ArticleJournal of computational chemistry2014
Modeling biophysical and biological properties from the characteristics of the molecular electron density, electron localization and delocalization matrices, and the electrostatic potential.
Article in Journal of computational chemistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed.
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- Development and Validation of Atomic Group Descriptors for Substituent Effects.Journal of computational chemistry · 2025Article
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- Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning.RSC advances · 2024Article
- Effect of a Substituent on the Properties of Salicylaldehyde Hydrazone Derivatives.The Journal of organic chemistry · 2023Article
- Analysis of the uncharted, druglike property space by self-organizing maps.Molecular diversity · 2022Article
- A combined study on structures and vibrational spectra of the antiviral rimantadine using SQMFF and DFT calculations.Heliyon · 2022Article
- Anti-Ebola: an initiative to predict Ebola virus inhibitors through machine learning.Molecular diversity · 2022Article
- Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.Molecular diversity · 2021Article
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Abstract
The electron density and the electrostatic potential are fundamentally related to the molecular hamiltonian, and hence are the ultimate source of all properties in the ground- and excited-states. The advantages of using molecular descriptors derived from these fundamental scalar fields, both accessible from theory and from experiment, in the formulation of quantitative structure-to-activity and structure-to-property relationships, collectively abbreviated as QSAR, are discussed. A few such descriptors encode for a wide variety of properties including, for example, electronic transition energies, pK(a)'s, rates of ester hydrolysis, NMR chemical shifts, DNA dimers binding energies, π-stacking energies, toxicological indices, cytotoxicities, hepatotoxicities, carcinogenicities, partial molar volumes, partition coefficients (log P), hydrogen bond donor capacities, enzyme-substrate complementarities, bioisosterism, and regularities in the genetic code. Electronic fingerprinting from the topological analysis of the electron density is shown to be comparable and possibly superior to Hammett constants and can be used in conjunction with traditional bulk and liposolubility descriptors to accurately predict biological activities. A new class of descriptors obtained from the quantum theory of atoms in molecules' (QTAIM) localization and delocalization indices and bond properties, cast in matrix format, is shown to quantify transferability and molecular similarity meaningfully. Properties such as "interacting quantum atoms (IQA)" energies which are expressible into an interaction matrix of two body terms (and diagonal one body "self" terms, as IQA energies) can be used in the same manner. The proposed QSAR-type studies based on similarity distances derived from such matrix representatives of molecular structure necessitate extensive investigation before their utility is unequivocally established.
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