A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Cardiotoxicity and ROS Protection Assessment of three Structure-Related N-Acylhydrazones with Potential for the Treatment of Neurodegenerative Diseases.

The senescence process is associated with accumulated oxidative damage and increased metal concentration in the heart and brain. Besides, abnormal metal-protein interactions have also been linked with the development of several conditions, including Alzheimer's and Parkinson's diseases. Over the years we have described a series of structure-related compounds with different activities towards models of such diseases. In this work, we evaluated the potential of three N-acylhydrazones (INHHQ: 8-hydroxyquinoline-2-carboxaldehyde isonicotinoyl hydrazone, HPCIH: pyridine-2-carboxaldehyde isonicotinoyl hydrazone and X1INH: 1-methyl-1H-imidazole-2-carboxaldehyde isonicotinoyl hydrazone) to prevent oxidative stress in cellular models, with the dual intent of being active on this pathway and also to confirm their lack of cardiotoxicity as an important step in the drug development process, especially considering that the target population often presents cardiovascular comorbidity. The 8-hydroxyquinoline-contaning compound, INHHQ, exhibits a significant cardioprotective effect against hydrogen peroxide and a robust antioxidant activity. However, this compound is the most toxic to the studied cell models and seems to induce oxidative damage on its own. Interestingly, although not possessing a phenol group in its structure, the new-generation 1-methylimidazole derivative X1INH showed a cardioprotective tendency towards H9c2 cells, demonstrating the importance of attaining a compromise between activity and intrinsic cytotoxicity when developing a drug candidate.

The effect of temperature on the synthesis of magnetite nanoparticles by the coprecipitation method.

Magnetic nanoparticles, such as magnetite (Fe3O4), exhibit superparamagnetic properties below 15 nm at room temperature. They are being explored for medical applications, and the coprecipitation technique is preferred for cost-effective production. This study investigates the impact of synthesis temperature on the nanoparticles' physicochemical characteristics. Two types of magnetic analysis were conducted. Samples T 40, T 50, and T 60 displayed superparamagnetic behavior, as evidenced by the magnetization curves. The experiments verified the development of magnetic nanoparticles with an average diameter of approximately dozens of nanometers, as determined by various measurement methods such as XDR, Raman, and TEM. Raman spectroscopy showed the characteristic bands of the magnetite phase at 319, 364, 499, and 680 cm-1. This was confirmed in the second analysis with the ZFC-FC curves, which showed that the samples' blocking temperatures were below ambient temperature. ZFC-FC curves revealed a similar magnetization of about 30 emu/g when applying a magnetic field of 5 kOe.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries.