Changelog

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Molecular Dynamics (MD)

• Upgraded MD engine to Revilico’s latest R&D version across all MD features.
• Added support for 4-point water models: TIP4P, OPC, and OPC3 for improved simulation accuracy.
• Expanded Ligand Membrane MD simulations with additional lipids and membrane systems for permeability analysis.
• Delivered performance optimizations resulting in faster MD simulation execution.

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Simulation Configuration

• Added UI components to configure solvents and solvent concentrations across MD workflows.
• Included ion concentration configuration to better resemble biological conditions.

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Analysis & Visualization

• Introduced RMSF plots and RMSF trajectory visualization tools with spatial fluctuation color mapping across protein surfaces.
• Enhanced Protein–Ligand MD analysis with detailed comparison tables including MM(PB/GB)SA, decomposition, and PCA insights for improved free energy estimation across trajectories.

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Models & Pipelines

• Updated Geometry Minimization and Thermochemistry Neural Network Potential (NNP) model weights.
• Added solvent configuration support to resemble physiological conditions.
• Synchronized Boltz Co-Folding and Virtual Screening Docking pipelines with Protein–Ligand MD input sequences.
• Standardized download file naming for improved analysis and seamless workflows.

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Retrosynthesis

• Upgraded Retrosynthesis Engine to the latest Revilico R&D version with architectural and performance improvements.

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Reliability & Operations

• Implemented automated Jira ticket creation on pipeline failures for improved incident tracking and operational visibility.
• New issues are automatically logged and triaged, enabling faster resolution within 24 hours.

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Docking & Pose Prediction

• Replaced classical empirical docking model with physics-based search algorithms powered by deep learning CNNs for more accurate poses and binding affinity calculations in Flexible and Ensemble Docking.
• Added the ability to extract receptor structures directly from Protein-in-Water MD simulations within defined timeframes and custom intervals for structural analysis across MD timescales.
• Introduced advanced configuration options to extract individual receptors at specific trajectory frame intervals for Ensemble Docking workflows.
• Enhanced Ensemble Docking workflows to allow grid box configuration across all trajectory structures.

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Visualization & UI

• Improved docking visualization UI to better identify and analyze binding sites and filter docking data effectively.

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Free Energy Calculations (Beta)

• Introduced ABFE and RBFE engines (Beta) enabling advanced alchemical transformations to compute ΔG binding of complexes.

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Platform & Architecture

• Implemented multiple stability enhancements across the platform.
• Implemented the Pharmacophore engine using Pritam Kumar Panda’s designs.
• Designed a new transcriptomic architecture for large-scale batch processing, improving scalability, reliability, and pipeline modularity for heavy workloads.

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Ligand Modeling

• Implemented ligand conformer search to generate low-energy 3D conformations, improving docking pose coverage and allowing chemists to evaluate energetic penalties across ligand–protein complexes.