Core Technology

Divamics is an algorithm that efficiently generates precise results using AI algorithms and self-correction, all based on physical models.

Striking the right balance between computational accuracy and efficiency

Understanding how the target conformation changes when binding with a drug molecule is a crucial aspect of molecular pharmacodynamics, in addition to identifying the conformation features and binding site of the target.

Divamics uses multi-scale molecular dynamics to thoroughly simulate the conformational features and motion modes of biological macromolecules in a physiological environment. Starting from the first principles, we greatly improve the accuracy of our force field by combining quantum mechanics, Newtonian mechanics and machine learning. Meanwhile, we developed our parallel sampling algorithms based on the Monte Carlo method. Together with other enhanced sampling methods such as Gaussian dynamics, meta-dynamics, and exchange-copy dynamics, the efficiency of our simulation can also be enhanced.

The above-mentioned technics enable Divamics Inc. to evaluate the ligand-target binding on a dual scale of thermodynamics and kinetics, and to provide more comprehensive information for new drug development

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