alvaDesc
alvaDesc is a cheminformatics software for the calculation and analysis of molecular descriptors, fingerprints, and structural patterns for QSAR, QSPR, read-across, and machine learning applications. It computes more than 5,000 molecular descriptors (0D–3D), including constitutional, topological, geometrical, electronic, physicochemical, and fragment-based descriptors.
The software also generates molecular fingerprints and structural pattern counts for similarity analysis, clustering, and classification. Integrated tools support descriptor filtering and correlation analysis for robust and reproducible modeling.
alvaDesc integrates seamlessly with KNIME and Python, enabling efficient connection to external data analysis and machine learning workflows. It is widely used in academic and industrial research and supported by extensive documentation and scientific publications.
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alvaBuilder
alvaBuilder is a no-code de novo molecular design software for generating novel chemical structures that satisfy user-defined structural, physicochemical, and modeling constraints. It enables the creation of new molecules starting from scratch or by evolving existing structures using fragment-based and rule-driven approaches.
alvaBuilder integrates seamlessly with QSAR/QSPR workflows, allowing users to guide molecule generation using predictive models, descriptor ranges, and property targets. The software supports medicinal chemistry, lead optimization, and virtual screening tasks by efficiently exploring chemical space while maintaining chemical feasibility and interpretability.
alvaBuilder is designed for research and industrial applications where transparent, controllable, and reproducible molecular generation is required.
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alvaMolecule
alvaMolecule is a no-code cheminformatics tool for visualizing, curating, and standardizing molecular datasets before analysis. It supports common molecular formats (SMILES, SDF/MOL2) and lets users explore collections in grid or spreadsheet views, with automatic import of associated data. The software provides structure verification and standardization using predefined standardizers and custom SMIRKS rules, helps detect and manage duplicates, and offers scaffold analysis to summarize core frameworks.
Built-in filters and charting tools enable sorting by substructure, calculated molecular descriptors, and physicochemical properties. alvaMolecule calculates ~88 structural and physicochemical properties, including drug-like and lead-like scores such as LogP, TPSA, and the Lipinski alert index, helping prepare high-quality datasets for QSAR/QSPR modeling, descriptor calculation, and virtual screening workflows.
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Schrödinger
Transform drug discovery and materials research with advanced molecular modeling. Our physics-based computational platform integrates differentiated solutions for predictive modeling, data analytics, and collaboration to enable rapid exploration of chemical space. Our platform is deployed by industry leaders worldwide for drug discovery, as well as for materials science in fields as diverse as aerospace, energy, semiconductors, and electronics displays. The platform powers our own drug discovery efforts, from target identification to hit discovery to lead optimization. It also drives our research collaborations to develop novel medicines for critical public health needs. With more than 150 Ph.D. scientists on our team, we invest heavily in R&D. We’ve published over 400 peer-reviewed papers that demonstrate the strength of our physics-based approaches, and we’re continually pushing the limits of computer modeling.
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