El Dr. Claudio Cavasotto es especialista en simulación computacional de biomacromoléculas, diseño de fármacos asistido por computadora e informática biomédica. Es Investigador Principal del CONICET y director científico del Instituto de Inteligencia Artificial Aplicada de la Universidad Austral.

Obtuvo su Licenciatura en Física por la Universidad de Buenos Aires, y el Doctorado en Física por la misma institución. Realizó estudios postdoctorales en The Scripps Research Institute (La Jolla, California) en el área de biología computacional y biofísica; luego se unió a  MolSoft LLC (San Diego, CA) como investigador senior, permaneciendo allí cinco años. De 2007 a 2012 fue profesor asociado en el School of Biomedical Informatics de la University of Texas Health Science Center at Houston (Houston, TX), y desde entonces pertenece a la carrera del investigador científico del CONICET.

De acuerdo al reciente estudio de Stanford University publicado en PLOS Biology, se ubica en el top 2% del ranking de mejores científicos del mundo.

El desarrollo de un nuevo fármaco tiene un costo de hasta 2.5 billones de dólares y una duración de hasta 15 años. Sin embargo, la mayoría de las moléculas candidatas fallan en ensayos clínicos debido a cuestiones de eficacia y seguridad. Esto constitutye un serio obstáculo, considerando que los pacientes necesitan acceso urgente a tratamientos efectivos e innovadores, sin efectos colaterales, y económicamente accesibles. Desde hace ya varios años, la (bio)química computacional se ha establecido como una herramienta fundamental en el largo proceso de desarrollo de nuevos fármacos, permitiendo un enfoque más racional, mejorando la eficiencia, y ahorrando tiempo, costos y esfuerzo.

Nuestro laboratorio se ha enfocado desde hace más de 15 años en dos líneas de investigación complementarias: i) estudiando la relación entre la estructura de los complejos biomoleculares, sus propiedades (termo)dinámicas, y su función, identificar moléculas que modulen blancos de interés terapéutico para una variedad de enfermedades, y ii) el desarrollo de una nueva generación de métodos computacionales para el diseño computacional de fármacos. Una componente esencial de nuestra investigación es la estrecha colaboración con investigadores experimentales del país y del extranjero. Utilizamos simulaciones biomoleculares, modelado de estructuras de proteínas por homología, métodos de descubrimiento de fármacos líderes basados en la estructura del receptor y del ligando, y herramientas de inteligencia artificial y quimioinformática.

Nuestro grupo de investigación mantiene activas colaboraciones con: Dra. Mariela Bollini (Centro de Investigaciones en Bionanociencias, CIBION); Dr. Philippe Diaz (Universidad de Montana, Missoula, MT, Estados Unidos); Pilar Cossio (Universidad de Antioquia, Medellín, Colombia).

• Descubrimiento y optimización de fármacos líderes para diferentes blancos terapéuticos, con especial énfasis en SARS-CoV-2, Dengue, Zika, y GPCRs.
• Caracterización de “druggability” de proteomas virales, en particular SARS-CoV-2.
• Desarrollo de métodos de simulación de última generación para el descubrimiento de fármacos líderes basados en mecánica molecular y cuántica, y machine learning.
• Predicción de toxicidad y propiedades farmacológicas utilizando herramientas de inteligencia artificial.

• Villoutreix, B.O., Cavasotto, C. N., and Fernandez-Recio, J. (2022). Editorial: Development of COVID-19 therapies: Lessons learnt and ongoing efforts. Front. Drug Discov. 2:1019705. [doi].
• Scardino, V., Di Filippo, J. I., and Cavasotto, C.N. (2022). How good are AlphaFold models for docking-based virtual screening? ChemRxiv. [doi]
• Adler, N.S., Cababie, L.A., Sarto, C., Cavasotto, C.N., Gebhard, L.G., Estrin, D.A., Gamarnik, A.V., Arrar, M., and Kaufman, S.B. (2022). Insights into the product release mechanism of dengue virus NS3 helicase. Nucleic Acids Res. 50, 6968-6979. [doi]
• Martinez, F.A., Adler, N.S., Cavasotto, C.N., and Aucar, G.A. (2022). Solvent effects on the NMR shieldings of stacked DNA base pairs. Phys. Chem. Chem. Phys. 24, 18150-18160. [doi]
• Di Filippo, J.I., and Cavasotto, C.N. (2022). Guided structure-based ligand identification and design via artificial intelligence modeling. Expert Opin. Drug Discov. 17, 71-78. [doi]
• Scardino, V., Bollini, M., and Cavasotto, C.N. (2021). Combination of pose and rank consensus in docking-based virtual screening: the best of both worlds. RSC Advances 11, 35383-35391. [doi]
• Gallo, G., Erdmann, E., and Cavasotto, C.N. (2021). Evaluation of Silicone Fluids and Resins as CO2 Thickeners for Enhanced Oil Recovery Using a Computational and Experimental Approach. ACS Omega 6, 24803-24813. [doi]
• Di Filippo, J.I., Bollini, M., and Cavasotto, C.N. (2021). A Machine Learning Model to Predict Drug Transfer Across the Human Placenta Barrier. Front. Chem. 9, 714678. [doi]
• Cavasotto, C.N., Lamas, M.S., and Maggini, J. (2021). Functional and druggability analysis of the SARS-CoV-2 proteome. Eur. J. Pharmacol. 890, 173705. [doi]
• Cavasotto, C.N., and Di Filippo, J.I. (2021). Artificial intelligence in the early stages of drug discovery. Arch. Biochem. Biophys. 698, 108730. [doi]
• Cavasotto, C.N., and Di Filippo, J. (2021). In silico Drug Repurposing for COVID-19: Targeting SARS-CoV-2 Proteins through Docking and Consensus Ranking. Mol. Inform. 40, e2000115. [doi]
• Bayo, J., Fiore, E.J., Dominguez, L.M., Cantero, M.J., Ciarlantini, M.S., Malvicini, M., Atorrasagasti, C., Garcia, M.G., Rossi, M., Cavasotto, C.N., Martinez, E., Comin, J., and Mazzolini, G.D. (2021). Bioinformatic analysis of RHO family of GTPases identifies RAC1 pharmacological inhibition as a new therapeutic strategy for hepatocellular carcinoma. Gut 70, 1362-1374. [doi]
• Lans, I., Palacio-Rodriguez, K., Cavasotto, C.N., and Cossio, P. (2020). Flexi-pharma: a molecule-ranking strategy for virtual screening using pharmacophores from ligand-free conformational ensembles. J. Comput-Aided. Mol. Des. 34, 1063-1077. [doi]
• Cavasotto, C.N. and Aucar, M.G. (2020). High-throughput docking using quantum mechanical scoring. Front. Chem. 8, 246. [doi]
• Cavasotto, C.N., and Di Filippo, J.I. (2020). In silico Drug Repurposing for COVID-19: Targeting SARS-CoV-2 Proteins through Docking and Quantum Mechanical Scoring. ChemRxiv. [doi]
• Aucar, M.G., and Cavasotto, C.N. (2020). Molecular Docking Using Quantum Mechanical-Based Methods. Methods Mol. Biol. 2114, 269-284. [pubmed] 
• Cavasotto, C.N. (2020). Binding Free Energy Calculation using Quantum Mechanics Aimed for Drug Lead Optimization. Methods Mol. Biol. 2114, 257-268. [pubmed] 
• Leal, E.S., Adler, N.S., Fernandez, G.A., Gebhard, L.G., Battini, L., Aucar, M.G., Videla, M., Monge, M.E., Hernandez De Los Rios, A., Acosta Davila, J.A., Morell, M.L., Cordo, S.M., Garcia, C.C., Gamarnik, A.V., Cavasotto, C.N., and Bollini, M. (2019). De novo design approaches targeting an envelope protein pocket to identify small molecules against dengue virus. Eur. J. Med. Chem. 182, 111628. [pubmed] [doi] 
• Palacio-Rodriguez, K., Lans, I., Cavasotto, C.N., and Cossio, P. (2019). Exponential consensus ranking improves the outcome in docking and receptor ensemble docking. Sci. Rep. 9, 5142. [pubmed]  [doi]
• Cavasotto, C.N., Aucar, M.G., and Adler, N.S. (2019). Computational chemistry in drug lead discovery and design. Int. J. Quantum Chem. 119, e25678. [doi]
• Szalai, A.M., Armando, N.G., Barabas, F.M., Stefani, F.D., Giordano, L., Bari, S.E., Cavasotto, C.N., Silberstein, S., and Aramendia, P.F. (2018). A fluorescence nanoscopy marker for corticotropin-releasing hormone type 1 receptor: computer design, synthesis, signaling effects, super-resolved fluorescence imaging, and in situ affinity constant in cells. Phys. Chem. Chem. Phys. 20, 29212-29220. [pubmed]  [doi]
• Pascual, M.J., Merwaiss, F., Leal, E., Quintana, M.E., Capozzo, A.V., Cavasotto, C.N., Bollini, M., and Alvarez, D.E. (2018). Structure-based drug design for envelope protein E2 uncovers a new class of bovine viral diarrhea inhibitors that block virus entry. Antivir. Res. 149, 179-190. [pubmed]  [doi]
• Jeong, Y.T., Simoneschi, D., Keegan, S., Melville, D., Adler, N.S., Saraf, A., Florens, L., Washburn, M.P., Cavasotto, C.N., Fenyo, D., Cuervo, A.M., Rossi, M., and Pagano, M. (2018). The ULK1-FBXW5-SEC23B nexus controls autophagy. eLife 7,e42253. [pubmed] [doi]
• Cavasotto, C.N., Adler, N.S., and Aucar, M.G. (2018). Quantum Chemical Approaches in Structure-Based Virtual Screening and Lead Optimization. Front. Chem. 6, 188. [pubmed] [doi]
• Bollini, M., Leal, E.S., Adler, N.S., Aucar, M.G., Fernandez, G.A., Pascual, M.J., Merwaiss, F., Alvarez, D.E., and Cavasotto, C.N. (2018). Discovery of Novel Bovine Viral Diarrhea Inhibitors Using Structure-Based Virtual Screening on the Envelope Protein E2. Front. Chem. 6, 79. [pubmed] [doi]
• Leal, E.S., Aucar, M.G., Gebhard, L.G., Iglesias, N.G., Pascual, M.J., Casal, J.J., Gamarnik, A.V., Cavasotto, C.N., and Bollini, M. (2017). Discovery of novel dengue virus entry inhibitors via a structure-based approach. Bioorg. Med. Chem. Lett. 27, 3851-3855. [pubmed] [doi]
• Echenique, P., Cavasotto, C.N., De Marco, M., Garcia-Risueno, P., and Alonso, J.L. (2017). Correction: An Exact Expression to Calculate the Derivatives of Position-Dependent Observables in Molecular Simulations with Flexible Constraints. PLoS One 12,, e0189454. [pubmed] [doi]
• Lavecchia, M.J., Puig De La Bellacasa, R., Borrell, J.I., and Cavasotto, C.N. (2016). Investigating molecular dynamics-guided lead optimization of EGFR inhibitors. Bioorg. Med. Chem. 24, 768-778. [pubmed]  [doi]
• Spyrakis, F., and Cavasotto, C.N. (2015). Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description. Arch. Biochem. Biophys. 583, 105-119. [pubmed] [doi]
• Spyrakis, F., and Cavasotto, C.N. (2015). «Incorporating Protein Flexibility in Structure-Based Drug Design,» in Lesson Learning from Medicinal Chemistry: In silico Food Science, ed. P. Cozzini. (Hauppauge, NY: Nova Science Publishers).
• Palomba, D., and Cavasotto, C.N. (2015). «Protein Structure Modeling in Drug Design,» in In Silico Drug Discovery and Design: Theory, Methods, Challenges, and Applications, ed. C.N. Cavasotto. (Boca Raton, FL: CRC Press, Taylor & Francis Group), 215-248.
• Cavasotto, C.N., and Palomba, D. (2015). Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models. Chem. Commun. 51, 13576-13594. [pubmed]  [doi]
• Rossi, M., Rotblat, B., Ansell, K., Amelio, I., Caraglia, M., Misso, G., Bernassola, F., Cavasotto, C.N., Knight, R.A., Ciechanover, A., and Melino, G. (2014). High throughput screening for inhibitors of the HECT ubiquitin E3 ligase ITCH identifies antidepressant drugs as regulators of autophagy. Cell Death Dis. 5, e1203. [pubmed]  [doi]
• Petrov, R.R., Knight, L., Chen, S.R., Wager-Miller, J., Mcdaniel, S.W., Diaz, F., Barth, F., Pan, H.L., Mackie, K., Cavasotto, C.N., and Diaz, P. (2013). Mastering tricyclic ring systems for desirable functional cannabinoid activity. Eur. J. Med. Chem. 69, 881-907. [pubmed] [doi]
• Domenech, R., Hernandez-Cifre, J.G., Bacarizo, J., Diez-Pena, A.I., Martinez-Rodriguez, S., Cavasotto, C.N., De La Torre, J.G., Camara-Artigas, A., Velazquez-Campoy, A., and Neira, J.L. (2013). The Histidine-Phosphocarrier Protein of the Phosphoenolpyruvate: Sugar Phosphotransferase System of Bacillus sphaericus Self-Associates. PLoS One 8,e69307. [pubmed]  [doi]
• Brand, C.S., Hocker, H.J., Gorfe, A.A., Cavasotto, C.N., and Dessauer, C.W. (2013). Isoform selectivity of adenylyl cyclase inhibitors: characterization of known and novel compounds. J. Pharmacol. Exp. Ther. 347, 265-275. [pubmed] [doi]
• He, W., Elizondo-Riojas, M.A., Li, X., Lokesh, G.L., Somasunderam, A., Thiviyanathan, V., Volk, D.E., Durland, R.H., Englehardt, J., Cavasotto, C.N., and Gorenstein, D.G. (2012). X-aptamers: a bead-based selection method for random incorporation of druglike moieties onto next-generation aptamers for enhanced binding. Biochemistry 51, 8321-8323. [pubmed]  [doi]
• Gatica, E.A., and Cavasotto, C.N. (2012). Ligand and Decoy Sets for Docking to G Protein-Coupled Receptors. J. Chem. Inf. Model. 52, 1-6. [pubmed]  [doi]
• Forti, F., Cavasotto, C.N., Orozco, M., Barril, X., and Luque, F.J. (2012). A Multilevel Strategy for the Exploration of the Conformational Flexibility of Small Molecules. J.Chem. Theory Comput. 8, 1808-1819. [pubmed]  [doi]
• Dasgupta, I., Tanifum, E.A., Srivastava, M., Phatak, S.S., Cavasotto, C.N., Analoui, M., and Annapragada, A. (2012). Non inflammatory boronate based glucose-responsive insulin delivery systems. PLoS One 7, e29585. [pubmed]  [doi]
• Cavasotto, C.N. (2012). Normal mode-based approaches in receptor ensemble docking. Methods Mol. Biol. 819, 157-168. [pubmed] [doi]
• Cavasotto, C.N. (2012). «Binding free energy calculations and scoring in small-molecule docking,» in Physico-Chemical and Computational Approaches to Drug Discovery, eds.  F.J. Luque & X. Barril. (London: Royal Society of Chemistry), 195-222.
• Vilar, S., Ferino, G., Phatak, S.S., Berk, B., Cavasotto, C.N., and Costanzi, S. (2011). Docking-based virtual screening for ligands of G protein-coupled receptors: not only crystal structures but also in silico models. J. Mol. Graph. Model. 29, 614-623. [pubmed]  [doi]
• Echenique, P., Cavasotto, C.N., and García-Risueño, P. (2011). The canonical equilibrium of constrained molecular models. Eur. Phys. J. Special Topics 200, 5-54. [doi]
• Echenique, P., Cavasotto, C.N., De Marco, M., Garca-Risueño, P., and Alonso, J.L. (2011). An exact expression to calculate the derivatives of position-dependent observables in molecular simulations with flexible constraints. PLoS One 6, e24563. [pubmed]  [doi]
• Cavasotto, C.N., and Phatak, S.S. (2011). Docking methods for structure-based library design. Methods Mol. Biol. 685, 155-174. [pubmed]  [doi]
• Cavasotto, C.N. (2011). Homology models in docking and high-throughput docking. Curr. Top. Med. Chem. 11, 1528-1534. [pubmed]  [doi]
• Cavasotto, C.N. (2011). «Handling protein flexibility in docking and high-throughput docking,» in Virtual Screening. Principles, Challenges and Practical Guidelines, ed. C. Sotriffer.  (Weinheim, Germany: Wiley-VCH Verlag), 245-262.
• Bocanegra, R., Nevot, M., Domenech, R., Lopez, I., Abian, O., Rodriguez-Huete, A., Cavasotto, C.N., Velazquez-Campoy, A., Gomez, J., Martinez, M.A., Neira, J.L., and Mateu, M.G. (2011). Rationally designed interfacial peptides are efficient in vitro inhibitors of HIV-1 capsid assembly with antiviral activity. PLoS One 6, e23877. [pubmed]  [doi]
• Anisimov, V.M., Ziemys, A., Kizhake, S., Yuan, Z., Natarajan, A., and Cavasotto, C.N. (2011). Computational and experimental studies of the interaction between phospho-peptides and the C-terminal domain of BRCA1. J.Comput. Aided Mol. Des. 25, 1071-1084. [pubmed]  [doi]
• Anisimov, V.M., and Cavasotto, C.N. (2011). Quantum mechanical binding free energy calculation for phosphopeptide inhibitors of the Lck SH2 domain. J. Comput. Chem. 32, 2254–2263. [pubmed]  [doi]
• Anisimov, V.M., and Cavasotto, C.N. (2011). Hydration free energies using semiempirical quantum mechanical Hamiltonians and a continuum solvent model with multiple atomic-type parameters. J. Phys. Chem. B 115, 7896-7905. [pubmed] [doi]
• Phatak, S.S., Gatica, E.A., and Cavasotto, C.N. (2010). Ligand-steered modeling and docking: A benchmarking study in Class A G-Protein-Coupled Receptors. J. Chem. Inf. Model. 50, 2119-2128. [pubmed]  [doi]
• Anisimov, V.M., and Cavasotto, C.N. (2010). «Quantum-Mechanical Molecular Dynamics of Charge Transfer,» in Kinetics and Dynamics, eds. P. Paneth & A. Dybala-Defratyka. Springer Netherlands), 247-266.
• Ziemys, A., Ferrari, M., and Cavasotto, C.N. (2009). Molecular modeling of glucose diffusivity in silica nanochannels. J. Nanosci. Nanotechnol. 9, 6349-6359. [pubmed]
• Phatak, S.S., Stephan, C.C., and Cavasotto, C.N. (2009). High-throughput and in silico screenings in drug discovery. Exp. Opin. Drug Discov. 4, 947-959. [pubmed] [doi]
• Monti, M.C., Casapullo, A., Cavasotto, C.N., Tosco, A., Dal Piaz, F., Ziemys, A., Margarucci, L., and Riccio, R. (2009). The binding mode of petrosaspongiolide M to the human group IIA phospholipase A(2): exploring the role of covalent and noncovalent interactions in the inhibition process. Chem.-Eur. J. 15, 1155-1163. [pubmed]
• Diaz, P., Phatak, S.S., Xu, J., Fronczek, F.R., Astruc-Diaz, F., Thompson, C.M., Cavasotto, C.N., and Naguib, M. (2009). 2,3-Dihydro-1-benzofuran derivatives as a series of potent selective cannabinoid receptor 2 agonists: design, synthesis, and binding mode prediction through ligand-steered modeling. ChemMedChem 4, 1615-1629. [pubmed]
• Diaz, P., Phatak, S.S., Xu, J., Astruc-Diaz, F., Cavasotto, C.N., and Naguib, M. (2009). 6-Methoxy-N-alkyl isatin acylhydrazone derivatives as a novel series of potent selective cannabinoid receptor 2 inverse agonists: Design, Synthesis and Binding Mode Prediction. J. Med. Chem. 52, 433-444. [pubmed]
• Cavasotto, C.N., and Phatak, S.S. (2009). Homology modeling in drug discovery: current trends and applications. Drug Discov. Today 14, 676-683. [pubmed]
• Anisimov, V.M., Bugaenko, V.L., and Cavasotto, C.N. (2009). Quantum mechanical dynamics of charge transfer in ubiquitin in aqueous solution. ChemPhysChem 10, 3194-3196. [pubmed]
• Torra, I.P., Ismaili, N., Feig, J.E., Xu, C.F., Cavasotto, C.N., Pancratov, R., Rogatsky, I., Neubert, T.A., Fisher, E.A., and Garabedian, M.J. (2008). Phosphorylation of liver X receptor alpha selectively regulates target gene expression in macrophages. Mol. Cell. Biol. 28, 2626-2636. [pubmed]
• Chen, W., Dang, T., Blind, R.D., Wang, Z., Cavasotto, C.N., Hittelman, A.B., Rogatsky, I., Logan, S.K., and Garabedian, M.J. (2008). Glucocorticoid receptor phosphorylation differentially affects target gene expression. Mol. Endocrinol. 22, 1754-1766. [pubmed]
• Cavasotto, C.N., and Singh, N. (2008). Docking and High Throughput Docking: Successes and the Challenge of Protein Flexibility. Comput.-Aided Drug Design 4, 221-234. [doi]
• Cavasotto, C.N., Orry, A.J., Murgolo, N.J., Czarniecki, M.F., Kocsi, S.A., Hawes, B.E., O’neill, K.A., Hine, H., Burton, M.S., Voigt, J.H., Abagyan, R.A., Bayne, M.L., and Monsma, F.J., Jr. (2008). Discovery of novel chemotypes to a G-protein-coupled receptor through ligand-steered homology modeling and structure-based virtual screening. J. Med. Chem. 51, 581-588. [pubmed]
• Bisson, W.H., Abagyan, R., and Cavasotto, C.N. (2008). Molecular basis of agonicity and antagonicity in the androgen receptor studied by molecular dynamics simulations. J. Mol. Graphics Modell. 27, 452-458. [pubmed]
• Monti, M.C., Casapullo, A., Cavasotto, C.N., Napolitano, A., and Riccio, R. (2007). Scalaradial, a Dialdehyde-Containing Marine Metabolite That Causes an Unexpected Noncovalent PLA(2) Inactivation. ChemBioChem 8, 1585-1591. [pubmed]
• Cavasotto, C.N., and Orry, A.J. (2007). Ligand Docking and Structure-based Virtual Screening in Drug Discovery. Curr. Top. Med. Chem. 7, 1006-1014. [pubmed]
• Orry, A.J., Abagyan, R.A., and Cavasotto, C.N. (2006). Structure-based development of target-specific compound libraries. Drug Discov. Today 11, 261-266. [pubmed]
• Cavasotto, C.N., Ortiz, M.A., Abagyan, R.A., and Piedrafita, F.J. (2006). In silico identification of novel EGFR inhibitors with antiproliferative activity against cancer cells. Bioorg. Med. Chem. Lett. 16, 1969-1974. [pubmed]
• Cavasotto, C.N., Orry, A.J.W., and Abagyan, R. (2006). «Receptor Flexibility in Ligand Docking,» in Handbook of Theoretical and Computational Nanotechnology, M. Rieth & W. Schommers. American Scientific Publishers), 218-257.
• Cavasotto, C.N. (2006). Ligand Docking and Virtual Screening in Structure‐based Drug Discovery. AIP Conf. Proc. 851, 34-49. [doi]
• Li, W., Cavasotto, C.N., Cardozo, T., Ha, S., Dang, T., Taneja, S.S., Logan, S.K., and Garabedian, M.J. (2005). Androgen receptor mutations identified in prostate cancer and androgen insensitivity syndrome display aberrant ART-27 coactivator function. Mol. Endocrinol. 19, 2273-2282. [pubmed]
• Kovacs, J.A., Cavasotto, C.N., and Abagyan, R.A. (2005). Conformational Sampling of Protein Flexibility in Generalized Coordinates: Application to ligand docking. J. Comp. Theor. Nanosci. 2, 354-361. [doi]
• Hernandez, J.A., Meier, J., Barrera, F.N., De Los Panos, O.R., Hurtado-Gomez, E., Bes, M.T., Fillat, M.F., Peleato, M.L., Cavasotto, C.N., and Neira, J.L. (2005). The conformational stability and thermodynamics of Fur A (ferric uptake regulator) from Anabaena sp. PCC 7119. Biophys J. 89, 4188-4200. [pubmed]
• Cavasotto, C.N., Orry, A.J.W., and Abagyan, R.A. (2005). The Challenge of Considering Receptor Flexibility in Ligand Docking and Virtual Screening. Curr. Comput.-Aided Drug Des. 1, 423-440. [doi]
• Cavasotto, C.N., Kovacs, J.A., and Abagyan, R.A. (2005). Representing Receptor Flexibility in Ligand Docking through Relevant Normal Modes. J. Am. Chem. Soc. 127, 9632-9640. [pubmed] [doi]
• Cavasotto, C.N., Liu, G., James, S.Y., Hobbs, P.D., Peterson, V.J., Bhattacharya, A.A., Kolluri, S.K., Zhang, X.K., Leid, M., Abagyan, R., Liddington, R.C., and Dawson, M.I. (2004). Determinants of retinoid X receptor transcriptional antagonism. J. Med. Chem. 47, 4360-4372. [pubmed]
• Cavasotto, C.N., and Abagyan, R.A. (2004). Protein flexibility in ligand docking and virtual screening to protein kinases. J. Mol. Biol. 337, 209-225.
• Giribet, C.G., De Azúa, M.C.R., Vizioli, C.V., and Cavasotto, C.N. (2003). Electronic mechanisms of intra and intermolecular J couplings in systems with C-H…O interactions. Int. J. Mol. Sci. 4, 203-217. [doi]
• Cavasotto, C.N., Orry, A.J., and Abagyan, R.A. (2003). Structure-based identification of binding sites, native ligands and potential inhibitors for G-protein coupled receptors. Proteins 51, 423-433. [pubmed]
• Bordner, A.J., Cavasotto, C.N., and Abagyan, R.A. (2003). Direct derivation of van der Waals force field parameters from quantum mechanical interaction energies. J. Phys. Chem. B 107, 9601-9609. [doi]
• Bordner, A.J., Cavasotto, C.N., and Abagyan, R.A. (2002). Accurate Transferable Model for Water, n-Octanol, and n-Hexadecane Solvation Free Energies. J. Phys. Chem. B 106, 11009-11015. [doi]
• Cavasotto, C.N. (2000). Finite expansion of the inverse matrix in the polarization propagator method. Theo. Chem. Acc. 104, 491-498. [doi]
• Cavasotto, C.N., and Grinberg, H. (1999). A Liouville-space method for the decoupling of the polarization propagator equation of motion. Chem.  Phys. Lett. 303, 558-566. [doi]
• Bochicchio, R.C., Ferraro, M.B., Grinberg, H., and Cavasotto, C.N. (1995). Self-Energies for the Particle-Hole Propagator from Feynman-Dyson Equations. J. Mol. Struct. (THEOCHEM) 335, 1-9. [doi]
• Cavasotto, C.N., Giribet, C.G., De Azúa, M.C.R., and Contreras, R.H. (1991). Exo-Exo and Endo-Endo Vicinal Proton Spin-Spin Coupling-Constants in Norbornane and Norbornene – an IPPP-CLOPPA Analysis. J.Comput. Chem. 12, 141-146. [doi]
• Contreras, R.H., Giribet, C.G., De Azúa, M.C.R., Cavasotto, C.N., Aucar, G.A., and Krivdin, L.B. (1990). Quantum Chemical-Analysis of the Orientational Lone-Pair Effect on Spin-Spin Coupling-Constants. J. Mol. Struct. (THEOCHEM) 69, 175-186. [doi]
• Cavasotto, C.N., Giribet, C.G., De Azúa, M.C.R., Contreras, R.H., and Pérez, J.E. (1990). 2J(Se-Se) Couplings in Diseleno-Substituted Alkenylic Compounds – a CLOPPA-IPPPAnalysis. J. Mag. Reson. 87, 209-219. [doi]
• Cavasotto, C.N., Giribet, C.G., and Contreras, R.H. (1990). Localization Method for Semiempirical Molecular-Orbitals Based on the Boys-Foster Criterion. J. Mol. Struct. (THEOCHEM) 69, 107-110. [doi]

• In Silico Drug Discovery and Design: Theory, Methods, Challenges, and Applications.  Ed. C. Cavasotto, CRC Press, Taylor & Francis Group, Boca Raton, FL, 2015; 558 pp, ISBN 978-1-4822-1783-4.

• PICT 2014-3599, “Cálculo de la energía libre de unión en complejos ligando-proteína con métodos cuánticos: Desarrollo y aplicación al diseño de fármacos”
• PICT-2017-3767, “Diseño y síntesis de moléculas pequeñas con actividad antiviral contra los virus de Dengue y Zika”

Dr. Claudio N. Cavasotto, Investigador Principal CONICET, CCavasotto@austral.edu.ar

Lic. M. Gabriela Aucar, Becaria doctoral CONICET, MGAucar@mail.austral.edu.ar

Lic. Natalia Adler, Becaria doctoral Agencia.

Lic. Juan Di Filippo, Becario doctoral, JDiFilippo@austral.edu.ar

Dirección: Av. Pte. Perón 1500, Derqui, Pilar, Buenos Aires

Mail: CCavasotto@austral.edu.ar