Mechanistic and Predictive QSAR Analysis of Diverse Molecules to Capture Salient and Hidden Pharmacophores for Anti-Thrombotic Activity

Novel Thiourea and Oxime Ether Isosteviol-Based Anticoagulants: MD Simulation and ADMET Prediction

Activated blood coagulation factor X (FXa) plays a critical initiation step of the blood-coagulation pathway and is considered a desirable target for anticoagulant drug development. It is reversibly inhibited by nonvitamin K antagonist oral anticoagulants (NOACs) such as apixaban, betrixaban, edoxaban, and rivaroxaban. Thrombosis is extremely common and is one of the leading causes of death in developed countries. In previous studies, novel thiourea and oxime ether isosteviol derivatives as FXa inhibitors were designed through a combination of QSAR studies and molecular docking. In the present contribution, molecular dynamics (MD) simulations were performed for 100 ns to assess binding structures previously predicted by docking and furnish additional information. Moreover, three thiourea- and six oxime ether-designed isosteviol analogs were then examined for their drug-like and ADMET properties. MD simulations demonstrated that four out of the nine investigated isosteviol derivatives, i.e., one thiourea and three oxime ether ISV analogs, form stable complexes with FXa. These derivatives interact with FXa in a manner similar to Food and Drug Administration (FDA)-approved drugs like edoxaban and betrixaban, indicating their potential to inhibit factor Xa activity. One of these derivatives, E24, displays favorable pharmacokinetic properties, positioning it as the most promising drug candidate. This, along with the other three derivatives, can undergo further chemical synthesis and bioassessment.

Mechanistic Analysis of Chemically Diverse Bromodomain-4 Inhibitors Using Balanced QSAR Analysis and Supported by X-ray Resolved Crystal Structures

Bromodomain-4 (BRD-4) is a key enzyme in post-translational modifications, transcriptional activation, and many other cellular processes. Its inhibitors find their therapeutic usage in cancer, acute heart failure, and inflammation to name a few. In the present study, a dataset of 980 molecules with a significant diversity of structural scaffolds and composition was selected to develop a balanced QSAR model possessing high predictive capability and mechanistic interpretation. The model was built as per the OECD (Organisation for Economic Co-operation and Development) guidelines and fulfills the endorsed threshold values for different validation parameters (R²_tr = 0.76, Q²_LMO = 0.76, and R²_ex = 0.76). The present QSAR analysis identified that anti-BRD-4 activity is associated with structural characters such as the presence of saturated carbocyclic rings, the occurrence of carbon atoms near the center of mass of a molecule, and a specific combination of planer or aromatic nitrogen with ring carbon, donor, and acceptor atoms. The outcomes of the present analysis are also supported by X-ray-resolved crystal structures of compounds with BRD-4. Thus, the QSAR model effectively captured salient as well as unreported hidden pharmacophoric features. Therefore, the present study successfully identified valuable novel pharmacophoric features, which could be beneficial for the future optimization of lead/hit compounds for anti-BRD-4 activity.

Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis

Cancer is a major life-threatening disease with a high mortality rate in many countries. Even though different therapies and options are available, patients generally prefer chemotherapy. However, serious side effects of anti-cancer drugs compel us to search for a safer drug. To achieve this target, Hsp90 (heat shock protein 90), which is responsible for stabilization of many oncoproteins in cancer cells, is a promising target for developing an anti-cancer drug. The QSAR (Quantitative Structure–Activity Relationship) could be useful to identify crucial pharmacophoric features to develop a Hsp90 inhibitor. Therefore, in the present work, a larger dataset encompassing 1141 diverse compounds was used to develop a multi-linear QSAR model with a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The new developed six-parameter model satisfies the recommended values for a good number of validation parameters such as R2tr = 0.78, Q2LMO = 0.77, R2ex = 0.78, and CCCex = 0.88. The present analysis reveals that the Hsp90 inhibitory activity is correlated with different types of nitrogen atoms and other hidden structural features such as the presence of hydrophobic ring/aromatic carbon atoms within a specific distance from the center of mass of the molecule, etc. Thus, the model successfully identified a variety of reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with Hsp90.