ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery

All of the individual docking data and ESSENCE-Dock consensus results for 21 diverse DUD-E targets as presented in the paper "ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery". The data is sorted per DUD-E target. It contains the prepared data that was used for the docking calculations (in the Undocked directory), as well as our docking results. Finally, our ESSENCE-Dock Consensus results are included as well Docking calculations were performed using: Metascreener (V1.1) (Gnina and LeadFinder Calculations; prefix VS_GN_ and VS_LF_ respectively) DiffDockHPC (v1.0) (DiffDock calculations; prefix VS_DD_ ) The consensus calculations were performed using ESSENCE-Dock, available via Metascreener as well. The whole methodology and all of the details are described in the ESSENCE-Dock paper: https://doi.org/10.1021/acs.jcim.3c01982 Paper Abstract Drug development is a complex, costly, and time-consuming endeavor. While high-throughput screening (HTS) plays a critical role in the discovery stage, it is one of many factors contributing to these challenges. In certain contexts, virtual screening can complement HTS, potentially offering a more streamlined approach in the initial stages of drug discovery. Molecular docking is an example of a popular virtual screening technique that is often used for this purpose, however, its effectiveness can vary greatly. This has led to the use of consensus docking approaches, which combine results from different docking methods to improve the identification of active compounds and reduce the occurrence of false positives. However, many of these methods do not fully leverage the latest advancements in molecular docking.In response, we present ESSENCE-Dock (Effective Structural Screening ENrichment ConsEnsus Dock), a new consensus docking workflow aimed at decreasing false positives and increasing the discovery of active compounds. By utilizing a combination of novel docking algorithms, we improve the selection process for potential active compounds. ESSENCE-Dock has been made to be user-friendly, requiring only a few simple commands to perform a complete screening, while also being designed for use in high-performance computing (HPC) environments.本数据集涵盖论文《ESSENCE-Dock：一种基于共识的方法以提升药物发现中的虚拟筛选富集能力》中所呈现的、针对21个多样化DUD-E靶点的全部单个体对接数据与ESSENCE-Dock共识分析结果。 数据集按DUD-E靶点进行分类，包含用于对接计算的预处理数据（存放于Undocked目录中）、本研究的对接结果，同时亦包含ESSENCE-Dock共识分析结果。 本次对接计算采用以下工具： 1. Metascreener（V1.1）：支持Gnina与LeadFinder计算，对应结果前缀分别为VS_GN_与VS_LF_； 2. DiffDockHPC（v1.0）：用于DiffDock计算，对应结果前缀为VS_DD_。 共识分析采用ESSENCE-Dock工具完成，该工具同样可通过Metascreener调用。 完整的研究方法与所有细节可参阅该ESSENCE-Dock相关论文：https://doi.org/10.1021/acs.jcim.3c01982。 论文摘要 药物研发是一项兼具复杂性、高成本与长周期的系统工程。尽管高通量筛选（HTS, High-Throughput Screening）在药物发现阶段占据核心地位，但它亦是加剧研发困境的诸多因素之一。在部分应用场景中，虚拟筛选可作为高通量筛选的有效补充，有望为药物发现的早期阶段提供更为精简高效的研发路径。分子对接作为当前主流的虚拟筛选技术之一，被广泛应用于该场景，但其实际效能存在显著差异。为此，学界提出了共识对接策略，即整合多种对接方法的结果以提升活性化合物的识别精度，减少假阳性结果的产生。然而，现有多数此类策略未能充分利用分子对接领域的最新研究进展。 针对上述问题，本研究提出ESSENCE-Dock（全称Effective Structural Screening ENrichment ConsEnsus Dock，有效结构筛选富集共识对接），一种全新的共识对接工作流，旨在降低假阳性结果占比，提升活性化合物的发现效率。通过融合多种新型对接算法，本研究优化了潜在活性化合物的筛选流程。ESSENCE-Dock兼具易用性与高性能计算（HPC, High-Performance Computing）环境适配性：仅需少量简单命令即可完成完整的筛选流程，同时可完美适配高性能计算集群环境。