2026-09-20T04:25:16Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/108299 2023-07-11 col_2142_5131 col_2142_105429 com_2142_5130 com_2142_105424

Caetano-Anolles, Gustavo Caetano-Anolles, Gustavo Hudson, Matthew E Rodriguez-Zas, Sandra L Zhao, Sihai Dave Mughal, Fizza 2020-08-27T00:50:16Z 2020-08-27T00:50:16Z 2022-08-27T00:51:40Z 2020-05-03 2020-05 Biological systems are complex entities comprising of parts that interact with each other within and across different levels of the hierarchy of biological organization to achieve common goals. We find that evolutionary constraints vary with different levels of granularity of the structure of biological systems. Different levels of organization and their parts often use similar strategies to achieve different goals. For example, at the organismal level cellular and viral proteomes leverage disorder to achieve advanced functionality and functional economy, respectively. Intrinsic disorder analysis at the protein domain level revealed that early protein domains were ordered and therefore, disorder is a benefit that was acquired later in evolution. In contrast, at the more granular level of protein secondary structure, we found that protein loops of ordered ancient fold families were highly disordered. Remarkably, the disorder analysis of protein loops uncovered the presence of ‘ordered’ loops, the existence of which could be explained by some molecular functions requiring a certain level of structural integrity, which is subsequently conserved to retain protein function. We surveyed pathways in biological systems to capture interactions of subnetworks and enzymes by analyzing evolving metabolic networks and find that hierarchical modularity is a key evolutionary principle of organization. Small world behavior increases at lower levels and decreases at higher levels of organization in evolving metabolic networks. Remarkably, we find similar small world tendencies in evolving dynamics networks of protein loops. Lastly, we present a structural morphospace to study these varying levels of organizations as well as the relationship between the order resulting from evolutionary constraints and intrinsic disorder that is also evolutionarily conserved. Structural morphospaces for dynamics networks, and evolving metabolic networks occupy regions that are reflective of the constraints acting on that specific level. We find that evolutionary constraints act on higher levels of organization following a biphasic pattern of diversification and growth, while optimizing for robustness. Moreover, evolution leverages disorder to maintain control, order and introduce innovation in the system. Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01 The student, Fizza Mughal, accepted the attached license on 2020-05-01 at 11:49. The student, Fizza Mughal, submitted this Dissertation for approval on 2020-05-01 at 11:50. This Dissertation was approved for publication on 2020-05-03 at 18:55. DSpace SAF Submission Ingestion Package generated from Vireo submission #15145 on 2020-08-25 at 17:42:27 Made available in DSpace on 2020-08-27T00:50:16Z (GMT). No. of bitstreams: 2 MUGHAL-DISSERTATION-2020.pdf: 15659473 bytes, checksum: a4516e5e20d40eeb04f4dad073bba021 (MD5) LICENSE.txt: 4209 bytes, checksum: bb38d1e2fa438f11cd9e02137777d577 (MD5) Previous issue date: 2020-05-03 Embargo set by: Seth Robbins for item 115913 Lift date: 2022-08-27T00:50:22Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 115913 Lift date: 2022-08-27T00:51:40Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system Author requested closed access (OA after 2yrs) in Vireo ETD system Limited application/pdf http://hdl.handle.net/2142/108299 en Copyright 2020 Fizza Mughal Phylogenomics Comparative genomics Evolution Protein Structure Network Biology Protein Flexibility Evolution of protein structure, function, and dynamics in biological systems text Thesis Graduate College Programs Informatics University of Illinois at Urbana-Champaign Dissertation Ph.D.