(2gz) Computational Studies of the Structure and Dynamics of Biomolecules at Interfaces

Research Interests:

My research focuses on understanding the biophysics and biochemistry of biological phenomena, with a particular emphasis on understanding the structure and interactions of biomolecules at interfaces. By unraveling the intricate details of biomolecular interactions at interfaces, my research holds the promise of contributing to the design of more efficient drugs to uncover novel strategies for combating diseases and solving the possible side effects of current drugs. In my research group, we will implement molecular modeling techniques to investigate these biological phenomena. Molecular simulations and statistical mechanical theories provide the atomic-level understanding that contributes to achieving additional biophysical and biochemical insights and describes and confirms experimental research. My initial research will encompass three directions:

Aim 1. It has been demonstrated that some Metal-Organic Frameworks (MOFs) are biocompatible and promising materials for drug delivery and protecting specific drugs inside the human body. The functionality of certain peptide drugs, like anti-microbial peptides, depends on their unique secondary structure. However, these peptides quickly unfold and adopt a coil structure in solution. Improving the functionality of peptides inside the body can be achieved by finding a proper MOF to encapsulate these peptides and maintain their secondary structures until they reach the desired target. To explore a variety of biocompatible MOFs for this purpose, a computational study in atomic detail would be beneficial. In my lab, we aim to investigate the structure of these drug peptides within diverse compatible MOFs to comprehend how their secondary peptide structures are retained. By employing enhanced-sampling techniques such as accelerated molecular dynamics, we can generate free-energy maps that reveal the most stable conformation of peptides inside MOFs. Additionally, these simulations will provide valuable insight into the interaction between these peptides and the active sites within the MOF. Ultimately, this study will contribute to designing better MOFs for encapsulating and safeguarding drugs, preserving their structures effectively.

Aim 2. The resistance of bacteria against various antibiotics or antimicrobial drugs has been increasing. One mechanism of bacteria resistance involves modifying the inner or outer membrane to reduce permeability. For instance, specific mutations in strains of Pseudomonas aeruginosa and Staphylococcus aureus alter the lipid bilayer composition and consequently enhance resistance against antibiotics. A detailed understanding of the membrane characteristics, such as rigidity, permeability, and mobility before and after the mutation, would aid in designing more effective antibiotics. We will study the interactions between different antibiotics and antimicrobial drugs and the mutant and non-mutant lipid bilayers by implementing atomistic computational methods. This investigation aims to identify how these membranes can resist antibiotics, providing valuable insights for developing effective treatments. In all models, we will consider a realistic distribution of lipid tails and headgroups to mimic the behavior of bacteria's membranes accurately.

Aim 3. The exponential rise of nanomaterials (NMs) in different applications, such as drug delivery, has been accompanied by growing concerns about their toxicity. Scientific and medical research studies have pointed out that NMs cause cell death and disrupt cellular functions by inducing damage to lipids and interactions with proteins and nucleic acids. However, the mechanisms underlying these interactions between NMs and cells remain largely unknown. Proteins can interact with NMs, making a protein-rich layer known as the protein corona (PC), which is a thermodynamic and kinetic process. Proteins with high binding affinity and a slow dissociation rate contribute to the formation of a hard corona (HC). In contrast, proteins with low binding affinity and a fast dissociation rate contribute to forming a soft corona (SC). The PC plays a significant role in particle-cell interactions. Most studies have focused on HC-membrane interactions by using simplified cell membrane models. Understanding the composition and dynamics of the SCs has proven challenging due to the difficulty in obtaining their actual composition in situ. In my lab, I aim to investigate these phenomena in more detail using computational techniques. For instance, we plan to incorporate realistic cell membranes, which have diverse types of membrane proteins, to study the interaction of these PCs with the cell membrane. Furthermore, our focus will extend to the structure and dynamics of the SC, which primarily involves protein-protein interactions.

Teaching interests:

Besides my research career, I have extensive teaching experience of about 12 years that shows my intensive interest and passion for education. I believe teaching helps me achieve a more profound understanding. My teaching journey commenced during my undergraduate years when I started instructing at high schools and institutes. As a Ph.D. student, I continued teaching as a Teaching Assistant (TA) at the University of Rhode Island (URI). Over the course of six years, I was privileged to serve as a TA for a diverse range of courses. Notably, I had the opportunity to be the sole instructor of "Chemical Engineering Thermodynamics 1" course (CHE313) and the "Process Dynamics and Control" course (CHE425) at URI, where my students' evaluations consistently reflected my high performance. Furthermore, during my postdoctoral training, I had the valuable opportunity to expand my teaching skills through mentoring Ph.D. and master's students. My previous experiences in teaching are summarized below:

1. Instructor of “ Chemical Engineering Thermodynamics 1” at URI – Spring 2017
2. Instructor of “ Process Dynamics and Control” at URI – Fall 2019
3. TA for Senior Chemical Engineering Lab I and II – 9 semesters at URI
4. TA for courses: Chemical Kinetics and Reactor Design, Thermodynamics 1 and 2, Engineering Materials, Chemical Process Calculations.
5. Teacher in Iran of Chemistry, Geometry, Analytical Geometry, and Linear algebra for 8 years at high school and university entrance exam preparation institutes.

In the future, I am most interested in teaching Applied mathematics in chemical engineering, Molecular modeling, Thermodynamics, Mass transfer, Heat transfer, Process Dynamics and Control, Fluid mechanics, and Unit Operations.

Research Experience:

Ph.D. Chemical Engineering, University of Rhode Island. As a Ph.D. student in Professor Michael L. Greenfield's group, I have been trained in utilizing high-resolution computational techniques to study mainly the dynamics and structure of biological systems. I had this opportunity to be the first student in his group who focused on studying biological systems. One of my notable contributions was developing a C++ package for all-atom normal mode analysis (NMA), which enabled the simultaneous calculation and monitoring of vibrational modes during molecular dynamics simulation [1,2]. We applied this method to study and improve the dynamics and vibrations of atoms in aromatic rings of tryptophan and tyrosine in a solution [1]. Moreover, the dynamics and vibrations of an antimicrobial peptide (AMP) in solution were studied during the structural transition between α-helical and helix-hinge-helix conformations. By employing high-resolution computational vibrational techniques, we found that the shapes and frequencies of amide bands II and III only changed for amide groups near the hinge structure [2]. Furthermore, we developed the most realistic and complex S. aureus lipid bilayer system. We implemented my developed reverse Monte Carlo package to optimize phospholipid types and their amounts to represent characterization data from the literature, which led us to using 19 different phospholipid types. We applied my developed C++ package to calculate the statistical and dynamic membrane characteristics of this lipid bilayer system [3]. We also applied 3D Voronoi tessellation to calculate the volume occupied by each lipid, subsequently enabling us to determine the area per lipid head group [4]. This study indicates interesting biochemical and biophysical membrane properties that point out the advantages of using diversity in molecule size and composition to model a complex phospholipid bilayer system [3,4].

Postdoctoral Fellow, Chemical Engineering, Northwestern University. During my postdoctoral training under the supervision of Professor Randall Q. Snurr, I had the opportunity to expand my knowledge of molecular modeling in the field of material science and adsorption. My primary focus was studying the adsorption and diffusion of water molecules in metal-organic frameworks (MOFs), particularly at low relative humidity. We generated thousands of hypothetical MOFs with diverse metal nodes, linkers, and topologies. We applied Grand Canonical Monte Carlo (GCMC) simulations on these MOFs at 10% relative humidity to identify the MOFs with high water uptakes and to gain valuable structure/property insights (in prep). In addition, we delved deeper into the fundamental aspects of water adsorption in MOFs. Our research involved the development of a specific Monte Carlo move within the RASPA source code. This implementation improved the comparison of calculated water adsorption isotherms with experimental results (in prep). Furthermore, I am studying the diffusion of diverse chemical warfare agents (CWAs) and their simulants within various zirconium-based MOFs in the presence of water molecules (in prep).

Selected publications:

1. Joodaki, L.M. Martin, M.L. Greenfield. Planarity and Out-of-Plane Vibrational Modes of Tryptophan and Tyrosine in Biomolecular Modeling. Phys. Chem. Chem. Phys., 2019, 21, 23943-23965.
2. Joodaki, L.M. Martin, M.L. Greenfield. Computational Study of Helical and Helix-Hinge-Helix Conformations of an Anti-Microbial Peptide in Solution by Molecular Dynamics and Vibrational Analysis, J. Phys. Chem. B, 2021, 125, 703-721.
3. Joodaki, L.M. Martin, M.L. Greenfield. Generation and Computational Characterization of a Complex Staphylococcus aureus Lipid Bilayer, Langmuir, 2022, 38, 31, 9481-9499, Cover Art.
4. L. Greenfield, L.M. Martin, F. Joodaki. Computing Individual Area per Head Group Reveals Lipid Bilayer Dynamics, J. Phys. Chem. B, 2022. 126, 10697-10711.