software · Zenodo (CERN European Organization for Nuclear Research)
A reproducible computational workflow prioritises covalent natural-product candidates targeting the enzymes falcipain-2 and falcipain-3. The screening pipeline combines Michael-acceptor filtering, dual recognition, covalent docking, molecular mechanics generalised Born surface area calculations, and density functional theory reactivity analyses using multiple descriptors. The released package contains a warhead-filtering cascade, retrospective enrichment benchmarks featuring property-matched and warhead-matched decoy controls, and bootstrap confidence intervals. It also provides robustness assessments covering docking-box dimensions and recognition ablation, alongside evaluations of pH sensitivity. Additional resources within the workflow include the OPT1 covalent cascade, comprehensive density functional theory reactivity data with population-scheme and basis-set cross-checks, three-dimensional covalent pose coordinates, regression test suites, and validation checksums.
Evaluating covalent chemical interactions computationally requires rigorous validation across multiple physical and chemical parameters. By establishing a standardised in silico workflow that connects warhead filtering, covalent docking, and quantum-chemical reactivity analyses, this package enables researchers to consistently assess and prioritise natural products against falcipain-2 and falcipain-3 using fully cross-checked benchmarking protocols.
This workflow serves early-stage computational drug discovery teams seeking to shortlist covalent inhibitors against falcipain-2 and falcipain-3. Because the package is entirely in silico, it sits at the initial research and discovery phase, far from clinical testing or commercial production. Pharmaceutical companies and biotechnology researchers could integrate the automated filtering cascades, DFT reactivity data, and docking protocols into their virtual screening pipelines prior to physical chemical synthesis and laboratory assays.
AI-generated from the published abstract. Always read the original work before citing.
Reproducible in silico workflow for prioritizing covalent natural-product candidates against falcipain-2 and falcipain-3: Michael-acceptor filtering, dual recognition and covalent docking, MM-GBSA, and a multi-descriptor DFT reactivity analysis. The package includes the warhead-filtering cascade, retrospective enrichment benchmarks for falcipain-2 and falcipain-3 (property-matched and warhead-matched decoy controls, bootstrap confidence intervals), docking-box and recognition-ablation robustness checks, pH sensitivity, the OPT1 covalent cascade, DFT reactivity data with population-scheme, basis-set, and ΔSCF cross-checks, covalent pose coordinates, regression tests, and checksums.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.5281/zenodo.22254130
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
