ABSTRACT Using compounds occupying four distinct clog P/molecular weight regions that define opti... more ABSTRACT Using compounds occupying four distinct clog P/molecular weight regions that define optimal and sub-optimal chemical space, and a developability score derived from solubility, permeability, protein binding and 3A4 inhibition screening data, OPLS regression models were constructed to determine which physico-chemical properties were most correlated with developability. The results suggested that whilst certain molecule properties were important for developability across all chemical space, such as [clog D + aromatic ring count], [clog D + (aromatic atom count – sp3 carbon count)] and [sp3 carbon count/total carbon count], others such as heteroaliphatic ring count, positive ionisable group count and H-bond donor character exhibited varying degrees of importance depending on the clog P/Mw region.
ABSTRACT Aqueous solubility, protein binding and CYP450 inhibition data for compounds containing ... more ABSTRACT Aqueous solubility, protein binding and CYP450 inhibition data for compounds containing a variety of heteroaromatic and heteroaliphatic rings were analysed and compared to determine which ring types fared best and worst in these developability screens. The results suggest that certain heterorings are generally more developable than others: how this information may be used and some caveats to be borne in mind are discussed.
Traditional methods for performing 3D-QSAR rely upon an alignment step that is often time-consumi... more Traditional methods for performing 3D-QSAR rely upon an alignment step that is often time-consuming and can introduce user bias, the resultant model being dependent upon and sensitive to the alignment used. There are several methods which overcome this problem, but in general the necessary transformations prevent a simple interpretation of the resultant models in the original descriptor space (i.e. 3D molecular coordinates). Here we present a novel class of molecular descriptors which we have termed GRid-INdependent Descriptors (GRIND). They are derived in such a way as to be highly relevant for describing biological properties of compounds while being alignment-independent, chemically interpretable, and easy to compute. GRIND are obtained starting from a set of molecular interaction fields, computed by the program GRID or by other programs. The procedure for computing the descriptors involves a first step, in which the fields are simplified, and a second step, in which the results are encoded into alignment-independent variables using a particular type of autocorrelation transform. The molecular descriptors so obtained can be used to obtain graphical diagrams called "correlograms" and can be used in different chemometric analyses, such as principal component analysis or partial least-squares. An important feature of GRIND is that, with the use of appropriate software, the original descriptors (molecular interaction fields) can be regenerated from the autocorrelation transform and, thus, the results of the analysis represented graphically, together with the original molecular structures, in 3D plots. In this respect, the article introduces the program ALMOND, a software package developed in our group for the computation, analysis, and interpretation of GRIND. The use of the methodology is illustrated using some examples from the field of 3D-QSAR. Highly predictive and interpretable models are obtained showing the promising potential of the novel descriptors in drug design.
... Two approaches have been adopted for encoding structural information in bit strings. ... In p... more ... Two approaches have been adopted for encoding structural information in bit strings. ... In principle, this should lead to Page 10. 10 Molecular Diversity and Combinatorial Libra y Design better retrieval performance in substructure or similarity searching, whatever the query. ...
Journal of Chemical Information and Modeling, Sep 28, 2010
Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the ef... more Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.
Recently, one of the key trends in the pharmaceutical industry has been the integration of what h... more Recently, one of the key trends in the pharmaceutical industry has been the integration of what have traditionally been considered 'development' activities into the early phases of drug discovery. The aim of this paradigm shift is the prompt identification and elimination of candidate molecules that are unlikely to survive later stages of discovery and development. In this review, the authors examine the growing role that is being played by computational methods in this filtering process, with a particular focus on the prediction of intestinal absorption and blood-brain barrier penetration.
ABSTRACT Using compounds occupying four distinct clog P/molecular weight regions that define opti... more ABSTRACT Using compounds occupying four distinct clog P/molecular weight regions that define optimal and sub-optimal chemical space, and a developability score derived from solubility, permeability, protein binding and 3A4 inhibition screening data, OPLS regression models were constructed to determine which physico-chemical properties were most correlated with developability. The results suggested that whilst certain molecule properties were important for developability across all chemical space, such as [clog D + aromatic ring count], [clog D + (aromatic atom count – sp3 carbon count)] and [sp3 carbon count/total carbon count], others such as heteroaliphatic ring count, positive ionisable group count and H-bond donor character exhibited varying degrees of importance depending on the clog P/Mw region.
ABSTRACT Aqueous solubility, protein binding and CYP450 inhibition data for compounds containing ... more ABSTRACT Aqueous solubility, protein binding and CYP450 inhibition data for compounds containing a variety of heteroaromatic and heteroaliphatic rings were analysed and compared to determine which ring types fared best and worst in these developability screens. The results suggest that certain heterorings are generally more developable than others: how this information may be used and some caveats to be borne in mind are discussed.
Traditional methods for performing 3D-QSAR rely upon an alignment step that is often time-consumi... more Traditional methods for performing 3D-QSAR rely upon an alignment step that is often time-consuming and can introduce user bias, the resultant model being dependent upon and sensitive to the alignment used. There are several methods which overcome this problem, but in general the necessary transformations prevent a simple interpretation of the resultant models in the original descriptor space (i.e. 3D molecular coordinates). Here we present a novel class of molecular descriptors which we have termed GRid-INdependent Descriptors (GRIND). They are derived in such a way as to be highly relevant for describing biological properties of compounds while being alignment-independent, chemically interpretable, and easy to compute. GRIND are obtained starting from a set of molecular interaction fields, computed by the program GRID or by other programs. The procedure for computing the descriptors involves a first step, in which the fields are simplified, and a second step, in which the results are encoded into alignment-independent variables using a particular type of autocorrelation transform. The molecular descriptors so obtained can be used to obtain graphical diagrams called "correlograms" and can be used in different chemometric analyses, such as principal component analysis or partial least-squares. An important feature of GRIND is that, with the use of appropriate software, the original descriptors (molecular interaction fields) can be regenerated from the autocorrelation transform and, thus, the results of the analysis represented graphically, together with the original molecular structures, in 3D plots. In this respect, the article introduces the program ALMOND, a software package developed in our group for the computation, analysis, and interpretation of GRIND. The use of the methodology is illustrated using some examples from the field of 3D-QSAR. Highly predictive and interpretable models are obtained showing the promising potential of the novel descriptors in drug design.
... Two approaches have been adopted for encoding structural information in bit strings. ... In p... more ... Two approaches have been adopted for encoding structural information in bit strings. ... In principle, this should lead to Page 10. 10 Molecular Diversity and Combinatorial Libra y Design better retrieval performance in substructure or similarity searching, whatever the query. ...
Journal of Chemical Information and Modeling, Sep 28, 2010
Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the ef... more Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.
Recently, one of the key trends in the pharmaceutical industry has been the integration of what h... more Recently, one of the key trends in the pharmaceutical industry has been the integration of what have traditionally been considered 'development' activities into the early phases of drug discovery. The aim of this paradigm shift is the prompt identification and elimination of candidate molecules that are unlikely to survive later stages of discovery and development. In this review, the authors examine the growing role that is being played by computational methods in this filtering process, with a particular focus on the prediction of intestinal absorption and blood-brain barrier penetration.
Uploads