About

me3I am a Marie Curie Post-Doctoral Fellow working at Eli Lilly and Company in the Computational Chemistry and Cheminformatics group. 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

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

  • 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. 2017. Under Review.
  • 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 2015Link
  • 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

Email

Advertisements