BHAGEERATH-H

BHAGEERATH-H predicts tertiary structures of small globular proteins using energy-based methods to generate and rank candidate conformations from sequence and secondary structure information.

Key Features:

• Automated Pipeline: The tool comprises eight distinct computational modules organized within an automated pipeline.
• Energy-Based Methodology: Uses physics-based potentials combined with biophysical filters to evaluate and rank potential protein conformations based on energy profiles.
• Candidate Structure Generation: Generates up to 10 plausible candidate structures per input starting from sequence and secondary structure information.
• Pattern Recognition and Ab Initio Integration: Integrates pattern recognition techniques with ab initio prediction methods to identify structural similarities and predict novel structures from linear sequences.
• Validation and Accuracy: Validated on a dataset of 50 small globular proteins, including 2–3 helix and strand configurations, where at least one model among the top ten lowest-energy structures achieved RMSD of 3–6 Å from native.

Scientific Applications:

• Protein Function Prediction: Provides structural models to assess how sequence variations influence protein structure and function.
• Evolutionary Studies: Enables investigation of conservation of structural motifs across species by comparing predicted conformations.
• Drug Target Identification: Supplies candidate protein conformations useful for identifying potential binding sites and interactions.

Methodology:

Integrates pattern recognition techniques with ab initio prediction methods, employs physics-based potentials and biophysical filters to score and rank conformations, and operates via an automated pipeline of eight computational modules taking sequence and secondary structure as input to generate up to ten candidate models.