Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America.
UC Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, California, United States of America.
PLoS Comput Biol. 2021 Nov 22;17(11):e1009620. doi: 10.1371/journal.pcbi.1009620. eCollection 2021 Nov.
A major challenge in designing proteins de novo to bind user-defined ligands with high affinity is finding backbones structures into which a new binding site geometry can be engineered with high precision. Recent advances in methods to generate protein fold families de novo have expanded the space of accessible protein structures, but it is not clear to what extend de novo proteins with diverse geometries also expand the space of designable ligand binding functions. We constructed a library of 25,806 high-quality ligand binding sites and developed a fast protocol to place ("match") these binding sites into both naturally occurring and de novo protein families with two fold topologies: Rossman and NTF2. Each matching step involves engineering new binding site residues into each protein "scaffold", which is distinct from the problem of comparing already existing binding pockets. 5,896 and 7,475 binding sites could be matched to the Rossmann and NTF2 fold families, respectively. De novo designed Rossman and NTF2 protein families can support 1,791 and 678 binding sites that cannot be matched to naturally existing structures with the same topologies, respectively. While the number of protein residues in ligand binding sites is the major determinant of matching success, ligand size and primary sequence separation of binding site residues also play important roles. The number of matched binding sites are power law functions of the number of members in a fold family. Our results suggest that de novo sampling of geometric variations on diverse fold topologies can significantly expand the space of designable ligand binding sites for a wealth of possible new protein functions.
从头设计能够与用户定义的配体高亲和力结合的蛋白质的主要挑战是找到骨架结构，可以高精度地设计新的结合位点几何形状。最近在从头生成蛋白质折叠家族的方法方面取得的进展扩大了可访问的蛋白质结构空间，但尚不清楚具有不同几何形状的从头蛋白质是否也扩展了可设计的配体结合功能的空间。我们构建了一个包含 25806 个高质量配体结合位点的文库，并开发了一种快速协议，将这些结合位点（“匹配”）放置到具有两种折叠拓扑结构（罗斯曼和 NTF2）的天然和从头蛋白质家族中。每个匹配步骤都涉及到在每个蛋白质“支架”中设计新的结合位点残基，这与比较已经存在的结合口袋的问题不同。分别有 5896 和 7475 个结合位点可以匹配到罗斯曼和 NTF2 折叠家族。从头设计的罗斯曼和 NTF2 蛋白质家族可以支持分别与具有相同拓扑结构的天然存在结构不匹配的 1791 和 678 个结合位点。虽然配体结合位点中的蛋白质残基数量是匹配成功的主要决定因素，但配体大小和结合位点残基的一级序列分离也起着重要作用。匹配的结合位点数量与折叠家族成员数量呈幂律关系。我们的结果表明，对不同折叠拓扑结构的几何变化进行从头采样可以显著扩展可设计的配体结合位点的空间，为大量可能的新蛋白质功能提供了更多选择。
