|M.Sc Student||Awad Rami|
|Subject||Modeling of Polymer as a Robot|
|Department||Department of Mechanical Engineering||Supervisors||Professor Emeritus Yehoshua Dayan|
|Professor Moshe Shoham|
|Full Thesis text|
This work presents a robotic perspective to an innate biological problem, amalgamates previous research in interdisciplinary fields and maps biological models with mechanical correspondents. The major objectives imply improving cancer drug-carriers’ efficacy by means of enhancing both mobility and ability to carry out predetermined tasks.
Drugs can't be released into the body on their own due to toxicity and rapid renal clearance. Current nanoparticle platforms offer marginal improvements over conventional chemotherapy due to facing a complex series of biological barriers. Remodeling barriers promotes metastasis and damages healthy tissues! Among the popular nanodrugs are linear Polymer-drug conjugates. They resemble biologically inspired snake-robots; the amino acids chain equivalent to serial hyper redundant manipulators. In contrary to currently recruited nanoparticles, a snake-polymer may possess a better chance of avoiding obstacles and penetrating deep into tumor core.
This study investigates tumor architecture and relative weaknesses. It highlights structures of nanomedicines and elaborates on the barriers to overcome. Further, reviews recent drug delivery enhancements and pays special emphasis to primary structures of polypeptides, intrinsic and extrinsic force applications, and pertinent angle constraints.
Subsequently, we constructed bio-robotic models to mimic the process. Though barriers were not perfectly accounted for, the recruited nano-mesh gel models were sufficiently viable. The geometrically recurring pattern of the polypeptides permitted proper modelling into a serial robot, peptide planes and dihedral angles comprising the links and joints’ variables, respectively. Data for static and variable inputs were derived from the Protein Data Bank and, subsequently, implemented into a Denavit-Hartenberg method, exploiting prediction of polypeptide configurations and kinematics.
As an example, we recruited tumor penetrating peptide and two of its variations, searched for proteins containing the sequences and acquired corresponding three-dimensional structures. Structures were analyzed and the dihedral angles calculated and arranged into statistical propensity maps, from which new structures were constructed. This model permits determining possible structural variations of sequences i.e. Correlations among shape, dihedral angles and map paths.
Two applications were investigated:
1) executing a purposeful mechanism, we demand a set of states a given peptide must undergo to complete a task and then select the most successful sequence based on the least error yield.
2) simulation for barrier evasion, this has been done through a comparative basis for different peptides, we set a variety of barriers and then simulated the sequences varying their configurations while driven by diffusion forces. The selection criterion is overcoming all required barriers in the least time.
This study will open the door to modeling polymers of a large range of sizes and tailoring optimally customized polymers with more powerful potencies. Simulations are meant to precede synthesis to determine the most potentially successful. Certain random combinations, determined through the above approach, have proven more efficient in simulations than others selected from literature. Yet remaining are lab tests to prove our theoretical model. Given that the numbers utilized were not scientifically acknowledged figures but rather subjects for comparative modeling, establishing a direct correlation between theoretical simulations and lab results would be sufficient to prove model accurate.