Vibrio natriegens genome-scale modeling reveals insights into halophilic adaptations and resource allocation.

Vibrio natriegens is a Gram-negative bacterium with an exceptional growth rate that has the potential to become a standard biotechnological host for laboratory and industrial bioproduction. Despite this burgeoning interest, the current lack of organism-specific qualitative and quantitative computational tools has hampered the community's ability to rationally engineer this bacterium. In this study, we present the first genome-scale metabolic model (GSMM) of V. natriegens. The GSMM (iLC858) was developed using an automated draft assembly and extensive manual curation and was validated by comparing predicted yields, central metabolic fluxes, viable carbon substrates, and essential genes with empirical data. Mass spectrometry-based proteomics data confirmed the translation of at least 76% of the enzyme-encoding genes predicted to be expressed by the model during aerobic growth in a minimal medium. iLC858 was subsequently used to carry out a metabolic comparison between the model organism Escherichia coli and V. natriegens, leading to an analysis of the model architecture of V. natriegens' respiratory and ATP-generating system and the discovery of a role for a sodium-dependent oxaloacetate decarboxylase pump. The proteomics data were further used to investigate additional halophilic adaptations of V. natriegens. Finally, iLC858 was utilized to create a Resource Balance Analysis model to study the allocation of carbon resources. Taken together, the models presented provide useful computational tools to guide metabolic engineering efforts in V. natriegens.

Genetic Modifications in Bacteria for the Degradation of Synthetic Polymers: A Review.

Synthetic polymers, commonly known as plastics, are currently present in all aspects of our lives. Although they are useful, they present the problem of what to do with them after their lifespan. There are currently mechanical and chemical methods to treat plastics, but these are methods that, among other disadvantages, can be expensive in terms of energy or produce polluting gases. A more environmentally friendly alternative is recycling, although this practice is not widespread. Based on the practice of the so-called circular economy, many studies are focused on the biodegradation of these polymers by enzymes. Using enzymes is a harmless method that can also generate substances with high added value. Novel and enhanced plastic-degrading enzymes have been obtained by modifying the amino acid sequence of existing ones, especially on their active site, using a wide variety of genetic approaches. Currently, many studies focus on the common aim of achieving strains with greater hydrolytic activity toward a different range of plastic polymers. Although in most cases the depolymerization rate is improved, more research is required to develop effective biodegradation strategies for plastic recycling or upcycling. This review focuses on a compilation and discussion of the most important research outcomes carried out on microbial biotechnology to degrade and recycle plastics.

Genome sequence analysis and characterization of Bacillus altitudinis B12, a polylactic acid- and keratin-degrading bacterium.

Keratin-rich wastes, mainly in the form of feathers, are recalcitrant residues generated in high amounts as by-products in chicken farms and food industry. Polylactic acid (PLA) is the second most common biodegradable polymer found in commercial plastics, which is not easily degraded by microbial activity. This work reports the 3.8-Mb genome of Bacillus altitudinis B12, a highly efficient PLA- and keratin-degrading bacterium, with potential for environmental friendly biotechnological applications in the feed, fertilizer, detergent, leather, and pharmaceutical industries. The whole genome sequence of B. altitudinis B12 revealed that this strain (which had been previously misclassified as Bacillus pumilus B12) is closely related to the B. altitudinis strains ER5, W3, and GR-8. A total of 4056 coding sequences were annotated using the RAST server, of which 2484 are core genes of the pan genome of B. altitudinis and 171 are unique to this strain. According to the sequence analysis, B. pumilus B12 has a predicted secretome of 353 proteins, among which a keratinase and a PLA depolymerase were identified by sequence analysis. The presence of these two enzymes could explain the characterized PLA and keratin biodegradation capability of the strain.

Multi-Omics Analysis Revealed Increased De Novo Synthesis of Serine and Lower Activity of the Methionine Cycle in Breast Cancer Cell Lines.

A pipeline for metabolomics, based on UPLC-ESI-MS, was tested on two malignant breast cancer cell lines of the sub-types ER(+), PR(+), and HER2(3+) (MCF-7 and BCC), and one non-malignant epithelial cancer cell line (MCF-10A). This allowed us to quantify 33 internal metabolites, 10 of which showed a concentration profile associated with malignancy. Whole-transcriptome RNA-seq was also carried out for the three mentioned cell lines. An integrated analysis of metabolomics and transcriptomics was carried out using a genome-scale metabolic model. Metabolomics revealed the depletion of several metabolites that have homocysteine as a precursor, which was consistent with the lower activity of the methionine cycle caused by lower expression of the AHCY gene in cancer cell lines. Increased intracellular serine pools in cancer cell lines appeared to result from the over-expression of PHGDH and PSPH, which are involved in intracellular serine biosynthesis. An increased concentration of pyroglutamic acid in malignant cells was linked to the overexpression of the gene CHAC1.

Contribution of branched chain amino acids to energy production and mevalonate synthesis in cancer cells.

Leucine, isoleucine and valine, known as branched chain amino acids (BCAAs), have been reported to be degraded by different cancer cells, and their biodegradation pathways have been suggested as anticancer targets. However, the mechanisms by which the degradation of BCAAs could support the growth of cancer cells remains unclear. In this work, 13C experiments have been carried out in order to elucidate the metabolic role of BCAA degradation in two breast cancer cell lines (MCF-7 and BCC). The results revealed that up to 36% of the energy production via respiration by MCF-7 cells was supported by the degradation of BCAAs. Also, 67% of the mevalonate (the precursor of cholesterol) synthesized by the cells was coming from the degradation of leucine. The results were lower for BCC cells (14 and 30%, respectively). The non-tumorigenic epythelial cell line MCF-10A was used as a control, showing that 10% of the mitochondrial acetyl-CoA comes from the degradation of BCAAs and no mevalonate production. Metabolic flux analysis around the mevalonate node, also revealed that significant amounts of acetoacetate are being produced from BCAA derived carbon, which could be at the source of lipid synthesis. From these results we can conclude that the degradation of BCAAs is an important energy and carbon source for the proliferation of some cancer cells and its therapeutic targeting could be an interesting option.

Elucidating the key environmental parameters during the production of ectoines from biogas by mixed methanotrophic consortia.

Anaerobic digestion (AD) is a robust biotechnology for the valorisation of organic waste into biogas. However, the rapid decrease in renewable electricity prices requires alternative uses of biogas. In this context, the engineering of innovative platforms for the bio-production of chemicals from CH4 has recently emerged. The extremolyte and osmoprotectant ectoine, with a market price of ~1000€/Kg, is the industrial flagship of CH4-based bio-chemicals. This work aimed at optimizing the accumulation of ectoines using mixed microbial consortia enriched from saline environments (a salt lagoon and a salt river) and activated sludge, and biogas as feedstock. The influence of NaCl (0, 3, 6, 9 and 12 %) and Na2WO4 (0, 35 and 70 µg L-1) concentrations and incubation temperature (15, 25 and 35 °C) on the stoichiometry and kinetics of the methanotrophic consortia was investigated. Consortia enriched from activated sludge at 15 °C accumulated the highest yields of ectoine and hydroxyectoine at 6 % NaCl (105.0 ± 27.2 and 24.2 ± 5.4 mgextremolyte gbiomass-1, respectively). The consortia enriched from the salt lagoon accumulated the highest yield of ectoine and hydroxyectoine at 9 % NaCl (56.6 ± 2.5 and 51.0 ± 2.0 mgextremolyte gbiomass-1, respectively) at 25 °C. The supplementation of tungsten to the cultivation medium did not impact on the accumulation of ectoines in any of the consortia. A molecular characterization of the enrichments revealed a relative abundance of ectoine-accumulating methanotrophs of 7-16 %, with Methylomicrobium buryatense and Methylomicrobium japanense as the main players in the bioconversion of methane into ectoine.

Halotolerance mechanisms of the methanotroph Methylomicrobium alcaliphilum.

Methylomicrobium alcaliphilum is an alkaliphilic and halotolerant methanotroph. The physiological responses of M. alcaliphilum to high NaCl concentrations, were studied using RNA sequencing and metabolic modeling. This study revealed that M. alcaliphilum possesses an unusual respiratory chain, in which complex I is replaced by a Na+ extruding NQR complex (highly upregulated under high salinity conditions) and a Na+ driven adenosine triphosphate (ATP) synthase coexists with a conventional H+ driven ATP synthase. A thermodynamic and metabolic model showing the interplay between these different components is presented. Ectoine is the main osmoprotector used by the cells. Ectoine synthesis is activated by the transcription of an ect operon that contains five genes, including the ectoine hydroxylase coding ectD gene. Enzymatic tests revealed that the product of ectD does not have catalytic activity. A new Genome Scale Metabolic Model for M. alcaliphilum revealed a higher flux in the oxidative branch of the pentose phosphate pathway leading to NADPH production and contributing to resistance to oxidative stress.

Genome Scale Metabolic Model of the versatile methanotroph Methylocella silvestris.

BACKGROUND: Methylocella silvestris is a facultative aerobic methanotrophic bacterium which uses not only methane, but also other alkanes such as ethane and propane, as carbon and energy sources. Its high metabolic versatility, together with the availability of tools for its genetic engineering, make it a very promising platform for metabolic engineering and industrial biotechnology using natural gas as substrate. RESULTS: The first Genome Scale Metabolic Model for M. silvestris is presented. The model has been used to predict the ability of M. silvestris to grow on 12 different substrates, the growth phenotype of two deletion mutants (ΔICL and ΔMS), and biomass yield on methane and ethanol. The model, together with phenotypic characterization of the deletion mutants, revealed that M. silvestris uses the glyoxylate shuttle for the assimilation of C1 and C2 substrates, which is unique in contrast to published reports of other methanotrophs. Two alternative pathways for propane metabolism have been identified and validated experimentally using enzyme activity tests and constructing a deletion mutant (Δ1641), which enabled the identification of acetol as one of the intermediates of propane assimilation via 2-propanol. The model was also used to integrate proteomic data and to identify key enzymes responsible for the adaptation of M. silvestris to different substrates. CONCLUSIONS: The model has been used to elucidate key metabolic features of M. silvestris, such as its use of the glyoxylate shuttle for the assimilation of one and two carbon compounds and the existence of two parallel metabolic pathways for propane assimilation. This model, together with the fact that tools for its genetic engineering already exist, paves the way for the use of M. silvestris as a platform for metabolic engineering and industrial exploitation of methanotrophs.

Genome scale metabolic modeling reveals the metabolic potential of three Type II methanotrophs of the genus Methylocystis.

Genome Scale Metabolic Models (GSMMs) of the recently sequenced Methylocystis hirsuta and two other methanotrophs from the genus Methylocystis have been reconstructed. These organisms are Type II methanotrophs with the ability of accumulating Polyhydroxyalkanoates under nutrient limiting conditions. For the first time, GSMMs have been reconstructed for Type II methanotrophs. These models, combined with experimental biomass and PHB yields of Methylocystis hirsuta, allowed elucidating the methane oxidation mechanism by the enzyme pMMO (particulate methane monooxygenase) in these organisms. In contrast to Type I methanotrophs, which use the "direct coupling mechanism", Type II methanotrophs appear to use the so called "redox arm mechanism". The utilization of the "redox arm mechanism", which involves the coupling between methane oxidation and complex I of the respiratory chain, was confirmed by inhibition of complex I with catechol. Utilization of the "redox arm" mechanism leads to lower biomass yields on methane compared to Type I methanotrophs. However, the ability of Type II methanotrophs to redirect high metabolic carbon fluxes towards acetoacetyl-CoA under nitrogen limiting conditions makes these organisms promising platforms for metabolic engineering.

Reconstruction of a Genome Scale Metabolic Model of the polyhydroxybutyrate producing methanotroph Methylocystis parvus OBBP.

BACKGROUND: Methylocystis parvus is a type II methanotroph characterized by its high specific methane degradation rate (compared to other methanotrophs of the same family) and its ability to accumulate up to 50% of its biomass in the form of poly-3-hydroxybutyrate (PHB) under nitrogen limiting conditions. This makes it a very promising cell factory. RESULTS: This article reports the first Genome Scale Metabolic Model of M. parvus OBBP. The model is compared to Genome Scale Metabolic Models of the closely related methanotrophs Methylocystis hirsuta and Methylocystis sp. SC2. Using the reconstructed model, it was possible to predict the biomass yield of M. parvus on methane. The prediction was consistent with the observed experimental yield, under the assumption of the so called "redox arm mechanism" for methane oxidation. The co-consumption of stored PHB and methane was also modeled, leading to accurate predictions of biomass yields and oxygen consumption rates and revealing an anaplerotic role of PHB degradation. Finally, the model revealed that anoxic PHB consumption has to be coupled to denitrification, as no fermentation of PHB is allowed by the reconstructed metabolic model. CONCLUSIONS: The "redox arm" mechanism appears to be a general characteristic of type II methanotrophs, versus type I methanotrophs that use the "direct coupling" mechanism. The co-consumption of stored PHB and methane was predicted to play an anaplerotic role replenishing the serine cycle with glyoxylate and the TCA cycle with succinyl-CoA, which allows the withdrawal of metabolic precursors for biosynthesis. The stored PHB can be also used as an energy source under anoxic conditions when coupled to denitrification.

Fatty Acid Synthesis and Degradation Interplay to Regulate the Oxidative Stress in Cancer Cells.

Both cytosolic fatty acid synthesis (FAS) and mitochondrial fatty acid oxidation (FAO) have been shown to play a role in the survival and proliferation of cancer cells. This study aimed to confirm experimentally whether FAS and FAO coexist in breast cancer cells (BCC). By feeding cells with 13C-labeled glutamine and measuring labeling patterns of TCA intermediates, it was possible to show that part of the cytosolic acetyl-CoA used in lipid synthesis is also fed back into the mitochondrion via fatty acid degradation. This results in the transfer of reductive potential from the cytosol (in the form of NADPH) to the mitochondrion (in the form of NADH and FADH2). The hypothesized mechanism was further confirmed by blocking FAS and FAO with siRNAs. Exposure to staurosporine (which induces ROS production) resulted in the disruption of simultaneous FAS and FAO, which could be explained by NADPH depletion.

Bio-conversion of methane into high profit margin compounds: an innovative, environmentally friendly and cost-effective platform for methane abatement.

Despite the environmental relevance of CH4 and forthcoming stricter regulations, the development of cost-efficient and environmentally friendly technologies for CH4 abatement is still limited. To date, one of the most promising solutions for the mitigation of this important GHG consists of the bioconversion of CH4 into bioproducts with a high profit margin. In this context, methanotrophs have been already proven as cell-factories of some of the most expensive products synthesized by microorganisms. In the case of ectoine (1000 $ kg-1), already described methanotrophic genera such as Methylomicrobium can accumulate up to 20% (ectoine wt-1) using methane as the only carbon source. Moreover, α-methanotrophs, such as Methylosynus and Methylocystis, are able to store bioplastic concentrations up to 50-60% of their total cell content. More than that, methanotrophs are one of the greatest potential producers of methanol and exopolysaccharides. Although this methanotrophic factory could be enhanced throughout metabolic engineering, the valorization of CH4 into valuable metabolites has been already consistently demonstrated under continuous and discontinuous mode, producing more than one compound in the same bioprocess, and using both, single strains and specific consortia. This review states the state-of-the-art of this innovative biotechnological platform by assessing its potential and current limitations.

Non-small cell lung cancer is characterized by dramatic changes in phospholipid profiles.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death globally. To develop better diagnostics and more effective treatments, research in the past decades has focused on identification of molecular changes in the genome, transcriptome, proteome, and more recently also the metabolome. Phospholipids, which nevertheless play a central role in cell functioning, remain poorly explored. Here, using a mass spectrometry (MS)-based phospholipidomics approach, we profiled 179 phospholipid species in malignant and matched non-malignant lung tissue of 162 NSCLC patients (73 in a discovery cohort and 89 in a validation cohort). We identified 91 phospholipid species that were differentially expressed in cancer versus non-malignant tissues. Most prominent changes included a decrease in sphingomyelins (SMs) and an increase in specific phosphatidylinositols (PIs). Also a decrease in multiple phosphatidylserines (PSs) was observed, along with an increase in several phosphatidylethanolamine (PE) and phosphatidylcholine (PC) species, particularly those with 40 or 42 carbon atoms in both fatty acyl chains together. 2D-imaging MS of the most differentially expressed phospholipids confirmed their differential abundance in cancer cells. We identified lipid markers that can discriminate tumor versus normal tissue and different NSCLC subtypes with an AUC (area under the ROC curve) of 0.999 and 0.885, respectively. In conclusion, using both shotgun and 2D-imaging lipidomics analysis, we uncovered a hitherto unrecognized alteration in phospholipid profiles in NSCLC. These changes may have important biological implications and may have significant potential for biomarker development.

Gcn4p and the Crabtree effect of yeast: drawing the causal model of the Crabtree effect in Saccharomyces cerevisiae and explaining evolutionary trade-offs of adaptation to galactose through systems biology.

By performing an integrated comparative analysis on the physiology and transcriptome of four different S. cerevisiae strains growing on galactose and glucose, it was inferred that the transcription factors Bas1p, Pho2p, and Gcn4p play a central role in the regulatory events causing the Crabtree effect in S. cerevisiae. The analysis also revealed that a point mutation in the RAS2 observed in a galactose-adapted strain causes a lower Crabtree effect and growth rate on glucose by decreasing the activity of Gcn4p while at the same time is at the origin of higher growth rate on galactose due to a lower activity of the transcriptional repressor Sok2p. The role of Gcn4p on the trade-off effect observed on glucose was confirmed experimentally. This was done by showing that the point mutation in RAS2 does not result in a lower growth rate on glucose if it is introduced in a GCN4-negative background.

Genome-scale metabolic model of the versatile bacterium Paracoccus denitrificans Pd1222.

A genome scale metabolic model of the bacterium Paracoccus denitrificans has been constructed. The model containing 972 metabolic genes, 1,371 reactions, and 1,388 unique metabolites has been reconstructed. The model was used to carry out quantitative predictions of biomass yields on 10 different carbon sources under aerobic conditions. Yields on C1 compounds suggest that formate is oxidized by a formate dehydrogenase O, which uses ubiquinone as redox co-factor. The model also predicted the threshold methanol/mannitol uptake ratio, above which ribulose biphosphate carboxylase has to be expressed in order to optimize biomass yields. Biomass yields on acetate, formate, and succinate, when NO3- is used as electron acceptor, were also predicted correctly. The model reconstruction revealed the capability of P. denitrificans to grow on several non-conventional substrates such as adipic acid, 1,4-butanediol, 1,3-butanediol, and ethylene glycol. The capacity to grow on these substrates was tested experimentally, and the experimental biomass yields on these substrates were accurately predicted by the model.IMPORTANCEParacoccus denitrificans has been broadly used as a model denitrifying organism. It grows on a large portfolio of carbon sources, under aerobic and anoxic conditions. These characteristics, together with its amenability to genetic manipulations, make P. denitrificans a promising cell factory for industrial biotechnology. This paper presents and validates the first functional genome-scale metabolic model for P. denitrificans, which is a key tool to enable P. denitrificans as a platform for metabolic engineering and industrial biotechnology. Optimization of the biomass yield led to accurate predictions in a broad scope of substrates.

Leveraging genome-scale metabolic models to understand aerobic methanotrophs.

Genome-scale metabolic models (GEMs) are valuable tools serving systems biology and metabolic engineering. However, GEMs are still an underestimated tool in informing microbial ecology. Since their first application for aerobic gammaproteobacterial methane oxidizers less than a decade ago, GEMs have substantially increased our understanding of the metabolism of methanotrophs, a microbial guild of high relevance for the natural and biotechnological mitigation of methane efflux to the atmosphere. Particularly, GEMs helped to elucidate critical metabolic and regulatory pathways of several methanotrophic strains, predicted microbial responses to environmental perturbations, and were used to model metabolic interactions in cocultures. Here, we conducted a systematic review of GEMs exploring aerobic methanotrophy, summarizing recent advances, pointing out weaknesses, and drawing out probable future uses of GEMs to improve our understanding of the ecology of methane oxidizers. We also focus on their potential to unravel causes and consequences when studying interactions of methane-oxidizing bacteria with other methanotrophs or members of microbial communities in general. This review aims to bridge the gap between applied sciences and microbial ecology research on methane oxidizers as model organisms and to provide an outlook for future studies.

Reconstruction of genome-scale active metabolic networks for 69 human cell types and 16 cancer types using INIT.

Development of high throughput analytical methods has given physicians the potential access to extensive and patient-specific data sets, such as gene sequences, gene expression profiles or metabolite footprints. This opens for a new approach in health care, which is both personalized and based on system-level analysis. Genome-scale metabolic networks provide a mechanistic description of the relationships between different genes, which is valuable for the analysis and interpretation of large experimental data-sets. Here we describe the generation of genome-scale active metabolic networks for 69 different cell types and 16 cancer types using the INIT (Integrative Network Inference for Tissues) algorithm. The INIT algorithm uses cell type specific information about protein abundances contained in the Human Proteome Atlas as the main source of evidence. The generated models constitute the first step towards establishing a Human Metabolic Atlas, which will be a comprehensive description (accessible online) of the metabolism of different human cell types, and will allow for tissue-level and organism-level simulations in order to achieve a better understanding of complex diseases. A comparative analysis between the active metabolic networks of cancer types and healthy cell types allowed for identification of cancer-specific metabolic features that constitute generic potential drug targets for cancer treatment.

Characterization of the Keratinolytic Activity of Three Streptomyces Strains and Impact of Their Co-Cultivation on This Activity.

In this study, we describe the characterization of three efficient chicken feather-degrading Streptomyces bacteria isolated from honeybee samples and assess the impact of their co-cultivation on this activity and antistaphylococcal activity. Streptomyces griseoaurantiacus AD2 was the strain showing the highest keratinolytic activity (4000 U × mL-1), followed by Streptomyces albidoflavus AN1 and Streptomyces drozdowiczii AD1, which both generated approximately 3000 U × mL-1. Moreover, a consortium constituted of these three strains was able to use chicken feathers as its sole nutrient source and growth in such conditions led to a significant increase in antibiotic production. S. griseoaurantiacus AD2 was the only strain that exhibited weak antimicrobial activity against Staphylococcus aureus. UPLC analyses revealed that a significant number of peaks detected in the extracts of co-cultures of the three strains were missing in the extracts of individual cultures. In addition, the production of specialized metabolites, such as undecylprodigiosin and manumycin A, was clearly enhanced in co-culture conditions, in agreement with the results of the antimicrobial bioassays against S. aureus. Our results revealed the benefits of co-cultivation of these bacterial species in terms of metabolic wealth and antibiotic production. Our work could thus contribute to the development of novel microbial-based strategies to valorize keratin waste.

Characterization of Bacillus Strains from Natural Honeybee Products with High Keratinolytic Activity and Antimicrobial Potential.

Two efficient feather-degrading bacteria were isolated from honeybee samples and identified as Bacillus sonorensis and Bacillus licheniformis based on 16S rRNA and genome sequencing. The strains were able to grow on chicken feathers as the sole carbon and nitrogen sources and degraded the feathers in a few days. The highest keratinase activity was detected by the B. licheniformis CG1 strain (3800 U × mL-1), followed by B. sonorensis AB7 (1450 U × mL-1). Keratinase from B. licheniformis CG1 was shown to be active across a wide range of pH, potentially making this strain advantageous for further industrial applications. All isolates displayed antimicrobial activity against Micrococcus luteus; however, only B. licheniformis CG1 was able to inhibit the growth of Mycobacterium smegmatis. In silico analysis using BAGEL and antiSMASH identified gene clusters associated with the synthesis of non-ribosomal peptide synthetases (NRPS), polyketide synthases (PKSs) and/or ribosomally synthesized and post-translationally modified peptides (RiPPs) in most of the Bacillus isolates. B. licheniformis CG1, the only strain that inhibited the growth of the mycobacterial strain, contained sequences with 100% similarity to lichenysin (also present in the other isolates) and lichenicidin (only present in the CG1 strain). Both compounds have been described to display antimicrobial activity against distinct bacteria. In summary, in this work, we have isolated a strain (B. licheniformis CG1) with promising potential for use in different industrial applications, including animal nutrition, leather processing, detergent formulation and feather degradation.

Evaluation of Cx43 Gap Junction Inhibitors Using a Quantitative Structure-Activity Relationship Model.

Gap junctions (GJs) made of connexin-43 (Cx43) are necessary for the conduction of electrical impulses in the heart. Modulation of Cx43 GJ activity may be beneficial in the treatment of cardiac arrhythmias and other dysfunctions. The search for novel GJ-modulating agents using molecular docking allows for the accurate prediction of binding affinities of ligands, which, unfortunately, often poorly correlate with their potencies. The objective of this study was to demonstrate that a Quantitative Structure-Activity Relationship (QSAR) model could be used for more precise identification of potent Cx43 GJ inhibitors. Using molecular docking, QSAR, and 3D-QSAR, we evaluated 16 known Cx43 GJ inhibitors, suggested the monocyclic monoterpene d-limonene as a putative Cx43 inhibitor, and tested it experimentally in HeLa cells expressing exogenous Cx43. The predicted concentrations required to produce 50% of the maximal effect (IC50) for each of these compounds were compared with those determined experimentally (pIC50 and eIC50, respectively). The pIC50ies of d-limonene and other Cx43 GJ inhibitors examined by our QSAR and 3D-QSAR models showed a good correlation with their eIC50ies (R = 0.88 and 0.90, respectively) in contrast to pIC50ies obtained from molecular docking (R = 0.78). However, molecular docking suggests that inhibitor potency may depend on their docking conformation on Cx43. Searching for new potent, selective, and specific inhibitors of GJ channels, we propose to perform the primary screening of new putative compounds using the QSAR model, followed by the validation of the most suitable candidates by patch-clamp techniques.