The structure of DNA fragments: Quantum-chemical modelling

In this review, we analyze and systematize our computational studies of the nucleic acid duplex formations and thermodynamic stability under the different factors of investigation. The proposed structural models of mini-helix contains N nucleobase pairs (N = 3-5); QM structural data suggest that the helical conformations of mini-helix adopt geometrical parameters comparable to those of natural A- and B-DNA forms under specific conditions as micro hydration and charge compensation. The gas-phase models adopt non regular conformations between the helical form and a ladder form.. The natural helical shape of DNA mini-helix is stabilized by the presence of counterions or by explicit micro-hydration of the major and minor groves. The presence of aqueous solution is shown as a minor factor for the helical shape formation. The studies are performed at the level of density functional theory

Auto3D: Automatic Generation of the Low-energy 3D Structures with ANI Neural Network Potentials

Computational programs accelerate the chemical discovery processes but often need proper 3-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing a huge space of stereoisomers and conformers. We developed the Python-based Auto3D package for generating the low-energy 3D structures using SMILES as the input. Auto3D is based on state-of-the-art algorithms and can automatize the isomer enumeration and duplicate filtering process, 3D building process, geometry optimization and ranking process. Tested on 50 molecules with multiple unspecified stereocenters, Auto3D is guaranteed to find the stereo-configuration that yields the lowest-energy conformer. With Auto3D we provide an extension of the ANI model. The new model, dubbed ANI-2xt, is trained on a tautomer-rich dataset. ANI-2xt is benchmarked with DFT methods on geometry optimization, electronic and Gibbs free energy calculations. Compared with ANI-2x, ANI-2xt provides a 42% error reduction for tautomeric reaction energy calculations when using the gold-standard coupled-cluster calculation as the reference. ANI-2xt can accurately predict the energies and is several orders of magnitude faster than DFT methods

Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials

Computational programs accelerate the chemical discovery processes but often need proper three-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing a huge space of stereoisomers and conformers. We developed the Python-based Auto3D package for generating the low-energy 3D structures using SMILES as the input. Auto3D is based on state-of-the-art algorithms and can automatize the isomer enumeration and duplicate filtering process, 3D building process, geometry optimization, and ranking process. Tested on 50 molecules with multiple unspecified stereocenters, Auto3D is guaranteed to find the stereoconfiguration that yields the lowest-energy conformer. With Auto3D, we provide an extension of the ANI model. The new model, dubbed ANI-2xt, is trained on a tautomer-rich data set. ANI-2xt is benchmarked with DFT methods on geometry optimization and electronic and Gibbs free energy calculations. Compared with ANI-2x, ANI-2xt provides a 42% error reduction for tautomeric reaction energy calculations when using the gold-standard coupled-cluster calculation as the reference. ANI-2xt can accurately predict the energies and is several orders of magnitude faster than DFT methods

Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials

Computational programs accelerate the chemical discovery processes but often need proper three-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing a huge space of stereoisomers and conformers. We developed the Python-based Auto3D package for generating the low-energy 3D structures using SMILES as the input. Auto3D is based on state-of-the-art algorithms and can automatize the isomer enumeration and duplicate filtering process, 3D building process, geometry optimization, and ranking process. Tested on 50 molecules with multiple unspecified stereocenters, Auto3D is guaranteed to find the stereoconfiguration that yields the lowest-energy conformer. With Auto3D, we provide an extension of the ANI model. The new model, dubbed ANI-2xt, is trained on a tautomer-rich data set. ANI-2xt is benchmarked with DFT methods on geometry optimization and electronic and Gibbs free energy calculations. Compared with ANI-2x, ANI-2xt provides a 42% error reduction for tautomeric reaction energy calculations when using the gold-standard coupled-cluster calculation as the reference. ANI-2xt can accurately predict the energies and is several orders of magnitude faster than DFT methods

Structural Waters in the Minor and Major Grooves of DNAA Major Factor Governing Structural Adjustments of the A–T Mini-Helix

The role of microhydration in structural adjustments of the AT-tract in B-DNA was studied at the B97-D/def2-SV­(P) level. The (dA:dT)₅ complexes with 10 water molecules in minor and 15 water molecules in major grooves were studied. The obtained network of hydrogen bonds revealed the dependence between the groove width and the types of water patterns. In the minor groove, the following patterns were observed: interstrand one-water bridges similar to that of the Dickerson “water spine” and interstrand two-water bridges. The network of structural waters in the major groove is more diverse than that in the minor groove, which agrees with crystallographic data. As the major groove is wider, it is enriched by water molecules forming two- and three-water bridges. Results suggest the nucleobase–water interactions in both grooves prevent AT-tract twisting and its “collapse” along the minor groove. Whereby, a helix structure with narrow minor and wide major grooves is formed. The structural waters affect the polynucleotide conformation so that it becomes similar to poly­(dA)·poly­(dT) in fibers and acquires features of the A-tracts in DNA in solution. We suggest that formation of specific water patterns in both grooves is the factor responsible for stabilization of A-tracts with a narrowed minor groove, leading in turn to their strong intrinsic bending in DNA

Structure and Binding Energy of Double-Stranded A‑DNA Mini-helices: Quantum-Chemical Study

A-DNA is thought to play a significant biological role in gene expression due to its specific conformation and binding features. In this study, double-stranded mini-helices (dA:dT)₃ and (dG:dC)₃ in A-like DNA conformation were investigated. M06-2X/6-31G­(d,p) method has been utilized to identify the optimal geometries and predict physicochemical parameters of these systems. The results show the ability of the corresponding mini-helices to preserve their A-like conformation under the influences of solvent, charge, and Na⁺ counterions. Presented structural and energetic data offer evidence that two steps of GG/CC or AA/TT are already enough to turn the DNA helix to generate different forms by favoring specific values of roll and slide at a local level. Our calculations support the experimentally known fact that AA/TT steps prefer the B-form over the A-ones, whereas GG/CC steps may be found in either the B- or A-form. The stability of mini-helices at the level of total energy analysis, Δ<i>E</i>_total^(A–B), is discussed