Now, a team of researchers from Presidency University Kolkata and the CSIR Indian Institute of Chemical Biology has taken a purely computational route to visualize one of these partnerships in atomic detail. Writing in Frontiers in Bioinformatics, Prakash Nandi, Izaz Monir Kamal, Saikat Chakrabarti and Sugopa Sengupta report a full-length three-dimensional model of yeast Top I and use it to predict, residue by residue, how the enzyme might dock onto Rpc82, a key subunit of RNA polymerase III. Their integrative pipeline—combining template-based structure modeling, molecular docking, molecular dynamics simulations and binding free-energy calculations—paints a plausible picture of a Top I–Rpc82 complex and delivers a testable blueprint for experiments that have never been possible before, largely because the enzyme itself had never been fully drawn.

The obstacle the team faced was structural, not conceptual. Two independent high-throughput studies in budding yeast, both using affinity chromatography followed by mass spectrometry, had already flagged a physical association between Top I and Rpc82, the largest subunit of the RNA polymerase III-specific trimer that also includes Rpc34 and Rpc31. Rpc82 is no bystander: it anchors to the clamp domain of the polymerase cleft, contacts duplex DNA downstream of the transcription bubble, and, through a disordered insertion in its third winged-helix (WH3) domain, engages the TFIIB-related factor Brf1 during pre-initiation complex assembly. Yet while the crystal structure of Rpc82 was available, Top I remained a 769-residue enigma. Only its DNA-binding domain had been resolved crystallographically, and even AlphaFold assigned very low confidence to the enzyme’s N-terminal region—the very region known to mediate protein–protein interactions with partners such as the RNA polymerase II subunit Rpb1 and the sirtuin Sir2.

The team’s answer was to model Top I piece by piece. They divided the protein into five segments: the N-terminal domain (D1, residues 1–142), the DNA-binding domain (D2, residues 143–363), the core domain (D3, residues 364–589), a linker region (D4, residues 590–698), and the C-terminal catalytic domain (D5, residues 699–769). Because the D2 crystal structure already existed, only the remaining four segments required prediction, and the researchers ran each through multiple engines—RoseTTAFold, I-TASSER, TrRosetta, ab initio modeling and DeepFold—rather than trusting any single algorithm. The best-scoring model for each domain was then validated against rigorous metrics: ERRAT scores above 95 percent, Verify3D values exceeding 85 percent, and Ramachandran plots showing more than 91 percent of residues in favored stereochemical regions.

Assembling the validated pieces with MODELLER produced a full-length model that held up remarkably well under scrutiny. The finished structure scored an ERRAT value of 93.43 percent, a Verify3D score of 86.35 percent, and placed 94.3 percent of residues in favored Ramachandran regions with only 0.1 percent in disallowed zones. When the team superimposed their model onto the crystal structure of human topoisomerase I—its closest structural relative, sharing 51.69 percent sequence identity—the overall root-mean-square deviation was just 1.021 angstroms, comfortably within the threshold considered indicative of an accurate model. Superimposition onto the AlphaFold prediction yielded an even tighter 0.7-angstrom agreement for the D2–D5 regions, and crucially, the new model reproduced a single alpha-helix in the N-terminal domain (residues 105–125) that AlphaFold had faintly glimpsed but could not resolve. Benchmarking against dozens of high-resolution eukaryotic crystal structures of comparable length confirmed that every quality metric sat within, and often above, reference ranges.

With a trustworthy Top I in hand, the docking question could finally be asked. The researchers ran blind docking using three independent servers—ClusPro, HDOCK and HADDOCK—followed by targeted docking in which the residues of Rpc82 already committed to binding Rpc34 and Rpc160 were masked, so that only surfaces genuinely accessible inside the living polymerase holoenzyme would be considered. Both strategies converged on the same answer: Top I preferentially engages the WH2–WH3 region of Rpc82, a peripheral patch of the protein that remains spatially free even within the assembled polymerase. The alternative surface, spanning WH1, WH4 and the coiled-coil domain, was set aside because it is pre-occupied by core subunits during holoenzyme assembly and an interaction there would create steric clashes. From the Top I side, the predicted interface was built primarily from the D1 N-terminal domain and the D3 core domain, with minor contributions from D2. The most favorable pose carried a binding energy of −11.5 kilocalories per mole as calculated by PDBePISA, involving 39 intermolecular contacts.

Molecular dynamics then put the model through the equivalent of a 200-nanosecond stress test in water, run in triplicate with the GROMACS engine and the AMBER99SB force field. The simulated complex held together. Root-mean-square deviation values settled around 0.8–1.0 nanometers, the solvent-accessible surface area remained steady at roughly 780–800 square nanometers, and the radius of gyration hovered near 4.3 nanometers, signaling sustained compactness. The buried interface area grew from about 30 to roughly 40 square nanometers over the trajectory—an increase the authors interpret as progressive tightening of the association. Strikingly, the interface itself proved more rigid than the flanks: the D3-mediated contact zone fluctuated by only about 0.3 nanometers, while the D1 side retained more local flexibility, and the non-interacting WH4 and coiled-coil regions of Rpc82 wobbled far more than the binding surface. A rigid interface amid flexible surroundings is exactly what one expects of a genuine, evolutionarily tuned protein–protein contact.

The energetic accounting reinforced the story. MM-PBSA analysis across 400 trajectory snapshots showed the complex’s total energy stabilizing near −37,300 kilocalories per mole in the later simulation stages, while the binding free energy of the interacting patch drifted toward strongly negative values, reaching roughly −300 to −310 kilocalories per mole by the end of the run. The binding energy-to-surface-area ratio of the modeled complex also fell squarely within the range observed for well-characterized eukaryotic heterodimeric complexes resolved at 3 angstroms or better, a benchmarking exercise that helps separate biologically credible interfaces from computational artifacts. Certain residues emerged as persistent hotspots: on Top I, the acidic cluster D50, E51, E126, E127 and E128 in D1, together with Y385, K400, V401, L403, E424, E427, Q486, G488, H489, Q490, Y507 and P509 in D3; on Rpc82, residues including R145, D148, E149, Y185, R368, H369 and H448 maintained contact for extended stretches. The team also observed transient secondary contact patches forming and dissolving over time, suggesting the complex may undergo adaptive rearrangements to preserve its grip under cellular conditions.

What would such a partnership be for? The functional logic is compelling. RNA polymerase III drives extraordinarily high levels of transcription of short genes—transfer RNAs, 5S ribosomal RNA and small nuclear RNAs—and recycles rapidly through repeated initiation cycles, generating intense local torsional strain. In budding yeast, loss of Top I has been shown to increase R-loop accumulation at heavily transcribed polymerase III loci, impairing elongation and pre-tRNA synthesis. A physical tether between Rpc82 and Top I would position the topoisomerase precisely where supercoils pile up, allowing it to relax DNA on demand and keep tRNA production flowing. The interaction would also echo established precedents: bacterial RNA polymerase’s beta-prime subunit contacts bacterial topoisomerase I, and Top I recruitment through RNA polymerase II stimulates relaxation activity during active transcription in flies and humans. Human topoisomerase I has even been reported to promote polymerase III reinitiation and termination through the TFIIIC factor complex.

The authors are careful to frame their results as a hypothesis rather than proof—the entire edifice rests on computation, and no wet-laboratory experiment has yet confirmed the interface. But the model now offers concrete targets for that confirmation: mutations of the identified hotspot residues could disrupt or preserve the interaction in vivo, providing a clean experimental test. Because both proteins are evolutionarily conserved, a comparable Top I–polymerase III interface may exist in human cells, where polymerase III transcription is frequently dysregulated in cancer. If future work validates the contact, the interface could represent a regulatory node—and, in disease contexts, a potential druggable one—linking the enzymes that read the genome with the enzymes that keep it from twisting itself apart.

Subject of Research: In silico prediction of the molecular interaction between yeast DNA topoisomerase I and the RNA polymerase III subunit Rpc82

Article Title: Exploring molecular interactions between yeast topoisomerase I and RNA polymerase III subunit, Rpc82 using an in-silico approach

Article References: Nandi, P., Kamal, I. M., Chakrabarti, S., & Sengupta, S. (2026). Exploring molecular interactions between yeast topoisomerase I and RNA polymerase III subunit, Rpc82 using an in-silico approach. Frontiers in Bioinformatics, 6, Article 1897635. https://doi.org/10.3389/fbinf.2026.1897635

Image Credits: AI Generated

DOI: 10.3389/fbinf.2026.1897635

Keywords: topoisomerase I, RNA polymerase III, Rpc82, Saccharomyces cerevisiae, protein-protein interaction, molecular docking, molecular dynamics simulation, binding free energy, DNA supercoiling, transcription, structural modeling, genome stability