Small-Molecule Factor Xa Inhibitors: Translational SAR, Assay-Aware Data Quality, and QSAR-Readiness for...

Area of Science:

• Medicinal Chemistry
• Pharmacology
• Drug Discovery

Background:

• Factor Xa (FXa) is a validated anticoagulant target, with numerous small-molecule inhibitors developed.
• Existing literature on FXa inhibitors exhibits heterogeneity in scaffold design, data reporting, and assay consistency, hindering computer-aided drug design (CADD).

Purpose of the Study:

• To critically evaluate published small-molecule FXa inhibitor series using a framework assessing translational structure-activity relationships (SARs), data quality, and quantitative structure-activity relationship (QSAR)-readiness.
• To identify datasets suitable for CADD and reproducible SAR interpretation.

Main Methods:

• A structured narrative synthesis of post-2014 studies on small-molecule or semisynthetic FXa inhibitors.
• Classification of inhibitor series into fully synthetic or natural-product-derived chemotypes.
• Extraction and assessment of data including scaffold, potency, assay context, selectivity, translational data, and QSAR-readiness metrics (e.g., analog density, endpoint quality, structural interpretability).

Main Results:

• Fully synthetic chemotypes, especially anthranilamide derivatives, yielded the most coherent and modellable FXa datasets.
• Natural-product-derived and semisynthetic series contributed to structural diversity but often had limitations in data quality and completeness.
• Many series were hampered by small analog sets, inconsistent endpoints, and incomplete translational characterization, impacting their value for CADD.

Conclusions:

• The value of FXa inhibitor series depends on data quality and reconstructability for reliable SAR interpretation and CADD.
• A QSAR-readiness framework is crucial for triaging datasets, distinguishing those suitable for rigorous modeling from those better for qualitative analysis or hypothesis generation.
• Prioritizing datasets with high data integrity and translational context is essential for advancing FXa inhibitor drug discovery.