Successful protein design is complicated by the "sequence space problem", where the majority of sequences that occur have no function, and those that do, inhabit the sequence space in small clusters separated by vast areas of non-functional proteins.
Evolutionary molecular engineering, which mimics natural Darwinian evolution in the confines of the laboratory, is a powerful advancement in the creation of functional proteins. Today, it has become an indispensable technology in the development of biologics as represented by antibody drugs, and protein-based drugs have become a key therapeutic approach in addressing many critically unmet needs in fighting disease. However, even with the latest advances in evolutionary molecular engineering, many challenges still exist in the ability to fully analyze the nearly infinite protein sequence space. As a result, there are many missed opportunities, and creating functional proteins is still a high-risk endeavor.
Out of this gap in the current state of the art, RevolKa was founded to address and find a solution to these challenges. Founded and led by experts in the field of protein engineering and drug development, RevolKa's team has developed an innovative and novel AI-based search technology to investigate the unexplored "frontier", that area of sequence space array that cannot be reached by current technology.
RevolKa's technology, named Library Design Cycle, can quickly create a comprehensive map of the vast sequence space array by combining evolutionary molecular engineering that imitates natural selection in vitro with artificial intelligence and machine learning in silico. And through cycles of in silico calculations and in vitro experimentation, Library Design Cycle rapidly interrogates the sequence space array until the protein with the desired functionality is found. In this way, RevolKa's goal is to find and explore undiscovered protein frontiers.
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