Protoss

Protoss predicts and places hydrogen atoms in protein–ligand complexes to provide explicit hydrogen positions for accurate modeling of hydrogen-bond networks, protonation states, and tautomeric forms.

Key Features:

• Automated Hydrogen Placement: Adds missing hydrogen atoms to protein structures and ligands to produce complete molecular complexes.
• Protonation States and Tautomers: Enumerates and accounts for multiple protonation states and tautomeric forms of ligands and residues.
• Optimal Hydrogen Bonding Network: Uses an empirical scoring function to generate the most probable hydrogen positions by optimizing hydrogen-bonding configurations and degrees of freedom.
• Robust Chemical Modeling: Incorporates a chemical model that describes tautomerism and ionization effects consistently.
• Resolution of Crystallographic Ambiguities: Resolves side-chain orientation ambiguities including flips in glutamine, asparagine, and histidine residues.
• Dynamic Programming Approach: Employs dynamic programming to optimize configurations efficiently and enable real-time score evaluation during molecular docking.

Scientific Applications:

• Protein–ligand interaction analysis: Provides explicit hydrogen positions to improve identification and characterization of hydrogen bonds within complexes.
• Binding energy and docking scoring: Supplies hydrogen placement and protonation/tautomeric information for more accurate binding energy calculations and docking scores.
• Modeling chemical microstates: Supports modeling of tautomerism and ionization effects in ligands and residues within complexes.
• Structural model refinement: Assists in resolving crystallographic ambiguities such as Gln, Asn, and His side-chain flips to improve structural representations.
• Validation against curated datasets: Produces results that have been verified against manually adjusted datasets.

Methodology:

Automated addition of hydrogen atoms; enumeration of protonation states and tautomers; empirical scoring function to optimize hydrogen-bonding networks over possible configurations and degrees of freedom; chemical modeling of tautomerism and ionization; resolution of side-chain flips in glutamine, asparagine, and histidine; dynamic programming for efficient optimization and real-time score evaluation during molecular docking.