Discovery of Non-Cysteine-Targeting Covalent Inhibitors by Activity-Based Proteomic Screening with a Cysteine-Reactive Probe

Covalent inhibitors of enzymes are increasingly appreciated as pharmaceutical seeds, yet discovering non-cysteine-targeting inhibitors remains challenging. Herein, we report an intriguing experience during our activity-based proteomic screening of 1601 reactive small molecules, in which we monitored the ability of library molecules to compete with a cysteine-reactive iodoacetamide probe. One epoxide molecule, F8, exhibited unexpected enhancement of the probe reactivity for glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a rate-limiting glycolysis enzyme. In-depth mechanistic analysis suggests that F8 forms a covalent adduct with an aspartic acid in the active site to displace NAD+, a cofactor of the enzyme, with concomitant enhancement of the probe reaction with the catalytic cysteine. The mechanistic underpinning permitted the identification of an optimized aspartate-reactive GAPDH inhibitor. Our findings exemplify that activity-based proteomic screening with a cysteine-reactive probe can be used for discovering covalent inhibitors that react with non-cysteine residues

Apparent diffusion coefficient (ADC) values in the response and non-response patients before and after chemotherapy treatment (mm²⋅s).

*<p>compare with pre-treatment ADC value, <i>p</i>>0.05;</p

Number of patient enrollment.

<p>Number of patient enrollment.</p

Agreement of tumor sizes, as measured by MRI versus postsurgical pathology.

<p>(A) Bland-Altman plot of tumor size measured by pretreatment MRI examination and postsurgical pathological results; 95% plots are within the limit of agreement (0±10 mm), indicating a good agreement between pretreatment MRI results and postsurgical pathological measurement. (B) Bland-Altman plot of tumor size measured by posttreatment MRI and postsurgical pathology; almost 40% plots are out of the limit of agreement (0±10 mm), which indicates a poor agreement between posttreatment MRI and postsurgical pathology, i.e posttreatment MRI results may not be in place of postsurgical pathological measurement.</p

The empirical (A) and smooth (B) AUCs in the validation cohort.

<p>MRI in combination with serum SCC-ag vs. MRI or SCC-ag alone, respectively.</p

Univariate and Multivariate Logistic Analysis of SCC-ag Level and Response to Neoadjuvant Chemotherapy in a Prospective Cohort.

*<p>ΔMRI indicated the decrease percentage in tumor size before and after NACT with MRI.</p>+<p>ΔSCC-ag indicated the decrease percentage in SCC-ag level before and after NACT.</p

The Accuracy Estimation of NACT Response in an External Validation Cohort.

<p>Abbreviation: ΔMRI: the decrease percentage in tumor size before and after NACT with MRI; ΔΔSCC-ag: the decrease percentage in SCC-ag level before and after NACT; PPV: positive predictive value; NPV: negative predictive value; AUC: area under the ROC curve;</p><p>The confidence interval was estimated based on exact test of binominal distribution.</p

Demographics and Clinical Characteristics of Eligible Patients in Prospective Cohort.

<p>The values in the parenthese represented the percentage frequency;</p

Tumor sizes before and after neoadjuvant chemotherapy with the percent of SCC-ag decease.

<p>Tumor sizes before and after neoadjuvant chemotherapy with the percent of SCC-ag decease.</p

Conventional and DW-MRI of the same lesion from a 55-year-old woman undergoing NACT.

<p>(A)–(C): pretreatment axial (A) and sagittal (B) conventional MR images and diffusion-weighted MR image (C). (D)–(F): preoperative axial (D) and sagittal (E) conventional MR images and diffusion-weighted MR image (F). The red circles in (B)–(F) indicate the largest pretreatment and preoperative lesion as measured in different planes and using different MRI techniques.</p