Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The influence of protein dynamics on the success of computational enzyme design.

ABSTRACT: We characterize the molecular dynamics of a previously described computational de novo designed enzyme optimized to perform a multistep retrol-aldol reaction when engineered into a TIM barrel protein scaffold. The molecular dynamics simulations show that the protein dynamics under physiological conditions of temperature and aqueous environment distorts the designed geometric factors of the substrate-enzyme reaction intermediates, such that catalysis is limited by the primary retrol-aldol step of proton abstraction from the covalently bound substrate and its interactions with a histidine-aspartate dyad. These results emphasize that computational enzyme designs will benefit from considerations of dynamical fluctuations when optimizing active site geometries.

SUBMITTER: Ruscio JZ

PROVIDER: S-EPMC2918245 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

The influence of protein dynamics on the success of computational enzyme design.

Ruscio Jory Z JZ Kohn Jonathan E JE Ball K Aurelia KA Head-Gordon Teresa T

Journal of the American Chemical Society 20091001 39

We characterize the molecular dynamics of a previously described computational de novo designed enzyme optimized to perform a multistep retrol-aldol reaction when engineered into a TIM barrel protein scaffold. The molecular dynamics simulations show that the protein dynamics under physiological conditions of temperature and aqueous environment distorts the designed geometric factors of the substrate-enzyme reaction intermediates, such that catalysis is limited by the primary retrol-aldol step of ...[more]

PMID: 19788332

Similar Datasets

Computational design of a protein-based enzyme inhibitor.

Project description:While there has been considerable progress in designing protein-protein interactions, the design of proteins that bind polar surfaces is an unmet challenge. We describe the computational design of a protein that binds the acidic active site of hen egg lysozyme and inhibits the enzyme. The design process starts with two polar amino acids that fit deep into the enzyme active site, identifies a protein scaffold that supports these residues and is complementary in shape to the lysozyme active-site region, and finally optimizes the surrounding contact surface for high-affinity binding. Following affinity maturation, a protein designed using this method bound lysozyme with low nanomolar affinity, and a combination of NMR studies, crystallography, and knockout mutagenesis confirmed the designed binding surface and orientation. Saturation mutagenesis with selection and deep sequencing demonstrated that specific designed interactions extending well beyond the centrally grafted polar residues are critical for high-affinity binding.

| S-EPMC3818146 | biostudies-literature

Enzyme-like proteins by computational design.

Project description:We report the development and initial experimental validation of a computational design procedure aimed at generating enzyme-like protein catalysts called "protozymes." Our design approach utilizes a "compute and build" strategy that is based on the physical/chemical principles governing protein stability and catalytic mechanism. By using the catalytically inert 108-residue Escherichia coli thioredoxin as a scaffold, the histidine-mediated nucleophilic hydrolysis of p-nitrophenyl acetate as a model reaction, and the ORBIT protein design software to compute sequences, an active site scan identified two promising catalytic positions and surrounding active-site mutations required for substrate binding. Experimentally, both candidate protozymes demonstrated catalytic activity significantly above background. One of the proteins, PZD2, displayed "burst" phase kinetics at high substrate concentrations, consistent with the formation of a stable enzyme intermediate. The kinetic parameters of PZD2 are comparable to early catalytic Abs. But, unlike catalytic Ab design, our design procedure is independent of fold, suggesting a possible mechanism for examining the relationships between protein fold and the evolvability of protein function.

| S-EPMC64672 | biostudies-literature

Iterative approach to computational enzyme design.

Project description:A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.

| S-EPMC3309769 | biostudies-literature

Computational protein design repurposed to explore enzyme vitality and help predict antibiotic resistance.

Project description:In response to antibiotics that inhibit a bacterial enzyme, resistance mutations inevitably arise. Predicting them ahead of time would aid target selection and drug design. The simplest resistance mechanism would be to reduce antibiotic binding without sacrificing too much substrate binding. The property that reflects this is the enzyme "vitality", defined here as the difference between the inhibitor and substrate binding free energies. To predict such mutations, we borrow methodology from computational protein design. We use a Monte Carlo exploration of mutation space and vitality changes, allowing us to rank thousands of mutations and identify ones that might provide resistance through the simple mechanism considered. As an illustration, we chose dihydrofolate reductase, an essential enzyme targeted by several antibiotics. We simulated its complexes with the inhibitor trimethoprim and the substrate dihydrofolate. 20 active site positions were mutated, or "redesigned" individually, then in pairs or quartets. We computed the resulting binding free energy and vitality changes. Out of seven known resistance mutations involving active site positions, five were correctly recovered. Ten positions exhibited mutations with significant predicted vitality gains. Direct couplings between designed positions were predicted to be small, which reduces the combinatorial complexity of the mutation space to be explored. It also suggests that over the course of evolution, resistance mutations involving several positions do not need the underlying point mutations to arise all at once: they can appear and become fixed one after the other.

| S-EPMC9868620 | biostudies-literature

Computational fluid dynamics simulate optimal design of segmental arteries reattachment: Influence of blood flow stagnation.

Project description:ObjectivesThis study aimed to simulate blood flow stagnation using computational fluid dynamics and to clarify the optimal design of segmental artery reattachment for thoracoabdominal aortic repair.MethodsBlood flow stagnation, defined by low-velocity volume or area of the segmental artery, was simulated by a 3-dimensional model emulating the systolic phase. Four groups were evaluated: direct anastomosis, graft interposition, loop-graft, and end graft. Based on contemporary clinical studies, direct anastomosis can provide a superior patency rate than other reattachment methods. We hypothesized that stagnation of the blood flow is negatively associated with patency rates. Over time, velocity changes were evaluated.ResultsThe direct anastomosis method led to the least blood flow stagnation, whilst the end-graft reattachment method resulted in worse blood flow stagnation. The loop-graft method was comparatively during late systole, which was also influenced by configuration of the side branch. Graft interposition using 20 mm showed a low-velocity area in the distal part of the side graft. When comparing length and diameter of an interposed graft, shorter and smaller branches resulted in less blood flow stagnation.ConclusionsIn our simulation, direct anastomosis of the segmental artery resulted in the most efficient design in terms of blood flow stagnation. A shorter (<20 mm) and smaller (<10 mm) branch should be used for graft interposition. Loop-graft is an attractive alternative to direct anastomosis; however, its blood flow pattern can be influenced.

| S-EPMC10556939 | biostudies-literature

Computational Fluid Dynamics data for improving freeze-dryers design.

Project description:Computational Fluid Dynamics (CFD) can be used to simulate different parts of an industrial freeze-drying equipment and to properly design them; in particular data concerning the freeze-dryer chamber and the duct connecting the chamber with the condenser, with the valves and vanes eventually present are given here, and can be used to understand the behavior of the apparatus allowing an improved design. Pilot and large scale freeze-drying chambers have been considered; data of a detailed simulation of a complete pilot scale apparatus, including duct and condenser, are included. Data on conductance of an empty duct with different L/D ratio, on disk valves with different geometry, and on mushroom valve are presented. Velocity, pressure, temperature and composition fields are reported on selected planes for chambers and valves. Results of dynamic simulations are also presented, to evaluate possible performance of monitoring devices in the chamber. Some further data, with detailed interpretation and discussion of the presented data can be found in the related research article by Barresi et al. [1] and Marchisio et al. [2].

| S-EPMC6140831 | biostudies-other

Incorporating Fast Protein Dynamics into Enzyme Design: A Proposed Mutant Aromatic Amine Dehydrogenase.

Project description:In recent years, there has been encouraging progress in the engineering of enzymes that are designed to catalyze reactions not accelerated by natural enzymes. We tested the possibility of reengineering an existing enzyme by introducing a fast protein motion that couples to the reaction. Aromatic amine dehydrogenase is a system that has been shown to use a fast substrate motion as part of the reaction mechanism. We identified a mutation that preserves this fast motion but also introduces a favorable fast motion near the active site that did not exist in the native enzyme. Transition path sampling was used for the analysis of the atomic details of the mechanism.

| S-EPMC5763476 | biostudies-literature

Enhancing computational enzyme design by a maximum entropy strategy.

Project description:Although computational enzyme design is of great importance, the advances utilizing physics-based approaches have been slow, and further progress is urgently needed. One promising direction is using machine learning, but such strategies have not been established as effective tools for predicting the catalytic power of enzymes. Here, we show that the statistical energy inferred from homologous sequences with the maximum entropy (MaxEnt) principle significantly correlates with enzyme catalysis and stability at the active site region and the more distant region, respectively. This finding decodes enzyme architecture and offers a connection between enzyme evolution and the physical chemistry of enzyme catalysis, and it deepens our understanding of the stability-activity trade-off hypothesis for enzymes. Overall, the strong correlations found here provide a powerful way of guiding enzyme design.

| S-EPMC8851541 | biostudies-literature

Combinatorial methods for small-molecule placement in computational enzyme design.

Project description:The incorporation of small-molecule transition state structures into protein design calculations poses special challenges because of the need to represent the added translational, rotational, and conformational freedoms within an already difficult optimization problem. Successful approaches to computational enzyme design have focused on catalytic side-chain contacts to guide placement of small molecules in active sites. We describe a process for modeling small molecules in enzyme design calculations that extends previously described methods, allowing favorable small-molecule positions and conformations to be explored simultaneously with sequence optimization. Because all current computational enzyme design methods rely heavily on sampling of possible active site geometries from discrete conformational states, we tested the effects of discretization parameters on calculation results. Rotational and translational step sizes as well as side-chain library types were varied in a series of computational tests designed to identify native-like binding contacts in three natural systems. We find that conformational parameters, especially the type of rotamer library used, significantly affect the ability of design calculations to recover native binding-site geometries. We describe the construction and use of a crystallographic conformer library and find that it more reliably captures active-site geometries than traditional rotamer libraries in the systems tested.

| S-EPMC1636520 | biostudies-literature

Alteration of enzyme specificity by computational loop remodeling and design.

Project description:Altering the specificity of an enzyme requires precise positioning of side-chain functional groups that interact with the modified groups of the new substrate. This requires not only sequence changes that introduce the new functional groups but also sequence changes that remodel the structure of the protein backbone so that the functional groups are properly positioned. We describe a computational design method for introducing specific enzyme-substrate interactions by directed remodeling of loops near the active site. Benchmark tests on 8 native protein-ligand complexes show that the method can recover native loop lengths and, often, native loop conformations. We then use the method to redesign a critical loop in human guanine deaminase such that a key side-chain interaction is made with the substrate ammelide. The redesigned enzyme is 100-fold more active on ammelide and 2.5e4-fold less active on guanine than wild-type enzyme: The net change in specificity is 2.5e6-fold. The structure of the designed protein was confirmed by X-ray crystallographic analysis: The remodeled loop adopts a conformation that is within 1-A Calpha RMSD of the computational model.

| S-EPMC2685249 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data