Multimodal Mass Spectrometry Identifies a Conserved Protective Epitope in S. pyogenes Streptolysin O.

An important element of antibody-guided vaccine design is the use of neutralizing or opsonic monoclonal antibodies to define protective epitopes in their native three-dimensional conformation. Here, we demonstrate a multimodal mass spectrometry-based strategy for in-depth characterization of antigen-antibody complexes to enable the identification of protective epitopes using the cytolytic exotoxin Streptolysin O (SLO) from Streptococcus pyogenes as a showcase. We first discovered a monoclonal antibody with an undisclosed sequence capable of neutralizing SLO-mediated cytolysis. The amino acid sequence of both the antibody light and the heavy chain was determined using mass-spectrometry-based de novo sequencing, followed by chemical cross-linking mass spectrometry to generate distance constraints between the antibody fragment antigen-binding region and SLO. Subsequent integrative computational modeling revealed a discontinuous epitope located in domain 3 of SLO that was experimentally validated by hydrogen-deuterium exchange mass spectrometry and reverse engineering of the targeted epitope. The results show that the antibody inhibits SLO-mediated cytolysis by binding to a discontinuous epitope in domain 3, likely preventing oligomerization and subsequent secondary structure transitions critical for pore-formation. The epitope is highly conserved across >98% of the characterized S. pyogenes isolates, making it an attractive target for antibody-based therapy and vaccine design against severe streptococcal infections.

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein.

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host-pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics.

Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass spectrometry (MS). Despite improved instrumentation and software, de novo MS data analysis remains challenging. In recent years, deep learning models have represented a performance breakthrough. Incorporating that technology into de novo protein sequencing workflows require machine-learning models capable of handling highly diverse MS data. In this study, we analyzed the requirements for assembling such generalizable deep learning models by systemcally varying the composition and size of the training set. We assessed the generated models' performances using two test sets composed of peptides originating from the multienzyme digestion of samples from various species. The peptide recall values on the test sets showed that the deep learning models generated from a collection of highly N- and C-termini diverse peptides generalized 76% more over the termini-restricted ones. Moreover, expanding the training set's size by adding peptides from the multienzymatic digestion with five proteases of several species samples led to a 2-3 fold generalizability gain. Furthermore, we tested the applicability of these multienzyme deep learning (MEM) models by fully de novo sequencing the heavy and light monomeric chains of five commercial antibodies (mAbs). MEMs extracted over 10000 matching and overlapped peptides across six different proteases mAb samples, achieving a 100% sequence coverage for 8 of the ten polypeptide chains. We foretell that the MEMs' proven improvements to de novo analysis will positively impact several applications, such as analyzing samples of high complexity, unknown nature, or the peptidomics field.

Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis.

Meningitis is a potentially life-threatening infection characterized by the inflammation of the leptomeningeal membranes. Many different viral and bacterial pathogens can cause meningitis, with differences in mortality rates, risk of developing neurological sequelae, and treatment options. Here, we constructed a compendium of digital cerebrospinal fluid (CSF) proteome maps to define pathogen-specific host response patterns in meningitis. The results revealed a drastic and pathogen-type specific influx of tissue-, cell-, and plasma proteins in the CSF, where, in particular, a large increase of neutrophil-derived proteins in the CSF correlated with acute bacterial meningitis. Additionally, both acute bacterial and viral meningitis result in marked reduction of brain-enriched proteins. Generation of a multiprotein LASSO regression model resulted in an 18-protein panel of cell- and tissue-associated proteins capable of classifying acute bacterial meningitis and viral meningitis. The same protein panel also enabled classification of tick-borne encephalitis, a subgroup of viral meningitis, with high sensitivity and specificity. The work provides insights into pathogen-specific host response patterns in CSF from different disease etiologies to support future classification of pathogen type based on host response patterns in meningitis.

G-score: A function to solve the puzzle of modeling the protonation states of ß-secretase binding pocket.

The population density concept has emerged as a proposal for the analysis of molecular dynamics results, the key characteristic of population density is the evaluation of the simultaneous occurrence of a set of relevant parameters for a system. However, despite its statistical strength, selection of the tolerance level for the comparison of different models may appear as arbitrary. This work introduces the G-score, a function which summarizes and categorizes the results of population density analysis. Additionally, it incorporates parameters based on rmsd and dihedral angles, besides the protein-protein and protein-ligand interatomic distances conventionally used, which complement each other to provide a better description of the behavior of the system. These newly-proposed tools were applied to determine the most probable protonation state of the aspartic dyad of BACE1, Asp93 and Asp289, in the presence of three types of transition state inhibitors namely: reduced amides, tertiary carbinamines and hydroxyethylamines. The results show a full agreement between G-score values and population density charts, with the advantage of allowing a quick and direct comparison among all the considered models. We anticipate that the simplicity of calculating the parameters employed in this study will permit the extensive use of population density and the G-score for other molecular systems.

Population density analysis for determining the protonation state of the catalytic dyad in BACE1-tertiary carbinamine-based inhibitor complex.

BACE1 is an aspartyl protease with a very relevant role in medicinal chemistry related to Alzheimer Disease since it has demonstrated to be a promising therapeutic target for inhibition and possible control for the progress of the peptide accumulation characteristic of this pathology. The enzymatic activity of this protein is given by the aspartic dyad, Asp93 and Asp289, which can adopt several protonation states depending on the chemical nature of its inhibitors, this is, monoprotonated, diprotonated and di-deprotonated states. In the present study, the analysis of the population density, for a series of protein-inhibitor molecular dynamics simulations, was carried out to identify the most feasible protonation state adopted by the catalytic dyad in the presence of tertiary carbinamine (TC) transition state analog inhibitors. The results revealed that the monoprotonated Asp289i state, in which the Asp93 and Asp289 residue side chains are deprotonated and protonated on the inner oxygen, respectively, is the most preferred in the presence of TC family inhibitors. This result was obtained after evaluating, for all 9 possible protonation state configurations, the individual and combined population densities of a set of parameters sensitive to protonation state of the Aspartic dyad, using an X-ray experimental BACE1/TC crystallographic structure as reference. This case study demonstrates again the usefulness of the concept of population density as a quantitative tool to establish the most stable system settings, among all possible, by measuring the level of occurrence of simultaneous events obtained from a sampling over time. These results will help to clear the phenomena related to the TCs inhibitory pathway, as well as assist in the design of better TC inhibitors against Alzheimer's protease.

A PM7 dynamic residue-ligand interactions energy landscape of the BACE1 inhibitory pathway by hydroxyethylamine compounds. Part I: The flap closure process.

BACE1 is an enzyme of scientific interest because it participates in the progression of Alzheimer's disease. Hydroxyethylamines (HEAs) are a family of compounds which exhibit inhibitory activity toward BACE1 at a nanomolar level, favorable pharmacokinetic properties and oral bioavailability. The first step in the inhibition of BACE1 by HEAs consists of their entrance into the protease active site and the resultant conformational change in the protein, from Apo to closed form. These two conformations differ in the position of an antiparallel loop (called the flap) which covers the entrance to the catalytic site. For BACE1, closure of this flap is vital to its catalytic activity and to inhibition of the enzyme due to the new interactions thereby formed with the ligand. In the present study a dynamic energy landscape of residue-ligand interaction energies (ReLIE) measured for 112 amino acids in the BACE1 active site and its immediate vicinity during the closure of the flap induced by 8 HEAs of different inhibitory power is presented. A total of 6.272 million ReLIE calculations, based on the PM7 semiempirical method, provided a deep and quantitative view of the first step in the inhibition of the aspartyl protease. The information suggests that residues Asp93, Asp289, Thr292, Thr293, Asn294 and Arg296 are anchor points for the ligand, accounting for approximately 45% of the total protein-ligand interaction. Additionally, flap closure improved the BACE1-HEA interaction by around 25%. Furthermore, the inhibitory activity of HEAs could be related to the capacity of these ligands to form said anchor point interactions and maintain them over time: the lack of some of these anchor interactions delayed flap closure or impeded it completely, or even caused the flap to reopen. The methodology employed here could be used as a tool to evaluate future structural modifications which lead to improvements in the favorability and stability of BACE1-HEA ReLIEs, aiding in the design of better inhibitors.

A molecular dynamics study of the BACE1 conformational change from Apo to closed form induced by hydroxyethylamine derived compounds.

BACE1 is an aspartyl protease which is a therapeutic target for Alzheimer's disease (AD) because of its participation in the rate-limiting step in the production of Aß-peptide, the accumulation of which produces senile plaques and, in turn, the neurodegenerative effects associated with AD. The active site of this protease is composed in part by two aspartic residues (Asp93 and Asp289). Additionally, the catalytic site has been found to be covered by an antiparallel hairpin loop called the flap. The dynamics of this flap are fundamental to the catalytic function of the enzyme. When BACE1 is inactive (Apo), the flap adopts an open conformation, allowing a substrate or inhibitor to access the active site. Subsequent interaction with the ligand induces flap closure and the stabilization of the macromolecular complex. Further, the protonation state of the aspartic dyad is affected by the chemical nature of the species entering the active site, so that appropriate selection of protonation states for the ligand and the catalytic residues will permit the elucidation of the inhibitory pathway for BACE1. In the present study, comparative analysis of different combinations of protonation states for the BACE1-hydroxyethylamine (HEA) system is reported. HEAs are potent inhibitors of BACE1 with favorable pharmacological and kinetic properties, as well as oral bioavailability. The results of Molecular Dynamics (MD) simulations and population density calculations using 8 different parameters demonstrate that the LnAsp289 configuration (HEA with a neutral amine and the Asp289 residue protonated) is the only one which permits the expected conformational change in BACE1, from apo to closed form, after flap closure. Additionally, differences in their capacities to establish and maintain interactions with residues such as Asp93, Gly95, Thr133, Asp289, Gly291, and Asn294 during this step allow differentiation among the inhibitory activities of the HEAs. The results and methodology here reported will serve to elucidate the inhibitory pathway of other families of compounds that act as BACE1 inhibitors, as well as the design of better leader compounds for the treatment of AD.

Determination of the protonation state for the catalytic dyad in ß-secretase when bound to hydroxyethylamine transition state analogue inhibitors: A molecular dynamics simulation study.

BACE1 is an aspartyl protease of pharmacological interest for its direct participation in Alzheimer's disease (AD) through ß-amyloid peptide production. Two aspartic acid residues are present in the BACE1 catalytic region which can adopt multiple protonation states depending on the chemical nature of its inhibitors, i.e., monoprotonated, diprotonated and di-deprotonated states. In the present study a series of protein-ligand molecular dynamics (MD) simulations was carried out to identify the most feasible protonation state adopted by the catalytic dyad in the presence of hydroxyethylamine transition state analogue inhibitors. The MD trajectories revealed that the di-deprotonated state is most prefered in the presence of hydroxyethilamine (HEA) family inhibitors. This appears as a result after evaluating, for all 9 protonation state configurations during the simulation time, the deviations of a set of distances and dihedral angles measured on the ligand, protein and protein-ligand complex with reference to an X-ray experimental BACE1/HEA crystallographic structure. These results will help to clarify the phenomena related to the HEAs inhibitory pathway, and improve HEAs databases' virtual screening and ligand design processes targeting ß-secretase protein.

Quantum mechanics study of the hydroxyethylamines-BACE-1 active site interaction energies.

The identification of BACE-1, a key enzyme in the production of Amyloid-ß (Aß) peptides, generated by the proteolytic processing of amyloid precursor protein, was a major advance in the field of Alzheimer's disease as this pathology is characterized by the presence of extracellular senile plaques, mainly comprised of Aß peptides. Hydroxyethylamines have demonstrated a remarkable potential, like candidate drugs, for this disease using BACE-1 as target. Density Functional Theory calculations were employed to estimate interaction energies for the complexes formed between the hydroxyethylamine derivated inhibitors and 24 residues in the BACE-1 active site. The collected data offered not only a general but a particular quantitative description that gives a deep insight of the interactions in the active site, showing at the same time how ligand structural variations affect them. Polar interactions are the major energetic contributors for complex stabilization and those ones with charged aspartate residues are highlighted, as they contribute over 90% of the total attractive interaction energy. Ligand-ARG296 residue interaction reports the most repulsive value and decreasing of the magnitude of this repulsion can be a key feature for the design of novel and more potent BACE-1 inhibitors. Also it was explained why sultam derivated BACE-1 inhibitors are better ones than lactam based. Hydrophobic interactions concentrated at S1 zone and other relevant repulsions and attractions were also evaluated. The comparison of two different theory levels (X3LYP and M062X) allowed to confirm the relevance of the detected interactions as each theory level has its own strength to depict the forces involved, as is the case of M062X which is better describing the hydrophobic interactions. Those facts were also evaluated and confirmed by comparing the quantitative trend, of selected ligand-residue interactions, with MP2 theory level as reference standard method for electrostatic plus dispersion energies.

Estudio de análogos de la sulfonanilida que actúan como supresores de la expresión de la aromatasa / Study of sulfonanilide analogues acting as suppressants of the aromatase expression

Se realizó un estudio tridimensional cuantitativo de relación-estructura con nuevos análogos de la sulfonanilida que actúan como supresores de la expresión y actividad de la aromatasa en células de cáncer de mama, independientemente de la inhibición de la ciclooxigenasa-2 (COX-2). La superposición molecular de los ligandos en la plantilla fue llevada a cabo por el método Database Alignment. El mejor modelo estuvo constituido por la combinación de los campos estérico e hidrofóbico, los cuales arrojaron los siguientes parámetros: q² = 0,613 con siete componentes, R² no validado igual a 0,976, valor de F igual a 81,695; 0,347 y 0,047 para los errores estándar de predicción y estimación, respectivamente. Las contribuciones estérica e hidrofóbica fueron de 50,5 y 49,5% respectivamente. Los datos generados por el presente estudio podrían impulsar el diseño de nuevos y más potentes reguladores selectivos de la expresión de la aromatasa.

A three-dimensional quantitative structure-activity relationship study was performed with new Sulfonanilide analogue molecules acting as aromatase expression and activity suppressors in breast cancer cells independent of COX-2 inhibition. The molecular supression of the ligands in the grid was carried out by the DATA-BASE ALIGNMENT method. The best model formed by combining the esteric fields and hydrophobic fields yielded the following parameters: q² = 0.613 with seven components, not validated R² equal to 0.976, with an F value of 81.695, 0.347 and 0.047 for the standard errors of prediction and estimate, respectively. The contribution of esteric and hydrophobic fields was 50.5 and 49.5% respectively. data generated from this study may be used to design new and more potent selective aromatase expression regulators.