About

me3I work at Eli Lilly and Company in the Computational Chemistry and Cheminformatics group in San Diego where I primarily work on applied drug discovery projects in oncology and immunology. Formally I was a Marie Curie Post-Doctoral Fellow in the same group at Lilly’s UK research site. I am a graduate of the University of Pittsburgh in the Department of Computational and Systems Biology. My interests include structure-based drug discovery, cheminformatics, protein modeling, molecular modeling, virtual screening, machine learning, software development and data visualization.

Research

My graduate work was conducted under the expert tutelage of Dr. Carlos Camacho in the joint Ph.D. Program in Computational Biology at the University of Pittsburgh and Carnegie Mellon University.

Molecular modeling of protein-ligand interactions

3LBK_fig_2I have modeled the interactions of a number of small molecules and lipids to a wide variety of protein targets families including kinases (ABL, c-Src, Chk1, Erk2 and more), ligases (XRCC1, MDM2), lipoxygenases (5-LOX) and globins (cytoglobin) using MD simulations, molecular docking and novel scoring functions.

Structure-based drug discovery
pharma_model_2I used and improved a structure-based virtual screening pipeline to target a number of challenging protein-protein interactions (PPIs) including XRCC1/Polβ, 14-3-3/p53, cop-γ/cop-ζ with no known inhibitors. I employed a variety of techniques including pharmacophore modeling, molecular docking, custom scoring functions and self-developed novel clustering and visualization methods.
Using molecular dynamics (MD) simulations to understand PPIs

md_simI have used molecular dynamics simulations to gain understanding of complex protein-protein interactions, rationalize the effect of mutations of transcription factors and to predict the binding poses of small molecules. I have studied a number of target systems including MDM2-p53, PAX6, ABL1, cytoglobin and more.

Machine Learning, statistics and data visualization

scoring

I have used a number of machine learning techniques to develop novel scoring functions, analyze big data sets and improve the efficiency and accuracy of existing cheminformatics methods.

 

Selected Publications

  • LR Vidler, MP Baumgartner. “Creating a Virtual Assistant for Medicinal Chemistry.” ACS Med Chem Lett. 2019, 10(7):1051-1055.
  • MP Baumgartner and DA Evans, “Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2.” J Comp Aided Molec Des. 2018. 32(1):45-58
  • Z Ye, MP Baumgartner, BM Wingert, CJ Camacho. “Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge” J Comp Aided Molec Des. 2016. 30: 695. doi:10.1007/s10822-016-9941-0. Link
  • J Tejero*, AA Kapralov*, MP Baumgartner*, CE Sparacino-Watkins, TS Anthonymutu, CJ Camacho, MT Gladwin, H Bayir and VE Kagan. “Peroxidase activation of cytoglobin by anionic phospholipids: Mechanisms and consequences.” BBA Mol Cell Bio Lipids 2016, 2016 May;1861(5):391-401. Link
  • MP Baumgartner and CJ Camacho. “Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment.” J Chem Inf Model 2015. Link
  • P Grover, H Shi, MP Baumgartner, CJ Camacho, and TE Smithgall. “Fluorescence Polarization Screening Assays for Small Molecule Allosteric Modulators of Abl Kinase Function.” PLoS One 2015, 10, e0133590. Link
  • JA Moroco, MP Baumgartner, HL Rust, HG Choi, W Hur, NS Gray, CJ Camacho, and TE Smithgall. “A Discovery Strategy for Selective Inhibitors of c-Src in Complex with the Focal Adhesion Kinase SH3/SH2-binding Region.” Chem Biol Drug Des 2015, 86, 144-155. Link
  • R. Wisastra, PAM Kok, N Eleftheriadis, MP Baumgartner, CJ Camacho, HJ Haisma, and, FJ Dekker. “Discovery of a novel activator of 5-lipoxygenase from an anacardic acid derived compound collection.” Bioorg & Med Chem, 2013 21 (24), 7763-7778. Link
  • DR Koes, MP Baumgartner, and CJ Camacho. “Lessons Learned in Empirical Scoring with smina from the CSAR 2011Benchmarking Exercise.” J Chem Inf Model 2013 53 (8), 1893-1904. Link

Education

University of Pittsburgh – Carnegie Mellon University
Ph.D., Joint Program in Computational Biology, February 2016

University of Pittsburgh
B.S. Biological Sciences, May 2010, Cum Laude; GPA: 3.4/4.0

Awards

2015 Student of the Year, Computational and Systems Biology, University of Pittsburgh

Contact

LinkedIn

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