[Paper Review] HBAT 2: A Python Package to Analyse Hydrogen Bonds and Other Non-covalent Interactions in Macromolecular Structures

Tiwari, Abhishek|arXiv (Cornell University)|Feb 16, 2026

Crystallography and molecular interactions0 citations

TL;DR

HBAT 2 is a Python reimplementation that analyzes hydrogen bonds and a broad range of non-covalent interactions in PDB structures, with GUI/CLI/API access and cooperativity visualization.

ABSTRACT

Hydrogen bonds and other non-covalent interactions play a crucial role in maintaining the structural integrity and functionality of biological macromolecules such as proteins and nucleic acids. Accurate identification and analysis of these interactions are essential for understanding molecular recognition, protein folding, and drug design. HBAT (Hydrogen Bond Analysis Tool) is software for analysing hydrogen bonds and other weak interactions in macromolecular structures. This paper presents HBAT 2, an updated Python reimplementation of the original HBAT tool published in 2007. HBAT 2 is a Python package for automated analysis of hydrogen bonds and other non-covalent interactions in macromolecular structures available in Protein Data Bank (PDB) file format. The software identifies and analyses traditional hydrogen bonds, weak hydrogen bonds, halogen bonds, X-H$\cdots$$π$, $π$-$π$ stacking, and n$ ightarrow$$π$* interactions using geometric criteria. It also detects cooperativity and anticooperativity chains and renders them as 2D visualisations. The latest version offers improved cross-platform tkinter-based graphical user interface (GUI), a web-based interface, a simple command-line interface (CLI), and a developer-friendly API, making it accessible to users with different computational backgrounds.

Motivation & Objective

• Provide a modern, cross-platform tool to analyze diverse non-covalent interactions in macromolecular structures.
• Automate structure preparation and comprehensive interaction detection beyond canonical hydrogen bonds.
• Visualize cooperativity networks and provide multiple output formats for integration into workflows.
• Offer user-friendly interfaces (GUI, web, CLI) and a developer-friendly API.
• Address limitations of the original HBAT and integrate with contemporary structural biology workflows.

Proposed method

• Modular architecture with separate components for PDB parsing, geometric analysis, statistics, and visualization.
• Use nearest-neighbor searching with configurable distance cutoffs and geometric filters to detect interactions.
• Structure preparation with PDBFixer and OpenBabel to add missing atoms and clean structures.
• Detect a broad spectrum of interactions: hydrogen bonds, halogen bonds, X-H...π, π-π stacking, and n→π* interactions.
• Cooperativity analysis and visualization using NetworkX/Matplotlib and GraphViz.
• 3D visualization via 3Dmol.js with a web server and Jupyter notebook widget.
• Parameter presets tailored to different experimental conditions (high-res X-ray, NMR, membranes, drug design).
• Output in text, CSV, and JSON formats; optional PDB output; integration with downstream tools.

Figure 1: The latest update to HBAT 2 uses tkinter to provide a cross-platform graphical user interface (GUI)

Experimental results

Research questions

• RQ1 How can HBAT 2 comprehensively detect and classify diverse non-covalent interactions in static macromolecular structures?
• RQ2 Can HBAT 2 effectively visualize and analyze cooperativity networks in hydrogen-bond networks?
• RQ3 What are the practical workflows and interfaces (GUI, web, CLI, API) that maximize accessibility for experimental and computational researchers?
• RQ4 How does HBAT 2 integrate structure preparation steps to enable end-to-end analysis from PDB files?
• RQ5 What presets optimize interaction analysis for different experimental contexts?

Key findings

• HBAT 2 implements detection for hydrogen bonds, halogen bonds, X-H...π, π-π stacking, and n→π* interactions using geometric criteria.
• It offers two visualization options for networks: NetworkX/Matplotlib and GraphViz to display cooperativity chains.
• 3Dmol.js provides interactive 3D visualization of structures with highlighted interactions in web and Jupyter environments.
• Presets streamline parameter selection for common experimental conditions, improving usability.
• HBAT 2 supports cross-platform GUI, web interface, CLI, and a developer-friendly API, enabling diverse user workflows.
• The tool integrates with PDBFixer/OpenBabel to automate structure preparation, enabling end-to-end analysis.

Figure 2: HBAT 2 analysis workflow showing the complete pipeline from PDB input to multiple output formats