PubMed · 13811155
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J E COLEMAN, B L VALLEE. 1960. Metallocarboxypeptidases.. https://pubmed.ncbi.nlm.nih.gov/13811155/
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Protein-based antibacterials such as bacteriophage endolysins offer a targeted therapeutic strategy against Gram-positive pathogens. However, prioritizing the most effective candidates from the large sequence diversity available remains a significant challenge. Here we present a standardized computational-experimental benchmarking framework that evaluates seven phage-derived endolysin variants (E1, E2, E3, E7, E10, E12, and E15) identified from Bacillus genomes. We combined molecular docking and residue-level interaction mapping against muramyl dipeptide (MDP), a minimal conserved peptidoglycan motif, with 1000-ns molecular dynamics simulations, MM/PBSA binding free-energy estimation, and matched functional inhibition assays against Staphylococcus aureus and Micrococcus luteus. Computational analyses revealed generally favorable MDP recognition across variants, albeit with notable differences in contact patterns and complex stability profiles. Experimental screening identified E2 as the most potent antibacterial agent against both species, while E7 and E1 performed strongly in selected computational metrics. Integrated analysis showed only modest correlations between computational descriptors of fragment recognition/stability and observed antibacterial performance. This study establishes a practical comparative benchmarking platform for endolysin candidate prioritization, nominates E2 and E7 as promising candidates for further development, and highlights E1 as a potential structural scaffold for rational engineering, while explicitly demonstrating both the utility and the current limitations of using minimal peptidoglycan fragments as proxies for full cell-wall recognition in lysin benchmarking.
A crêpe silk fabric was treated with different alkaline (3374-L, GC 897-H), neutral (3273-C), and acid (EC 3.4 23.18) proteases with the aim to study their effectiveness as degumming agents. Proteases were used under optimum conditions of pH and temperature, while enzyme dosage (0.05-2 U/g fabric) and treatment time (5-240 min) were changed in order to study the kinetics of sericin removal. Degumming loss with soap and alkali was 27 wt.%. The maximum amount of sericin removed in 1 h was 17.6, 24, and 19 wt.% for 3374-L (2 U/g fabric), GC 897-H (1U/g fabric), and 3273-C (0.1 U/g fabric), respectively. Under the experimental conditions adopted, EC 3.4 23.18 was almost ineffective as a degumming agent. Degumming loss increased as a function of the treatment time, reaching a value of 25 wt.% with 1 U/g fabric of 3374-L. The morphological analysis showed that sericin was completely removed from the warp yarns of the crêpe fabric, while the highly twisted weft yarns still exhibited the presence of sericin deposits within the most internal parts of the close fibre texture. The chromatographic pattern of soluble sericin peptides changed as a function of the kind of enzyme used, enzyme dosage, and treatment time. A mixture of peptides from 5 to 20 kDa in weight, with a weight-average molecular weight of about 12 kDa was obtained.
The lambda-dynamics method was used to calculate the relative binding free energies of inhibitors to the hepatitis C virus (HCV) protease. A total of seven HCV protease p-side product inhibitors were used in this study. The inhibitors are 6-mer peptides spanning P6-P1 (Ac-Asp-d-Glu-Leu-Ile-Cha-P1-CO(2)H). For this protein, S1 is a major hydrophobic pocket for binding. Binding of various residues to this pocket was investigated through free energy simulations and experimental inhibition constants. Several 300 ps lambda-dynamics simulations in explicit solvent were performed. The relative binding free energy was estimated from these simulations. From a single simulation, the inhibitors can be correctly classified into highly potent and weakly potent groups. The multiple simulations give an accurate rank ordering of inhibitor potency; computed and experimental binding free energies agree with 0.6 kcal/mol for five of the seven inhibitors. In addition, free energy perturbation (FEP) calculations were carried out to validate the results from lambda-dynamics. A total of 6 ligand pairs were compared. For each pair, 5-11 windows were used to map one ligand to the other. The cumulative simulation time was over 2 ns for each ligand pair. For four of the six ligand pairs, the lambda-dynamics free energy difference fits better than the FEP difference to the experimental value. The fact that the lambda-dynamics method achieved similar results in only a fraction of the total simulation time for FEP further demonstrates the robustness of the lambda-dynamics method.