AMO
  • Overview
  • Motivation
  • Getting Started
    • Requirements
    • Installation
    • All-in-one installation
  • Usages
  • Protein sequence
    • Sequence alignment
    • Quality control
  • Protein evolution-design-folding
    • Amino acid sequence
    • Residue communities
    • Sequence potential & energy
    • Inferring functional networks
    • Point mutation
    • Protein design
    • Sequence energy
    • Protein folding
  • Protein function
  • Structural bioinformatics
    • PDB parser
    • Structure to point cloud
    • Ramachandran map
    • Residue distances to coordinates
    • Infer residue-contact
    • Structure prediction
    • Swarm-intelligence-based folding
    • Coarse-grained MD
    • Folding energy
    • Probabilistic deep learning
    • Sequence features
  • Protein stability
    • OptiFel for stability
  • DNA sequence analysis
    • Format conversion
    • Quality control
  • Lipidomics
    • Data visualization
    • Functional mapping
  • Machine learning
    • Sequential evolving neural networks
    • Optimization
  • Plotting
  • FAQs
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  1. Protein evolution-design-folding

Point mutation

Mutant effects

Before doing point mutation, we are required to prepare a parametric file using sequence_eca as a potential for the given protein.

amo point_mutation \
-threads 1 \
-hlog \
-jobname [JOB_NAME] \
-fastx <INPUT_WT_SEQUENCE_FILE> \
-mat <POTENTIAL_FILE> \
-output [OUTPUT_DIRECTORY]
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Last updated 2 years ago