Machine Learning to Predict Enzyme-Substrate Interactions in Elucidation of Synthesis Pathways: A Review.

Enzyme-substrate interactions play a fundamental role in elucidating synthesis pathways and synthetic biology, as they allow for the understanding of important aspects of a reaction. Establishing the interaction experimentally is a slow and costly process, which is why this problem has been addressed using computational methods such as molecular dynamics, molecular docking, and Monte Carlo simulations. Nevertheless, this type of method tends to be computationally slow when dealing with a large search space. Therefore, in recent years, methods based on artificial intelligence, such as support vector machines, neural networks, or decision trees, have been implemented, significantly reducing the computing time and covering vast search spaces. These methods significantly reduce the computation time and cover broad search spaces, rapidly reducing the number of interacting candidates, as they allow repetitive processes to be automated and patterns to be extracted, are adaptable, and have the capacity to handle large amounts of data. This article analyzes these artificial intelligence-based approaches, presenting their common structure, advantages, disadvantages, limitations, challenges, and future perspectives.

Saccharomyces cerevisiae biofactory to produce naringenin using a systems biology approach and a bicistronic vector expression strategy in flavonoid production.

IMPORTANCE: Flavonoids are a group of compounds generally produced by plants with proven biological activity, which have recently beeen recommended for the treatment and prevention of diseases and ailments with diverse causes. In this study, naringenin was produced in adequate amounts in yeast after in silico design. The four genes of the involved enzymes from several organisms (bacteria and plants) were multi-expressed in two vectors carrying each two genes linked by a short viral peptide sequence. The batch kinetic behavior of the product, substrate, and biomass was described at lab scale. The engineered strain might be used in a more affordable and viable bioprocess for industrial naringenin procurement.

Exploring the Spectrum of RHOBTB2 Variants Associated with Developmental Encephalopathy 64: A Case Series and Literature Review.

Background: Rho-related BTB domain-containing protein 2 (RHOBTB2) is a protein that interacts with cullin-3, a crucial E3 ubiquitin ligase for mitotic cell division. RHOBTB2 has been linked to early infantile epileptic encephalopathy, autosomal dominant type 64 (OMIM618004), in 34 reported patients. Methods: We present a case series of seven patients with RHOBTB2-related disorders (RHOBTB2-RD), including a description of a novel heterozygous variant. We also reviewed previously published cases of RHOBTB2-RD. Results: The seven patients had ages ranging from 2 years and 8 months to 26 years, and all had experienced seizures before the age of one (onset, 4-12 months, median, 4 months), including various types of seizures. All patients in this cohort also had a movement disorder (onset, 0.3-14 years, median, 1.5 years). Six of seven had a baseline movement disorder, and one of seven only had paroxysmal dystonia. Stereotypies were noted in four of six, choreodystonia in three of six, and ataxia in one case with multiple movement phenotypes at baseline. Paroxysmal movement disorders were observed in six of seven patients for whom carbamazepine or oxcarbazepine treatment was effective in controlling acute or paroxysmal movement disorders. Four patients had acute encephalopathic episodes at ages 4 (one patient) and 6 (three patients), which improved following treatment with methylprednisolone. Magnetic resonance imaging scans revealed transient fluid-attenuated inversion recovery abnormalities during these episodes, as well as myelination delay, thin corpus callosum, and brain atrophy. One patient had a novel RHOBTB2 variant (c.359G>A/p.Gly120Glu). Conclusion: RHOBTB2-RD is characterized by developmental delay or intellectual disability, early-onset seizures, baseline movement disorders, acute or paroxysmal motor phenomena, acquired microcephaly, and episodes of acute encephalopathy. Early onsets of focal dystonia, acute encephalopathic episodes, episodes of tongue protrusion, or peripheral vasomotor disturbances are important diagnostic clues. Treatment with carbamazepine or oxcarbazepine was found to be effective in controlling acute or paroxysmal movement disorders. Our study highlights the clinical features and treatment response of RHOBTB2-RD.

Genotype and Phenotype Characterization of Patients with Mucopolysaccharidosis IV-A in Chile.

Introduction: Morquio syndrome or mucopolysaccharidosis type IV-A (MPS IV-A) is an autosomal recessive disease caused by biallelic variants in the GALNS gene, encoding the lysosomal enzyme GalN6S, responsible for glycosaminoglycan keratan sulfate and chondroitin-6-sulfate degradation. Studies have shown that the degree of evolutionary and chemical divergence of missense variants in GalN6S when compared to ancestral amino acids is associated with the severity of the syndrome, suggesting a genotype-phenotype correlation. There is little information on Latin American patients with MPS IV-A that replicate these findings. This study aimed to characterize the phenotype and genotype from patients with MPS IV-A, who are under Enzyme Replacement Therapy at the Children's Neuropsychiatry Service of the Hospital Clínico San Borja Arriarán, Santiago, Chile, and to determine if there is any association between genotype and phenotype with those findings. Methods: Information was collected from medical charts, all patients went through a GalN6S enzymatic activity measurement in leukocytes from peripheral blood, and the GALNS gene was sequenced for all cases. Results: 12 patients with MPS IV-A were recruited, all patients presented multisystem involvement, mostly skeletal, and 75% of cases underwent surgical interventions, and cervical arthrodesis was the most frequent procedure. In regards of the genotype, the two most frequent variants were c.319+2T>C (n = 10, 41.66%) and p.(Arg386Cys) (n = 8, 33.33%), the first one was previously described in 2018 in a patient from Chile [Bochernitsan et al., 2018]. Conclusion: This is the first time that a genotype-phenotype correlation has been studied by analyzing the variants effect on the molecular structure of human GalN6S and the evolutionary conservation degree of affected residues in a cohort of patients in Chile. Albeit our work could not find statistically significant associations, we may infer that the evolutionary conservations of affected amino acids and the effect of variants on enzyme structure may play a main role. Further analyzes should consider a meta-analysis of published cases with genotype data and larger samples and include other variables that could provide more information. Finally, our data strongly suggest that variant c.319+2T>C could have a founder effect in Chilean patients with MPS IV-A.

Genome-Scale Metabolic Reconstruction, Non-Targeted LC-QTOF-MS Based Metabolomics Data, and Evaluation of Anticancer Activity of Cannabis sativa Leaf Extracts.

Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa, leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.

Enhancing Wound Healing: A Novel Topical Emulsion Combining CW49 Peptide and Lavender Essential Oil for Accelerated Regeneration and Antibacterial Protection.

Wound healing is a complex process involving blood cells, extracellular matrix, and parenchymal cells. Research on biomimetics in amphibian skin has identified the CW49 peptide from Odorrana grahami, which has been demonstrated to promote wound regeneration. Additionally, lavender essential oil exhibits anti-inflammatory and antibacterial activities. Given these considerations, we propose an innovative emulsion that combines the CW49 peptide with lavender oil. This novel formulation could serve as a potent topical treatment, potentially fostering the regeneration of damaged tissues and providing robust antibacterial protection for skin wounds. This study investigates the physicochemical properties, biocompatibility, and in vitro regenerative capacity of the active components and the emulsion. The results show that the emulsion possesses appropriate rheological characteristics for topical application. Both the CW49 peptide and lavender oil exhibit high viability in human keratinocytes, indicating their biocompatibility. The emulsion induces hemolysis and platelet aggregation, an expected behavior for such topical treatments. Furthermore, the lavender-oil emulsion demonstrates antibacterial activity against both Gram-positive and Gram-negative bacterial strains. Finally, the regenerative potential of the emulsion and its active components is confirmed in a 2D wound model using human keratinocytes. In conclusion, the formulated emulsion, which combines the CW49 peptide and lavender oil, shows great promise as a topical treatment for wound healing. Further research is needed to validate these findings in more advanced in vitro models and in vivo settings, potentially leading to improved wound-care management and novel therapeutic options for patients with skin injuries.

A Holistic Approach from Systems Biology Reveals the Direct Influence of the Quorum-Sensing Phenomenon on Pseudomonas aeruginosa Metabolism to Pyoverdine Biosynthesis.

Computational modeling and simulation of biological systems have become valuable tools for understanding and predicting cellular performance and phenotype generation. This work aimed to construct, model, and dynamically simulate the virulence factor pyoverdine (PVD) biosynthesis in Pseudomonas aeruginosa through a systemic approach, considering that the metabolic pathway of PVD synthesis is regulated by the quorum-sensing (QS) phenomenon. The methodology comprised three main stages: (i) Construction, modeling, and validation of the QS gene regulatory network that controls PVD synthesis in P. aeruginosa strain PAO1; (ii) construction, curating, and modeling of the metabolic network of P. aeruginosa using the flux balance analysis (FBA) approach; (iii) integration and modeling of these two networks into an integrative model using the dynamic flux balance analysis (DFBA) approximation, followed, finally, by an in vitro validation of the integrated model for PVD synthesis in P. aeruginosa as a function of QS signaling. The QS gene network, constructed using the standard System Biology Markup Language, comprised 114 chemical species and 103 reactions and was modeled as a deterministic system following the kinetic based on mass action law. This model showed that the higher the bacterial growth, the higher the extracellular concentration of QS signal molecules, thus emulating the natural behavior of P. aeruginosa PAO1. The P. aeruginosa metabolic network model was constructed based on the iMO1056 model, the P. aeruginosa PAO1 strain genomic annotation, and the metabolic pathway of PVD synthesis. The metabolic network model included the PVD synthesis, transport, exchange reactions, and the QS signal molecules. This metabolic network model was curated and then modeled under the FBA approximation, using biomass maximization as the objective function (optimization problem, a term borrowed from the engineering field). Next, chemical reactions shared by both network models were chosen to combine them into an integrative model. To this end, the fluxes of these reactions, obtained from the QS network model, were fixed in the metabolic network model as constraints of the optimization problem using the DFBA approximation. Finally, simulations of the integrative model (CCBM1146, comprising 1123 reactions and 880 metabolites) were run using the DFBA approximation to get (i) the flux profile for each reaction, (ii) the bacterial growth profile, (iii) the biomass profile, and (iv) the concentration profiles of metabolites of interest such as glucose, PVD, and QS signal molecules. The CCBM1146 model showed that the QS phenomenon directly influences the P. aeruginosa metabolism to PVD biosynthesis as a function of the change in QS signal intensity. The CCBM1146 model made it possible to characterize and explain the complex and emergent behavior generated by the interactions between the two networks, which would have been impossible to do by studying each system's individual components or scales separately. This work is the first in silico report of an integrative model comprising the QS gene regulatory network and the metabolic network of P. aeruginosa.

Multifunctional magnetoliposomes as drug delivery vehicles for the potential treatment of Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. Therefore, development of novel technologies and strategies to treat PD is a global health priority. Current treatments include administration of Levodopa, monoamine oxidase inhibitors, catechol-O-methyltransferase inhibitors, and anticholinergic drugs. However, the effective release of these molecules, due to the limited bioavailability, is a major challenge for the treatment of PD. As a strategy to solve this challenge, in this study we developed a novel multifunctional magnetic and redox-stimuli responsive drug delivery system, based on the magnetite nanoparticles functionalized with the high-performance translocating protein OmpA and encapsulated into soy lecithin liposomes. The obtained multifunctional magnetoliposomes (MLPs) were tested in neuroblastoma, glioblastoma, primary human and rat astrocytes, blood brain barrier rat endothelial cells, primary mouse microvascular endothelial cells, and in a PD-induced cellular model. MLPs demonstrated excellent performance in biocompatibility assays, including hemocompatibility (hemolysis percentages below 1%), platelet aggregation, cytocompatibility (cell viability above 80% in all tested cell lines), mitochondrial membrane potential (non-observed alterations) and intracellular ROS production (negligible impact compared to controls). Additionally, the nanovehicles showed acceptable cell internalization (covered area close to 100% at 30 min and 4 h) and endosomal escape abilities (significant decrease in lysosomal colocalization after 4 h of exposure). Moreover, molecular dynamics simulations were employed to better understand the underlying translocating mechanism of the OmpA protein, showing key findings regarding specific interactions with phospholipids. Overall, the versatility and the notable in vitro performance of this novel nanovehicle make it a suitable and promising drug delivery technology for the potential treatment of PD.

Omics approaches to understand cocoa processing and chocolate flavor development: A review.

The global market of chocolate has increased worldwide during the last decade and is expected to reach a value of USD 200 billion by 2028. Chocolate is obtained from different varieties of Theobroma cacao L, a plant domesticated more than 4000 years ago in the Amazon rainforest. However, chocolate production is a complex process requiring extensive post-harvesting, mainly involving cocoa bean fermentation, drying, and roasting. These steps have a critical impact on chocolate quality. Standardizing and better understanding cocoa processing is, therefore, a current challenge to boost the global production of high-quality cocoa worldwide. This knowledge can also help cocoa producers improve cocoa processing management and obtain a better chocolate. Several recent studies have been conducted to dissect cocoa processing via omics analysis. A vast amount of data has been produced regarding omics studies of cocoa processing performed worldwide. This review systematically analyzes the current data on cocoa omics using data mining techniques and discusses opportunities and gaps for cocoa processing standardization from this data. First, we observed a recurrent report in metagenomics studies of species of the fungi genus Candida and Pichia as well as bacteria from the genus Lactobacillus, Acetobacter, and Bacillus. Second, our analyzes of the available metabolomics data showed clear differences in the identified metabolites in cocoa and chocolate from different geographical origin, cocoa type, and processing stage. Finally, our analysis of peptidomics data revealed characteristic patterns in the gathered data including higher diversity and lower size distribution of peptides in fine-flavor cocoa. In addition, we discuss the current challenges in cocoa omics research. More research is still required to fill gaps in central matter in chocolate production as starter cultures for cocoa fermentation, flavor evolution of cocoa, and the role of peptides in the development of specific flavor notes. We also offer the most comprehensive collection of multi-omics data in cocoa processing gathered from different research articles.

Design and Assembly of a Biofactory for (2S)-Naringenin Production in Escherichia coli: Effects of Oxygen Transfer on Yield and Gene Expression.

The molecule (2S)-naringenin is a scaffold molecule with several nutraceutical properties. Currently, (2S)-naringenin is obtained through chemical synthesis and plant isolation. However, these methods have several drawbacks. Thus, heterologous biosynthesis has emerged as a viable alternative to its production. Recently, (2S)-naringenin production studies in Escherichia coli have used different tools to increase its yield up to 588 mg/L. In this study, we designed and assembled a bio-factory for (2S)-naringenin production. Firstly, we used several parametrized algorithms to identify the shortest pathway for producing (2S)-naringenin in E. coli, selecting the genes phenylalanine ammonia lipase (pal), 4-coumarate: CoA ligase (4cl), chalcone synthase (chs), and chalcone isomerase (chi) for the biosynthetic pathway. Then, we evaluated the effect of oxygen transfer on the production of (2S)-naringenin at flask (50 mL) and bench (4 L culture) scales. At the flask scale, the agitation rate varied between 50 rpm and 250 rpm. At the bench scale, the dissolved oxygen was kept constant at 5% DO (dissolved oxygen) and 40% DO, obtaining the highest (2S)-naringenin titer (3.11 ± 0.14 g/L). Using genome-scale modeling, gene expression analysis (RT-qPCR) of oxygen-sensitive genes was obtained.

Evaluation of roasting and storage conditions as a strategy to improve the sensory characteristics and shelf life of coffee.

Coffee is one of the most consumed products worldwide. Among the varieties of this product, specialty coffee is a type of coffee that has been growing in the world market. This paper aims to assess the effects that the conditions derived from coffee roasting at different altitude levels have on the quality of the product. It was discovered that processing coffee at a higher altitude level yielded a smaller increase in bitterness. This led to a better Specialty Coffee Association (SCA) score in cupping and, consequently, to better preservation of the coffee quality. The storage time affected the aroma by associating roaster aromas with older coffees. Although the assessed origins had the same NIR spectra, differences in peak intensity lead to variations in the flavor and aroma of the coffee. Furthermore, although green beans prolong quality allowing a SCA score of 84.73 ± 2.81 after 4 months of storage, roasted coffee at higher altitudes could also maintain the quality between production and consumption (SCA score of 80.22 ± 0.91 after 2 months). Finally, this research found that the instrumental equipment helped to find minor changes in the sensorial profile, and with these changes correlated with the sensorial panel, the best conditions to preserve coffee quality were found.

Identification of Active Compounds against Melanoma Growth by Virtual Screening for Non-Classical Human DHFR Inhibitors.

Antifolates such as methotrexate (MTX) have been largely known as anticancer agents because of their role in blocking nucleic acid synthesis and cell proliferation. Their mechanism of action lies in their ability to inhibit enzymes involved in the folic acid cycle, especially human dihydrofolate reductase (hDHFR). However, most of them have a classical structure that has proven ineffective against melanoma, and, therefore, inhibitors with a non-classical lipophilic structure are increasingly becoming an attractive alternative to circumvent this clinical resistance. In this study, we conducted a protocol combining virtual screening (VS) and cell-based assays to identify new potential non-classical hDHFR inhibitors. Among 173 hit compounds identified (average logP = 3.68; average MW = 378.34 Da), two-herein, called C1 and C2-exhibited activity against melanoma cell lines B16 and A375 by MTT and Trypan-Blue assays. C1 showed cell growth arrest (39% and 56%) and C2 showed potent cytotoxic activity (77% and 51%) in a dose-dependent manner. The effects of C2 on A375 cell viability were greater than MTX (98% vs 60%) at equivalent concentrations and times. Our results indicate that the integrated in silico/in vitro approach provided a benchmark to identify novel promising non-classical DHFR inhibitors showing activity against melanoma cells.

Formulation of a novel antibacterial topical treatment based on Magnetite-Buforin-II-silver nanobioconjugates.

Community acquired infections caused by Meticillin-resistant Staphylococcus aureus (MRSA) have become a growing concern due to its impact on the world public health. This microorganism is a commonly spreading pathogen associated predominantly with skin infections and connected to other more severe conditions (septic shock, and generalized infection). The lack of highly effective antibiotics and treatments to control skin infections with S. aureus has led to the search of novel therapies using alternative agents such as antimicrobial peptides (AMPs). In order to obtain a viable administration route to counteract superficial skin infections (impetigo, abscesses, furuncles, and cellulitis), a topical formulation based on Magnetite-Buforin-II-silver nanobioconjugates as active antibacterial agents was designed by their dispersion in O/W concentrated emulsions. The prepared topical characterization indicated that O/W emulsions were stable in time, the droplets size remained within the appropriate values (∼1 µm) and their rheological properties, such as pseudoplastic and shear-thinning behavior, remained unchanged for up to 3 months. Additionally, hemolysis and platelet aggregation tests were acceptable (i.e., 14.72 ± 2.62% and 8.06 ± 2.90%, respectively) in compliance with the ISO-10993 standard. Furthermore, the treatment reduced significantly (p < 0.0001) the growth of both clinical isolated MRSA and wild Type S. aureus strains as evidenced by the contact diffusion method. These results are important in the context of proposing new alternatives that allow manage effectively the threat posed by the antibiotic resistant bacterial strains, which jeopardize the lives of thousands of people every year.

The new world of philanthropy: How changing financial behavior, public policies, and COVID-19 affect nonprofit fundraising and marketing.

Evolving financial behavior, an unpredictable public policy atmosphere, and an unparalleled global pandemic have collaborated to disrupt nonprofit fundraising. The COVID-19 pandemic alone exacerbated consumer demands for nonprofit services while curtailing nonprofit organizations' ability to fundraise. Without fundraising, nonprofit organizations cannot achieve their mission or support their causes, leading to a precarious situation for societal well-being. Meanwhile, consumers are changing their financial behaviors, with younger generations often going cashless. At the same time, governments continue to change policies that affect nonprofit organizations. In keeping with the transformative consumer research movement, the present study provides a conceptual framework for the state of nonprofit fundraising amid the challenges associated with changes in financial behavior and public policy, coupled with the effects of the global pandemic. Marketing strategies for fundraising success are presented to aid nonprofits going forward and serve societal interests.

Lipidomic profiling of bioactive lipids during spontaneous fermentations of fine-flavor cocoa.

The impact of cocoa lipid content on chocolate quality has been extensively described. Nevertheless, few studies have elucidated the cocoa lipid composition and their bioactive properties, focusing only on specific lipids. In the present study the lipidome of fine-flavor cocoa fermentation was analyzed using LC-MS-QTOF and a Machine Learning model to assess potential bioactivity was developed. Our results revealed that the cocoa lipidome, comprised mainly of fatty acyls and glycerophospholipids, remains stable during fine-flavor cocoa fermentations. Also, several Machine Learning algorithms were trained to explore potential biological activity among the identified lipids. We found that K-Nearest Neighbors had the best performance. This model was used to classify the identified lipids as bioactive or non-bioactive, nominating 28 molecules as potential bioactive lipids. None of these compounds have been previously reported as bioactive. Our work is the first untargeted lipidomic study and systematic effort to investigate potential bioactivity in fine-flavor cocoa lipids.

Novel covalent and non-covalent complex-based pharmacophore models of SARS-CoV-2 main protease (Mpro) elucidated by microsecond MD simulations.

As the world enters its second year of the pandemic caused by SARS-CoV-2, intense efforts have been directed to develop an effective diagnosis, prevention, and treatment strategies. One promising drug target to design COVID-19 treatments is the SARS-CoV-2 Mpro. To date, a comparative understanding of Mpro dynamic stereoelectronic interactions with either covalent or non-covalent inhibitors (depending on their interaction with a pocket called S1' or oxyanion hole) has not been still achieved. In this study, we seek to fill this knowledge gap using a cascade in silico protocol of docking, molecular dynamics simulations, and MM/PBSA in order to elucidate pharmacophore models for both types of inhibitors. After docking and MD analysis, a set of complex-based pharmacophore models was elucidated for covalent and non-covalent categories making use of the residue bonding point feature. The highest ranked models exhibited ROC-AUC values of 0.93 and 0.73, respectively for each category. Interestingly, we observed that the active site region of Mpro protein-ligand complex undergoes large conformational changes, especially within the S2 and S4 subsites. The results reported in this article may be helpful in virtual screening (VS) campaigns to guide the design and discovery of novel small-molecule therapeutic agents against SARS-CoV-2 Mpro protein.

Teleworking and technostress: early consequences of a COVID-19 lockdown.

This paper analyzes teleworkers' technostress evolution over time, as well as its effects on these individuals' work-related well-being over time. The proposed research model was tested using a survey-based longitudinal study with individuals that forcibly moved to teleworking in the context of a COVID-19 lockdown at two points in time (T0 and T1). Results indicate that two techno-stressors (work-home conflict and work overload) generated strain in teleworkers, which in turn decreased their satisfaction with telework and perceived job performance. In addition, teleworkers experienced two types of enduring technostress: synchronous effect (i.e., stressors generating strain at T1), and a cumulative reverse causation effect (i.e., strain at T0 has an effect on stressors at T1). These findings contribute to cognition, work, and technology literature by providing a more complete understanding of teleworkers' technostress and its possible cumulative effects over time. Practical insights for managing technostress when moving to and remaining in teleworking are provided.