PMC:7299399 / 46295-49391
Annnotations
LitCovid-PD-FMA-UBERON
| Id | Subject | Object | Predicate | Lexical cue | fma_id |
|---|---|---|---|---|---|
| T220 | 1656-1664 | Body_part | denotes | proteins | http://purl.org/sig/ont/fma/fma67257 |
| T221 | 1686-1691 | Body_part | denotes | cells | http://purl.org/sig/ont/fma/fma68646 |
| T222 | 2127-2132 | Body_part | denotes | cells | http://purl.org/sig/ont/fma/fma68646 |
| T223 | 2142-2147 | Body_part | denotes | cells | http://purl.org/sig/ont/fma/fma68646 |
| T224 | 2507-2522 | Body_part | denotes | plasma membrane | http://purl.org/sig/ont/fma/fma63841 |
| T225 | 2591-2596 | Body_part | denotes | cells | http://purl.org/sig/ont/fma/fma68646 |
LitCovid-PD-MONDO
| Id | Subject | Object | Predicate | Lexical cue | mondo_id |
|---|---|---|---|---|---|
| T145 | 50-58 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T146 | 1520-1528 | Disease | denotes | COVID-19 | http://purl.obolibrary.org/obo/MONDO_0100096 |
| T147 | 2136-2141 | Disease | denotes | tumor | http://purl.obolibrary.org/obo/MONDO_0005070 |
| T148 | 2585-2590 | Disease | denotes | tumor | http://purl.obolibrary.org/obo/MONDO_0005070 |
| T149 | 3085-3093 | Disease | denotes | SARS-CoV | http://purl.obolibrary.org/obo/MONDO_0005091 |
LitCovid-PD-CLO
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| T427 | 122-123 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | a |
| T428 | 986-987 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | a |
| T429 | 1080-1086 | http://purl.obolibrary.org/obo/CLO_0001658 | denotes | active |
| T430 | 1568-1571 | http://purl.obolibrary.org/obo/PR_000001343 | denotes | aim |
| T431 | 1686-1691 | http://purl.obolibrary.org/obo/GO_0005623 | denotes | cells |
| T432 | 1808-1810 | http://purl.obolibrary.org/obo/CLO_0007622 | denotes | MD |
| T433 | 2127-2132 | http://purl.obolibrary.org/obo/GO_0005623 | denotes | cells |
| T434 | 2142-2147 | http://purl.obolibrary.org/obo/GO_0005623 | denotes | cells |
| T435 | 2293-2294 | http://purl.obolibrary.org/obo/CLO_0001020 | denotes | a |
| T436 | 2330-2332 | http://purl.obolibrary.org/obo/CLO_0007622 | denotes | MD |
| T437 | 2507-2513 | http://purl.obolibrary.org/obo/UBERON_0001969 | denotes | plasma |
| T438 | 2514-2522 | http://purl.obolibrary.org/obo/UBERON_0000158 | denotes | membrane |
| T439 | 2591-2596 | http://purl.obolibrary.org/obo/GO_0005623 | denotes | cells |
| T440 | 3051-3053 | http://purl.obolibrary.org/obo/CLO_0008192 | denotes | NP |
LitCovid-PD-CHEBI
| Id | Subject | Object | Predicate | Lexical cue | chebi_id |
|---|---|---|---|---|---|
| T391 | 104-108 | Chemical | denotes | drug | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T392 | 109-118 | Chemical | denotes | molecules | http://purl.obolibrary.org/obo/CHEBI_25367 |
| T393 | 181-186 | Chemical | denotes | drugs | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T394 | 496-500 | Chemical | denotes | drug | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T395 | 650-655 | Chemical | denotes | drugs | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T396 | 962-966 | Chemical | denotes | drug | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T397 | 1451-1455 | Chemical | denotes | drug | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T398 | 1609-1614 | Chemical | denotes | drugs | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T399 | 1656-1664 | Chemical | denotes | proteins | http://purl.obolibrary.org/obo/CHEBI_36080 |
| T400 | 1771-1775 | Chemical | denotes | drug | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T401 | 1776-1785 | Chemical | denotes | molecules | http://purl.obolibrary.org/obo/CHEBI_25367 |
| T402 | 1808-1810 | Chemical | denotes | MD | http://purl.obolibrary.org/obo/CHEBI_74699 |
| T403 | 2099-2102 | Chemical | denotes | NPs | http://purl.obolibrary.org/obo/CHEBI_50803 |
| T404 | 2330-2332 | Chemical | denotes | MD | http://purl.obolibrary.org/obo/CHEBI_74699 |
| T405 | 2396-2398 | Chemical | denotes | Au | http://purl.obolibrary.org/obo/CHEBI_29287 |
| T406 | 2428-2437 | Chemical | denotes | nanocages | http://purl.obolibrary.org/obo/CHEBI_51117 |
| T407 | 2439-2447 | Chemical | denotes | nanorods | http://purl.obolibrary.org/obo/CHEBI_50805 |
| T408 | 2570-2573 | Chemical | denotes | NPs | http://purl.obolibrary.org/obo/CHEBI_50803 |
| T409 | 2609-2614 | Chemical | denotes | drugs | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T410 | 2683-2687 | Chemical | denotes | drug | http://purl.obolibrary.org/obo/CHEBI_23888 |
| T411 | 3051-3053 | Chemical | denotes | NP | http://purl.obolibrary.org/obo/CHEBI_50803|http://purl.obolibrary.org/obo/CHEBI_53793|http://purl.obolibrary.org/obo/CHEBI_73425 |
LitCovid-PD-HP
| Id | Subject | Object | Predicate | Lexical cue | hp_id |
|---|---|---|---|---|---|
| T38 | 2136-2141 | Phenotype | denotes | tumor | http://purl.obolibrary.org/obo/HP_0002664 |
| T39 | 2585-2590 | Phenotype | denotes | tumor | http://purl.obolibrary.org/obo/HP_0002664 |
LitCovid-sentences
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| T179 | 0-80 | Sentence | denotes | Speeding up the Nanomedicine-Based Approaches for COVID-19 by In Silico Analysis |
| T180 | 81-715 | Sentence | denotes | Currently, repurposing drug molecules is a key strategy for identifying approved or investigational drugs outside the scope of the original medical indication that can be used to fight COVID-19.130,131 There are various advantages to this strategy, including already-established safety profiles, fast transition to clinical studies, and less investment needed, compared to the process of developing an entirely new drug.132,133 Therefore, these advantages have the potential to result in less risky and more rapid returns on investment in the development of repurposed drugs, benefits that are particularly important during pandemics. |
| T181 | 716-849 | Sentence | denotes | In addition to rapid diagnosis, making recommendations to physicians about rapid treatment methods can save the lives of many people. |
| T182 | 850-1109 | Sentence | denotes | Combining in silico tools such as molecular docking, molecular dynamics, and computational chemistry with large drug databases provides a great advantage in selecting “possible candidates” from among thousands of pharmaceutically active substances (Figure 3). |
| T183 | 1110-1272 | Sentence | denotes | In silico analyses should be supported by the literature, expert opinions (pharmacologists and clinicians), and, when possible, preclinical and clinical findings. |
| T184 | 1273-1432 | Sentence | denotes | After selecting the best candidates following in silico analyses, detailed in vitro and in vivo experimentation should be undertaken prior to clinical studies. |
| T185 | 1433-1692 | Sentence | denotes | Recently, various drug-repurposing studies have been published to assist in the global COVID-19 pandemic response.134−136 Such studies aim to identify whether already-approved drugs have the capacity to interact with viral proteins or receptors on host cells. |
| T186 | 1693-1807 | Sentence | denotes | Figure 3 Schematic of how in silico analysis can be used to select candidate drug molecules for clinical studies. |
| T187 | 1808-1831 | Sentence | denotes | MD, molecular dynamics. |
| T188 | 1832-2064 | Sentence | denotes | In nanomedicine, computational models have recently garnered attention; such work may help to identify how nanomaterials interact with biological systems and to determine how the efficacy of these nanotherapeutics could be improved. |
| T189 | 2065-2893 | Sentence | denotes | Computational models indicate how NPs are taken up by healthy cells or tumor cells, enabling better predictions regarding the pharmacokinetic and pharmacodynamic properties of these materials.134 For example, Lunnoo et al. used a coarse-grained molecular dynamics (MD) simulation to observe the internalization pathways of various Au nanostructures (nanospheres, nanocages, nanorods, nanoplates, and nanohexapods) into an idealized mammalian plasma membrane.137 Other studies have simulated how different NPs can target tumor cells and deliver drugs.138,139 Therefore, in silico approaches that are currently used for drug repurposing, including molecular docking, molecular dynamics, and computational chemistry, constitute valuable tools to aid preclinical and clinical studies of nanomaterials directed for disease treatment. |
| T190 | 2894-3096 | Sentence | denotes | Considering the urgent need for nanomedicine against the current pandemic, in silico analyses may be especially useful in guiding the rational design of new NP formulations required to fight SARS-CoV-2. |
LitCovid-PubTator
| Id | Subject | Object | Predicate | Lexical cue | tao:has_database_id |
|---|---|---|---|---|---|
| 691 | 50-58 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 695 | 842-848 | Species | denotes | people | Tax:9606 |
| 696 | 266-274 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 697 | 1520-1528 | Disease | denotes | COVID-19 | MESH:C000657245 |
| 703 | 2497-2506 | Species | denotes | mammalian | Tax:9606 |
| 704 | 3085-3095 | Species | denotes | SARS-CoV-2 | Tax:2697049 |
| 705 | 2396-2398 | Chemical | denotes | Au | MESH:D006046 |
| 706 | 2136-2141 | Disease | denotes | tumor | MESH:D009369 |
| 707 | 2585-2590 | Disease | denotes | tumor | MESH:D009369 |
2_test
| Id | Subject | Object | Predicate | Lexical cue |
|---|---|---|---|---|
| 32519842-30310233-158555 | 501-504 | 30310233 | denotes | 132 |
| 32519842-32305088-158556 | 1547-1550 | 32305088 | denotes | 134 |
| 32519842-32305088-158557 | 2257-2260 | 32305088 | denotes | 134 |
| 32519842-31065337-158558 | 2619-2622 | 31065337 | denotes | 139 |