Update README.md

README.md

@@ -31,7 +31,7 @@ Sets 7-16 of hallucinated peptide cif files and experimental CCDC structures.
 
 This dataset contains hallucinated cyclic peptide scaffold structures (in CIF format) generated using AfCycDesign, a deep learning approach built on AlphaFold2 for de novo design of cyclic peptides. The scaffolds span peptide lengths of 7–16 residues and were generated through a hallucination procedure that simultaneously samples sequence and structure to produce well-ordered cyclic peptides. Structures in this dataset were filtered for high prediction confidence (pLDDT > 0.9) by AfCycDesign, representing 24,104 structurally diverse peptides predicted to fold into their designed conformations. These scaffolds serve as starting points for incorporating functional elements such as target-binding motifs for therapeutic applications.
 
-- **Curated by:** Akshaya Narayanasamy, Jie Chen, Zachary Drake, Adriana Hernandez Gonzalez, Lina Maria Pena
+- **Curated by:** Jie Chen / jiechen7 (at) uw.edu, Zachary Drake / zacharydrake (at) g.ucla.edu, Adriana Hernandez Gonzalez / ahgonzalez (at) ucdavis.edu, Akshaya Narayanasamy / akshayanarayanasamy (at) gmail.com, Lina Maria Pena Pardo / linamp (at) umich.edu
 - **Language(s) (NLP):** Not applicable (structural biology data)
 - **License:** MIT
 
@@ -127,4 +127,4 @@ The AfCycDesign code is implemented within the ColabDesign framework. For additi
 
 ## Dataset Card Authors
 
-Jie Chen, Zachary Drake
+Jie Chen / jiechen7 (at) uw.edu, Zachary Drake / zacharydrake (at) g.ucla.edu, Adriana Hernandez Gonzalez / ahgonzalez (at) ucdavis.edu, Akshaya Narayanasamy / akshayanarayanasamy (at) gmail.com, Lina Maria Pena Pardo / linamp (at) umich.edu