Comparative Evaluation of the Antibacterial and Antitumor Activities of 9-Phenylfascaplysin and Its Analogs.

Based on the results of our own preliminary studies, the derivative of the marine alkaloid fascaplysin containing a phenyl substituent at C-9 was selected to evaluate the therapeutic potential in vivo and in vitro. It was shown that this compound has outstandingly high antimicrobial activity against Gram-positive bacteria, including antibiotic-resistant strains in vitro. The presence of a substituent at C-9 of the framework is of fundamental importance, since its replacement to neighboring positions leads to a sharp decrease in the selectivity of the antibacterial action, which indicates the presence of a specific therapeutic target in bacterial cells. On a model of the acute bacterial sepsis in mice, it was shown that the lead compound was more effective than the reference antibiotic vancomycin seven out of nine times. However, ED50 value for 9-phenylfascaplysin (7) was similar for the unsubstituted fascaplysin (1) in vivo, despite the former being significantly more active than the latter in vitro. Similarly, assessments of the anticancer activity of compound 7 against various variants of Ehrlich carcinoma in mice demonstrated its substantial efficacy. To conduct a structure-activity relationship (SAR) analysis and searches of new candidate compounds, we synthesized a series of analogs of 9-phenylfascaplysin with varying aryl substituents. However, these modifications led to the reduced aqueous solubility of fascaplysin derivatives or caused a loss of their antibacterial activity. As a result, further research is required to explore new avenues for enhancing its pharmacokinetic characteristics, the modification of the heterocyclic framework, and optimizing of treatment regimens to harness the remarkable antimicrobial potential of fascaplysin for practical usage.

Design of stable circular permutants of the GroEL chaperone apical domain.

Enhancing protein stability holds paramount significance in biotechnology, therapeutics, and the food industry. Circular permutations offer a distinctive avenue for manipulating protein stability while keeping intra-protein interactions intact. Amidst the creation of circular permutants, determining the optimal placement of the new N- and C-termini stands as a pivotal, albeit largely unexplored, endeavor. In this study, we employed PONDR-FIT's predictions of disorder propensity to guide the design of circular permutants for the GroEL apical domain (residues 191-345). Our underlying hypothesis posited that a higher predicted disorder value would correspond to reduced stability in the circular permutants, owing to the increased likelihood of fluctuations in the novel N- and C-termini. To substantiate this hypothesis, we engineered six circular permutants, positioning glycines within the loops as locations for the new N- and C-termini. We demonstrated the validity of our hypothesis along the set of the designed circular permutants, as supported by measurements of melting temperatures by circular dichroism and differential scanning microcalorimetry. Consequently, we propose a novel computational methodology that rationalizes the design of circular permutants with projected stability. Video Abstract.

In Silico Simulations Reveal Molecular Mechanism of Uranyl Ion Toxicity towards DNA-Binding Domain of PARP-1 Protein.

The molecular toxicity of the uranyl ion (UO22+) in living cells is primarily determined by its high affinity to both native and potential metal-binding sites that commonly occur in the structure of biomolecules. Recent advances in computational and experimental research have shed light on the structural properties and functional impacts of uranyl binding to proteins, organic ligands, nucleic acids, and their complexes. In the present work, we report the results of the computational investigation of the uranyl-mediated loss of DNA-binding activity of PARP-1, a eukaryotic enzyme that participates in DNA repair, cell differentiation, and the induction of inflammation. The latest experimental studies have shown that the uranyl ion directly interacts with its DNA-binding subdomains, zinc fingers Zn1 and Zn2, and alters their tertiary structure. Here, we propose an atomistic mechanism underlying this process and compute the free energy change along the suggested pathway. Our Quantum Mechanics/Molecular Mechanics (QM/MM) simulations of the Zn2-UO22+ complex indicate that the uranyl ion replaces zinc in its native binding site. However, the resulting state is destroyed due to the spontaneous internal hydrolysis of the U-Cys162 coordination bond. Despite the enthalpy of hydrolysis being +2.8 kcal/mol, the overall reaction free energy change is -0.6 kcal/mol, which is attributed to the loss of domain's native tertiary structure originally maintained by a zinc ion. The subsequent reorganization of the binding site includes the association of the uranyl ion with the Glu190/Asp191 acidic cluster and significant perturbations in the domain's tertiary structure driven by a further decrease in the free energy by 6.8 kcal/mol. The disruption of the DNA-binding interface revealed in our study is consistent with previous experimental findings and explains the loss of PARP-like zinc fingers' affinity for nucleic acids.

Using AlphaFold to predict the impact of single mutations on protein stability and function.

AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted the pLDDT and metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the same AlphaFold pLDDT metrics with the impact of a single mutation on structure using a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold may not be immediately applied to other problems or applications in protein folding.

Best templates outperform homology models in predicting the impact of mutations on protein stability.

MOTIVATION: Prediction of protein stability change upon mutation (ΔΔG) is crucial for facilitating protein engineering and understanding of protein folding principles. Robust prediction of protein folding free energy change requires the knowledge of protein three-dimensional (3D) structure. In case, protein 3D structure is not available, one can predict the structure from protein sequence; however, the perspectives of ΔΔG predictions for predicted protein structures are unknown. The accuracy of using 3D structures of the best templates for the ΔΔG prediction is also unclear. RESULTS: To investigate these questions, we used a representative set of seven diverse and accurate publicly available tools (FoldX, Eris, Rosetta, DDGun, ACDC-NN, ThermoNet and DynaMut) for stability change prediction combined with AlphaFold or I-Tasser for protein 3D structure prediction. We found that best templates perform consistently better than (or similar to) homology models for all ΔΔG predictors. Our findings imply using the best template structure for the prediction of protein stability change upon mutation if the protein 3D structure is not available. AVAILABILITY AND IMPLEMENTATION: The data are available at https://github.com/ivankovlab/template-vs-model. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.