{"id":{"repo_id":"syracuse-diss","oai_identifier":"oai:surface.syr.edu:etd-2538"},"canonical_url":"https://search.dev.ndltd.org/etd/syracuse-diss/oai:surface.syr.edu:etd-2538","repository":{"repo_id":"syracuse-diss","name":"Syracuse University","base_url":"https://surface.syr.edu/do/oai/"},"display":{"title":"Computational Algorithms for Predicting Membrane Protein Assembly From Angstrom to Micron Scale","abstract":"<p>Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications and pharmaceutical interests, a systematic in silico approach is undertaken in this work in order to complete the molecular puzzle of the tight junctions. This work presents a bottom-up approach involving a careful consideration of protein interactions with Angstrom-level details integrated systematically, based on the principles of statistical thermodynamics and probabilities and designed using well-structured computational algorithms, up to micron-level molecular architecture of tight junctions, forming a robust prediction with molecular details packed for up to four orders of magnitude in length scale. This work is intended to bridge the gap between the computational nano-scale studies and the experimental micron-scale observations and provide a molecular explanation for cellular behaviors in the maintenance, and the adverse consequences of breakdown of these barriers. Furthermore, a comprehensive understanding of tight junctions shall enable development of safe strategies for enhanced delivery of therapeutics.</p>","abstract_html":"&lt;p&gt;Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications and pharmaceutical interests, a systematic in silico approach is undertaken in this work in order to complete the molecular puzzle of the tight junctions. This work presents a bottom-up approach involving a careful consideration of protein interactions with Angstrom-level details integrated systematically, based on the principles of statistical thermodynamics and probabilities and designed using well-structured computational algorithms, up to micron-level molecular architecture of tight junctions, forming a robust prediction with molecular details packed for up to four orders of magnitude in length scale. This work is intended to bridge the gap between the computational nano-scale studies and the experimental micron-scale observations and provide a molecular explanation for cellular behaviors in the maintenance, and the adverse consequences of breakdown of these barriers. Furthermore, a comprehensive understanding of tight junctions shall enable development of safe strategies for enhanced delivery of therapeutics.&lt;/p&gt;","abstract_has_math":false,"creators":["Rajagopal, Nandhini"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Biomedical and Chemical Engineering","degree_department":null,"school":null,"contributors":["Nangia, Shikha"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-05-23T07:00:00Z","date_published":"2021-05-23T07:00:00Z","updated_at":"2026-07-24T04:56:23Z","subjects":["Biophysics","Claudin","Molecular Dynamics Simulation","Molecular Modeling","Protein","Tight Junctions","Biochemistry, Biophysics, and Structural Biology","Biomedical Engineering and Bioengineering","Chemistry","Computational Chemistry","Engineering","Life Sciences","Molecular Biology","Physical Sciences and Mathematics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://surface.syr.edu/etd/1537","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nangia, Shikha"]},{"key":"dc:creator","label":"Author","values":["Rajagopal, Nandhini"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Biomedical and Chemical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biophysics","Claudin","Molecular Dynamics Simulation","Molecular Modeling","Protein","Tight Junctions","Biochemistry, Biophysics, and Structural Biology","Biomedical Engineering and Bioengineering","Chemistry","Computational Chemistry","Engineering","Life Sciences","Molecular Biology","Physical Sciences and Mathematics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://surface.syr.edu/etd/1537"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications and pharmaceutical interests, a systematic in silico approach is undertaken in this work in order to complete the molecular puzzle of the tight junctions. This work presents a bottom-up approach involving a careful consideration of protein interactions with Angstrom-level details integrated systematically, based on the principles of statistical thermodynamics and probabilities and designed using well-structured computational algorithms, up to micron-level molecular architecture of tight junctions, forming a robust prediction with molecular details packed for up to four orders of magnitude in length scale. This work is intended to bridge the gap between the computational nano-scale studies and the experimental micron-scale observations and provide a molecular explanation for cellular behaviors in the maintenance, and the adverse consequences of breakdown of these barriers. Furthermore, a comprehensive understanding of tight junctions shall enable development of safe strategies for enhanced delivery of therapeutics.</p>"]},{"key":"dc:title","label":"Title","values":["Computational Algorithms for Predicting Membrane Protein Assembly From Angstrom to Micron Scale"]}]}],"canonical_facts":{"dc:contributor":["Nangia, Shikha"],"dc:creator":["Rajagopal, Nandhini"],"dc:description.abstract":["<p>Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications and pharmaceutical interests, a systematic in silico approach is undertaken in this work in order to complete the molecular puzzle of the tight junctions. This work presents a bottom-up approach involving a careful consideration of protein interactions with Angstrom-level details integrated systematically, based on the principles of statistical thermodynamics and probabilities and designed using well-structured computational algorithms, up to micron-level molecular architecture of tight junctions, forming a robust prediction with molecular details packed for up to four orders of magnitude in length scale. This work is intended to bridge the gap between the computational nano-scale studies and the experimental micron-scale observations and provide a molecular explanation for cellular behaviors in the maintenance, and the adverse consequences of breakdown of these barriers. Furthermore, a comprehensive understanding of tight junctions shall enable development of safe strategies for enhanced delivery of therapeutics.</p>"],"dc:identifier":["https://surface.syr.edu/etd/1537"],"dc:subject":["Biophysics","Claudin","Molecular Dynamics Simulation","Molecular Modeling","Protein","Tight Junctions","Biochemistry, Biophysics, and Structural Biology","Biomedical Engineering and Bioengineering","Chemistry","Computational Chemistry","Engineering","Life Sciences","Molecular Biology","Physical Sciences and Mathematics"],"dc:title":["Computational Algorithms for Predicting Membrane Protein Assembly From Angstrom to Micron Scale"],"thesis:degree_discipline":["Biomedical and Chemical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T04:56:23Z"}