Research interests

  • Kinetics and thermodynamics of ligand-protein binding
  • Molecular modeling and simulation of ligand-protein interactions
  • structure-based drug design
  • quantitative structure-kinetics relationship
  • tunnel engineering

Research Units in UniSysCat

Awards (selection)

2020 HITS award for commitment to women in science
2019 Capes-Humboldt Research Fellowship for postdoctoral research
2018 Selected for the CellNetworks Postdoctoral Program
2014 Ph.D. fellowship from Fapesp (São Paulo Research Foundation, Brazil)

Dr. Ariane Ferreira Nunes Alves
Technische Universität Berlin
Institute of Chemistry, Office TC 019
Straße des 17. Juni 124
10623 Berlin
+49 (0)30 314-29555
ferreira.nunes.alves(at)tu-berlin.de
https://anunesalves.owlstown.net/

Publications (selection)

Nunes-Alves, A.; Ormersbach, F.; Wade, R.C. Prediction of drug-target binding kinetics for flexible proteins by Comparative Binding Energy analysis. J. Chem. Inf. Model. 2021, in press. https://doi.org/10.1021/acs.jcim.1c00639

Nunes-Alves, A.; Kokh, D.B.; Wade, R.C. Comprehensive characterization of ligand unbinding mechanisms and kinetics for T4 lysozyme mutants using tauRAMD. Curr. Res. Struct. Biol., 3,106-111, 2021, ArXiv: 2010.08763 [q-bio.QM].

Dey, D.; Marciano, S.; Nunes-Alves, A.; Kiss, V.; Wade, R.C.; Schreiber G. LineFRAP, a versatile method to measure diffusion rates in vitro and in vivo. J. Mol. Biol., 433: 166898, 2021

Berger, B.-T.; Amaral, M.; Kokh, D.B.; Nunes-Alves, A.; Musil, D.; Heinrich, T.; Schröder, M.; Neil, R.; Wang, J.; Navratilova, I.; Bomke, J.; Elkins, J.M.; Müller, S.; Frech, M.; Wade, R.C.; Knapp, S. Structure-kinetic relationship reveals the mechanism of selectivity of FAK inhibitors over PYK2. Cell Chem. Biol., 28: 686- 698, 2021

Salo-Ahen, O.M.H.; Alanko, I; Bhadane, R.; Bonvin, A.M.J.J. ; Honorato, R.V.; Hossain, S.; Juffer, A.H.; Kabedev, A.; Lahtela-Kakkonen, M.; Larsen, A.S.; Lescrinier, E.; Marimuthu, P.; Mirza, M.U.; Mustafa, G.; Nunes-Alves, A.; Pantsar, T.; Saadabadi, A.; Singaravelu, K.; Vanmeert, M. Molecular dynamics simulations in drug discovery and pharmaceutical development. Processes, 9: 71, 2021

Ganotra, G.K.; Nunes-Alves, A.; Wade, R.C. A protocol to use Comparative Binding Energy analysis to estimate drug-target residence time. In: F. Ballante (ed.). Protein-ligand interactions and drug design. Methods in molecular biology. Springer, ISBN 978-1-0716-1208-8, p. 171-186, 2021

Nunes-Alves, A.; Mazzolari, A.; Merz Jr., K.M. What Makes a Paper Be Highly Cited? 60 Years of the Journal of Chemical Information and Modeling. J. Chem. Inf. Model., 60: 5866-5867, 2020

Nunes-Alves, A.; Kokh, D.B.; Wade, R.C. Recent progress in molecular simulation methods for drug binding kinetics. Curr. Opin. Struct. Biol., 64: 126-133, 2020

Diestelkoetter-Bachert, P.; Beck, R.; Reckmann, I.; Hellwig, A.; Garcia-Saez, A.; Zelman-Hopf, M.; Hanke, A.; Nunes-Alves, A.; Wade, R.C.; Mayer, M.P.; Wieland, F. rf dimer interface: molecular mechanism of Arfdependent membrane scission. FEBS Lett., 594: 2240-2253, 2020.

Weidner, P.; Söhn, M.; Schroeder, T.; Helm, L.; Hauber, V.; Gutting, T.; Betge, J.; Roecken, C.; Rohrbacher, F.N.; Pattabiraman, V.R.; Bode, J.W.; Seger, R.; Saar, D.; Nunes-Alves, A.; Wade, R.C.; Ebert, M.P.A., Burgermeister, E. Myotubularin-related protein 7 activates peroxisome proliferator-activated receptor-gamma. Oncogenesis, 9: 59, 2020

 

Latest News

An article by UniSysCat researchers and collaborators was published in Nature Communications. It sheds light on the mechanism of Plasmodium falciparum chloroquine resistance transporter (PfCRT).

Interesting interview with UniSysCat researcher Ariane Nunes Alves published in Berlin newspaper “Tagesspiegel”. In it, she talks about catalysts, enzymes, proteins and how to harness AI for cancer medication development.

Understanding how drugs bind to their target is very helpful for drug development. UniSysCat researchers Sohraby and Nunes Alves reviewed the latest computational methods for predicting the kinetics of binding mechanisms.

UniSysCat researcher Ariane Nunes Alves et al. describe the boost of structure-activity prediction by machine learning methods in an editorial for a virtual issue in the Journal of Chemical Information and Modeling.