CV

Education

• 2018 – 2023    Current student at The University of Maryland, College Park
  • Ph.D. in Biophysics expected spring 2023
• 2013 – 2017    Johns Hopkins University, Krieger School of Arts & Sciences
  • Bachelor of Arts, Biophysics

Research Interests

• Using enhanced sampling methods to develop an ensemble-based drug discovery pipeline.
• Studying proteins as highly structured data with network science and graph neural networks.

Research Experience

• 2015 – 2017    Application and method development in constant pH molecular dynamics Research under Bernard Brooks and Ana Damjanovic through the NIH and Johns Hopkins University
• 2018 – 2023    Method development using SGOOP, RAVE, and AMINO Leveraging accelerated simulations for computer-aided drug design Research under Pratyush Tiwary at the University of Maryland

Publications

1. Mrinal Shekhar, Zachary Smith, Markus Seeliger, and Pratyush Tiwary. Protein flexibility and dissociation pathway differentiation can explain onset of resistance mutations in kinases Hot paper in Angewandte Chemie (134), e202200983, 2022.
2. Zachary Smith, and Pratyush Tiwary. Making high-dimensional molecular distribution functions tractable through Belief Propagation on Factor Graphs The Journal of Physical Chemistry B 125 (40), 11150-11158, 2021.
3. Sun-Ting Tsai, Zachary Smith, and Pratyush Tiwary. SGOOP-d: Estimating kinetic distances and reaction coordinate dimensionality for rare event systems from biased/unbiased simulations Journal of Chemical Theory and Computation 17 (11), 6757-6765, 2021.
4. Shashank Pant, Zachary Smith, Yihang Wang, Emad Tajkhorshid, and Pratyush Tiwary. Confronting pitfalls of AI-augmented molecular dynamics using statistical physics Editor’s choice, featured article, and cover of The Journal of Chemical Physics 153 (23): 234118, 2020.
5. Zachary Smith, Pavan Ravindra, Yihang Wang, Rory Cooley, Pratyush Tiwary. Discovering Protein Conformational Flexibility through Artificial-Intelligence-Aided Molecular Dynamics Machine Learning in Physical Chemistry special issue of The Journal of Physical Chemistry B 124 (38): 8221-8229, 2020.
6. Zachary Smith, Pavan Ravindra, Pratyush Tiwary. Automatic mutual information noise omission (AMINO): generating order parameters for molecular systems Emerging Investigators special issue of Molecular Systems Design & Engineering 5 (1): 339-348, 2020.
7. Sun-Ting Tsai, Zachary Smith, Pratyush Tiwary. Reaction coordinates and rate constants for liquid droplet nucleation: Quantifying the interplay between driving force and memory The Journal of Chemical Physics 151 (15): 154106, 2019.
8. Debabrata Pramanik, Zachary Smith, Adam Kells, Pratyush Tiwary. Can One Trust Kinetic and Thermodynamic Observables from Biased Metadynamics Simulations?: Detailed Quantitative Benchmarks on Millimolar Drug Fragment Dissociation The Journal of Physical Chemistry B 123 (17): 3672-3678, 2019.
9. Zachary Smith, Debabrata Pramanik, Sun-Ting Tsai, Pratyush Tiwary. Multi-dimensional spectral gap optimization of order parameters (SGOOP) through conditional probability factorization Markov Models of Molecular Kinetics special issue of The Journal of Chemical Physics 149 (23): 234105, 2018.

Honors and Awards

• 2023    Biophysics Award for Research Excellence
• 2022    Ann G. Wylie Dissertation Fellowship
• 2020    Outstanding Graduate Research Assistant Award
• 2019    NSF COMBINE Fellowship
• 2018    Drs. Wayne T. & Mary T. Hockmeyer Endowed Fellowship
• 2017    Graduated with General Honors from Johns Hopkins University
• 2014 – 2017    Dr. Janet Bassett Baker and Dr. Lawrence H. Baker Memorial Scholarship
• 2014 – 2017    Johns Hopkins University Dean’s List

Students Mentored

• Pavan Ravindra
  • Previously a student in Biochemistry and Computer Science at Maryland
  • Currently pursuing a Ph.D. in Chemistry at Columbia
• Rorey Cooley
  • Previously a student in Biochemistry at Maryland
  • Currently pursuing a Ph.D. in Computational Neuroscience at Chicago
• Michael Strobel
  • Previously a student in Computer Science at Maryland
  • Currently pursuing a Ph.D. in Computer Science at UC Riverside

Invited Talks

1. iPoLS meeting “Understanding Drug Resistance through Molecular Simulation”, Montpellier, France (June 2022)
2. BPS networking event on Computational Methods for Biomolecular Kinetics “Predicting drug dissociation kinetics and pathways through reaction coordinate optimization”, Virtual, (September 2021)
3. UMD Biochemistry seminar “From atoms to pathways: Automated sampling of ligand dissociation and protein conformational change”, College Park, Maryland (February 2021)
4. PoLS student talks “From atoms to pathways: automated protein conformational sampling with AMINO and RAVE”, College Park, Maryland (December 2019)
5. iPols meeting “Why was Gleevec unsuccessful? Investigating Abl Kinase drug binding through SGOOP and metadynamics”, Munich, Germany (July 2019)

Teaching Experience

• 2018 – 2019    Cell Biology and Physiology
  • Lab section instructor, office hours, exam and lab report grading
• 2014 – 2017    Introduction to Computing
  • Office hours, in-class assistance, graded weekly assignments

Computational Skills

UNIX, Python, PyTorch, PyTorch Geometric, CHARMM, NAMD, GROMACS, PLUMED