Property landscapes

The identification and optimisation of drug-like small molecule inhibitors for kinase targets is a highly competitive arena and given the high level of structural similarity across family members it is unsurprising that the intellectual property landscape has become crowded, especially around some of the more validated targets. The situation is particularly apparent for type I kinase... 

Jensen K, Murray F (2005). Enhanced Intellectnal property landscape of the hnman genome. Science. 310 239-240. 

Jensen, K., Murray, F. Intellectual property landscape of the human genome. Science 2005, 310, 239-240. 

The concept of activity landscapes can also be extended to property landscapes where any set of measurable molecular properties can be added as another dimension to the chemical space of a compound dataset [146], In line with the concept of activity cliffs, odor cliffs [181] and flavor cliffs [182] have been recently described. 

SAS maps have also been used to represent consensus models of activity landscapes by means of fusing similarity measures obtained from different 2D and 3D molecule representations and similarity functions [145,189,191]. In addition, SAS maps were recently adapted to model multitarget activity landscapes by representing in one axis the activity similarity of compound datasets screened across multiple biological endpoints [192]. SAS maps have been extended to characterize property landscapes other than activity landscapes. For example, stmcture-flavor similarity maps have been proposed to systematically characterize stmcture-flavor associations of a comprehensive flavor database [182]. A number of additional types of 2D MFS maps that characterize a different fusion-based similarity on each axis have also been developed and are described in Section 15.5.3. 

Although few publications on novel formulation technologies are available in the literature (Becker et al., 1997 Hasan et al., 2010), the intellectual property landscape is filled with composition of matter patents and patent apphcations... 

While the chemical universe of molecitles potentially relevant in food science is considerably smaller, it nonetheless is large enough to benefit from many of the chemical informatic concepts that have proved useful in medicinal chemistry and related fields of chemistry. Two of these concepts, molecttlar similarity and chemical space (CS), are dealt with in this chapter. Of the two, molecular similarity is more fundamental since it plays a cmcial role in the definition of CS itself. Though important, activity or property landscapes, which provide the third leg of a triad of activities that play important roles in much of chemical informatics, will not be discussed here. Numerous recent publications describing the visual and statistical aspects of activity landscapes as well as the basic features of these landscapes should be consrrlted for details [4-8],... 

Over the past two decades, computational methods have been playing an ever-in-creasing role in drag discovery research due especially to the burgeoning amount of data being generated by ever faster and more powerful experimental techniques. Three concepts, molecular similarity, CS, and activity/property landscapes, in some fashion underlie all of these methods— the current woik addresses molecular/strac-tural similarity and CS, two important pillars supporting the edifice of chemical informatics. 

Many factors affect the mechanisms and kinetics of sorption and transport processes. For instance, differences in the chemical stmcture and properties, ie, ionizahility, solubiUty in water, vapor pressure, and polarity, between pesticides affect their behavior in the environment through effects on sorption and transport processes. Differences in soil properties, ie, pH and percentage of organic carbon and clay contents, and soil conditions, ie, moisture content and landscape position climatic conditions, ie, temperature, precipitation, and radiation and cultural practices, ie, crop and tillage, can all modify the behavior of the pesticide in soils. Persistence of a pesticide in soil is a consequence of a complex interaction of processes. Because the persistence of a pesticide can govern its availabiUty and efficacy for pest control, as weU as its potential for adverse environmental impacts, knowledge of the basic processes is necessary if the benefits of the pesticide ate to be maximized. 

Kauffman ([kauffSO], [kauffOOa]) has introduced a class of parametrizable fitness landscapes called NK-landscapes, that provide a formalism for studying the efficacy of GA evolution as a function of certain statistical properties of the landscape. Given N binary variables Xi = 1, so that x = (xi, X2, , Xjv) represents a vertex of an A -dimensional hypercube, an NK-landscape is defined by a fitness function, JF, of the form... 

Worldwide suppliers with bioengineering capabilities are displacing established polymers with cost-effective and higher performing plastics. An explosion of novel polymers has been made by enzymatic control. The use of enzymes for polymerization has drastically altered the landscape of polymer chemistry. Processors can request specific properties for each application as opposed to the usual making do with what is available. The supplier can deliver to the processor desired properties requested. 

Based on the descriptions of spatial variation in each environmental compartment, multimedia models can be categorized into multimedia compartmental models (MCMs) [3-20], spatial multimedia models (SMs) [21-24] and spatial multimedia compartmental models (SMCMs) [25-27]. MCMs assume homogeneous landscape properties in each medium and assume all environmental compartments are well mixed. SMs are collections of single-media models in which the output of one model serves as the input to the others. Each individual model in the SMs is a spatial model describing the variation of environmental properties in one or more directions. SMCMs are similar to MCMs, but consider one or more environmental compartments as nonuniform regions. 

Cavigelli MA, Lengnick LL, Buyer JS, Fravel D, Handoo Z, McCarty G, Millner P, Sikora L, Wright S, Vinyard B, Rabenhorst M. Landscape level variation in soil resources and microbial properties in a no-till corn field. Appl. Soil Ecol. 2005 29 99-123. 

In order to further explore the properties of the landscape formed by the sum of squares as a function of parameters, we concentrate on a slightly more... 

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