Investigation of solvent effect and NMR shielding tensors of p53 tumor-suppressor gene in drug design

The p53 tumor-suppressor gene encodes a nuclear phosphoprotein with cancer- inhibiting properties. The most probable cancerous mutations occur as point mutations in exons 5 up to 8 of p53, as a base pair substitution that encompasses CUA and GAT sequences. As DNA drug design represents a direct genetic treatment of cancer, in the research reported computational drug design was carried out to explore, at the Hartree–Fock level, effects of solvents on the thermochemical properties and nuclear magnetic resonance (NMR) shielding tensors of some atoms of CUA involved in the hydrogen-bonding network. The observed NMR shielding variations of the solutes caused by solvent change seemed significant and were attributed to solvent polarity, and solute–solvent and solvent–solute hydrogen-bonding interactions. The results provide a reliable insight into the nature of mutation processes. However, to improve our knowledge of the hydration pattern more rigorous computations of the hydrated complexes are needed

QSAR models and scaffold-based analysis of non-nucleoside HIV RT inhibitors

© 2015 Elsevier B.V. A selection of 289 pyrimidine derivatives with anti-HIV RT activities as non-nucleoside HIV RT inhibitors (NNRTI) were studied. The associative neural network (ASNN) method was applied to develop a quantitative structure-activity relationship (QSAR) for anti-HIV RT activity. The calculated models were validated using the bagging approach. A consensus model with R2=0.87 and RMSE=0.5 was obtained from 10 individual models. Scaffold analysis and molecular docking of the compounds used in the QSAR model identified a potential chemical scaffold. The results showed that scaffold-based analysis of the QSAR model could be helpful in identifying potent scaffolds for further exploration than analyzing the overall model. Matched molecular pair analysis (MMPA) was applied in the QSAR model to characterize molecular transformations causing a significant change in the anti-HIV activity. The linear QSAR model was calculated to explore the structural features important for NNRTI activity. The results revealed that the activity of NNRT inhibitors is strongly dependent on their aromaticity and structural flexibility. The scaffold-based analysis of QSAR models with molecular docking and MMPA was found to be helpful in characterizing potential scaffolds for anti-HIV RT derivatives. The outcome of this study provides a deeper insight into the computer-aided scaffold-based design of novel molecules with HIV RT activities. It was also clearly shown that the consensus model's failure to correctly predict new chemical series could be due to the limitation of its applicability domain (AD). Redevelopment of models using new measurements can dramatically increase their AD and performance

QSAR analysis on tacrine-related acetylcholinesterase inhibitors

Background: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer's disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous interest, and for this reason we establish Quantitative Structure-Activity Relationships on their Acetylcholinesterase inhibitory activity. Results: Ten groups of new developed Tacrine-related inhibitors are explored, which have been experimentally measured in different biochemical conditions and AChE sources. The number of included descriptors in the structure-activity relationship is characterized by 'Rule of Thumb'. The 1502 applied molecular descriptors could provide the best linear models for the selected Alzheimer's data base and the best QSAR model is reported for the considered data sets. Conclusion: The QSAR models developed in this work have a satisfactory predictive ability, and are obtained by selecting the most representative molecular descriptors of the chemical structure, represented through more than a thousand of constitutional, topological, geometrical, quantum-mechanical and electronic descriptor types.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

QSAR models and scaffold-based analysis of non-nucleoside HIV RT inhibitors.

A selection of 289 pyrimidine derivatives with anti-HIV RT activities as non-nucleoside HIV RT inhibitors (NNRTI) were studied. The associative neural network (ASNN) method was applied to develop a quantitative structure-activity relationship (QSAR) for anti-HIV RT activity. The calculated models were validated using the bagging approach. A consensus model with R2=0.87 and RMSE=0.5 was obtained from 10 individual models. Scaffold analysis and molecular docking of the compounds used in the QSAR model identified a potential chemical scaffold. The results showed that scaffold-based analysis of the QSAR model could be helpful in identifying potent scaffolds for further exploration than analyzing the overall model. Matched molecular pair analysis (MMPA) was applied in the QSAR model to characterize molecular transformations causing a significant change in the anti-HIV activity. The linear QSAR model was calculated to explore the structural features important for NNRTI activity. The results revealed that the activity of NNRT inhibitors is strongly dependent on their aromaticity and structural flexibility. The scaffold-based analysis of QSAR models with molecular docking and MMPA was found to be helpful in characterizing potential scaffolds for anti-HIV RT derivatives. The outcome of this study provides a deeper insight into the computer-aided scaffold-based design of novel molecules with HIV RT activities. It was also clearly shown that the consensus model's failure to correctly predict new chemical series could be due to the limitation of its applicability domain (AD). Redevelopment of models using new measurements can dramatically increase their AD and performance

QSAR models and scaffold-based analysis of non-nucleoside HIV RT inhibitors

© 2015 Elsevier B.V. A selection of 289 pyrimidine derivatives with anti-HIV RT activities as non-nucleoside HIV RT inhibitors (NNRTI) were studied. The associative neural network (ASNN) method was applied to develop a quantitative structure-activity relationship (QSAR) for anti-HIV RT activity. The calculated models were validated using the bagging approach. A consensus model with R2=0.87 and RMSE=0.5 was obtained from 10 individual models. Scaffold analysis and molecular docking of the compounds used in the QSAR model identified a potential chemical scaffold. The results showed that scaffold-based analysis of the QSAR model could be helpful in identifying potent scaffolds for further exploration than analyzing the overall model. Matched molecular pair analysis (MMPA) was applied in the QSAR model to characterize molecular transformations causing a significant change in the anti-HIV activity. The linear QSAR model was calculated to explore the structural features important for NNRTI activity. The results revealed that the activity of NNRT inhibitors is strongly dependent on their aromaticity and structural flexibility. The scaffold-based analysis of QSAR models with molecular docking and MMPA was found to be helpful in characterizing potential scaffolds for anti-HIV RT derivatives. The outcome of this study provides a deeper insight into the computer-aided scaffold-based design of novel molecules with HIV RT activities. It was also clearly shown that the consensus model's failure to correctly predict new chemical series could be due to the limitation of its applicability domain (AD). Redevelopment of models using new measurements can dramatically increase their AD and performance

QSAR models and scaffold-based analysis of non-nucleoside HIV RT inhibitors

© 2015 Elsevier B.V. A selection of 289 pyrimidine derivatives with anti-HIV RT activities as non-nucleoside HIV RT inhibitors (NNRTI) were studied. The associative neural network (ASNN) method was applied to develop a quantitative structure-activity relationship (QSAR) for anti-HIV RT activity. The calculated models were validated using the bagging approach. A consensus model with R2=0.87 and RMSE=0.5 was obtained from 10 individual models. Scaffold analysis and molecular docking of the compounds used in the QSAR model identified a potential chemical scaffold. The results showed that scaffold-based analysis of the QSAR model could be helpful in identifying potent scaffolds for further exploration than analyzing the overall model. Matched molecular pair analysis (MMPA) was applied in the QSAR model to characterize molecular transformations causing a significant change in the anti-HIV activity. The linear QSAR model was calculated to explore the structural features important for NNRTI activity. The results revealed that the activity of NNRT inhibitors is strongly dependent on their aromaticity and structural flexibility. The scaffold-based analysis of QSAR models with molecular docking and MMPA was found to be helpful in characterizing potential scaffolds for anti-HIV RT derivatives. The outcome of this study provides a deeper insight into the computer-aided scaffold-based design of novel molecules with HIV RT activities. It was also clearly shown that the consensus model's failure to correctly predict new chemical series could be due to the limitation of its applicability domain (AD). Redevelopment of models using new measurements can dramatically increase their AD and performance

QSAR models and scaffold-based analysis of non-nucleoside HIV RT inhibitors

© 2015 Elsevier B.V. A selection of 289 pyrimidine derivatives with anti-HIV RT activities as non-nucleoside HIV RT inhibitors (NNRTI) were studied. The associative neural network (ASNN) method was applied to develop a quantitative structure-activity relationship (QSAR) for anti-HIV RT activity. The calculated models were validated using the bagging approach. A consensus model with R2=0.87 and RMSE=0.5 was obtained from 10 individual models. Scaffold analysis and molecular docking of the compounds used in the QSAR model identified a potential chemical scaffold. The results showed that scaffold-based analysis of the QSAR model could be helpful in identifying potent scaffolds for further exploration than analyzing the overall model. Matched molecular pair analysis (MMPA) was applied in the QSAR model to characterize molecular transformations causing a significant change in the anti-HIV activity. The linear QSAR model was calculated to explore the structural features important for NNRTI activity. The results revealed that the activity of NNRT inhibitors is strongly dependent on their aromaticity and structural flexibility. The scaffold-based analysis of QSAR models with molecular docking and MMPA was found to be helpful in characterizing potential scaffolds for anti-HIV RT derivatives. The outcome of this study provides a deeper insight into the computer-aided scaffold-based design of novel molecules with HIV RT activities. It was also clearly shown that the consensus model's failure to correctly predict new chemical series could be due to the limitation of its applicability domain (AD). Redevelopment of models using new measurements can dramatically increase their AD and performance

NMR and Solvent Effect Study on the Thymine-Adenine-Thymine Sequence: A Theoretical Investigation on chemical behavior of Nucleotides in solution

In our current research, we have taken into account nuclear shielding parameters of Thymine-Adenine-Thymine (TAT) sequence using GIAO and Self-Consistent Reaction Field (SCRF) method at the level of HF/ 3-21G theory both in the gas phase and in different solvents such as water, ethanol, methanol, nitromethane and DMSO. These solvents represent a wide range of solvent propertis from the point of view of polarity as well as hydrogen bonding interactions. Our results reveal that NMR chemical shielding parameters are strongly affected by inducing different solvent media. Regarding to our plotted graphs of σiso and ΔE relatives versus є, the lowest σiso values obtained in methanol for nitrogen atoms. However, the opposite trend yielded for the graph of asymmetry parameter (η) versus є. Hydrogen bonding environment strongly affects the chemical shielding tensors and orientation of nuclei. It is noteworthy that the small variation in the position of atoms, eventually yields considerable change in the NMR shielding tensors of the various intermolecular hydrogen bonds. So, solute to solvent hydrogen-bonding effects on the calculated NMR shielding tensors has been concerned. According to our theoretical results of energy values, some important relationships have been found between the dielectric constant and structural stability of TAT sequence. For further evidences, we have discussed about the plotted graphs of relative energies versus dielectric constants of our considered solvents. Thus, we can drastically conclude that the dielectric permittivity of the solvent is a key factor that determines the chemical behavior of DNA in solution. Keywords: TAT sequence; solvent effect; NMR parameters; Ab initio Egyptian Journal of Biochemistry and Molecular Biology Vol. 26 (1) 2008 pp. 83-10

Density Functional Theory Study on the Complexation of NOTA as a Bifunctional Chelator with Radiometal Ions

1,4,7-Triazacyclononane-1,4,7-triacetic acid (NOTA) is a key bifunctional chelator utilized for the complexation of metal ions in radiopharmaceutical applications; the ability of these chelators depends on the strength of their binding with ions. The focus of the present work is to evaluate the complexation of Cu²⁺, Ga³⁺, Sc³⁺, and In³⁺ radiometal ions with NOTA using density functional theory (B3LYP functional) and 6-311+G­(2d,2p)/DGDZVP basis sets. The significant role of ion–water interactions in the chelation interaction energies in solution reflects the competition between ion–water and NOTA–ion interaction in the chelation process. There is reasonable agreement between experimental and theoretical binding constants, geometries, and ¹H NMR chemical shifts. Chelation interaction energies, Gibbs free energies, and entropies in solution show that the NOTA–Ga³⁺ and NOTA–Cu²⁺ are the most and least stable complexes, respectively. The natural atomic charges and second order perturbation analysis reveal charge transfer between NOTA and radiometal ions. The theoretical ¹H NMR chemical shifts of NOTA are in good agreement with experiment; these values are influenced by the presence of the ions, which have a deshielding effect on the protons of NOTA. Global scalar properties such as <i>E</i>_HOMO/<i>E</i>_LUMO, Δ<i>E</i>_LUMO–HOMO, and chemical hardness/softness confirm that the NOTA–Cu²⁺ complex, which has a singly occupied molecular orbital, has the lowest Δ<i>E</i>_LUMO–HOMO value, the least chemical hardness, and the highest chemical softness. The significant variation of the hardness and Δ<i>E</i>_LUMO–HOMO values of the complexes can be attributed to the different positions of the metal ions on the periodic table. This study affirms that, among the radiometal ions, Ga³⁺ can be used to effectively radiolabel NOTA chelator for radiopharmaceutical usage as it binds most stably with NOTA