Predictive and Experimental Approaches for Elucidating Protein-Protein Interactions and Quaternary Structures

Co-evolution at protein-protein interfaces guides inference of stoichiometry of oligomeric protein complexes by de novo structure prediction

The quaternary structure with specific stoichiometry is pivotal to the specific function of protein complexes. However, determining the structure of many protein complexes experimentally remains a major bottleneck. Structural bioinformatics approaches, such as the deep learning algorithm Alphafold2-multimer (AF2-multimer), leverage the co-evolution of amino acids and sequence-structure relationships for accurate de novo structure and contact prediction. Pseudo-likelihood maximization direct coupling analysis (plmDCA) has been used to detect co-evolving residue pairs by statistical modeling. Here, we provide evidence that combining both methods can be used for de novo prediction of the quaternary structure and stoichiometry of a protein complex. We achieve this by augmenting the existing AF2-multimer confidence metrics with an interpretable score to identify the complex with an optimal fraction of native contacts of co-evolving residue pairs at intermolecular interfaces. We use this strategy to predict the quaternary structure and non-trivial stoichiometries of Bacillus subtilis spore germination protein complexes with unknown structures. Co-evolution at intermolecular interfaces may therefore synergize with AI-based de novo quaternary structure prediction of structurally uncharacterized bacterial protein complexes.

Linearly Polarized Infrared Spectroscopy for the Analysis of Biological Materials

The analysis of biological samples with polarized infrared spectroscopy (p-IR) has long been a widely practiced method for the determination of sample orientation and structural properties. In contrast to earlier works, which employed this method to investigate the fundamental chemistry of biological systems, recent interests are moving toward "real-world" applications for the evaluation and diagnosis of pathological states. This focal point review provides an up-to-date synopsis of the knowledge of biological materials garnered through linearly p-IR on biomolecules, cells, and tissues. An overview of the theory with special consideration to biological samples is provided. Different modalities which can be employed along with their capabilities and limitations are outlined. Furthermore, an in-depth discussion of factors regarding sample preparation, sample properties, and instrumentation, which can affect p-IR analysis is provided. Additionally, attention is drawn to the potential impacts of analysis of biological samples with inherently polarized light sources, such as synchrotron light and quantum cascade lasers. The vast applications of p-IR for the determination of the structure and orientation of biological samples are given. In conclusion, with considerations to emerging instrumentation, findings by other techniques, and the shift of focus toward clinical applications, we speculate on the future directions of this methodology.

Regulatory Light Chains in Cardiac Development and Disease

The role of regulatory light chains (RLCs) in cardiac muscle function has been elucidated progressively over the past decade. The RLCs are among the earliest expressed markers during cardiogenesis and persist through adulthood. Failing hearts have shown reduced RLC phosphorylation levels and that restoring baseline levels of RLC phosphorylation is necessary for generating optimal force of muscle contraction. The signalling mechanisms triggering changes in RLC phosphorylation levels during disease progression remain elusive. Uncovering this information may provide insights for better management of heart failure patients. Given the cardiac chamber-specific expression of RLC isoforms, ventricular RLCs have facilitated the identification of mature ventricular cardiomyocytes, opening up possibilities of regenerative medicine. This review consolidates the standing of RLCs in cardiac development and disease and highlights knowledge gaps and potential therapeutic advancements in targeting RLCs.

Computational Methods for the Elucidation of Protein Structure and Interactions

Biologists are increasingly aware of the importance of protein structure in revealing function. The computational tools now exist which allow researchers to model unknown proteins simply on the basis of their primary sequence. However, for the non-specialist bioinformatician, there is a dazzling array of terminology, acronyms, and competing computer software available for this process. This review is intended to highlight the key stages of computational protein structure prediction, as well as explain the reasons behind some of the procedures and list some established workarounds for common pitfalls. Thereafter follows a review of five one-stop servers for start-to-finish structure prediction.

Functional Prediction and Assignment of Methanobrevibacter ruminantium M1 Operome Using a Combined Bioinformatics Approach

Methanobrevibacter ruminantium M1 (MRU) is a rod-shaped rumen methanogen with the ability to use H₂ and CO₂, and formate as substrates for methane formation in the ruminants. Enteric methane emitted from this organism can also be influential to the loss of dietary energy in ruminants and humans. To date, there is no successful technology to reduce methane due to a lack of knowledge on its molecular machinery and 73% conserved hypothetical proteins (HPs; operome) whose functions are still not ascertained perceptively. To address this issue, we have predicted and assigned a precise function to HPs and categorize them as metabolic enzymes, binding proteins, and transport proteins using a combined bioinformatics approach. The results of our study show that 257 (34%) HPs have well-defined functions and contributed essential roles in its growth physiology and host adaptation. The genome-neighborhood analysis identified 6 operon-like clusters such as hsp, TRAM, dsr, cbs and cas, which are responsible for protein folding, sudden heat-shock, host defense, and protection against the toxicities in the rumen. The functions predicted from MRU operome comprised of 96 metabolic enzymes with 17 metabolic subsystems, 31 transcriptional regulators, 23 transport, and 11 binding proteins. Functional annotation of its operome is thus more imperative to unravel the molecular and cellular machinery at the systems-level. The functional assignment of its operome would advance strategies to develop new anti-methanogenic targets to mitigate methane production. Hence, our approach provides new insight into the understanding of its growth physiology and lifestyle in the ruminants and also to reduce anthropogenic greenhouse gas emissions worldwide.

Evaluation of gene expression and protein structural modeling involved in persister cell formation in Salmonella Typhimurium

Persisters are phenotypic variants of the bacterial population that survive against lethal doses of bactericidal antibiotics.These phenotypes are created in numerous bacterial species, including those of clinical significance, such as Salmonella Typhimurium. Since persister cells are associated with the failure of antibiotic treatment and infection recurrence, it is crucial to identify the mechanisms that influence the formation of these cells. The aim of this study is to investigate the persister cell formation and expression analysis as well as to predict the 3D structure of the genes involved in the production of persister cells. The presence of persisters in S. Typhimurium was determined by time dependent killing of different types of bactericidal antibiotics and expression of genes associated with persister cell formation which was assessed five hours after the addition of antibiotics by the qRT-PCR. Indeed, the 3D structural model of the proteins studied was predicted by performing several computational methods of retrieved primary protein sequences. The results of the study showed that the S. Typhimurium produced high levels of persister cells in the exposure of bactericidal antibiotics. Furthermore, qRT-PCR resulted in the fact that the expression of related genes was different depending on the type of antibiotic. Overall, this study provides information on the creation of persister cells and the role of different genes in the formation of these cells and structure of proteins involved in the production of persister cells in S. Typhimurium.

Neighborhood Preference of Amino Acids in Protein Structures and its Applications in Protein Structure Assessment

Amino acids form protein 3D structures in unique manners such that the folded structure is stable and functional under physiological conditions. Non-specific and non-covalent interactions between amino acids exhibit neighborhood preferences. Based on structural information from the protein data bank, a statistical energy function was derived to quantify amino acid neighborhood preferences. The neighborhood of one amino acid is defined by its contacting residues, and the energy function is determined by the neighboring residue types and relative positions. The neighborhood preference of amino acids was exploited to facilitate structural quality assessment, which was implemented in the neighborhood preference program NEPRE. The source codes are available via https://github.com/LiuLab-CSRC/NePre.

Functional prediction, characterization, and categorization of operome from Acetoanaerobium sticklandii DSM 519

Acetoanaerobium sticklandii DSM 519 is a hyper-ammonia producing anaerobic bacterium that can be able utilizes amino acids as sole carbon and energy sources for its growth and energetic metabolism. A lack of knowledge on its molecular machinery and 30.5% conserved hypothetical proteins (HPs; operome) hinders the successful utility in biofuel applications. In this study, we have predicted, characterized and categorized its operome whose functions are still not determined accurately using a combined bioinformatics approach. The functions of 64 of the 359 predicted HPs are involved in diverse metabolic subsystems. A. sticklandii operome has consisted of 16% Rossmann fold and 46% miscellaneous folds. Subsystems-based technology has classified 51 HPs contributing to the small-molecular reactions, 26 in macromolecular reactions and 12 in the biosynthesis of cofactors, prosthetic groups and electron carriers. A generality of functions predicted from its operome contributed to the cell cycle, amino acid metabolism, membrane transport, and regulatory processes. Many of them have duplicated functions as paralogs in this genome. A. sticklandii has the ability to compete with invading microorganisms and tolerate abiotic stresses, which can be overwhelmed by the predicted functions of its operome. Results of this study revealed that it has specialized systems for amino acid catabolism-directed solventogenesis and acidogenesis but the level of gene expression may determine the metabolic function in amino acid fermenting niches in the rumina of cattle. As shown by our analysis, the predicted functions of its operome allow us for a better understanding of the growth and physiology at systems-scale.

Investigation of quaternary structure of aggregating 3-ketosteroid dehydrogenase from Sterolibacterium denitrificans: In the pursuit of consensus of various biophysical techniques

In this work we analyzed the quaternary structure of FAD-dependent 3-ketosteroid dehydrogenase (AcmB) from Sterolibacterium denitrificans, the protein that in solution forms massive aggregates (>600 kDa). Using size-excursion chromatography (SEC), dynamic light scattering (DLS), native-PAGE and atomic force microscopy (AFM) we studied the nature of enzyme aggregation. Partial protein de-aggregation was facilitated by the presence of non-ionic detergent such as Tween 20 or by a high degree of protein dilution but not by addition of a reducing agent or an increase of ionic strength. De-aggregating influence of Tween 20 had no impact on either enzyme's specific activity or FAD reconstitution to recombinant AcmB. The joint experimental (DLS, isoelectric focusing) and theoretical investigations demonstrated gradual shift of enzyme's isoelectric point upon aggregation from 8.6 for a monomeric form to even 5.0. The AFM imaging on mica or highly oriented pyrolytic graphite (HOPG) surface enabled observation of individual protein monomers deposited from a highly diluted solution (0.2 μg/ml). Such approach revealed that native AcmB can indeed be monomeric. AFM imaging supported by theoretical random sequential adsorption (RSA) kinetics allowed estimation of distribution enzyme forms in the bulk solution: 5%, monomer, 11.4% dimer and 12% trimer. Finally, based on results of AFM as well as analysis of the surface of AcmB homology models we have observed that aggregation is most probably initiated by hydrophobic forces and then assisted by electrostatic attraction between negatively charged aggregates and positively charged monomers.