Long term interest in novel approaches to rational drug design and preclinical translational research. Wide interest in the field of computational approaches and research which merges chemistry with biology and focuses on the design and development of drugs that selectively target DNA and inhibitors of signaling and metabolic pathways important to tumor progression and survival; Robust SAR/QSAR model building to apply to successful drug selection; Experience in applying screening approaches, docking and handling large databases of small molecules (NCI Database, ChemNavigator iResearch Library, and PubChem) and large-scale high-throughput screening (HTS) as well as concomitant development of large combinatorial libraries. Developing new tools for innovative drug discovery is my passion.
My current project aims to develop new models based on NIH Roadmap curated assay data. The key point is that Pubchem is the main repository for a vast collection of bioassay data for a wide range of targets. This massive number of data points has not been available to the academic research community until now. I am using it to improve available models, develop new models and computer-based methods to aid in the drug discovery.
Additionally I apply computer aided methods to detect pharmacological pathways involved in cancer, anti-virus, neurological treatment. Proteins have been very successfully classified according to amino acid sequence or structure and this enabled improved prediction of function. I carry this idea one step further and develop minimally biased scheme to compare and classify proteins purely according to their biological networks and motion patterns.
- Development of Virtual Screening Models Based on NIH Roadmap Assay Data - Experimental Validation
- Improving the Interpretation of Virtual Screening Results and Prediction of Drug-Like Compounds
- Exploring Ligand-Based Virtual Screening for Hepatitis C Virus RNA Polymerase Inhibitors by docking and QSAR Analysis
- Improving Drug Development and Prediction of Drug-Like Compounds by Connecting Systems Biology and Medicinal Chemistry with Modern Machine Learning Methods
- I.E.Weidlich,Igor V. Filippov, Jodian Brown, Neerja Kaushik-Basu, Ramalingam Krishnan, Marc C. Nicklaus, Ian F. Thorpe: Inhibitors for the hepatitis C virus RNA polymerase explored by SAR with advanced machine learning methods, Bioorg.Med.Chem., 2013 (Accepted).
- I.E.Weidlich, Markus Sitzmann, Igor V. Filippov, Chenzhong Liao, Megan L. Peach, Rajeshri G. Karki, Yulia V. Borodina, Raul E. Cachau, Marc C. Nicklaus: PDB ligand conformational energies calculated quantum mechanically, J.Chem.Inf.Model.,2012, 52 (3),pp 739-756.
- I.E.Weidlich, Y.Pommier, T.S.Dexheimer, C.Marchand and M.C.Nicklaus: Virtual screening using ligand-based pharmacophores for inhibitors of human tyrosyl-DNA phosphodiesterase (hTdp1), Biorg.Med.Chem., 18, 2010, 2347-2355.
- T.S.Dexheimer, A.G.Stephen, I.E.Weidlich, S.Antony, C.Marchand, M.C.Nicklaus, R.J.Fisher, V.C. Njar, and Y.Pommier: 4-Pregnen-21-ol-3,20-dione-21-(4-bromobenzenesulfonate) (NSC 88915) and Related Novel Steroid Derivatives as Tyrosyl DNA Phosphodiesterase (Tdp1) Inhibitors, J. Med. Chem. 2009, 52,7122-7131.
- Sung-Eun Kim, Won Jun Choi, A.G.Stephen, I.E.Weidlich, M.C.Nicklaus, T.R.Burke et al.: Use of Peptoid-Peptide Hybrids in the Development of Shc SH2 Domain-Binding Inhibitors. Proceedings of the 21st American Peptide Symposium (American Peptide Society), 2009, 175-176.
- Won Jun Choi, Sung-Eun Kim, A.G.Stephen, I.E.Weidlich, A.Giubellino, M.C.Nicklaus, T.R.Burke et al.: Identification of Shc Src Homology 2 Domain-Binding Peptoid-Peptide Hybrids, J.Med.Chem. 2009, 52, 1612-1618.
- M.Kubicki, T.Borowiak, G.Dutkiewicz, S.Sobiak, I.E.Weidlich: 1,2dimethyl4nitro5morpholino-imidazole and its hydrate: a case of centro-noncentro ambiguity. Acta Crystallogr. B 2003, 59, 487-491.
Invited Oral Presentations
- Improving Drug Development by Connecting Medicinal Chemistry with Drug Repositioning and Modern Machine Learning Methods, CINF, 244th ACS, Philadelphia, PA, August 19-23 2012.
- Improving Drug Development by Connecting Medicinal Chemistry with Drug Repositioning and Modern Machine Learning Methods, Autonomous Robotics Laboratory, George Mason University, May 1, 2012.
- Anti-Cancer Drug Development by Drug Repositioning with Machine Learning, Georgetown University, April 2, 2012.
- Exploring Novel Approaches in Rational Drug Design, Computational Materials Science Center, George Mason University, Fairfax, VA, October 31, 2011.
- Development of Virtual Screening Models Based on NIH Roadmap Assay DataExperimental Validation, GlaxoSmithKline, Collegeville, PA, April 26, 2011.
- Ligand Energies Calculated Quantum-Chemically in Vacuum and Solvent Model, 5th International Conference Genomics, Proteomics, Bioinformatics and Nanobiotechnologies for Medicine, St.Petersburg-Mandrogi-Kizhi-Konevets-Valaam-St.Petersburg, Russia, May 31-June 5, 2010.
- Inhibitors of Human Tyrosyl-DNA Phosphodiesterase Developed by Virtual Screening Using Ligand-Based Pharmacophores, Accelrys User Group Meeting, Boston, May 4-6, 2010.
- Screening tools and results for inhibitors of human tyrosyl DNA phosphodiesterase (Tdp1), 237th ACS National Meeting and Exposition, Salt Lake City, UT, COMP 211, March 22-26, 2009
- Examination of proposed intercalation models for imidazoacridone related compounds, 235th ACS National Meeting and Exposition, New Orleans, LA, COMP 242, April 6-10, 2008.
- Synthesis and chemical properties of nitro and aminoimidazole derivatives of nitrogen mustard, 229th ACS National Meeting, San Diego, CA, ORGN 893, March 13-17, 2005.
- An Analysis of the Structural Properties and Anti-Neoplastic Activity of 1-(4-halogen-phenacyl)-4-nitroimidazole via The Method of Molecular Modeling, Poznan Congress of Students of Medicine, Poznań, Poland, May 28-29, 2000.
42 presentations and conference abstracts, including 14 in Europe.