The Consortium of Molecular Design at BYU provides cutting edge interdisciplinary research opportunities for students to push the envelope for protein engineering and drug discovery.
We use close collaboration between laboratories at BYU in Physics, Chemistry, Computer Science, LifeSciences, and Engineering to tackle these challenging topics from all angles.
We actively seek industrial collaboration and support for our efforts and are excited to explore mutually beneficial application of all state-of-the-art technologies to revolutionize molecular design.
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Selected Publications
Computational enzyme design has made great strides over the last five years. Traditional methods of enzyme design require synthesis and evaluation of many mutations. Computational enzyme design has emerged as a powerful tool to predict how specific mutations modify a protein’s activity, stability, and/or selectivity. Such computational approaches can evaluate many mutations and reduce the load of in vitro work by identifying mutations likely to accomplish design objectives. Computational approaches can explore mutational spaces inaccessible in traditional mutagenesis. Computational methods reduce cost and time compared with experimental approaches. We review the efficacy and key differences of computational enzyme design methods as published in recent studies. The included articles used computational methods to design enzymes, were published no earlier than 2015, met design objectives, and verified results in vitro.
Objective
To provide a systematic overview of world dietary sugar and sugar-sweetened beverage (SSB) intake trends in children and adolescents.
Data Sources
Medline, Embase, and the Cochrane Central Register of Controlled Trials in the Cochrane Library were searched through January 2019 to identify longitudinal follow-up studies with time-trend data and repeated cross-sectional studies.
Data Extraction
Data from studies reporting ≥ 2 measurements (sugars, SSB, or sweets/candy) over ≥ 2 years and included ≥ 20 healthy, normal- or overweight children or adolescents aged 1–19 years.
Data Analysis
Data from 43 articles (n = 4 prospective cohort studies; n = 39 repeated cross-sectional studies) from 15 countries (n = 8 European countries plus Australia, Canada, China, South Korea, Mexico, Russia, and the United States) are presented narratively. According to the risk of bias in nonrandomized studies of interventions tool, 34 studies were judged to have a moderate risk of bias, and 5 to have a serious risk of bias.
Conclusions
Consumption among US children and adolescents increased substantially in the decades preceding 2000, followed by a faster and continued decline. As a whole, other international intake trends did not reveal drastic increases and decreases in SSB and dietary sugars; they tended to change only slightly across 3 decades.
Cell factories converting bio-based precursors to chemicals present an attractive avenue to a sustainable economy, yet screening of genetically diverse strain libraries to identify the best-performing whole-cell biocatalysts is a low-throughput endeavor. For this reason, transcriptional biosensors attract attention as they allow the screening of vast libraries when used in combination with fluorescence-activated cell sorting (FACS). However, broad ligand specificity of transcriptional regulators (TRs) often prohibits the development of such ultra-high-throughput screens. Here, we solve the structure of the TR LysG of Corynebacterium glutamicum, which detects all three basic amino acids. Based on this information, we follow a semi-rational engineering approach using a FACS-based screening/counterscreening strategy to generate an l-lysine insensitive LysG-based biosensor. This biosensor can be used to isolate l-histidine-producing strains by FACS, showing that TR engineering towards a more focused ligand spectrum can expand the scope of application of such metabolite sensors.