Mole 2.5 - Tool for Detection and Analysis of Macromolecular Pores and Channels

Large-scale annotation of biochemically relevant pockets and tunnels in cognate enzyme-ligand complexes

Tunnels in enzymes with buried active sites are key structural features allowing the entry of substrates and the release of products, thus contributing to the catalytic efficiency. Targeting the bottlenecks of protein tunnels is also a powerful protein engineering strategy. However, the identification of functional tunnels in multiple protein structures is a non-trivial task that can only be addressed computationally. We present a pipeline integrating automated structural analysis with an in-house machine-learning predictor for the annotation of protein pockets, followed by the calculation of the energetics of ligand transport via biochemically relevant tunnels. A thorough validation using eight distinct molecular systems revealed that CaverDock analysis of ligand un/binding is on par with time-consuming molecular dynamics simulations, but much faster. The optimized and validated pipeline was applied to annotate more than 17,000 cognate enzyme-ligand complexes. Analysis of ligand un/binding energetics indicates that the top priority tunnel has the most favourable energies in 75% of cases. Moreover, energy profiles of cognate ligands revealed that a simple geometry analysis can correctly identify tunnel bottlenecks only in 50% of cases. Our study provides essential information for the interpretation of results from tunnel calculation and energy profiling in mechanistic enzymology and protein engineering. We formulated several simple rules allowing identification of biochemically relevant tunnels based on the binding pockets, tunnel geometry, and ligand transport energy profiles.Scientific contributionsThe pipeline introduced in this work allows for the detailed analysis of a large set of protein-ligand complexes, focusing on transport pathways. We are introducing a novel predictor for determining the relevance of binding pockets for tunnel calculation. For the first time in the field, we present a high-throughput energetic analysis of ligand binding and unbinding, showing that approximate methods for these simulations can identify additional mutagenesis hotspots in enzymes compared to purely geometrical methods. The predictor is included in the supplementary material and can also be accessed at https://github.com/Faranehhad/Large-Scale-Pocket-Tunnel-Annotation.git . The tunnel data calculated in this study has been made publicly available as part of the ChannelsDB 2.0 database, accessible at https://channelsdb2.biodata.ceitec.cz/ .

Ribosome Tunnel Environment Drives the Formation of α-Helix during Cotranslational Folding

Protein conformations in cells are not solely determined by amino acid sequences; they also depend on cellular environments. For instance, the ribosome tunnel induces its specific α-helix formation during cotranslational folding. Owing to the link between these temporally α-helix and biological functions, the mechanism of α-helix formation inside the ribosome tunnel has been previously explored. Consequently, the conformational restrictions of the tunnel were considered one of the driving forces of α-helix formation. Conversely, the ribosomal tunnel environment, including its chemical properties, appears to influence the α-helix formation. However, a comprehensive analysis of the ribosome tunnel environment's impact on the α-helix formation has not been conducted yet due to challenges in experimentally controlling it. Therefore, as a new computational approach, we proposed a ribosome environment-mimicking model (REMM) based on the radius and components of the experimentally determined ribosome tunnel structures. Using REMM, we assessed the impact of the ribosome tunnel environment on α-helix formation. Herein, we employed carbon nanotubes (CNT) as a reference model alongside REMM because CNT reproduce conformational restrictions rather than the ribosome tunnel environment. Quantitatively, the ability to reproduce the α-helix of nascent peptides in the experimental structure was compared between the CNT and REMM using enhanced all-atom molecular dynamics simulations. Consequently, the REMM more accurately reproduced the α-helix of the nascent peptides than the CNT, highlighting the significance of the ribosome tunnel environment in α-helix formation. Additionally, we analyzed the properties of the peptide inside each model to reveal the mechanism of ribosome tunnel-specific α-helix formation. Consequently, we revealed that the chemical diversities of the tunnel are essential for the formation of backbone-to-backbone hydrogen bonds in the peptides. In conclusion, the ribosome tunnel environment, with the diverse chemical properties, drives its specific α-helix formation. By proposing REMM, we newly provide the technical basis for investigating the protein conformations in various cellular environments.

Reinforcing Tunnel Network Exploration in Proteins Using Gaussian Accelerated Molecular Dynamics

Tunnels are structural conduits in biomolecules responsible for transporting chemical compounds and solvent molecules from the active site. They have been shown to be present in a wide variety of enzymes across all functional and structural classes. However, the study of such pathways is experimentally challenging, because they are typically transient. Computational methods, such as molecular dynamics (MD) simulations, have been successfully proposed to explore tunnels. Conventional MD (cMD) provides structural details to characterize tunnels but suffers from sampling limitations to capture rare tunnel openings on longer time scales. Therefore, in this study, we explored the potential of Gaussian accelerated MD (GaMD) simulations to improve the exploration of complex tunnel networks in enzymes. We used the haloalkane dehalogenase LinB and its two variants with engineered transport pathways, which are not only well-known for their application potential but have also been extensively studied experimentally and computationally regarding their tunnel networks and their importance in multistep catalytic reactions. Our study demonstrates that GaMD efficiently improves tunnel sampling and allows the identification of all known tunnels for LinB and its two mutants. Furthermore, the improved sampling provided insight into a previously unknown transient side tunnel (ST). The extensive conformational landscape explored by GaMD simulations allowed us to investigate in detail the mechanism of ST opening. We determined variant-specific dynamic properties of ST opening, which were previously inaccessible due to limited sampling of cMD. Our comprehensive analysis supports multiple indicators of the functional relevance of the ST, emphasizing its potential significance beyond structural considerations. In conclusion, our research proves that the GaMD method can overcome the sampling limitations of cMD for the effective study of tunnels in enzymes, providing further means for identifying rare tunnels in enzymes with the potential for drug development, precision medicine, and rational protein engineering.

Targeted Mutagenesis of the Multicopy Myrosinase Gene Family in Allotetraploid Brassica juncea Reduces Pungency in Fresh Leaves across Environments

Recent breeding efforts in Brassica have focused on the development of new oilseed feedstock crop for biofuels (e.g., ethanol, biodiesel, bio-jet fuel), bio-industrial uses (e.g., bio-plastics, lubricants), specialty fatty acids (e.g., erucic acid), and producing low glucosinolates levels for oilseed and feed meal production for animal consumption. We identified a novel opportunity to enhance the availability of nutritious, fresh leafy greens for human consumption. Here, we demonstrated the efficacy of disarming the ‘mustard bomb’ reaction in reducing pungency upon the mastication of fresh tissue—a major source of unpleasant flavor and/or odor in leafy Brassica. Using gene-specific mutagenesis via CRISPR-Cas12a, we created knockouts of all functional copies of the type-I myrosinase multigene family in tetraploid Brassica juncea. Our greenhouse and field trials demonstrate, via sensory and biochemical analyses, a stable reduction in pungency in edited plants across multiple environments. Collectively, these efforts provide a compelling path toward boosting the human consumption of nutrient-dense, fresh, leafy green vegetables.