Molecular connectivity study of muscarinic receptor affinity of acetylcholine antagonists

QSAR modeling of beta-lactam binding to human serum proteins

The binding of beta-lactams to human serum proteins was modeled with topological descriptors of molecular structure. Experimental data was the concentration of protein-bound drug expressed as a percent of the total plasma concentration (percent fraction bound, PFB) for 87 penicillins and for 115 beta-lactams. The electrotopological state indices (E-State) and the molecular connectivity chi indices were found to be the basis of two satisfactory models. A data set of 74 penicillins from a drug design series was successfully modeled with statistics: r2 = 0.80, s = 12.1, q2 = 0.76, spress = 13.4. This model was then used to predict protein binding (PFB) for 13 commercial penicillins, resulting in a very good mean absolute error, MAE = 12.7 and correlation coefficient, q2 = 0.84. A group of 28 cephalosporins were combined with the penicillin data to create a dataset of 115 beta-lactams that was successfully modeled: r2 = 0.82, s = 12.7, q2 = 0.78, spress = 13.7. A ten-fold 10% leave-group-out (LGO) cross-validation procedure was implemented, leading to very good statistics: MAE = 10.9, spress = 14.0, q2 (or r2press) = 0.78. The models indicate a combination of general and specific structure features that are important for estimating protein binding in this class of antibiotics. For the beta-lactams, significant factors that increase binding are presence and electron accessibility of aromatic rings, halogens, methylene groups, and =N- atoms. Significant negative influence on binding comes from amine groups and carbonyl oxygen atoms.

E-state modeling of fish toxicity independent of 3D structure information

Topological structure methods are used to model fish toxicity against three classes of organic chemicals. The models were obtained independent of 3D structure information. Further, no mechanism of partitioning was assumed, thus avoiding the problems associated with selection of partitioning system for computation of log P. QSAR models were developed for a set of 92 compounds, including phenols, anilines and substituted aromatic hydrocarbons, yielding excellent statistics: r2 = 0.87, s = 0.25 and q2 = 0.85 leave-one-out (LOO), that are better than those reported in the literature. The model is based on molecular connectivity valence chi-1 index [1chiv], the atom type E-State indices for chlorine [ST(-Cl)] and for ether oxygen [ST(-O-)], and the maximum hydrogen E-State atom value in a molecule [Hmax]. Each of the subgroups was also separately well modeled. The model for the full set is validated through use of external validation test sets and ten-fold cross-validation (repeated three times). The quality of the validation statistics supports the claim that the model may be used for estimation of pLC50 values for similar molecules. Detailed structure interpretation is given for the descriptors in the model. These four structure descriptors encode influence of molecular context of groups as well as counts of those groups, in addition to molecular skeletal structure.

Issues in representation of molecular structure the development of molecular connectivity

Significant issues in the representation of molecular structure and the development of the molecular connectivity paradigm are presented. In the molecular connectivity paradigm, molecular structure is represented directly. Kier and Hall developed the method by creating ways to encode electronic information based on the paradigm developed from the Randić branching index. The simple and valence delta values were created to encode atomic and valence-state electronic information through counts of sigma, pi, and lone pair electrons. A family of indices was created to provide a wide range of structure information. The key aspects of the development are presented and discussed in such a way as to reveal, at least in part, the imaginative thinking involved in the process. Possible future roles for molecular connectivity chi indices are discussed.

Derivation and significance of valence molecular connectivity

The physical basis for valence molecular connectivity was studied. The delta v and delta values are cardinal numbers describing the electronic structure of atoms in their valence states. The value delta v + delta describes the volume of a bonding atom while the value delta v - delta describes the electronegativity. By using the principle of electronegativity equalization, bond electronegativity is defined as (delta vi delta vj)-1/2, and the valence molecular connectivity index (l chi v) is derived as a sum of these bond descriptions. The valence chi index is interpreted in terms of the information encoded, describing both the volume and electronic characteristics of bonds in molecules. Examples of close relationships with molecular volume and electronic properties are shown. A new way of estimating valence state electronegativity is proposed from a count of exterjacent electrons divided by the quantum number squared for at least the first three quantum levels.

Molecular structure influencing either a sweet or bitter taste among aldoximes

A series of cyclohexylaldoximes was examined for their sweet or bitter taste using discriminant analysis. The structures of the molecules were described using molecular connectivity. A two-variable linear discriminant function and critical value were computed that correctly assigned 17 of the 20 molecules to their observed sweet or bitter taste categories. The same discriminant function can predict correctly the taste categories of seven of eight additional molecules.