Transcriptomic and genomic studies classify NKL54 as a histone deacetylase inhibitor with indirect influence on MEF2-dependent transcription.

In leiomyosarcoma class IIa HDACs (histone deacetylases) bind MEF2 and convert these transcription factors into repressors to sustain proliferation. Disruption of this complex with small molecules should antagonize cancer growth. NKL54, a PAOA (pimeloylanilide o-aminoanilide) derivative, binds a hydrophobic groove of MEF2, which is used as a docking site by class IIa HDACs. However, NKL54 could also act as HDAC inhibitor (HDACI). Therefore, it is unclear which activity is predominant. Here, we show that NKL54 and similar derivatives are unable to release MEF2 from binding to class IIa HDACs. Comparative transcriptomic analysis classifies these molecules as HDACIs strongly related to SAHA/vorinostat. Low expressed genes are upregulated by HDACIs, while abundant genes are repressed. This transcriptional resetting correlates with a reorganization of H3K27 acetylation around the transcription start site (TSS). Among the upregulated genes there are several BH3-only family members, thus explaining the induction of apoptosis. Moreover, NKL54 triggers the upregulation of MEF2 and the downregulation of class IIa HDACs. NKL54 also increases the binding of MEF2D to promoters of genes that are upregulated after treatment. In summary, although NKL54 cannot outcompete MEF2 from binding to class IIa HDACs, it supports MEF2-dependent transcription through several actions, including potentiation of chromatin binding.

Essential Oils from Mediterranean Plants Inhibit In Vitro Monocyte Adhesion to Endothelial Cells from Umbilical Cords of Females with Gestational Diabetes Mellitus.

Essential oils (EOs) are mixtures of volatile compounds belonging to several chemical classes derived from aromatic plants using different distillation techniques. Recent studies suggest that the consumption of Mediterranean plants, such as anise and laurel, contributes to improving the lipid and glycemic profile of patients with diabetes mellitus (DM). Hence, the aim of the present study was to investigate the potential anti-inflammatory effect of anise and laurel EOs (AEO and LEO) on endothelial cells isolated from the umbilical cord vein of females with gestational diabetes mellitus (GDM-HUVEC), which is a suitable in vitro model to reproduce the pro-inflammatory phenotype of a diabetic endothelium. For this purpose, the Gas Chromatographic/Mass Spectrometric (GC-MS) chemical profiles of AEO and LEO were first analyzed. Thus, GDM-HUVEC and related controls (C-HUVEC) were pre-treated for 24 h with AEO and LEO at 0.025% v/v, a concentration chosen among others (cell viability by MTT assay), and then stimulated with TNF-α (1 ng/mL). From the GC-MS analysis, trans-anethole (88.5%) and 1,8-cineole (53.9%) resulted as the major components of AEO and LEO, respectively. The results in C- and GDM-HUVEC showed that the treatment with both EOs significantly reduced: (i) the adhesion of the U937 monocyte to HUVEC; (ii) vascular adhesion molecule-1 (VCAM-1) protein and gene expression; (iii) Nuclear Factor-kappa B (NF-κB) p65 nuclear translocation. Taken together, these data suggest the anti-inflammatory efficacy of AEO and LEO in our in vitro model and lay the groundwork for further preclinical and clinical studies to study their potential use as supplements to mitigate vascular endothelial dysfunction associated with DM.

An Undefined Interaction between Polyamines and Heat Shock Proteins Leads to Cellular Protection in Plasmodium falciparum and Proliferating Cells in Various Organisms.

Environmental stimuli can distress the internal reaction of cells and their normal function. To react promptly to sudden environmental changes, a cascade of heat shock proteins (Hsps) functions to protect and act as housekeepers inside the cells. In parallel to the heat shock response, the metabolic polyamine (PA) status changes. Here, we discuss possible ways of putative interactions between Hsps and polyamines in a wide lineage of eukaryotic model organisms with a particular focus on parasitic protozoa such as Plasmodium falciparum (P. falciparum). The supposed interaction between polyamines and Hsps may protect the parasite from the sudden change in temperature during transmission from the female Anopheles mosquito to a human host. Recent experiments performed with the spermidine mimetic inhibitor 15-deoxyspergualine in Plasmodium in vitro cultures show that the drug binds to the C-terminal EEVD motif of Hsp70. This leads to inhibition of protein biosynthesis caused by prevention of eIF5A2 phosphorylation and eukaryotic initiation factor 5A (eIF5A) modification. These observations provide further evidence that PAs are involved in the regulation of protein biosynthesis of Hsps to achieve a protective effect for the parasite during transmission.

Molecular Docking Assessment of Cathinones as 5-HT2AR Ligands: Developing of Predictive Structure-Based Bioactive Conformations and Three-Dimensional Structure-Activity Relationships Models for Future Recognition of Abuse Drugs.

Commercially available cathinones are drugs of long-term abuse drugs whose pharmacology is fairly well understood. While their psychedelic effects are associated with 5-HT2AR, the enclosed study summarizes efforts to shed light on the pharmacodynamic profiles, not yet known at the receptor level, using molecular docking and three-dimensional quantitative structure-activity relationship (3-D QSAR) studies. The bioactive conformations of cathinones were modeled by AutoDock Vina and were used to build structure-based (SB) 3-D QSAR models using the Open3DQSAR engine. Graphical inspection of the results led to the depiction of a 3-D structure analysis-activity relationship (SAR) scheme that could be used as a guideline for molecular determinants by which any untested cathinone molecule can be predicted as a potential 5-HT2AR binder prior to experimental evaluation. The obtained models, which showed a good agreement with the chemical properties of co-crystallized 5-HT2AR ligands, proved to be valuable for future virtual screening campaigns to recognize unused cathinones and similar compounds, such as 5-HT2AR ligands, minimizing both time and financial resources for the characterization of their psychedelic effects.

Chemical Composition and Anti-Candida Activity of Mentha suaveolens Ehrh. Essential Oils Obtained by Different Distillation Processes.

A comparative study on essential oils extracted from Mentha suaveolens Ehrh. from Italy is reported. Two extraction procedures were investigated: hydrodistillation and steam distillation, carried out as a continuous and fractionated procedure. Fresh and dried plant material from two harvests was used. The hydrodistillation method yielded a higher amount of essential oil. The dried plant was significantly richer in essential oil per kg of starting plant material. Gas chromatography-mass spectrometry analysis of 112 samples showed that the essential oils belong to the piperitenone oxide-rich chemotype. In addition, piperitenone, p-cymen-8-ol, and limonene were among the most abundant compounds in the different samples. A higher amount of piperitenone oxide was obtained by hydrodistillation, while steam distillation gave a higher percentage of piperitenone and limonene. The essential oils were characterized for their anti-Candida albicans activity; higher potency was observed for the samples rich in piperitenone oxide, with MIC values ranging from 0.39 to 0.78 mg·mL-1 (0.039% and 0.078% p/v). The results of this work provide a deep insight into the methodology of essential oil extraction and the associated chemical variability of M. suaveolens Ehrh. Some of the essential oils are potent against C. albicans and could be considered for potential use in therapy.

Bovine Serum Amine Oxidase and Polyamine Analogues: Chemical Synthesis and Biological Evaluation Integrated with Molecular Docking and 3-D QSAR Studies.

Natural polyamines (PAs) are key players in cellular homeostasis by regulating cell growth and proliferation. Several observations highlight that PAs are also implicated in pathways regulating cell death. Indeed, the PA accumulation cytotoxic effect, maximized with the use of bovine serum amine oxidase (BSAO) enzyme, represents a valuable strategy against tumor progression. In the present study, along with the design, synthesis, and biological evaluation of a series of new spermine (Spm) analogues (1-23), a mixed structure-based (SB) and ligand-based (LB) protocol was applied. Binding modes of BSAO-PA modeled complexes led to clarify electrostatic and steric features likely affecting the BSAO-PA biochemical kinetics. LB and SB three-dimensional quantitative structure-activity relationship (Py-CoMFA and Py-ComBinE) models were developed by means of the 3d-qsar.com portal, and their analysis represents a strong basis for future design and synthesis of PA BSAO substrates for potential application in oxidative stress-induced chemotherapy.

Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal.

The main protease (Mpro) of SARS-Cov-2 is the essential enzyme for maturation of functional proteins implicated in viral replication and transcription. The peculiarity of its specific cleavage site joint with its high degree of conservation among all coronaviruses promote it as an attractive target to develop broad-spectrum inhibitors, with high selectivity and tolerable safety profile. Herein is reported a combination of three-dimensional quantitative structure-activity relationships (3-D QSAR) and comparative molecular binding energy (COMBINE) analysis to build robust and predictive ligand-based and structure-based statistical models, respectively. Models were trained on experimental binding poses of co-crystallized Mpro-inhibitors and validated on available literature data. By means of deep optimization both models' goodness and robustness reached final statistical values of r2/q2 values of 0.97/0.79 and 0.93/0.79 for the 3-D QSAR and COMBINE approaches respectively, and an overall predictiveness values of 0.68 and 0.57 for the SDEPPRED and AAEP metrics after application to a test set of 60 compounds covered by the training set applicability domain. Despite the different nature (ligand-based and structure-based) of the employed methods, their outcome fully converged. Furthermore, joint ligand- and structure-based structure-activity relationships were found in good agreement with nirmatrelvir chemical features properties, a novel oral Mpro-inhibitor that has recently received U.S. FDA emergency use authorization (EUA) for the oral treatment of mild-to-moderate COVID-19 infected patients. The obtained results will guide future rational design and/or virtual screening campaigns with the aim of discovering new potential anti-coronavirus lead candidates, minimizing both time and financial resources. Moreover, as most of calculation were performed through the well-established web portal 3d-qsar.com the results confirm the portal as a useful tool for drug design.

Inhibition of PKCθ Improves Dystrophic Heart Phenotype and Function in a Novel Model of DMD Cardiomyopathy.

Chronic cardiac muscle inflammation and subsequent fibrotic tissue deposition are key features in Duchenne Muscular Dystrophy (DMD). The treatment of choice for delaying DMD progression both in skeletal and cardiac muscle are corticosteroids, supporting the notion that chronic inflammation in the heart plays a pivotal role in fibrosis deposition and subsequent cardiac dysfunction. Nevertheless, considering the adverse effects associated with long-term corticosteroid treatments, there is a need for novel anti-inflammatory therapies. In this study, we used our recently described exercised mdx (ex mdx) mouse model characterised by accelerated heart pathology, and the specific PKCθ inhibitor Compound 20 (C20), to show that inhibition of this kinase leads to a significant reduction in the number of immune cells infiltrating the heart, as well as necrosis and fibrosis. Functionally, C20 treatment also prevented the reduction in left ventricle fractional shortening, which was typically observed in the vehicle-treated ex mdx mice. Based on these findings, we propose that PKCθ pharmacological inhibition could be an attractive therapeutic approach to treating dystrophic cardiomyopathy.

Human Estrogen Receptor Alpha Antagonists, Part 3: 3-D Pharmacophore and 3-D QSAR Guided Brefeldin A Hit-to-Lead Optimization toward New Breast Cancer Suppressants.

The estrogen receptor α (ERα) is an important biological target mediating 17ß-estradiol driven breast cancer (BC) development. Aiming to develop innovative drugs against BC, either wild-type or mutated ligand-ERα complexes were used as source data to build structure-based 3-D pharmacophore and 3-D QSAR models, afterward used as tools for the virtual screening of National Cancer Institute datasets and hit-to-lead optimization. The procedure identified Brefeldin A (BFA) as hit, then structurally optimized toward twelve new derivatives whose anticancer activity was confirmed both in vitro and in vivo. Compounds as SERMs showed picomolar to low nanomolar potencies against ERα and were then investigated as antiproliferative agents against BC cell lines, as stimulators of p53 expression, as well as BC cell cycle arrest agents. Most active leads were finally profiled upon administration to female Wistar rats with pre-induced BC, after which 3DPQ-12, 3DPQ-3, 3DPQ-9, 3DPQ-4, 3DPQ-2, and 3DPQ-1 represent potential candidates for BC therapy.

Pinus mugo Essential Oil Impairs STAT3 Activation through Oxidative Stress and Induces Apoptosis in Prostate Cancer Cells.

Essential oils (EOs) and their components have been reported to possess anticancer properties and to increase the sensitivity of cancer cells to chemotherapy. The aim of this work was to select EOs able to downregulate STAT3 signaling using Western blot and RT-PCR analyses. The molecular mechanism of anti-STAT3 activity was evaluated through spectrophotometric and fluorometric analyses, and the biological effect of STAT3 inhibition was analyzed by flow cytometry and wound healing assay. Herein, Pinus mugo EO (PMEO) is identified as an inhibitor of constitutive STAT3 phosphorylation in human prostate cancer cells, DU145. The down-modulation of the STAT3 signaling cascade decreased the expression of anti-proliferative as well as anti-apoptotic genes and proteins, leading to the inhibition of cell migration and apoptotic cell death. PMEO treatment induced a rapid drop in glutathione (GSH) levels and an increase in reactive oxygen species (ROS) concentration, resulting in mild oxidative stress. Pretreatment of cells with N-acetyl-cysteine (NAC), a cell-permeable ROS scavenger, reverted the inhibitory action of PMEO on STAT3 phosphorylation. Moreover, combination therapy revealed that PMEO treatment displayed synergism with cisplatin in inducing the cytotoxic effect. Overall, our data highlight the importance of STAT3 signaling in PMEO cytotoxic activity, as well as the possibility of developing adjuvant therapy or sensitizing cancer cells to conventional chemotherapy.

Human Estrogen Receptor α Antagonists. Part 1: 3-D QSAR-Driven Rational Design of Innovative Coumarin-Related Antiestrogens as Breast Cancer Suppressants through Structure-Based and Ligand-Based Studies.

The estrogen receptor α (ERα) represents a 17ß-estradiol-inducible transcriptional regulator that initiates the RNA polymerase II-dependent transcriptional machinery, pointed for breast cancer (BC) development via either genomic direct or genomic indirect (i.e., tethered) pathway. To develop innovative ligands, structure-based (SB) three-dimensional (3-D) quantitative structure-activity relationship (QSAR) studies have been undertaken from structural data taken from partial agonists, mixed agonists/antagonists (selective estrogen receptor modulators (SERMs)), and full antagonists (selective ERα downregulators (SERDs)) correlated with either wild-type or mutated ERα receptors. SB and ligand-based (LB) alignments allow us to rule out guidelines for the SB/LB alignment of untested compounds. 3-D QSAR models for ERα ligands, coupled with SB/LB alignment, were revealed to be useful tools to dissect the chemical determinants for ERα-based anticancer activity as well as to predict their potency. The herein developed protocol procedure was verified through the design and potency prediction of 12 new coumarin-based SERMs, namely, 3DQ-1a to 3DQ-1e, that upon synthesis turned to be potent ERα antagonists by means of either in vitro or in vivo assays (described in the second part of this study).

Altered mitochondrial function in cells carrying a premutation or unmethylated full mutation of the FMR1 gene.

Fragile X-related disorders are due to a dynamic mutation of the CGG repeat at the 5' UTR of the FMR1 gene, coding for the RNA-binding protein FMRP. As the CGG sequence expands from premutation (PM, 56-200 CGGs) to full mutation (> 200 CGGs), FMRP synthesis decreases until it is practically abolished in fragile X syndrome (FXS) patients, mainly due to FMR1 methylation. Cells from rare individuals with no intellectual disability and carriers of an unmethylated full mutation (UFM) produce slightly elevated levels of FMR1-mRNA and relatively low levels of FMRP, like in PM carriers. With the aim of clarifying how UFM cells differ from CTRL and FXS cells, a comparative proteomic approach was undertaken, from which emerged an overexpression of SOD2 in UFM cells, also confirmed in PM but not in FXS. The SOD2-mRNA bound to FMRP in UFM more than in the other cell types. The high SOD2 levels in UFM and PM cells correlated with lower levels of superoxide and reactive oxygen species (ROS), and with morphological anomalies and depolarization of the mitochondrial membrane detected through confocal microscopy. The same effect was observed in CTRL and FXS after treatment with MC2791, causing SOD2 overexpression. These mitochondrial phenotypes reverted after knock-down with siRNA against SOD2-mRNA and FMR1-mRNA in UFM and PM. Overall, these data suggest that in PM and UFM carriers, which have high levels of FMR1 transcription and may develop FXTAS, SOD2 overexpression helps to maintain low levels of both superoxide and ROS with signs of mitochondrial degradation.

Essential Oils Biofilm Modulation Activity, Chemical and Machine Learning Analysis. Application on Staphylococcus aureus Isolates from Cystic Fibrosis Patients.

Bacterial biofilm plays a pivotal role in chronic Staphylococcus aureus (S. aureus) infection and its inhibition may represent an important strategy to develop novel therapeutic agents. The scientific community is continuously searching for natural and "green alternatives" to chemotherapeutic drugs, including essential oils (EOs), assuming the latter not able to select resistant strains, likely due to their multicomponent nature and, hence, multitarget action. Here it is reported the biofilm production modulation exerted by 61 EOs, also investigated for their antibacterial activity on S. aureus strains, including reference and cystic fibrosis patients' isolated strains. The EOs biofilm modulation was assessed by Christensen method on five S. aureus strains. Chemical composition, investigated by GC/MS analysis, of the tested EOs allowed a correlation between biofilm modulation potency and putative active components by means of machine learning algorithms application. Some EOs inhibited biofilm growth at 1.00% concentration, although lower concentrations revealed different biological profile. Experimental data led to select antibiofilm EOs based on their ability to inhibit S. aureus biofilm growth, which were characterized for their ability to alter the biofilm organization by means of SEM studies.

Identification of Inhibitors to Trypanosoma cruzi Sirtuins Based on Compounds Developed to Human Enzymes.

Chagas disease is an illness caused by the protozoan parasite Trypanosoma cruzi, affecting more than 7 million people in the world. Benznidazole and nifurtimox are the only drugs available for treatment and in addition to causing several side effects, are only satisfactory in the acute phase of the disease. Sirtuins are NAD+-dependent deacetylases involved in several biological processes, which have become drug target candidates in various disease settings. T. cruzi presents two sirtuins, one cytosolic (TcSir2rp1) and the latter mitochondrial (TcSir2rp3). Here, we characterized the effects of human sirtuin inhibitors against T. cruzi sirtuins as an initial approach to develop specific parasite inhibitors. We found that, of 33 compounds tested, two inhibited TcSir2rp1 (15 and 17), while other five inhibited TcSir2rp3 (8, 12, 13, 30, and 32), indicating that specific inhibitors can be devised for each one of the enzymes. Furthermore, all inhibiting compounds prevented parasite proliferation in cultured mammalian cells. When combining the most effective inhibitors with benznidazole at least two compounds, 17 and 32, demonstrated synergistic effects. Altogether, these results support the importance of exploring T. cruzi sirtuins as drug targets and provide key elements to develop specific inhibitors for these enzymes as potential targets for Chagas disease treatment.

Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils.

In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among the prominent studies essential oils are investigated as antibacterial agents alone or in combination with known drugs. Minor studies involved essential oil inspection as potential anticancer and antiviral natural remedies. In line with the authors previous reports the investigation of an in-house library of extracted essential oils as a potential blocker of HSV-1 infection is reported herein. A subset of essential oils was experimentally tested in an in vitro model of HSV-1 infection and the determined IC50s and CC50s values were used in conjunction with the results obtained by gas-chromatography/mass spectrometry chemical analysis to derive machine learning based classification models trained with the partial least square discriminant analysis algorithm. The internally validated models were thus applied on untested essential oils to assess their effective predictive ability in selecting both active and low toxic samples. Five essential oils were selected among a list of 52 and readily assayed for IC50 and CC50 determination. Interestingly, four out of the five selected samples, compared with the potencies of the training set, returned to be highly active and endowed with low toxicity. In particular, sample CJM1 from Calaminta nepeta was the most potent tested essential oil with the highest selectivity index (IC50 = 0.063 mg/mL, SI > 47.5). In conclusion, it was herein demonstrated how multidisciplinary applications involving machine learning could represent a valuable tool in predicting the bioactivity of complex mixtures and in the near future to enable the design of blended essential oil possibly endowed with higher potency and lower toxicity.

Breakthroughs in Medicinal Chemistry: New Targets and Mechanisms, New Drugs, New Hopes-7.

Breakthroughs in Medicinal Chemistry [...].

Teaching and Learning Computational Drug Design: Student Investigations of 3D Quantitative Structure-Activity Relationships through Web Applications.

The increasing use of information technology in the discovery of new molecular entities encourages the use of modern molecular-modeling tools to help teach important concepts of drug design to chemistry and pharmacy undergraduate students. In particular, statistical models such as quantitative structure-activity relationships (QSAR)-often as its 3D QSAR variant-are commonly used in the development and optimization of a leading compound. We describe how these drug discovery methods can be taught and learned by means of free and open-source web applications, specifically the online platform www.3d-qsar.com. This new suite of web applications has been integrated into a drug design teaching course, one that provides both theoretical and practical perspectives. We include the teaching protocol by which pharmaceutical biotechnology master students at Pharmacy Faculty of Sapienza Rome University are introduced to drug design. Starting with a choice among recent articles describing the potencies of a series of molecules tested against a biological target, each student is expected to build a 3D QSAR ligand-based model from their chosen publication, proceeding as follows: creating the initial data set (Py-MolEdit); generating the global minimum conformations (Py-ConfSearch); proposing a promising mutual alignment (Py-Align); and finally, building, and optimizing a robust 3D QSAR models (Py-CoMFA). These student activities also help validate these new molecular modeling tools, especially for their usability by inexperienced hands. To more fully demonstrate the effectiveness of this protocol and its tools, we include the work performed by four of these students (four of the coauthors), detailing the satisfactory 3D QSAR models they obtained. Such scientifically complete experiences by undergraduates, made possible by the efficiency of the 3D QSAR methodology, provide exposure to computational tools in the same spirit as traditional laboratory exercises. With the obsolescence of the classic Comparative Molecular Field Analysis Sybyl host, the 3dqsar web portal offers one of the few available means of performing this well-established 3D QSAR method.

www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices-the Py-CoMFA web application as tool to build models from pre-aligned datasets.

Comparative molecular field analysis (CoMFA), introduced in 1988, was the first 3-D QSAR method ever published and sold. Since then thousands of application, articles and citation have proved 3-D QSAR as a valuable method to be used in drug design. Several other 3-D QSAR methods have appeared, but still CoMFA remains the most used and cited. Nevertheless from a survey on the Certara® web site it seems that CoMFA is no more available. Herein is presented a python implementation of the CoMFA (Py-CoMFA). Py-CoMFA is usable through the www.3d-qsar.com web applications suites portal by mean of any electronic device that can run a web browser. As benchmark, 30 different publicly available datasets were used to assess the Py-CoMFA usability and robustness. Comparisons with published results proved Py-COMFA to be in very good agreement with those obtained with the original CoMFA. Although the used datasets were pre-aligned, by means of the other web application available through the portal, 3-D QSAR models can be easily build from scratch. In conclusion, although CoMFA is a well known methodology and given the availability of several publicly available Hansch type QSAR web portals, Py-CoMFA represents a valuable tools for any chemoinformatics and informatics non-skilled user that can also be used as support to teach 3-D QSAR. Importantly, Py-CoMFA is the first and unique tool publicly available to build 3-D QSAR models.

In-Vitro Evaluation of Different Antimicrobial Combinations with and without Colistin Against Carbapenem-Resistant Acinetobacter Baumannii.

Carbapenem-resistant Acinetobacter baumannii (CR-Ab) infections are associated with high morbidity and mortality. The aim of the study was to evaluate the in-vitro activity of different antimicrobial combinations (with and without colistin, COL) against clinical isolates of CR-Ab collected from patients with CR-Ab infection, including unconventional combinations such as COL + VANcomycin (VAN) and COL + rifampin (RIF). CR-Ab strains were collected from hospitalized patients at Sapienza University of Rome. Antimicrobial susceptibility patterns were determined throughout MIC50/90s whereas the synergistic activity was evaluated by qualitative (i.e., checkerboard) and quantitative (i.e., killing studies) methods. All the strains were found oxacillinase (OXA) producers and tigecycline (TIG) sensitive whereas 2 strains were resistant to COL. Application of the checkerboard method indicated complete synergism in COL combinations at different extension: 21.4%, 57.1%, 42.8%, 35.7% for COL + meropenem (MEM), COL + RIF, COL + VAN and COL + TIG, respectively, with the non-conventional combinations COL + VAN and COL + RIF exhibiting the highest rate of synergism. Regarding COL-free combination, complete synergism was observed in 35.7% of the strains for MEM + TIG. Killing studies showed that the combinations COL + MEM, COL + TIG and MEM + TIG were bactericidal and synergistic against both colistin-sensitive and low colistin-resistant strains whereas only the combinations COL + VAN and COL + RIF showed an early and durable bactericidal activity against all the tested strains, with absence of growth at 24 h. This study demonstrated that COL-based combinations lead to a high level of synergic and bactericidal activity, especially COL + VAN and COL + RIF, even in the presence of high level of COL resistance.

Machine Learning Analyses on Data including Essential Oil Chemical Composition and In Vitro Experimental Antibiofilm Activities against Staphylococcus Species.

Biofilm resistance to antimicrobials is a complex phenomenon, driven not only by genetic mutation induced resistance, but also by means of increased microbial cell density that supports horizontal gene transfer across cells. The prevention of biofilm formation and the treatment of existing biofilms is currently a difficult challenge; therefore, the discovery of new multi-targeted or combinatorial therapies is growing. The development of anti-biofilm agents is considered of major interest and represents a key strategy as non-biocidal molecules are highly valuable to avoid the rapid appearance of escape mutants. Among bacteria, staphylococci are predominant causes of biofilm-associated infections. Staphylococci, especially Staphylococcus aureus (S. aureus) is an extraordinarily versatile pathogen that can survive in hostile environmental conditions, colonize mucous membranes and skin, and can cause severe, non-purulent, toxin-mediated diseases or invasive pyogenic infections in humans. Staphylococcus epidermidis (S. epidermidis) has also emerged as an important opportunistic pathogen in infections associated with medical devices (such as urinary and intravascular catheters, orthopaedic implants, etc.), causing approximately from 30% to 43% of joint prosthesis infections. The scientific community is continuously looking for new agents endowed of anti-biofilm capabilities to fight S. aureus and S epidermidis infections. Interestingly, several reports indicated in vitro efficacy of non-biocidal essential oils (EOs) as promising treatment to reduce bacterial biofilm production and prevent the inducing of drug resistance. In this report were analyzed 89 EOs with the objective of investigating their ability to modulate bacterial biofilm production of different S. aureus and S. epidermidis strains. Results showed the assayed EOs to modulated the biofilm production with unpredictable results for each strain. In particular, many EOs acted mainly as biofilm inhibitors in the case of S. epidermidis strains, while for S. aureus strains, EOs induced either no effect or stimulate biofilm production. In order to elucidate the obtained experimental results, machine learning (ML) algorithms were applied to the EOs' chemical compositions and the determined associated anti-biofilm potencies. Statistically robust ML models were developed, and their analysis in term of feature importance and partial dependence plots led to indicating those chemical components mainly responsible for biofilm production, inhibition or stimulation for each studied strain, respectively.