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AI generated: Scientific infographic illustrating an AI-driven closed-loop framework for virtual molecular library...

Scientific infographic illustrating an AI-driven closed-loop framework for virtual molecular library construction, showing the adaptive cycle of “Representation – Generation – Prediction – Feedback”. Central theme: artificial intelligence empowering drug discovery and molecular design. The diagram is a circular workflow structure centered on the AI virtual molecular library system. Left module: Representation Learning, visualized with neural network icons, molecular graphs, protein structures, and amino acid sequence symbols, representing molecular and protein feature embeddings. Upper-right module: Molecular Generation, showing diffusion or VAE-like model generating diverse small molecules, arrows indicating exploration of chemical space, novelty, and synthesizability constraints. Lower-right module: Property Prediction, containing ADMET, activity, and selectivity metrics represented by radar charts or data panels, feeding results back to the representation module to close the loop. Bottom section: Evolution from virtual to drug-like molecular libraries, shown as a smooth gradient arrow with multi-objective optimization icons balancing drug-likeness and diversity. Right-side branch: Pretrained models for new target ligand design, divided into three submodules—small molecule pretraining, protein pretraining, and cross-modal pretraining (protein–ligand interaction)—depicting embedding fusion or contrastive learning in shared latent space. No human figures, only abstract scientific symbols and molecular visuals. Style: flat vector scientific infographic, modern and minimalistic, clear logical flow, smooth connections between modules. Color scheme: blue for AI and representation, orange-yellow for generation, green for prediction; background light gray or white. Typography: clean sans-serif labels, concise annotations. High resolution (≥600 dpi), suitable for journal publication, ultra-clear, balanced layout, professional academic tone.

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Nano Banana
AI generated: 画面分为三区:左(杀虫剂)、中(杀菌剂)、右(除草剂);
每区展示1–2个典型分子结构(线型骨架+立体构象简图):
杀虫剂:吡虫啉(氯代吡啶 + 胍基)→ 作用于昆虫nAChR受体;
杀菌剂:嘧菌酯(...

画面分为三区:左(杀虫剂)、中(杀菌剂)、右(除草剂); 每区展示1–2个典型分子结构(线型骨架+立体构象简图): 杀虫剂:吡虫啉(氯代吡啶 + 胍基)→ 作用于昆虫nAChR受体; 杀菌剂:嘧菌酯(甲氧基丙烯酸酯 + 嘧啶环)→ 抑制Cyt bc₁复合物; 除草剂:唑啉草酯(苯并噁唑啉酮 + 三唑环)→ 抑制ACC酶; 背景为农田生态场景:绿色作物、少量害虫/病菌图标(用显微镜放大框展示靶标酶活性位点); 底部横幅标注:“高效·低残留·精准靶向” + 绿色农药认证标志(如EU Ecolabel); 风格:科技农业插画风(清新自然色调:叶绿#4CAF50,土壤棕#795548,分子用亮黄#FFEB3B高亮氮环)。

06
Nano Banana
AI generated: 画面分为三区:左(杀虫剂)、中(杀菌剂)、右(除草剂);
每区展示1–2个典型分子结构(线型骨架+立体构象简图):
杀虫剂:吡虫啉(氯代吡啶 + 胍基)→ 作用于昆虫nAChR受体;
杀菌剂:嘧菌酯(...

画面分为三区:左(杀虫剂)、中(杀菌剂)、右(除草剂); 每区展示1–2个典型分子结构(线型骨架+立体构象简图): 杀虫剂:吡虫啉(氯代吡啶 + 胍基)→ 作用于昆虫nAChR受体; 杀菌剂:嘧菌酯(甲氧基丙烯酸酯 + 嘧啶环)→ 抑制Cyt bc₁复合物; 除草剂:唑啉草酯(苯并噁唑啉酮 + 三唑环)→ 抑制ACC酶; 背景为农田生态场景:绿色作物、少量害虫/病菌图标(用显微镜放大框展示靶标酶活性位点); 底部横幅标注:“高效·低残留·精准靶向” + 绿色农药认证标志(如EU Ecolabel); 风格:科技农业插画风(清新自然色调:叶绿#4CAF50,土壤棕#795548,分子用亮黄#FFEB3B高亮氮环)。

019
Nano Banana
AI generated: 中央突出一个三维分子结构(如喜树碱中的喹啉环,或吉非替尼中的喹唑啉骨架),用球棍模型+高亮氮原子(蓝色);
围绕中心分子分布多个上市药物分子缩略图(如:奥氮平→吩噻嗪类;伊马替尼→吡啶+嘧啶;利伐沙班...

中央突出一个三维分子结构(如喜树碱中的喹啉环,或吉非替尼中的喹唑啉骨架),用球棍模型+高亮氮原子(蓝色); 围绕中心分子分布多个上市药物分子缩略图(如:奥氮平→吩噻嗪类;伊马替尼→吡啶+嘧啶;利伐沙班→吗啉酮+氯苯),标注名称与治疗领域(抗肿瘤/精神/抗凝); 背景为人体靶点示意图:如EGFR激酶活性口袋(PDB 1M17结构简化版),显示氮杂芳烃与关键氨基酸(Asp855, Met793)形成氢键/π-π堆积; 左下角添加统计标签:“>80% 小分子药物含氮杂环”(引用文献[10–12]); 风格:专业SCI插图风(扁平化+科学配色:深蓝/紫/绿主调,氮原子统一为#1E90FF)。

07
Nano Banana