Modern computational tools can predict the mutational effects on protein stability, sometimes at the expense of activity or solubility. Here, we investigate two homologous computationally stabilized haloalkane dehalogenases: (i) the soluble thermostable DhaA115 (Tmapp = 74 °C) and (ii) the poorly soluble and aggregating thermostable LinB116 (Tmapp = 65 °C), together with their respective wild-type variants. The intriguing difference in the solubility of these highly homologous proteins has remained unexplained for three decades. We combined experimental and in-silico techniques and examined the effects of stabilization on solubility and aggregation propensity. A detailed analysis of the unfolding mechanisms in the context of aggregation explained the negative consequences of stabilization observed in LinB116. With the aid of molecular dynamics simulations, we identified regions exposed during the unfolding of LinB116 that were later found to exhibit aggregation propensity. Our analysis identified cryptic aggregation-prone regions and increased surface hydrophobicity as key factors contributing to the reduced solubility of LinB116. This study reveals novel molecular mechanisms of unfolding for hyperstabilized dehalogenases and highlights the importance of contextual information in protein engineering to avoid the negative effects of stabilizing mutations on protein solubility.

• MeSH
• hydrofobní a hydrofilní interakce MeSH
• hydrolasy * chemie   metabolismus   genetika   MeSH
• proteinové agregáty * MeSH
• rozbalení proteinů * MeSH
• rozpustnost MeSH
• simulace molekulární dynamiky MeSH
• stabilita proteinů MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• haloalkane dehalogenase MeSH Prohlížeč
• hydrolasy * MeSH
• proteinové agregáty * MeSH

Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.

• MeSH
• algoritmy MeSH
• internet * MeSH
• konformace proteinů MeSH
• neuronové sítě MeSH
• proteinové agregáty * MeSH
• proteinové inženýrství metody   MeSH
• proteiny chemie   genetika   MeSH
• rozpustnost MeSH
• sbalování proteinů MeSH
• software * MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• proteinové agregáty * MeSH
• proteiny MeSH

Thermostable proteins find their use in numerous biomedical and biotechnological applications. However, the computational design of stable proteins often results in single-point mutations with a limited effect on protein stability. However, the construction of stable multiple-point mutants can prove difficult due to the possibility of antagonistic effects between individual mutations. FireProt protocol enables the automated computational design of highly stable multiple-point mutants. FireProt 2.0 builds on top of the previously published FireProt web, retaining the original functionality and expanding it with several new stabilization strategies. FireProt 2.0 integrates the AlphaFold database and the homology modeling for structure prediction, enabling calculations starting from a sequence. Multiple-point designs are constructed using the Bron-Kerbosch algorithm minimizing the antagonistic effect between the individual mutations. Users can newly limit the FireProt calculation to a set of user-defined mutations, run a saturation mutagenesis of the whole protein or select rigidifying mutations based on B-factors. Evolution-based back-to-consensus strategy is complemented by ancestral sequence reconstruction. FireProt 2.0 is significantly faster and a reworked graphical user interface broadens the tool's availability even to users with older hardware. FireProt 2.0 is freely available at http://loschmidt.chemi.muni.cz/fireprotweb.

• Klíčová slova
• B-factor, ancestral, back-to-consensus, epistasis, evolution, force-field, multiple-point mutant, protein engineering, saturation mutagenesis, thermostability,
• MeSH
• algoritmy * MeSH
• internet MeSH
• mutace MeSH
• proteiny * genetika   chemie   MeSH
• stabilita proteinů MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• proteiny * MeSH

Thermostability is an essential requirement for the use of enzymes in the bioindustry. Here, we compare different protein stabilization strategies using a challenging target, a stable haloalkane dehalogenase DhaA115. We observe better performance of automated stabilization platforms FireProt and PROSS in designing multiple-point mutations over the introduction of disulfide bonds and strengthening the intra- and the inter-domain contacts by in silico saturation mutagenesis. We reveal that the performance of automated stabilization platforms was still compromised due to the introduction of some destabilizing mutations. Notably, we show that their prediction accuracy can be improved by applying manual curation or machine learning for the removal of potentially destabilizing mutations, yielding highly stable haloalkane dehalogenases with enhanced catalytic properties. A comparison of crystallographic structures revealed that current stabilization rounds were not accompanied by large backbone re-arrangements previously observed during the engineering stability of DhaA115. Stabilization was achieved by improving local contacts including protein-water interactions. Our study provides guidance for further improvement of automated structure-based computational tools for protein stabilization.

• Publikační typ
• časopisecké články MeSH

Haloalkane dehalogenase (HLD) enzymes employ an SN 2 nucleophilic substitution mechanism to erase halogen substituents in diverse organohalogen compounds. Subfamily I and II HLDs are well-characterized enzymes, but the mode and purpose of multimerization of subfamily III HLDs are unknown. Here we probe the structural organization of DhmeA, a subfamily III HLD-like enzyme from the archaeon Haloferax mediterranei, by combining cryo-electron microscopy (cryo-EM) and x-ray crystallography. We show that full-length wild-type DhmeA forms diverse quaternary structures, ranging from small oligomers to large supramolecular ring-like assemblies of various sizes and symmetries. We optimized sample preparation steps, enabling three-dimensional reconstructions of an oligomeric species by single-particle cryo-EM. Moreover, we engineered a crystallizable mutant (DhmeAΔGG ) that provided diffraction-quality crystals. The 3.3 Å crystal structure reveals that DhmeAΔGG forms a ring-like 20-mer structure with outer and inner diameter of ~200 and ~80 Å, respectively. An enzyme homodimer represents a basic repeating building unit of the crystallographic ring. Three assembly interfaces (dimerization, tetramerization, and multimerization) were identified to form the supramolecular ring that displays a negatively charged exterior, while its interior part harboring catalytic sites is positively charged. Localization and exposure of catalytic machineries suggest a possible processing of large negatively charged macromolecular substrates.

• Klíčová slova
• DhmeA, Haloferax mediterranei, catalysis, cryo-EM, haloalkane dehalogenase, multimerization, x-ray crystallography,
• MeSH
• elektronová kryomikroskopie metody   MeSH
• hydrolasy * chemie   MeSH
• krystalografie rentgenová MeSH
• substrátová specifita MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• haloalkane dehalogenase MeSH Prohlížeč
• hydrolasy * MeSH