Real high standards of research data mining, integration, and evolution.

Drug Discovery Pro came to the researcher’s life to help them achieve their goals efficiently and successfully without waiving the high quality.

Our Vision
Our Mission
All the drug discovery services conducted inside drug discovery pro-enterprise are dry services that involve using advanced computational tools for data calculations, data mining, compound designing, similarity scoring, structure diversity analysis, and chemical accessibility. Mega and Giga docking of chemical space for drug repurposing and identifying unique chemical entities to work against specific protein targets besides the molecular dynamics simulation are prominent strategies for lead identification, which have recently entered the drug discovery pro services. Pocket finder and protein druggability services of new protein targets are possible to be assessed upon request.

Commercial sources of starting materials for drug synthesis is important for those directed for industry.

Dynamism of protein structure is a crucial factor in determining the binding stability of drug-receptor complex.

It is the path for thousands times shorter distance to drug discovery.

Finding a new druggable pockets is a requirement for discovering innovative chemical entities of drugs.

Protein molecule is intricate structure and it is hard to target for the first time without exploring the druggability.

Mega and Giga docking is a new entry of computational tools for drug repurposing and target fishing.

How we pursue perfection

Problem solving

Some of the partners & clients we’ve worked with

Thoth Biosimulations Inc. provides various computational drug discovery services. This includes but not limited to setting up, running and analyzing all types of molecular dynamics simulations (e.g. classical all atom, coarse-grained, QM-MM) to study protein-drug interaction, protein-protein interactions and protein-DNA/RNA interactions and to predict their binding affinities. Services also include developing bioinformatics and data-driven machine learning models to predict drug off-target interactions, physicochemical properties and target profiles for investigational small molecule drugs.