Abstract A wide portfolio of advanced programmable materials and structures has been developed for biological applications in the last two decades. Particularly, due to their unique properties, semiconducting materials have been utilized in areas of biocomputing, implantable electronics, and healthcare. As a new concept of such programmable material design, biointerfaces based on inorganic semiconducting materials as substrates introduce unconventional paths for bioinformatics and biosensing. In particular, understanding how the properties of a substrate can alter microbial biofilm behavior enables researchers to better characterize and thus create programmable biointerfaces with necessary characteristics on demand. Herein, the current status of advanced microorganism–inorganic biointerfaces is summarized along with types of responses that can be observed in such hybrid systems. This work identifies promising inorganic material types along with target microorganisms that will be critical for future research on programmable biointerfacial structures.
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MinActionPath2: path generation between different conformations of large macromolecular assemblies by action minimization
Abstract Recent progress in solving macromolecular structures and assemblies by cryogenic electron microscopy techniques enables sampling of their conformations in different states that are relevant to their biological function. Knowing the transition path between these conformations would provide new avenues for drug discovery. While the experimental study of transition paths is intrinsically difficult, in-silico methods can be used to generate an initial guess for those paths. The Elastic Network Model (ENM), along with a coarse-grained representation (CG) of the structures are among the most popular models to explore such possible paths. Here we propose an update to our software platform MinActionPath that generates non-linear transition paths based on ENM and CG models, using action minimization to solve the equations of motion. The new website enables the study of large structures such as ribosomes or entire virus envelopes. It provides direct visualization of the trajectories along with quantitative analyses of their behaviors at http://dynstr.pasteur.fr/servers/minactionpath/minactionpath2_submission.
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- Award ID(s):
- 1934568
- PAR ID:
- 10556095
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Nucleic Acids Research
- Volume:
- 52
- Issue:
- W1
- ISSN:
- 0305-1048
- Page Range / eLocation ID:
- W256 to W263
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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