ROSHAMBO2: Accelerating Molecular Alignment for Large Chemical Libraries with GPU Optimization and Algorithmic Advances

Molecular alignment and 3D similarity are crucial tasks
in computational
drug discovery, enabling applications such as virtual screening and
pharmacophore modeling. ROSHAMBO, an open-source package for optimizing
molecular alignment using Gaussian volume overlaps, demonstrated near-state-of-the-art
performance and accuracy across multiple target classes. However,
its computational efficiency has been a limiting factor in the virtual
screening of ultralarge chemical libraries. To address this limitation,
we introduce ROSHMABO2, an optimized version that achieves a greater
than 200-fold improvement in performance over the original ROSHAMBO
implementation through algorithmic innovations, GPU acceleration,
and optimized memory handling. This performance establishes ROSHMABO2
as an ideal tool for high-throughput applications, such as virtual
screening and chemical library design, enabling efficient exploration
of large chemical spaces. In addition to its computational enhancements,
the new version retains its modularity, accessibility, and compatibility
with diverse workflows. These improvements position ROSHAMBO2 as a
transformative tool for modern cheminformatics, addressing the growing
demands for scalable molecular modeling. ROSHAMBO2 is accessible at https://github.com/molecularinformatics/roshambo2 and is available for use under the MIT license.