The mitochondrial protein IF1 binds to the catalytic domain of the ATP synthase and inhibits ATP hydrolysis in ischemic tissues. Moreover, IF1 is overexpressed in many tumors and has been shown to act as a pro-oncogenic protein, although its mechanism of action is still debated. Here, we show that ATP5IF1 gene disruption in HeLa cells decreases colony formation in soft agar and tumor mass development in xenografts, underlining the role of IF1 in cancer. Notably, the lack of IF1 does not affect proliferation or oligomycin-sensitive mitochondrial respiration, but it sensitizes the cells to the opening of the permeability transition pore (PTP). Immunoprecipitation and proximity ligation analysis show that IF1 binds to the ATP synthase OSCP subunit in HeLa cells under oxidative phosphorylation conditions. The IF1–OSCP interaction is confirmed by NMR spectroscopy analysis of the recombinant soluble proteins. Overall, our results suggest that the IF1-OSCP interaction protects cancer cells from PTP-dependent apoptosis under normoxic conditions.

Fragment-based lead discovery (FBLD) is one of the most efficient methods to develop new drugs. We present here a new computational protocol called High-Throughput Supervised Molecular Dynamics (HT-SuMD), which makes it possible to automatically screen up to thousands of fragments, representing therefore a new valuable resource to prioritise fragments in FBLD campaigns. The protocol was applied to Bcl-X L , an oncological protein target involved in the regulation of apoptosis through protein–protein interactions. Initially, HT-SuMD performances were validated against a robust NMR-based screening, using the same set of 100 fragments. These independent results showed a remarkable agreement between the two methods. Then, a virtual screening on a larger library of additional 300 fragments was carried out and the best hits were validated by NMR. Remarkably, all the in silico selected fragments were confirmed as Bcl-X L binders. This represents, to date, the largest computational fragments screening entirely based on MD.

CK2 is a Ser/Thr protein kinase involved in many cellular processes such as gene expression, cell cycle progression, cell growth and differentiation, embryogenesis, and apoptosis. Aberrantly high CK2 activity is widely documented in cancer, but the enzyme is also involved in several other pathologies, such as diabetes, inflammation, neurodegeneration, and viral infections, including COVID-19. Over the last years, a large number of small-molecules able to inhibit the CK2 activity have been reported, mostly acting with an ATP-competitive mechanism. Polyoxometalates (POMs), are metal-oxide polyanionic clusters of various structures and dimensions, with unique chemical and physical properties. POMs were identified as nanomolar CK2 inhibitors, but their mechanism of inhibition and CK2 binding site remained elusive. Here, we present the biochemical and biophysical characterizing of the interaction of CK2α with a ruthenium-based polyoxometalate, [Ru4(μ-OH)2(μ-O)4(H2O)4 (γ-SiW10O36)2]10− (Ru4POM), a potent inhibitor of CK2. Using analytical Size-Exclusion Chromatography (SEC), Isothermal Titration Calorimetry (ITC), and SAXS we were able to unravel the mechanism of inhibition of Ru4POM. Ru4POM binds to the positively-charged substrate binding region of the enzyme through electrostatic interactions, triggering the dimerization of the enzyme which consequently is inactivated. Ru4POM is the first non-peptide molecule showing a substrate-competitive mechanism of inhibition for CK2. On the basis of SAXS data, a structural model of the inactivated (CK2α)2(Ru4POM)2 complex is presented.

<p>In this manuscript, for the first time, we presented a fragment library and we validated its performance by comparison with a well-established technique for fragment screening as solution NMR. We were able to screen 400 different fragments producing a total of 1200 independent fragment-protein recognition pathways. As far as we know, this represents the largest screening based on Molecular dynamics ever reported. Our simulations successfully detected the true binders in the library in a prospective study, showing a notable agreement with a state-of-art screening we performed by NMR on the same dataset.</p>

<p>In this manuscript, for the first time, we presented a fragment library and we validated its performance by comparison with a well-established technique for fragment screening as solution NMR. We were able to screen 400 different fragments producing a total of 1200 independent fragment-protein recognition pathways. As far as we know, this represents the largest screening based on Molecular dynamics ever reported. Our simulations successfully detected the true binders in the library in a prospective study, showing a notable agreement with a state-of-art screening we performed by NMR on the same dataset.</p>