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

The programmed sequence-based oxygenase screening for polypropylene degradation

Enzymatic degradation of plastic is an effective means of plastic recycling and pollution control. However, the strong chemical inertness of polypropylene plastic (PP) severely impedes its oxidative cleavage, making it resistant to degradation. In this study, based on sequence screening of Hidden Markov Model (HMM), a dioxygenase (HIS1) was identified and characterized to be effective in PP oxidation. Various kinds of PP products, including plastic films, microplastics, and disposable water cups or bags, were HIS1-degraded with cracks and holes on the surface. The hydrophobic binding was the primary force driving oxidative degradation in the specific cavity of HIS1. The discovery of HIS1 achieved a zero breakthrough in PP biodegradation, providing a promising candidate for the selection and evolution of degrading enzymes.

Hydrolase mimic via second coordination sphere engineering in metal-organic frameworks for environmental remediation

Enzymes achieve high catalytic activity with their elaborate arrangements of amino acid residues in confined optimized spaces. Nevertheless, when exposed to complicated environmental implementation scenarios, including high acidity, organic solvent and high ionic strength, enzymes exhibit low operational stability and poor activity. Here, we report a metal-organic frameworks (MOFs)-based artificial enzyme system via second coordination sphere engineering to achieve high hydrolytic activity under mild conditions. Experiments and theoretical calculations reveal that amide cleavage catalyzed by MOFs follows two distinct catalytic mechanisms, Lewis acid- and hydrogen bonding-mediated hydrolytic processes. The hydrogen bond formed in the secondary coordination sphere exhibits 11-fold higher hydrolytic activity than the Lewis acidic zinc ions. The MOFs exhibit satisfactory degradation performance of toxins and high stability under extreme working conditions, including complicated fermentation broth and high ethanol environments, and display broad substrate specificity. These findings hold great promise for designing artificial enzymes for environmental remediation.

EnzyHTP Computational Directed Evolution with Adaptive Resource Allocation

Directed evolution facilitates enzyme engineering via iterative rounds of mutagenesis. Despite the wide applications of high-throughput screening, building "smart libraries" to effectively identify beneficial variants remains a major challenge in the community. Here, we developed a new computational directed evolution protocol based on EnzyHTP, a software that we have previously reported to automate enzyme modeling. To enhance the throughput efficiency, we implemented an adaptive resource allocation strategy that dynamically allocates different types of computing resources (e.g., GPU/CPU) based on the specific need of an enzyme modeling subtask in the workflow. We implemented the strategy as a Python library and tested the library using fluoroacetate dehalogenase as a model enzyme. The results show that compared to fixed resource allocation where both CPU and GPU are on-call for use during the entire workflow, applying adaptive resource allocation can save 87% CPU hours and 14% GPU hours. Furthermore, we constructed a computational directed evolution protocol under the framework of adaptive resource allocation. The workflow was tested against two rounds of mutational screening in the directed evolution experiments of Kemp eliminase (KE07) with a total of 184 mutants. Using folding stability and electrostatic stabilization energy as computational readout, we identified all four experimentally observed target variants. Enabled by the workflow, the entire computation task (i.e., 18.4 μs MD and 18,400 QM single-point calculations) completes in 3 days of wall-clock time using ∼30 GPUs and ∼1000 CPUs.

Computer-Aided Lipase Engineering for Improving Their Stability and Activity in the Food Industry: State of the Art

As some of the most widely used biocatalysts, lipases have exhibited extreme advantages in many processes, such as esterification, amidation, and transesterification reactions, which causes them to be widely used in food industrial production. However, natural lipases have drawbacks in terms of organic solvent resistance, thermostability, selectivity, etc., which limits some of their applications in the field of foods. In this systematic review, the application of lipases in various food processes was summarized. Moreover, the general structure of lipases is discussed in-depth, and the engineering strategies that can be used in lipase engineering are also summarized. The protocols of some classical methods are compared and discussed, which can provide some information about how to choose methods of lipase engineering. Thermostability engineering and solvent tolerance engineering are highlighted in this review, and the basic principles for improving thermostability and solvent tolerance are summarized. In the future, comput er-aided technology should be more emphasized in the investigation of the mechanisms of reactions catalyzed by lipases and guide the engineering of lipases. The engineering of lipase tunnels to improve the diffusion of substrates is also a promising prospect for further enhanced lipase activity and selectivity.

pyCaverDock: Python implementation of the popular tool for analysis of ligand transport with advanced caching and batch calculation support

SUMMARY

Access pathways in enzymes are crucial for the passage of substrates and products of catalysed reactions. The process can be studied by computational means with variable degrees of precision. Our in-house approximative method CaverDock provides a fast and easy way to set up and run ligand binding and unbinding calculations through protein tunnels and channels. Here we introduce pyCaverDock, a Python3 API designed to improve user experience with the tool and further facilitate the ligand transport analyses. The API enables users to simplify the steps needed to use CaverDock, from automatizing setup processes to designing screening pipelines.

AVAILABILITY AND IMPLEMENTATION

pyCaverDock API is implemented in Python 3 and is freely available with detailed documentation and practical examples at https://loschmidt.chemi.muni.cz/caverdock/.

Understanding Life at High Temperatures: Relationships of Molecular Channels in Enzymes of Methanogenic Archaea and Their Growth Temperatures

Analyses of protein structures have shown the existence of molecular channels in enzymes from Prokaryotes. Those molecular channels suggest a critical role of spatial voids in proteins, above all, in those enzymes functioning under high temperature. It is expected that these spaces within the protein structure are required to access the active site and to maximize availability and thermal stability of their substrates and cofactors. Interestingly, numerous substrates and cofactors have been reported to be highly temperature-sensitive biomolecules. Methanogens represent a singular phylogenetic group of Archaea that performs anaerobic respiration producing methane during growth. Methanogens inhabit a variety of environments including the full range of temperatures for the known living forms. Herein, we carry out a dimensional analysis of molecular tunnels in key enzymes of the methanogenic pathway from methanogenic Archaea growing optimally over a broad temperature range. We aim to determine whether the dimensions of the molecular tunnels are critical for those enzymes from thermophiles. Results showed that at increasing growth temperature the dimensions of molecular tunnels in the enzymes methyl-coenzyme M reductase and heterodisulfide reductase become increasingly restrictive and present strict limits at the highest growth temperatures, i.e., for hyperthermophilic methanogens. However, growth at lower temperature allows a wide dimensional range for the molecular spaces in these enzymes. This is in agreement with previous suggestions on a potential major role of molecular tunnels to maintain biomolecule stability and activity of some enzymes in microorganisms growing at high temperatures. These results contribute to better understand archaeal growth at high temperatures. Furthermore, an optimization of the dimensions of molecular tunnels would represent an important adaptation required to maintain the activity of key enzymes of the methanogenic pathway for those methanogens growing optimally at high temperatures.

Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis.