Design of molecules from quantitative structure-activity relationship models. 3. Role of higher order path counts: Path 3

Hall, Lowell H.; Dailey, Robert S.; Kier, Lemont B.

doi:10.1021/ci00014a012

Cited by 39 publications

(34 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The main challenge of in silico molecular design approaches is generation of structural fragments from de facto modeling descriptors. Inverse-QSAR is an attempt in this direction [83][84][85][86][87][88][89]. Developments in new metrics are required to address different features of drug-receptor interactions so far not tamed.…”

Section: Resultsmentioning

confidence: 99%

“…Most of the developments in inverse QSAR revolve around the graph theoretical concepts. It is associated with the reconstruction of structural fragments from the vertex and edge information of descriptors present in identified QSAR equations [83]. It is a mathematical strategy to predict structures of interest from the descriptors of QSAR equations.…”

Section: Graph Reconstruction (Inverse Qsar)mentioning

confidence: 99%

See 1 more Smart Citation

Chemical Structure Indices in In Silico Molecular Design

Prabhakar

2008

Sci Pharm

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Section: Graph Reconstruction (Inverse Qsar)mentioning

confidence: 99%

Chemical Structure Indices in In Silico Molecular Design

Prabhakar

2008

Sci Pharm

View full text Add to dashboard Cite

“…using techniques that generate exhaustive lists of molecular structures matching predefined descriptor values. In a series of three papers Kier, Hall, and co-workers reconstructed molecular structures from the count of paths, l P, up to length l=3 [20][21][22]. Their technique essentially computes all the possible degree sequences matching the count of paths up to length l=2.…”

Section: Reverse Engineering Methodsmentioning

confidence: 99%

Reverse engineering chemical structures from molecular descriptors: how many solutions?

Faulon

Brown

Martin

2005

J Comput Aided Mol Des

View full text Add to dashboard Cite

Physical, chemical and biological properties are the ultimate information of interest for chemical compounds. Molecular descriptors that map structural information to activities and properties are obvious candidates for information sharing. In this paper, we consider the feasibility of using molecular descriptors to safely exchange chemical information in such a way that the original chemical structures cannot be reverse engineered. To investigate the safety of sharing such descriptors, we compute the degeneracy (the number of structure matching a descriptor value) of several 2D descriptors, and use various methods to search for and reverse engineer structures. We examine degeneracy in the entire chemical space taking descriptors values from the alkane isomer series and the PubChem database. We further use a stochastic search to retrieve structures matching specific topological index values. Finally, we investigate the safety of exchanging of fragmental descriptors using deterministic enumeration.

show abstract

“…In de novo molecular design [1] based on quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR), [2] evolutionary algorithms (EAs) [3,4] and inverse QSPR/QSAR [5][6][7][8] are promising methods for producing chemical structures with desired properties or activities. In EAs, evolutionary operations are directly applied to chemical structures, [9,10] and an evaluation function legitimizes the modified structures for next iterations (generations).…”

Section: Introductionmentioning

confidence: 99%

Finding Chemical Structures Corresponding to a Set of Coordinates in Chemical Descriptor Space

Miyao

Funatsu

2017

Mol. Inf.

View full text Add to dashboard Cite

When chemical structures are searched based on descriptor values, or descriptors are interpreted based on values, it is important that corresponding chemical structures actually exist. In order to consider the existence of chemical structures located in a specific region in the chemical space, we propose to search them inside training data domains (TDDs), which are dense areas of a training dataset in the chemical space. We investigated TDDs' features using diverse and local datasets, assuming that GDB11 is the chemical universe. These two analyses showed that considering TDDs gives higher chance of finding chemical structures than a random search-based method, and that novel chemical structures actually exist inside TDDs. In addition to those findings, we tested the hypothesis that chemical structures were distributed on the limited areas of chemical space. This hypothesis was confirmed by the fact that distances among chemical structures in several descriptor spaces were much shorter than those among randomly generated coordinates in the training data range

show abstract

Design of molecules from quantitative structure-activity relationship models. 3. Role of higher order path counts: Path 3

Cited by 39 publications

References 9 publications

Chemical Structure Indices in In Silico Molecular Design

Chemical Structure Indices in In Silico Molecular Design

Reverse engineering chemical structures from molecular descriptors: how many solutions?

Finding Chemical Structures Corresponding to a Set of Coordinates in Chemical Descriptor Space

Contact Info

Product

Resources

About