ix, 682 s. : il., tab.
- Keywords
- Klonování, Proteiny,
- MeSH
- Cloning, Molecular MeSH
- Molecular Biology MeSH
- Proteins MeSH
- Protein Binding physiology MeSH
- Publication type
- Laboratory Manual MeSH
- Conspectus
- Biochemie. Molekulární biologie. Biofyzika
- NML Fields
- molekulární biologie, molekulární medicína
Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.
Protein engineering strategies aimed at constructing enzymes with novel or improved activities, specificities, and stabilities greatly benefit from in silico methods. Computational methods can be principally grouped into three main categories: bioinformatics; molecular modelling; and de novo design. Particularly de novo protein design is experiencing rapid development, resulting in more robust and reliable predictions. A recent trend in the field is to combine several computational approaches in an interactive manner and to complement them with structural analysis and directed evolution. A detailed investigation of designed catalysts provides valuable information on the structural basis of molecular recognition, biochemical catalysis, and natural protein evolution.
- MeSH
- Enzymes genetics MeSH
- Humans MeSH
- Models, Molecular MeSH
- Mutation MeSH
- Protein Engineering methods MeSH
- Enzyme Stability MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.
- MeSH
- Point Mutation genetics physiology MeSH
- Databases, Genetic MeSH
- Lyases chemistry genetics metabolism MeSH
- Models, Molecular MeSH
- Computer Simulation MeSH
- Protein Engineering methods MeSH
- Enzyme Stability genetics MeSH
- Temperature MeSH
- Computational Biology methods MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
β-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-β-sheet proteins from first principles lags far behind the design of all-α or mixed-αβ domains owing to their non-local nature and the tendency of exposed β-strand edges to aggregate. Through study of loops connecting unpaired β-strands (β-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and β-strand length that arise from hydrogen bonding and packing constraints on regular β-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded β-helices formed by eight antiparallel β-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the β-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local β-sheet protein structures.
- MeSH
- Protein Conformation, beta-Strand MeSH
- Protein Conformation MeSH
- Models, Molecular MeSH
- Nuclear Magnetic Resonance, Biomolecular MeSH
- Computer Simulation MeSH
- Protein Engineering methods MeSH
- Proteins chemistry genetics MeSH
- Protein Folding MeSH
- Amino Acid Sequence MeSH
- Protein Stability MeSH
- Hydrogen Bonding MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- MeSH
- Allosteric Regulation * MeSH
- Allosteric Site * MeSH
- Benzodiazepines pharmacokinetics pharmacology MeSH
- Chemistry, Pharmaceutical MeSH
- Pharmacokinetics MeSH
- Calcimimetic Agents pharmacokinetics pharmacology MeSH
- Drug Delivery Systems MeSH
- Humans MeSH
- Neurotransmitter Agents pharmacokinetics pharmacology MeSH
- Drug Design MeSH
- Receptors, GABA-A * physiology MeSH
- Receptors, G-Protein-Coupled physiology MeSH
- Sirtuin 1 pharmacokinetics pharmacology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
HotSpot Wizard 2.0 is a web server for automated identification of hot spots and design of smart libraries for engineering proteins' stability, catalytic activity, substrate specificity and enantioselectivity. The server integrates sequence, structural and evolutionary information obtained from 3 databases and 20 computational tools. Users are guided through the processes of selecting hot spots using four different protein engineering strategies and optimizing the resulting library's size by narrowing down a set of substitutions at individual randomized positions. The only required input is a query protein structure. The results of the calculations are mapped onto the protein's structure and visualized with a JSmol applet. HotSpot Wizard lists annotated residues suitable for mutagenesis and can automatically design appropriate codons for each implemented strategy. Overall, HotSpot Wizard provides comprehensive annotations of protein structures and assists protein engineers with the rational design of site-specific mutations and focused libraries. It is freely available at http://loschmidt.chemi.muni.cz/hotspotwizard.
- MeSH
- Automation MeSH
- Biocatalysis MeSH
- Databases, Protein MeSH
- Internet * MeSH
- Evolution, Molecular MeSH
- Models, Molecular MeSH
- Mutation * MeSH
- Mutagenesis, Site-Directed methods MeSH
- Peptide Library * MeSH
- Proteins chemistry genetics MeSH
- Software * MeSH
- Protein Stability MeSH
- Amino Acid Substitution MeSH
- Substrate Specificity MeSH
- Publication type
- Journal Article MeSH
