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The study evaluated the full TASC-VS package on a curated 15-target subset of the LIT-PCBA benchmark. TASC-VS integrates test-time adaptation, calibration, and uncertainty-aware ranking to support fixed-budget decisions. Results showed modest, directionally consistent improvements versus evaluated comparators, with calibration improving reliability and uncertainty penalization yielding small top-20 benefits. 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PLoSOne 21(8): e0356482. [https://doi.org/10.1371/](https://doi.org/10.1371/)[ ](https://doi.org/10.1371/)[journal.pone.0356482](journal.pone.0356482)  \nEditor: Soumendranath Bhakat, AlloTec Bio,  \nUNITED STATES OF AMERICA Received: April 9, 2026  \nAccepted: August 4, 2026  \nPublished: August 19, 2026  \nCopyright: © 2026 Zou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData availability statement: LIT-PCBA benchmark dataset, from the official public LIT-PCBA benchmark resource, accessible via [https://doi](https://doi). org/10.1021/acs.jcim.0c00155 .  \nFunding: This study was supported by the Changsha Municipal Natural Science Foundation (grant no. kq2502148) . The award recipient is not an author of this manuscript.  \nRESEARCH ARTICLE  \nFrom ranking to decision: TASC-VS for calibration-aware top-k virtual screening  \nLisha Zou, Shiyu Tian*, Zhipiao Tang, Keyi Zou  \nHunan University of Information Technology, Changsha, Hunan, China  \n* [pegasus.zodiacz@gmail.com](pegasus.zodiacz@gmail.com)  \nAbstract  \nVirtual screening is most useful when it improves top-k prioritization under lim  \nited experimental budgets. We evaluated the full TASC-VS package on a curated 15-target subset of the LIT-PCBA virtual-screening benchmark. Methodologically, TASC-VS combines test-time adaptation (TTA), calibration, and uncertainty-aware ranking to support fixed-budget decisions. Coverage analysis showed that the subset is not full LIT-PCBA: it contains 23,250 evaluated molecule-target records and 181 positives, with positives in seven targets. Empirically, TASC-VS full showed modest, directionally consistent benefits over the evaluated comparators. On the seven positive targets, normalized enrichment factor at 1%(NEF1) and Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) were 0.052 and 0.062 for TASC-VS full, compared with 0.0057 and 0.0279 for RTMScore-on-Vina-poses. Across all 15 targets, precision and false-positive count among the top 20 candidates (P20 and FP20) were 0.0433 and 19.13 for TASC-VS full, compared with 0.0067 and 19.87 for RTMScore-on-Vina-poses. Calibration improved reliability metrics, uncertainty penalization produced a small top-20 benefit, and TTA changed reliability slightly without driving the main ranking gain. Paired P20 analysis versus RTMScoreon-Vina-poses gave a mean benefit of 0.0367 (95% bootstrap confidence interval (CI), 0.0067–0.0733; raw Wilcoxon p = 0.026), but multiplicity-corrected values were not significant (Holm p = 1.0; Benjamini–Hochberg (BH) q = 0.322) . An external Directory of Useful Decoys, Enhanced (DUD-E) stress test favored Vina over TASC-VS full. Thus, TASC-VS full provides calibration-aware top-k decision support on the curated LIT-PCBA subset; broader deployment requires separate validation.  \nIntroduction  \nIn early-stage drug discovery, virtual screening is widely used to prioritize potentially bioactive compounds from large chemical libraries [ 1 ,2] . Its true value lies not merely in improving overall scoring performance or global ranking correlation, but in determining whether the most promising candidates can be placed reliably at the top of the  \nPLOS One | [https://doi.org/10.1371/journal.pone.0356482](https://doi.org/10.1371/journal.pone.0356482) August 19, 2026 1 / 18  \nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  \nCompeting interests: No authors have competing interests.  \nlist when experimental validation resources are limited. In recent years, as screenable chemical space has continued to expand, structure-based screening workflows ","cbCaihXLCz84eU9z","https://ap.wps.com/l/cbCaihXLCz84eU9z","pdf",1046894,18,"English","# Abstract\n## Introduction\n## Methods and evaluation\n## Results and analysis\n## Conclusion","[{\"question\":\"What problem does the study address in virtual screening?\",\"answer\":\"It examines whether a complete virtual-screening package can provide reproducible, calibration-aware top-k decision advantage under a fixed-budget validation setting.\"},{\"question\":\"What components are included in TASC-VS?\",\"answer\":\"TASC-VS combines test-time adaptation (TTA), calibration, and uncertainty-aware ranking to support fixed-budget top-k decisions.\"},{\"question\":\"How did TASC-VS full perform compared with the evaluated comparators?\",\"answer\":\"The paper reports modest, directionally consistent benefits for TASC-VS full across the curated subset, including improvements on precision/false-positive metrics within the top 20 candidates.\"}]","From ranking to decision - TASC-VS for calibration-aware top-k virtual screening | PDF",1789402681,45]