Principal Investigator

Alex Dickson

Hon. B. Sc. Chemical Physics, University of Toronto (2006)
M. Sc. Chemistry, University of Chicago (2007)
Ph. D. Chemistry, University of Chicago (2011)

Prof. Dickson has extensive experience developing new methods for the simulation of rare events, and is driven to apply these tools to the study of ligand binding processes that are relevant to human health. Alex is cross-appointed in the Department of Computational Mathematics, Science and Engineering, where he currently teaches graduate courses in computational modeling. He loves computational research, and still gets his hands dirty in the lab, assisting in the development of sampling tools and persuing his own research projects.

Before MSU, Alex was a Postdoctoral Researcher at the University of Michigan with Prof. Charles L. Brooks, III. There he worked on a wide range of projects:

  • Development of a new sampling method, WExplore, and its application to several biomolecular rare events such as the unfolding of the chignolin protein, and large loop motions in HIV-1 TAR RNA
  • Development of new tools for the network visualization of protein dynamics, where entire free energy landscapes are visualized in a single 2D plot, without the specification of specific visualization axes, as in principal component analysis
  • Utilization of coarse-grained models in conjuction with enhanced sampling methods to observe and characterize the coupled unfolding and binding of the HdeA homodimer: a periplasmic bacterial protein that helps respond to acid shock
  • Modeling higher-order biological reaction networks to study protein chaperone activity in E. coli

Alex obtained his Ph.D. in Chemistry from the University of Chicago in 2011 in Prof. Aaron Dinner's group. His work was mostly focused on the development of another enhanced sampling method: Nonequilibrium Umbrella Sampling, and these ideas helped form the foundation of the WExplore method. In Chicago Alex also worked on projects related to the large deviation theory of driven oscillators, and Ising models of lattice gases.

ORCID: 0000-0002-9640-1380
Google Scholar: Alex Dickson
twitter: @DicksonLab
CV: link

Postdoctoral Researchers

Arzu Uyar

B. Sc. Chemical Engineering, Istanbul University (2004)
M. Sc. Chemical Engineering, Bogazici University (2008)
Ph. D. Chemical Engineering, Bogazici University (2014)

Arzu focused on the analysis of large conformational transitions of biomolecules during her Ph.D. studies at the Bogazici University in the group of Pemra Doruker. The main aim of her studies was to develop computationally fast and efficient hybrid tecnhiques and to apply them to different types of proteins such as hinge-bending, shear, DNA-binding proteins, and enzymes showing local motions. Those techniques can be summarized as:

  • ANM-MC: a combination of Elastic Network Model (ENM/ANM) and Monte-Carlo (MC) methods to generate conformational transition pathways between open and closed conformations of biomolecules. For more information, please visit our database involving different type of proteins such as adenylate kinase, GroEL, calmodulin (
  • Rg-ANM-MC: a fast hybrid technique for coarse-grained closed structure prediction of hinge-bending type proteins, where radius of gyration (Rg) was used as a constraint during the selection of direction/mode.

She also worked on the dynamics of G-protein coupled receptors (GPCRs) and protein-DNA complexes using molecular dynamics simulations and elastic network model calculations.

The aim of her recent projects is to understand the biophysics of ligand binding using the WExplore method and pharmacophore-based virtual screening.

Graduate Students

Samuel D. Lotz

B. Sc. Biology, Slippery Rock University (2014)

The main goals of my research are to understand the structural factors that determine the kinetics of ligand unbinding and to develop Quantitative Structure Kinetics Relationships (QSKRs) for customizing kinetic properties in drug design. This involves applying machine learning techniques to biological macromolecular dynamics data to predict kinetic properties of ligands in virtual screening. Data mining of large molecular dynamics (MD) datasets from enhanced sampling for information on intermolecular interactions, water hydrogen bonding networks, transition state pharmacophores, etc. is of great importance, motivating the development of mastic which is a hackable/extensible python library for doing analyses on complex macromolecular systems to accomplish this.

In collaboration with Dr. Kin Sing Lee at MSU we are currently focused on inhibitors of soluble epoxide hydrolase (sEH), which has been of intense interest as a drug target for a variety of diseases including diabetic neuropathic pain. Kinetics and /in vitro/ assays have shown that increasing the residence time of inhibitors show a marked increase in efficacy, motivating an understanding of the the unbinding transition state. We plan to make predictions of new high residence time inhibitors of sEH.

I am also interested in a more general understanding of the physical principles underlying dynamic processes of biological molecules, their evolution, and the tools used to understand them. Including Max Entropy (MaxEnt) and Maximum Caliber (MaxCal) methods for equilibrium and dynamics respectively, Geometric Algebra (Clifford Algebras), network flow theory on markov state models, interactive molecular and network visualization, and software development.

For a list of works:
ORCID: 0000-0001-6159-615X
Google Scholar: Samuel D. Lotz

github: @salotz
twitter: @real_salotz
linkedin: in/salotz

Thomas M. Dixon

B. Sc. Chemical Engineering, Kettering University (2015)

I am a CMSE graduate student working on pharmacokinetic modeling for protein-drug interactions.

Previously, I worked on optimizing reactor conditions, such as temperature, pressure, and reaction time, to extract polyphenolic compounds from plant waste using supercritical fluid extraction. Additionally, I took the extracted compounds and tested to see if they could protect DNA against radical cleavage by hydroxyl radicals.

Nazanin Donyapour

B. Sc. Computer Engineering, Hamedan University, Iran (2005)
M. Sc. Information Technology (IT) Engineering-Computer Networks, Urmia University, Iran (2013)

I am a PhD student in the CMSE department at MSU. I have a bachelors degree in Computer Engineering and MS in Information Technology. I have always been passionate about modeling and simulation. I believe if we can conquer challenges with well-engineered simulations there can be a large impact in the real-world. More importantly, it is through simulation that we can test new ideas.

My current focus is developing new algorithms to effectively run molecular simulations and unravel the mystery of protein-drug binding/unbinding problems. Molecular simulations are often very resource-heavy experiments. Thanks to recent advancements in computational power, specifically GPUs, researchers have the ability to conduct large-scale molecular simulation experiments. However, even with this new hardware in hand, efficient and well-designed parallel algorithms are still a must. It is my job to design such algorithms.

I am also interested in the application of machine learning algorithms (ML) in drug design. Specifically, I am studying how we can leverage ML in biomolecular simulations and experiments.

Thomas Díaz

B. Sc. Chemistry, Georiga Institute of Technology (2015)

I am a 4th-year PhD student in the Chemistry department at MSU. My work focuses on the development and use of enhanced sampling methods to study the unbinding processes of protein-ligand complex systems. Currently, I am studying the unbinding kinetics of the G protein-coupled receptor for C5a (C5AR). Activation of this complement system plays a crucial role in host reponse to infection and tissue damage and has been linked to diseases such as rheumatoid arthritis and Crohn's disease. Also I apply machine learning algorithms to molecular dynamics simulations for the design of pharmaceutical drugs.

At Georiga Tech, I worked with Dr. Joseph Perry on characterizing the optical properties of donor-acceptor charge carriers using Raman spectroscopy. The aim of the project was to determine the rates of generation, separation, and recombination of charge carriers to be applied in the eventual development of optical electronics.

Nicole M. Roussey

B. Sc. Biochemistry, Oakland University (2017)

I am a graduate student in the Biochemistry and Molecular Biology department here at MSU. The current focus of my project is running enchanced sampling simulations of inwardly rectifying potassium (Kir) channels. These channels are of interest due to their role in the setting and stabilization of resting membrane potentials through the IK1 current in phase 4 of the cardiac action potential. This family of channels plays an important role in many other cellular functions as well. Improper function of certain Kir-family channels is involved in many diseases including Long-QT syndrome.

My undergraduate research focused on protein structure-function analysis of the ocular protein Peripherin-2/rds. The project's aim was to determine the mechanism through which the protein was able to create and maintain an energetically unfavorable membrane curvature in rod and cone photoreceptor outer-segment disk rims.

Robert Hall

B. Sc. Biochemistry, Michigan State University (2018)

I am a 1st-year student in the Biochemistry Research Trainee Program at MSU. My work is focused on studying the biochemical structure and function of the translocator protein, TSPO, in Rhodobacter sphaeroides as well as its binding/unbinding kinetics. TSPO is of much interest due to its involvement in a number of neurodegenerative diseases, such as Alzheimer’s disease. In Dr. Shelagh Ferguson-Miller's laboratory, I conduct various biochemical assays and spectrometric strategies to study mutant forms of TSPO and how such alterations effect binding of ligands, such as protoporphyrin IX, to the enzyme. In the Dickson lab, I perform simulations to gain a deeper understanding of the ligand binding and unbinding process to TSPO and will use this knowledge to help formulate new drugs that target TSPO to treat and better diagnose neurodegenerative disease.

Undergraduate Students

Chris Bailey

I am a sophomore majoring in Biochemistry and Molecular Biology and Physics.

I am studying small molecule binding and unfolding in the BioA transaminase of Mycobacterium tuberculosis using Window Exchange Umbrella Sampling and coarse-grained sampling methods.

Kezia Suwintono

I am a senior majoring in Biochemistry and Molecular Biology/ Biotechnology. I am studying computer simulations of ligand protein systems. Previously, I worked as a research assistant at the Great Lakes Bioenergy Research Center, mainly doing sample preparation of biomass samples used for biofuel research projects.