PSP-GNM

'PSP-GNM' is a novel software tool designed to address the critical biological problem of understanding the impact of missense mutations on protein stability. Missense mutations in the genome can alter one or more amino acids in a protein, potentially leading to changes in the stability of the encoded proteins.
PSP-GNM employs a unique approach called the Protein Stability Prediction with a Gaussian Network Model (PSP-GNM) to assess the unfolding Gibbs free energy change (ΔΔG) and evaluate the effects of single amino acid substitutions on protein stability. Specifically, PSP-GNM utilizes a coarse-grained Gaussian Network Model (GNM) that considers interactions between amino acids weighted by the Miyazawa-Jernigan statistical potential. The tool simulates partial unfolding of both the wildtype and mutant protein structures, and then calculates ΔΔG by measuring the difference in energies and entropies of the unfolded wildtype and mutant proteins.

Topic

Protein folding, stability and design;Genetic variation;Small molecules;Transcription factors and regulatory sites;Machine learning

Detail

  • Operation: Variant effect prediction;Network analysis;Residue distance calculation

  • Software interface: Command-line user interface

  • Language: Python

  • License: The MIT License

  • Cost: Free

  • Version name: v1.0

  • Credit: -

  • Input: -

  • Output: -

  • Contact: Sambit Kumar Mishra sambit.mishra@nih.gov

  • Collection: -

  • Maturity: -

Publications

  • PSP-GNM: Predicting Protein Stability Changes upon Point Mutations with a Gaussian Network Model.
  • Mishra SK. PSP-GNM: Predicting Protein Stability Changes upon Point Mutations with a Gaussian Network Model. PSP-GNM: Predicting Protein Stability Changes upon Point Mutations with a Gaussian Network Model. 2022; 23:(unknown pages). doi: 10.3390/ijms231810711
  • https://doi.org/10.3390/IJMS231810711
  • PMID: 36142614
  • PMC: PMC9505940

Download and documentation


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