Project

Back to overview

Computergestützer Entwurf und biophysikalische Charakterisierung immunmodulatorischer und antibakterieller Peptide und Peptidomimetika

English title Computer-assisted design and biophysical characterization of immunomodulatory and antibacterial peptides and peptidomimetic agents
Applicant Schneider Gisbert
Number 134783
Funding scheme Project funding (Div. I-III)
Research institution Institut für Pharmazeutische Wissenschaften ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Physical Chemistry
Start/End 01.08.2011 - 31.07.2014
Approved amount 562'446.00
Show all

All Disciplines (6)

Discipline
Physical Chemistry
Pharmacology, Pharmacy
Infectious Diseases
Biophysics
Structural Research
Biochemistry

Keywords (11)

Drug discovery; Pharmacology; Computational chemistry; Bioinformatics; Peptide design; Chemoinformatics; Biophysical methods; Antimicrobial peptides; Anticancer peptides; MHC-I; Membrane

Lay Summary (English)

Lead
In this study we addressed the need for novel immune-modulators and antibacterial molecular agents using innovative methods and concepts for computer-assisted drug design. The research project was divided into three main sections: i) Development and implementation of adaptive algorithms for the de novo design of bioactive peptides and peptide mimetics, ii) characterization and design of MHC-I binding peptides and druglike compounds, and iii) characterization and design of peptides and peptide mimetics targeting bacterial and cancer cell membranes (antimicrobial and anticancer peptides).
Lay summary

 

Relevance

The project has led to a deeper understanding of the fundamental principles of peptide-membrane interaction and the architecture of immunomodulatory compounds. In addition, advanced methods for computer-assisted drug design were developed to provide a technological basis for the development of novel anti-infective agents and vaccines.

Aim

In this study we addressed the pressing need for novel immune-modulators and antibacterial molecular agents by developing and applying innovative methods and concepts for computer-assisted drug design. The research project had three main goals: i) Development and implementation of computer algorithms for the design of bioactive compounds, ii) characterization and design of MHC-I binding peptides, and iii) characterization and design of peptides and peptide mimetics targeting bacterial membranes ("antimicrobial peptides"). We employed nature-inspired optimization methods like the evolution strategy and the ant colony optimization paradigm for molecular design.

Background

Pathogens develop evasive strategies that lead to resistant strains on which today’s antibiotics are no longer effective. The immune defense can be supported not only by antibiotics that prevent bacterial growth but alternative concepts that possibly help escape from the vicious circle of novel antibiotic drugs and novel resistances. Antimicrobial peptides destroy pathogens by targeting fundamental differences between bacterial and human cell membranes, and MHC-I stabilizing agents act as modulators of the immune response.

Lead

Our society is continuously confronted with pathogens that are resistant to drug treatment. In this project we explored the structure-activity relationships of immunomodulatory peptides that will help us better understand and deal with the mechanisms of bacterial resistance.

Main Applicant

Prof. Dr. Gisbert Schneider, Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich

Project Title

Computer-assisted design and biophysical characterization of immunomodulatory and antibacterial peptides and peptidomimetic agents

Direct link to Lay Summary Last update: 07.09.2014

Responsible applicant and co-applicants

Employees

Publications

Publication
Multidimensional Design of Anticancer Peptides
Lin YC, Lim YF, Russo E, Schneider P, Bolliger L, Edenharter A, Altmann KH, Halin C, Hiss JA, Schneider G (2015), Multidimensional Design of Anticancer Peptides, in Angew Chem Int Ed Engl., 54(35), 10370-103704.
Combinatorial chemistry by ant colony optimization.
Hiss Jan A, Reutlinger Michael, Koch Christian P, Perna Anna M, Schneider Petra, Rodrigues Tiago, Haller Sarah, Folkers Gerd, Weber Lutz, Baleeiro Renato B, Walden Peter, Wrede Paul, Schneider Gisbert (2014), Combinatorial chemistry by ant colony optimization., in Future medicinal chemistry, 6(3), 267-80.
Coping with Polypharmacology by Computational Medicinal Chemistry
Schneider Gisbert, Reker Daniel, Rodrigues Tiago, Schneider Petra (2014), Coping with Polypharmacology by Computational Medicinal Chemistry, in Chimia, 68(9), 648-653.
Machine learning estimates of natural product conformational energies.
Rupp Matthias, Bauer Matthias R, Wilcken Rainer, Lange Andreas, Reutlinger Michael, Boeckler Frank M, Schneider Gisbert (2014), Machine learning estimates of natural product conformational energies., in PLoS computational biology, 10(1), 1003400-1003400.
Special focus issue of Future Medicinal Chemistry: "Computational Medicinal Chemistry"
Schneider G. (ed.) (2014), Special focus issue of Future Medicinal Chemistry: "Computational Medicinal Chemistry", Future Science Ltd, London.
Adaptive peptide design
Schneider Gisbert, Lin Yenchu, Koch Christian P., Pillong Max, Perna Anna Maria, Reutlinger Michael, Hiss Jan Alexander (2013), Adaptive peptide design, in Chimia, 67(12), 859-863.
CATS for scaffold-hopping in medicinal chemistry
Koch C.P., Reutlinger M., Todoroff N., Schneider P., Schneider G. (2013), CATS for scaffold-hopping in medicinal chemistry, in Brown Nathan (ed.), John Wiley & Sons, Weinheim, 119-130.
Chemically Advanced Template Search (CATS) for Scaffold-Hopping and Prospective Target Prediction for 'Orphan' Molecules.
Reutlinger Michael, Koch Christian P, Reker Daniel, Todoroff Nickolay, Schneider Petra, Rodrigues Tiago, Schneider Gisbert (2013), Chemically Advanced Template Search (CATS) for Scaffold-Hopping and Prospective Target Prediction for 'Orphan' Molecules., in Molecular informatics, 32(2), 133-138.
Computational resources for MHC ligand identification
Koch Christian P., Pillong Max, Hiss Jan Alexander, Schneider Gisbert (2013), Computational resources for MHC ligand identification, in Molecular Informatics, 32(4), 326-336.
De novo design - hop(p)ing against hope.
Schneider Gisbert (2013), De novo design - hop(p)ing against hope., in Drug discovery today. Technologies, 10(4), 453-60.
De novo design and optimization of Aurora A kinase inhibitors
Rodrigues Tiago Martins, Roudnicky Filip, Koch Christian P., Kudoh Takayuki, Reker Daniel, Detmar Michael J., Schneider Gisbert (2013), De novo design and optimization of Aurora A kinase inhibitors, in Chemical Science, 4(3), 1229-1233.
De novo design: From models to molecules.
Gisbert Schneider, Baringhaus K.-H. (2013), De novo design: From models to molecules., in Schneider Gisbert (ed.), John Wiley & Sons, Weinheim, 1-56.
De novo Molecular Design
Gisbert Schneider (2013), De novo Molecular Design, Wiley-VCH, Weinheim.
Drugs by numbers: reaction-driven de novo design of potent and selective anticancer leads.
Spänkuch Birgit, Keppner Sarah, Lange Lisa, Rodrigues Tiago, Zettl Heiko, Koch Christian P, Reutlinger Michael, Hartenfeller Markus, Schneider Petra, Schneider Gisbert (2013), Drugs by numbers: reaction-driven de novo design of potent and selective anticancer leads., in Angewandte Chemie (International ed. in English), 52(17), 4676-81.
Exhaustive Proteome Mining for Functional MHC-I Ligands
Koch Christian P., Perna Anna M., Weissmueller Sabrina, Bauer Stefanie, Pillong Max, Baleeiro Renato B., Reutlinger Michael, Folkers Gerd, Walden Peter, Wrede Paul, Hiss Jan A., Waibler Zoe, Schneider Gisbert (2013), Exhaustive Proteome Mining for Functional MHC-I Ligands, in ACS CHEMICAL BIOLOGY, 8(9), 1876-1881.
Molecula ex machina - Maschinen machen Moleküle.
Schneider Gisbert (2013), Molecula ex machina - Maschinen machen Moleküle., in KutE, Schmid M. (ed.), Edition Collegium Helveticum, Zürich, 131-134.
Peptide design by nature-inspired computing.
Hiss J. A., Schneider Gisbert (2013), Peptide design by nature-inspired computing., in Schneider Gisbert (ed.), John Wiley & Sons, Weinheim, 441-470.
Scrutinizing MHC-I binding peptides and their limits of variation.
Koch Christian P, Perna Anna M, Pillong Max, Todoroff Nickolay K, Wrede Paul, Folkers Gerd, Hiss Jan A, Schneider Gisbert (2013), Scrutinizing MHC-I binding peptides and their limits of variation., in PLoS computational biology, 9(6), 1003088-1003088.
Steering target selectivity and potency by fragment-based de novo drug design.
Rodrigues Tiago, Kudoh Takayuki, Roudnicky Filip, Lim Yi Fan, Lin Yen-Chu, Koch Christian P, Seno Masaharu, Detmar Michael, Schneider Gisbert (2013), Steering target selectivity and potency by fragment-based de novo drug design., in Angewandte Chemie (International ed. in English), 52(38), 10006-9.
Designing antimicrobial peptides: form follows function.
Fjell Christopher D, Hiss Jan A, Hancock Robert E W, Schneider Gisbert (2012), Designing antimicrobial peptides: form follows function., in Nature reviews. Drug discovery, 11(1), 37-51.
From theory to bench experiment by computer-assisted drug design.
Schneider Gisbert (2012), From theory to bench experiment by computer-assisted drug design., in Chimia, 66(3), 120-4.
Immunosuppressive small molecule discovered by structure-based virtual screening for inhibitors of protein-protein interactions.
Geppert Tim, Bauer Stefanie, Hiss Jan A, Conrad Elea, Reutlinger Michael, Schneider Petra, Weisel Martin, Pfeiffer Bernhard, Altmann Karl-Heinz, Waibler Zoe, Schneider Gisbert (2012), Immunosuppressive small molecule discovered by structure-based virtual screening for inhibitors of protein-protein interactions., in Angewandte Chemie (International ed. in English), 51(1), 258-61.
Virtual screening for compounds that mimic protein-protein interface epitopes.
Geppert Tim, Reisen Felix, Pillong Max, Hähnke Volker, Tanrikulu Yusuf, Koch Christian P, Perna Anna Maria, Perez Tatiana Batista, Schneider Petra, Schneider Gisbert (2012), Virtual screening for compounds that mimic protein-protein interface epitopes., in Journal of computational chemistry, 33(5), 573-9.
Designing the molecular future
Schneider Gisbert (2011), Designing the molecular future, in Journal of Computer-Aided Molecular Design, 26(1), 115-120.
Neighborhood-Preserving Visualization of Adaptive Structure-Activity Landscapes: Application to Drug Discovery
Reutlinger M, Guba W, Martin RE, Alanine AI, Hoffmann T, Klenner A, Hiss JA, Schneider P, Schneider G (2011), Neighborhood-Preserving Visualization of Adaptive Structure-Activity Landscapes: Application to Drug Discovery, in Angew Chem Int Ed Engl., 50(49), 11633-11636.
Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library
Petra Schneider, Katharina Stutz, Ladina Kasper, Sarah Haller, Michael Reutlinger, Felix Reisen, Tim Geppert, Gisbert Schneider (2011), Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library, in Pharmaceuticals, 4(9), 1236-1247.
Piloting the membrane-lytic activities of peptides by a self-organizing map
Lin Y.-C. Hiss J. A. Schneider P. Thelesklaf P. Lim Y. F. Pillong M. Koehler F. M., Piloting the membrane-lytic activities of peptides by a self-organizing map, in ChemBioChem, 2014.

Collaboration

Group / person Country
Types of collaboration
Prof. Dr. Silja Wessler, Universität Salzburg Austria (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Exchange of personnel
Prof. Dr. Peter Walden, Charité Berlin Germany (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Exchange of personnel

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
ACS National Meeting Talk given at a conference Peptide design reloaded 12.08.2014 San Francisco, United States of America Schneider Gisbert;
ACS National Meeting Poster Thermodynamic properties of membrane-binding peptides 10.08.2014 San Francisco, United States of America Pillong Max; Schneider Gisbert; Lin Yen-Chu;
10th International Conference on Chemical Structures (ICCS) and the 10th German Conference on Chemoinformatics (GCC) Poster Vectorizing hydrophobicity: From in silico models to membrane-active peptides 03.06.2014 Noordwijkerhout, Netherlands Lin Yen-Chu; Schneider Gisbert; Pillong Max;
ACS National Meeting Poster De novo design antimicrobial peptides using self-organizing maps 19.03.2014 Dallas, United States of America Lin Yen-Chu; Schneider Gisbert; Pillong Max;


Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
Naturama (Aargauische Naturforschende Gesellschaft) Talk 21.01.2014 Aarau, Switzerland Schneider Gisbert;


Awards

Title Year
Posterpreis 10th International Conference on Chemical Structures (ICCS) and 10th German Conference on Chemoinformatics (GCC) (Noordwijkerhout, June 1-5, 2014) 2014
Posterpreis 9th German Conference on Chemoinformatics (GCC) (Fulda, November 10-12, 2013) 2013

Associated projects

Number Title Start Funding scheme
157190 Experiment-guided computational de novo exploration of peptide-membrane interaction 01.01.2015 Project funding (Div. I-III)

Abstract

In this study we addressed the need for novel immune-modulators and antibacterial molecular agents using innovative methods and concepts for computer-assisted drug design. The research project was divided into three main sections: i) Development and implementation of adaptive algorithms for the de novo design of bioactive peptides and peptide mimetics, ii) characterization and design of MHC-I binding peptides and druglike compounds, and iii) characterization and design of peptides and peptide mimetics targeting bacterial and cancer cell membranes (antimicrobial peptides, AMPs; anticancer peptides, ACPs). We employed nature-inspired optimization methods like the evolution strategy and the ant colony optimization (ACO) paradigm for the computer-based assembly of novel peptides that exhibit the desired biological activity. The ‘fitness function’ was represented by kernel-based machine-learning systems in the case of in silico design, and actual biochemical in vitro assays in a combination of computer-assisted design with robotic peptide synthesis and testing. A particular research focus was on the understanding of function-determining structural features of AMPs.
-