Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods. - Wolfgang Sippl (J. Comput. Aided Mol. Des., 2000)

Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors. - Wolfgang Sippl; Jean-Marie Contreras; Isabelle Parrot; Yveline M. Rival; Camille G. Wermuth (J. Comput. Aided Mol. Des., 2001)

Development of biologically active compounds by combining 3D QSAR and structure-based design methods. - Wolfgang Sippl (J. Comput. Aided Mol. Des., 2002)

Generation of a homology model of the human histamine H3 receptor for ligand docking and pharmacophore-based screening. - Birgit Schlegel; Christian Laggner; René Meier 002; Thierry Langer; David Schnell; Roland Seifert; Holger Stark; Hans-Dieter Höltje; Wolfgang Sippl (J. Comput. Aided Mol. Des., 2007)

ParaDockS: A Framework for Molecular Docking with Population-Based Metaheuristics. - René Meier 002; Martin Pippel; Frank Brandt; Wolfgang Sippl; Carsten Baldauf (J. Chem. Inf. Model., 2010)

Postprocessing of Protein-Ligand Docking Poses Using Linear Response MM-PB/SA: Application to Wee1 Kinase Inhibitors. - Kanin Wichapong; Michael Lawson; Somsak Pianwanit; Sirirat Kokpol; Wolfgang Sippl (J. Chem. Inf. Model., 2010)

Application of biasing-potential replica exchange simulations for loop modeling and refinement of proteins in explicit solvent. - Srinivasaraghavan Kannan; Wolfgang Sippl; Martin Zacharias (J. Cheminformatics, 2011)

PARADOCKS - a framework for molecular docking. - Martin Pippel; René Meier 002; Wolfgang Sippl (J. Cheminformatics, 2011)

Docking and virtual screening of novel inhibitors for mono-ADP-ribosylating toxins. - Michael Scharfe; Benjamin Maurer; Klaus Aktories; Manfred Jung; Wolfgang Sippl (J. Cheminformatics, 2011)

ParaDockS - an open source framework for molecular docking. - Martin Pippel; Michael Scharfe; René Meier 002; Wolfgang Sippl (J. Cheminformatics, 2012)

Development of target-biased scoring functions for protein-ligand docking. - Michael Scharfe; Martin Pippel; Wolfgang Sippl (J. Cheminformatics, 2012)

Postprocessing of molecular docking poses using binding free energy calculations. - Kanin Wichapong; Wolfgang Sippl (J. Cheminformatics, 2012)

Ligand-based and structure-based design of novel histone demethylase inhibitors. - Luca Carlino; Martin Schmitt; Manfred Jung; Wolfgang Sippl (J. Cheminformatics, 2013)

ParaDockS - an open-source framework for molecular docking: implementation of target-class-specific scoring methods. - Michael Scharfe; Martin Pippel; Wolfgang Sippl (J. Cheminformatics, 2013)

Discovery of Inhibitors of Schistosoma mansoni HDAC8 by Combining Homology Modeling, Virtual Screening, and in Vitro Validation. - Srinivasaraghavan Kannan; Jelena Melesina; Alexander-Thomas Hauser; Alokta Chakrabarti; Tino Heimburg; Karin Schmidtkunz; Alexandra Walter; Martin Marek; Raymond J. Pierce; Christophe Romier; Manfred Jung; Wolfgang Sippl (J. Chem. Inf. Model., 2014)

Molecular Modeling of Potential Anticancer Agents from African Medicinal Plants. - Fidele Ntie-Kang; Justina Ngozi Nwodo; Akachukwu Ibezim; Conrad Veranso Simoben; Berin Karaman; Valery Fuh Ngwa; Wolfgang Sippl; Michael Umale Adikwu; Luc Meva'a Mbaze (J. Chem. Inf. Model., 2014)

Virtual Screening of PRK1 Inhibitors: Ensemble Docking, Rescoring Using Binding Free Energy Calculation and QSAR Model Development. - Inna Slynko; Michael Scharfe; Tobias Rumpf; Julia Eib; Eric Metzger; Roland Schüle; Manfred Jung; Wolfgang Sippl (J. Chem. Inf. Model., 2014)

Application of Docking and QM/MM-GBSA Rescoring to Screen for Novel Myt1 Kinase Inhibitors. - Kanin Wichapong; Alexander Rohe; Charlott Platzer; Inna Slynko; Frank Erdmann; Matthias Schmidt 002; Wolfgang Sippl (J. Chem. Inf. Model., 2014)

Exploring aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction: an in silico study. - Chiara Luise; Dina Robaa; Wolfgang Sippl (J. Comput. Aided Mol. Des., 2021)

Development of New Inhibitors of HDAC1-3 Enzymes Aided by In Silico Design Strategies. - Narges Cheshmazar; Salar Hemmati; Maryam Hamzeh-Mivehroud; Babak Sokouti; Matthes Zessin; Mike Schutkowski; Wolfgang Sippl; Hojjatollah Nozad Charoudeh; Siavoush Dastmalchi (J. Chem. Inf. Model., 2022)

Utilization of AlphaFold models for drug discovery: Feasibility and challenges. Histone deacetylase 11 as a case study. - Fady Baselious; Dina Robaa; Wolfgang Sippl (Comput. Biol. Medicine, 2023)

Exploring Aromatic Cage Flexibility Using Cosolvent Molecular Dynamics Simulations─An In-Silico Case Study of Tudor Domains. - Christopher Vorreiter; Dina Robaa; Wolfgang Sippl (J. Chem. Inf. Model., 2024)

In silico screening of a designed focused chemical space identifies novel alkyl hydrazides as potent HDAC11 inhibitors. - Fady Baselious; Sebastian Hilscher; Lukas Handke; Cyril Barinka; Mike Schutkowski; Wolfgang Sippl (Comput. Biol. Medicine, 2025)

HADDOCK-Guided modeling and molecular simulations of cereblon-based ternary complexes: Development of novel PROTACs for Ataxia telangiectasia and RAD3-Related (ATR) kinase. - Anne-Christin Sarnow; Husam Nassar; Abdallah M. Alfayomy; Dina Robaa; Wolfgang Sippl (Comput. Biol. Medicine, 2025)