HBAT 2: A Python Package to analyse Hydrogen Bonds and Other Non-covalent Interactions in Macromolecular Structures

HBAT 2: A Python Package to analyse Hydrogen Bonds and Other Non-covalent Interactions in Macromolecular Structures Abhishek Tiwari1* 1Independent Researcher * [email protected] 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 hydrogen bonds and other non-covalent interactions are essential for understanding molecular interactions, protein folding, and drug design. HBAT (Hydrogen Bond Analysis Tool) is a widely used software for analysing hydrogen bonds and other weak interactions in macromolecular structures. In this paper, we present HBAT 2, an updated Python reimplementation of the original HBAT tool. DOI 10.5281/zenodo.17645321 Published 2025-11-18 Software •Code Repository •Documentation •PyPI Package 1 Summary 1 HBAT 2 is a Python package for automated analysis of hydrogen bonds and other 2 non-covalent interactions in macromolecular structures, available in Protein Data Bank 3 (PDB) file format. Originally developed in Perl/Tk and published in 2007 [1], HBAT 2 4 has been completely rewritten in Python. The software identifies and analyses 5 traditional hydrogen bonds, weak hydrogen bonds, halogen bonds, X-H· · ·π, and π-π6 stacking, and n→π* interactions using geometric criteria. It also detects cooperativity 7 and anticooperativity chains and renders them as 2D visualisations. The latest version 8 of HBAT offers improved cross-platform tkinter -based graphical user interface (GUI), a 9 simple command-line interface (CLI), and a developer-friendly API making it accessible 10 to users with different computational backgrounds and needs. 11 2 Statement of need 12 Hydrogen bonds and other non-covalent interactions are fundamental to protein 13 structure, stability, and function. With over 200,000 structures in the Protein Data 14 Bank [2], there is an increasing need for automated tools to analyse these interactions 15 systematically. 16 The landscape of hydrogen bond analysis tools is diverse but fragmented. Classic 17 tools like HBPLUS [3] and HBexplore [4] pioneered automated H-bond detection but 18 lack modern interfaces and support for a diverse range of interactions. More recent tools 19 serve specialized niches: PLIP [5] and Arpeggio [6] excel at protein-ligand interactions 20 but are web-based without standalone GUI options; HBonanza [7], HBCalculator [8],21 1/6 and BRIDGE2 [9] focus on molecular dynamics trajectories rather than static 22 structures; MDAnalysis [10], GROMACS [11], and AMBER [12] provide H-bond 23 analysis within larger MD suites. Tools like VMD [13] and ChimeraX [14] offer 24 interactive hydrogen bond visualisation but limited statistical analysis. ProteinTools 25 [15] provides web-based network analysis but lacks cross-platform desktop capabilities. 26 Despite this ecosystem, there remains a gap for a comprehensive and reliable 27 cross-platform desktop tool that: (1) analyses diverse interaction types beyond 28 canonical hydrogen bonds, (2) provides both graphical and command-line interfaces for 29 different user workflows, (3) identifies potential cooperativity, (4) integrates seamlessly 30 with the existing scientific ecosystem, and (5) supports flexible parameter customization 31 with domain-specific presets. 32 HBAT 2 addresses these limitations by providing a modern, Python implementation 33 that integrates seamlessly with contemporary structural biology workflows. The 34 software is particularly valuable for researchers in structural biology, computational 35 chemistry, and drug design who need detailed analysis of molecular interactions. 36 The original HBAT [1] was developed in Perl/Tk with a Windows-only GUI, limiting 37 its adoption in modern computational environments. This update addresses this 38 limitation by making HBAT 2 cross-platform with support for Windows, Linux, and 39 Mac. 40 Figure 1. The latest update to HBAT 2 uses tkinter to provide a cross-platform graphical user interface (GUI) 2/6 3 Key Enhancements 41 HBAT 2 introduces several key improvements over the original 2007 version: 42 3.1 Structure Preparation 43 HBAT 2 uses PDBFixer [16],[17] and OpenBabel [18] to automatically enhance 44 macromolecular structures by adding missing atoms, converting residues, and cleaning 45 up structural issues. These capabilities are particularly valuable when working with 46 crystal structures missing hydrogen atoms, low-resolution structures with incomplete 47 side chains, structures containing non-standard amino acid residues, and structures with 48 unwanted ligands or contaminants. This integration improves the quality of analysis. 49 3.2 Interaction Coverage 50 HBAT 2 analyses a broad spectrum of interactions including hydrogen bonds (O-H · · · O, 51 N-H· · ·O, N-H· · ·N, C-H···O), halogen bonds (C-X···Y where X=F,Cl,Br,I), X-H···π52 interactions with aromatic systems, π-πstacking [19],[20], carbonyl-carbonyl n→π*53 interactions [21],[22], and n→π* interactions [23]. This comprehensive approach 54 addresses the growing recognition of weak interactions’ importance in protein structure 55 and stability [24],[25],[26].56 3.3 Cooperativity Chains 57 HBAT 2 offers two ways to visualise hydrogen bond networks: NetworkX 58 [27]/Matplotlib [28] and GraphViz [29]. Unlike tools that provide only basic 59 visualisation (VMD, ChimeraX) or focus solely on MD trajectory dynamics (BRIDGE2, 60 HBonanza), HBAT 2 emphasises cooperativity chains and network topology in static 61 structures with customizable layouts and high-resolution export (PNG, SVG, PDF). 62 3.4 Parameter Presets 63 Built-in parameter sets optimised for different experimental conditions (high-resolution 64 X-ray, NMR, membrane proteins, drug design) address a common challenge in hydrogen 65 bond analysis. While other tools require manual parameter specification, HBAT’s preset 66 system makes it accessible to experimental structural biologists while maintaining 67 flexibility for computational experts. 68 3.5 Flexible Output 69 Multiple export formats (text, CSV, JSON) enable integration with downstream 70 analysis pipelines and statistical software. Combined with optional PDBFixer and 71 OpenBabel integration for automated hydrogen addition, HBAT 2 provides a complete 72 workflow from raw PDB files to publication-ready analyses. 73 4 Implementation 74 HBAT 2 employs a modular architecture with separate components for PDB parsing, 75 geometric analysis, statistical computation, and visualisation. The core analysis engine 76 uses efficient nearest-neighbor searching with configurable distance cutoffs, followed by 77 geometric filtering based on distance and angular criteria. 78 The software implements the same fundamental geometric approach as the original 79 version [1] but with optimised algorithms and improved handling. 80 3/6 Figure 2. An example visualisation of potential cooperativity chain generated by HBAT 2 software for Protein Data Bank (PDB) entry 6RSA 5 Impact and Applications 81 Since its original publication, HBAT has been cited in numerous studies of protein 82 structure and molecular recognition [1]. The latest update, however, extends this 83 impact by providing modern tools for structure-based drug design, protein engineering, 84 molecular dynamics analysis, crystallographic studies, and comparative structural 85 analysis. 86 The software’s preset configurations and flexible parameter system make it accessible 87 to both computational experts and experimental structural biologists, broadening its 88 potential user base compared to the original version. 89 6 Availability 90 HBAT 2 is freely available to download from GitHub and PyPI under the MIT license 91 with detailed user and API documentation. The software can be installed via PyPI 92 ( pip install hbat ) or via Conda ( conda install −c hbat hbat ), with optional GraphViz 93 integration for advanced visualization features. 94 7 Acknowledgements 95 The author thanks the original co-developer Sunil K. 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