Project Z04 – Computational models of structure, dynamics and evolution of GPCRs

This core unit provides a comprehensive computational analysis of all receptors of interest in the CRC. In an iterative loop, Z04 will construct computational models consistent with experimental data combining ROSETTA modeling, molecular dynamics simulation, and evolutionary analysis. From these models, we will derive testable hypothesis for the next iteration of experimental validation in the respective projects. Lastly, we will integrate information from these approaches into a holistic model that creates experimentally testable hypothesis. Given that a set of established computational protocols will need to be applied repetitively and timely to a large number of biological systems, this work is best conducted in a core unit.

Contact

Prof. Dr. Jens Meiler (Project Leader)

Leipzig University, Faculty of Medicine
Institute for Drug Development
Liebigstraße 19, D-04103 Leipzig

Phone +49 341 97 11801
E-Mail
Web https://meilerlab.org/
Web https://www.uniklinikum-leipzig.de/einrichtungen/wirkstoffentwicklung

Prof. Dr. Peter Stadler (Project Leader)

Leipzig University, Faculty of Mathematics and Computer Science
Institute of Computer Science
Härtelstraße 16 – 18, D-04107 Leipzig

Phone +49 341 97 16690
E-Mail

Prof. Dr. Peter Hildebrand (Project Leader)

Leipzig University, Faculty of Medicine
Institute of Medical Physics and Biophysics
Härtelstraße 16 – 18, D-04107 Leipzig

Phone +49 341 97 15705
E-Mail
Web uni-leipzig.de/prof-dr-peter-w-hildebrand

Resources

We focus on: 

  1. Structural intermediates, complexes
  2. Combining MD simulations with evolutionary analysis
  3. Performing MD simulations of the membrane-embedded proteins
  4. Usage of paramagnetic restranst in structre determination

Techniques

  • computational models
  • MD Simulations: Classical Molecular Dynamics, QM/MM, QMD, DFT, Enhanced Sampling, AMBER, Gromacs, VMD
  • evolutionary analysis

Publications

Sala D, Batebi H, Ledwitch K, Hildebrand PW, Meiler J. Targeting in silico GPCR conformations with ultra-large library screening for hit discovery. Trends Pharmacol Sci. 2023; 44:150-61.

Sala D, Hildebrand PW, Meiler J. Biasing AlphaFold2 to predict GPCRs and Kinases with user-defined functional or structural properties. Front Mol Biosci. 2023; 10:1121962.

Schmidt P, Vogel A, Schwarze B, Seufert F, Licha K, Wycisk V, Kilian W, Hildebrand PW, Mitschang L. Towards Probing Conformational States of Y2 Re-ceptor Using Hyperpolarized 129Xe NMR. Molecules. 2023; 28:1424

Staritzbichler R, Ristic N, Stapke T, Hildebrand P. SmoothT – a server constructing low energy pathways from conformational ensembles for interactive visualization and enhanced sampling. Bioinformatics. 2023 Apr 5:btad176.

Canzler S, Fischer M, Ulbricht D, Ristic N, Hildebrand PW, Staritzbichler R. ProteinPrompt: a webserver for predicting protein–protein interactions. Bioinformatics Advances. 2022, 2:1 vbac059. https://doi.org/10.1093/bioadv/vbac059.
 
Del Alamo D, Sala D, Mchaourab HS, Meiler J. Sampling alternative conformational states of transporters and receptors with AlphaFold2. Int J Mol Sci. 2022 Sep 8;23(18):10405. doi: 10.3390/ijms231810405.
 
Sala D, Del Alamo D, Mchaourab HS, Meiler J. Modeling of protein conformational changes with Rosetta guided by limited experimental data. Structure. 2022 May 12:S0969-2126(22)00140-X. doi: 10.1016/j.str.2022.04.013. Online ahead of print. PMID: 35597243.
 

Schaller D, Lafond M, Stadler PF, Wieseke N, Hellmuth M. Indirect identification of horizontal gene transfer. Journal of Mathematical
Biology. 2021; 83:10. https://doi.org/10.1007/s00285-021-01631-0.

Kasmanas JC. Bartholomäus A, Corrêa FB, Tal T, Jehmlich N, Herberth Gunda, von Bergen M, Stadler PF, de Carvalho ACPLF, da Rocha UN. HumanMetagenomeDB: a public repository of curated and standardized metadata for human metagenomes. Nucleic Acids Res. 2021; 49:D743-D750.

Koehler Leman J, Lyskov S, Lewis SM, Adolf-Bryfogle J, Alford RF, Barlow K, Ben-Aharon Z, Farrell D, Fell J, Hansen WA, Harmalkar A, Jeliazkov J, Kuenze G, Krys JD, Ljubetič A, Loshbaugh AL, Maguire J, Moretti R, Mulligan VK, Nance ML, Nguyen PT, Ó Conchúir S, Roy Burman SS, Samanta R, Smith ST, Teets F, Tiemann JKS, Watkins A, Woods H, Yachnin BJ, Bahl CD, Bailey-Kellogg C, Baker D, Das R, DiMaio F, Khare SD, Kortemme T, Labonte JW, Lindorff-Larsen K, Meiler J, Schief W, Schueler-Furman O, Siegel JB, Stein A, Yarov-Yarovoy V, Kuhlman B, Leaver-Fay A, Gront D, Gray JJ, Bonneau R. Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks. Nat Commun. 2021; 12:6947.

Nunn A, Can SN, Otto C, Fasold M, Diez Rodrigues B, Fernandez-Pozo N,Rensing SA, Stadler PF, Langenberger D. EpiDiverse Toolkit: a pipeline suite for the analysis of bisulfite sequencing data in ecological plant epigenetics. Nucleic Acids Res. Genom Bioinf. 2021; 3:lqab106.

Rudolf S, Kaempf K, Vu O, Meiler J, Beck-Sickinger AG, Coin I. Binding of Natural Peptide Ligands to the Neuropeptide Y5 Receptor. Angew Chem Int Ed Engl. 2021 Nov 25. doi: 10.1002/anie.202108738 . PMID:34822209. 

Staritzbichler R, Ristic N, Goede A, Preissner R, Hildebrand PW. Voronoia 4-ever. Nucleic Acids Res. 2021 Jun 9:gkab466. doi: 10.1093/nar/gkab466. Epub ahead of print. PMID: 34107038.

Koehler Leman J, Weitzner BD, Renfrew PD, Lewis SM, Moretti R, Watkins AM, Mulligan VK, Lyskov S, Adolf-Bryfogle J, Labonte JW, Krys J; RosettaCommons Consortium, Bystroff C, Schief W, Gront D, Schueler-Furman O, Baker D, Bradley P, Dunbrack R, Kortemme T, Leaver-Fay A, Strauss CEM, Meiler J, Kuhlman B, Gray JJ, Bonneau R. Better together: Elements of successful scientific software development in a distributed collaborative community. PLoS computational biology. 2020; 16:e1007507.

Lem Leman JK, Weitzner BD, Lewis SM, Adolf-Bryfogle J, Alam N, Alford RF, Aprahamian M, Baker D, Barlow KA, Barth P, Basanta B, Bender BJ, Blacklock K, Bonet J, Boyken SE, Bradley P, Bystroff C, Conway P, Cooper S, Correia BE, Coventry B, Das R, De Jong RM, DiMaio F, Dsilva L, Dunbrack R, Ford AS, Frenz B, Fu DY, Geniesse C, Goldschmidt L, Gowthaman R, Gray JJ, Gront D, Guffy S, Horowitz S, Huang PS, Huber T, Jacobs TM, Jeliazkov JR, Johnson DK, Kappel K, Karanicolas J, Khakzad H, Khar KR, Khare SD, Khatib F, Khramushin A, King IC, Kleffner R, Koepnick B, Kortemme T, Kuenze G, Kuhlman B, Kuroda D, Labonte JW, Lai JK, Lapidoth G, Leaver-Fay A, Lindert S, Linsky T, London N, Lubin JH, Lyskov S, Maguire J, Malmström L, Marcos E, Marcu O, Marze NA, Meiler J, Moretti R, Mulligan VK, Nerli S, Norn C, Ó’Conchúir S, Ollikainen N, Ovchinnikov S, Pacella MS, Pan X, Park H, Pavlovicz RE, Pethe M, Pierce BG, Pilla KB, Raveh B, Renfrew PD, Burman SSR, Rubenstein A, Sauer MF, Scheck A, Schief W, Schueler-Furman O, Sedan Y, Sevy AM, Sgourakis NG, Shi L, Siegel JB, Silva DA, Smith S, Song Y, Stein A, Szegedy M, Teets FD, Thyme SB, Wang RY, Watkins A, Zimmerman L, Bonneau R. Macromolecular modeling and design in Rosetta: recent methods and frameworks. Nature methods. 2020; 17:665-80.