The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families

Toll-like receptor 4 pathway evolutionary trajectory and functional emergence

Introduction

Toll-like receptors 4 (TLR4) recognize lipopolysaccharides (LPS) from bacteria as their conventional ligands and undergo downstream signaling to produce cytokines. They mediate the signaling either by the TIRAP-MyD88 complex or by the TRAM-TRIF complex. The MyD88 pathway is common to all other TLRs, whereas the TRAM-TRIF complex is largely exclusive to TLR4. Here we study the TIR domain of TRAM and TRIF ortholog proteins that are crucial for downstream signaling. Our previous work on pan-genome-wide survey, indicates Callorhincus milli to be the ancestral organism with both TRAM and TRIF proteins.

Methods

To gain a deeper insight into the protein function and to compare them with Homo sapiens adaptor proteins, we modeled the docking of the TRAM-TRIF complex of representative organisms across various taxa. These modeling experiments provide insights to ascertain a possible interaction surface and calculate the energetics and electrostatic potential of the complex. Furthermore, this enables us to employ normal mode analysis (NMA) to examine fluctuating, interacting, and other specific residue clusters that could have a role in protein functioning in both C. milli and H. sapiens. We also performed molecular dynamics simulations of these complexes and cross-validated the functionally important residues using network parameters.

Results

We compared the stoichiometry of TRAM-TRIF complexes and found that the tetrameric models (TRAM and TRIF dimer) were more stable than the trimeric model (TRAM dimer and TRIF monomer). While the critical residues of TIRAP, TRIF, and MyD88 were preserved, we also found that the important residues of TRAM signaling were not conserved in C. milli.

Discussion

This suggests the presence of functional TIRAP-MyD88-mediated TLR4 signaling and TRIF-mediated TLR3 signaling in the ancestral species. The overall biological function of this signaling domain appears to be gradually acquired through the orchestration of several motifs through an evolutionary scale.

Engineering an Ancestral Glycosyltransferase for Biosynthesis of 2-Phenylethyl-β-d-Glucopyranoside and Salidroside

Phenylethanoid glycosides (PhGs) are naturally occurring glycosides derived from plants with various biological activities. Glycosyltransferases catalyze the production of PhGs from phenylethanols via a transglycosylation reaction. The low activity and stability of glycosyltransferase limit its industrial application. An ancestral glycosyltransferase, UGTAn85, with heat resistance, alkali resistance, and high stability was resurrected using ancestral sequence reconstruction technology. This enzyme can efficiently convert phenylethanols to PhGs. The optimal reaction temperature and pH for UGTAn85 were found to be 70 °C and pH 10.0, respectively. This study employed a combination of structure-guided rational design and co-evolution analysis to enhance its catalytic activity. Potential mutation sites were identified through computer-aided design, including homology modeling, molecular docking, Rosetta dock design, molecular dynamics simulation, and co-evolution analysis. By targeted mutagenesis, the UGTAn85 mutant Q23E/N65D exhibited a 2.2-fold increase in enzyme activity (11.85 U/mg) and elevated affinity (Km = 0.11 mM) for 2-phenylethanol compared to UGTAn85. Following a fed-batch reaction, 36.16 g/L 2-phenylethyl-β-d-glucopyranoside and 51.49 g/L salidroside could be produced within 24 h, respectively. The findings in this study provide a new perspective on enhancing the stability and activity of glycosyltransferases, as well as a potential biocatalyst for the industrial production of PhGs.

Coevolutionary analysis reveals a distal amino acid residue pair affecting the catalytic activity of GH5 processive endoglucanase from Bacillus subtilis BS-5

EG5C-1, processive endoglucanase from Bacillus subtilis, is a typical bifunctional cellulase with endoglucanase and exoglucanase activities. The engineering of processive endoglucanase focuses on the catalytic pocket or carbohydrate-binding module tailoring based on sequence/structure information. Herein, a computational strategy was applied to identify the desired mutants in the enzyme molecule by evolutionary coupling analysis; subsequently, four residue pairs were selected as evolutionary mutational hotspots. Based on iterative-saturation mutagenesis and subsequent enzymatic activity analysis, a superior mutant K51T/L93T was identified away from the active center. This variant had increased specific activity from 4170 U/µmol of wild-type (WT) to 5678 U/µmol towards CMC-Na and an increase towards the substrate Avicel from 320 U/µmol in WT to 521 U/µmol. In addition, kinetic measurements suggested that superior mutant K51T/L93T had a high substrate affinity (K_m ) and a remarkable improvement in catalytic efficiency (k_cat /K_m ). Furthermore, molecular dynamics simulations revealed that the K51T/L93T mutation altered the spatial conformation at the active site cleft, enhancing the interaction frequency between active site residues and substrate, improving catalytic efficiency and substrate affinity. The current studies provided some perspectives on the effects of distal residue substitution, which might assist in the engineering of processive endoglucanase or other glycoside hydrolases. This article is protected by copyright. All rights reserved.

NLRexpress-A bundle of machine learning motif predictors-Reveals motif stability underlying plant Nod-like receptors diversity

Examination of a collection of over 80,000 Plant Nod-like receptors (NLRs) revealed an overwhelming sequence diversity underlying functional specificity of pathogen detection, signaling and cooperativity. The NLR canonical building blocks-CC/TIR/RPW8, NBS and LRR-contain, however, a number of conserved sequence motifs showing a significant degree of invariance amongst different NLR groups. To identify these motifs we developed NLRexpress-a bundle of 17 machine learning (ML)-based predictors, able to swiftly and precisely detect CC, TIR, NBS, and LRR motifs while minimizing computing time without accuracy losses-aimed as an instrument scalable for screening overall proteomes, transcriptomes or genomes for identifying integral NLRs and discriminating them against incomplete sequences lacking key motifs. These predictors were further used to screen a subset of ∼34,000 regular plant NLR sequences. Motifs were analyzed using unsupervised ML techniques to assess the structural correlations hidden underneath pattern variabilities. Both the NB-ARC switch domain which admittedly is the most conserved region of NLRs and the highly diverse LRR domain with its vastly variable lengths and repeat irregularities-show well-defined relations between motif subclasses, highlighting the importance of structural invariance in shaping NLR sequence diversity. The online NLRexpress webserver can be accessed at https://nlrexpress.biochim.ro.

Evolutionary coupling-inspired engineering of alcohol dehydrogenase reveals the influence of distant sites on its catalytic efficiency for stereospecific synthesis of chiral alcohols

Alcohol dehydrogenase (ADH) has attracted much attention due to its ability to catalyze the synthesis of important chiral alcohol pharmaceutical intermediates with high stereoselectivity. ADH protein engineering efforts have generally focused on reshaping the substrate-binding pocket. However, distant sites outside the pocket may also affect its activity, although the underlying molecular mechanism remains unclear. The current study aimed to apply evolutionary coupling-inspired engineering to the ADH CpRCR and to identify potential mutation sites. Through conservative analysis, phylogenic analysis and residues distribution analysis, the co-evolution hotspots Leu34 and Leu137 were confirmed to be highly evolved under the pressure of natural selection and to be possibly related to the catalytic function of the protein. Hence, Leu34 and Leu137, far away from the active center, were selected for mutation. The generated CpRCR-L34A and CpRCR-L137V variants showed high stereoselectivity and 1.24-7.81 fold increase in k cat /K m value compared with that of the wild type, when reacted with 8 aromatic ketones or β-ketoesters. Corresponding computational study implied that L34 and L137 may extend allosteric fluctuation in the protein structure from the distal mutational site to the active site. Moreover, the L34 and L137 mutations modified the pre-reaction state in multiple ways, in terms of position of the hydride with respect to the target carbonyl. These findings provide insights into the catalytic mechanism of the enzyme and facilitate its regulation from the perspective of the site interaction network.

Recent advances in user-friendly computational tools to engineer protein function

Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.

Mustguseal and Sister Web-Methods: A Practical Guide to Bioinformatic Analysis of Protein Superfamilies

Bioinformatic analysis of functionally diverse superfamilies can help to study the structure-function relationship in proteins, but represents a methodological challenge. The Mustguseal web-server can build large structure-guided sequence alignments of thousands of homologs that cover all currently available sequence variants within a common structural fold. The input to the method is a PDB code of the query protein, which represents the protein superfamily of interest. The collection and subsequent alignment of protein sequences and structures is fully automated and driven by the particular choice of parameters. Four integrated sister web-methods-the Zebra, pocketZebra, visualCMAT, and Yosshi-are available to further analyze the resulting superimposition and identify conserved, subfamily-specific, and co-evolving residues, as well as to classify and study disulfide bonds in protein superfamilies. The integration of these web-based bioinformatic tools provides an out-of-the-box easy-to-use solution, first of its kind, to study protein function and regulation and design improved enzyme variants for practical applications and selective ligands to modulate their functional properties. In this chapter, we provide a step-by-step protocol for a comprehensive bioinformatic analysis of a protein superfamily using a web-browser as the main tool and notes on selecting the appropriate values for the key algorithm parameters depending on your research objective. The web-servers are freely available to all users at https://biokinet.belozersky.msu.ru/m-platform with no login requirement.

Structural Insights into Carboxylic Polyester-Degrading Enzymes and Their Functional Depolymerizing Neighbors

Esters are organic compounds widely represented in cellular structures and metabolism, originated by the condensation of organic acids and alcohols. Esterification reactions are also used by chemical industries for the production of synthetic plastic polymers. Polyester plastics are an increasing source of environmental pollution due to their intrinsic stability and limited recycling efforts. Bioremediation of polyesters based on the use of specific microbial enzymes is an interesting alternative to the current methods for the valorization of used plastics. Microbial esterases are promising catalysts for the biodegradation of polyesters that can be engineered to improve their biochemical properties. In this work, we analyzed the structure-activity relationships in microbial esterases, with special focus on the recently described plastic-degrading enzymes isolated from marine microorganisms and their structural homologs. Our analysis, based on structure-alignment, molecular docking, coevolution of amino acids and surface electrostatics determined the specific characteristics of some polyester hydrolases that could be related with their efficiency in the degradation of aromatic polyesters, such as phthalates.

Catalytic and lectin domains in neuraminidase A from Streptococcus pneumoniae are capable of an intermolecular assembly: Implications for biofilm formation

Neuraminidase A from Streptococcus pneumoniae (NanA) is a cell wall-bound modular enzyme containing one lectin and one catalytic domain. Unlike homologous NanB and NanC expressed by the same bacterium, the two domains within one NanA molecule do not form a stable interaction and are spatially separated by a 16-amino acid-long flexible linker. In this work, the ability of NanA to form intermolecular assemblies was characterized using the methods of molecular modeling and bioinformatic analysis based on crystallographic data and by bringing together previously published experimental data. It was concluded that two catalytic domains, as well as one catalytic and one lectin domain, originating from two cell wall-bound NanA molecules, can interact through a previously uncharacterized interdomain interface to form complexes stabilized by a network of intermolecular hydrogen bonds and salt bridges. Supercomputer modeling strongly indicated that artocarpin, an earlier experimentally discovered inhibitor of the pneumococcal biofilm formation, is able to bind to a site located in the catalytic domain of one NanA entity and prevent its interaction with the lectin or catalytic domain of another NanA entity, thus directly precluding the generation of intermolecular assemblies. The revealed structural adaptation is discussed as one plausible mechanism of noncatalytic participation of this potentially key pathogenicity enzyme in pneumococcal biofilm formation.

Evolutionary coupling saturation mutagenesis: Coevolution-guided identification of distant sites influencing Bacillus naganoensis pullulanase activity

Pullulanases are well-known debranching enzymes hydrolyzing α-1,6-glycosidic linkages. To date, engineering of pullulanase is mainly focused on catalytic pocket or domain tailoring based on structure/sequence information. Saturation mutagenesis-involved directed evolution is, however, limited by the low number of mutational sites compatible with combinatorial libraries of feasible size. Using Bacillus naganoensis pullulanase as a target protein, here we introduce the 'evolutionary coupling saturation mutagenesis' (ECSM) approach: residue pair covariances are calculated to identify residues for saturation mutagenesis, focusing directed evolution on residue pairs playing important roles in natural evolution. Evolutionary coupling (EC) analysis identified seven residue pairs as evolutionary mutational hotspots. Subsequent saturation mutagenesis yielded variants with enhanced catalytic activity. The functional pairs apparently represent distant sites affecting enzyme activity.

A Single Mutation Increases the Thermostability and Activity of Aspergillus terreus Amine Transaminase

Enhancing the thermostability of (R)-selective amine transaminases (AT-ATA) will expand its application in the asymmetric synthesis of chiral amines. In this study, mutual information and coevolution networks of ATAs were analyzed by the Mutual Information Server to Infer Coevolution (MISTIC). Subsequently, the amino acids most likely to influence the stability and function of the protein were investigated by alanine scanning and saturation mutagenesis. Four stabilized mutants (L118T, L118A, L118I, and L118V) were successfully obtained. The best mutant, L118T, exhibited an improved thermal stability with a 3.7-fold enhancement in its half-life (t_1/2) at 40 °C and a 5.3 °C increase in T₅₀¹⁰ compared to the values for the wild-type protein. By the differential scanning fluorimetry (DSF) analysis, the best mutant, L118T, showed a melting temperature (T_m) of 46.4 °C, which corresponded to a 5.0 °C increase relative to the wild-type AT-ATA (41.4 °C). Furthermore, the most stable mutant L118T displayed the highest catalytic efficiency among the four stabilized mutants.

Acyltransferases as Tools for Polyketide Synthase Engineering

Polyketides belong to the most valuable natural products, including diverse bioactive compounds, such as antibiotics, anticancer drugs, antifungal agents, immunosuppressants and others. Their structures are assembled by polyketide synthases (PKSs). Modular PKSs are composed of modules, which involve sets of domains catalysing the stepwise polyketide biosynthesis. The acyltransferase (AT) domains and their “partners”, the acyl carrier proteins (ACPs), thereby play an essential role. The AT loads the building blocks onto the “substrate acceptor”, the ACP. Thus, the AT dictates which building blocks are incorporated into the polyketide structure. The precursor- and occasionally the ACP-specificity of the ATs differ across the polyketide pathways and therefore, the ATs contribute to the structural diversity within this group of complex natural products. Those features make the AT enzymes one of the most promising tools for manipulation of polyketide assembly lines and generation of new polyketide compounds. However, the AT-based PKS engineering is still not straightforward and thus, rational design of functional PKSs requires detailed understanding of the complex machineries. This review summarizes the attempts of PKS engineering by exploiting the AT attributes for the modification of polyketide structures. The article includes 253 references and covers the most relevant literature published until May 2018.