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
The pharmaceutical industry needs to reverse current cost and revenue trends in the research and development process. Digital transformation is the process of turning a classical industry into a data-driven industry that leverages new technologies and opportunities arising from data science, such as artificial intelligence and machine learning. For pharma to successfully maneuver this digital transformation, changes to strategy, platforms, and cultures are necessary. Within this paper, we review the current challenges for the digital transformation of the pharma enterprise and offer a solution in form of a data centric architecture powered by a digital hub and Self-reporting data assets (SRDAs). SRDAs represents an efficient subset of the more generic FAIR – Findable, Accessible, Interoperable, Reusable – principles in pharma, as they were developed explicitly to solve important data sharing and reuse cases in this domain. Along with multiple use cases, we show how SRDAs harmonize information and make it accessible in a reusable fashion to data scientists. We present a variety of dashboards that can be created on a solid foundation of SRDAs and outline future business benefits that can follow from this transformative technology.
CASP (Critical Assessment of Structure Prediction) is an organization aimed at advancing the state of the art in computing protein structure from sequence. In the spring of 2020, CASP launched a community project to compute the structures of the most structurally challenging proteins coded for in the SARS-CoV2 genome. Forty-seven research groups submitted over 3000 three-dimensional models and 700 sets of accuracy estimates on ten proteins. The resulting models were released to the public. CASP community members also worked together to provide estimates of local and global accuracy and identify structure-based domain boundaries for some proteins. Subsequently, two of these structures (ORF3a and ORF8) have been solved experimentally, allowing assessment of both model quality and the accuracy estimates. Models from the AlphaFold2 group were found to have good agreement with the experimental structures, with main chain GDT_TS accuracy scores ranging from 63 (a correct topology) to 87 (competitive with experiment).
The pharmaceutical industry is on the brink of entering into the digital age, yet still suffers from fundamental misconceptions and outdated IT systems that inhibit its progress. Four key criteria are identified that have enabled labs to reach the post-modern stage, which are insights generation through advanced analytics, automatic communication through machine to machine interfaces, removal of boundaries for an open lab, and novel means of ensuring trust through automatic submissions. Further progress in these four areas will enable the pharmaceutical laboratory to enter the digital age. Unfortunately, historical roadblocks in the form of an application-centric mindset have so far stifled progress. However, initiatives that supported other industries on their path into the digital age are introduced and evidences for the benefits of the digital age are provided. These span from advanced analytics, data-centric architecture, metadata supported communication, knowledge assisted submissions, to digital maturity models. It is concluded that executives and lab staff within Pharma needs a transition to a data-centric world view to reap all the benefits of the digital age for faster, better, and cheaper drug development.