The Efficacy of Conceptual DFT Descriptors and Docking Scores on the QSAR Models of HIV Protease Inhibitors

Abstract

This study critically examines the role of conceptual DFT descriptors and docking scores on a diverse set of 156 inhibitors of HIV proteases. Five QSAR models were developed on the basis of available experimental IC(50) values (HIV-I and HIV-IIIB infected MT4 and CEMSS cells and HIV-I infected C8166 cells) and sixth QSAR model was generated by combining the inhibitors of all five models. B3LYP/6-31G(d) optimizations were carried out on all considered inhibitors, and the results are compared with more economic semi-empirical SCF AM1 results in order to find out the best and efficient way of descriptor calculations. Interestingly semi-empirical results appear to be satisfactory for this class of inhibitors. Selected QSAR models were validated by taking about 20% of inhibitors in the test sets. The effect of the number of descriptors on the R(2) and R(2)(cv) values was tested and three to four orthogonal descriptors based models were selected to be the optimum ones to avoid over correlation.

Anti-HIV Drug Development Through Computational Methods

“…A series of danuravir derivatives was evaluated with 3D-QSAR and docking methods (18), demonstrating that the ligand-based and receptor-based results were in agreement with the experimental results (18). Five QSAR models were generated on the basis of available experimental IC (50) values (HIV-I-and HIV-IIIB-infected MT4 and CEMSS cells and HIV-I-infected C8166 cells) (19). The sixth model was generated by combining the inhibitors of all five models, critically examining the role of conceptual DFT descriptors and docking scores on 156 HIV PR inhibitors (19).…”

“…Five QSAR models were generated on the basis of available experimental IC (50) values (HIV-I-and HIV-IIIB-infected MT4 and CEMSS cells and HIV-I-infected C8166 cells) (19). The sixth model was generated by combining the inhibitors of all five models, critically examining the role of conceptual DFT descriptors and docking scores on 156 HIV PR inhibitors (19). Previous molecular dynamics simulations revealed some opening pathways and conformations in the opening process of HIV PR (20).…”

Adsorption of Various Monoterpenoids on the Surface of Graphene and Nitrogen-Doped Graphene: A DFT Based Study

“…Hardness (η) is the resistance of a system to changes in electron density and softness (S) correlates linearly with the polarizability, which is a measure of the change of the electronic density due to the presence of an electric field . The hardness and softness values are calculated based on the commonly used approximations (η=(E LUMO ‐E HOMO )/2; S=1/2 η) . Chattaraj et al.…”

Assessment of the electronic structure and properties of trichothecene toxins using density functional theory

“…Type B trichothecenes possess a carbonyl in the R5 position and include compounds 1-10, and 29. This study also includes the type A trichothecene T-2 toxin and related compounds (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28). T-2 toxin is associated with a variety of harmful effects, including alimentary toxic aleukia, and is a possible war agent [1].…”

“…Quantitative structure-activity relationship (QSAR) analysis develops polynomial equations based on the formalism that activities can be mathematically related to certain properties of molecules represented by descriptors [20][21][22]. Successful QSAR models have been derived using a wide range of descriptors, including descriptors based on quantum chemical, electrostatic, electronic, lipophilic, topological, constitutional, geometric, and steric properties [23][24][25]. The aim of this study is to obtain fundamental information on the electronic structures and properties of a comprehensive set of trichothecenes, and identify relationships between molecular descriptors and activities.…”