Investigations of FAK inhibitors: a combination of 3D-QSAR, docking, and molecular dynamics simulations studies

Identification of potential FAK inhibitors using mol2vec molecular descriptor-based QSAR, molecular docking, ADMET study, and molecular dynamics simulation

This study aims to identify potential focal adhesion kinase (FAK) inhibitors through an integrated computational approach, combining mol2vec descriptor-based QSAR, molecular docking, ADMET study, and molecular dynamics simulation. A dataset of 437 compounds with known FAK inhibitory activities was used to develop QSAR models using machine learning algorithms combined with mol2vec descriptors. Subsequently, the most promising compounds were subjected to molecular docking against FAK to evaluate their binding affinities and key interactions. ADMET study and molecular dynamics simulation were also employed to investigate the pharmacokinetic, drug-like properties, and the stability of the protein-ligand complexes. The results showed that the mol2vec descriptor-based QSAR model established by support vector regression demonstrated good predictive performance (R2 = 0.813, RMSE = 0.453, MAE = 0.263 in case of training set, and R2 = 0.729, RMSE = 0.635, MAE = 0.477 in case of test set), indicating their reliability in identifying potent FAK inhibitors. Using this QSAR model and molecular docking, compound 21 (ZINC000004523722) was identified as the most potential compound, with predicted logIC50 value and binding energy of 2.59 and - 9.3 kcal/mol, respectively. The results of molecular dynamics simulation and ADMET study also further suggested its potential as a promising drug candidate. However, because our research was merely theoretical, additional in vitro and in vivo studies are required for the verification of these results.

Exploring the therapeutic potential of focal adhesion kinase inhibition in overcoming chemoresistance in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is among the leading causes of cancer-related deaths worldwide. Focal adhesion kinase (FAK) is a nonreceptor tyrosine kinase often overexpressed in PDAC. FAK has been linked to cell migration, survival, proliferation, angiogenesis and adhesion. This review first highlights the chemoresistant nature of PDAC. Second, the role of FAK in PDAC cancer progression and resistance is carefully described. Additionally, it discusses recent developments of FAK inhibitors as valuable drugs in the treatment of PDAC, with a focus on diamine-substituted-2,4-pyrimidine-based compounds, which represent the most potent class of FAK inhibitors in clinical trials for the treatment of PDAC disease. To conclude, relevant computational studies performed on FAK inhibitors are reported to highlight the key structural features required for interaction with the protein, with the aim of optimizing this novel targeted therapy.

Identification of defactinib derivatives targeting focal adhesion kinase using ensemble docking, molecular dynamics simulations and binding free energy calculations

Focal adhesion kinase (FAK) belongs to the nonreceptor tyrosine kinases, which selectively phosphorylate tyrosine residues on substrate proteins. FAK is associated with bladder, esophageal, gastric, neck, breast, ovarian and lung cancers. Thus, FAK has been considered as a potential target for tumor treatment. Currently, there are six adenosine triphosphate (ATP)-competitive FAK inhibitors tested in clinical trials but no approved inhibitors targeting FAK. Defactinib (VS-6063) is a second-generation FAK inhibitor with an IC50 of 0.6 nM. The binding model of VS-6063 with FAK may provide a reference model for developing new antitumor FAK-targeting drugs. In this study, the VS-6063/FAK binding model was constructed using ensemble docking and molecular dynamics simulations. Furthermore, the molecular mechanics/generalized Born (GB) surface area (MM/GBSA) method was employed to estimate the binding free energy between VS-6063 and FAK. The key residues involved in VS-6063/FAK binding were also determined using per-residue energy decomposition analysis. Based on the binding model, VS-6063 could be separated into seven regions to enhance its binding affinity with FAK. Meanwhile, 60 novel defactinib-based compounds were designed and verified using ensemble docking. Overall, the present study improves our understanding of the binding mechanism of human FAK with VS-6063 and provides new insights into future drug designs targeting FAK.Communicated by Ramaswamy H. Sarma.

Interactions of heparin derivatives with recombinant human keratinocyte growth factor: Structural stability and bioactivity effect study

Heparin and heparan sulfate are important glycosaminoglycans that can regulate the activities of many vital proteins, especially the fibroblast growth factor (FGF) family. Because FGF7 (KGF) has an important role in tissue repair and maintaining the integrity of the mucosal barrier, recombinant human keratinocyte growth factor (rhKGF, palifermin) has been approved for the treatment of wound healing and oral cavity. Due to heparin plays an important role in the KGF signaling pathway, a more detailed study of the drug-drug interactions (DDIs) between rhKGF and heparin at the atomic level and investigating their synergistic effect on each other in terms of biology, especially in silico, is necessary for a better understanding of DDIs. In this study, DDIs between rhKGF and low-molecular weight heparin types (LMWH) were investigated. In this regard, scrutiny of the influence of the synergistic heparin types on the structure and biostability of rhKGF is accomplished using computational methods such as molecular docking and molecular dynamic simulations (MDs). Subsequently, the motion behavior of rhKGF in interaction with LMWHs was evaluated based on eigenvectors by using principal component analysis (PCA). Also, the binding free energies of rhKGF-LMWH complexes were calculated by the molecular mechanics/Poisson-Boltzmann surface area (MM-BPSA) method. The result showed that rhKGF-idraparinux (-6.9 kcal/mol) and rhKGF-heparin (-6.0 kcal/mol) complexes had significant binding affinity as well as they had a more stable binding to rhKGF than to other LMWH during 100 ns simulation. However, in order to confirm the curative effect of these drugs, clinical trials must be done.

Identification of the structural features of quinazoline derivatives as EGFR inhibitors using 3D-QSAR modeling, molecular docking, molecular dynamics simulations and free energy calculations

Epidermal growth factor receptor (EGFR) is a promising target for the treatment of different types of malignant tumors. Therefore, a combined molecular modeling study was performed on a series of quinazoline derivatives as EGFR inhibitors. The optimum ligand-based CoMFA and CoMSIA models showed reliable and satisfactory predictability (with R²_cv=0.681, R²_ncv=0.844, R²_pred=0.8702 and R²_cv=0.643, R²_ncv=0.874, R²_pred=0.6423). The derived contour maps provide structural features to improve inhibitory activity. Furthermore, the contour maps, molecular docking, and molecular dynamics (MD) simulations have good consistency, illustrating that the derived models are reliable. In addition, MD simulations and binding free energy calculations were also carried out to understand the conformational fluctuations at the binding pocket of the receptor. The results indicate that hydrogen bond, hydrophobic and electrostatic interactions play significant roles on activity and selectivity. Furthermore, amino acids Val31, Lys50, Thr95, Leu149 and Asp160 are considered as essential residues to participate in the ligand-receptor interactions. Overall, this work would offer reliable theoretical basis for future structural modification, design and synthesis of novel EGFR inhibitors with good potency.Communicated by Ramaswamy H. Sarma.

A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

BACKGROUND

Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32).

AIM

The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL.

METHODOLOGY

Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds.

RESULT

MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies.

CONCLUSION

Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.

In silico design of novel FAK inhibitors using integrated molecular docking, 3D-QSAR and molecular dynamics simulation studies

Focal adhesion kinase (FAK) is a cytoplasmic tyrosine kinase that plays a crucial role in integrin signaling that regulates essential cellular functions including growth, motility, proliferation and survival in different types of cells. Interestingly, it has also shown to be up-regulated in various types of tumors, hence it has emerged as a significant therapeutic target for the development of selective inhibitors. In present work, with the aim of achieving further insight into the structural characteristics required for the FAK inhibitory activity, a combined approach of molecular modeling studies including molecular docking, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) simulation were carried out on a series of 7H-pyrrolo[2,3-d]pyrimidine and thieno[3,2-d]pyrimidine FAK inhibitors. The probable binding modes and interactions of inhibitors into the FAK active site were predicted by molecular docking. The 3D-QSAR models were developed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods, with three ligand-based, docking-based and receptor-based alignment techniques. Both CoMFA and CoMSIA models obtained from receptor-based alignment were superior to the ones obtained by other alignment methods. However, the CoMSIA model (q² = 0.679, r² = 0.954 and r²_pred = 0.888) depicted almost better predictive ability than the CoMFA model (q² = 0.617, r² = 0.932 and r²_pred = 0.856). The contour map analysis revealed the relationship between the structural features and inhibitory activity. The docking results and CoMFA and CoMSIA contour maps were in good accordance. Based on the information obtained from the molecular docking and contour map analysis, a series of novel FAK inhibitors were designed that showed better predicted inhibitory activity than the most potent compound 31 in the data set. Finally, the stability of the reference molecule 31 and the designed compounds D15 and D27 were evaluated through a 30 ns of MD simulation and their binding free energies were calculated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The result of MD simulation and binding free energy decomposition demonstrated the important role of van der Waals interactions alongside H-bond ones that were in consistent with the docking and contour maps analysis results. In sum, the results from this study may provide a significant insight for developing more effective novel FAK inhibitors.Communicated by Ramaswamy H. Sarma.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

In silico mutagenesis in recombinant human keratinocyte growth factor: Improvement of stability and activity in addition to decrement immunogenicity

The recombinant human keratinocyte growth factor (rhKGF) is clinically applied to decrease the incidence and duration of cancer therapeutic agents. Particularly, it is extensively used for oral mucositis after chemotherapy-induced damage of different human cancers. However, the usage of rhKGF in treatment is limited owing to its short half-life, poor stability, immunogenicity, tendency to aggregate, and side effects. Therefore, there is a need to enhance the stability and to reduce immunogenicity of rhKGF for therapeutic applications. In this study, the stability, activity, and immunogenicity of rhKGF were improved using computational methods. The several mutations were generated based on sequence alignment, amino acids physic-chemical properties, and the structure simulation. The 3D structure of rhKGF and proposed mutants were predicted by Modeller v9.15 program, and then were evaluated using PROSESS, PROCHECK, and ProSA web tools. Afterwards, the effect of these mutants on rhKGF structure, stability, activity, and its interaction with fibroblast growth factor receptor2-IIb (FGFR2-IIb) was analyzed through utilizing GROMACS molecular dynamics simulations and docking tools, respectively. Also, binding free energies were calculated by the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method. We found that F63Y, R121K, and combine1 (K38R, F63Y, K72E, N105S) mutants lead to reduction of the number of T-cell epitopes. However, all of the selected mutants, except for R121K, could considerably increase stability and affinity of the rhKGF to FGFR2-IIb, in silico. In conclusion, this study, for the first time, offered that the combine1 and F63Y mutants could highly improve the stability and activity of rhKGF and even reduce immunogenicity without having any significant effect on the biological functions of rhKGF.

The inhibitory mechanism of aurintricarboxylic acid targeting serine/threonine phosphatase Stp1 in Staphylococcus aureus: insights from molecular dynamics simulations

Serine/threonine phosphatase (Stp1) is a member of the bacterial Mg2+- or Mn2+- dependent protein phosphatase/protein phosphatase 2C family, which is involved in the regulation of Staphylococcus aureus virulence. Aurintricarboxylic acid (ATA) is a known Stp1 inhibitor with an IC50 of 1.03 μM, but its inhibitory mechanism has not been elucidated in detail because the Stp1-ATA cocrystal structure has not been determined thus far. In this study, we performed 400 ns molecular dynamics (MD) simulations of the apo-Stp1 and Stp1-ATA complex models. During MD simulations, the flap subdomain of the Stp1-ATA complex experienced a clear conformational transition from an open state to a closed state, whereas the flap domain of apo-Stp1 changed from an open state to a semi-open state. In the Stp1-ATA complex model, the hydrogen bond (H-bond) between D137 and N142 disappeared, whereas critical H-bond interactions were formed between Q160 and H13, Q160/R161 and ATA, as well as N162 and D198. Finally, four residues (D137, N142, Q160, and R161) in Stp1 were mutated to alanine and the mutant enzymes were assessed using phosphate enzyme activity assays, which confirmed their important roles in maintaining Stp1 activity. This study indicated the inhibitory mechanism of ATA targeting Stp1 using MD simulations and sheds light on the future design of allosteric Stp1 inhibitors.

Computational investigations of gram-negative bacteria phosphopantetheine adenylyltransferase inhibitors using 3D-QSAR, molecular docking and molecular dynamic simulations

Phosphopantetheine adenylyltransferase (PPAT) has been recognized as a promising target to develop novel antimicrobial agents, which is a hexameric enzyme that catalyzes the penultimate step in coenzyme A biosynthesis. In this work, molecular modeling study was performed with a series of PPAT inhibitors using molecular docking, three-dimensional qualitative structure-activity relationship (3D-QSAR) and molecular dynamic (MD) simulations to reveal the structural determinants for their bioactivities. Molecular docking study was applied to understand the binding mode of PPAT with its inhibitors. Subsequently, 3D-QSAR model was constructed to find the features required for different substituents on the scaffolds. For the best comparative molecular field analysis (CoMFA) model, the Q² and R² values of which were calculated as 0.702 and 0.989, while they were calculated as 0.767 and 0.983 for the best comparative molecular similarity index analysis model. The statistical data verified the significance and accuracy of our 3D-QSAR models. Furthermore, MD simulations were carried out to evaluate the stability of the receptor-ligand contacts in physiological conditions, and the results were consistent with molecular docking studies and 3D-QSAR contour map analysis. Binding free energy was calculated with molecular mechanics generalized born surface area approach, the result of which coincided well with bioactivities and demonstrated that van der Waals accounted for the largest portion. Overall, our study provided a valuable insight for further research work on the recognition of potent PPAT inhibitors.Communicated by Ramaswamy H. Sarma.

Identification of new DNA gyrase inhibitors based on bioactive compounds from streptomyces: structure-based virtual screening and molecular dynamics simulations approaches

DNA gyrase enzyme has vital role in bacterial survival and can be considered as a potential drug target. Owing to the appearance of resistance to gyrase-targeted drugs, especially fluoroquinolone, screening new compounds which bind more efficiently to the mutant binding pocket is essential. Hence, in this work, using Smina Autodock and through structure-based virtual screening of StreptomeDB, several natural products were discovered based on the SimocyclinoneD8 (SD8) binding pocket of GyrA subunit of DNA gyrase. After evaluation of binding affinity, binding modes, critical interactions and physicochemical and pharmaceutical properties, three lead compounds were selected for further analysis. Afterward 60 ns molecular dynamics simulations were performed and binding free energies were calculated by the molecular mechanics/Poisson-Boltzmann surface area method. Also, interaction of the selected lead compounds with the mutated GyrA protein was evaluated. Results indicated that all of the selected compounds could bind to the both wild-type and mutated GyrA with the binding affinities remarkably higher than SimocyclinoneD8. Interestingly, we noticed that the selected compounds comprised angucycline moiety in their structure which could sufficiently interact with GyrA and block the DNA binding pocket of DNA gyrase, in silico. In conclusion, three DNA gyrase inhibitors were identified successfully which were highly capable of impeding DNA gyrase and can be considered as potential drug candidates for treatment of fluoroquinolone-resistant strains.Communicated by Ramaswamy H. Sarma.

Design and development of novel focal adhesion kinase (FAK) inhibitors using Monte Carlo method with index of ideality of correlation to validate QSAR

Quantitative structure-activity relationship (QSAR) modelling of 55 focal adhesion kinase (FAK) (EC 2.7.10.2) inhibitors of triazinic nature was performed using the Monte Carlo method. The QSAR models were designed by CORAL software, and optimal descriptors were calculated with the simplified molecular input line entry system (SMILES). Four splits were made from the triazinic derivative data by random division into training, invisible training, calibration and validation sets. The QSAR results from these four random splits were robust, very simple, predictive and reliable. The best statistical parameters of the validation set (r² = 0.8398 and Q² = 0.7722) for the QSAR equation for split 3 with IIC = 0.9127 were obtained. The predictive potential of QSAR models of FAK inhibitors was explored by applying the index of ideality of correlation (IIC), which is a new criterion for the prediction of the potential for quantitative structure-property activity relationships (QSPRs/QSARs). The present method follows OECD principles.

In Vitro and In Silico Insights into sEH Inhibitors with Amide-Scaffold from the Leaves of Capsicum chinense Jacq

Two compounds termed 1 and 2 were isolated from the leaves of Capsicum chinense using column chromatography. Their structures were identified as amide scaffolds by analyzing spectroscopic signals. Compounds 1 and 2 have been confirmed to be competitive soluble epoxide hydrolase (sEH) inhibitors that suppress the catalytic reaction of sEH in a dose-dependent manner in vitro. Molecular docking was used for analyzing two binding clusters of ligand and receptor. The results confirmed that the key amino acids interacting with the ligand were Asp335, Tyr383, and Gln384. On the basis of molecular dynamics, inhibitors 1 and 2 were noted to interact at a distance of 3.5 Å from Asp335, Tyr383, Leu408 and Tyr466, and Asp335, Tyr383, and Tyr466, respectively. These results highlight the potential of N-trans-coumaroyltyramine (1) and N-trans-feruloyltyramine (2) as sEH inhibitors.