This cover article for the October 2022 issue of the Journal of Chemical Information and Modeling (JCIM) provides an in-depth look at the results of a three-way collaboration between Divamics' technical team, Wuhan University of Technology, And QuantumBio Inc., an US computer-based drug design software company. The paper was co-authored by Wenlang Liu, Zhenhao Liu, Hao Liu, Lance M. Westerhoff and Zheng Zheng.

Through long-term collaboration, Divamics and QuantumBio have continued to develop MovableType (MT) binding free energy algorithms,  introducing various sampling methods such as induced fit molecular docking, long-time molecular dynamics simulation, and Monte Carlo coupled with multi-trajectory molecular dynamics simulation into the simulation of the binding free energy between the target and the drug-like compound. 

Divamics’ drug discovery platform is able to strike the right balance between speed and accuracy in various drug developing scenarios, and provides diverse DBDD solutions for new drug developers when dealing with targets with different conformational features.  When combining the MT algorithm with multi-scale dynamics simulation and sampling, we can expand the application of free energy simulation universally to more complexes between targets and drug-like compounds. 

The MovableType algorithm software suite is currently widely used by many pharmaceutical companies around the world. "Since we launched MovableType over the past two years, we have explored a number of cases with our customers where Our algorithms have delivered significant value to our customers," said Dr Westerhoff, President and General Manager of QuantumBio.

· Original link:

https://pubs.acs.org/doi/10.1021/acs.jcim.2c00278

· Please indicate when quoting this article:

J. Chem. Inf. Model. 2022, 62, 5645−5665