Redox reactions define the energetic constraints within which life exists. However, measurements of reduction potentials are scarce and current prediction methods fall short of desired accuracy and coverage. We harness quantum chemistry to enable the high-throughput prediction of reduction potentials with unparalleled accuracy. We calculate the reduction potentials of all redox pairs that can be generated using known biochemical compounds. This high-resolution dataset reveals global trends in metabolism - including the differences between and within oxidoreductase groups - and optimality principles that explain the redox potential of NAD(P). The cover figure depicts the predicted reversibility of the reaction converting shikimate to 3-dehydroshikimate.
Image Credit: Benjamin Sanchez-Lengeling
Editorials
Ten simple rules for scientists: Improving your writing productivity
PLOS Computational Biology: published October 4, 2018 | https://doi.org/10.1371/journal.pcbi.1006379
Ten simple rules when considering retirement
PLOS Computational Biology: published October 4, 2018 | https://doi.org/10.1371/journal.pcbi.1006411
Ten simple rules for developing good reading habits during graduate school and beyond
PLOS Computational Biology: published October 11, 2018 | https://doi.org/10.1371/journal.pcbi.1006467
Education Articles
Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor
PLOS Computational Biology: published October 3, 2018 | https://doi.org/10.1371/journal.pcbi.1006468
Ten quick tips for getting the most scientific value out of numerical data
PLOS Computational Biology: published October 11, 2018 | https://doi.org/10.1371/journal.pcbi.1006141
Perspective
What to know before forecasting the flu
PLOS Computational Biology: published October 12, 2018 | https://doi.org/10.1371/journal.pcbi.1005964
Research Articles
Use of an individual-based model of pneumococcal carriage for planning a randomized trial of a whole-cell vaccine
PLOS Computational Biology: published October 1, 2018 | https://doi.org/10.1371/journal.pcbi.1006333
Linking signal detection theory and encoding models to reveal independent neural representations from neuroimaging data
PLOS Computational Biology: published October 1, 2018 | https://doi.org/10.1371/journal.pcbi.1006470
Cooperation of dual modes of cell motility promotes epithelial stress relaxation to accelerate wound healing
PLOS Computational Biology: published October 1, 2018 | https://doi.org/10.1371/journal.pcbi.1006502
Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design
PLOS Computational Biology: published October 1, 2018 | https://doi.org/10.1371/journal.pcbi.1006505
meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays
PLOS Computational Biology: published October 1, 2018 | https://doi.org/10.1371/journal.pcbi.1006506
Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties
PLOS Computational Biology: published October 4, 2018 | https://doi.org/10.1371/journal.pcbi.1006484
A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons
PLOS Computational Biology: published October 4, 2018 | https://doi.org/10.1371/journal.pcbi.1006510
Noise propagation in an integrated model of bacterial gene expression and growth
PLOS Computational Biology: published October 5, 2018 | https://doi.org/10.1371/journal.pcbi.1006386
Functional conservation of sequence determinants at rapidly evolving regulatory regions across mammals
PLOS Computational Biology: published October 5, 2018 | https://doi.org/10.1371/journal.pcbi.1006451
Interactive reservoir computing for chunking information streams
PLOS Computational Biology: published October 8, 2018 | https://doi.org/10.1371/journal.pcbi.1006400
In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability
PLOS Computational Biology: published October 8, 2018 | https://doi.org/10.1371/journal.pcbi.1006460
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Modeling large fluctuations of thousands of clones during hematopoiesis: The role of stem cell self-renewal and bursty progenitor dynamics in rhesus macaque
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Quantum chemistry reveals thermodynamic principles of redox biochemistry
PLOS Computational Biology: published October 24, 2018 | https://doi.org/10.1371/journal.pcbi.1006471
Dilution and titration of cell-cycle regulators may control cell size in budding yeast
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Structural and dynamic basis of substrate permissiveness in hydroxycinnamoyltransferase (HCT)
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Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments
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Computational discovery of dynamic cell line specific Boolean networks from multiplex time-course data
PLOS Computational Biology: published October 29, 2018 | https://doi.org/10.1371/journal.pcbi.1006538
Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interactions
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Modeling and subtleties of K-Ras and Calmodulin interaction
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Suboptimal community growth mediated through metabolite crossfeeding promotes species diversity in the gut microbiota
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Steered molecular dynamics simulations reveal critical residues for (un)binding of substrates, inhibitors and a product to the malarial M1 aminopeptidase
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A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments
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Correction
Correction: Elucidation of molecular kinetic schemes from macroscopic traces using system identification
PLOS Computational Biology: published October 16, 2018 | https://doi.org/10.1371/journal.pcbi.1006539