scholarly journals An Adaptive Geometric Search Algorithm for Macromolecular Scaffold Selection

2017 ◽  
Author(s):  
Tian Jiang ◽  
P. Douglas Renfrew ◽  
Kevin Drew ◽  
Noah Youngs ◽  
Glenn Butterfoss ◽  
...  
Keyword(s):  
Protein Design ◽  
Active Site ◽  
Metal Binding ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Side Chain ◽  
Enzyme Design ◽  
Hydrogen Binding ◽  
Performance Improvements ◽  
Geometric Search

AbstractA wide variety of protein and peptidomimetic design tasks require matching functional three-dimensional motifs to potential oligomeric scaffolds. Enzyme design, for example, aims to graft active-site patterns typically consisting of 3 to 15 residues onto new protein surfaces. Identifying suitable proteins capable of scaffolding such active-site engraftment requires costly searches to identify protein folds that can provide the correct positioning of side chains to host the desired active site. Other examples of biodesign tasks that require simpler fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications the speed and scaling of geometric search limits downstream design to small patterns. Here we present an adaptive algorithm to searching for side chain take-off angles compatible with an arbitrarily specified functional pattern that enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided but our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).

VESTA 3for three-dimensional visualization of crystal, volumetric and morphology data

2011 ◽  
Vol 44 (6) ◽  
pp. 1272-1276 ◽  
Author(s):  
Koichi Momma ◽  
Fujio Izumi
Keyword(s):  
Search Algorithm ◽  
Voronoi Tessellation ◽  
Three Dimensional ◽  
Structure Parameters ◽  
Volumetric Data ◽  
Complex Molecules ◽  
Visualization System ◽  
Performance Improvements ◽  
Significant Performance

VESTAis a three-dimensional visualization system for crystallographic studies and electronic state calculations. It has been upgraded to the latest version,VESTA 3, implementing new features including drawing the external morphology of crystals; superimposing multiple structural models, volumetric data and crystal faces; calculation of electron and nuclear densities from structure parameters; calculation of Patterson functions from structure parameters or volumetric data; integration of electron and nuclear densities by Voronoi tessellation; visualization of isosurfaces with multiple levels; determination of the best plane for selected atoms; an extended bond-search algorithm to enable more sophisticated searches in complex molecules and cage-like structures; undo and redo in graphical user interface operations; and significant performance improvements in rendering isosurfaces and calculating slices.

Transthyretin is a metallopeptidase with an inducible active site

2012 ◽  
Vol 443 (3) ◽  
pp. 769-778 ◽  
Author(s):  
Márcia A. Liz ◽  
Sérgio C. Leite ◽  
Luiz Juliano ◽  
Maria J. Saraiva ◽  
Ana M. Damas ◽  
...  
Keyword(s):  
Active Site ◽  
Three Dimensional ◽  
Point Mutations ◽  
Site Directed Mutagenesis ◽  
Side Chain ◽  
Metal Chelators ◽  
Serine Residue ◽  
General Base ◽  
Apolipoprotein A ◽  
Β Amyloid

TTR (transthyretin) was found recently to possess proteolytic competency besides its well-known transport capabilities. It was described as a cryptic serine peptidase cleaving multiple natural substrates (including β-amyloid and apolipoprotein A-I) involved in diseases such as Alzheimer's disease and atherosclerosis. In the present study, we aimed to elucidate the catalytic machinery of TTR. All attempts to identify a catalytic serine residue were unsuccessful. However, metal chelators abolished TTR activity. Proteolytic inhibition by EDTA or 1,10-phenanthroline could be reversed with Zn2+ and Mn2+. These observations, supported by analysis of three-dimensional structures of TTR complexed with Zn2+, led to the hypothesis that TTR is a metallopeptidase. Site-directed mutagenesis of selected amino acids unambiguously confirmed this hypothesis. The TTR active site is inducible and constituted via a protein rearrangement resulting in ~7% of proteolytically active TTR at pH 7.4. The side chain of His88 is shifted near His90 and Glu92 establishing a Zn2+-chelating pattern HXHXE not found previously in any metallopeptidase and only conserved in TTR of humans and some other primates. Point mutations of these three residues yielded proteins devoid of proteolytic activity. Glu72 was identified as the general base involved in activation of the catalytic water. Our results unveil TTR as a metallopeptidase and define its catalytic machinery.

scholarly journals Ensemble-based enzyme design can recapitulate the effects of laboratory directed evolution in silico

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Aron Broom ◽  
Rojo V. Rakotoharisoa ◽  
Michael C. Thompson ◽  
Niayesh Zarifi ◽  
Erin Nguyen ◽  
...  
Keyword(s):  
Directed Evolution ◽  
Protein Design ◽  
Active Site ◽  
Room Temperature ◽  
De Novo ◽  
Conformational Ensemble ◽  
Enzyme Design ◽  
X Ray ◽  
Conformational Ensembles ◽  
X Ray Crystallography

Abstract The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we use room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 146 M−1s−1). We observe that catalytic residues are increasingly rigidified, the active site becomes better pre-organized, and its entrance is widened. Based on these observations, we engineer HG4, an efficient biocatalyst (kcat/KM 103,000 M−1s−1) containing key first and second-shell mutations found during evolution. HG4 structures reveal that its active site is pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

scholarly journals Computational Tools Applied to Enzyme Design − a review

Biocatalysis ◽  
2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Fernando García-Guevara ◽  
Mayra Avelar ◽  
Marcela Ayala ◽  
Lorenzo Segovia
Keyword(s):  
Reaction Mechanism ◽  
Protein Design ◽  
Sequence Space ◽  
De Novo ◽  
Three Dimensional ◽  
Deep Understanding ◽  
Dimensional Structure ◽  
Enzyme Design ◽  
Computational Simulations ◽  
Computational Tools

AbstractThe protein design toolbox has been greatly improved by the addition of enzyme computational simulations. Not only do they warrant a more ambitious and thorough exploration of sequence space, but a much higher number of variants and protein-ligand systems can be analyzed in silico compared to experimental engineering methods. Modern computational tools are being used to redesign and also for de novo generation of enzymes. These approaches are contingent on a deep understanding of the reaction mechanism and the enzyme’s three-dimensional structure coordinates, but the wealth of information produced by these analyses leads to greatly improved or even totally new types of catalysis.

scholarly journals Evolution of an enzyme conformational ensemble guides design of an efficient biocatalyst

2020 ◽  
Author(s):  
Aron Broom ◽  
Rojo V. Rakotoharisoa ◽  
Michael C. Thompson ◽  
Niayesh Zarifi ◽  
Erin Nguyen ◽  
...  
Keyword(s):  
Directed Evolution ◽  
Protein Design ◽  
Active Site ◽  
Room Temperature ◽  
De Novo ◽  
Conformational Ensemble ◽  
Enzyme Design ◽  
X Ray ◽  
Conformational Ensembles ◽  
X Ray Crystallography

AbstractThe creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we used room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 160 M−1s−1). We observed that catalytic residues were increasingly rigidified, the active site became better pre-organized, and its entrance was widened. Based on these observations, we engineered HG4, an efficient biocatalyst (kcat/KM 120,000 M−1s−1) containing active-site mutations found during evolution but not distal ones. HG4 structures revealed that its active site was pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

scholarly journals Proteus software for physics-based protein design

2020 ◽  
Author(s):  
David Mignon ◽  
Karen Druart ◽  
Vaitea Opuu ◽  
Savvas Polydorides ◽  
Francesco Villa ◽  
...  
Keyword(s):  
Protein Design ◽  
Catalytic Efficiency ◽  
Trna Synthetase ◽  
Side Chain ◽  
Pdz Domains ◽  
Enzyme Design ◽  
Generalized Born ◽  
Binding Reaction ◽  
Unfolded State ◽  
Replica Exchange Monte Carlo

AbstractWe describe methods and software for physics-based protein design. The folded state energy combines molecular mechanics with Generalized Born solvent. Sequence and conformation space are sampled with Replica Exchange Monte Carlo, assuming one or a few fixed protein backbone structures and discrete side chain rotamers. Whole protein design and enzyme design are presented as illustrations. Full redesign of three PDZ domains was done using a simple, empirical, unfolded state model. Designed sequences were very similar to natural ones. Enzyme redesign exploited a powerful, adaptive, importance sampling approach that allows the design to directly target substrate binding, reaction rate, catalytic efficiency, or the specificity of these properties. Redesign of tyrosyl-tRNA synthetase stereospecificity is reported as an example.

Structures of c-di-GMP/cGAMP degrading phosphodiesterase VcEAL: identification of a novel conformational switch and its implication

2019 ◽  
Vol 476 (21) ◽  
pp. 3333-3353 ◽  
Author(s):  
Malti Yadav ◽  
Kamalendu Pal ◽  
Udayaditya Sen
Keyword(s):  
Active Site ◽  
Metal Binding ◽  
Metal Ion ◽  
Triosephosphate Isomerase ◽  
Catalytic Mechanism ◽  
Degradation Mechanism ◽  
Structural Basis ◽  
Conserved Residues ◽  
Phosphodiester Bond ◽  
Cyclic Dinucleotides

Cyclic dinucleotides (CDNs) have emerged as the central molecules that aid bacteria to adapt and thrive in changing environmental conditions. Therefore, tight regulation of intracellular CDN concentration by counteracting the action of dinucleotide cyclases and phosphodiesterases (PDEs) is critical. Here, we demonstrate that a putative stand-alone EAL domain PDE from Vibrio cholerae (VcEAL) is capable to degrade both the second messenger c-di-GMP and hybrid 3′3′-cyclic GMP–AMP (cGAMP). To unveil their degradation mechanism, we have determined high-resolution crystal structures of VcEAL with Ca2+, c-di-GMP-Ca2+, 5′-pGpG-Ca2+ and cGAMP-Ca2+, the latter provides the first structural basis of cGAMP hydrolysis. Structural studies reveal a typical triosephosphate isomerase barrel-fold with substrate c-di-GMP/cGAMP bound in an extended conformation. Highly conserved residues specifically bind the guanine base of c-di-GMP/cGAMP in the G2 site while the semi-conserved nature of residues at the G1 site could act as a specificity determinant. Two metal ions, co-ordinated with six stubbornly conserved residues and two non-bridging scissile phosphate oxygens of c-di-GMP/cGAMP, activate a water molecule for an in-line attack on the phosphodiester bond, supporting two-metal ion-based catalytic mechanism. PDE activity and biofilm assays of several prudently designed mutants collectively demonstrate that VcEAL active site is charge and size optimized. Intriguingly, in VcEAL-5′-pGpG-Ca2+ structure, β5–α5 loop adopts a novel conformation that along with conserved E131 creates a new metal-binding site. This novel conformation along with several subtle changes in the active site designate VcEAL-5′-pGpG-Ca2+ structure quite different from other 5′-pGpG bound structures reported earlier.

scholarly journals Synthesis of New Derivatives of BEDT-TTF: Installation of Alkyl, Ethynyl, and Metal-Binding Side Chains and Formation of Tris(BEDT-TTF) Systems

2021 ◽  
Vol 7 (8) ◽  
pp. 110
Author(s):  
Songjie Yang ◽  
Matteo Zecchini ◽  
Andrew Brooks ◽  
Sara Krivickas ◽  
Desiree Dalligos ◽  
...  
Keyword(s):  
Metal Binding ◽  
Tricarboxylic Acid ◽  
Metal Salts ◽  
Side Chain ◽  
Side Chains ◽  
Ethynyl Group ◽  
X Ray ◽  
Transition Metal Salts ◽  
Alkyl Side Chains ◽  
Derivatives Of

The syntheses of new BEDT-TTF derivatives are described. These comprise BEDT-TTF with one ethynyl group (HC≡C-), with two (n-heptyl) or four (n-butyl) alkyl side chains, with two trans acetal (-CH(OMe)2) groups, with two trans aminomethyl (-CH2NH2) groups, and with an iminodiacetate (-CH2N(CH2CO2−)2 side chain. Three transition metal salts have been prepared from the latter donor, and their magnetic properties are reported. Three tris-donor systems are reported bearing three BEDT-TTF derivatives with ester links to a core derived from benzene-1,3,5-tricarboxylic acid. The stereochemistry and molecular structure of the donors are discussed. X-ray crystal structures of two BEDT-TTF donors are reported: one with two CH(OMe)2 groups and with one a -CH2N(CH2CO2Me)2 side chain.

scholarly journals Structural and functional insights into esterase-mediated macrolide resistance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michał Zieliński ◽  
Jaeok Park ◽  
Barry Sleno ◽  
Albert M. Berghuis
Keyword(s):  
Active Site ◽  
Pathogenic Bacteria ◽  
Catalytic Mechanism ◽  
Three Dimensional ◽  
Resistance Mechanisms ◽  
Docking Studies ◽  
Macrolide Resistance ◽  
Flexible Docking ◽  
Sequence Identity ◽  
Substrate Spectrum

AbstractMacrolides are a class of antibiotics widely used in both medicine and agriculture. Unsurprisingly, as a consequence of their exensive usage a plethora of resistance mechanisms have been encountered in pathogenic bacteria. One of these resistance mechanisms entails the enzymatic cleavage of the macrolides’ macrolactone ring by erythromycin esterases (Eres). The most frequently identified Ere enzyme is EreA, which confers resistance to the majority of clinically used macrolides. Despite the role Eres play in macrolide resistance, research into this family enzymes has been sparse. Here, we report the first three-dimensional structures of an erythromycin esterase, EreC. EreC is an extremely close homologue of EreA, displaying more than 90% sequence identity. Two structures of this enzyme, in conjunction with in silico flexible docking studies and previously reported mutagenesis data allowed for the proposal of a detailed catalytic mechanism for the Ere family of enzymes, labeling them as metal-independent hydrolases. Also presented are substrate spectrum assays for different members of the Ere family. The results from these assays together with an examination of residue conservation for the macrolide binding site in Eres, suggests two distinct active site archetypes within the Ere enzyme family.

scholarly journals Machine learning differentiates enzymatic and non-enzymatic metals in proteins

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Feehan ◽  
Meghan W. Franklin ◽  
Joanna S. G. Slusky
Keyword(s):  
Machine Learning ◽  
Metal Binding ◽  
Binding Sites ◽  
Active Sites ◽  
De Novo ◽  
Enzyme Design ◽  
Metal Binding Sites ◽  
Ensemble Machine Learning ◽  
Machine Learning Model ◽  
Physicochemical Features

AbstractMetalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate between them. Yet distinguishing these two classes is critical for the identification of both native and designed enzymes. Because of similarities between catalytic and non-catalytic  metal binding sites, finding physicochemical features that distinguish these two types of metal sites can indicate aspects that are critical to enzyme function. In this work, we develop the largest structural dataset of enzymatic and non-enzymatic metalloprotein sites to date. We then use a decision-tree ensemble machine learning model to classify metals bound to proteins as enzymatic or non-enzymatic with 92.2% precision and 90.1% recall. Our model scores electrostatic and pocket lining features as more important than pocket volume, despite the fact that volume is the most quantitatively different feature between enzyme and non-enzymatic sites. Finally, we find our model has overall better performance in a side-to-side comparison against other methods that differentiate enzymatic from non-enzymatic sequences. We anticipate that our model’s ability to correctly identify which metal sites are responsible for enzymatic activity could enable identification of new enzymatic mechanisms and de novo enzyme design.

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