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In Silico Peptide Selection for Biomining

Authors: Nayebi, Niloofar;

In Silico Peptide Selection for Biomining

Abstract

Biomining is an efficient way for improving mineral extraction and remediation processes. Using specific/targeted separation is a promising method to increase purification yield of minerals and metals at low cost. In traditional methods extraction and purification of the desired materials from ores requires extensive processes. Through these processes, tailing streams coming out of a mine are usually discharged into tailing ponds. Presence of toxic and bioavailable elements in tailing ponds causes deleterious long-term consequences on the ecosystem. On the other hand, tailings ponds are usually mineral- and metal-rich environments. Our objective in this study was to consider tailings ponds as secondary sources for minerals and to design methods for the removal of toxic elements to help the environment. To this end, we have introduced a new in silico method to select peptides with high affinity and specificity for a given target material (calcite 104 surface) to use as a recognition block in biomining applications. The selected peptides are proposed to be used as coating on magnetic nanoparticle core. Peptide-based engineered materials will have the ability to detect, bind and extract the target material by using magnetic fields.

Country
Canada
Related Organizations
Keywords

Virtual library, Onragin-inorganic interaction, Computational approach, Peptides

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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