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通过分析氨基酸序列的某些参数，可达到预测抗原决定簇。但没有一种单参数预测获得较满意结果，故有必要进行多参数联立综合预测。选用６个参数加权叠加。首先假设形成表位的残基上的原子数正比于Ｎ２／３（Ｎ为整蛋白中残基原子数），再对３４个共含１６９个已知抗原位点的蛋白进行训练性综合预测，选出最佳权重。结果表明，Ｈｏｐｐ＆Ｗｏｏｄｓ亲水性参数和Ｊａｎｉｎ可及性参数在综合中很重要。对ＣＲＧＰ，ＳＣＸ２－ＡＮＤＡＮ，ＴＮＦＡ－ＨＵＭＡＮ，ＳＯＭＡ－ＢＯＶＩＮ，ＨＳ７Ｈ－ＨＵＭＡＮ这５个已知位点蛋白进行回顾性分析，初次预测率为４５．８％，再配以β－转角结构，二次预测率为４７．４％，结果可提供实验参考。
Predicted antigenic determinants can be achieved by analyzing some of the amino acid sequence parameters. However, no single parameter prediction obtains more satisfactory results, so it is necessary to carry out multi-parameter simultaneous synthesis prediction. Choose 6 parameters weighted overlay. It is first assumed that the number of atoms on the epitope forming an epitope is proportional to N2 / 3 (N is the number of residue atoms in the whole protein), and then a total of 34 proteins with 169 known antigenic sites are subjected to a comprehensive training prediction. Select the best weight. The results show that Hopp & Woods hydrophilicity parameters and Janin accessibility parameters are important in the synthesis. Retrospective analysis of five known sites of CRGP, SCX2-ANDAN, TNFA-HUMAN, SOMA-BOVIN, and HS7H-HUMAN revealed that the initial prediction rate was 45.8% The forecast rate is 47.4%, the result can provide experimental reference.