FSM06-1P1G-CABL-ACTD-FixLevel-Reg-EnzBased-Wt-Rxn-Case1.gms is a NHDE solver using one group individual to identify optimal anticancer enzymes. from Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer

Computer-aided methods can be used to screen potential candidate targets and to reduce the time and cost of drug development. In most of these methods, synthetic lethality is used as a therapeutic criterion to identify drug targets. However, these methods do not consider the side effects during the identification stage. This study developed a fuzzy multi-objective optimization for identifying anti-cancer targets that not only evaluated cancer cell mortality, but also minimized side effects due to treatment. We identified potential anti-cancer enzymes and antimetabolites for the treatment of head and neck cancer (HNC). The identified one- and two-target enzymes were primarily involved in six major pathways, namely, purine and pyrimidine metabolism and the pentose phosphate pathway. Most of the identified targets can be regulated by approved drugs; thus, these drugs are potential candidates for drug repurposing as a treatment for HNC. Furthermore, we identified antimetabolites involved in pathways similar to those identified using a gene-centric approach. Moreover, HMGCR knockdown could not block the growth of HNC cells. However, the two-target combinations of UMPS, HMGCR) and (CAD, HMGCR) could achieve cell mortality and improve metabolic deviation grades over 22% without reducing the cell viability grade.

计算机辅助方法可用于筛选潜在候选靶点，同时缩短药物研发周期、降低研发成本。此类方法大多以合成致死（synthetic lethality）作为治疗判定标准来筛选药物靶点。然而，此类方法在靶点识别阶段并未考量治疗相关的副作用。本研究构建了一种用于筛选抗癌靶点的模糊多目标优化模型，该模型不仅能够评估癌细胞致死率，还可将治疗引发的副作用降至最低。本研究筛选出了可用于治疗头颈部癌（HNC）的潜在抗癌酶类与抗代谢物。经筛选得到的单靶点与双靶点酶类主要参与六大核心通路，包括嘌呤代谢、嘧啶代谢以及磷酸戊糖途径。多数已筛选出的靶点可被已获批药物调控，因此这些药物可作为头颈部癌治疗的潜在药物重定位候选方案。此外，本研究筛选出的抗代谢物所参与的通路，与采用以基因为中心的研究方法得到的通路高度相似。此外，HMGCR基因敲除无法抑制头颈部癌细胞的增殖。但UMPS与HMGCR、CAD与HMGCR这两组双靶点组合，可在不降低细胞活力等级的前提下，使癌细胞致死率与代谢偏差等级均提升22%以上。