Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of potent drug molecules across the bacterial envelope to reach their target, and thus hindering their activities in vivo. With the aid of state-of-the-art computational methods and tools, we developed a computational platform to automate and study the translocation of small molecule drugs across bacterial outer membrane proteins, with a goal of accelerating the antibiotic discovery process. We applied all-atom and coarse-grained molecular modeling, enhanced sampling techniques, and a parallel computing environment to maximize the performance. We further demonstrate the efficacy of this platform with a comprehensive study of a benchmark case. Key findings include free energy profile, translocation kinetics and thermodynamics, and molecular interactions between drug molecules and protein residues. Ultimately, this approach is designed to screen small molecule libraries with a fast turnaround time to yield structure-property relationships to discover antibiotics with high permeability. Furthermore, this work is expected to provide insights in inverse engineering and mutation design during drug development.
","abstract_html":"<p>Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of potent drug molecules across the bacterial envelope to reach their target, and thus hindering their activities in vivo. With the aid of state-of-the-art computational methods and tools, we developed a computational platform to automate and study the translocation of small molecule drugs across bacterial outer membrane proteins, with a goal of accelerating the antibiotic discovery process. We applied all-atom and coarse-grained molecular modeling, enhanced sampling techniques, and a parallel computing environment to maximize the performance. We further demonstrate the efficacy of this platform with a comprehensive study of a benchmark case. Key findings include free energy profile, translocation kinetics and thermodynamics, and molecular interactions between drug molecules and protein residues. Ultimately, this approach is designed to screen small molecule libraries with a fast turnaround time to yield structure-property relationships to discover antibiotics with high permeability. Furthermore, this work is expected to provide insights in inverse engineering and mutation design during drug development.</p>","abstract_has_math":false,"creators":["Dai, Yinghui"],"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":"2021-07-16T07:00:00Z","date_published":"2021-07-16T07:00:00Z","updated_at":"2026-07-24T04:56:14Z","subjects":["Chemical Engineering","Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://surface.syr.edu/etd/1450","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":["Dai, Yinghui"]}]},{"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":["Chemical Engineering","Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://surface.syr.edu/etd/1450"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of potent drug molecules across the bacterial envelope to reach their target, and thus hindering their activities in vivo. With the aid of state-of-the-art computational methods and tools, we developed a computational platform to automate and study the translocation of small molecule drugs across bacterial outer membrane proteins, with a goal of accelerating the antibiotic discovery process. We applied all-atom and coarse-grained molecular modeling, enhanced sampling techniques, and a parallel computing environment to maximize the performance. We further demonstrate the efficacy of this platform with a comprehensive study of a benchmark case. Key findings include free energy profile, translocation kinetics and thermodynamics, and molecular interactions between drug molecules and protein residues. Ultimately, this approach is designed to screen small molecule libraries with a fast turnaround time to yield structure-property relationships to discover antibiotics with high permeability. Furthermore, this work is expected to provide insights in inverse engineering and mutation design during drug development.
"]},{"key":"dc:title","label":"Title","values":["Development of Computational Antibiotic Screening Platform Across Bacterial Outer Membrane Proteins"]}]}],"canonical_facts":{"dc:contributor":["Nangia, Shikha"],"dc:creator":["Dai, Yinghui"],"dc:description.abstract":["Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of potent drug molecules across the bacterial envelope to reach their target, and thus hindering their activities in vivo. With the aid of state-of-the-art computational methods and tools, we developed a computational platform to automate and study the translocation of small molecule drugs across bacterial outer membrane proteins, with a goal of accelerating the antibiotic discovery process. We applied all-atom and coarse-grained molecular modeling, enhanced sampling techniques, and a parallel computing environment to maximize the performance. We further demonstrate the efficacy of this platform with a comprehensive study of a benchmark case. Key findings include free energy profile, translocation kinetics and thermodynamics, and molecular interactions between drug molecules and protein residues. Ultimately, this approach is designed to screen small molecule libraries with a fast turnaround time to yield structure-property relationships to discover antibiotics with high permeability. Furthermore, this work is expected to provide insights in inverse engineering and mutation design during drug development.
"],"dc:identifier":["https://surface.syr.edu/etd/1450"],"dc:subject":["Chemical Engineering","Engineering"],"dc:title":["Development of Computational Antibiotic Screening Platform Across Bacterial Outer Membrane Proteins"],"thesis:degree_discipline":["Biomedical and Chemical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T04:56:14Z"}