ARIScience's novel in silico platform, BioTD, leverages the power of High-Performance Computing (HPC) to drive breakthroughs in drug discovery and development. With its ability to simulate complex biological systems and predict the behavior of small molecules, BioTD represents a revolutionary step forward in the field of computational drug design. Easily perform quantum chemistry-driven molecular optimization without the complexity of setting up in-house processes.
Discover areas of interest in organic molecules
Our algorithm automatically identifies areas of interest in organic molecules that could be used for active site or allosteric effects.
Align organic molecules
Automatically determine energy and coverage/distance favorable alignments of organic molecules to find the best candidate molecules for a target protein.
Our lightweight library renders molecules without the need for GPUs, making it versatile and accessible.
Identify charge distribution in organic molecules
Our algorithm identifies areas of interest in organic molecules due to charge distribution that could be used for active site or allosteric changes.
Insert H atoms
Analyze molecules and recommend favorable positions for missing H atoms in protein structures.
Provide similarity matches for both primary and sub-domains against a large library of publicly available molecular structures.
Determine vibrational, absorption, and emission frequencies
Our platform uses Density Functional Theory (DFT) to determine vibrational, absorption, and emission frequencies.
Identify functional groups
Identify a large number of common functional groups in organic molecules.
Identify symmetries in molecules
Automatically determine certain symmetries of organic molecules and protein structures.
Optimize molecular structures and energy
Easily perform Quantum Chemistry driven molecular optimization using published basis sets and Cartesian Gaussian Type Orbitals (CGTO) based Density Functional Theory routines without the complexity of setting up in-house processes.
Estimate pKa values
Estimate pKa values of hydrogens associated with certain organic functional groups and match simple and well-known molecules.
Identify sub-domains of organic molecules
Determine the sub-domains of organic molecules to provide insight into how the molecule was formed.