Search

Intrinsically Disordered Peptides and Proteins (IDPs) in solution can span a broad range of conformations that often are hard to characterize by both experimental and computational methods. However, obtaining a significant representation of the conformational space is important to understand mechanisms underlying protein functions such as partner recognition. In this work, we investigated the behavior of the Sic1 Kinase-Inhibitor Domain (KID) in solution by Molecular Dynamics (MD) simulations. Our results point out that application of common descriptors of molecular shape such as Solvent Accessible Surface (SAS) area can lead to misleading outcomes. Instead, more appropriate molecular descriptors can be used to define 3D structures. In particular, we exploited Weighted Holistic Invariant Molecular (WHIM) descriptors to get a coarse-grained but accurate definition of the variegated Sic1 KID conformational ensemble. We found that Sic1 is able to form a variable amount of folded structures even in absence of partners. Among them, there were some conformations very close to the structure that Sic1 is supposed to assume in the binding with its physiological complexes. Therefore, our results support the hypothesis that this protein relies on the conformational selection mechanism to recognize the correct molecular partners.

Soil sorption coefficients (K-OC) of 185 non-ionic organic heterogeneous pesticides have been studied searching for quantitative structure-property relationships (QSPRs). The chemical description of pesticide structure has been made in terms of some molecular descriptors: count descriptors, topological indices, information indices, fragment-based descriptors and weighted holistic invariant molecular (WHIM) descriptors; these last are statistical indices describing size, shape, symmetry and atom distribution of molecules in the three-dimensional space. Three new topological indices derived from the electrotopological state indices of Kier and Hall were proposed. Multiple linear regression analysis was performed after previous selection of the descriptors mostly correlated to the response by Genetic Algorithms. The obtained results confirm the capability of the proposed approach to give predictive models for one of the most important partition properties, such as soil sorption coefficient (K-OC). (C) 2000 Elsevier Science Ltd. All rights reserved.

Physico-chemical properties of polychlorinated biphenyls (PCBs) congeners have been extensively studied searching for quantitative structure–property relationships (QSPR). The chemical description of PCBs structure is made in terms of WHIM descriptors, which are 3D molecular descriptors taking into account size, shape, symmetry and atom distribution of the molecules. The regression models have been obtained by optimizing their prediction power and by selecting the best subset of descriptors by genetic algorithm. The results confirm the capability of this approach to give predictive models for important physico-chemical properties, such as relative retention time, log K ow , melting point, total surface area, Henry's law constant, solubility, and aqueous activity coefficients.

WHIM descriptors are 3-dimensional molecular indices that represent different sources of chemical information. WHIM descriptors contain information about the whole 3D-molecular structure in terms of size, shape, symmetry and atom distribution. These indices are calculated from (x,y,z)-coordinates of a molecule within different weighting schemes in a straightforward manner and represent a very general approach to describe molecules in a unitary conceptual framework. A. set of 40 simple heterogeneous compounds is used to show the main characteristics, some properties and the modelling power of WHIM descriptors by using simple scatter plots of the descriptors, Principal Component Analysis and predictions of simple physicochemical properties.