Quantum chemical descriptors based on semiempirical methods for large biomolecules

Abstract

In this Review, we reviewed the efforts to expand the applications of conceptual density functional theory reactivity descriptors and hard and soft acid and base principles for macromolecules and other strategies that focused on low-level quantum chemistry methods. Currently, recent applications are taking advantage of modifications of these descriptors using semiempirical electronic structures to explain enzymatic catalysis reactions, protein-binding processes, and structural analysis in proteins. We have explored these new solutions along with their implementations in the software PRIMoRDiA, discussing their impact on the field and its perspectives. We show the main issues in the analysis of the electronic structure of macromolecules, which are the application of the same calculation protocols used for small molecules without considering particularities in those large systems’ electronic configuration. The major result of our discussions is that the use of semiempirical methods is crucial to obtain such a type of analysis, which can provide a powerful dimension of information and be part of future low-cost predictive tools. We expect semiempirical methods continue playing an important role in the quantum chemistry evaluation of large molecules. As computational resources advance, semiempirical methods might lead us to explore the electronic structure of even larger biological macromolecular entities and sets of structures representing larger timescales.

Pentafuhalol-B, a Phlorotannin from Brown Algae, Strongly Inhibits the PLK-1 Overexpression in Cancer Cells as Revealed by Computational Analysis

“…The chosen basis set overlaps with a surrounding atom, which has an impact on the minimisation process [33,34]. Overall, our prediction and study demonstrated that PtB displayed higher stability and bioactivity, as it has a reduced energy gap (E HOMO -E LUMO ), less hardness, and more softness compared with the other phlorotannins when compared to volasertib [35,36]. As a result, PtB may become increasingly chemically reactive as it approaches the target protein (PLK-1).…”

A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide‐resistant Mycobacterium tuberculosis

“…56 The use of quantum descriptors in this study is validated by works such as that of Sifonte et al (2021), who used quantum mechanics to elucidate the toxicity of metal oxide nanoparticles in human keratin cells. 57 In addition, Grillo et al (2023) showed that quantum descriptors can provide valuable insights into the electronic structure of biological macromolecules relevant to processes such as catalysis and protein binding. 58 However, the intermediate values of Comp4, particularly its second highest chemical potential (μ), may indicate possible interactions with DNA or generation of cardiotoxic reactive oxygen species.…”

“…57 In addition, Grillo et al (2023) showed that quantum descriptors can provide valuable insights into the electronic structure of biological macromolecules relevant to processes such as catalysis and protein binding. 58 However, the intermediate values of Comp4, particularly its second highest chemical potential (μ), may indicate possible interactions with DNA or generation of cardiotoxic reactive oxygen species. 59 In contrast, Comp1, with its increased reactivity and electrophilicity, raises concerns about off-target effects and potential damage to DNA and cell membranes.…”

Solvate Suite: A Command-Line Interface for Molecular Simulations and Multiscale Microsolvation Modeling

“…Molecular simulation is an essential tool for studying and understanding chemical processes on the atomic scale. The use of specialized programs enables comprehensive exploration of structural, thermodynamic, and electronic properties within complex chemical systems, contributing to a wide range of applications including drug development, material design, and biochemical mechanism studies. − Molecular dynamics packages commonly offer various approaches for performing simulations. Consequently, the use of simulation tools usually requires specific knowledge of different programs, each with its own set of features. − Multiple developments by diverse research groups have led to fragmentation in the process of computational experimentation that can make it difficult to integrate the information obtained between the different programs used.…”