EspalomaCharge: Machine Learning-Enabled Ultrafast Partial Charge Assignment.

Atomic partial charges are crucial parameters in molecular dynamics simulation, dictating the electrostatic contributions to intermolecular energies and thereby the potential energy landscape. Traditionally, the assignment of partial charges has relied on surrogates of ab initio semiempirical quantum chemical methods such as AM1-BCC and is expensive for large systems or large numbers of molecules. We propose a hybrid physical/graph neural network-based approximation to the widely popular AM1-BCC charge model that is orders of magnitude faster while maintaining accuracy comparable to differences in AM1-BCC implementations. Our hybrid approach couples a graph neural network to a streamlined charge equilibration approach in order to predict molecule-specific atomic electronegativity and hardness parameters, followed by analytical determination of optimal charge-equilibrated parameters that preserve total molecular charge. This hybrid approach scales linearly with the number of atoms, enabling for the first time the use of fully consistent charge models for small molecules and biopolymers for the construction of next-generation self-consistent biomolecular force fields. Implemented in the free and open source package EspalomaCharge, this approach provides drop-in replacements for both AmberTools antechamber and the Open Force Field Toolkit charging workflows, in addition to stand-alone charge generation interfaces. Source code is available at https://github.com/choderalab/espaloma-charge.

Combined Strategy Using High Hydrostatic Pressure, Temperature and Enzymatic Hydrolysis for Development of Fibre-Rich Ingredients from Oat and Wheat By-Products.

Wheat bran (WB) and oat hull (OH) are two interesting undervalued cereal processing sources rich in total dietary fibre (TDF) and other associated bioactive compounds, such as ß-glucans and polyphenols. The aim of this study was to optimise a combination chemical (enzymes) and physical (high hydrostatic pressure-temperature) strategies to increase the bioaccessibility of bioactive compounds naturally bound to the bran and hull outer layers. WB and OH were hydrolysed using food-grade enzymes (UltraFloXL and Viscoferm, for WB and OH, respectively) in combination with HPP at different temperatures (40, 50, 60 and 70 °C) and hydrolysis either before or after HPP. Proximal composition, phytic acid, ß-glucans, total phenolics (TPs) and total antioxidant activity (TAC) were evaluated to select the processing conditions for optimal nutritional and bioactive properties of the final ingredients. The application of the hydrolysis step after the HPP treatment resulted in lower phytic acid levels in both matrices (WB and OH). On the other hand, the release of ß-glucan was more effective at the highest temperature (70 °C) used during pressurisation. After the treatment, the TP content ranged from 756.47 to 1395.27 µmol GAE 100 g-1 in WB, and OH showed values from 566.91 to 930.45 µmol GAE 100 g-1. An interaction effect between the temperature and hydrolysis timing (applied before or after HPP) was observed in the case of OH. Hydrolysis applied before HPP was more efficient in releasing OH TPs at lower HPP temperatures (40-50 °C); meanwhile, at higher HPP temperatures (60-70 °C), hydrolysis yielded higher TP values when applied after HPP. This effect was not observed in WB, where the hydrolysis was more effective before HPP. The TP results were significantly correlated with the TAC values. The results showed that the application of optimal process conditions (hydrolysis before HPP at 60 or 70 °C for WB; hydrolysis after HPP at 70 °C for OH) can increase the biological value of the final ingredients obtained.

Identifying and Overcoming the Sampling Challenges in Relative Binding Free Energy Calculations of a Model Protein:Protein Complex.

Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on protein:protein binding affinities, but these calculations can involve sampling challenges due to the complex networks of protein and water interactions frequently present in protein:protein interfaces. We investigate these challenges by extending a graphics processing unit (GPU)-accelerated open-source relative free energy calculation package (Perses) to predict the impact of amino acid mutations on protein:protein binding. Using the well-characterized model system barnase:barstar, we describe analyses for identifying and characterizing sampling problems in protein:protein relative free energy calculations. We find that mutations with sampling problems often involve charge-changes, and inadequate sampling can be attributed to slow degrees of freedom that are mutation-specific. We also explore the accuracy and efficiency of current state-of-the-art approaches─alchemical replica exchange and alchemical replica exchange with solute tempering─for overcoming relevant sampling problems. By employing sufficiently long simulations, we achieve accurate predictions (RMSE 1.61, 95% CI: [1.12, 2.11] kcal/mol), with 86% of estimates within 1 kcal/mol of the experimentally determined relative binding free energies and 100% of predictions correctly classifying the sign of the changes in binding free energies. Ultimately, we provide a model workflow for applying protein mutation free energy calculations to protein:protein complexes, and importantly, catalog the sampling challenges associated with these types of alchemical transformations. Our free open-source package (Perses) is based on OpenMM and is available at https://github.com/choderalab/perses.

Antioxidant, Immunostimulatory, and Anticancer Properties of Hydrolyzed Wheat Bran Mediated through Macrophages Stimulation.

Previous studies demonstrated that enzymatic hydrolysis enhances wheat bran (WB) biological properties. This study evaluated the immunostimulatory effect of a WB hydrolysate (HYD) and a mousse enriched with HYD (MH) before and after in vitro digestion on murine and human macrophages. The antiproliferative activity of the harvested macrophage supernatant on colorectal cancer (CRC) cells was also analyzed. MH showed significantly higher content than control mousse (M) in soluble poly- and oligosaccharides (OLSC), as well as total soluble phenolic compounds (TSPC). Although in vitro gastrointestinal digestion slightly reduced the TSPC bioaccessibility of MH, ferulic acid (FA) levels remained stable. HYD showed the highest antioxidant activity followed by MH, which demonstrated a greater antioxidant activity before and after digestion as compared with M. RAW264.7 and THP-1 cells released the highest amounts of pro-inflammatory cytokines after being treated with 0.5 mg/mL of digested WB samples. Treatment with digested HYD-stimulated RAW264.7 supernatant for 96 h showed the most anticancer effect, and spent medium reduced cancer cell colonies more than direct WB sample treatments. Although a lack of inner mitochondrial membrane potential alteration was found, increased Bax:Bcl-2 ratio and caspase-3 expression suggested activation of the mitochondrial apoptotic pathway when CRC cells were treated with macrophage supernatants. Intracellular reactive oxygen species (ROS) were positively correlated with the cell viability in CRC cells exposed to RAW264.7 supernatants (r = 0.78, p < 0.05) but was not correlated in CRC cells treated with THP-1 conditioned media. Supernatant from WB-stimulated THP-1 cells may be able to stimulate ROS production in HT-29 cells, leading to a decrease of viable cells in a time-dependent manner. Therefore, our present study revealed a novel anti-tumour mechanism of HYD through the stimulation of cytokine production in macrophages and the indirect inhibition of cell proliferation, colony formation, and activation of pro-apoptotic proteins expression in CRC cells.

Identifying and overcoming the sampling challenges in relative binding free energy calculations of a model protein:protein complex.

Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on protein:protein binding affinities, but these calculations can involve sampling challenges due to the complex networks of protein and water interactions frequently present in protein:protein interfaces. We investigate these challenges by extending a GPU-accelerated open-source relative free energy calculation package (Perses) to predict the impact of amino acid mutations on protein:protein binding. Using the well-characterized model system barnase:barstar, we describe analyses for identifying and characterizing sampling problems in protein:protein relative free energy calculations. We find that mutations with sampling problems often involve charge-changes, and inadequate sampling can be attributed to slow degrees of freedom that are mutation-specific. We also explore the accuracy and efficiency of current state-of-the-art approaches-alchemical replica exchange and alchemical replica exchange with solute tempering-for overcoming relevant sampling problems. By employing sufficiently long simulations, we achieve accurate predictions (RMSE 1.61, 95% CI: [1.12, 2.11] kcal/mol), with 86% of estimates within 1 kcal/mol of the experimentally-determined relative binding free energies and 100% of predictions correctly classifying the sign of the changes in binding free energies. Ultimately, we provide a model workflow for applying protein mutation free energy calculations to protein:protein complexes, and importantly, catalog the sampling challenges associated with these types of alchemical transformations. Our free open-source package (Perses) is based on OpenMM and available at https://github.com/choderalab/perses .

Twin-Screw Extrusion as Hydrothermal Technology for the Development of Gluten-Free Teff Flours: Effect on Antioxidant, Glycaemic Index and Techno-Functional Properties.

Gluten-free products (GFP) currently are the fastest-growing category of baked goods probably due to the high worldwide incidence of celiac disease (CD). Refined rice is one of the most used cereal flour for GFP development, due to its high content in starch and good technological aptitude. However, its low content in fibre, protein and minerals has awakened a recent interest as alternative to balance the GF flour formulas. Teff is a cereal with high levels in fibre and antioxidants compounds but the lack of gluten results in very limited techno-functional properties. Extrusion is a thermal technology that allows to combine flours, overcoming negative impacts on quality characteristics. This study evaluated the effect of twin-screw extruder on rice-teff (white and brown) mixtures with different teff concentrations (25, 50 and 75%) on their antioxidant, glycaemic index and techno-functional properties. The results showed than the high shear−temperature process produced important modifications on the flour, which were confirmed using scanning electron microscopy (SEM). Significant increases in total dietary fibre (16 to 100% increase) were observed in teff containing flours, due to carbohydrate−lipid−protein complexes, which lead to resistant starch, with no significant increase in rice flour. Hydration and pasting properties were significantly (p > 0.05) affected by extrusion, and the effect was related to the concentration of teff used. The thermal process showed a decrease in total phenol (TP) content for rice; however, extrusion enhanced the release of total phenol in rice-teff blends, which was reflected on the antioxidant activities of blend flours, especially those prepared with brown teff.

End-to-end differentiable construction of molecular mechanics force fields.

Molecular mechanics (MM) potentials have long been a workhorse of computational chemistry. Leveraging accuracy and speed, these functional forms find use in a wide variety of applications in biomolecular modeling and drug discovery, from rapid virtual screening to detailed free energy calculations. Traditionally, MM potentials have relied on human-curated, inflexible, and poorly extensible discrete chemical perception rules (atom types) for applying parameters to small molecules or biopolymers, making it difficult to optimize both types and parameters to fit quantum chemical or physical property data. Here, we propose an alternative approach that uses graph neural networks to perceive chemical environments, producing continuous atom embeddings from which valence and nonbonded parameters can be predicted using invariance-preserving layers. Since all stages are built from smooth neural functions, the entire process-spanning chemical perception to parameter assignment-is modular and end-to-end differentiable with respect to model parameters, allowing new force fields to be easily constructed, extended, and applied to arbitrary molecules. We show that this approach is not only sufficiently expressive to reproduce legacy atom types, but that it can learn to accurately reproduce and extend existing molecular mechanics force fields. Trained with arbitrary loss functions, it can construct entirely new force fields self-consistently applicable to both biopolymers and small molecules directly from quantum chemical calculations, with superior fidelity than traditional atom or parameter typing schemes. When adapted to simultaneously fit partial charge models, espaloma delivers high-quality partial atomic charges orders of magnitude faster than current best-practices with low inaccuracy. When trained on the same quantum chemical small molecule dataset used to parameterize the Open Force Field ("Parsley") openff-1.2.0 small molecule force field augmented with a peptide dataset, the resulting espaloma model shows superior accuracy vis-á-vis experiments in computing relative alchemical free energy calculations for a popular benchmark. This approach is implemented in the free and open source package espaloma, available at https://github.com/choderalab/espaloma.

Sprouting and Hydrolysis as Biotechnological Tools for Development of Nutraceutical Ingredients from Oat Grain and Hull.

Oat consumption has increased during the last decade because of the health benefits associated with its soluble dietary fiber (ß-glucan), functional proteins, lipids, and the presence of specific phytochemicals, such as avenanthramides. Oat is consumed mainly as whole grain, and the hull (seed coat), comprising 25-35% of the entire grain, is removed, generating a large amount of waste/by-product from the milling industry. The objective of this study was to evaluate the use of biotechnological strategies, such as sprouting for oat grain (OG) and hydrolysis for oat hull (OH), to enhance antioxidant and anti-inflammatory properties and lower the glycemic index (GI). Sprouting produced significant (p ≤ 0.05) increases in free (32.10 to 76.62 mg GAE (100 g)-1) and bound phenols (60.45 to 124.36 mg GAE (100 g)-1), increasing significantly (p ≤ 0.05) the avenanthramide (2c, 2p and 2f) soluble phenolic alkaloid content and anti-inflammatory properties of OG. On the other hand, the hydrolysis of OH using Viscoferm (EH2-OH) and Ultraflo XL (EH21-OH) increased by 4.5 and 5-fold the release of bound phenols, respectively; meanwhile, the use of Viscoferm increased the 4.55-fold soluble ß-glucan content in OH, reaching values close to those of OG (4.04 vs. 4.46 g (100 g)-1). The study shows the potential of both strategies to enhance the nutritional and bioactive properties of OG and OH and describes these processes as feasible for the industry to obtain an ingredient with high antioxidant and anti-inflammatory activities. Single or combined biotechnological tools can be used on oat grains and hulls to provide nutraceutical ingredients.

Impact of Protein Content on the Antioxidants, Anti-Inflammatory Properties and Glycemic Index of Wheat and Wheat Bran.

Conventional wheat milling generates important volumes of wheat bran (WB), which is a concentrated source of polyphenols and insoluble fiber. In terms of health benefits and based on epidemiological and experimental evidence, these compounds contribute to reducing the risk of certain chronic pathologies. Protein concentration is the main quality factor conditioning wheat use in the agroindustry. When turning waste into feasible resources, it is essential to evaluate the variability of the raw material. The aim of this study was the evaluation of the impact of protein content in the valorization of WB based on its antioxidants, anti-inflammatory properties and glycemic index (GI). A significantly (p ≤ 0.05) lower content of phenolic compounds was found in the whole grain (WG) fractions, both free (FP) and bound (BP), as compared to the WB phenolic fractions, differences that ranged from 4- to 6-fold (538 to 561 mg GAE 100 g-1 in WG vs. 1027 to 1236 in WB mg GAE 100 g-1 in FP and 2245 to 2378 vs. 6344 to 7232 mg GAE 100 g-1 in BP). A significant (p ≤ 0.05) effect of the protein content on the resulting phenolic content and antioxidant capacity was observed, especially in WG, but also in WB, although in the latter a significant (p ≤ 0.05) negative correlation was observed, and increasing the protein content resulted in decreasing total phenolic content, antioxidants, and ferric-reducing capacities, probably due to their different types of proteins. The highest protein content in WB produced a significant (p ≤ 0.05) reduction in GI value, probably due to the role of protein structure in protecting starch from gelatinization, along with phytic acid, which may bind to proteins closely associated to starch and chelate calcium ions, required for α-amylase activity. A significant (p ≤ 0.05) effect of the protein content on the GI was also found, which may be explained by the structural effect of the proteins associated with starch, reducing the GI (21.64). The results obtained show the importance of segregation of WB in valorization strategies in order to increase the efficiency of the processes.

Bioprocessed Wheat Ingredients: Characterization, Bioaccessibility of Phenolic Compounds, and Bioactivity During in vitro Digestion.

To enlarge the applications of whole wheat grain (WWG) and wheat bran (WB) as functional ingredients in foodstuffs that can promote human health, researchers have explored bioprocessing approaches to improve the bioaccessibility of phenolic compounds from these food matrices and, subsequently, their biological effects. The objective of this study was to compare the composition in nutrients, anti-nutrients, and bioactive compounds of WWG and WB, and their respective bioprocessed products: sprouted wheat (GERM) and WB hydrolysate (stabilized by spray-drying [SPD] and microencapsulated [MEC]). In addition, to evaluate the functional properties of these ingredients, the bioaccessibility of phenolic compounds and their potential antioxidant and anti-inflammatory activities were monitored in different digestion steps. GERM had increased amounts of insoluble dietary fiber, higher diversity of oligosaccharides, and higher concentration of monosaccharides, free phosphorous, and phenolic compounds than WWG. SPD had improved content of soluble dietary fiber, oligosaccharides, monosaccharides, free phosphorous, and phenolic compounds (vs. WB), whereas MEC was mainly composed of protein and had nearly 2-fold lower content of SPD components. All the ingredients showed lower amounts of phytic acid as compared with raw materials. In all samples, hydroxycinnamic acids were the most representative polyphenols followed by minor amounts of hydroxybenzoic acids and flavonoids. Gastrointestinal digestion of GERM, SPD, and MEC revealed high stability of total phenolic compounds in both gastric and intestinal phases. Hydroxycinnamic acids were the most bioaccessible compounds during digestion among the three bioprocessed wheat ingredients studied, although their bioaccessibility varied across ingredients. In this sense, the bioaccessibility of ferulic acid (FA) derivatives increased in GERM with progression of the digestion, while it was reduced in SPD and MEC up to the end of the intestinal phase. Microencapsulation of SPD with pea protein led to generally to lower bioaccessible amounts of phenolic acids. Comparison analysis of biological effects highlighted SPD for its most potent antioxidant effects in the gastrointestinal tract (3 out 4 antioxidant parameters with highest values), while no clear differences were observed with regard to in vitro anti-inflammatory activity. Overall, these results support the potential application of GERM, SPD, and MEC as functional and nutraceutical ingredients.