SBIR Phase I: A General 3-Dimensional Quantitative Structure-Property Relationship (QSPR) Algorithm

这个小企业创新研究项目将基于多维数据块的张量表示，产生一个通用算法和相应的软件包，以表达相关属性和独立分子特征度量之间的关系。这些数据环问题的解决方案是三维定量结构-性质关系，3D-QSPR。虽然这一提议关注的是三维关系，但形式主义很容易扩展到更高的维度。分子特征分为本征分子形状张量、分子场张量、非形状/场特征张量和实验特征张量。本征分子形状张量包含关于接触表面内分子形状的信息，而分子场张量包含接触表面之外的信息。与分子形状没有直接关系的分子特征被放置在非形状/场张量中。不作为因变量的实验测量可以被认为是实验张量中的独立分子特征。3D-QSPR是通过构造变换张量来实现的，该张量优化了因变量和自变量之间的统计显著性。我们将分别探讨因子分析、偏最小二乘回归和多维线性回归分析，以确定变换张量。所提出的形式论已经(以有限的方式)应用于一系列灵活的M2/M3毒碱类抑制剂，导致了3D-QSA(性质=活性)R，其中已经确定了活性构象，并应用于一组二氢叶酸还原酶的苄基嘧啶抑制剂，其中酶结合的构象和排列得到了正确的鉴定。还给出了进一步探索所提出的形式主义的实用性的其他数据集。该算法在计算机辅助分子设计领域具有深远的意义。这是迄今为止提出的唯一方法，一旦开发出来，将为研究人员提供一般的分析函数，这些函数可以定量地将结构与可呈现多重排列的柔性分子组的成员的性质联系起来。建议的3D-QSPR算法产品可能会被目前使用的所有CoMFA站点购买，以促进构象灵活性和多重比对的处理。此外，计算分子形状属性(分子形状分析)的一般功能使该软件包成为独立的3D-QSPR产品。在1.0版产品发布后的18个月内，可能会有超过10个安装成为目标。

This Small Business Innovation Research project will produce a general algorithm, and corresponding software package, based upon tensor representation of multidimensional data blocks, to express relationships between dependent properties and independent molecular feature measures. The solutions to these data riet problems are three-dimensional quantitative structure-property relationships, 3D-QSPRs. While this proposal focuses on three-dimensional relationships, the formalism can easily be extended to higher dimensions. The molecular features are partitioned into the intrinsic molecular shape tensor, the molecular field tensor, a non-shape/field feature tensor, and an experimental feature tensor. The intrinsic molecular shape tensor contains information on the shape of a molecule within the contact surface while the molecular field tensor contains information outside of the contact surface. Molecular features not directly related to molecular shape are placed in the non-shape/field tensor. Experimental measures not being used as dependent variables can be considered as independent molecular features in the experimental tensor. The 3D-QSPR is realized by constructing the transformation tensor which optimizes the statistical significance between the dependent and independent variables. Factor analysis, partial least squares regression and multidimensional linear regression analyses will be explored individually, and in combination, to determine the transformation tensors. The proposed formalism has beran applied (in a limited fashion) to a raet of flexible M2/M3 muscarinic inhibitors leading to a 3D-QSA (Property=Activity) R in which an active conformation has been identified, and to a set of benzylpyrimidine inhibitors of dihydrofolate reductase where the enzyme bound conformation and alignment have been correctly identified. Other data sets to further explore the utility of the proposed formalism are presented. The proposed algorithm has far-reaching implications in the field of computer-aided molecular design. It is the only method proposed to date, which once developed, will provide the researcher with general, analytical functions which quantitatively relate structure to properties of members of sets of flexible molecules which can assume multiple alignments. The proposed 3D-QSPR algorithm product is likely to be purchased by all sites currently used CoMFA in order to facilitate treatment of conformational flexibility and multiple alignments. In addition, the general features to compute molecular shape propertles (molecular shape analysis) make the package a stand-alone 3D-QSPR product. More than installations have been targeted as likely within 18 months of version 1.0 product release.