CSD-Discovery
E474957
computational chemistry software suite
molecular modelling software
structure-based drug design software
CSD-Discovery is a computational chemistry software suite from the Cambridge Crystallographic Data Centre designed for structure-based drug design and molecular modeling using crystallographic data.
All labels observed (1)
| Label | Occurrences |
|---|---|
| CSD-Discovery canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4850588 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CSD-Discovery Context triple: [Cambridge Crystallographic Data Centre, product, CSD-Discovery]
-
A.
CSD
CSD is the renowned Computer Science Department at Carnegie Mellon University, recognized globally for its pioneering research and education in computer science.
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B.
CSDC
CSDC is a research center based at McGill University that focuses on the study and advancement of democratic citizenship and political participation.
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C.
Data-Driven Discovery Initiative
The Data-Driven Discovery Initiative is a research program that advances scientific discovery by supporting innovative data science methods, tools, and researchers across disciplines.
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D.
Search and Discovery
Search and Discovery is a regular Physics Today section that highlights notable recent advances and findings across the physical sciences.
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E.
DSCD
DSCD is the Dynamic Systems and Control Division of the American Society of Mechanical Engineers, focusing on research, education, and professional activities in systems dynamics, control theory, and related technologies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CSD-Discovery Target entity description: CSD-Discovery is a computational chemistry software suite from the Cambridge Crystallographic Data Centre designed for structure-based drug design and molecular modeling using crystallographic data.
-
A.
CSD
CSD is the renowned Computer Science Department at Carnegie Mellon University, recognized globally for its pioneering research and education in computer science.
-
B.
CSDC
CSDC is a research center based at McGill University that focuses on the study and advancement of democratic citizenship and political participation.
-
C.
Data-Driven Discovery Initiative
The Data-Driven Discovery Initiative is a research program that advances scientific discovery by supporting innovative data science methods, tools, and researchers across disciplines.
-
D.
Search and Discovery
Search and Discovery is a regular Physics Today section that highlights notable recent advances and findings across the physical sciences.
-
E.
DSCD
DSCD is the Dynamic Systems and Control Division of the American Society of Mechanical Engineers, focusing on research, education, and professional activities in systems dynamics, control theory, and related technologies.
- F. None of above. chosen
Statements (53)
| Predicate | Object |
|---|---|
| instanceOf |
computational chemistry software suite
ⓘ
molecular modelling software ⓘ structure-based drug design software ⓘ |
| abbreviation | CSD ⓘ |
| basedOn | experimental crystallographic data ⓘ |
| developer | Cambridge Crystallographic Data Centre NERFINISHED ⓘ |
| domain |
computational chemistry
ⓘ
drug discovery ⓘ medicinal chemistry ⓘ structural biology ⓘ |
| supportsTask |
SAR analysis
ⓘ
binding affinity estimation ⓘ binding mode analysis ⓘ binding pocket characterisation ⓘ binding site analysis ⓘ cavity detection ⓘ compound prioritisation ⓘ conformer generation ⓘ crystal structure analysis ⓘ crystallographic data mining ⓘ ensemble docking ⓘ fragment elaboration ⓘ fragment growing ⓘ fragment linking ⓘ fragment-based drug design ⓘ hit identification ⓘ hit-to-lead optimisation ⓘ interaction fingerprinting ⓘ interaction hotspot mapping ⓘ knowledge-based scoring ⓘ lead optimisation ⓘ library design ⓘ ligand efficiency analysis ⓘ ligand preparation ⓘ ligand similarity searching ⓘ ligand-based design ⓘ molecular docking ⓘ pharmacophore modelling ⓘ pharmacophore-based screening ⓘ pose clustering ⓘ pose filtering ⓘ pose prediction ⓘ pose rescoring ⓘ protein preparation ⓘ protein–ligand interaction analysis ⓘ protein–ligand interaction visualisation ⓘ protein–ligand scoring ⓘ selectivity analysis ⓘ structure-based drug design ⓘ virtual screening ⓘ water displacement analysis ⓘ water network analysis ⓘ |
| usesDataFrom | Cambridge Structural Database NERFINISHED ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: CSD-Discovery Description of subject: CSD-Discovery is a computational chemistry software suite from the Cambridge Crystallographic Data Centre designed for structure-based drug design and molecular modeling using crystallographic data.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.