A stochastic approach for parameter optimization of feature detection algorithms for non-target screening in mass spectrometry.

Feature detection plays a crucial role in non-target screening (NTS), requiring careful selection of algorithm parameters to minimize false positive (FP) features. In this study, a stochastic approach was employed to optimize the parameter settings of feature detection algorithms used in processing high-resolution mass spectrometry data. This approach was demonstrated using four open-source algorithms (OpenMS, SAFD, XCMS, and KPIC2) within the patRoon software platform for processing extracts from drinking water samples spiked with 46 per- and polyfluoroalkyl substances (PFAS). The designed method is based on a stochastic strategy involving random sampling from variable space and the use of Pearson correlation to assess the impact of each parameter on the number of detected suspect analytes. Using our approach, the optimized parameters led to improvement in the algorithm performance by increasing suspect hits in case of SAFD and XCMS, and reducing the total number of detected features (i.e., minimizing FP) for OpenMS. These improvements were further validated on three different drinking water samples as test dataset. The optimized parameters resulted in a lower false discovery rate (FDR%) compared to the default parameters, effectively increasing the detection of true positive features. This work also highlights the necessity of algorithm parameter optimization prior to starting the NTS to reduce the complexity of such datasets.

Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites.

Thousands of biochemical reactions with characterized activities are "orphan," meaning they cannot be assigned to a specific enzyme, leaving gaps in metabolic pathways. Novel reactions predicted by pathway-generation tools also lack associated sequences, limiting protein engineering applications. Associating orphan and novel reactions with known biochemistry and suggesting enzymes to catalyze them is a daunting problem. We propose the method BridgIT to identify candidate genes and catalyzing proteins for these reactions. This method introduces information about the enzyme binding pocket into reaction-similarity comparisons. BridgIT assesses the similarity of two reactions, one orphan and one well-characterized nonorphan reaction, using their substrate reactive sites, their surrounding structures, and the structures of the generated products to suggest enzymes that catalyze the most-similar nonorphan reactions as candidates for also catalyzing the orphan ones. We performed two large-scale validation studies to test BridgIT predictions against experimental biochemical evidence. For the 234 orphan reactions from the Kyoto Encyclopedia of Genes and Genomes (KEGG) 2011 (a comprehensive enzymatic-reaction database) that became nonorphan in KEGG 2018, BridgIT predicted the exact or a highly related enzyme for 211 of them. Moreover, for 334 of 379 novel reactions in 2014 that were later cataloged in KEGG 2018, BridgIT predicted the exact or highly similar enzymes. BridgIT requires knowledge about only four connecting bonds around the atoms of the reactive sites to correctly annotate proteins for 93% of analyzed enzymatic reactions. Increasing to seven connecting bonds allowed for the accurate identification of a sequence for nearly all known enzymatic reactions.

Surface charging behavior of nanoparticles by considering site distribution and density, dielectric constant and pH changes--a Monte Carlo approach.

Monte Carlo simulations are used to describe the charging behavior of metal oxide nanoparticles thus enabling a novel and original approach to predict nanoparticle reactivity and the possible interactions with biological and environmental molecules. The charging behavior of spherical nanoparticles is investigated by adjusting the pH of the media and the influence of surface site distribution, density and dielectric constant as well as the acid/base properties of the surface sites and ΔpKa(0) values (difference between two successive deprotonation constants) is systematically studied using a grand canonical Monte Carlo method. A primitive Coulomb model is applied to describe the interaction energies between the explicit discrete sites. Homogeneous/heterogeneous surfaces and patches with homogeneous and heterogeneous distributions are considered in order to reproduce possible site distributions of metal oxide nanoparticles. Two models are used. In the 1-pKa(0) model (one deprotonation step) the results indicate that the deprotonation process is controlled by inter-site distances which are defined by site distributions and densities. It is shown that the homogeneous surface is the most efficient site distribution to obtain high ionization degrees. In the 2-pKa(0) model (two deprotonation steps), the ΔpKa(0) value is found to control the surface charge properties with regard to pH changes. By considering the variation of the total nanoparticle surface charge as a function of pH our results help in the distinction between the zero charge and the isoelectric point and interpretation of experimental NP titration curves.

Explicit solvent simulations of the aqueous oxidation potential and reorganization energy for neutral molecules: gas phase, linear solvent response, and non-linear response contributions.

First principles simulations were used to predict aqueous one-electron oxidation potentials (Eox) and associated half-cell reorganization energies (λaq) for aniline, phenol, methoxybenzene, imidazole, and dimethylsulfide. We employed quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations of the oxidized and reduced species in an explicit aqueous solvent, followed by EOM-IP-CCSD computations with effective fragment potentials for diabatic energy gaps of solvated clusters, and finally thermodynamic integration of the non-linear solvent response contribution using classical MD. A priori predicted Eox and λaq values exhibit mean absolute errors of 0.17 V and 0.06 eV, respectively, compared to experiment. We also disaggregate Eox into several well-defined free energy properties, including the gas phase adiabatic free energy of ionization (7.73 to 8.82 eV), the solvent-induced shift in the free energy of ionization due to linear solvent response (-2.01 to -2.73 eV), and the contribution from non-linear solvent response (-0.07 to -0.14 eV). The linear solvent response component is further apportioned into contributions from the solvent-induced shift in vertical ionization energy of the reduced species (ΔVIEaq) and the solvent-induced shift in negative vertical electron affinity of the ionized species (ΔNVEAaq). The simulated ΔVIEaq and ΔNVEAaq are found to contribute the principal sources of uncertainty in computational estimates of Eox and λaq. Trends in the magnitudes of disaggregated solvation properties are found to correlate with trends in structural and electronic features of the solute. Finally, conflicting approaches for evaluating the aqueous reorganization energy are contrasted and discussed, and concluding recommendations are given.

A computational framework for integration of lipidomics data into metabolic pathways.

Lipids are important compounds for human physiology and as renewable resources for fuels and chemicals. In lipid research, there is a big gap between the currently available pathway-level representations of lipids and lipid structure databases in which the number of compounds is expanding rapidly with high-throughput mass spectrometry methods. In this work, we introduce a computational approach to bridge this gap by making associations between metabolic pathways and the lipid structures discovered increasingly thorough lipidomics studies. Our approach, called NICELips (Network Integrated Computational Explorer for Lipidomics), is based on the formulation of generalized enzymatic reaction rules for lipid metabolism, and it employs the generalized rules to postulate novel pathways of lipid metabolism. It further integrates all discovered lipids in biological networks of enzymatic reactions that consist their biosynthesis and biodegradation pathways. We illustrate the utility of our approach through a case study of bis(monoacylglycero)phosphate (BMP), a biologically important glycerophospholipid with immature synthesis and catabolic route(s). Using NICELips, we were able to propose various synthesis and degradation pathways for this compound and several other lipids with unknown metabolism like BMP, and in addition several alternative novel biosynthesis and biodegradation pathways for lipids with known metabolism. NICELips has potential applications in designing therapeutic interventions for lipid-associated disorders and in the metabolic engineering of model organisms for improving the biobased production of lipid-derived fuels and chemicals.

Dielectric discontinuity effects on the adsorption of a linear polyelectrolyte at the surface of a neutral nanoparticle.

The formation of complexes between nanoparticles and polyelectrolytes is a key process for the control of the reactivity of manufactured nanoparticles and rational design of core shell nanostructures. In this work, we investigate the influence of the nanoparticle dielectric constant on the adsorption of a linear charged polymer (polyelectrolyte) at the surface of a neutral nanoparticle. The polyelectrolyte linear charge density, as well as the image charges in the nanoparticle due to the dielectric discontinuity, is taken into account. Monte Carlo simulations are used to predict the adsorption/desorption limits and system properties. Effects of the nanoparticle size and polyelectrolyte length are also investigated. The polyelectrolyte is found adsorbed on the nanoparticle when the dielectric constant of the nanoparticle is greater than the dielectric constant of the medium. Attractive interactions induced by the presence of opposite sign image charges are found strong enough to adsorb the polyelectrolyte showing that the reaction field contribution has to be considered. The affinity between the polyelectrolyte and the nanoparticle is found to increase in magnitude by increasing the nanoparticle size and dielectric constant. The reaction field magnitude is also found to depend in a nonlinear way from the polyelectrolyte length.

Modeling the surface charge evolution of spherical nanoparticles by considering dielectric discontinuity effects at the solid/electrolyte solution interface.

It is well known that the electrostatic repulsions between charges on neighboring sites decrease the effective charge at the surface of a charged nanoparticle (NP). However, the situation is more complex close to a dielectric discontinuity, since charged sites are interacting not only with their neighbors but also with their own image charges and the image charges of all neighbors. Titrating site positions, solution ionic concentration, dielectric discontinuity effects, and surface charge variations with pH are investigated here using a grand canonical Monte Carlo method. A Tanford and Kirkwood approach is used to calculate the interaction potentials between the discrete charged sites. Homogeneous, heterogeneous, and patch site distributions are considered to reproduce the various titrating site distributions at the solid/solution interface of spherical NPs. By considering Coulomb, salt, and image charges effects, results show that for different ionic concentrations, modifications of the dielectric constant of NPs having homogeneous and heterogeneous site distributions have little effect on their charging process. Thus, the reaction field, due to the presence of image charges, fully counterbalances the Coulomb interactions. This is not the case for patch distributions, where Coulomb interactions are not completely counterbalanced by the reaction field. Application of the present model to pyrogenic silica is also performed and comparison is made with published experimental data of titration curves at various ionic concentrations.

A monte carlo study of weak polyampholytes: stiffness and primary structure influences on titration curves and chain conformations.

The conformation and titration curves of weak polyampholytes are examined using Monte Carlo simulations with screened Coulomb potentials in the Grand Canonical ensemble. Two different types of monomers are considered. Depending on the solution pH, monomers A are weak acidic sites that can either be negatively charged or uncharged (as carboxylic groups), whereas monomers B are weak basic sites that can either be positively charged or uncharged (as amino groups). The influence of the chain stiffness, primary structure, and ionic concentration on the acid/base properties of the polyampholyte chains are systematically investigated. By adjusting the pH values, titration curves and then the fractions of positively and negatively ionized charged monomers are calculated. Stiffness influence is estimated by comparing two models of chain: a fully flexible and a rod-like polyampholyte. Different primary structures such as statistical (diblock, octablock, and alternating) and random polyampholytes are also considered. We demonstrate that the primary structure plays important roles in the acid/base properties as well as the charge distribution along the polymer backbone of a statistical rod-like polyampholyte. When flexible polyampholytes are considered, polyampholyte conformations promote the attractive electrostatic interactions between positively and negatively charged monomers, hence leading to more or less compact conformations and acid/base properties relatively different in comparison to the rod-like polyampholytes. Various conformations such as extended, globular, and pearl-necklace conformations are found in good agreement with the literature by adjusting the interaction parameter between monomers and monomer stoichiometry.

Nanoparticle adsorption on a weak polyelectrolyte. Stiffness, pH, charge mobility, and ionic concentration effects investigated by Monte Carlo simulations.

Monte Carlo simulations have been used to study two different models for a weak linear polyelectrolyte in the presence of nanoparticles: (i) a rodlike and (ii) a flexible polyelectrolytes. The use of simulated annealing has made it possible to simulate a polyelectrolyte chain in the presence of several nanoparticles by improving conformation sampling and avoiding multiple minima problems when dense conformations are produced. Nanoparticle distributions along the polymer backbone were analyzed versus the ionic concentration, polyelectrolyte stiffness, and nanoparticle surface charge. Titration curves were calculated and the influences of the ionic concentration, solution pH, and number of adsorbed nanoparticles on the acid/base polyelectrolyte properties have been systematically investigated. The subtle balance of attractive and repulsive interactions has been discussed, and some characteristic conformations are presented. The comparison of the two limit models provides a good representation of the stiffness influence on the complex formation. In some conditions, overcharging was obtained and presented with respect to both the polyelectrolyte and nanoparticle as the central element. Finally, the charge mobility influence along the polyelectrolyte backbone was investigated by considering annealed and quenched polyelectrolyte chains.

Modeling the adsorption and coagulation of fulvic acids on colloids by Brownian dynamics simulations.

Humic substances (HS) play an important role in the reactivity and transport of colloids in natural environments. In particular, the presence of fulvic acids (FA) in natural waters modifies the interactions between inorganic particles and biopolymers and makes difficult to predict their stability with regard to aggregation processes. In this study, Brownian dynamics (BD) modeling is applied to quantify the interactions between negatively charged FA and (i) a positively charged inorganic particle and (ii) a rigid neutral polysaccharide in aqueous solutions. Hematite and schizophyllan are respectively used as model colloids. Modeling the adsorption of FA at the hematite particle surface and on the polysaccharide is based on van der Waals attractive forces and electrostatic interactions. Possible applications of the model, however, are not restricted to this system and any interaction potential or colloidal particle can be considered. The competition between FA adsorption and FA homocoagulation in solution is studied as function of the solution ionic strength. Results show that, under the conditions used, the amount of adsorbed FA is largely controlled by the solution ionic strength. At low ionic strength the amount of adsorbed FA is limited by the electrostatic repulsion between FA at the colloid surfaces and FA monolayers are formed. By increasing the ionic strength the number of adsorbed FA is found to increase. At a sufficiently large ionic strength, however, FA coagulation in solution may strongly compete with FA adsorption at the hematite and polysaccharide surfaces. FA aggregates then adsorb at the colloid surfaces to form extended and porous structures. Results also suggest that FA adsorption and structure of the adsorbed layers are mainly driven by the complex interplay between electrostatic attractive and repulsive interactions.

Conformational changes and aggregation of alginic acid as determined by fluorescence correlation spectroscopy.

Insight into the conformations and aggregation of alginic acid was gained by measuring its diffusion coefficient at very dilute concentrations using fluorescence correlation spectroscopy. Both the pH and ionic strength (I) had an important influence on the diffusion coefficient of the polysaccharide. For pH, three effects were isolated: (i) below pH 4, the charge density decreased causing increased aggregation; (ii) between pH 4 and 8, a molecular expansion was observed with increasing pH, whereas (iii) above pH 8 some dissociation of the polymer was observed. Increasing I from 0.001 to 0.1 M resulted in a ca. 20% increase in the diffusion coefficient. By coupling these measurements to molar mass determinations obtained by size exclusion chromatography and monomer size estimations determined from ab initio calculations, it was possible to determine the radii of gyration via de Gennes renormalization theory. From diffusion coefficients and radii of gyration obtained as a function of ionic strength, persistence lengths (total, electrostatic, and intrinsic) were calculated from the Benoit-Doty relationship.

Effects of surface site distribution and dielectric discontinuity on the charging behavior of nanoparticles: a grand canonical Monte Carlo study.

The surface site distribution and the dielectric discontinuity effects on the charging process of a spherical nanoparticle (NP) have been investigated. It is well known that electrostatic repulsion between charges on neighbouring sites tends to decrease the effective charge of a NP. The situation is more complicated close to a dielectric breakdown, since here a charged site is not only interacting with its neighbours but also with its own image charge and the image charges of all its neighbours. Coexistence of opposite charges, titration sites positions, and pH dependence are systematically studied using a grand canonical Monte Carlo method. A Tanford and Kirkwood approach has been applied to describe the interaction potentials between explicit discrete ampholytic charging sites. Homogeneous, heterogeneous and patch site distributions were considered to reproduce the titration site distribution at the solid/solution interface of natural NPs. Results show that the charging process is controlled by the balance between Coulomb interactions and the reaction field through the solid-liquid interface. They also show that the site distribution plays a crucial role in the charging process. In patch distributions, charges accumulate at the perimeter of each patch due to finite size effects. When homogeneous and heterogeneous distributions are compared, three different charging regimes are obtained. In homogeneous and heterogeneous (with quite low polydispersity indexes) distributions, the effects of the NP dielectric constant on Coulomb interactions are counterbalanced by the reaction field and in this case, the dielectric breakdown has no significant effect on the charging process. This is not the case in patch distributions, where the dielectric breakdown plays a crucial role in the charging process.