Discovery and mechanism of a pH-dependent dual-binding-site switch in the interaction of a pair of protein modules

Dissecting the pH Sensitivity of Kinesin-Driven Transport

Kinesin-1 is a crucial motor protein that drives the microtubule-based movement of organelles, vital for cellular function and health. Mostly studied at pH 6.9, it moves at approximately 800 nm/s, covers about 1 μm before detaching, and hydrolyzes one ATP per 8 nm step. Given that cellular pH is dynamic and alterations in pH have significant implications for disease, understanding how kinesin-1 functions across different pH levels is crucial. To explore this, we executed single-molecule motility assays paired with precise optical trapping techniques over a pH range of 5.5-9.8. Our results show a consistent positive relationship between increasing pH and the enhanced detachment (off rate) and speed of kinesin-1. Measurements of the nucleotide-dependent off rate show that kinesin-1 exhibits the highest rate of ATPase activity at alkaline pH, while it demonstrates the optimal number of ATP turnover and cargo translocation efficiency at the acidic pH. Physiological pH of 6.9 optimally balances the biophysical activity of kinesin-1, potentially allowing it to function effectively across a range of pH levels. These insights emphasize the crucial role of pH homeostasis in cellular function, highlighting its importance for the precise regulation of motor proteins and efficient intracellular transport.

PPI3D: a web server for searching, analyzing and modeling protein-protein, protein-peptide and protein-nucleic acid interactions

Structure-resolved protein interactions with other proteins, peptides and nucleic acids are key for understanding molecular mechanisms. The PPI3D web server enables researchers to query preprocessed and clustered structural data, analyze the results and make homology-based inferences for protein interactions. PPI3D offers three interaction exploration modes: (i) all interactions for proteins homologous to the query, (ii) interactions between two proteins or their homologs and (iii) interactions within a specific PDB entry. The server allows interactive analysis of the identified interactions in both summarized and detailed manner. This includes protein annotations, structures, the interface residues and the corresponding contact surface areas. In addition, users can make inferences about residues at the interaction interface for the query protein(s) from the sequence alignments and homology models. The weekly updated PPI3D database includes all the interaction interfaces and binding sites from PDB, clustered based on both protein sequence and structural similarity, yielding non-redundant datasets without loss of alternative interaction modes. Consequently, the PPI3D users avoid being flooded with redundant information, a typical situation for intensely studied proteins. Furthermore, PPI3D provides a possibility to download user-defined sets of interaction interfaces and analyze them locally. The PPI3D web server is available at https://bioinformatics.lt/ppi3d.

Resolving coupled pH titrations using alchemical free energy calculations

In a protein, nearby titratable sites can be coupled: the (de)protonation of one may affect the other. The degree of this interaction depends on several factors and can influence the measured p K a . Here, we derive a formalism based on double free energy differences ( Δ Δ G ) for quantifying the individual site p K a values of coupled residues. As Δ Δ G values can be obtained by means of alchemical free energy calculations, the presented approach allows for a convenient estimation of coupled residue p K a s in practice. We demonstrate that our approach and a previously proposed microscopic p K a formalism, can be combined with alchemical free energy calculations to resolve pH-dependent protein p K a values. Toy models and both, regular and constant-pH molecular dynamics simulations, alongside experimental data, are used to validate this approach. Our results highlight the insights gleaned when coupling and microstate probabilities are analyzed and suggest extensions to more complex enzymatic contexts. Furthermore, we find that naïvely computed p K a values that ignore coupling, can be significantly improved when coupling is accounted for, in some cases reducing the error by half. In short, alchemical free energy methods can resolve the p K a values of both uncoupled and coupled residues.

Composition of Lignocellulose Hydrolysate in Different Biorefinery Strategies: Nutrients and Inhibitors

The hydrolysis and biotransformation of lignocellulose, i.e., biorefinery, can provide human beings with biofuels, bio-based chemicals, and materials, and is an important technology to solve the fossil energy crisis and promote global sustainable development. Biorefinery involves steps such as pretreatment, saccharification, and fermentation, and researchers have developed a variety of biorefinery strategies to optimize the process and reduce process costs in recent years. Lignocellulosic hydrolysates are platforms that connect the saccharification process and downstream fermentation. The hydrolysate composition is closely related to biomass raw materials, the pretreatment process, and the choice of biorefining strategies, and provides not only nutrients but also possible inhibitors for downstream fermentation. In this review, we summarized the effects of each stage of lignocellulosic biorefinery on nutrients and possible inhibitors, analyzed the huge differences in nutrient retention and inhibitor generation among various biorefinery strategies, and emphasized that all steps in lignocellulose biorefinery need to be considered comprehensively to achieve maximum nutrient retention and optimal control of inhibitors at low cost, to provide a reference for the development of biomass energy and chemicals.

Rapid and Mechanically Robust Immobilization of Proteins on Silica Studied at the Single-Molecule Level by Force Spectroscopy and Verified at the Macroscopic Level

Typical methods for stable immobilization of proteins often involve time-consuming surface modification of silicon-based materials to enable specific binding, while the nonspecific adsorption method is faster but usually unstable. Herein, we fused a silica-binding protein, Si-tag, to target proteins so that the target proteins could attach directly to silica substrates in a single step, markedly streamlining the immobilization process. The adhesion force between the Si-tag and glass substrates was determined to be approximately 400-600 pN at the single-molecule level by atomic force microscopy, which is greater than the unfolding force of most proteins. The adhesion force of the Si-tag exhibits a slight increase when pulled from the C-terminus compared to that from the N-terminus. Furthermore, the Si-tag's adhesion force on a glass surface is marginally higher than that on a silicon nitride probe. The binding properties of the Si-tag are not obviously affected by environmental factors, including pH, salt concentration, and temperature. In addition, the macroscopic adhesion force between the Si-tag-coated hydrogel and glass substrates was ∼40 times higher than that of unmodified hydrogels. Therefore, the Si-tag, with its strong silica substrate binding ability, provides a useful tool as an excellent fusion tag for the rapid and mechanically robust immobilization of proteins on silica and for the surface coating of silica-binding materials.

Essential autoproteolysis of bacterial anti-σ factor RsgI for transmembrane signal transduction

Autoproteolysis has been discovered to play key roles in various biological processes, but functional autoproteolysis has been rarely reported for transmembrane signaling in prokaryotes. In this study, an autoproteolytic effect was discovered in the conserved periplasmic domain of anti-σ factor RsgIs from Clostridium thermocellum, which was found to transmit extracellular polysaccharide-sensing signals into cells for regulation of the cellulosome system, a polysaccharide-degrading multienzyme complex. Crystal and NMR structures of periplasmic domains from three RsgIs demonstrated that they are different from all known proteins that undergo autoproteolysis. The RsgI-based autocleavage site was located at a conserved Asn-Pro motif between the β1 and β2 strands in the periplasmic domain. This cleavage was demonstrated to be essential for subsequent regulated intramembrane proteolysis to activate the cognate SigI, in a manner similar to that of autoproteolysis-dependent activation of eukaryotic adhesion G protein-coupled receptors. These results indicate the presence of a unique prevalent type of autoproteolytic phenomenon in bacteria for signal transduction.

Basis for Accurate Protein pKa Prediction with Machine Learning

pH regulates protein structures and the associated functions in many biological processes via protonation and deprotonation of ionizable side chains where the titration equilibria are determined by pK_a's. To accelerate pH-dependent molecular mechanism research in the life sciences or industrial protein and drug designs, fast and accurate pK_a prediction is crucial. Here we present a theoretical pK_a data set PHMD549, which was successfully applied to four distinct machine learning methods, including DeepKa, which was proposed in our previous work. To reach a valid comparison, EXP67S was selected as the test set. Encouragingly, DeepKa was improved significantly and outperforms other state-of-the-art methods, except for the constant-pH molecular dynamics, which was utilized to create PHMD549. More importantly, DeepKa reproduced experimental pK_a orders of acidic dyads in five enzyme catalytic sites. Apart from structural proteins, DeepKa was found applicable to intrinsically disordered peptides. Further, in combination with solvent exposures, it is revealed that DeepKa offers the most accurate prediction under the challenging circumstance that hydrogen bonding or salt bridge interaction is partly compensated by desolvation for a buried side chain. Finally, our benchmark data qualify PHMD549 and EXP67S as the basis for future developments of protein pK_a prediction tools driven by artificial intelligence. In addition, DeepKa built on PHMD549 has been proven an efficient protein pK_a predictor and thus can be applied immediately to, for example, pK_a database construction, protein design, drug discovery, and so on.

Current challenges in designer cellulosome engineering

Designer cellulosomes (DCs) are engineered multi-enzyme complexes, comprising carbohydrate-active enzymes attached to a common backbone, the scaffoldin, via high-affinity cohesin-dockerin interactions. The use of DCs in the degradation of renewable biomass polymers is a promising approach for biorefineries. Indeed, DCs have shown significant hydrolytic activities due to the enhanced enzyme-substrate proximity and inter-enzyme synergies, but technical hurdles in DC engineering have hindered further progress towards industrial application. The challenge in DC engineering lies in the large diversity of possible building blocks and architectures, resulting in a multivariate and immense design space. Simultaneously, the precise DC composition affects many relevant parameters such as activity, stability, and manufacturability. Since protein engineers face a lack of high-throughput approaches to explore this vast design space, DC engineering may result in an unsatisfying outcome. This review provides a roadmap to guide researchers through the process of DC engineering. Each step, starting from concept to evaluation, is described and provided with its challenges, along with possible solutions, both for DCs that are assembled in vitro or are displayed on the yeast cell surface. KEY POINTS: • Construction of designer cellulosomes is a multi-step process. • Designer cellulosome research deals with multivariate construction challenges. • Boosting designer cellulosome efficiency requires exploring a vast design space.

Deciphering Cellodextrin and Glucose Uptake in Clostridium thermocellum

Sugar uptake is of great significance in industrially relevant microorganisms. Clostridium thermocellum has extensive potential in lignocellulose biorefineries as an environmentally prominent, thermophilic, cellulolytic bacterium. The bacterium employs five putative ATP-binding cassette transporters which purportedly take up cellulose hydrolysates. Here, we first applied combined genetic manipulations and biophysical titration experiments to decipher the key glucose and cellodextrin transporters. In vivo gene inactivation of each transporter and in vitro calorimetric and nuclear magnetic resonance (NMR) titration of each putative sugar-binding protein with various saccharides supported the conclusion that only transporters A and B play the roles of glucose and cellodextrin transport, respectively. To gain insight into the structural mechanism of the transporter specificities, 11 crystal structures, both alone and in complex with appropriate saccharides, were solved for all 5 putative sugar-binding proteins, thus providing detailed specific interactions between the proteins and the corresponding saccharides. Considering the importance of transporter B as the major cellodextrin transporter, we further identified its cryptic, hitherto unknown ATPase-encoding gene as clo1313_2554, which is located outside the transporter B gene cluster. The crystal structure of the ATPase was solved, showing that it represents a typical nucleotide-binding domain of the ATP-binding cassette (ABC) transporter. Moreover, we determined that the inducing effect of cellobiose (G2) and cellulose on cellulosome production could be eliminated by deletion of transporter B genes, suggesting the coupling of sugar transport and regulation of cellulosome components. This study provides key basic information on the sugar uptake mechanism of C. thermocellum and will promote rational engineering of the bacterium for industrial application.

patcHwork: a user-friendly pH sensitivity analysis web server for protein sequences and structures

pH regulates protein function and interactions by altering the charge of individual residues causing loss or gain of intramolecular noncovalent bonds, which may lead to structural rearrangements. While tools to analyze residue-specific charge distribution of proteins at a given pH exist, currently no tool is available to investigate noncovalent bond changes at two different pH values. To make protein pH sensitivity analysis more accessible, we developed patcHwork, a web server that combines the identification of amino acids undergoing a charge shift with the determination of affected noncovalent bonds at two user-defined pH values. At the sequence-only level, patcHwork applies the Henderson–Hasselbalch equation to determine pH-sensitive residues. When the 3D protein structure is available, patcHwork can be employed to gain mechanistic understanding of the effect of pH. This is achieved using the PDB2PQR and PROPKA tools and noncovalent bond determination algorithms. A user-friendly interface allows visualizing pH-sensitive residues, affected salt bridges, hydrogen bonds and aromatic (pi–pi and cation–pi) interactions. patcHwork can be used to identify patches, a new concept we propose of pH-sensitive residues in close proximity on the protein, which may have a major impact on function. We demonstrate the attractiveness of patcHwork studying experimentally investigated pH-sensitive proteins (https://patchwork.biologie.uni-freiburg.de/).

NMR chemical shift assignments of a module of unknown function in the cellulosomal secondary scaffoldin ScaF from Clostridium thermocellum

The cellulosome is a highly efficient cellulolytic complex containing cellulolytic enzymes and non-catalytic subunits, i.e. scaffoldins, which are assembled by the interactions between the dockerin modules of the enzymes and the cohesin modules of the primary scaffoldins. The cellulosome attaches to the cell surface via the S-layer homology (SLH) modules of the anchoring scaffoldins. Clostridium thermocellum DSM1313 is a thermophilic cellulosome-producing bacterium with great potential in lignocellulose bioconversion and biofuel production. The bacterium contains four anchoring scaffoldins ScaB, ScaC, ScaD and ScaF, among which ScaF is the only one that contains an additional module of unknown function (ScaF-X) between the cohesin and SLH modules. The gene of ScaF is located outside the scaffoldin gene cluster of scaA, scaB, scaC and scaD. Previous studies showed unique regulation properties and function of ScaF compared to other anchoring scaffoldins, which might be related to the additional ScaF-X module. Here we report the NMR chemical shift assignments of ScaF-X from C. thermocellum DSM1313. The well-dispersed NMR spectrum and the secondary structure prediction based on the chemical shifts of ScaF-X indicated that ScaF-X is a well-folded protein module. The chemical shift assignments provide the basis for future studies on the structure of this module and its function in cellulosomes.

A dual cohesin-dockerin complex binding mode in Bacteroides cellulosolvens contributes to the size and complexity of its cellulosome

The Cellulosome is an intricate macromolecular protein complex that centralizes the cellulolytic efforts of many anaerobic microorganisms through the promotion of enzyme synergy and protein stability. The assembly of numerous carbohydrate processing enzymes into a macromolecular multiprotein structure results from the interaction of enzyme-borne dockerin modules with repeated cohesin modules present in noncatalytic scaffold proteins, termed scaffoldins. Cohesin-dockerin (Coh-Doc) modules are typically classified into different types, depending on structural conformation and cellulosome role. Thus, type I Coh-Doc complexes are usually responsible for enzyme integration into the cellulosome, while type II Coh-Doc complexes tether the cellulosome to the bacterial wall. In contrast to other known cellulosomes, cohesin types from Bacteroides cellulosolvens, a cellulosome-producing bacterium capable of utilizing cellulose and cellobiose as carbon sources, are reversed for all scaffoldins, i.e., the type II cohesins are located on the enzyme-integrating primary scaffoldin, whereas the type I cohesins are located on the anchoring scaffoldins. It has been previously shown that type I B. cellulosolvens interactions possess a dual-binding mode that adds flexibility to scaffoldin assembly. Herein, we report the structural mechanism of enzyme recruitment into B. cellulosolvens cellulosome and the identification of the molecular determinants of its type II cohesin-dockerin interactions. The results indicate that, unlike other type II complexes, these possess a dual-binding mode of interaction, akin to type I complexes. Therefore, the plasticity of dual-binding mode interactions seems to play a pivotal role in the assembly of B. cellulosolvens cellulosome, which is consistent with its unmatched complexity and size.