Universitat Rovira i Virgili

CV Santi Garcia-Vallve

Santi Garcia-Vallvé
Biochemistry and Biotechnology Department
Rovira i Virgili University. Tarragona.

ORCID ID: 0000-0002-0348-7497
ResearcherID:  A-4226-2008
Publons: publons.com/a/645325/

Contact address:
Santi Garcia-Vallve
Departament de Bioquímica i Biotecnologia
Universitat Rovira i Virgili (URV)
Campus Sescelades
c/ Marcel·li Domingo, 1
43007 TARRAGONA
SPAIN
Phone:+34 977558778
Fax:+34 977558232
Email: santi.garcia-vallve at urv.cat

   ACADEMIC RECORD
2003-present: Lecturer at the Biochemistry and Biotechnology Department, Faculty of Chemistry, Universitat Rovira i Virgili (URV), Tarragona
July-October 2016 Visitor at the Bender Group, Department of Chemistry, Cambridge University, UK
2001-2003: Assistant Professor at the Biochemistry and Biotechnology Department, URV
May-Sept. 2001: EMBO-short term fellow (Ref. ASTF 9801) at the Computational Genomics Group, European Bioinformatics Institute (EBI), Cambridge, UK
2000: Associate Professor at the Biochemistry and Biotechnology Department, URV
1996-1999: PhD degree in Biochemistry (URV). PhD Fellow from the Generalitat de Catalunta (FIAP/96-7.030)
1990-1995:

B.Sc degree in Chemistry (URV). Fellowship from the Ministerio de Educación y Ciencia to collaborate with the Biochemistry and Biotechnology Department (URV) (B.O.E. no 108, 6 de mayo de 1995, pág. 13219).

    MERITS RELATED TO RESEARCH/ACADEMIC ACTIVITY

  • SER-LAB prize at 1995 to the student with the best academic expedient integrated in a research group of the Faculty of Chemistry of the URV
  • Participant of the BioROM (learning material to biochemistry, biotechnology and molecular biology)
  • Member of the Scientific Committee of the organization of the congress of the Spanish Society of Evolutionary Biology. Tarragona, 27-29th September 2007
  • Evaluation favorable at the Recognition Program Quality Research (RQR) of the Rovira i Virgili University that identifies the scientist with a research activity that has an impact on quality significantly higher than the world average in his/her research field. Since 2011-12 to 2014-15
  • Included in the 2020 Stanford University list of the World's Top 2% of most influential researchers. Rank 592 for the composite citation index (self-citations excluded) among a total 80622 scientist from the Medicinal and Biomolecular Chemistry discipline (Ioannidis et al. Updated science-wide author databases of standardized citation indicators. PLoS Biol. 2020 Oct 16;18(10):e3000918. doi: 10.1371/journal.pbio.3000918)
  • Included in 2021 the Stanford University list of the World's Top 2% of most influential researchers. Rank 633 for the composite citation index (self-citations excluded) among a total 88725 scientist from the Medicinal and Biomolecular Chemistry discipline (Baas et al. 2021 Mendeley Data, V3, doi: 10.17632/ btchxktzyw.3)
  • Included in the 2022 Stanford University list of the World's Top 2% of most influential researchers. Rank 1224 for the composite citation index (self-citations excluded) among a total 94,672 scientist from the Medicinal and Biomolecular Chemistry discipline (Ioannidis et al. 2022. September 2022 data-update for “Updated science-wide author databases of standardized citation indicators”. Mendeley Data, V5, doi: 10.17632/btchxktzyw.5)
  • Included in the 2023 Stanford University list of the World's Top 2% of most influential researchers. Rank 1234 for the composite citation index (self-citations excluded) among a total 99,369 scientist from the Medicinal and Biomolecular Chemistry discipline (Ioannidis, John P.A. (2023), "October 2023 data-update for "Updated science-wide author databases of standardized citation indicators"", Elsevier Data Repository, V6, doi: 10.17632/btchxktzyw.6).

    MEMBER OF

   RESEARCH INTERESTS

In my beginning as a researcher, I was introduced to the fields of Bioinformatics and sequence analysis. My PhD thesis was centered in the analysis of bacterial complete genomes and in the detection, using computational tools, of horizontally transferred genes. My post-doctoral stay for 5 months in the European Bioinformatics Institute (EBI) in Cambridge, UK, helped me to acquire a solid formation in programming and bioinformatics. With my research team, we published several articles in prestigious international journals, such as Nucleic Acids Research, Trends in Genetics, Trends in Microbiology, Genome Research, Bioinformatics and Molecular Biology and Evolution. I also developed several databases, web-servers and tools for the prediction of horizontally transferred genes and highly expressed genes, the analysis of codon usage bias, codon adaptation and codon usage optimization in bacterial genes and genomes. With my integration, in 2009, to the Nutrigenomics group at the Biochemistry and Biotechnology Department of the Rovira i Virgili University, I changed my research focus to Cheminformatics and Computational Drug Design. Now, I belong to the Cheminformatics and Nutrition Group at the Biochemistry and Biotechnology Department of the Rovira i Virgili University. Our aim is, using a similar methodology used in the field of computational drug design, to search for natural compounds that can activate or inhibit certain molecular targets, such enzymes and transcription factors, and be potential new ingredients in the food industry to develop new functional foods (a food given an additional function, often one related to health-promotion or disease prevention).

In the field of developing new antidiabetics, we have contributed to the analysis of the differences between full and partial agonists of PPARgamma and we have developed a virtual screening procedure to search for new partial agonists of PPARgamma. Using this procedure we have demonstrated that several natural compounds act as antidiabetic compounds, reducing the insulin resistance associated with the diabetes type II, because they bind and activate the nuclear receptor PPARgamma. In addition, our research group have found new antidiabetic compounds that inhibit the dipeptidyl peptidase-4 (DPP4) and new anti-inflammatory compounds that inhibit the inhibitor of nuclear factor kappa-B kinase subunit beta (IKK2). We have also developed several new cheminformatic tools for helping the virtual screening process, for example for finding decoys and validate the models of crystallized protein structures. My short stay as a visitor in the Bender group at the Department of Chemistry, Cambridge University, UK in 2016, allowed me to acquire solid knowledge in machine learning. Our results have been published in prestigious international journals, such as Journal of Medicinal Chemistry, Methods, Journal of Cheminformatics, Plos One, Journal of Computer-Aided Molecular Design, and European Journal of Medicinal Chemistry. We have been funded by the Spanish Government with the project AGL2011-25831 and by some enterprise projects.

Since the COVID-19 epidemic we have focused our research activity on the development of new SARS-CoV-2 M-pro inhibitors and the analysis of the SARS-CoV-2 mutations. We have proposed new M-pro inhibitors, we have highlighted the limitations of protein-docking to identify new SARS-CoV-2 M-pro inhibitors, analyzed the mutations of SARS-CoV-2 and predicted the recurrent mutations in SARS-CoV-2 using artificial neural networks. Our results on SARS-CoV-2 have been published in the International Journal of Molecular Sciences, International Journal of Infectious Diseases and Medicinal Research Reviews.

  • Past Research interests:
Bioinformatics, Molecular evolution, Phylogenetic analyses, Horizontal Gene Transfer Prediction, Bacterial Genome Analysis, Codon usage, Highly Expressed Genes.
  • Current Research Interests:
Cheminformatics, Medicinal Chemistry, Virtual screening, QSAR, Machine Learning, Target Fishing, Decoys, Computational Drug Design, Machine learning, Development of new functional food ingredients, SARS-CoV-2 M-pro inhibitors, SARS-CoV-2 mutations.
   PhD STUDENTS
  • 2004-2007 Pere Puigbò Avalos
  • 2007-2011 Laura Guasch Pàmies
  • 2012-2017 Adrià Ceretó Massagué
  • 2012-2017 Maria José Ojeda
  • 2012-2017 Sarah Tomás Hernández
  • 2015-2019 Aleix Gimeno Vives
  • 05/03/2019-  Bryan Saldivar Espinoza
  • 02/12/2019-15/05/2023  Guillem Macip Sancho
  • 15/02/2023 – Ariadna Llop Peiró
 

   Bioinformatic Tools and Databases Developed

SARS-CoV-2 Mutation Portal
Authors: Rubén Martínez Bernabé, Santi Garcia-Vallvé and Bryan Saldivar-Espinoza

http://sarscov2-mutation-portal.urv.cat/SARS-CoV-2_mutation-portal/

Saldivar-Espinoza B, Garcia-Segura P, Novau-Ferré N, Macip G, Martínez R, Puigbò P, Cereto-Massagué A, Pujadas G, Garcia-Vallve S. The Mutational Landscape of SARS-CoV-2. Int J Mol Sci. 2023 May 22;24(10):9072. doi: 10.3390/ijms24109072

This database contains SARS-CoV-2 mutation data from the beginning of the COVID-19 pandemic. The data are derived from the analysis of more than 4.5 million complete genomes available in GISAID. Various information such as mutation type, location, % of times observed, countries, lineages, VOCs, ..... is collected. The results are displayed in tabular form and in a scatter plot.

 

VHELIBS
Author: Adrià Ceretó

https://github.com/URVquimioinformatica-COS/VHELIBS

Cereto-Massagué A, Ojeda MJ, Joosten RP, Valls C, Mulero M, Salvado MJ, Arola-Arnal A, Arola L, Garcia-Vallvé S, Pujadas G. (2013). The good, the bad and the dubious: VHELIBS, a validation helper for ligands and binding sites. J Cheminform., 5(1):36. doi: 10.1186/1758-2946-5-36

The Validation HElper for LIgands and Binding Sites (VHELIBS) aims to ease the validation of binding site and ligand coordinates for non-crystallographers (i.e. users with little or no crystallography knowledge) by checking how their coordinates fit to their corresponding electron density map and letting the user to use models from either the PDB or PDB_REDO. The user can specify threshold values for a series of properties related with coordinates to electron density fitting (where Real Space R, Real Space Correlation Coefficient and average occupancy are the ones used by default) and, VHELIBS will automatically label residues and ligands with values within the specified limits, and the rest as either dubious or bad based on an user-configurable tolerance value. The user then is able to visually check the fitness quality of the residues/ligands to their corresponding electron density map, and reclassify them if needed.

 

DecoyFinder
Author: Adrià Ceretó

https://github.com/URVquimioinformatica-COS/DecoyFinder

Releases

Cereto-Massague, A., Guasch, L., Valls, C., Mulero, M., Pujadas, G., & Garcia-Vallve, S. (2012). DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets. Bioinformatics, 28(12):1661-1662. doi:10.1093/bioinformatics/bts249

DecoyFinder is a graphical tool which helps finding sets of decoy molecules for a given group of active ligands. It does so by finding molecules which have a similar number of rotational bonds, hydrogen bond acceptors, hydrogen bond donors, logP value and molecular weight, but are chemically different, which is defined by a maximum Tanimoto value threshold between active ligand and decoy molecule MACCS fingerprints. Optionally, a maximum Tanimoto value threshold can be set between decoys in order to assure chemical diversity in the decoy set.

 

RCDI / eRCDI
Author: Pere Puigbò

http://genomes.urv.cat/CAIcal/RCDI/

http://ppuigbo.me/programs/CAIcal/RCDI/

Puigbo P, Aragones L and Garcia-Vallve S. (2010) RCDI/eRCDI: a web-server to estimate codon usage deoptimization. BMC Research Notes, 3:87.

The RCDI server is a web-application that calculates the Relative Codon Deoptimization Index (RCDI) and an expected value of the RCDI for a set of query sequences by generating random sequences with similar G+C content and amino acid composition to the input. This expected RCDI therefore provides a direct threshold value for discerning whether the differences in the RCDI value are statistically significant and arise from the codon preferences or whether they are merely artifacts that arise from internal biases in the G+C composition and/or amino acid composition of the query sequences. Please, click here to get a quick tutorial.

 

CAIcal/E-CAI
Author: Pere Puigbò

http://genomes.urv.cat/CAIcal/

http://genomes.urv.cat/CAIcal/E-CAI/

http://ppuigbo.me/programs/CAIcal/

Puigbo P, Bravo IG and Garcia-Vallve S. 2008 E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI). BMC Bioinformatics, 9:65.

Puigbo P., Bravo IG and Garcia-Vallve S. 2008 CAIcal: a combined set of tools to assess codon usage adaptation. Biology Direct, 3:38.

This server performs several computations in relation to codon usage and the codon adaptation of DNA or RNA sequences to host organisms. The E-CAI server is a web-application and an executable program that calculates the expected value of the Codon Adaptation Index (CAI) for a set of query sequences by generating random sequences with similar G+C content and amino acid composition to the input. This expected CAI therefore provides a direct threshold value for discerning whether the differences in the CAI value are statistically significant and arise from the codon preferences or whether they are merely artifacts that arise from internal biases in the G+C composition and/or amino acid composition of the query sequences.

 

Highly Expresse Genes Database
Author: Pere Puigbò

http://genomes.urv.cat/HEG-DB/

Puigbo P, Romeu A and Garcia-Vallve S. 2008. HEG-DB: a database of predicted highly expressed genes in prokaryotic complete genomes under translational selection.Nucleic Acids Research36:D524-7. doi:10.1093/nar/gkm831

The HEG-DB is a genomic database that includes the prediction of which genes are highly expressed in prokaryotic complete genomes under strong translational selection. The current version of the database contains general features for almost 200 genomes under translational selection, including the correspondence analysis of the relative synonymous codon usage for all genes, and the analysis of their highly expressed genes. For each genome, the database contains functional and positional information about the predicted group of highly expressed genes. This information can also be accessed using a search engine. Among other statistical parameters, the database also provides the Codon Adaptation Index for all of the genes using the codon usage of the highly expressed genes as a reference set. The "Pathway Tools Omics Viewer" from the BioCyc database enables the metabolic capabilities of each genome to be explored, particularly those related to the group of highly expressed genes.

 

OPTIMIZER
Author: Pere Puigbò

http://genomes.urv.cat/OPTIMIZER/

http://ppuigbo.me/programs/optimizerlite/

P. Puigbò, E. Guzman, A. Romeu and S. Garcia-Vallvé (2007) OPTIMIZER: A web server for optimizing the codon usage of DNA sequences. Nucleic Acids Research 35:W126-W131.

OPTIMIZER is an on-line PHP application that optimizes the codon usage of a DNA sequence to increase its expression level. Users can introduce their own preference tables to be used in the optimization process or use pre-computed tables from several prokaryotic species under a strong translational selection. Three methods of optimization are available: the 'one amino acid - one codon' approach, a random approach or an intermediate one. Several options, such as avoiding specific restriction sites and several outputs, are also available. This server can be useful for predicting and optimizing the level expression of a gene in heterologous gene expression.

 

TOPD/fMtS
Author: Pere Puigbò

http://ppuigbo.me/programs/topd/

P. Puigbò, S. Garcia-Vallvé and J.O. McInernet (2007) TOPD/FMTS: a new software to compare phylogenetic trees. Bioinformatics, 23:1556-1558. doi: 10.1093/bioinformatics/btm135.

TOPD/FMTS is a new software for comparing phylogenetic trees. It has been developed to calculate the differences between trees. The software implements several previously described methods and new algorithms for comparing phylogenetic trees. It combines the TOPD program (TOPological Distance), which compares two trees with the same taxa or two pruned trees, and the FMTS program (From Multiple To Single), which converts multi-gene family trees to single-gene trees.

 

Horizontal Gene Tranfer Database
Author: Santi Garcia-Vallvé

http://genomes.urv.cat/HGT-DB/ (not available anymore)

https://usuaris.tinet.cat/debb/HGT/welcomeOLD.html (an old version)

S. Garcia-Vallve, E. Guzman, MA. Montero and A. Romeu. 2003. HGT-DB: a database of putative horizontally transferred genes in prokaryotic complete genomes. Nucleic Acids Research 31:187-189.

The HGT-DB is a genomic database that includes statistical parameters such as G+C content, codon and amino-acid usage, as well as information about which genes deviate in these parameters for prokaryotic complete genomes. Under the hypothesis that genes from distantly related species have different nucleotide compositions, these deviated genes may have been acquired by horizontal gene transfer. The current version of the database includes the analysis of 94 bacterial and archaeal complete genomes, including multiple chromosomes and strains, when available. Other complete genomes will be added progressively.

 

DendroUPGMA
Author: Santi Garcia-Vallvé

http://genomes.urv.cat/UPGMA/

https://usuaris.tinet.cat/debb/UPGMA/

S. Garcia-Vallve, J. Palau and A. Romeu (1999) Horizontal gene transfer in glycosyl hydrolases inferred from codon usage in Escherichia coli and Bacillus subtilis. Molecular Biology and Evolution 9:1125-1134.

Use this program to create a dendrogram from a set of variables. The program calculates a similarity coefficient between pairs of sets of variables, transforms these coefficients into distances and makes a clustering using the Unweighted Pair Group Method with Arithmetic mean (UPGMA) algorithm.

TRANSLATE

Translate
Author: Santi Garcia-Vallvé

https://usuaris.tinet.cat/debb/Translate/

A web server utility that translates a set of DNA sequences.

   REVIEWER OF THE FOLLOWING JOURNALS

Algal Research, Applied Microbiology, Bioinformatics, Biomolecules, Bioorganic & Medicinal Chemistry, Biosystems, BMC Bioinformatics, BMC Biotechnology, BMC Evolutionary Biology, BMC Genomics, BMC Microbiology, Briefings in Bioinformatics, Database, European Journal of Pharmaceutical Sciences, Food & Function, Gene, Genome, Genome Biology and Evolution, International Journal of Molecular Sciences, In Silico Pharmacology,  Journal of Computational Science, Journal of Computer-Aided Molecular Design, Journal of Ethnopharmacology, Journal of Food Science and Nutrition Therapy, Journal of Molecular Evolution, Molecular Biology and Evolution, Journal of Molecular Graphics and Modelling, Medicinal research Reviews, Molecules, Nature Communications, Nucleic Acids Research, Pharmacological Research, Planta Medica, RSC Advances, SAR and QSAR in Environmental Research, Transactions on Computational Biology and bioinformatics, Trends in Genetics

 Publons publons.com/a/645325/

RECENT TALKS:

  • "A general view of computational methods for target fishing and focus on the use of fingerprints for chemical similarity searching". International Work-Conference on Bioinformatics and Biomedical Engineering. Granada, 20-22th April 2016

PUBLICATIONS

- Llop-Peiró A, Pujadas G, Garcia-Vallvé S. Challenges in distinguishing functional proteins from polyproteins in databases: implications for drug discovery. Brief Bioinform. 2024 Jan 22;25(2):bbae012. doi: 10.1093/bib/bbae012.

- Cuffaro D, Gimeno A, Bernardoni BL, Di Leo R, Pujadas G, Garcia-Vallvé S, Nencetti S, Rossello A, Nuti E. Identification of N-Acyl Hydrazones as New Non-Zinc-Binding MMP-13 Inhibitors by Structure-Based Virtual Screening Studies and Chemical Optimization. Int J Mol Sci. 2023 Jul 4;24(13):11098. doi: 10.3390/ijms241311098

- Saldivar-Espinoza B, Garcia-Segura P, Novau-Ferré N, Macip G, Martínez R, Puigbò P, Cereto-Massagué A, Pujadas G, Garcia-Vallve S. The Mutational Landscape of SARS-CoV-2. Int J Mol Sci. 2023 May 22;24(10):9072. doi: 10.3390/ijms24109072

- Fadlallah S, Julià C, García-Vallvé S, Pujadas G, Serratosa F. Drug Potency Prediction of SARS-CoV-2 Main Protease Inhibitors Based on a Graph Generative Model. Int J Mol Sci. 2023 May 15;24(10):8779. doi: 10.3390/ijms24108779

- Saldivar-Espinoza B, Macip G, Garcia-Segura P, Mestres-Truyol J, Puigbo P, Cereto-Massague A, Pujadas G, Garcia-Vallve S. Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks. Int. J. Mol. Sci. 2022, 23(23), 14683; https://doi.org/10.3390/ijms232314683

- Saldivar-Espinoza B, Macip G, Pujadas G, Garcia-Vallve S. Could nucleocapsid be a next-generation COVID-19 vaccine candidate? Int J Infect Dis. 2022 Nov 5;125:231-232. doi: 10.1016/j.ijid.2022.11.002.

- Estanyol-Torres N, Domenech-Coca C, González-Domínguez R, Miñarro A, Reverter F, Moreno-Muñoz JA, Jiménez J, Martín-Palomas M, Castellano-Escuder P, Mostafa H, García-Vallvé S, Abasolo N, Rodríguez MA, Torrell H, Del Bas JM, Sanchez-Pla A, Caimari A, Mas-Capdevila A, Andres-Lacueva C, Crescenti A. A mixture of four dietary fibres ameliorates adiposity and improves metabolic profile and intestinal health in cafeteria-fed obese rats: an integrative multi-omics approach. J Nutr Biochem. 2023 Jan;111:109184. doi: 10.1016/j.jnutbio.2022.109184.

- Grau-Bové C, Grau-Bové X, Terra X, Garcia-Vallve S, Rodríguez-Gallego E, Beltran-Debón R, Blay MT, Ardévol A, Pinent M. Functional and genomic comparative study of the bitter taste receptor family TAS2R: Insight into the role of human TAS2R5. FASEB J. 2022 Mar;36(3):e22175. doi: 10.1096/fj.202101128RR.

- Macip G, Garcia-Segura P, Mestres-Truyol J, Saldivar-Espinoza B, Pujadas G, Garcia-Vallvé S. A Review of the Current Landscape of SARS-CoV-2 Main Protease Inhibitors: Have We Hit the Bullseye Yet? Int. Int J Mol Sci. 2022 23(1):259. doi: 10.3390/ijms23010259.

- Macip G, Garcia-Segura P, Mestres-Truyol J, Saldivar-Espinoza B, Ojeda-Montes MJ, Gimeno A, Cereto-Massagué A, Garcia-Vallvé S, Pujadas G. Haste makes waste: A critical review of docking-based virtual screening in drug repurposing for SARS-CoV-2 main protease (M-pro) inhibition. Med Res Rev. 2021 Oct 26. doi: 10.1002/med.21862

- Gimeno A, Cuffaro D, Nuti E, Ojeda-Montes MJ, Beltrán-Debón R, Mulero M, Rossello A, Pujadas G, Garcia-Vallvé S. Identification of Broad-Spectrum MMP Inhibitors by Virtual Screening. Molecules. 2021 Jul 28;26(15):4553. doi: 10.3390/molecules26154553.

- Tomas-Hernandez S, Blanco J, Garcia-Vallvé S, Pujadas G, Ojeda-Montes MJ, Gimeno A, Arola L, Minghetti L, Beltrán-Debón R, Mulero M. Anti-Inflammatory and Immunomodulatory Effects of the Grifola frondosa Natural Compound o-Orsellinaldehyde on LPS-Challenged Murine Primary Glial Cells. Roles of NF-κβ and MAPK. Pharmaceutics. 2021 May 28;13(6):806. doi: 10.3390/pharmaceutics13060806.

- Truong Nguyen P, Garcia-Vallvé S, Puigbò P. An Unsupervised Algorithm for Host Identification in Flaviviruses. Life (Basel). 2021 May 14;11(5):442. doi: 10.3390/life11050442.

- Gimeno A, Mestres-Truyol J, Ojeda-Montes MJ, Macip G, Saldivar-Espinoza B, Cereto-Massagué A, Pujadas G, Garcia-Vallvé S. Prediction of Novel Inhibitors of the Main Protease (M-pro) of SARS-CoV-2 through Consensus Docking and Drug Reposition. Int J Mol Sci. 2020 May 27;21(11):3793. doi: 10.3390/ijms21113793.

- Gimeno A, Beltrán-Debón R, Mulero M, Pujadas G, Garcia-Vallvé S. Understanding the variability of the S1' pocket to improve matrix metalloproteinase inhibitor selectivity profiles. Drug Discov Today. 2020 Jan;25(1):38-57. doi: 10.1016/j.drudis.2019.07.013.

- Ojeda-Montes MJ, Casanova-Martí À, Gimeno A, Tomás-Hernández S, Cereto-Massagué A, Wolber G, Beltrán-Debón R, Valls C, Mulero M, Pinent M, Pujadas G, Garcia-Vallvé S. Mining large databases to find new leads with low similarity to known actives: application to find new DPP-IV inhibitors. Future Med Chem. 2019 Jun;11(12):1387-1401. doi: 10.4155/fmc-2018-0597.

- Gimeno A, Ojeda-Montes MJ, Tomás-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Mulero M, Pujadas G, Garcia-Vallvé S. The Light and Dark Sides of Virtual Screening: What Is There to Know? Int J Mol Sci. 2019 Mar 19;20(6). pii: E1375. doi: 10.3390/ijms20061375.

- Tomas-Hernandez S, Garcia-Vallvé S, Pujadas G, Valls C, Ojeda-Montes MJ, Gimeno A, Cereto-Massagué A, Roca-Martinez J, Suárez M, Arola L, Blanco J, Mulero M, Beltran-Debón R. Anti-inflammatory and Proapoptotic Properties of the Natural Compound o-Orsellinaldehyde. J Agric Food Chem. 2018 Oct 24;66(42):10952-10963. doi: 10.1021/acs.jafc.8b00782.

- Gimeno A, Ardid-Ruiz A, Ojeda-Montes MJ, Tomás-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Mulero M, Valls C, Aragonès G, Suárez M, Pujadas G, Garcia-Vallvé S. Combined ligand- and receptor-based virtual screening methodology to identify structurally diverse PTP1B inhibitors. ChemMedChem. 2018 Sep 19;13(18):1939-1948. doi: 10.1002/cmdc.201800267.

- Solé-Llussà A, Casanoves M, Salvadó Z, Garcia-Vallvé S, Valls C, Novo M. Annapurna expedition game: applying molecular biology tools to learn genetics. J Bio Educ. 2018. doi: 10.1080/00219266.2018.1501409

- Ojeda-Montes MJ, Gimeno A, Tomas-Hernández S, Cereto-Massagué A, Beltrán-Debón R, Valls C, Mulero M, Pujadas G, Garcia-Vallvé SActivity and selectivity cliffs for DPP-IV inhibitors: Lessons we can learn from SAR studies and their application to virtual screening. Med Res Rev. 2018 Sep;38(6):1874-1915. doi: 10.1002/med.21499.

- Tomas-Hernández S, Blanco J, Rojas C, Roca-Martínez J, Ojeda-Montes MJ, Beltrán-Debón R, Garcia-Vallve S, Pujadas G, Arola L, Mulero M. Resveratrol Potently Counteracts Quercetin Starvation-Induced Autophagy and Sensitizes HepG2 Cancer Cells to Apoptosis. Mol Nutr Food Res. 2018 Mar;62(5). doi: 10.1002/mnfr.201700610.

- Kukhtar D, Mulero M, Beltrán-Debón R, Valls C, Pujadas G , Garcia-Vallve S. Multiple Peroxisome Proliferator-Activated Receptor-Based Ligands, in Drug Selectivity: An Evolving Concept in Medicinal Chemistry (eds N. Handler and H. Buschmann), Book Series: Methods and Principles in Medicinal Chemistry. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2017 doi: 10.1002/9783527674381.ch14

- Ojeda-Montes MJ, Ardid-Ruiz A, Tomás-Hernández S, Gimeno A, Cereto-Massagué A, Beltrán-Debón R, Mulero M, Garcia-Vallvé S, Pujadas G, Valls C. Ephedrine as a lead compound for the development of new DPP-IV inhibitors. Future Med Chem. 2017 Nov 27; 9(18):2129-2146. doi: 10.4155/fmc-2017-0080.

- Teresa Novo M, Casanoves M, Garcia-Vallvé S, Pujadas G, Mulero M, Valls C. How do Detergents Work? A Qualitative Assay to Measure Amylase Activity. J Bio Educ. 2016 50(3):251-60 doi: 10.1080/00219266.2015.1058843

- Garcia-Vallvé S, Guasch L, Tomas-Hernández S, Del Bas JM, Ollendorff V, Arola L, Pujadas G, Mulero M. Peroxisome Proliferator-Activated Receptor γ (PPARγ) and Ligand Choreography: Newcomers Take the Stage. J Med Chem. 2015 Jul 23;58(14):5381-94. doi: 10.1021/jm501155f.

- Cereto-Massagué A, Ojeda MJ, Valls C, Mulero M, Pujadas G, Garcia-Vallve STools for in silico target fishing. Methods. 2015 Jan;71:98-103. doi: 10.1016/j.ymeth.2014.09.006

- Cereto-Massagué A, Ojeda MJ, Valls C, Mulero M, Garcia-Vallvé S, Pujadas G. Molecular fingerprint similarity search in virtual screening. Methods. 2015 Jan;71:58-63. doi: 10.1016/j.ymeth.2014.08.005

- García-Vallve S, Guasch L, Mulero M. Discovery of Natural Products that Modulate the Activity of PPARgamma: A Source for New Antidiabetics. In: Foodinformatics. Applications of Chemical Information to Food Chemistry. Martinez-Mayorga, Karina, Medina-Franco, José Luis (Eds.), pp 151-176. Springer, 2014. ISBN 978-3-319-10226-9

- Rojas C, Pan-Castillo B, Valls C, Pujadas G, Garcia-Vallve S, Arola L, Mulero M. Resveratrol enhances palmitate-induced ER stress and apoptosis in cancer cells. PLoS One. 2014 Dec 1;9(12):e113929. doi: 10.1371/journal.pone.0113929. eCollection 2014

- Cereto-Massagué A, Ojeda MJ, Joosten RP, Valls C, Mulero M, Salvado MJ, Arola-Arnal A, Arola L, Garcia-Vallvé S, Pujadas G. The good, the bad and the dubious: VHELIBS, a validation helper for ligands and binding sites. J Cheminform. 2013 Jul 29;5(1):36. doi: 10.1186/1758-2946-5-36

- Pallarès V, Fernández-Iglesias A, Cedó L, Castell-Auví A, Pinent M, Ardévol A, Salvadó MJ, Garcia-Vallvé S, Blay M. Grape seed procyanidin extract reduces the endotoxic effects induced by lipopolysaccharide in rats. Free Radic Biol Med. 2013 Jul;60:107-14. doi: 10.1016/j.freeradbiomed.2013.02.007

- Guasch L, Sala E, Mulero M, Valls C, Salvadó MJ, Pujadas G, Garcia-Vallvé S. Identification of PPARgamma partial agonists of natural origin (II): in silico prediction in natural extracts with known antidiabetic activity. PLoS One. 2013;8(2):e55889. doi: 10.1371/journal.pone.0055889

- Guasch L, Sala E, Castell-Auví A, Cedó L, Liedl KR, Wolber G, Muehlbacher M, Mulero M, Pinent M, Ardévol A, Valls C, Pujadas G, Garcia-Vallvé S. Identification of PPARgamma partial agonists of natural origin (I): development of a virtual screening procedure and in vitro validation. PLoS One. 2012;7(11):e50816. doi: 10.1371/journal.pone.0050816

- Guerrero L, Castillo J, Quiñones M, Garcia-Vallvé S, Arola L, Pujadas G, Muguerza B. Inhibition of angiotensin-converting enzyme activity by flavonoids: structure-activity relationship studies. PLoS One. 2012;7(11):e49493. doi:10.1371/journal.pone.0049493

- Guasch L, Sala E, Ojeda MJ, Valls C, Bladé C, Mulero M, Blay M, Ardévol A, Garcia-Vallvé S, Pujadas G. Identification of novel human dipeptidyl peptidase-IV inhibitors of natural origin (Part II): in silico prediction in antidiabetic extracts. PLoS One. 2012;7(9):e44972. doi: 10.1371/journal.pone.0044972

- Guasch L, Ojeda MJ, González-Abuín N, Sala E, Cereto-Massagué A, Mulero M, Valls C, Pinent M, Ardévol A, Garcia-Vallvé S, Pujadas G. Identification of novel human dipeptidyl peptidase-IV inhibitors of natural origin (part I): virtual screening and activity assays. PLoS One. 2012;7(9):e44971. doi: 10.1371/journal.pone.0044971

- González-Abuín N, Martínez-Micaelo N, Blay M, Pujadas G, Garcia-Vallvé S, Pinent M, Ardévol A. Grape seed-derived procyanidins decrease dipeptidyl-peptidase 4 activity and expression. J Agric Food Chem. 2012 Sep 12;60(36):9055-61. doi: 10.1021/jf3010349

- Valls C, Rojas C, Pujadas G, Garcia-Vallve S, Mulero M. Characterization of the activity and stability of amylase from saliva and detergent: laboratory practicals for studying the activity and stability of amylase from saliva and various commercial detergents. Biochem Mol Biol Educ. 2012 Jul;40(4):254-65. doi: 10.1002/bmb.20612

- Cereto-Massagué A, Guasch L, Valls C, Mulero M, Pujadas G, Garcia-Vallvé S. DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets. Bioinformatics. 2012 Jun 15;28(12):1661-2. doi:10.1093/bioinformatics/bts249

- Guasch L, Sala E, Valls C, Mulero M, Pujadas G, Garcia-Vallvé S. Development of docking-based 3D-QSAR models for PPARgamma full agonists. J Mol Graph Model. 2012 Jun;36:1-9. doi: 10.1016/j.jmgm.2012.03.001

- Castell-Auví A, Cedó L, Pallarès V, Blay MT, Pinent M, Motilva MJ, Garcia-Vallvé S, Pujadas G, Maechler P, Ardévol A. Procyanidins modify insulinemia by affecting insulin production and degradation. J Nutr Biochem. 2012 Dec;23(12):1565-72. doi: 10.1016/j.jnutbio.2011.10.010

- Quesada H, Díaz S, Pajuelo D, Fernández-Iglesias A, Garcia-Vallvé S, Pujadas G, Salvadó MJ, Arola L, Bladé C. The lipid-lowering effect of dietary proanthocyanidins in rats involves both chylomicron-rich and VLDL-rich fractions. Br J Nutr. 2012 Jul;108(2):208-17. doi: 10.1017/S0007114511005472

- Sala E, Guasch L, Iwaszkiewicz J, Mulero M, Salvadó MJ, Bladé C, Ceballos M, Valls C, Zoete V, Grosdidier A, Garcia-Vallvé S, Michielin O, Pujadas G. Identification of human IKK-2 inhibitors of natural origin (Part II): in Silico prediction of IKK-2 inhibitors in natural extracts with known anti-inflammatory activity. Eur J Med Chem. 2011 Dec;46(12):6098-103. doi:10.1016/j.ejmech.2011.09.022

- Valls C, Pujadas G, Garcia-Vallve S, Mulero M. Characterization of the protease activity of detergents: laboratory practicals for studying the protease profile and activity of various commercial detergents. Biochem Mol Biol Educ. 2011 Jul;39(4):280-90. doi: 10.1002/bmb.20488

- Guasch L, Sala E, Valls C, Blay M, Mulero M, Arola L, Pujadas G, Garcia-Vallvé S. Structural insights for the design of new PPARgamma partial agonists with high binding affinity and low transactivation activity. J Comput Aided Mol Des. 2011 Aug;25(8):717-28. doi: 10.1007/s10822-011-9446-9

- Sala E, Guasch L, Iwaszkiewicz J, Mulero M, Salvadó MJ, Pinent M, Zoete V, Grosdidier A, Garcia-Vallvé S, Michielin O, Pujadas G. Identification of human IKK-2 inhibitors of natural origin (part I): modeling of the IKK-2 kinase domain, virtual screening and activity assays. PLoS One. 2011 Feb 24;6(2):e16903. doi:10.1371/journal.pone.0016903

- Puigbò P, Aragonès L, Garcia-Vallvé S. RCDI/eRCDI: a web-server to estimate codon usage deoptimization. BMC Res Notes. 2010 Mar 31;3:87. doi: 10.1186/1756-0500-3-87

- Pallejà A, García-Vallvé S, Romeu A. Adaptation of the short intergenic spacers between co-directional genes to the Shine-Dalgarno motif among prokaryote genomes. BMC Genomics. 2009 Nov 18;10:537. doi: 10.1186/1471-2164-10-537

- Pallejà A, Reverter T, Garcia-Vallvé S, Romeu A. PairWise Neighbours database: overlaps and spacers among prokaryote genomes. BMC Genomics. 2009 Jun 25;10:281. doi: 10.1186/1471-2164-10-281

- Puigbò P, Bravo IG, Garcia-Vallve S. CAIcal: a combined set of tools to assess codon usage adaptation. Biol Direct. 2008 Sep 16;3:38. doi: 10.1186/1745-6150-3-38

- Pallejà A, Guzman E, Garcia-Vallvé S, Romeu A. In silico prediction of the origin of replication among bacteria: a case study of Bacteroides thetaiotaomicron. OMICS. 2008 Sep;12(3):201-10. doi: 10.1089/omi.2008.0004

- Guzmán E, Romeu A, Garcia-Vallve S. Completely sequenced genomes of pathogenic bacteria: a review. Enferm Infecc Microbiol Clin. 2008 Feb;26(2):88-98

- Puigbò P, Bravo IG, Garcia-Vallvé S. E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI). BMC Bioinformatics. 2008 Jan 29;9:65. doi: 10.1186/1471-2105-9-65

- Puigbò P, Pasamontes A, Garcia-Vallve S. Gaining and losing the thermophilic adaptation in prokaryotes. Trends Genet. 2008 Jan;24(1):10-4

- Puigbò P, Romeu A, Garcia-Vallvé S. HEG-DB: a database of predicted highly expressed genes in prokaryotic complete genomes under translational selection. Nucleic Acids Res. 2008 Jan;36(Database issue):D524-7

- Marcet-Houben M, Puigbò P, Romeu A, Garcia-Vallve S. Towards reconstructing a metabolic tree of life. Bioinformation. 2007;2(4):135-44

- Puigbò P., Garcia-Vallvé S. and McInerney J.O.  TOPD/FMTS: a new software to compare phylogenetic trees. Bioinformatics. 2007 Jun 15;23(12):1556-8

- Puigbò P., Guzmán E., Romeu A. and Garcia-Vallvé S. OPTIMIZER: A web server for optimizing the codon usage of DNA sequences. Nucleic Acids Res. 2007 Jul;35(Web Server issue):W126-31

- Rojas A, Montero MA, Guzmán E, Pallejà A, Puigbò P, Garcia-Vallvé S and Romeu A. Thodosius Dobzhansky (1900-1975). El naixement de la teoria sintètica. Actes de la VIII trobada d'història de la ciència i de la tècnica. Barcelona, SCHCT, 2006. 349-354

- Pasamontes A. and Garcia-Vallve S. 2006. Use of a multi-way method to analyze the amino acid composition of a conserved group of orthologous proteins in prokaryotes. BMC Bioinformatics 7:257

- Garcia-Vallve S, Iglesias-Rozas JR, Alonso A, Bravo IG. 2006. Different papillomaviruses have different repertoires of transcription factor binding sites: convergence and divergence in the upstream regulatory region. BMC Evol. Biol. 6:20

- Garcia-Vallve, S., Alonso, A. and Bravo, I.G. 2005. Papillomaviruses: different genes have different histories. Trends in Microbiology 13(11):514-21

- Bravo, I.G., Garcia-Vallvé, S., Romeu, A. and Reglero, A. 2004. Prokaryotic origin of cytidylyltransferases and alpha-ketoacid synthases. Trends in Microbiology 12:120-8

- Garcia-Vallve, S. 2004. Contribution of each complex of the mitochondrial respiratory chain in the generation of the proton-motive force. Biochemistry and Molecular Biology Education 32:17-19

- Rojas, A., Garcia-Vallvé, S., Montero, M.A., Arola, Ll. and Romeu, A. 2003. Frameshift mutation events in beta-glucosidases. GENE 314: 191-199

- Garcia-Vallve, S, Guzman, E., Montero, MA. and Romeu, A. 2003. HGT-DB: a database of putative horizontally transferred genes in prokaryotic complete genomes. Nucleic Acids Research 31: 187-189

- Garcia-Vallve, S, Janssen, P i Ouzounis CA. 2002. Genetic variation between Helicobacter pylori strains: gene acquisition or loss? Trends in Microbiology 10:445-447

- Garcia-Vallve, S, Simó, FX, Montero, MA, Arola, Ll and Romeu, A. 2002. Simultaneous horizontal gene transfer of a gene coding for ribosomal protein L27 and operational genes in Arthrobacter sp. Journal Molecular and Evolution 55: 632-637

- Garcia-Vallve, S., Romeu, A. and Palau, J. 2000. Horizontal gene transfer in bacterial and archeal complete genomes. Genome Research 10:1719-1725

- Garcia-Vallve, S., Romeu, A. and Palau, J. 2000. Horizontal gene transfer of glycosyl hydrolases of the rumen fungi. Molecular Biology and Evolution 17:352-361

- Garcia-Vallve, S., Palau, J. and Romeu, A. 1999. Horizontal gene transfer in glycosyl hydrolases inferred from codon usage in Escherichia coli and Bacillus subtili. Molecular Biology and Evolution 16:1125-1134

- Rojas, A., Garcia-Vallve, S., Palau, J. and Romeu, A. 1999. Circular permutation in proteins. Biologia 54:255-277

- Garcia-Vallve, S., Rojas, A., Palau, J. and Romeu, A. 1998. Circular permutants in b-glucosidases (family 3) within a predicted double-domain topology which includes a (b/a)8-barrel. Proteins 31:214-223

- Palau, J., Pujadas, G., Negrete, JA., Viñuales, Y. and Garcia-Vallve, S. 1998. La tecnologia computacional com a eina d’anàlisi per a l’evolució molecular i per al desxiframent d’estructures de proteïnes. Dinàmica Estructural de Macromolècules. Treballs de la Societat Catalana de Biologia 48:93-141 15:665-682

- Garcia-Vallve, S. and Palau, J. 1998. Nuclear receptors, nuclear receptor factors, and nuclear recepetor-like orphans form a large paralog cluster in Homo sapiens. Molecular Biology and Evolution 15:665-682