Kororamides, convolutamines, and indole derivatives as possible tau and dual specificity kinases inhibitors for Alzheimer's Disease

Alzheimer's disease (AD) is becoming one of the most disturbing health and socioeconomic problems nowadays, as it is a neurodegenerative pathology with no treatment, which is expected to grow further due to population ageing. Actual treatments for AD produce only a modest amelioration of symptoms, although there is a constant ongoing research of new therapeutic strategies oriented to improve the amelioration of the symptoms, and even to completely cure the disease. A principal feature of AD is the presence of neurofibrillary tangles (NFT) induced by the aberrant phosphorylation of the microtubule-associated protein tau in the brains of affected individuals. Glycogen synthetase kinase-3 beta (GSK3β), casein kinase 1 delta (CK1δ), dual-specificity tyrosine phosphorylation regulated kinase 1A (DYRK1A) and dual-specificity kinase cdc2-like kinase 1 (CLK1) have been identified as the principal proteins involved in this process. Due to this, the inhibition of these kinases has been proposed as a plausible therapeutic strategy to fight AD. In this study, we tested in silico the inhibitory activity of different marine natural compounds, as well as newly-designed molecules from some of them, over the mentioned protein kinases, finding some new possible inhibitors with potential therapeutic application

Evaluation of cross-validation strategies in sequence-based binding prediction using deep learning

Binding prediction between targets and drug-like compounds through deep neural networks has generated promising results in recent years, outperforming traditional machine learning-based methods. However, the generalization capability of these classification models is still an issue to be addressed. In this work, we explored how different cross-validation strategies applied to data from different molecular databases affect to the performance of binding prediction proteochemometrics models. These strategies are (1) random splitting, (2) splitting based on K-means clustering (both of actives and inactives), (3) splitting based on source database, and (4) splitting based both in the clustering and in the source database. These schemas are applied to a deep learning proteochemometrics model and to a simple logistic regression model to be used as baseline. Additionally, two different ways of describing molecules in the model are tested: (1) by their SMILES and (2) by three fingerprints. The classification performance of our deep learning-based proteochemometrics model is comparable to the state of the art. Our results show that the lack of generalization of these models is due to a bias in public molecular databases and that a restrictive cross-validation schema based on compound clustering leads to worse but more robust and credible results. Our results also show better performance when representing molecules by their fingerprints.Peer ReviewedPostprint (author's final draft

Computer-Aided Drug Design (CADD) to De-Orphanize Marine Molecules: Finding Potential Therapeutic Agents for Neurodegenerative and Cardiovascular Diseases

Computer-aided drug design (CADD) techniques allow the identification of compounds capable of modulating protein functions in pathogenesis-related pathways, which is a promising line on drug discovery. Marine natural products (MNPs) are considered a rich source of bioactive compounds, as the oceans are home to much of the planet's biodiversity. Biodiversity is directly related to chemodiversity, which can inspire new drug discoveries. Therefore, natural products (NPs) in general, and MNPs in particular, have been used for decades as a source of inspiration for the design of new drugs. However, NPs present both opportunities and challenges. These difficulties can be technical, such as the need to dive or trawl to collect the organisms possessing the compounds, or biological, due to their particular marine habitats and the fact that they can be uncultivable in the laboratory. For all these difficulties, the contributions of CADD can play a very relevant role in simplifying their study, since, for example, no biological sample is needed to carry out an in-silico analysis. Therefore, the amount of natural product that needs to be used in the entire preclinical and clinical study is significantly reduced. Here, we exemplify how this combination between CADD and MNPs can help unlock their therapeutic potential. In this study, using a set of marine invertebrate molecules, we elucidate their possible molecular targets and associated therapeutic potential, establishing a pipeline that can be replicated in future studies

Meridianins and Lignarenone B as Potential GSK3β Inhibitors and Inductors of Structural Neuronal Plasticity

Glycogen Synthase Kinase 3 (GSK3) is an essential protein, with a relevant role in many diseases such as diabetes, cancer and neurodegenerative disorders. Particularly, the isoform GSK3β is related to pathologies such as Alzheimer's disease (AD). This enzyme constitutes a very interesting target for the discovery and/or design of new therapeutic agents against AD due to its relation to the hyperphosphorylation of the microtubule-associated protein tau (MAPT), and therefore, its contribution to neurofibrillary tangles (NFT) formation. An in silico target profiling study identified two marine molecular families, the indole alkaloids meridianins from the tunicate genus Aplidium, and lignarenones, the secondary metabolites of the shelled cephalaspidean mollusc Scaphander lignarius, as possible GSK3β inhibitors. The analysis of the surface of GSK3β, aimed to find possible binding regions, and the subsequent in silico binding studies revealed that both marine molecular families can act over the ATP and/or substrate binding regions. The predicted inhibitory potential of the molecules from these two chemical families was experimentally validated in vitro by showing a ~50% of increased Ser9 phosphorylation levels of the GSK3β protein. Furthermore, we determined that molecules from both molecular families potentiate structural neuronal plasticity in vitro. These results allow us to suggest that meridianins and lignarenone B could be used as possible therapeutic candidates for the treatment of GSK3β involved pathologies, such as AD

Silibinin is a direct inhibitor of STAT3.

We herein combined experimental and computational efforts to delineate the mechanism of action through which the flavonolignan silibinin targets STAT3. Silibinin reduced IL-6 inducible, constitutive, and acquired feedback activation of STAT3 at tyrosine 705 (Y705). Silibinin attenuated the inducible phospho-activation of Y705 in GFP-STAT3 genetic fusions without drastically altering the kinase activity of the STAT3 upstream kinases JAK1 and JAK2. A comparative computational study based on docking and molecular dynamics simulation over 14 different STAT3 inhibitors (STAT3i) predicted that silibinin could directly bind with high affinity to both the Src homology-2 (SH2) domain and the DNA-binding domain (DBD) of STAT3. Silibinin partially overlapped with the cavity occupied by other STAT3i in the SH2 domain to indirectly prevent Y705 phosphorylation, yet showing a unique binding mode. Moreover, silibinin was the only STAT3i predicted to establish direct interactions with DNA in its targeting to the STAT3 DBD. The prevention of STAT3 nuclear translocation, the blockade of the binding of activated STAT3 to its consensus DNA sequence, and the suppression of STAT3-directed transcriptional activity confirmed silibinin as a direct STAT3i. The unique characteristics of silibinin as a bimodal SH2- and DBD-targeting STAT3i make silibinin a promising lead for designing new, more effective STAT3i.This work was supported by grants from the Ministerio de Ciencia e Innovacion (Grant SAF2016-80639-P to J. A. Menendez), Plan Nacional de I + D + I, Spain, and the Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR) (Grant 2014 SGR229 to J. A. Menendez). This study was supported also by unrestricted research grants from Roche Pharma (Spain) and Astellas Pharma (Spain) to the Program Against Cancer Therapeutic Resistance (ProCURE, Catalan Institute of Oncology). Joaquim Bosch-Barrera is supported by SEOM, Pfizer (Grant WI190764), Boehringer Ingelheim, Meda Pharma, and Pla strategic de recerca i innovacio en salut 2016-2020 de la Generalitat de Catalunya (SLT006/17/114). Elisabet Cuyas is supported by a Sara Borrell postdoctoral contract (CD15/00033) from the Ministerio de Sanidad y Consumo, Fondo de Investigacion Sanitaria (FIS), Spain. The authors would like to thank Dr. Kenneth McCreath for editorial support.S

Metformin Is a Direct SIRT1-Activating Compound: Computational Modeling and Experimental Validation

Metformin has been proposed to operate as an agonist of SIRT1, a nicotinamide adenine dinucleotide (NAD(+))-dependent deacetylase that mimics most of the metabolic responses to calorie restriction. Herein, we present an in silico analysis focusing on the molecular docking and dynamic simulation of the putative interactions between metformin and SIRT1. Using eight different crystal structures of human SIRT1 protein, our computational approach was able to delineate the putative binding modes of metformin to several pockets inside and outside the central deacetylase catalytic domain. First, metformin was predicted to interact with the very same allosteric site occupied by resveratrol and other sirtuin-activating compounds (STATCs) at the amino-terminal activation domain of SIRT1. Second, metformin was predicted to interact with the NAD(+) binding site in a manner slightly different to that of SIRT1 inhibitors containing an indole ring. Third, metformin was predicted to interact with the C-terminal regulatory segment of SIRT1 bound to the NAD(+) hydrolysis product ADP-ribose, a "C-pocket"-related mechanism that appears to be essential for mechanism-based activation of SIRT1. Enzymatic assays confirmed that the net biochemical effect of metformin and other biguanides such as a phenformin was to improve the catalytic efficiency of SIRT1 operating in conditions of low NAD(+) in vitro. Forthcoming studies should confirm the mechanistic relevance of our computational insights into how the putative binding modes of metformin to SIRT1 could explain its ability to operate as a direct SIRT1 -activating compound. These findings might have important implications for understanding how metformin might confer health benefits via maintenance of SIRT1 activity during the aging process when NAD(+) levels decline

The extra virgin olive oil phenolic oleacein is a dual substrate-inhibitor of catechol-O-methyltransferase

Catechol-containing polyphenols present in coffee and tea, while serving as excellent substrates for catechol-Omethyltransferase (COMT)-catalyzed O-methylation, can also operate as COMT inhibitors. However, little is known about the relationship between COMT and the characteristic phenolics present in extra virgin olive oil (EVOO). We here selected the EVOO dihydroxy-phenol oleacein for a computational study of COMT-driven methylation using classic molecular docking/molecular dynamics simulations and hybrid quantum mechanical/ molecular mechanics, which were supported by in vitro activity studies using human COMT. Oleacein could be superimposed onto the catechol-binding site of COMT, maintaining the interactions with the atomic positions involved in methyl transfer from the S-adenosyl-L-methionine cofactor. The transition state structure for the meta-methylation in the O5 position of the oleacein benzenediol moiety was predicted to occur preferentially. Enzyme analysis of the conversion ratio of catechol to O-alkylated guaiacol confirmed the inhibitory effect of oleacein on human COMT, which remained unaltered when tested against the protein version encoded by the functional Val158Met polymorphism of the COMT gene. Our study provides a theoretical determination of how EVOO dihydroxy-phenols can be metabolized via COMT. The ability of oleacein to inhibit COMT adds a new dimension to the physiological and therapeutic utility of EVOO secoiridoids

Metformin Is a Direct SIRT1-Activating Compound: Computational Modeling and Experimental Validation

Metformin has been proposed to operate as an agonist of SIRT1, a nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase that mimics most of the metabolic responses to calorie restriction. Herein, we present an in silico analysis focusing on the molecular docking and dynamic simulation of the putative interactions between metformin and SIRT1. Using eight different crystal structures of human SIRT1 protein, our computational approach was able to delineate the putative binding modes of metformin to several pockets inside and outside the central deacetylase catalytic domain. First, metformin was predicted to interact with the very same allosteric site occupied by resveratrol and other sirtuin-activating compounds (STATCs) at the amino-terminal activation domain of SIRT1. Second, metformin was predicted to interact with the NAD+ binding site in a manner slightly different to that of SIRT1 inhibitors containing an indole ring. Third, metformin was predicted to interact with the C-terminal regulatory segment of SIRT1 bound to the NAD+ hydrolysis product ADP-ribose, a “C-pocket”-related mechanism that appears to be essential for mechanism-based activation of SIRT1. Enzymatic assays confirmed that the net biochemical effect of metformin and other biguanides such as a phenformin was to improve the catalytic efficiency of SIRT1 operating in conditions of low NAD+ in vitro. Forthcoming studies should confirm the mechanistic relevance of our computational insights into how the putative binding modes of metformin to SIRT1 could explain its ability to operate as a direct SIRT1-activating compound. These findings might have important implications for understanding how metformin might confer health benefits via maintenance of SIRT1 activity during the aging process when NAD+ levels decline

Extra-virgin olive oil contains a metabolo-epigenetic inhibitor of cancer stem cells

We are grateful to Custodio Borrego for giving us free use of the photograph he took of EVOO and olive trees in Granada (Spain), which have been included in Figure 7. This work has been awarded with the IV Premio Internacional Castillo de Canena de Investigación Oleícola ‘LUIS VAÑÓ’(IV Edition of Castillo de Canena LUIS VAÑÓ Award for Research on Olive Cultivation and Olive Oil; UC Davis Olive Center, Castillo de Canena, and Universidad de Jaén).The authors would like to thank Dr Kenneth McCreath for editorial support. We are greatly indebted to Prof Robert A. Weinberg (Whitehead Institute for Biomedical Research, Cambridge, MA) for providing the HMLERshCntrol/HMLERshEcad cells used in this work.Targeting tumor-initiating, drug-resistant populations of cancer stem cells (CSC) with phytochemicals is a novel paradigm for cancer prevention and treatment. We herein employed a phenotypic drug discovery approach coupled to mechanism-of-action profiling and target deconvolution to identify phenolic components of extra virgin olive oil (EVOO) capable of suppressing the functional traits of CSC in breast cancer (BC). In vitro screening revealed that the secoiridoid decarboxymethyl oleuropein aglycone (DOA) could selectively target subpopulations of epithelial-like, aldehyde dehydrogenase (ALDH)-positive and mesenchymal-like, CD44+CD24−/low CSC. DOA could potently block the formation of multicellular tumorspheres generated from single-founder stem-like cells in a panel of genetically diverse BC models. Pretreatment of BC populations with noncytotoxic doses of DOA dramatically reduced subsequent tumor-forming capacity in vivo. Mice orthotopically injected with CSC-enriched BC-cell populations pretreated with DOA remained tumor-free for several months. Phenotype microarray-based screening pointed to a synergistic interaction of DOA with the mTOR inhibitor rapamycin and the DNA methyltransferase (DNMT) inhibitor 5-azacytidine. In silico computational studies indicated that DOA binds and inhibits the ATP-binding kinase domain site of mTOR and the S-adenosyl-l-methionine (SAM) cofactorbinding pocket of DNMTs. FRET-based Z-LYTE™ and AlphaScreen-based in vitro assays confirmed the ability of DOA to function as an ATP-competitive mTOR inhibitor and to block the SAM-dependent methylation activity of DNMTs. Our systematic in vitro, in vivo and in silico approaches establish the phenol-conjugated oleoside DOA as a dual mTOR/DNMT inhibitor naturally occurring in EVOO that functionally suppresses CSC-like states responsible for maintaining tumorinitiating cell properties within BC populations.This work was supported by grants from the Ministerio de Ciencia e Innovación (Grant SAF2016-80639-P to J.A.M.), Plan Nacional de I+D+I, Spain, the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR; Grant 2014 SGR229 to J.A.M.), Departament d’Economia i Coneixement, Catalonia, Spain, the Andalusian Regional Government Council of Innovation and Science (Grant P11-CTS-7625 to A.S.-C.), the Ministerio de Economía, Industria y Competitividad, Spain (Grants AGL2015- 67995-C2-3-R and AGL2015-67995-C3-1-R to A.S.-C. and V.M.) and Conselleria d’Educació, Investigació, Cultura I Esport, Generalitat Valenciana, Spain (Grant PROMETEO/2016/006 to V.M). E.C. is supported by the Sara Borrell post doctoral contract (CD15/00033) from the Ministerio de Sanidad y Consumo, Fondo de Investigación Sanitaria (FIS), Spain

Qm and qm/mm studies on organic and bioinorganic systems

En els darrers anys, les millores tant a nivell de maquinari com a nivell de programari han suposat un gran avenç, per la química computacional, ajudant-la a estar cada vegada més a prop dels problemes reals de la química i la bioquímica.Així doncs, si fins fa uns anys per descriure un sistema només es podia fer amb un nombre molt limitat d'àtoms, actualment la millor eficiència dels mètodes de mecànica quàntica (QM) i la possibilitat de fer càlculs híbrids (QM/MM), barrejant la mecànica quàntica amb la molecular (MM), fan créixer enormement les possibilitats de càlcul.En aquesta tesi es recullen alguns exemples d'aplicacions dels mètodes QM i QM/MM de la química computacional en diferents situacions de sistemes orgànics (estabilitat dels 4-ehlicens, síntesi assimètrica de 5-helicenoquinones i l'ús de salts de guanidini com a catal·litzadors ens organocatàl·lisi) i de sistemes bioinorgànics (estudi de les format deshidrogenases per entendre l'efecte del seleni i el metall en el centre actiu).The application of computational chemistry has been expanding in recent years. It is due the huge increase of the available computer resources and the improvement of more effective software. It helps the computational chemistry to become increasingly closer to understand and solve key chemical problems.Some years ago, only small systems with a reduced number of atoms can be studied. Nowadays, the better efficiency of the quantum mechanics methods (QM) plus the possibility to work with hybrid (QM/MM), mixing quantum mechanics and molecular mechanics methods, implies a huge increment of possibilities.In this thesis, some applications of QM and QM/MM are summarized and different organic (thermal stability of 4-helicenes, asymmetric synthesis of 5-helicenequinones and the application of guanidinium salts derivatives as organocatalyst) and bioinorganic (study the role of selenium and molybdenum or tungsten in the active center of the formate dehydrogenases enzymes) have been studied