scholarly journals Structure-based enzyme engineering improves donor-substrate recognition of Arabidopsis thaliana glycosyltransferases

2020 ◽  
Vol 477 (15) ◽  
pp. 2791-2805
Author(s):  
Aishat Akere ◽  
Serena H. Chen ◽  
Xiaohan Liu ◽  
Yanger Chen ◽  
Sarath Chandra Dantu ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Biochemical Characterization ◽  
Structural Information ◽  
Substrate Recognition ◽  
Industrial Applications ◽  
Enzyme Engineering ◽  
Donor Substrate ◽  
Substrate Preferences ◽  
Dynamics Simulations ◽  
Experimental Crystal

Glycosylation of secondary metabolites involves plant UDP-dependent glycosyltransferases (UGTs). UGTs have shown promise as catalysts in the synthesis of glycosides for medical treatment. However, limited understanding at the molecular level due to insufficient biochemical and structural information has hindered potential applications of most of these UGTs. In the absence of experimental crystal structures, we employed advanced molecular modeling and simulations in conjunction with biochemical characterization to design a workflow to study five Group H Arabidopsis thaliana (76E1, 76E2, 76E4, 76E5, 76D1) UGTs. Based on our rational structural manipulation and analysis, we identified key amino acids (P129 in 76D1; D374 in 76E2; K275 in 76E4), which when mutated improved donor substrate recognition than wildtype UGTs. Molecular dynamics simulations and deep learning analysis identified structural differences, which drive substrate preferences. The design of these UGTs with broader substrate specificity may play important role in biotechnological and industrial applications. These findings can also serve as basis to study other plant UGTs and thereby advancing UGT enzyme engineering.

scholarly journals Structural basis of substrate recognition and catalysis by fucosyltransferase 8

2020 ◽  
Author(s):  
Michael A. Järvå ◽  
Marija Dramicanin ◽  
James P. Lingford ◽  
Runyu Mao ◽  
Alan John ◽  
...  
Keyword(s):  
Substrate Binding ◽  
Structural Basis ◽  
Simple Modification ◽  
Acceptor Substrate ◽  
Guanosine Diphosphate ◽  
Antibody Therapeutics ◽  
Donor Substrate ◽  
Substrate Preferences ◽  
Dynamics Simulations ◽  
Core Fucosylation

AbstractFucosylation of the inner-most N-acetyl-glucosamine (GlcNAc) of N-glycans by fucosyltransferase 8 (FUT8) is an important step in the maturation of complex and hybrid N-glycans. This simple modification can have a dramatic impact on the activity and half-life of glycoproteins. These effects are relevant to understanding the invasiveness of some cancers, the development of monoclonal antibody therapeutics, and to a congenital disorder of glycosylation. The acceptor substrate preferences of FUT8 are well characterised and provide a framework for understanding N-glycan maturation in the Golgi, however the structural basis for these substrate preferences and the mechanism through which catalysis is achieved remains unknown. Here, we describe several structures of mouse and human FUT8 in the apo state and in complex with guanosine diphosphate (GDP), a mimic of the donor substrate, and a glycopeptide acceptor substrate. These structures provide insights into: a unique conformational change associated with donor substrate binding; common strategies employed by fucosyltransferases to coordinate GDP; features that define acceptor substrate preferences; and a likely mechanism for enzyme catalysis. Together with molecular dynamics simulations, the structures also reveal how FUT8 dimerisation plays an important role in defining the acceptor substrate binding site. Collectively, this information significantly builds on our understanding of the core-fucosylation process.

scholarly journals Structural basis of substrate recognition and catalysis by fucosyltransferase 8

2020 ◽  
Vol 295 (19) ◽  
pp. 6677-6688 ◽  
Author(s):  
Michael A. Järvå ◽  
Marija Dramicanin ◽  
James P. Lingford ◽  
Runyu Mao ◽  
Alan John ◽  
...  
Keyword(s):  
Enzyme Catalysis ◽  
Substrate Binding ◽  
Structural Basis ◽  
Simple Modification ◽  
Acceptor Substrate ◽  
The Core ◽  
Donor Substrate ◽  
Substrate Preferences ◽  
Dynamics Simulations ◽  
Core Fucosylation

Fucosylation of the innermost GlcNAc of N-glycans by fucosyltransferase 8 (FUT8) is an important step in the maturation of complex and hybrid N-glycans. This simple modification can dramatically affect the activities and half-lives of glycoproteins, effects that are relevant to understanding the invasiveness of some cancers, development of mAb therapeutics, and the etiology of a congenital glycosylation disorder. The acceptor substrate preferences of FUT8 are well-characterized and provide a framework for understanding N-glycan maturation in the Golgi; however, the structural basis of these substrate preferences and the mechanism through which catalysis is achieved remain unknown. Here we describe several structures of mouse and human FUT8 in the apo state and in complex with GDP, a mimic of the donor substrate, and with a glycopeptide acceptor substrate at 1.80–2.50 Å resolution. These structures provide insights into a unique conformational change associated with donor substrate binding, common strategies employed by fucosyltransferases to coordinate GDP, features that define acceptor substrate preferences, and a likely mechanism for enzyme catalysis. Together with molecular dynamics simulations, the structures also revealed how FUT8 dimerization plays an important role in defining the acceptor substrate-binding site. Collectively, this information significantly builds on our understanding of the core fucosylation process.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

2019 ◽  
Vol 25 (31) ◽  
pp. 3339-3349 ◽  
Author(s):  
Indrani Bera ◽  
Pavan V. Payghan
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Drug Target ◽  
Structural Information ◽  
Drug Binding ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Target Binding ◽  
Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

Enzyme engineering and its industrial applications

2021 ◽  
Author(s):  
Isabela Victorino da Silva Amatto ◽  
Nathalia Gonsales da Rosa‐Garzon ◽  
Flávio Antônio de Oliveira Simões ◽  
Fernanda Santiago ◽  
Nathália Pereira da Silva Leite ◽  
...  
Keyword(s):  
Industrial Applications ◽  
Enzyme Engineering

scholarly journals Two β-glucuronosyltransferases involved in the biosynthesis of type II arabinogalactans function in mucilage polysaccharide matrix organization in Arabidopsis thaliana

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Oyeyemi O. Ajayi ◽  
Michael A. Held ◽  
Allan M. Showalter
Keyword(s):  
Arabidopsis Thaliana ◽  
Seed Size ◽  
Seed Coat ◽  
Glucuronic Acid ◽  
Industrial Applications ◽  
Crystalline Cellulose ◽  
Sugar Residue ◽  
Composition Analysis ◽  
Cellulose Content ◽  
Type Ii

Abstract Background Arabinogalactan-proteins (AGPs) are heavily glycosylated with type II arabinogalactan (AG) polysaccharides attached to hydroxyproline residues in their protein backbone. Type II AGs are necessary for plant growth and critically important for the establishment of normal cellular functions. Despite the importance of type II AGs in plant development, our understanding of the underlying role of these glycans/sugar residues in mucilage formation and seed coat epidermal cell development is poorly understood and far from complete. One such sugar residue is the glucuronic acid residues of AGPs that are transferred onto AGP glycans by the action of β-glucuronosyltransferase genes/enzymes. Results Here, we have characterized two β-glucuronosyltransferase genes, GLCAT14A and GLCAT14C, that are involved in the transfer of β-glucuronic acid (GlcA) to type II AGs. Using a reverse genetics approach, we observed that glcat14a-1 mutants displayed subtle alterations in mucilage pectin homogalacturonan (HG) compared to wild type (WT), while glcat14a-1glcat14c-1 mutants displayed much more severe mucilage phenotypes, including loss of adherent mucilage and significant alterations in cellulose ray formation and seed coat morphology. Monosaccharide composition analysis showed significant alterations in the sugar amounts of glcat14a-1glcat14c-1 mutants relative to WT in the adherent and non-adherent seed mucilage. Also, a reduction in total mucilage content was observed in glcat14a-1glcat14c-1 mutants relative to WT. In addition, glcat14a-1glcat14c-1 mutants showed defects in pectin formation, calcium content and the degree of pectin methyl-esterification (DM) as well as reductions in crystalline cellulose content and seed size. Conclusions These results raise important questions regarding cell wall polymer interactions and organization during mucilage formation. We propose that the enzymatic activities of GLCAT14A and GLCAT14C play partially redundant roles and are required for the organization of the mucilage matrix and seed size in Arabidopsis thaliana. This work brings us a step closer towards identifying potential gene targets for engineering plant cell walls for industrial applications.

scholarly journals Molecular dynamics simulations and CD spectroscopy reveal hydration-induced unfolding of the intrinsically disordered LEA proteins COR15A and COR15B from Arabidopsis thaliana

2016 ◽  
Vol 18 (37) ◽  
pp. 25806-25816 ◽  
Author(s):  
Carlos Navarro-Retamal ◽  
Anne Bremer ◽  
Jans Alzate-Morales ◽  
Julio Caballero ◽  
Dirk K. Hincha ◽  
...  
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Arabidopsis Thaliana ◽  
Molecular Dynamics Simulations ◽  
Md Simulations ◽  
Cd Spectroscopy ◽  
Lea Proteins ◽  
Intrinsically Disordered ◽  
Dynamics Simulations ◽  
Crowded Environment

Unfolding of intrinsically unstructured full-length LEA proteins in a differentially crowded environment can be modeled by 30 ns MD simulations in accordance with experimental data.

scholarly journals Large-Scale Molecular Dynamics Simulations Reveal New Insights Into the Phase Transition Mechanisms in MIL-53(Al)

2021 ◽  
Vol 9 ◽  
Author(s):  
Sander Vandenhaute ◽  
Sven M. J. Rogge ◽  
Veronique Van Speybroeck
Keyword(s):  
Large Scale ◽  
Pressure Control ◽  
Layer By Layer ◽  
Major Step ◽  
Transition Mechanism ◽  
External Pressures ◽  
Pressure Regime ◽  
Dynamics Simulations ◽  
Experimental Crystal ◽  
External Stimuli

Soft porous crystals have the ability to undergo large structural transformations upon exposure to external stimuli while maintaining their long-range structural order, and the size of the crystal plays an important role in this flexible behavior. Computational modeling has the potential to unravel mechanistic details of these phase transitions, provided that the models are representative for experimental crystal sizes and allow for spatially disordered phenomena to occur. Here, we take a major step forward and enable simulations of metal-organic frameworks containing more than a million atoms. This is achieved by exploiting the massive parallelism of state-of-the-art GPUs using the OpenMM software package, for which we developed a new pressure control algorithm that allows for fully anisotropic unit cell fluctuations. As a proof of concept, we study the transition mechanism in MIL-53(Al) under various external pressures. In the lower pressure regime, a layer-by-layer mechanism is observed, while at higher pressures, the transition is initiated at discrete nucleation points and temporarily induces various domains in both the open and closed pore phases. The presented workflow opens the possibility to deduce transition mechanism diagrams for soft porous crystals in terms of the crystal size and the strength of the external stimulus.

scholarly journals Automated and optimally FRET-assisted structural modeling

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Mykola Dimura ◽  
Thomas-Otavio Peulen ◽  
Hugo Sanabria ◽  
Dmitro Rodnin ◽  
Katherina Hemmen ◽  
...  
Keyword(s):  
Open Source Software ◽  
Structural Information ◽  
Structural Modeling ◽  
Automated Design ◽  
Design Tool ◽  
Coarse Grained ◽  
Complex Dynamic ◽  
X Ray ◽  
Link Type ◽  
Dynamics Simulations

Abstract FRET experiments can provide state-specific structural information of complex dynamic biomolecular assemblies. However, to overcome the sparsity of FRET experiments, they need to be combined with computer simulations. We introduce a program suite with (i) an automated design tool for FRET experiments, which determines how many and which FRET pairs should be used to minimize the uncertainty and maximize the accuracy of an integrative structure, (ii) an efficient approach for FRET-assisted coarse-grained structural modeling, and all-atom molecular dynamics simulations-based refinement, and (iii) a quantitative quality estimate for judging the accuracy of FRET-derived structures as opposed to precision. We benchmark our tools against simulated and experimental data of proteins with multiple conformational states and demonstrate an accuracy of ~3 Å RMSDCα against X-ray structures for sets of 15 to 23 FRET pairs. Free and open-source software for the introduced workflow is available at https://github.com/Fluorescence-Tools. A web server for FRET-assisted structural modeling of proteins is available at http://nmsim.de.

scholarly journals Enlighten2: molecular dynamics simulations of protein–ligand systems made accessible

2020 ◽  
Vol 36 (20) ◽  
pp. 5104-5106
Author(s):  
Kirill Zinovjev ◽  
Marc W van der Kamp
Keyword(s):  
Molecular Dynamics ◽  
Expert Knowledge ◽  
Structural Data ◽  
Md Simulations ◽  
Enzyme Engineering ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Dynamics Simulations ◽  
User Friendly ◽  
Dynamical Information

Abstract Motivation Experimental structural data can allow detailed insight into protein structure and protein–ligand interactions, which is crucial for many areas of bioscience, including drug design and enzyme engineering. Typically, however, little more than a static picture of protein–ligand interactions is obtained, whereas dynamical information is often required for deeper understanding and to assess the effect of mutations. Molecular dynamics (MD) simulations can provide such information, but setting up and running these simulations is not straightforward and requires expert knowledge. There is thus a need for a tool that makes protein–ligand simulation easily accessible to non-expert users. Results We present Enlighten2: efficient simulation protocols for protein–ligand systems alongside a user-friendly plugin to the popular visualization program PyMOL. With Enlighten2, non-expert users can straightforwardly run and visualize MD simulations on protein–ligand models of interest. There is no need to learn new programs and all underlying tools are free and open source. Availability and implementation The Enlighten2 Python package and PyMOL plugin are free to use under the GPL3.0 licence and can be found at https://enlighten2.github.io. We also provide a lightweight Docker image via DockerHub that includes Enlighten2 with all the required utilities.

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