TransportTools

TransportTools analyzes internal voids in biomolecules and characterizes ligand transport pathways from high-throughput molecular dynamics simulation datasets to support studies in drug design, protein engineering, and structural biology.

Key Features:

• Internal void analysis: Detects and analyzes internal voids within biomolecules from simulation data.
• Ligand transport pathway characterization: Characterizes ligand transport mechanisms and pathways through molecular voids.
• High-throughput MD dataset processing: Processes high-throughput molecular dynamics simulation datasets to extract transport-relevant events.
• Pathway utilization assessment: Assesses pathway utilization across extensive simulated datasets to evaluate transport occurrences.
• Custom analysis support: Supports custom-made analyses to tailor investigations to specific research needs.
• Implementation: Implemented in Python3.

Scientific Applications:

• Drug design: Analyzing ligand access and egress pathways to inform structure-based drug design.
• Protein engineering: Revealing how internal voids and transport pathways affect protein function for engineering efforts.
• Structural biology: Elucidating pathways within complex biomolecular structures to advance structural interpretation.
• Study of rare transport events: Detecting and analyzing rare transport events captured in molecular dynamics simulations.
• Hypothesis-driven transport studies: Enabling exploration of novel hypotheses in biomolecular transport mechanisms.

Methodology:

Implemented in Python3; analyzes high-throughput molecular dynamics simulation datasets to identify internal voids, characterize ligand transport pathways, assess pathway utilization, and support custom analyses.