An important first step in the development of a small molecule drug is to screen large libraries of drug-like molecules against a given protein target, either experimentally or computationally.
These computational screening methods are poised to significantly and rapidly improve in coming years thanks to leaps in computational power, dramatic expansion of the accessible chemistry space, improvements of physics-based methods/force fields and maturation of deep learning.
CACHE will reveal the most efficient computational methods for hit-finding and guide future technological improvement.
CACHE builds on the power of crowd sourcing by attracting funding from industry, governments and foundations to support its infrastructure. In addition, challenge-specific funding mechanisms will give disease-focused funders the opportunity to recruit community-wide efforts to proteins of their interest.
An ancillary and valuable benefit of CACHE will be to discover ligands for new protein targets and thereby expand the open science paradigm for drug discovery.