Our Solutions at a Glance

Our portfolio covers the full research lifecycle — from molecular design and screening to data management and regulatory compliance.

Discovery & Design

Accelerate molecular design, screening, and optimization.

• Molecular Modelling & Virtual Screening
  Simulate ligand–receptor interactions, perform docking, and identify novel leads.

• Medicinal & Computational Chemistry
  Build QSAR models, predict physicochemical properties, and support structure–activity analysis.

• Virtual Library Generation & Enumeration
  Design and screen diverse compound libraries for hit identification.

• Bioinformatics & Homology Modelling
  Explore protein structures and biological targets to guide structure-based design.

Data & Knowledge Management

Organize, analyze, and retrieve scientific data with accuracy.

• Chemoinformatics & Data Management
  Register compounds, calculate properties, and visualize large datasets.

• Chemical Drawing & Reaction Design
  Draw and manage chemical structures, reactions, and Markush representations.

• Chemical Structure Standardization and Cleaning
  Clean and standardize your data for AI/ML workflows and storage in databases

• LIMS, ELN & Laboratory Informatics
  Digitize lab workflows and ensure secure, traceable experimental data management.

AI/ML based solutions

Empowering discovery, design, and data interpretation through artificial intelligence and machine learning.

• AI-Driven Lead Identification
  MolSoft’s MolScreen — a suite of 2D/3D AI/ML models across 1,000+ targets — predicts activity, selectivity, and toxicity for faster hit-to-lead decisions. → Accelerates early research with predictive analytics.
• Generative Molecule Design
  ChemPass AI uses deep learning to design novel, synthesizable molecules. It explores billions of compounds to identify those most likely to bind or modulate a target. → Transforms ideation into intelligent structure generation.
• Deep Learning for Ultra-Large Virtual Screening
  The GigaScreen method merges ML and deep-learning tools to screen ~1 billion compounds in just 2 days on a single RTX 4090 GPU. → Enables high-speed discovery at massive scale.
• RTCNN for Ligand Scoring
  MolSoft’s RTCNN applies graph-convolutional neural networks to capture both 2D (topological) and 3D (radial) atomic interactions for accurate ligand–receptor binding predictions. → Improves scoring precision in virtual screening.