Molecular Characterization
Machine-readable representations, descriptors, and features of molecules are vital for constructing statistical and machine learning models for chemical property prediction. In C-CAS, we use experimental data from spectroscopic techniques such as FTIR, UV-Vis, NMR, and mass spectrometry to construct and develop molecular representations.
Publications
Jie Xu, Samantha Grosslight, Kyle A. Mack, Sierra C. Nguyen, Kyle Clagg, Ngiap-Kie Lim, Jacob C. Timmerman, Jeff Shen, Nicholas A. White, Lauren E. Sirois, Chong Han, Haiming Zhang*, Matthew S. Sigman*, and Francis Gosselin. Atroposelective Negishi Coupling Optimization Guided by Multivariate Linear Regression Analysis: Asymmetric Synthesis of KRAS G12C Covalent Inhibitor GDC-6036. J. Am. Chem. Soc. 2022, 144, 45, 20955-20963. https://doi.org/10.1021/jacs.2c09917
Guo, K., Nan, B., Zhou, Y., Guo, T., Guo, Z., Surve, M., Liang, Z., Chawla, N.V., Wiest, O., Zhang, X. Can LLMs Solve Molecular Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation. NeurPS 2024 https://nips.cc/virtual/2024/poster/97472
Park, Y., Slshafei, F.H., Silva De Moraes, L., Hernandez Rodriguez, I., Deem, M.W., Nelson, H.M., Davis, M.E., High-Silica, Enantiomerically Enriched STW-Type Molecular Sieves. Chem. Mater. 2024. DOI: 10.1021/acs.chemmater.4c01792
Gusev, F., Kline, B.C., Quinn, R., Xu, A., Smith, B., Frezza, B., Isayev, O., Machine Learning anomaly detection of automated HPLC experiments in the Cloud Laboratory. Dig. Disc. 2025, 4, 3445-3454 https://doi.org/10.1039/D5DD00253B
Jin, T., Sass, J.I., Gao, W., Hurst, A.A., Coley, C.W.; Alexander-Katz, A., 2026. Polymerized Short Sequences as a Template for Protein Folding and Evolution. Nano Lett. 2026, 26, ASAP https://doi.org/10.1021/acs.nanolett.6c00527
Sigmund LM, Sowndarya S, Albers A, Erdmann P, Paton RS, Greb L. Predicting Lewis Acidity: Machine‐Learning the Fluoride Ion Affinity of p‐Block‐Atom‐based Molecules. Angewandte Chemie International Edition. 2024 Mar 7:e202401084. https://doi.org/10.1002/anie.202401084
Eremin, D.B., Jha, K.K., Delgadillo, D.A., Zhng, H., Foxman, S.H., Johnson, S.N., Vlahakis, N.W., Cascio, D., Lavallo, V., Rodriguez, J.A., Nelson, H.M. Spatially Aware Defraction Mapping Enables Fully Autonomous MicroED. J. Am. Chem. Soc. 2025, 147,46,4299-42310. https://doi.org/10.1021/jacs.5c10751
de Moraes, L.S., Burch, J.E., Delgadillo, D.A., Rodriguez, I.H., Mai, H., Smith, A.G., Caille, S., Walker, S.D., Wurz, R.P., Cee, V.J. and Rodriguez, J.A. Structural Elucidation and Absolute Stereochemistry for Pharma Compounds Using MicroED. Org. Lett. 2024, 26, ASAP https://doi.org/10.1021/acs.orglett.4c01865