Molecular properties visualization

The total molecular energy is invariant to all transformations involving basis orbitals, just as any physical event is invariant under any transformation of coordinates. But just as the proper choice of coordinates helps in visualizing physical events, so the choice of the proper orbital basis is helpful in visualizing molecular properties. 

This small dataset is used to visualize molecular properties such as chemical scaffold, functional groups, pharmacological profile, etc., that are recognized and interpreted by the diversity computation algorithms. 

In its most general form the name "correlation diagram" denotes the schematic graphical dependence of some molecular property on the systematic variation of a certain geometrical parameters. In dependence on what exactly is the visualized molecular property, the correlation diagrams can be of various types. Thus, e.g., when the displayed quantity is the energy of individual molecular orbitals, we speak of orbital correlation diagrams. Another possible choice is to display the variation of... 

Besides molecular orbitals, other molecular properties, such as electrostatic potentials or spin density, can be represented by isovalue surfaces. Normally, these scalar properties are mapped onto different surfaces see above). This type of high-dimensional visualization permits fast and easy identification of the relevant molecular regions. 

The representation of molecular properties on molecular surfaces is only possible with values based on scalar fields. If vector fields, such as the electric fields of molecules, or potential directions of hydrogen bridge bonding, need to be visualized, other methods of representation must be applied. Generally, directed properties are displayed by spatially oriented cones or by field lines. 

Since e > eo, we seek to explain the smaller field in the presence of the dielectric in terms of molecular properties and the way in which they are affected by the electric field. An easy way to visualize the effect is to picture an opposing surface charge-indicated as in Fig. 10.4b—accumulating on the dielectric. This partially offsets the charge on the capacitor plates to a net charge density a - so that Eq becomes E and is given by... 

We contend therefore that introduction of molecular modeling very early into the currieulum need not complicate or eonfuse the learning of organie chemistry, but rather assist the student in visualizing the structures of organic molecules and in learning the intimate connections between molecular structure and molecular properties. 

Molecular modeling seeks to answer questions about molecular properties— stabilities, reactivities, electronic properties—as they are related to molecular structure. The visualization and analysis of such structures, as well as their molecular properties and molecular interactions, are based on some theoretical means for predicting the structures and properties of molecules and complexes. If an algorithm can be developed to calculate a structure with a given stoichiometry and connectivity, one can then attempt to compute properties based on calculated molecular structure and vice versa. 

UNIVIS-2000, The molecular properties visualization package, developed at the Theoretical Chemistry Group, Department of Chemistry, University of Pune, Pune, India http //chem.unipune.emet.in/univis.html. See also Limaye, A. C. and Gadre, S. R. Curr. Sci. (India) 2001, 80, 1296. 

The microscopic world of atoms is difficult to imagine, let alone visualize in detail. Chemists and chemical engineers employ different molecular modelling tools to study the structure, properties, and reactivity of atoms, and the way they bond to one another. Richard Bader, a chemistry professor at McMaster University, has invented an interpretative theory that is gaining acceptance as an accurate method to describe molecular behaviour and predict molecular properties. According to Dr. Bader, shown below, small molecules are best represented using topological maps, where contour lines (which are commonly used to represent elevation on maps) represent the electron density of molecules. 

A very powerful tool of visualizing three-dimensional molecular properties, including potential surfaces, is computer graphics.(32) Computer graphics is particularly useful in the qualitative comparison of two or more molecules. 

Fig. 15.6. Seamless integration between PGVL Hub and SpotFire. User can launch SpotFire within PGVL Hub to visualize the molecular properties associated with a molecule collection. Any selection done within SpotFire is dynamically passed back to PGVL Hub as marking on individual molecules. And user then can use the Decision Maker within PGVL Hub to make selections based on the SpotFire marking.

The importance of visual inspection Visual inspection of reactants and product molecules offers a library designer tremendous value in terms of what product molecules can or cannot be synthesized to help formulate and address SAR hypotheses. Project medicinal chemists have fondly called this popular approach cerebral processing. PGVL Hub has provided a capable environment to enable this approach (e.g., Structural Viewer panel with many molecules per page for fast browsing, sorting of displayed molecules by molecular properties, and multiple color markers to label molecules for further processing). 

Visualization and analysis of structures, molecular properties (thermodynamics, reactivity, spectroscopy), and molecular interactions, based on a theoretical means for predicting the structures and properties of molecules and complexes (see computer-assisted molecular design). 

Other molecular properties and phenomena that can benefit from the aid of visualization are the distribution of unpaired electron spin in radicals and the changes in orbitals and charge distribution as a reaction progresses. These and many other... 

An alternative to dimension reduction is the use of composite and uncorrelated descriptors that are suitable for the design of information-rich yet low-dimensional chemical spaces. An elegant example is presented by the popular BCUT (Burden-CAS-University of Texas) descriptors (Pearlman and Smith 1998). BCUTs are a set of uncorrelated descriptors that combine information about molecular connectivity, inter-molecular distances, and other molecular properties. BCUT spaces used for many applications are typically only six-dimensional and can frequently be further reduced to 3D representations for visualization purposes by identifying those BCUT axes around which most compounds map. 

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