• Dominant theme involves constructing and comparing computational energy landscapes for polynucleotides via steric models, virtual bonds, and torsional energies to determine conformational preferences and dimensions [2], [1], [4].

• A second recurring pattern uses ab initio, Hartree–Fock, and semi-empirical quantum-chemical approaches to quantify barriers and nonbonded interactions in nucleotide units and related molecules, enabling energy-based conformational predictions [3], [7], [8].

• Intramolecular energy maps and backbone torsion energy analyses for polynucleotides reveal energy surfaces and potential functions, enabling systematic comparison with experiments and guiding structure prediction [13], [7], [8].

• Protein-focused work emphasizes local interactions, nearest-neighbor effects, and dipeptide energetics as determinants of secondary structure and backbone topology in known proteins [9], [14], [6].

• Theoretical frameworks for parameter estimation, kinetics, and binding analyses provide general methods to extract kinetic constants and model conformational transitions from experimental data in biomolecules [11], [12], [15], [19].

• Energy-transfer and angular-momentum formalisms are applied to understand conformational dynamics and reactive encounters in biomolecular systems, illustrating cross-domain methodological transfer [10], [16], [18].