Progress on the Tasting Mechanism and Computer Aided Analysis of Food Taste-Modulating Peptides
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摘要: 食品呈味肽主要通过与咸味受体ENaC、TRPV1和TMC4、鲜味受体T1R1/T1R3、甜味受体T1R2/T1R3、苦味受体T2R和浓厚感味受体CaSR互相作用引发PLCβ2/IP3或cAMP/PKA等多种途径达成味觉信号转导。分子对接、动力学模拟、虚拟筛选和深度学习等计算机辅助分析技术可以高效、准确、广泛地鉴定和开发新型呈味肽，有效推动营养健康食品产业高质量发展。本文旨在介绍人体味觉感受机制、食品呈味肽呈味机制及计算机辅助分析技术在呈味肽领域的最新研究进展，为实现未来大算力时代食品呈味肽研发领域的降本增效和后续深入研究开发新型呈味肽产品提供思路方向。Abstract: Food taste-modulating peptides mainly interact with salt taste receptor ENaC, TRPV1 or TMC4, umami receptor T1R1/T1R3, sweet receptor T1R2/T1R3, bitter receptor T2R and kokumi receptor CaSR to induce PLCβ2/IP3 or cAMP/PKA pathway to achieve taste transduction. Computer aided analysis techniques such as molecular docking, dynamic simulation, virtual screening and deep learning can efficiently, accurately and widely identify and develop novel taste-modulating peptides, which can effectively promote the high-quality development of nutrition and health food industry. This paper aims to present the latest research progress in the field of taste-modulating peptides, including the human taste perception mechanism, the taste mechanism of food taste-modulating peptides, as well as computer aided analysis techniques. This provides ideas for cost reduction, efficiency enhancement, and subsequent in-depth research in the era of Big Compute and development of new taste-modulating peptide products in the field of food taste-modulating peptides development.
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呈味肽是现代食品工业通过生物合成、发酵、水解、酶解、美拉德反应、透析、色谱法等方法从食物中制取的、能调节食物味觉感知的小分子肽类物质。近年来，国内外对呈味肽的关注和相关的研究论文报道数呈逐年递增趋势，这与现在绿色消费的大趋势不谋而合：随着经济的发展和居民收入水平的提高，消费者们对于食品安全风险愈加关心[1]，对于美味、绿色、天然、更可持续的环境友好型食品的需求变得越来越旺盛，新冠大流行进一步加强了这种消费意识[2]。在调味品领域，近年来发现部分无机盐调味剂存在风味缺陷甚至健康风险[3−5]，因此消费者们倾向于购买以呈味肽为代表的风味浓郁、绿色健康的调味品[6]。目前，许多研究者们从动物、植物、微生物源的食物中提取了种类繁多的呈味肽，但许多研究仍比较粗浅，存在相当程度的不足。例如，许多文章尚停留在提取工艺的优化上；对于新型呈味肽的呈味机制探索较为浅显；采用单一的感官评价体系进行呈味肽的味觉感知验证，可靠性不够等。这可能是由于传统的蛋白质和肽类分离纯化鉴定工作艰苦繁重、效率低下；高校及研究院所一般缺乏稳定的专业感官评定团队来获得可靠性高的结果。鉴于此，在呈味肽领域亟需引入药学领域近年来广泛使用的计算机辅助药物设计、人工智能药物研发等技术，以此推动食品呈味肽研发领域的降本增效。本文希望通过对已有呈味肽相关研究进行总结和分析，以推动这一领域的研究进一步深入展开，并产生更多新的理论和实践成果。本文综述了味觉的生理学基础、呈味肽的呈味机理、制备鉴定技术，并概述了计算机辅助分析技术在呈味肽领域的研究进展，为进一步促进呈味肽的深入研究和新产品研发提供思路方向和参考。
1. 呈味肽介绍
呈味肽是近年来崭露头角的一种小分子新型天然食品添加剂，被称为味觉调节肽（Taste-Modulating Peptides）、味觉活性肽（Taste-Active Peptides）或味觉增强肽（Taste-Enhancing Peptide）。呈味肽有多种呈味类型，包括但不限于：肽本身可呈现滋味、本身无味但能增强食物整体的味觉感知、在高低浓度条件下可双向调节味觉感知等。例如，一些浓厚感肽本身在水溶液中的味道微乎其微，但在添加到食物中后能显著增强食物整体风味[7]；部分味觉调节肽对咸味具有双向效应，在低浓度下肽可增强食盐咸味，在高浓度下肽则会削弱咸味[8]；部分味觉调节肽浓度处于亚阈值水平时无法被人类尝到味道，但与其他亚阈值浓度水平的肽共同添加后可在同一体系内形成协同效应，显著增强产品整体风味[9]。
这些呈味肽具有完全或部分代替现有调味料的潜力，可以在保证食品风味和适口性的前提下降低食品中钠盐的含量，进而降低产品对现代人健康的负面影响[10]。部分呈味肽在具有良好呈味效果的同时还显示出了抗焦虑[11]、抗抑郁[12]、减弱氧化应激[13]、抗炎[14]、抗肥胖[15]等多种保健特性，这意味着呈味肽具有良好的产业化前景。
1.1 味觉生理学
要探索和讨论食品呈味肽的呈味机制，绕不开人体的味觉生理学基础。人的化学味觉分为酸甜苦咸鲜五种，主要由舌头味蕾中不同的细胞亚群感受。味蕾由味细胞、支持细胞和基细胞组成，其中存在I到 III型三种不同的味觉细胞亚群：I 型细胞充当支持细胞并呈现神经胶质状，II型细胞亚群可感受苦味、甜味和鲜味，III型细胞亚群可感受酸味和咸味[16]。
II型细胞膜表面的甜味受体由 1 型G 蛋白偶联受体（T1R）中的T1R2/T1R3异二聚体构成[17−19] 。不同的甜味剂与甜味受体结合形成复合物后会刺激G蛋白不同的活性位点，进而分离出β3γ13亚基或α亚基，通过PLCβ2/IP3途径或cAMP/PKA途径达成细胞膜去极化并促成神经递质的释放，刺激传入神经产生电信号再经孤束核、丘脑到达大脑皮层产生甜味[20−22]。除了典型的T1R外，也有研究显示葡萄糖转运蛋白 4 型（GLUT4）和钠/葡萄糖协同转运蛋白 1（SGLT1）可能参与了糖类的甜味转导[23]。
鲜味由II型味觉细胞表面T1R1/T1R3异二聚体受体、代谢型谷氨酸受体mGLUR和其他G蛋白偶联受体感受[24−26]，其中T1R1/T1R3的鲜味呈递也通过PLCβ2/IP3途径达成[27]。
苦味由II型味觉细胞表面多种2型G蛋白偶联受体（T2R）感受，苦味形成通过PLCβ2/IP3途径、cAMP/PKA途径或直接激活细胞膜上K+通道使膜去极化促成神经传导[28]。
酸味作为一种pH低于7时产生的“伤害性”味觉较为特殊，由III型味觉细胞表面的质子通道 OTOP1和瞬时受体电位TRP阳离子通道所调控。外界阳离子进入质子通道 OTOP1会直接导致细胞膜去极化，而胞内高浓度质子会对内向整流型K+通道Kir2.1产生抑制作用进而间接促进细胞膜的去极化和后续的神经信号转导[29−31]。
咸味由III型味觉细胞中的上皮钠通道ENaC和辣椒素受体TRPV1调控。中低盐刺激下，ENaC途径可以引发动物对盐的渴望，而TRPV1途径可诱导高盐刺激下动物对盐的排斥行为[10]。Na+、K+、NH4+等阳离子在味觉感受器细胞中富集后引起细胞膜去极化和后续的神经信号转导，导致咸味的最终感知[32]。另外，属于TMC家族的阴离子/氯离子通道的跨膜通道样4（TMC4）也可参与咸味感知[33]。
五味之外的浓厚感则由细胞表面G蛋白偶联受体家族中的钙敏感受体CaSR感受，浓厚感味物质可与CaSR的胞外捕蝇草结构域结合并激活PLCβ2/IP3途径，达成细胞膜去极化和神经传导[34]。
综上所述，甜、苦、鲜和浓厚感味的感受主要由GPCR家族介导：异二聚体受体T1R负责鲜（T1R1/T1R3）和甜味（T1R2/T1R3），T2R负责苦味[35]。负责浓厚感味的CaSR表达独立于鲜味和甜味的受体亚基T1R3[36]，但可能与T2R存在共表达[37]。鲜、甜、苦、浓厚感在味觉细胞内存在着与PLCβ2/IP3相同或类似的信号传导途径[38]。咸味主要由ENaC和TRPV1负责。酸味主要由OTOP1和TRP负责[10]。在味觉系统中，不同物质对味觉的调节、味蕾内细胞间信号传导、脑部处理味觉信号的机制在近年来又涌现出更多的研究成果和新的谜题，例如多种味觉都共用PLCβ2/IP3途径却能区分出味道的原理、不同甜味剂激活甜味受体的结构学基础和神经元调控机制、味觉感知与大脑边缘系统如何联动最终给食用者带来主观情绪体验等。这些疑问表明味觉产生过程比以前认知的更加复杂。对于食品来说，消费者在摄入食物、接收风味时的主观感受至关重要，而消费者多样化的味觉体验涉及到包括额叶、颞叶、顶叶、扣带回等多个大脑区域[39]，并且与情感、记忆、注意力等认知因素有关[40]，因此神经区域通路作为味觉感知的核心场所需要更多与呈味剂联动的系统性研究。
1.2 呈味肽分类及呈味机制
呈味肽主要分为咸味肽（与咸味受体ENaC、TRPV1和TMC4发生相互作用）、鲜味肽（与鲜味受体T1R1/T1R3互作）、酸味肽（基本囊括于鲜味肽中）、甜味肽（与甜味受体T1R2/T1R3互作）、苦味肽（与苦味受体T2R互作）和浓厚感肽（与钙敏感受体CaSR互作）。呈味肽与味觉细胞发生互相作用后可以引发PLCβ2/IP3或cAMP/PKA等多种途径达成味觉信号转导。而就具体的不同呈味肽而言，其呈味机制迥然不同。
目前咸味（Salty）肽研究尚处于零散起步阶段。例如，Zheng等[41]从酵母提取物中分离出了多种咸味活性肽。Chen等[42]从腐乳中分离出增咸肽，在50 mmol/L NaCl 溶液中添加0.4 mg/mL肽即可达到相当于63 mmol/L NaCl参比溶液的咸味感知水平。Salger等[43]从过发酵可可豆溶剂中提取的增咸肽能显著增强模型肉汤的咸味。咸味肽的呈味机制目前尚不明确。Le等[10]推测是肽螯合了矿物质离子引起了呈味神经信号的传导。Rhyu等[44]发现酱油中筛选出的咸味肽不会影响ENaC途径介导的阿米洛利敏感（Amiloride Sensitive）通路，但会影响阿米洛利不敏感（Amiloride Insensitive）通路，推测咸味肽呈味可能是通过含有 TRPV1 的三叉神经末梢与阿米洛利不敏感通路的味觉细胞间的相互作用达成的。Yu等[45]将草鱼中提取的胶原蛋白进行氨基葡萄糖化制备出低反应程度的美拉德反应肽，通过分析发现该肽可以与TRPV1受体相互作用并显著增强咸味。Xu等[46]发现二肽Ala-Arg可显著增加阿米洛利敏感受体ENaC-α和ENaC-δ的反应，从而产生咸味增强作用。最近Bu等[47]发现从加州鲈鱼（Micropterus salmoides）肌球蛋白中筛选出的咸味增强肽可与最新发现的TMC家族阴离子/氯离子通道跨膜通道样4（TMC4）以氢键进行结合，达到咸味增强的作用。现有的研究显示，不同种类咸味肽的呈味机制可能与ENaC、TRPV1或TMC4通道均有关，提示咸味肽呈味机制仍需更多的系统性探索和总结。
鲜味（Umami）肽最早受到学界关注，目前研究成果最多。常见鲜味剂谷氨酸钠MSG和核苷酸钠盐可以与T1R上VFT结构域口袋结合形成鲜味感[25,48]，而鲜味肽结合T1R的呈味机制与MSG有所不同。Haid等[49]发现T1R1阳性味觉细胞中的额外鲜味受体GPR92可受到蛋白水解物的激活。许多学者们则通过同源建模和分子对接技术模拟了肉汤鲜味肽、海鲜鲜味肽和食用菌鲜味肽与鲜味受体T1R1/T1R3的结合，并在感官评价中得以验证，筛选出了许多种类的鲜味肽[50−54]。Dang等[55]通过分子对接技术分析了鲜味增强肽协同味精MSG呈味的可能机制：MSG与T1R1口袋结合后扩大了T1R3结合腔大小从而使肽更容易与T1R3结合，与此同时呈味肽的五个残基（Glu-429、Gln-302、Gly-304、Try-107和His-364）与位于T1R3 VFT结构域中的MSG形成了氢键，由此增鲜肽与MSG的多重互作巩固了T1R1/T1R3的构象从而增强了味觉细胞对鲜味的感知。目前鲜味肽主要围绕鲜味受体T1R1/T1R3开展呈味研究，已建立了较为完整的数据库和预测成功率较高的结构模型，取得了良好的研究进展。
就酸味（Sour）肽而言，单独针对酸味肽的研究较少，目前发现含有谷氨酸（Glu）和天冬氨酸（Asp）的二肽或三肽通常具有酸味。这两种氨基酸普遍被囊括在鲜味肽研究中[50,52,56]。
甜味（Sweet）肽包括了小分子的甜味肽和大分子的甜味蛋白质。目前已发现多种小分子甜味肽，例如阿斯巴甜（APM）及其衍生物，从豆瓣酱中鉴定出的GFSSEFLA[57]，从发酵茶中鉴定出的VGV[58]，从发酵油腐乳中鉴定出的DF、DMP等多种甜味肽[59]。大分子甜味蛋白质的发现和研究相对较早，其包括应乐果甜蛋白（Monellin）、奇异果甜蛋白（Thaumatin）等，但目前大分子甜蛋白由于天然成分含量低、性质不稳定、成本高昂的特点，商业化规模生产仍较为困难[60]。由于蛋白质较大的表面积及电子特性，大分子甜味蛋白质的结构-功能关系与小分子甜味肽的结构-功能关系存在着一定区别[61]。Temussi[62]认为小分子甜味肽倾向于与游离形式I（open-open_Resting）的无配体受体活性位点结合，而大分子甜味蛋白倾向于与游离形式II（closed-open_Active）的受体结合。Temussi[63]进一步提出了甜味蛋白和受体之间相互作用的楔形模型，即甜味蛋白和甜味受体之间的表面电荷产生互补并引起了甜味呈味作用。许多学者通过同源建模和分子对接技术模拟了各类甜味肽与甜味受体T1R2/T1R3结合并以感官评价加以验证，证明了这些新型甜味肽的呈味效果[17,64−66]。由于味觉生理学中甜味的识别与转导均与T1R2/T1R3有关，因此目前针对甜味肽的呈味研究也主要集中在肽与T1R2/T1R3的结合上。为了揭示更多潜在的甜味肽呈味机制，需要进一步深化在味觉生理学领域的探索研究。
苦味（Bitter）通常是消费者难以接受的味道，且常在食品蛋白水解和药物加工过程中形成，这成为了食品加工和制药行业的长期挑战[67]。而苦味肽研究应用目标并非制备苦味肽，而是聚焦在食品脱苦或苦味阻滞上（Bitter-blockers）。目前人体已经发现25种苦味受体（TAS2Rs，也称作T2R）与苦味感知有关，它们能与不同类型的配体进行结合[68]。影响肽苦味的因素包括了多肽的疏水性、多肽氨基酸的序列、肽链的长度以及多肽分子量的大小[69]。许多学者通过选择性提取、吸附等手段直接对苦味肽本身进行分离处理[70−72]。然而，蛋白质水解物中一些生物活性肽具有抗高血压、抗血栓、抗癌、抗菌、抗氧化和免疫调节活性等功能特性[73]，这些活性肽常常具有苦味，因此如何在能抑制苦味的情况下还能享受到蛋白水解活性肽的益处成为了学界感兴趣的方向。以苦味阻滞肽、乙酸钠、葡萄糖酸钠等为代表的许多苦味阻滞剂逐渐得到研究，它们可以直接与苦味受体相互作用从而抑制苦味[74]。目前苦味阻滞肽的研究主要在肉品领域。例如Zhang等[75]利用商业酶酶解制备了牛肉蛋白水解多肽并证明该水解物可以抑制经过转染的HEK-293细胞中的奎宁依赖性苦味受体T2R4，通过抑制钙离子释放从而阻滞奎宁的苦味。Xu等[76]制备了超市废鸡肉的蛋白水解物并证明其可以抑制经过转染的HEK293T细胞中的苦味受体T2R4、T2R7和T2R14的钙动员机制从而阻滞奎宁的苦味。Yu等[77]制备了虹鳟鱼蛋白水解物并与T2R14 受体进行分子对接模拟，证明了 ADM 和 ADW肽可以通过氢键相互作用和疏水相互作用形成对受体的高亲和力，通过竞争性抑制来阻断苦味物质与苦味受体的结合。苦味肽的呈味和阻滞研究目前均围绕着苦味受体T2R开展，因此针对T2R家族内种类繁多的受体仍有待更多的研究。
浓厚感（Kokumi）肽呈味机制特殊，近年来受到许多学者的关注。浓厚感物质通常无味或味道微弱，却可改变食品整体风味，使之呈现更饱满、复杂和持久的风味[78]。例如，Feng等[79]从双孢蘑菇中筛选并人工合成出的Gly-Leu-Pro-Asp和Gly-His-Gly-Asp两种浓厚感肽可显著提升模型鸡汤的咸味和鲜味。Kuroda等[80]发现羊奶酪中较高浓度的浓厚感肽γ-Glu-Val-Gly有助于羊奶酪风味的形成。Lu等[81]发现绿茶中的浓厚感肽GSH和γ-Glu-Gln能在低浓度下与茶氨酸协同增强茶汤的醇厚感。部分学者发现浓厚感肽γ-谷氨酰肽具有包括抗炎、抗氧化、抗肿瘤、降血糖等诸多生物学活性[82]，研究显示这些生物学活性以及呈味机制均与钙敏感受体（CaSR）有关[83]。Chang等[84]通过分子对接发现浓厚感肽的呈味机制可能类似于色氨酸，其无法单独激活 CaSR，但可以在Ca2+存在的条件下通过氢键、静电相互作用和疏水相互作用促进CaSR激活。Maruyama等[85]使用浓厚感肽γ-Glu-Val-Gly激活了经转染的HEK-293细胞中的CaSR，并确定了γ-谷氨酰肽激活CaSR的结构需要肽存在N-末端γ-L-谷氨酰残基，在L-构型的第二个残基上存在中等大小的脂肪族中性取代基以及C末端羧酸官能团。浓厚感肽与钙敏感受体CaSR的激活高度相关，但如何协调增强其他几种基本味觉的后续机制尚需更深入的研究。
相比于简单的氨基酸分子而言，肽链的分子量庞大，可形成的构象更繁杂，呈味肽的结构与其调控的味觉感知途径类型的关联性尚不十分清楚。即便是相同味型的呈味肽，其调控的味觉感知途径也可能迥然不同。因此，虽然基础呈味受体目前已经被发现并应用于呈味研究，但呈味肽与受体的结合机制仍应进一步考虑更多的影响因素，包括但不限于呈味肽的一二级结构、呈味肽的亲疏水性、食品基质因素、肽与受体结合时的外界环境条件、呈味肽与其他呈味物质的互作、呈味肽本身之间的互作、多种呈味肽与受体结合时的协同或干扰作用等等。
2. 呈味肽研究方法
2.1 传统呈味肽研究方法
传统的呈味肽研究通常是使用包括但不限于酸碱水解[86]、酶水解[87] 、美拉德反应[88]等方法制备天然食物中的内源或外源性呈味肽，采用膜分离[89]、体积排阻[45]、离子交换[90]、亲和层析[91]在内的多种方法分离纯化呈味肽，并通过Edman降解[92]、液相色谱[93]、质谱[94]等技术进一步进行鉴定，之后使用电子舌[95]、感官鉴定[96]等方法进行味觉验证。例如，Liu等[97]通过加热和超声波处理河豚肉并利用纳米液相色谱三重四极杆飞行时间质谱鉴定出7种鲜味肽，基于感官评价验证了分离肽和人工合成肽的鲜味。Chen等[98]利用凝胶过滤色谱和反相高效液相色谱从鸡肉水解液中分离出10种新型呈味肽，基于感官评价和电子舌发现所有合成肽都具有增鲜作用。Pratama等[99]使用酸水解螺旋藻后通过凝胶过滤色谱和高效液相色谱串联电喷雾质谱分离出多种鲜味增强型谷氨酰肽。传统的呈味肽研究方法技术要求低、工艺相对成熟、操作简便、分离纯化度高，能获取可靠的真实证据材料，缺点是研究工作机械而繁重、纯化设备相对昂贵、实验周期较长、筛选存在一定运气成分。
2.2 计算机辅助信息分析
与传统的肽制备及鉴定研究方法相比，以计算机辅助分析等技术为代表的新型呈味肽研究方法具有多重优点，包括鉴定范围更广、鉴定效率更高、鉴定结果准确可靠、设备要求低，减少了机械繁重的工作，但需要掌握食品与计算机学科交叉内容，技术掌握的难度较大[94,100−102]。由于研究面向的多肽数量众多，高通量生信技术筛选变得越来越迫切，因此计算机辅助信息分析等技术近年来逐渐成为了呈味肽研究的有力助手并产生了广阔的潜在研究空间。
目前人类G蛋白偶联受体家族结构研究取得了一些进展，但由于该家族蛋白具有高度动态变化的性质，难以大规模表达和纯化，因此直到现在学界还没有完全厘清人类的味觉受体结构[35]。作为替代方案，使用包括同源建模在内的生物信息学（In Silico）方法生成味觉受体的3D结构模型并采用分子对接、分子动力学模拟、深度学习等在内的多种计算机辅助分析技术探索呈味肽的配体结合位点和与受体作用的机制可大大加速呈味肽的研发工作。
2.2.1 同源建模
使用计算机模拟分子间结合需要使用到分子对接技术。在分子对接流程的受体结构准备阶段，若受体结构已知（在药学领域较为常见），则可使用PDB（Protein Data Bank）数据库下载并调用已有的人类受体结构来进行后续的分子对接。
然而，在味觉相关的计算机模拟分析研究领域，由于许多人源味觉受体的具体结构仍未知，目前往往采用同源建模（Homology Modeling）的方法进行模拟，即使用现有数据库中各类动物物种中已知结构、与目标蛋白的氨基酸序列相近、具有物种同源性的3D结构模型（例如小鼠、青鳉鱼等）建立靶点蛋白质的3D结构模型。味觉受体的同源建模存在多种方法，咸味相关受体通常由TMC4构建[47]，甜味相关受体T1R1模型通常由T1R2、T1R3和mGluRs结构构建，甜鲜味相关受体T1R3模型通常由T1R3和mGluRs结构构建[103]，苦味受体由于目前可用的各类G蛋白偶联受体模板序列同一性有限，仍未出现较为普及的方法，往往使用现实实验验证来提升模拟结果可靠性[35]。举例来说，Yu等[104]使用小鼠和人类代谢型谷氨酸受体mGluR进行同源建模及分子对接，使用分子动力学优化并筛选出虾夷扇贝肌球蛋白中的重要鲜味肽。Kashani-Amin等[105]使用青鳉鱼T1R2/T1R3晶体结构作为模板来模拟T1R2和T1R3细胞外域，其性能优于使用mGluR模板构建的模型。Nuemket等[106]将青鳉鱼T1R2/T1R3晶体结构同时用于构建T1R1/T1R3同源模型。Liu等[107]使用青鳉鱼T1R3的晶体结构来模拟T1R1配体的结合域。
然而，一些基础性研究显示同源建模结果可能并不十分可靠。例如鱼类 T1R 在某些功能上不同于哺乳动物 T1R[108]；灵长类在长期演化过程中味觉感知机制也出现了差异，例如松鼠猴T1R1/T1R3与小鼠类似，对谷氨酸的敏感性较低；一些灵长类动物的味觉对肌苷酸和鸟苷酸等游离核苷酸相比于人类和大猩猩要敏感的多[109]。同源建模所利用的动物味觉受体模型与人体存在差异，结果仅能提供参考。尽管同源建模技术目前仍存在缺陷，但基于同源结构的建模方法对揭示呈味肽的分子机制仍有巨大的帮助。
2.2.2 分子对接
分子对接是基于分子间空间结构互补和最小化能量匹配原则，使用计算机软件模拟和预测靶标分子与配体分子之间结合形成稳定复合物过程中配体分子和靶点口袋的结合模式（Binding Mode）及该模式下结合作用强弱（Affinity）的技术。在新药研发领域，分子对接有多种用途：在靶点已知的情况下从大数据库中筛选可与目标靶点结合的先导化合物或指导现有药物分子的结构优化[110]；在靶点未知的情况下探索活性药物小分子的潜在靶点，与大分子受体的具体作用方式，解释药物产生活性的原因[111]；寻找已有药物的新疾病靶点[112]；研究药物副作用[113]；研究复杂化合物的合成过程[114]等等。近年来分子对接被逐渐应用于食品呈味肽研究，能直观且定量地反映呈味肽与味觉受体的结合位点、结合方式及结合强弱。例如，Chen等[98]通过Discovery Studio软件进行分子对接证实，分步色谱筛选出的呈味肽都可以进入T1R3维纳斯捕蝇草（VFT）结构域，其中 Arg303、Ser123和His121可能在增鲜作用中起关键作用。Shen等[115]通过凝胶过滤层析和反相高效液相色谱提取野生乳菇中的鲜味肽，通过SYBYL-X软件分子对接筛选出四种鲜味肽，四种肽均以氢键和疏水相互作用嵌入味觉受体T1R3腔的结合口袋中。Kan等[116]使用计算机模拟水解蛋清蛋白后获得GVDTK和DNDK肽，与苦味受体TAS2R14进行分子对接发现两种肽可通过氢键和疏水相互作用阻断奎宁的苦味。Chang等[84]利用CDOCKER方法进行分子对接发现事先从酵母中提取的浓厚感肽能通过氢键、静电作用和疏水相互作用与CaSR结合产生浓厚感味。然而，分子对接目前仍存在一些缺点：只考虑理想环境下对接口袋附近的结合亲和力，无法涵盖现实条件下蛋白质和小分子动态构象受到时间、温度、溶剂或 pH影响的情况；受限于人源受体蛋白3D结构不完整和打分函数的算法缺陷，导致对结合亲和力预测仍不够准确；需要现实验证的实验数据支撑匹配等。但该技术仍可显著提高呈味肽研究效率并降低研发成本，这会愈发成为呈味肽领域的重要研究工具[117]。
2.2.3 分子动力学模拟
分子动力学模拟 （Molecular Dynamic Simulation）是一项基于牛顿力学和分子力学原理来研究连续时间间隔内，分子之间的相互作用以及研究分子互作如何受到外界环境参数影响的多体模拟方法[118]。在计算机辅助药物设计领域，该技术通常使用物理、化学和数学关系推导出特定时间间隔内，处于特定能量水平、运动方式或其他物理参数下的配体和受体在特定环境之下一步步的相互作用从而最终结合生成新复合物结构的过程，通过计算结合自由能来评判新复合物的结构稳定性，因此分子动力学模拟可以作为分子对接技术在复杂环境参数下的良好补充[119]。例如，Chang等[84]利用分子动力学软件AMBER 18动态模拟了酵母提取物浓厚感味肽可以通过常规氢键、碳氢键和盐桥相互作用与CaSR结合。Song等[120]通过Gromacs软件模拟了牛肝菌中鉴定出的鲜味肽能与鲜味受体T1R1/T1R3通过氢键和疏水相互作用结合，鲜味肽中的带电氨基酸残基（D1、E4和K1）在鲜味肽和受体的分子识别中起主导作用。Zhang等[121]利用工程菌生产人源T1R1-VFT蛋白并构建了基于荧光光谱检测的新型鲜味肽定量感受系统，通过AMBER14SB软件模拟出该味觉感受系统能与鲜味肽稳定结合，从而可以定量检测呈味肽的鲜味。上述这些基于经典键合/非键合势能理论解释分子间作用力的分子动力学模拟方法获得了良好的研究进展，但仍存在分子力场计算耗时、参数拟合繁琐复杂、很难在较大的生物尺度上进行模拟的缺点，因此近年来基于深度学习等机器学习算法的分子动力学模拟方法逐渐崭露头角[122]。
2.2.4 虚拟筛选
虚拟筛选（Virtual Screening）是一项通过大型数据库和特定计算机脚本语言实现的批量3D建模和批量分子对接的技术，其面对的化学空间少则几万，多则达到上百万，由此可以加速配体的筛选速度、降低筛选成本、提升筛选准确性并降低操作复杂性。由于味觉受体种类相对较少，近年来虚拟筛选逐渐被应用于食品呈味肽研究中，学者们将味觉受体模型应用于虚拟筛选以识别新的味觉受体配体。例如，Zhang等[123]通过Python脚本批量调用并对接了208个肽并从中虚拟筛选出能与T1R1/T1R3结合口袋稳定结合的9种鲜味肽，从中发现氢键和疏水作用力在受体-肽相互作用中发挥关键作用。Cheng等[124]对具有胰蛋白酶水解位点的鲜味牛肉肽（BMP）进行了进一步修饰并利用虚拟筛选鉴定出大量优于原牛肉呈味肽的改性呈味肽，优化后的鲜味肽优秀的呈味性能在感官实验中得到验证。Xiong等[125]从已发表的文献中收集鲜味二肽构建了共同特征药效团模型，该模型可以直接从食品成分超滤后的质谱鉴定结果中快速虚拟筛选出鲜味肽，准确率甚至优于部分基于机器学习算法的虚拟筛选方法。运用计算机脚本的虚拟筛选技术已经脱离了传统手工作坊式的研究方法，转而向多学科交叉协作的科研工业化智能化转化，这极大加快了新型呈味肽的筛选速度，降低了各项研发成本和风险。而当研究积累的数据库越来越大以致虚拟筛选方法无法满足计算机辅助药物设计对百万以上化学空间的精确筛选要求时，往往会采用全新的筛选策略，包括应用超大规模的构象枚举甚至机器学习算法[126]。
2.2.5 深度学习
基于多层感知机（Multilayer Perceptron）的深度学习是机器学习近年来的新研究热点。随着多图形处理器（GPU）硬件算力的提升，训练效果好、理论要求低、可解决复杂问题的深度学习（Deep Learning）在各领域大显身手。其使用大数据集、多隐藏层和GPU来并行训练包括卷积神经网络、循环神经网络等在内的深度神经网络[127]，以对数据进行预测、分类和聚类。在药物研发领域显著降低了各项成本，加速了新药研发速度[128]。
在食品呈味肽研究领域，由于呈味肽与味觉受体结合过程复杂，基于人工神经网络的深度学习模型能实现提取、存放呈味肽结构的多维数据特征和拟合大数据量预测模型，这比更重理论支撑的传统机器学习方法更适合进行呈味肽的预测分析。举例而言，Qi等[129]从BIOPEP-UWM数据库和前人研究中收集了212种鲜味肽和287种非鲜味肽构建出UMP499数据集来训练多层递归神经网络（MRNN），该Umami-MRNN模型在10折交叉验证和独立测试实验中能避免过拟合的同时使未知鲜味肽的预测分类准确率达到 91.5%，其预测性能优于其他传统机器学习方法。Jiang等[130]从BIOPEP-UWM数据库和前人研究中收集了140个鲜味肽和304个非鲜味肽构建出UMP442数据集，以此数据集训练乘法长短期记忆神经网络（mLSTM），其所构建的iUmami-DRLF模型在10 折交叉验证和独立测试实验中证明能够比报道的最先进的方法更可靠、稳健和准确地预测鲜味肽。Jiang等[131]从BIOPEP 数据库和前人研究中收集了320种苦味肽和320种非苦味肽构建了BTP640数据集训练双向长短期记忆神经网络（BiLSTM），该iBitter-DRLF模型实现了仅基于肽序列数据的准确预测，大大提高了目前现有的各类预测模型识别苦味肽的能力。Jiang等[132]从BIOPEP数据库结合前人研究中收集了112种苦味肽和241种非苦味肽组成的数据集结合预训练BERT模型训练双向长短期记忆神经网络（BiLSTM），该IUP-BERT模型明显优于现有的需要手动提取特征组合的多种预测模型。随着食品和人工智能领域交叉研究的不断推进，更多优化过的呈味肽大数据库可以被应用于模型的训练和预测，许多训练完成的高性能呈味肽预测模型都得以在互联网上开源并供学者们在线分析使用[133]。最近，在蛋白设计领域，Verkuil等[134]利用经过训练的自然语言模型ESM2从无到有设计生成了自然界不存在的新蛋白质。Chen等[135]开发了千亿级参数的蛋白质语言模型xTrimoPGLM以供理解和生成蛋白质。这意味着人工智能语言模型可以被应用于更广泛的蛋白/肽类相关研究领域。在未来必定到来的比拼算力的“大算力时代”，尽快掌握并使用以深度学习为代表的一系列人工智能技术能达成呈味肽研究领域的降本增效，甚至可以直接逆转传统呈味肽“自上而下”的低效率研究方式：通过基于天然呈味肽的大数据集、人工智能计算方法进行呈味肽的从头设计，结合合成生物学来大规模生产性能更加优异的人工呈味肽，“自下而上”地通过人工智能赋能肽类科学研究新范式，从而构建呈味肽领域的产学研协作新模式。能预见到以深度学习为代表的一系列人工智能技术会成为探索开发新型呈味肽和促进食品行业高质量发展的有力工具。
3. 总结与展望
目前较多食品呈味肽的研究仍停留在鉴定、筛选、分离和制备工艺优化阶段，对呈味肽的呈味机制仍处于探索阶段，但食品呈味肽仍具有相当大的、可供探索的空间，具有广泛的研究前景。
就呈味领域而言，对呈味机制的研究会愈发将焦点投向主体本身，即人体上行通路和神经区域。作为味觉感知的核心场所，味觉相关神经需要更多与呈味剂联动的系统研究，而繁多的绿色天然呈味肽可视为一种有效工具，进一步解析并探索呈味机制研究的深层次领域。
人体多样的味觉体验涉及多个大脑区域，且与情感、记忆、注意力等认知因素相关。许多天然绿色的呈味肽具有抗焦虑、抗抑郁、减弱氧化应激、抗炎、抗肥胖等良好的生物学活性，很可能可通过干预精神疾病相关的神经生物学基础从而间接改善食用者的精神心理问题。业界可开辟出以功能性呈味肽为代表的“精神性食疗”的食品研发新领域，用来改善和缓解后现代社会人群普遍的身心亚健康状态，这个新领域与中国传统的食疗法相契合，并共同形成了一种新型理念和研发策略。
计算机辅助分析技术在食品领域中可用于加速繁琐漫长的呈味肽研发历程。近年国产高端芯片普及化和以深度学习为代表的新型人工智能技术会为传统实验科学和统计分析带来划时代的变革，算力工具的提升会普遍把蛋白和肽类结构预测带入高通量时代。利用计算机辅助分析技术和深度学习模型能有效促进呈味肽的高通量筛选或产生结构功能相似的新型呈味肽并加以验证，可以为传统蛋白质和肽类研究的繁重工作降本增效。而通过模仿生物制药和化学制药的思路，使用大批量工业化合成、工程菌生物发酵等技术生产结构相对简单、绿色健康的呈味肽；或通过优良可行的工艺大批量提取农林渔牧产品副产物制备具有特定风味的呈味肽复合物；或通过大数据、人工智能计算进行蛋白质从头设计结合合成生物学来设计并生产性能优异的人工呈味肽，可能为食品调味行业甚至功能性食品行业引领一波绿色创新潮流，为经济和社会带来积极影响，并推动我国在全球食品产业高质量发展中占据优势地位。综上所述，食品呈味肽是一个潜力巨大的研究宝库，亟待有更多的有识之士投身到这片蓝海中进行创新研发工作。
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