Computational Investigation of Adenosine 5′- (α, β-methylene)- diphosphate (AMPCP) Derivatives as Ecto-5′-nucleotidase (CD73) Inhibitors by Using 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulations

Abstract CD73, as a surface enzyme anchored on the outside of the cell membrane via glycosylphosphatidylinositol (GPI), can convert the AMP in the tumor cell microenvironment into adenosine to promote the growth of tumor cells. It has been overexpressed in many different types of human tumors, such as gastric cancer, pancreatic cancer, liver cancer and other tumor cells. Therefore, targeted inhibitors of CD73 are considered as potential tumor treatment methods. Due to the low bioavailability of nucleoside CD73 inhibitors, it is necessary to develop new inhibitors. In this study, through molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular dynamics (MD) simulations, a series of CD73 inhibitors were calculated and studied to reveal their structure-activity relationships. Through molecular docking studies, explore the possible mode of interaction between inhibitors and protein. Subsequently, a 3D-QSAR model was established by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). For the best CoMFA model, the Q2 and R2 values are 0.708 and 0.983, respectively, while for the best CoMSIA model, the Q2 and R2 values are 0.809 and 0.992, respectively. In addition, the stability of the complex formed by the two inhibitors and CD73 was evaluated by molecular dynamics simulation, and the results are consistent with the results of molecular docking and 3D-QSAR research. Finally, the binding free energy was calculated by the surface area method (MM-GBSA), and the results are consistent with the activities that Van Der Waals and Coulomb contribute the most during the binding process of the molecule to the CD73 protein. In conclusion, our research provides valuable information for the further development of CD73 inhibitors.

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Design, Synthesis, Biological Evaluation, and Molecular Modeling of 2-Difluoromethylbenzimidazole Derivatives as Potential PI3Kα Inhibitors

Molecules ◽

10.3390/molecules27020387 ◽

2022 ◽

Vol 27 (2) ◽

pp. 387

Author(s):

Xiangcong Wang ◽

Moxuan Zhang ◽

Ranran Zhu ◽

Zhongshan Wu ◽

Fanhong Wu ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Molecular Modeling ◽

3D Qsar ◽

Binding Mode ◽

Biological Evaluation ◽

Field Analysis ◽

Dynamics Simulation ◽

Comfa Model ◽

Qsar Models

PI3Kα is one of the potential targets for novel anticancer drugs. In this study, a series of 2-difluoromethylbenzimidazole derivatives were studied based on the combination of molecular modeling techniques 3D-QSAR, molecular docking, and molecular dynamics. The results showed that the best comparative molecular field analysis (CoMFA) model had q2 = 0.797 and r2 = 0.996 and the best comparative molecular similarity indices analysis (CoMSIA) model had q2 = 0.567 and r2 = 0.960. It was indicated that these 3D-QSAR models have good verification and excellent prediction capabilities. The binding mode of the compound 29 and 4YKN was explored using molecular docking and a molecular dynamics simulation. Ultimately, five new PI3Kα inhibitors were designed and screened by these models. Then, two of them (86, 87) were selected to be synthesized and biologically evaluated, with a satisfying result (22.8 nM for 86 and 33.6 nM for 87).

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Investigating the Binding Mode of Reversible LSD1 Inhibitors Derived from Stilbene Derivatives by 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulation

Molecules ◽

10.3390/molecules24244479 ◽

2019 ◽

Vol 24 (24) ◽

pp. 4479

Author(s):

Yongtao Xu ◽

Zihao He ◽

Min Yang ◽

Yunlong Gao ◽

Linfeng Jin ◽

...

Keyword(s):

Molecular Dynamics ◽

Binding Free Energy ◽

Clinical Stage ◽

3D Qsar ◽

Structure Activity Relationship ◽

Field Analysis ◽

Dynamics Simulation ◽

Activity Relationship ◽

Structure Activity ◽

Stilbene Derivatives

Overexpression of lysine specific demethylase 1 (LSD1) has been found in many cancers. New anticancer drugs targeting LSD1 have been designed. The research on irreversible LSD1 inhibitors has entered the clinical stage, while the research on reversible LSD1 inhibitors has progressed slowly so far. In this study, 41 stilbene derivatives were studied as reversible inhibitors by three-dimensional quantitative structure–activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q 2 = 0.623, r 2 = 0.987, r pred 2 = 0.857) and comparative molecular similarity indices analysis (CoMSIA q 2 = 0.728, r 2 = 0.960, r pred 2 = 0.899) were used to establish the model, and the structure–activity relationship of the compounds was explained by the contour maps. The binding site was predicted by two different kinds of software, and the binding modes of the compounds were further explored. A series of key amino acids Val288, Ser289, Gly314, Thr624, Lys661 were found to play a key role in the activity of the compounds. Molecular dynamics (MD) simulations were carried out for compounds 04, 17, 21, and 35, which had different activities. The reasons for the activity differences were explained by the interaction between compounds and LSD1. The binding free energy was calculated by molecular mechanics generalized Born surface area (MM/GBSA). We hope that this research will provide valuable information for the design of new reversible LSD1 inhibitors in the future.

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In Silico Studies of Piperidine Derivatives as Protein Kinase B Inhibitors through 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

Letters in Drug Design & Discovery ◽

10.2174/1570180818666211207105516 ◽

2021 ◽

Vol 18 ◽

Author(s):

Sisi Liu ◽

Yaxin Li ◽

Jin Wang ◽

Xue Rui ◽

Haobo Tian ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Molecular Dynamics Simulation ◽

Protein Kinase ◽

Protein Kinase B ◽

Similarity Index ◽

3D Qsar ◽

Field Analysis ◽

Dynamics Simulation ◽

In Silico Studies

Background: Protein kinase B (Akt) is a serine/threonine-protein kinase that drives the diverse physiological process. Akt is a promising therapeutic target, which involves cancer cell growth, survival, proliferation and metabolism. Objective: The study aims to design highly active Akt inhibitors and to elucidate the structural requirements for their biological activity, we analyzed the key binding features and summarized the structural determinants for their bioactivities. Methods: A series of piperidine derivatives have been investigated employing three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulation. Results: The statistics of the comparative molecular field analysis (CoMFA) model (Q2=0.631, R2=0.951) and the comparative molecular similarity index analysis (CoMSIA) model (Q2=0.663, R2=0.966) indicated that our 3D-QSAR model was accurate and reliable. Besides, the stability of receptor-ligand interactions under physiological conditions was then evaluated by molecular dynamics simulation, in agreement with the molecular docking results. Conclusion: Our study provided valuable insights for the discovery of potent Akt inhibitors.

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3D-QSAR Assisted Design of Novel 7-Deazapurine Derivatives as TNNI3K Kinase Inhibitors Using Molecular Docking and Molecular Dynamics Simulation

Letters in Drug Design & Discovery ◽

10.2174/1570180816666190110121300 ◽

2020 ◽

Vol 17 (2) ◽

pp. 155-168

Author(s):

Pavithra K. Balasubramanian ◽

Anand Balupuri ◽

Swapnil P. Bhujbal ◽

Seung Joo Cho

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Molecular Dynamics Simulation ◽

3D Qsar ◽

Structure Activity Relationship ◽

Dynamics Simulation ◽

Activity Relationship ◽

Dual Function ◽

Contour Maps ◽

Structure Activity

Background: Cardiac troponin I-interacting kinase (TNNI3K) is a cardiac-specific kinase that belongs to MAPKKK family. It is a dual-function kinase with tyrosine and serine/threonine kinase activity. Over-expression of TNNI3K results in various cardiovascular diseases such as cardiomyopathy, ischemia/reperfusion injury, heart failure, etc. Since, it is a cardiac-specific kinase and expressed only in heart tissue, it is an ideal molecular target to treat cardiac diseases. The main objective of the work is to study and understand the structure-activity relationship of the reported deazapurine derivatives and to use the 3D-QSAR and docking results to design potent and novel TNNI3K inhibitors of this series. Methods: In the present study, we have used molecular docking 3D QSAR, and molecular dynamics simulation to understand the structure-activity correlation of reported TNNI3K inhibitors and to design novel compounds of deazapurine derivatives with increased activity. Results: Both CoMFA (q2=0.669, NOC=5, r2=0.944) and CoMSIA (q2=0.783, NOC=5, r2=0.965) have resulted in satisfactory models. The models were validated using external test set, Leave-out- Five, bootstrapping, progressive scrambling, and rm2 metrics calculations. The validation procedures showed the developed models were robust and reliable. The docking results and the contour maps analysis helped in the better understanding of the structure-activity relationship. Conclusion: This is the first report on 3D-QSAR modeling studies of TNNI3K inhibitors. Both docking and MD results were consistent and showed good correlation with the previous experimental data. Based on the information obtained from contour maps, 31 novel TNNI3K inhibitors were designed. These designed compounds showed higher activity than the existing dataset compounds.

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3D-QSAR, Molecular Docking, and MD Simulations of Anthraquinone Derivatives as PGAM1 Inhibitors

Frontiers in Pharmacology ◽

10.3389/fphar.2021.764351 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yuwei Wang ◽

Yifan Guo ◽

Shaojia Qiang ◽

Ruyi Jin ◽

Zhi Li ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Rational Design ◽

Binding Free Energy ◽

3D Qsar ◽

Md Simulations ◽

Structure Activity Relationships ◽

Structure Activity ◽

Wide Range ◽

Anthraquinone Derivatives

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors.

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3D-QSAR, Molecular Docking, and Molecular Dynamics Simulation Study of Thieno[3,2-b]Pyrrole-5- Carboxamide Derivatives as LSD1 Inhibitors

10.20944/preprints201908.0223.v1 ◽

2019 ◽

Author(s):

Meilan Huang ◽

yongtao Xu ◽

Zihao He ◽

Min Yang ◽

Hongyi Liu ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Three Dimensional ◽

3D Qsar ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Dynamics Simulation ◽

Binding Modes ◽

Binding Interaction ◽

Contour Maps

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and become a new target for anticancer drugs. In recent years, the small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamides LSD1 inhibitors using molecular docking, three dimensional quantitative structure-activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q2=0.783, r2=0.944, r2pred=0.851) and Comparative molecular similarity indices analysis (CoMSIA q2=0.728, r2=0.982, r2pred=0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, the ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

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In silico Prediction of Novel SARS-CoV 3CL pro Inhibitors: a Combination of 3D-QSAR, Molecular Docking, ADMET Prediction, and Molecular Dynamics Simulation

Biointerface Research in Applied Chemistry ◽

10.33263/briac124.51005115 ◽

2021 ◽

Vol 12 (4) ◽

pp. 5100-5115

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Predictive Ability ◽

3D Qsar ◽

Quantitative Structure Activity Relationship ◽

Field Analysis ◽

Dynamics Simulation ◽

Qsar Study ◽

Determination Coefficient ◽

Pharmacokinetic Properties

The Chymotrypsin-like protease (3CLpro) is a drug target in the coronavirus because of its role in processing the polyproteins that are translated from the viral RNA. This study applied 3D quantitative structure-activity relationship (3D-QSAR), molecular docking, and ADMET prediction on a series of SARS-CoV 3CLpro inhibitors. The 3D-QSAR study was applied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods, which gave the cross-validation coefficient (Q2) values of 0.64 and 0.80, the determination coefficient (R2) values of 0.998 and 0.993 and the standard error of the estimate (SEE) values of 0.046 and 0.091, respectively. The acceptable values of the determination coefficient (R2 test) to CoMFA and CoMSIA respectively corresponding to values of 0.725 and 0.690 utilizing a test set of seven molecules prove the high predictive ability of this model. Molecular docking analysis was utilized to validate 3D-QSAR methods and explain the binding site interactions and affinity between the most active ligands and the SARS-CoV 3CLpro receptor. Based on these results, a novel series of compounds were predicted, and their pharmacokinetic properties were verified using drug-likeness and ADMET prediction. Finally, the best-docked candidate molecules were subjected to molecular dynamics (MD) simulation to affirm their dynamic behavior and stability.

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Computational Studies on Imidazo[1,2-a] Pyridine-3-Carboxamide Analogues as Antimycobacterial Agents: Common Pharmacophore Generation, Atom-based 3D-QSAR, Molecular dynamics Simulation, QikProp, Molecular Docking and Prime MMGBSA Approaches

Open Pharmaceutical Sciences Journal ◽

10.2174/1874844901805010012 ◽

2018 ◽

Vol 5 (1) ◽

pp. 12-23 ◽

Cited By ~ 10

Author(s):

Suraj N. Mali ◽

Hemchandra K. Chaudhari

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Molecular Dynamics Simulation ◽

3D Qsar ◽

Qsar Model ◽

Dynamics Simulation ◽

Drug Resistant ◽

Drug Resistant Tuberculosis ◽

Resistant Tuberculosis ◽

Pharmacophore Hypothesis

Background: IMB-1402, Q203 and ND09759 analogs were found to have strong efficiency against Multi-drug-resistant tuberculosis (MDR-TB)/Extensively drug-resistant tuberculosis (XDR-TB) strains. Objectives: To know the structural necessities for imidazo[1,2-a]pyridine-3-carboxamide analogues, we intended to develop the ligand-based pharmacophore, Quantitative structure–activity relationship models(3D-QSAR model). We also performed Molecular docking, molecular simulation and Prime/Molecular Mechanics Generalized Born Surface Area (Prime/MM-GBSA) studies. Methods: All the studies like Common pharmacophore hypothesis generation, Atom based 3D-QSAR study, Prime MMGBSA, Docking, Qikprop, and Molecular dynamics simulation were processed using various modules incorporated within the maestro software interface from Schrodinger, LLC, New York USA (release 2017). Results: The common pharmacophore hypothesis(CPH) generation resulted in a five-featured hypothesis HHPRR, containing 1 positive, 2 hydrophobic and 2 aromatic rings. An Atom-based 3D-QSAR model was predicted for twenty seven training sets (a correlation coefficient i.e.R2= 0.9181,Standard deviation i.e.SD =0.3305, variance ratio i.e. F = 85.9) and eleven test sets (cross-validation correlation coefficient i.e.Q2 =0.6745, Root Mean Square Error i.e. RMSE = 0.65, Pearson R = 0.8427, P=1.21E-12) compounds employing alignment based on CPH. The dataset of thirty-eight molecules was allowed for docking into the active site of pantothenate synthetase (PDBID-3IVX) that shows H-bonding (Hydrogen bonding) interactions with residues Gly158, Met195, Pro38 and additionally shows further Pi-cation interactions with a residue like Hie47. We also obtained good simulation results for1.2ns study. Conclusion: From the results, the generated 3D-QSAR model may be applicable for additional designing of various novel potent derivatives in the future.

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Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

Pharmaceuticals ◽

10.3390/ph14040357 ◽

2021 ◽

Vol 14 (4) ◽

pp. 357

Author(s):

Magdi E. A. Zaki ◽

Sami A. Al-Hussain ◽

Vijay H. Masand ◽

Siddhartha Akasapu ◽

Sumit O. Bajaj ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Virtual Screening ◽

Simulation Analysis ◽

Qsar Model ◽

Quantitative Structure Activity Relationship ◽

Dynamics Simulation ◽

Multilinear Regression ◽

Qsar Analysis ◽

Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

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Simulation studies, 3D QSAR and molecular docking on a point mutation of protein kinase B with flavonoids targeting ovarian Cancer

BMC Pharmacology and Toxicology ◽

10.1186/s40360-021-00512-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Suchitra Maheswari Ajjarapu ◽

Apoorv Tiwari ◽

Gohar Taj ◽

Dev Bukhsh Singh ◽

Sakshi Singh ◽

...

Keyword(s):

Ovarian Cancer ◽

Molecular Dynamics ◽

Molecular Docking ◽

Molecular Dynamics Simulation ◽

Protein Kinase ◽

Point Mutation ◽

Protein Kinase B ◽

3D Qsar ◽

Dynamics Simulation ◽

Simulation Studies

Abstract Background Ovarian cancer is the world’s dreaded disease and its prevalence is expanding globally. The study of integrated molecular networks is crucial for the basic mechanism of cancer cells and their progression. During the present investigation, we have examined different flavonoids that target protein kinases B (AKT1) protein which exerts their anticancer efficiency intriguing the role in cross-talk cell signalling, by metabolic processes through in-silico approaches. Method Molecular dynamics simulation (MDS) was performed to analyze and evaluate the stability of the complexes under physiological conditions and the results were congruent with molecular docking. This investigation revealed the effect of a point mutation (W80R), considered based on their frequency of occurrence, with AKT1 protein. Results The ligand with high docking scores and favourable behaviour on dynamic simulations are proposed as potential W80R inhibitors. A virtual screening analysis was performed with 12,000 flavonoids satisfying Lipinski’s rule of five according to which drug-likeness is predicted based on its pharmacological and biological properties to be active and taken orally. The pharmacokinetic ADME (adsorption, digestion, metabolism, and excretion) studies featured drug-likeness. Subsequently, a statistically significant 3D-QSAR model of high correlation coefficient (R2) with 0.822 and cross-validation coefficient (Q2) with 0.6132 at 4 component PLS (partial least square) were used to verify the accuracy of the models. Taxifolin holds good interactions with the binding domain of W80R, highest Glide score of − 9.63 kcal/mol with OH of GLU234 and H bond ASP274 and LEU156 amino acid residues and one pi-cation interaction and one hydrophobic bond with LYS276. Conclusion Natural compounds have always been a richest source of active compounds with a wide variety of structures, therefore, these compounds showed a special inspiration for medical chemists. The present study has aimed molecular docking and molecular dynamics simulation studies on taxifolin targeting W80R mutant protein of protein kinase B/serine- threonine kinase/AKT1 (EC:2.7.11.1) protein of ovarian cancer for designing therapeutic intervention. The expected result supported the molecular cause in a mutant form which resulted in a gain of ovarian cancer. Here we discussed validations computationally and yet experimental evaluation or in vivo studies are endorsed for further study. Several of these compounds should become the next marvels for early detection of ovarian cancer.

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