also important to take into account when looking at how channels might play their role.

Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey

Detecting and analyzing protein cavities provides significant information about active sites for biological processes (e.g., protein-protein or protein-ligand binding) in molecular graphics and modeling. Using the three-dimensional structure of a given protein (i.e., atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels, and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution-based, energy-based, and geometry-based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere-, grid-, and tessellation-based methods, but also surface-based, hybrid geometric, consensus, and time-varying methods. Finally, we detail those techniques that have been customized for GPU (Graphics Processing Unit) computing.

Statistical Profiling of One Promiscuous Protein Binding Site: Illustrated by Urokinase Catalytic Domain

While recent literature focuses on drug promiscuity, the characterization of promiscuous binding sites (ability to bind several ligands) remains to be explored. Here, we present a proteochemometric modeling approach to analyze diverse ligands and corresponding multiple binding sub-pockets associated with one promiscuous binding site to characterize protein-ligand recognition. We analyze both geometrical and physicochemical profile correspondences. This approach was applied to examine the well-studied druggable urokinase catalytic domain inhibitor binding site, which results in a large number of complex structures bound to various ligands. This approach emphasizes the importance of jointly characterizing pocket and ligand spaces to explore the impact of ligand diversity on sub-pocket properties and to establish their main profile correspondences. This work supports an interest in mining available 3D holo structures associated with a promiscuous binding site to explore its main protein-ligand recognition tendency.

The Cytochrome P450 3A4 has three Major Conformations: New Clues to Drug Recognition by this Promiscuous Enzyme

We computed the channels of the 3A4 isoform of the cytochrome P450 3A4 (CYP) on the basis of 24 crystal structures extracted from the Protein Data Bank (PDB). We identified three major conformations (denoted C, O1 and O2) using an enhanced version of the CCCPP software that we developed for the present work, while only two conformations (C and O² ) are considered in the literature. We established the flowchart of definition of these three conformations in function of the structural and physicochemical parameters of the ligand. The channels are characterized with qualitative and quantitative parameters, and not only with their surrounding secondary structures as it is usually done in the literature.

Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets

We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9).

Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification

Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket-based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket-estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket-estimation methods on the results of pocket-based approaches. We focused on the effect of three pocket-estimation methods on a pocket-ligand (PL) classification. This pocket-based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket-estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket-estimation method choice in pocket-based approaches.

A Fast Algorithm to Compute Conical Pockets in Proteins. Application to the Structural Characterization of γ-Carbonic Anhydrases

Some major proteins families, such as carbonic anhydrases (CAs), have a conical cavity at the active site. No algorithm was available to compute conical cavities, so we needed to design one. The fast algorithm we designed let us show on a set of 717 CAs extracted from the PDB database that γ-CAs are characterized by active site cavity cone angles significantly larger than those of α-CAs and β-CAs: the generatrix-axis angles are greater than 60° for the γ-CAs while they are smaller than 50° for the other CAs. Free binaries of the CONICA software implementing the algorithm are available through a software repository at http://petitjeanmichel.free.fr/itoweb.petitjean.freeware.html.

Global vision of druggability issues: applications and perspectives

During the preliminary stage of a drug discovery project, the lack of druggability information and poor target selection are the main causes of frequent failures. Elaborating on accurate computational druggability prediction methods is a requirement for prioritizing target selection, designing new drugs and avoiding side effects. In this review, we describe a survey of recently reported druggability prediction methods mainly based on networks, statistical pocket druggability predictions and virtual screening. An application for a frequent mutation of p53 tumor suppressor is presented, illustrating the complementarity of druggability prediction approaches, the remaining challenges and potential new drug development perspectives.

MAP_CHANNELS: a computation tool to aid in the visualization and characterization of solvent channels in macromolecular crystals

A computation tool is described that facilitates visualization and characterization of solvent channels or pores within macromolecular crystals. A scalar field mapping the shortest distance to protein surfaces is calculated on a grid covering the unit cell and is written as a map file. The map provides a multiscale representation of the solvent channels, which when viewed in standard macromolecular crystallographic software packages gives an intuitive sense of the solvent channel architecture. The map is analysed to yield descriptors of the topology and the morphology of the solvent channels, including bottleneck radii, tortuosity, width variation and anisotropy.

Principal Component Analysis reveals correlation of cavities evolution and functional motions in proteins

Protein conformation has been recognized as the key feature determining biological function, as it determines the position of the essential groups specifically interacting with substrates. Hence, the shape of the cavities or grooves at the protein surface appears to drive those functions. However, only a few studies describe the geometrical evolution of protein cavities during molecular dynamics simulations (MD), usually with a crude representation. To unveil the dynamics of cavity geometry evolution, we developed an approach combining cavity detection and Principal Component Analysis (PCA). This approach was applied to four systems subjected to MD (lysozyme, sperm whale myoglobin, Dengue envelope protein and EF-CaM complex). PCA on cavities allows us to perform efficient analysis and classification of the geometry diversity explored by a cavity. Additionally, it reveals correlations between the evolutions of the cavities and structures, and can even suggest how to modify the protein conformation to induce a given cavity geometry. It also helps to perform fast and consensual clustering of conformations according to cavity geometry. Finally, using this approach, we show that both carbon monoxide (CO) location and transfer among the different xenon sites of myoglobin are correlated with few cavity evolution modes of high amplitude. This correlation illustrates the link between ligand diffusion and the dynamic network of internal cavities.