Date of Award
2016
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Committee Chair
Ramazan Aygun
Committee Member
Haeyong Chung
Committee Member
Marc Pusey
Subject(s)
Proteins--Analysis, Crystallization, Image analysis
Abstract
Protein crystallization screening focuses on determining the factors crucial for successful protein crystallization. Protein crystallization may require large number of parameters to be considered for setting up cocktails that would yield suitable large crystals for X-ray data collection. These parameters include types of reagents, ionic strengths, types of salts, pH value of buffers, temperature, etc. GenScreen is a genetic algorithm which identifies combinations of reagents and concentrations that have a higher degree of synergy and potentially offer better crystalline outcome. The advantage of using genetic algorithm for protein crystallization screening lies in its ability to handle large number of parameters in an uneven search space environment. With GenScreen, we can employ selective pairing of conditions, which could be useful in identifying precipitant synergy for obtaining crystals and antergy (pairs that produce no crystals) and thus narrow down the screening process. Our initial experiments showed that the output of GenScreen had a 33% average overlap with the associative experimental design (AED) in terms of the crystalline conditions. Wet lab experiments for protein AbIPPase using the output of GenScreen produced 50 crystalline conditions (30 more than crystalline conditions by the AED). These results show that GenScreen is an effective protein crystallization screening method.
Recommended Citation
Acharya, Samyam, "GenScreen : a genetic algorithm for protein crystallization screening" (2016). Theses. 174.
https://louis.uah.edu/uah-theses/174
