Computational pipeline for estimation of small-molecule T1 relaxation times

Prediction of 1H Singlet Relaxation via Intermolecular Dipolar Couplings Using the Molecular Dynamics Method

Dissolution dynamic nuclear polarization has been applied in various fields, including chemistry, biology, and medical science. To expand the scope of these applications, the nuclear singlet state, which is decoherence-free against dipolar relaxation between spin pairs, has been studied experimentally, theoretically, and numerically. The singlet state composed of proton spins is used in several applications, such as enhanced polarization preservation, molecular tagging to probe slow dynamic processes, and detection of ligand-protein complexes. In this study, we predict the lifetimes of the nuclear spin states composed of proton spin pairs using the molecular dynamics method and quantum chemistry simulations. We consider intramolecular dipolar, intermolecular dipolar between solvent and solute, chemical shift anisotropy, and spin-rotation interactions. In particular, the relaxation rate of intermolecular dipolar interactions is calculated using the molecular dynamics method for various solvents. The calculated values and the experimental values are of the same order of magnitude. Our program would provide insight into the molecular design of several NMR applications and would be helpful in predicting the nuclear spin relaxation time of synthetic molecules in advance.

Functional Genetic Screening Enables Theranostic Molecular Imaging in Cancer

PURPOSE

Targeted therapies for cancer have accelerated the need for functional imaging strategies that inform therapeutic efficacy. This study assesses the potential of functional genetic screening to integrate therapeutic target identification with imaging probe selection through a proof-of-principle characterization of a therapy-probe pair using dynamic nuclear polarization (DNP)-enhanced magnetic resonance spectroscopic imaging (MRSI).

EXPERIMENTAL DESIGN

CRISPR-negative selection screens from a public dataset were used to identify the relative dependence of 625 cancer cell lines on 18,333 genes. Follow-up screening was performed in hepatocellular carcinoma with a focused CRISPR library targeting imaging-related genes. Hyperpolarized [1-¹³C]-pyruvate was injected before and after lactate dehydrogenase inhibitor (LDHi) administration in male Wistar rats with autochthonous hepatocellular carcinoma. MRSI evaluated intratumoral pyruvate metabolism, while T₂-weighted segmentations quantified tumor growth.

RESULTS

Genetic screening data identified differential metabolic vulnerabilities in 17 unique cancer types that could be imaged with existing probes. Among these, hepatocellular carcinoma required lactate dehydrogenase (LDH) for growth more than the 29 other cancer types in this database. LDH inhibition led to a decrease in lactate generation (P < 0.001) and precipitated dose-dependent growth inhibition (P < 0.01 overall, P < 0.05 for dose dependence). Intratumoral alanine production after inhibition predicted the degree of growth reduction (P < 0.001).

CONCLUSIONS

These findings demonstrate that DNP-MRSI of LDH activity using hyperpolarized [1-¹³C]-pyruvate is a theranostic strategy for hepatocellular carcinoma, enabling quantification of intratumoral LDHi pharmacodynamics and therapeutic efficacy prediction. This work lays the foundation for a novel theranostic platform wherein functional genetic screening informs imaging probe selection to quantify therapeutic efficacy on a cancer-by-cancer basis.