Developing a variation of 3D‐QSAR/MD method in drug design

Abstract

In continuation of the previous reports on a combination of 3D‐quantitative structure–activity relationships (QSAR) with computational molecular dynamics (MD) studies, a new variation of 3D‐QSAR/MD method has been employed for drug‐design as an alternative or supplementary for the typical experimental methods. The presented method is more cost‐effective and less time‐consuming than the previous methods and avoids several restrictions of experimental methods, such as validity estimation, and predictability. For this purpose, seven inhibitors for bromodomain (BRD)‐containing protein, as an important protein in the development of different types of cancer and responsible for oncogenic rearrangements, have been selected to study of their interactions by docking and MD simulations using molecular mechanics/generalized born surface area (MM/GBSA) method. To build the proposed model, a common variant of 3D‐QSAR methods, comparative molecular field analysis has been employed using a dataset of 100 MD‐extracted ligand conformations and their corresponding MM/GBSA BRD4‐binding energies. The results showed excellent predictability of the generated model for both the training set and test groups. Finally, two new inhibitors were selected among total 4000 designed derivatives (generated through evolutionary techniques) using the proposed 3D‐QSAR‐MD model. The potentials of these inhibitors were assessed by MD simulations, which showed the higher inhibitory of these compounds than the previous inhibitors. Therefore, this method showed high potentials for acceleration of the procedure of drug design and a basis for joining researchers in computational biology and pharmaceutical sciences.

Computational basis of TEAD‐3 protein noncovalent inhibition: 3D‐QSAR modeling and molecular dynamics simulation

“…As shown in our previous works, the need for structural alignment can be eliminated by extracting the 3D ligand conformations directly from MD simulations and building the model by more than one conformation per inhibitor. This can provide structural information for all possible inhibitor orientations in the protein's active site 63,64 …”

“…This can provide structural information for all possible inhibitor orientations in the protein's active site. 63,64 In this study, the interactions of TEAD3 protein with its noncovalent inhibitors were investigated, and a 3D-QSAR model was developed based on these interactions. The molecular interaction patterns were provided in detail by MD simulations, and Tyr230, Val317, Thr333, Met367, Cys368, Met371, Phe394, Ile396, Gln398, and Phe416 residues in the central pocket of TEAD3 were introduced as the most critical residues in noncovalent interaction of TEAD3 with its inhibitors.…”

“…Following our previous studies, 63,64 we employed a novel 3D-QSAR/MD approach for applying CoMFA to TEAD3inhibitor noncovalent interactions. 65 Sybyl-X v2.1 software was used to construct and evaluate the CoMFA model.…”

Molecular modeling studies of Indoline Scaffold derivatives as PD‐1/PD‐L1 pathway inhibitors by QSAR, molecular docking and molecular dynamics simulation techniques

“…[16] Quantitative structure-activity relationship are methods that use chemometric techniques to establish computational or mathematical models between structure and function and reveal, to some extent, the connection between drug molecules and biological macromolecules. [17] One of the advantages of the QSAR study is to reduce the number of molecules that will be designed by facilitating the selection of the structure of candidate molecules to design new molecules with biological properties that allow them to be used in drugs. [18] Molecular docking is an effective tool used to analyze ligand-protein interactions and helps to further understand their binding patterns.…”

“…Computer‐aided drug design (CADD), which includes quantitative structure‐activity relationship, molecular docking, and molecular dynamics simulations, has been widely used in the development of lead compound drugs due to its advantages in shortening the drug development cycle and reducing the risk of failure [16] . Quantitative structure‐activity relationship are methods that use chemometric techniques to establish computational or mathematical models between structure and function and reveal, to some extent, the connection between drug molecules and biological macromolecules [17] . One of the advantages of the QSAR study is to reduce the number of molecules that will be designed by facilitating the selection of the structure of candidate molecules to design new molecules with biological properties that allow them to be used in drugs [18] .…”