General information
| Name: ALFONSO T. |
| Surname: GARCIA-SOSA |
| E-mail: t.alfonso @ gmail . com |
| Cell phone number with international prefix: |
| Country: Estonia |
| Affiliation: Institute of Chemistry, University of Tartu |
| Gender: M □x |
| PhD: University of Cambridge, UK. New Approaches to the Use of Water Molecules in Computer-Aided Drug Design |
| Personal web page: http://hermes.chem.ut.ee/~alfx/index.html ; www.atg21.com |
| Previous COST participation: Yes □ x COST CM1307 Targeted chemotherapy towards diseases caused by endoparasites |
List of 10 selected publications within last 5 years
| 1. Viira B., Selyutina A., García-Sosa A. T., Karonen M., Sinkkonen J., Merits A., Maran U., “Design, Discovery, Modelling, Synthesis, and Biological Evaluation of Novel and Small, Low Toxicity s-Triazine Derivatives as HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors”, Bioorganic & Medicinal Chemistry, 2016, In the Press, Published online 8th April 2016. B.V., A.S. and A.T.G.-S. contributed equally. DOI: http://dx.doi.org/10.1016/j.bmc.2016.04.018 |
| 2. Takkis K., García-Sosa A. T., Sild S., “Virtual Screening for HIV Protease Inhibitors Using a Novel Database Filtering Procedure”, Molecular Informatics, 2015, Vol. 34, Iss. 6-7, 485-492. DOI: http://onlinelibrary.wiley.com/doi/10.1002/minf.201400170/full |
| 3. García-Sosa A.T.* and Mancera R.L., “Free Energy Calculations of Mutations Involving a Tightly Bound Water Molecule and Ligand Substitutions in a Ligand-Protein Complex”, Molecular Informatics, 2010, Vol. 29, Iss. 8-9, 589-600. http://www.atg21.com/Garcia-SosaAT_molinf2010.pdf |
| 4. García-Sosa A.T.,* and Maran U., “Improving the Use of Ranking in Virtual Screening against HIV-1 Integrase with Triangular Numbers and Including Ligand Profiling with Anti-Targets”, Journal of Chemical Information and Modeling, 2014, Vol. 54, Iss. 11, 3172-3185. DOI: http://pubs.acs.org/doi/pdf/10.1021/ci500300u |
| 5. García-Sosa A.T.,* Tulp I., Langel K., Langel U., “Peptide-Ligand Binding Modeling of siRNA with Cell-Penetrating Peptides”, BioMed Research International, 2014, Vol. 2014, Article ID 257040, 7 pages. DOI: http://dx.doi.org/10.1155/2014/257040 |
| 6. García-Sosa A.T.* “Hydration Properties of Ligands and Drugs in Protein Binding Sites: Tightly-Bound, Bridging Water Molecules and Their Effects and Consequences on Molecular Design Strategies”, Journal of Chemical Information and Modeling, 2013, Vol. 53, Iss. 6, 1388-1405. DOI: http://dx.doi.org/10.1021/ci3005786 |
| 7. García-Sosa A.T.* and Maran U., “Drugs, Non-Drugs, and Disease Category Specificity: Organ Effects by Ligand Pharmacology”, SAR and QSAR in Environmental Research, 2013, Vol. 24, Iss. 4, 585-597. http://dx.doi.org/10.1080/1062936X.2013.773373 |
| 8. García-Sosa A.T.,* Oja M., Hetényi C., Maran U., “DrugLogit: Logistic Discrimination Between Drugs and Non-drugs Including Disease-Specificity by Assigning Probabilities Based on Molecular Properties”, Journal of Chemical Information and Modeling, 2012, Vol. 52, Iss. 8, 2165-2180. DOI: http://dx.doi.org/10.1021/ci200587h |
| 9. García-Sosa A.T., Maran U., Hetényi C., “Molecular Property Filters Describing Pharmacokinetics and Drug Binding”, Current Medicinal Chemistry, 2012, Vol. 19, 1646-1662. http://www.atg21.com/Garcia-SosaATcurrmedchem2012forweb.pdf |
| 10. García-Sosa A.T.,* Sild S., Takkis K., Maran U., “Combined Approach using Ligand Efficiency, Cross-Docking, and Anti-Target Hits for Wild-Type and Drug-Resistant Y181C HIV-1 Reverse Transcriptase”, Journal of Chemical Information and Modeling, 2011, Vol. 51, Iss. 10, 2595-2611. http://dx.doi.org/10.1021/ci200203h |
Main skills and expertise (up to 5)
| 1. Molecular dynamics of biomolecules such as proteins, peptides, and nucleic acids, including protein-ligand complexes and biomembranes |
| 2. Virtual screening and profiling of compounds, docking and targeting |
| 3. Anti-targets |
| 4. Homology modeling |
| 5. Quantum mechanics calculations |
Main equipment/facilities available in the participants’ lab (up to 5)
| 1. Server room hosting a computer cluster with 400 CPU cores and graphical processing units for computationally intensive tasks, various application servers, two database and two storage servers with 66 TB of disk space |
| 2. State-of-the-art commercial software packages, as well as in-house developed software, including QSARdb, a database of chemicals and models. |
| 3. A wet lab with equipment for synthesis and analysis, UV-Vis. |
| 4. A recently-built chemistry dedicated building with advanced capabilities for teaching and research |
| 5. 16 workstations and dedicated technical staff. |
Short personal activity proposal for the COST Action CA15135 (max 1000 characters)
| Our group has been successfully involved in other COST actions, participating in research collaborations, and STSMs. The aim for the present COST action would be to foster new research projects and collaborations, hosting and being involved in new STSMs, including other COST member countries in grant applications.
We are open and ready to promote collaborations with other groups to compliment computational and data approaches with experimental chemistry and biology. |
Work Group preference: score from 1 (preferred) to 4 (not preferred)
| Work Group of the CA15135 COST Action | Score |
| WG1: Development of new chemical entities | 1 |
| WG2: Selection of biological targets and assessment of biological data | 2 |
| WG3: Development of chemical databases | 3 |
| WG4: Development of Computational methods for multiple ligand design and discovery | 1 |
