RESUMO
Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specificity and binding affinity. Despite their potential, optimizing antibodies for superior efficacy presents significant challenges in both monetary and time costs. Recent strides in computational and artificial intelligence (AI), especially generative diffusion models, have begun to address these challenges, offering novel approaches for antibody design. This review delves into specific diffusion-based generative methodologies tailored for antibody design tasks, de novo antibody design, and optimization of complementarity-determining region (CDR) loops, along with their evaluation metrics. We aim to provide an exhaustive overview of this burgeoning field, making it an essential resource for leveraging diffusion-based generative models in antibody design endeavors.
RESUMO
Phosphoglycerate kinase (Pgk), catalyzing the reversible conversions between glycerate-1.3-2P and glycerate-3P, plays an important role in carbohydrate metabolism. Here, we show that a Pgk-deficient mutant (NΔpgk) of Xanthomonas axonopodis pv. glycines (Xag) could grow in medium with glucose, galactose, fructose, mannose, or sucrose, as the sole carbon source, suggesting that Xag may employ Entner-Doudoroff (ED) and pentose phosphate pathway (PPP), but not glycolysis, to catabolize glucose. NΔpgk could not utilize pyruvate, suggesting that Pgk might be essential for gluconeogenesis. Mutation in pgk led to a reduction of extracellular polysaccharide (EPS) biosynthesis, cell motility, and intracellular ATP. As a result, the virulence of NΔpgk was significantly compromised in soybean. NΔpgk could be fully complemented by the wild-type pgk, but not by clp (encoding Crp-like protein). qRT-PCR analyses demonstrated that pgk is regulated by the HrpG/HrpX cascade, but not by Clp. These results suggest that Pgk is involved in carbohydrate utilization, EPS biosynthesis, and cell motility of Xag independent of Clp.