Ligand interaction landscape of transcription factors and essential enzymes in E. coli

Integrating protein contact networks for the engineering of thermostable lipase A

In the field of industrial biocatalysis, the rapid advancement of enzyme functional evolution necessitates new theories and computational methods to achieve target functions with fewer iterations. This study identified key residues affecting enzyme stability by constructing the protein contact network (PCN) of Lipase A. Comparing the PCNs of the wild-type (WT) and the 6B variant revealed that changes in residue interactions and node properties (e.g., degree and betweenness centrality (BC)) positively impacted stability. Using thresholds for degree and BC, 25 candidate sites were screened, and 11 out of 18 single-point mutation designs improved thermal stability. Mutations were divided into three groups (M1, M2, M3) based on network communities and contributions, followed by iterative combinations. M1, containing five mutations distributed across four communities, increased the melting temperature (Tm) by 14.61 °C, close to the predicted 13.97 °C, demonstrating a linear additive effect. In M2, three new mutations resulted in a non-linear additive effect, with a ΔTm of 17.58 °C (Expected ΔTm = 18.93 °C). In contrast, the three new mutations in M3 destabilized the enzyme (Observed ΔTm = 15.94 °C vs Expected ΔTm = 19.92 °C). Molecular dynamics simulations showed that polar edge nodes enhanced network connectivity, while proline mutations rigidified flexible regions, improving stability. Conversely, M3 mutations disrupted α-helix stability by increasing the dihedral angle fluctuations of residue Y161, might to a stability-activity trade-off. The PCN provides valuable insights for developing efficient and precise design strategies.

High-throughput protein target mapping enables accelerated bioactivity discovery for ToxCast and PFAS compounds

Chemical pollution is a global threat to human health, yet the toxicity mechanism of most contaminants remains unknown. Here, we applied an ultrahigh-throughput affinity-selection mass spectrometry (AS-MS) platform to systematically identify protein targets of prioritized chemical contaminants. After benchmarking the platform, we screened 50 human proteins against 481 prioritized chemicals, including 446 ToxCast chemicals and 35 per- and polyfluoroalkyl substances (PFAS). Among 24,050 interactions assessed, we discovered 35 novel interactions involving 14 proteins, with fatty acid-binding proteins (FABPs) emerging as the most ligandable protein family. Given this, we selected FABPs for further validation, which revealed a distinct PFAS binding pattern: legacy PFAS selectively bound to FABP1, whereas replacement compounds, PFECAs, unexpectedly interacted with all FABPs. X-ray crystallography further revealed that the ether group enhances molecular flexibility of alternative PFAS, to accommodate the binding pockets of FABPs. Our findings demonstrate that AS-MS is a robust platform for the discovery of novel protein targets beyond the scope of the ToxCast program and highlight the broader protein-binding spectrum of alternative PFAS as potential regrettable substitutes.