Biomolecule-derived quantum dots for sustainable optoelectronics

Bhandari, Satyapriya; Mondal, Dibyendu; Nataraj, Sanna Kotrappanavar; Balakrishna, R. Geetha

doi:10.1039/c8na00332g

Cited by 47 publications

(42 citation statements)

References 167 publications

(648 reference statements)

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“…Despite their success, the above sequence based approaches do not generalize to broader classes of chemical compounds of similar scale as proteins that are equally capable of forming complexes with proteins that are not based on amino acids, and thus lack of an equivalent sequence-based representation. While the interaction of proteins with DNA can be accurately predicted [27], the supramolecular complexes with high molecular weight lipids [7], sugars [8], polymers [9], dendrimers [28] and inorganic nanoparticles [11,12] that receive much attention in nanomedicine and nanodiagnostics, cannot [29][30][31][32][33][34][35]. As a consequence, computational approaches that take into account the structure of proteins and their variable counterparts are preferred for interaction prediction tasks, as these methods are not protein-specific.…”

Section: Introductionmentioning

confidence: 99%

Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

Baranwal

Magner²,

Saldinger

et al. 2020

Preprint

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Development of new methods for analysis of protein-protein interactions (PPIs) at molecular and nanometer scales gives insights into intracellular signaling pathways and will improve understanding of protein functions, as well as other nanoscale structures of biological and abiological origins. Recent advances in computational tools, particularly the ones involving modern deep learning algorithms, have been shown to complement experimental approaches for describing and rationalizing PPIs. However, most of the existing works on PPI predictions use protein-sequence information, and thus have difficulties in accounting for the three-dimensional organization of the protein chains. In this study, we address this problem and describe a PPI analysis method based on a graph attention network, named Struct2Graph, for identifying PPIs directly from the structural data of folded protein globules. Our method is capable of predicting the PPI with an accuracy of 98.89% on the balanced set consisting of an equal number of positive and negative pairs. On the unbalanced set with the ratio of 1:10 between positive and negative pairs, Struct2Graph achieves a five-fold cross validation average accuracy of 99.42%. Moreover, unsupervised prediction of the interaction sites by Struct2Graph for phenol-soluble modulins are found to be in concordance with the previously reported binding sites for this family.Author summaryPPIs are the central part of signal transduction, metabolic regulation, environmental sensing, and cellular organization. Despite their success, most strategies to decode PPIs use sequence based approaches do not generalize to broader classes of chemical compounds of similar scale as proteins that are equally capable of forming complexes with proteins that are not based on amino acids, and thus lack of an equivalent sequence-based representation. Here, we address the problem of prediction of PPIs using a first of its kind, 3D structure based graph attention network (available at https://github.com/baranwa2/Struct2Graph). Despite its excellent prediction performance, the novel mutual attention mechanism provides insights into likely interaction sites through its knowledge selection process in a completely unsupervised manner.

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Section: Introductionmentioning

confidence: 99%

Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

Baranwal

Magner²,

Saldinger

et al. 2020

Preprint

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“…In the past decade, the global consumption of energy and the population have increased signicantly; this has prompted the development of energy-efficient, sustainable optical energy detection systems. [1][2][3][4][5][6][7] Among the energy detection systems, presently, ultraviolet (UV) photodetectors (PDs) have drawn potential applications in society, the scientic community and military defense. [1][2][3][4] Moreover, the human body is sensitive to UV radiation that may cause different types of diseases including cataracts and skin cancer.…”

Section: Introductionmentioning

confidence: 99%

“…[1][2][3][4][5][6][7] Among the energy detection systems, presently, ultraviolet (UV) photodetectors (PDs) have drawn potential applications in society, the scientic community and military defense. [1][2][3][4] Moreover, the human body is sensitive to UV radiation that may cause different types of diseases including cataracts and skin cancer. [8][9][10][11] Thus, the development of modern efficient UV PDs is necessary.…”

Section: Introductionmentioning

confidence: 99%

Zinc oxide ultraviolet photodetectors: rapid progress from conventional to self-powered photodetectors

2019

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“…Particularly, playing with substituents present in biomolecules are of great interest as they triggered several bio‐chemical events in the living systems . Interestingly, suitably modified biomolecules have demonstrated several interesting material properties . They have recently drawn significant attention in bio‐optoelectronics as they can be more environment friendly due to their low toxicity, potential for easy waste disposal and biodegradability.…”

Section: Introductionmentioning

confidence: 99%

“…[2,3] Interestingly, suitably modified biomolecules have demonstrated several interesting material properties. [4][5][6][7] They have recently drawn significant attention in biooptoelectronics [8] as they can be more environment friendly due to their low toxicity, potential for easy waste disposal [9] and biodegradability. [9][10][11][12] Further, bio-derived small molecules upon subtle modifications in the structures have been introduced as an efficient candidate in the realm of organic electronics.…”

Section: Introductionmentioning

confidence: 99%

Tuning Thin Film Properties by Structural Modulations in Red Fluorescent Protein Chromophore Analogues

et al. 2019

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The study of the role of substituents present in molecules is extremely important for designing new functional materials. In the present study, we have designed and synthesized four analogues (AR1‐AR4) of the red fluorescence protein (rfp) chromophore by varying the substituents and have studied their thin film properties by fabricating opto‐electronic devices with them. Molecules AR1 and AR2 were designed with improved donor‐acceptor (D−A) properties. Molecule AR3 was synthesized with an increased vinyl conjugation and molecule AR4 had an extra fluorescent moiety in the conjugation. The orbital levels and optical energy gap were estimated theoretically by density function theory. The optical absorption in solution/thin films, quality of film formation and the electrical charge transport mobility in films were studied. Photovoltaic parameters of bulk heterojunction solar cell devices formed with the four molecules were then determined. Interestingly, molecule AR3 with the extra vinyl conjugation was found to be the best of the four molecules reported here for application in organic electronics. The extra vinyl conjugation improved the π‐π stacking and helps to form smoother films with increased optical absorption and a desirable hole mobility.

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Biomolecule-derived quantum dots for sustainable optoelectronics

Abstract: The recent advances in sustainable optoelectronics applications of quantum dots derived from different biomolecules are documented in this review.

Cited by 47 publications

References 167 publications

Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

Zinc oxide ultraviolet photodetectors: rapid progress from conventional to self-powered photodetectors

Tuning Thin Film Properties by Structural Modulations in Red Fluorescent Protein Chromophore Analogues

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