scholarly journals Pharmacophore modeling, virtual computational screening and biological evaluation studies

2017 ◽  
Author(s):  
Serena Dotolo ◽  
Angelo Facchiano
Keyword(s):  
Molecular Mechanisms ◽  
Prediction Models ◽  
Pharmacophore Modeling ◽  
Biological Evaluation ◽  
Bioactive Molecules ◽  
Investigational Drug ◽  
Discovery Studio ◽  
Lead Compounds ◽  
Computational Screening ◽  
Computational Strategy

Drug discovery process plays an important role in identifying new investigational drug-likes and developing new potential inhibitors related to a determinate target, in biopharmaceutical field [1]. An alternative promising and efficient used to identify new active substances is Pharmacophore modeling method.We defined a new computational strategy protocol characterized by the use of bioinformatics online tools and by the application of locally installed tools, for lead candidates generation-optimization able to reduce the cycle time and cost of this process and to promote the next steps of study [2].Hence, we have tried to apply this new computational procedure, in a more detailed screening, of small bioactive molecules, searching and identifying new candidates as “lead compounds”, potentially able to inhibit biological target AKT1 human protein and its related molecular mechanisms [3].The workflow executed in our work has been characterized by a multi-step design, which concerns different topics: search in PDB database of a model structure for AKT1, pharmacophore modeling and virtual computational screening, biological evaluation divided in two parts (molecular validation of selected compounds and study of physical-chemical properties related to pharmacokinetic/pharmacodynamics prediction models). All these step have been performed through PHARMIT (http://pharmit.csb.pitt.edu) and Discovery Studio 4.5 platform.We selected the PDB structure 3O96 as the reference complex (protein-ligand), and we analyzed it by means of PHARMIT and Discovery Studio, to generate four different “pharmacophore models” with four different list of natural compounds.It is performed a thorough screening of compounds applying several filters, to find some good candidates as possible natural AKT1 allosteric inhibitors.The compounds that match a well-defined pharmacophore have been analyzed through direct molecular docking, for selecting only the best candidates and studying the protein-ligand interactions. Selected compounds have been investigated in more details, to trace their origin, by their chemical-physical properties.This information can help us to predict some plausible enzyme-catalyzed reaction pathways, through PathPred web-server and KEGG compound database, in order to highlight the most important reactions for biosynthesis of compounds and obtain PharmacoKinetics/PharmacoDynamics (PK/PD) models, to investigate the ADMET properties of these lead compounds and to study their behavior in some biological systems, for the next experimental assays.This new computational strategy has been very efficient in showing what could be good “lead compounds” and potential natural inhibitors of AKT1 and PI3K/AKT1 signaling cascade. Therefore, the next steps could be the experimental analysis of pharmacokinetics-pharmacodynamics and toxicity properties “in vitro/in vivo”, in order to evaluate the results obtained “in silico”.

scholarly journals Pharmacophore modeling, virtual computational screening and biological evaluation studies

2017 ◽  
Author(s):  
Serena Dotolo ◽  
Angelo Facchiano
Keyword(s):  
Molecular Mechanisms ◽  
Prediction Models ◽  
Pharmacophore Modeling ◽  
Biological Evaluation ◽  
Bioactive Molecules ◽  
Investigational Drug ◽  
Discovery Studio ◽  
Lead Compounds ◽  
Computational Screening ◽  
Computational Strategy

Drug discovery process plays an important role in identifying new investigational drug-likes and developing new potential inhibitors related to a determinate target, in biopharmaceutical field [1]. An alternative promising and efficient used to identify new active substances is Pharmacophore modeling method.We defined a new computational strategy protocol characterized by the use of bioinformatics online tools and by the application of locally installed tools, for lead candidates generation-optimization able to reduce the cycle time and cost of this process and to promote the next steps of study [2].Hence, we have tried to apply this new computational procedure, in a more detailed screening, of small bioactive molecules, searching and identifying new candidates as “lead compounds”, potentially able to inhibit biological target AKT1 human protein and its related molecular mechanisms [3].The workflow executed in our work has been characterized by a multi-step design, which concerns different topics: search in PDB database of a model structure for AKT1, pharmacophore modeling and virtual computational screening, biological evaluation divided in two parts (molecular validation of selected compounds and study of physical-chemical properties related to pharmacokinetic/pharmacodynamics prediction models). All these step have been performed through PHARMIT (http://pharmit.csb.pitt.edu) and Discovery Studio 4.5 platform.We selected the PDB structure 3O96 as the reference complex (protein-ligand), and we analyzed it by means of PHARMIT and Discovery Studio, to generate four different “pharmacophore models” with four different list of natural compounds.It is performed a thorough screening of compounds applying several filters, to find some good candidates as possible natural AKT1 allosteric inhibitors.The compounds that match a well-defined pharmacophore have been analyzed through direct molecular docking, for selecting only the best candidates and studying the protein-ligand interactions. Selected compounds have been investigated in more details, to trace their origin, by their chemical-physical properties.This information can help us to predict some plausible enzyme-catalyzed reaction pathways, through PathPred web-server and KEGG compound database, in order to highlight the most important reactions for biosynthesis of compounds and obtain PharmacoKinetics/PharmacoDynamics (PK/PD) models, to investigate the ADMET properties of these lead compounds and to study their behavior in some biological systems, for the next experimental assays.This new computational strategy has been very efficient in showing what could be good “lead compounds” and potential natural inhibitors of AKT1 and PI3K/AKT1 signaling cascade. Therefore, the next steps could be the experimental analysis of pharmacokinetics-pharmacodynamics and toxicity properties “in vitro/in vivo”, in order to evaluate the results obtained “in silico”.

scholarly journals Drug discovery by integration of pharmacophore modeling, virtual screening and biological evaluation by means of bioinformatics resources

2016 ◽  
Author(s):  
Serena Dotolo ◽  
Angelo Facchiano
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Development Process ◽  
Chemical Space ◽  
Pharmacophore Modeling ◽  
Biological Evaluation ◽  
Lead Compounds ◽  
Computational Screening ◽  
Computational Strategy

Drug discovery is a step-by-step process very important in biopharmaceutical field. We are interested in identifying new investigational drug-likes as potential inhibitors of determinate biological-therapeutic targets, trying to decrease the side effects and to safeguard the human health. However, it is a long and very expensive process. Therefore, we are using a new computational strategy, based on Pharmacophore modeling, to select bioactive substances (natural or synthetic), through the integration of bioinformatics online tools and local resource and platforms, in order to include into the strategy also knowledge from high-throughput studies, for new potential lead compounds generation-optimization, trying to accelerate the early phase of the drug development process. The protocol of this new computational strategy is characterized by a multi-step design focused on: 1) screening in RCSB-PDB for a crystal structure of a specific biological target, suitable for the following steps; 2) pharmacophore modeling and virtual computational screening, by using public domain databases of bioactive compounds, as the ZINC12 database [5], in order to find a promising molecule that could become a new potential medicine. 3) molecular and biological evaluation, to check the compounds selected by virtual screening, for their biological properties through public databases, as PubChem Compound, SciFinder, and Chemicalize to trace their origin and underline their most important physical-chemical features, PathPred (an enzyme-catalyzed metabolic pathway predictor server) to highlight and identify their biosynthetic-metabolic pathways and investigating the biotransformation of best candidates, analyzing their metabolites and their potential biological activity. Moreover, ADMET/toxicity predictor server applying the Lipinski-Veber filter are used to calculate the bioavailability the ADMET/toxicity properties. After this check, only molecules with good bioavailability, good predicted activity and good ADMET properties are considered as hits compounds or drug-likes to direct the design of next experimental assays [6]. Finally, the lead compounds selected are analyzed through molecular dynamics simulations. 4) simulations of molecular dynamics on the best lead compounds, to investigate atomic details of protein-compound molecular interactions in different conditions (different organic solutions, organisms and systems). REFERENCES [1] Dubey A, Facchiano A, Ramteke PW, Marabotti A. “In silico approach to find chymase inhibitors among biogenic compounds.” Future Med Chem. 2016; 8(8):841-51 [2] Dubey A, Marabotti A, Ramteke PW, Facchiano A. "Interaction of human chymase with ginkgolides, terpene trilactones of Ginkgo biloba investigated by molecular docking simulations.” Biochem Biophys Res Commun. 2016; 473(2):449-54. [3] Katara P. “Role of bioinformatics and pharmacogenomics in drug discovery and development process”. Netw Model Anal Health Inform Bioinforma 2013; 2: 225-230. [4] Sunseri J. and Koes D. R. “Pharmit: Interactive Exploration of Chemical Space”.Nucl. Acids Res. 2016; 44(W1): W442-448. [5] Irwin J.J. and Shoichet B.K. “ZINC- A free database of Commercially Available Compounds for Virtual Screening”. J.Chem.Inf.Model. 2005; 45: 177-182. [6] Kaserer T., Beck K. R., Akram M., Odermatt A., Schuster D. “Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Application Exemplified on Hydroxysteroid Dehydrogenases”.Molecules 2015; 20: 22799–22832.

scholarly journals Drug discovery by integration of pharmacophore modeling, virtual screening and biological evaluation by means of bioinformatics resources

2016 ◽  
Author(s):  
Serena Dotolo ◽  
Angelo Facchiano
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Development Process ◽  
Chemical Space ◽  
Pharmacophore Modeling ◽  
Biological Evaluation ◽  
Lead Compounds ◽  
Computational Screening ◽  
Computational Strategy

Drug discovery is a step-by-step process very important in biopharmaceutical field. We are interested in identifying new investigational drug-likes as potential inhibitors of determinate biological-therapeutic targets, trying to decrease the side effects and to safeguard the human health. However, it is a long and very expensive process. Therefore, we are using a new computational strategy, based on Pharmacophore modeling, to select bioactive substances (natural or synthetic), through the integration of bioinformatics online tools and local resource and platforms, in order to include into the strategy also knowledge from high-throughput studies, for new potential lead compounds generation-optimization, trying to accelerate the early phase of the drug development process. The protocol of this new computational strategy is characterized by a multi-step design focused on: 1) screening in RCSB-PDB for a crystal structure of a specific biological target, suitable for the following steps; 2) pharmacophore modeling and virtual computational screening, by using public domain databases of bioactive compounds, as the ZINC12 database [5], in order to find a promising molecule that could become a new potential medicine. 3) molecular and biological evaluation, to check the compounds selected by virtual screening, for their biological properties through public databases, as PubChem Compound, SciFinder, and Chemicalize to trace their origin and underline their most important physical-chemical features, PathPred (an enzyme-catalyzed metabolic pathway predictor server) to highlight and identify their biosynthetic-metabolic pathways and investigating the biotransformation of best candidates, analyzing their metabolites and their potential biological activity. Moreover, ADMET/toxicity predictor server applying the Lipinski-Veber filter are used to calculate the bioavailability the ADMET/toxicity properties. After this check, only molecules with good bioavailability, good predicted activity and good ADMET properties are considered as hits compounds or drug-likes to direct the design of next experimental assays [6]. Finally, the lead compounds selected are analyzed through molecular dynamics simulations. 4) simulations of molecular dynamics on the best lead compounds, to investigate atomic details of protein-compound molecular interactions in different conditions (different organic solutions, organisms and systems). REFERENCES [1] Dubey A, Facchiano A, Ramteke PW, Marabotti A. “In silico approach to find chymase inhibitors among biogenic compounds.” Future Med Chem. 2016; 8(8):841-51 [2] Dubey A, Marabotti A, Ramteke PW, Facchiano A. "Interaction of human chymase with ginkgolides, terpene trilactones of Ginkgo biloba investigated by molecular docking simulations.” Biochem Biophys Res Commun. 2016; 473(2):449-54. [3] Katara P. “Role of bioinformatics and pharmacogenomics in drug discovery and development process”. Netw Model Anal Health Inform Bioinforma 2013; 2: 225-230. [4] Sunseri J. and Koes D. R. “Pharmit: Interactive Exploration of Chemical Space”.Nucl. Acids Res. 2016; 44(W1): W442-448. [5] Irwin J.J. and Shoichet B.K. “ZINC- A free database of Commercially Available Compounds for Virtual Screening”. J.Chem.Inf.Model. 2005; 45: 177-182. [6] Kaserer T., Beck K. R., Akram M., Odermatt A., Schuster D. “Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Application Exemplified on Hydroxysteroid Dehydrogenases”.Molecules 2015; 20: 22799–22832.

Synthesis and Biological Evaluation of the Antimicrobial Natural Product Lipoxazolidinone A

2018 ◽  
Author(s):  
Jonathan J. Mills ◽  
Kaylib R. Robinson ◽  
Troy E. Zehnder ◽  
Joshua G. Pierce
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Mechanism Of Action ◽  
Marine Natural Products ◽  
Biological Evaluation ◽  
Lead Compounds ◽  
Follow Up Studies ◽  
Initial Resistance ◽  
Synthesis And Biological Evaluation

The lipoxazolidinone family of marine natural products, with an unusual 4-oxazolidinone heterocycle at their core, represents a new scaffold for antimicrobial discovery; however, questions regarding their mechanism of action and high lipophilicity have likely slowed follow-up studies. Herein, we report the first synthesis of lipoxazolidinone A, 15 structural analogs to explore its active pharmacophore, and initial resistance and mechanism of action studies. These results suggest that 4-oxazolidinones are valuable scaffolds for antimicrobial development and reveal simplified lead compounds for further optimization.

Novel Thiazole-Based Thiazolidinones as Potent Anti-infective Agents: In silico PASS and Toxicity Prediction, Synthesis, Biological Evaluation and Molecular Modelling

2020 ◽  
Vol 23 (2) ◽  
pp. 126-140 ◽  
Author(s):  
Christophe Tratrat
Keyword(s):  
In Silico ◽  
Antimicrobial Agents ◽  
Target Identification ◽  
Biological Evaluation ◽  
Microbial Infection ◽  
Toxicity Prediction ◽  
Discovery Studio ◽  
Bacteria And Fungi ◽  
Multiple Drugs ◽  
Antibacterial And Antifungal

Aims and Objective: The infectious disease treatment remains a challenging concern owing to the increasing number of pathogenic microorganisms associated with resistance to multiple drugs. A promising approach for combating microbial infection is to combine two or more known bioactive heterocyclic pharmacophores in one molecular platform. Herein, the synthesis and biological evaluation of novel thiazole-thiazolidinone hybrids as potential antimicrobial agents were dissimilated. Materials and Methods: The preparation of the substituted 5-benzylidene-2-thiazolyimino-4- thiazolidinones was achieved in three steps from 2-amino-5-methylthiazoline. All the compounds have been screened in PASS antibacterial activity prediction and in a panel of bacteria and fungi strains. Minimum inhibitory concentration and minimum bacterial concentration were both determined by microdilution assays. Molecular modeling was conducted using Accelrys Discovery Studio 4.0 client. ToxPredict (OPEN TOX) and ProTox were used to estimate the toxicity of the title compounds. Results: PASS prediction revealed the potentiality antibacterial property of the designed thiazolethiazolidinone hybrids. All tested compounds were found to kill and to inhibit the growth of a vast variety of bacteria and fungi, and were more potent than the commercial drugs, streptomycin, ampicillin, bifomazole and ketoconazole. Further, in silico study was carried out for prospective molecular target identification and revealed favorable interaction with the target enzymes E. coli MurB and CYP51B of Aspergillus fumigatus. Toxicity prediction revealed that none of the active compounds was found toxic. Conclusion: Substituted 5-benzylidene-2-thiazolyimino-4-thiazolidinones, endowing remarkable antibacterial and antifungal properties, were identified as a novel class of antimicrobial agents and may find a potential therapeutic use to eradicate infectious diseases.

scholarly journals Experimental Models of Hepatocellular Carcinoma—A Preclinical Perspective

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3651
Author(s):  
Alexandru Blidisel ◽  
Iasmina Marcovici ◽  
Dorina Coricovac ◽  
Florin Hut ◽  
Cristina Adriana Dehelean ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Molecular Mechanisms ◽  
Prediction Models ◽  
3D Models ◽  
Experimental Models ◽  
Health Concern ◽  
Liver Carcinoma ◽  
Tumor Type

Hepatocellular carcinoma (HCC), the most frequent form of primary liver carcinoma, is a heterogenous and complex tumor type with increased incidence, poor prognosis, and high mortality. The actual therapeutic arsenal is narrow and poorly effective, rendering this disease a global health concern. Although considerable progress has been made in terms of understanding the pathogenesis, molecular mechanisms, genetics, and therapeutical approaches, several facets of human HCC remain undiscovered. A valuable and prompt approach to acquire further knowledge about the unrevealed aspects of HCC and novel therapeutic candidates is represented by the application of experimental models. Experimental models (in vivo and in vitro 2D and 3D models) are considered reliable tools to gather data for clinical usability. This review offers an overview of the currently available preclinical models frequently applied for the study of hepatocellular carcinoma in terms of initiation, development, and progression, as well as for the discovery of efficient treatments, highlighting the advantages and the limitations of each model. Furthermore, we also focus on the role played by computational studies (in silico models and artificial intelligence-based prediction models) as promising novel tools in liver cancer research.

scholarly journals Structure-Based Virtual Screening and Biological Evaluation of Peptide Inhibitors for Polo-Box Domain

Molecules ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 107 ◽  
Author(s):  
Fang Yan ◽  
Guangmei Liu ◽  
Tingting Chen ◽  
Xiaochen Fu ◽  
Miao-Miao Niu
Keyword(s):  
Cell Cycle ◽  
Virtual Screening ◽  
Fold Increase ◽  
Pharmacophore Modeling ◽  
Biological Evaluation ◽  
Peptide Inhibitors ◽  
Regulatory Proteins ◽  
Competitive Binding Assay ◽  
M Phase ◽  
Cell Cycle Regulatory Proteins

The polo-box domain of polo-like kinase 1 (PLK1-PBD) is proved to have crucial roles in cell proliferation. Designing PLK1-PBD inhibitors is challenging due to their poor cellular penetration. In this study, we applied a virtual screening workflow based on a combination of structure-based pharmacophore modeling with molecular docking screening techniques, so as to discover potent PLK1-PBD peptide inhibitors. The resulting 9 virtual screening peptides showed affinities for PLK1-PBD in a competitive binding assay. In particular, peptide 5 exhibited an approximately 100-fold increase in inhibitory activity (IC50 = 70 nM), as compared with the control poloboxtide. Moreover, cell cycle experiments indicated that peptide 5 effectively inhibited the expression of p-Cdc25C and cell cycle regulatory proteins by affecting the function of PLK1-PBD, thereby inducing mitotic arrest at the G2/M phase. Overall, peptide 5 can serve as a potent lead for further investigation as PLK1-PBD inhibitors.

scholarly journals Sialylated human milk oligosaccharides program cognitive development through a non-genomic transmission mode

2021 ◽  
Author(s):  
Jonas Hauser ◽  
Edoardo Pisa ◽  
Alejandro Arias Vásquez ◽  
Flavio Tomasi ◽  
Alice Traversa ◽  
...  
Keyword(s):  
Cognitive Development ◽  
Gut Microbiota ◽  
Human Milk ◽  
Molecular Mechanisms ◽  
Brain Regions ◽  
Nervous System Development ◽  
Bioactive Molecules ◽  
Human Milk Oligosaccharides ◽  
Milk Oligosaccharides ◽  
Eye Opening

AbstractBreastmilk contains bioactive molecules essential for brain and cognitive development. While sialylated human milk oligosaccharides (HMOs) have been implicated in phenotypic programming, their selective role and underlying mechanisms remained elusive. Here, we investigated the long-term consequences of a selective lactational deprivation of a specific sialylated HMO in mice. We capitalized on a knock-out (KO) mouse model (B6.129-St6gal1tm2Jxm/J) lacking the gene responsible for the synthesis of sialyl(alpha2,6)lactose (6′SL), one of the two sources of sialic acid (Neu5Ac) to the lactating offspring. Neu5Ac is involved in the formation of brain structures sustaining cognition. To deprive lactating offspring of 6′SL, we cross-fostered newborn wild-type (WT) pups to KO dams, which provide 6′SL-deficient milk. To test whether lactational 6′SL deprivation affects cognitive capabilities in adulthood, we assessed attention, perseveration, and memory. To detail the associated endophenotypes, we investigated hippocampal electrophysiology, plasma metabolomics, and gut microbiota composition. To investigate the underlying molecular mechanisms, we assessed gene expression (at eye-opening and in adulthood) in two brain regions mediating executive functions and memory (hippocampus and prefrontal cortex, PFC). Compared to control mice, WT offspring deprived of 6′SL during lactation exhibited consistent alterations in all cognitive functions addressed, hippocampal electrophysiology, and in pathways regulating the serotonergic system (identified through gut microbiota and plasma metabolomics). These were associated with a site- (PFC) and time-specific (eye-opening) reduced expression of genes involved in central nervous system development. Our data suggest that 6′SL in maternal milk adjusts cognitive development through a short-term upregulation of genes modulating neuronal patterning in the PFC.

scholarly journals Synthesis and biological evaluation of triphenyl-imidazoles as a new class of antimicrobial agents

2018 ◽  
Vol 9 (4) ◽  
pp. 369-374 ◽  
Author(s):  
Anupam Anupam ◽  
Mohammed Al-Bratty ◽  
Hassan Ahmad Alhazmi ◽  
Shamim Ahmad ◽  
Supriya Maity ◽  
...  
Keyword(s):  
Antimicrobial Agents ◽  
Biological Evaluation ◽  
Fungal Strain ◽  
Dilution Method ◽  
Serum Glutamic Oxaloacetic Transaminase ◽  
Active Compounds ◽  
Lead Compounds ◽  
New Class ◽  
Diffusion Technique ◽  
Ft Ir

Newer triphenyl-imidazole derivatives (4a-h) were synthesized in good yields by the reaction of benzil and substituted benzaldehydes in equimolar quantities and refluxing the product with acetyl chloride thereafter. Structures were confirmed by using FT-IR, 1H NMR and 13C NMR spectroscopic methods. All the synthesized compounds were tested for their antimicrobial activity using agar diffusion technique against Gram positive (Staphhylococcus aureus and Bacillus subtilis), Gram negative (Escherichia coli and Pseudomonas aureginosa) as well as Fungal strain (Candida albicans). Interestingly compounds 4a, 4b, 4f and 4h showed significant antibacterial activity, whereas compound 4b was found to have remarkable activity against the fungal strain. The Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of most active compounds were determined by broth dilution method and compound 4b emerged to have potent activities against most of the strains having MIC in the range of 25-200 µg/mL. To check the possible toxicities of the most active compounds, they were orally administered in rats and the concentration of liver enzymes serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT) and alkaline phosphatase (ALKP) were determined. Compound 4h showed significant increase in the enzymes level depicting the hepatotoxicity. The structure-activity relationship studies showed the importance of electron withdrawing groups at the distant phenyl ring at ortho and para positions as the compounds having chloro or nitro at these positions tend to be more active than the compounds with electron releasing groups such as methoxy. These compounds may act as lead compounds for further studies and appropriate modification in their structure may lead to agents having high efficacy with lesser toxicity.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Venom Gland ◽  
Bioactive Molecules ◽  
Specific Gene ◽  
Animal Kingdom ◽  
Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

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