scholarly journals A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: Probing the binding pathway of dasatinib to Src-kinase

2019 ◽  
Author(s):  
Farzin Sohraby ◽  
Mostafa Javaheri Moghadam ◽  
Masoud Aliyar ◽  
Hassan Aryapour
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Molecular Dynamics Simulations ◽  
Src Kinase ◽  
Deep Understanding ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Dynamics Simulations ◽  
Computational Resources ◽  
Binding Mechanisms

AbstractSmall molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.

A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase

2020 ◽  
Vol 36 (18) ◽  
pp. 4714-4720
Author(s):  
Farzin Sohraby ◽  
Mostafa Javaheri Moghadam ◽  
Masoud Aliyar ◽  
Hassan Aryapour
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Md Simulation ◽  
Src Kinase ◽  
Deep Understanding ◽  
Md Simulations ◽  
Binding Mode ◽  
Supplementary Information ◽  
Computational Resources ◽  
Binding Mechanisms

Abstract Summary Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased MD simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased MD simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) MD simulations, in this case a protein–ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nanosecond time scales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction. Availability and implementation The links of the tutorial and technical documents are accessible in the article. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations

Biomedicines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1197
Author(s):  
Vikas Kumar ◽  
Shraddha Parate ◽  
Gunjan Thakur ◽  
Gihwan Lee ◽  
Hyeon-Su Ro ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Binding Affinity ◽  
Cost Effective ◽  
Binding Mode ◽  
Kinase Domain ◽  
Dynamics Simulation ◽  
Mode Analysis ◽  
Atp Binding Site ◽  
Dynamics Simulations

The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits—ZINC20392430, SN00112175, SN00004718, and SN00262261—having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.

Flavin oxidation state impacts on nitrofuran antibiotic binding orientation in nitroreductases

2021 ◽  
Vol 478 (18) ◽  
pp. 3423-3428
Author(s):  
Helen S. Toogood ◽  
Nigel S. Scrutton
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Molecular Dynamics Simulations ◽  
Oxidation State ◽  
Binding Mode ◽  
Kinetic Mechanism ◽  
Binding Orientation ◽  
Nitrofuran Antibiotics ◽  
Dynamics Simulations ◽  
Binding Orientations

Nitroreductases catalyse the NAD(P)H-dependent nitro reduction in nitrofuran antibiotics, which activates them into cytotoxic molecules leading to cell death. The design of new effective nitrofuran antibiotics relies on knowledge of the kinetic mechanism and nitrofuran binding mode of microbial nitroreductases NfsA and NfsB. This has been hampered by multiple co-crystallisation studies revealing ligand binding in non-electron transfer competent states. In a recent study by Day et al. (2021) the authors investigated the likely reaction mechanism and mode of nitrofurantoin binding to NfsA using potentiometry, global kinetics analysis, crystallography and molecular dynamics simulations. Their findings suggest nitrofurantoin reduction proceeds via a direct hydride transfer from reduced FMN, while the crystallographic binding orientation is an inhibitory complex. Molecular dynamics simulations suggest ligand binding orientations is dependent on the oxidation state of the FMN. This study highlights the importance of utilising computational studies alongside traditional crystallographic approaches, when multiple stable ligand binding orientations can occur.

scholarly journals Variable time domain discretization methodology for molecular dynamics simulation of metallic compounds

2021 ◽  
Author(s):  
Jamal Zeinalov
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Molecular Dynamics Simulations ◽  
Dynamics Simulation ◽  
Time Step ◽  
Variable Time ◽  
Metallic Compounds ◽  
Dynamics Simulations ◽  
Computational Resources

The present work proposes a methodology to improve the computational requirements of molecular dynamics simulations while maintaining or improving the fidelity of the obtained results. The most common method of molecular dynamics simulation at present is the multi-force, constant time-step, explicit computation, which advances a single time step at a time to determine the next state of the system. The present work proposes a variable time-step strategy, where a single large simulation is subdivided into multiple time domains which redistribute computational resources where they are needed the most: in areas of higher than average potential or kinetic energy or highly dynamic areas around impurity clusters, void formations and crack propagations. The research focuses on the simulation of metallic compounds, as these form the basis of most common molecular dynamics simulations, and have been very thoroughly investigated over the years, thus providing a very extensive body of work for the purpose of comparison and validation of the proposed methodology. The novel methodology presented in this work allows to alleviate some of the limitations associated with the molecular dynamics methodologies and go beyond traditional scales of simulation. The proposed method has been observed to deliver 5 to 20 percent increase in simulation size domain while maintaining or improving the accuracy and computational cycle time. The benefits were observed to be greater for large simulations with one or more areas of higher than average kinetic or potential energy levels, such as those found during crack initiation and propagation, coating-substrate interface, localized pressure application or large thermal gradient. The large difference allows for very clear prioritization of computational resources for high energy areas and as a result provides for faster and more accurate simulation even with increased domain size. Conversely, this method has been observed to provide little to no benefit when simulating stable systems that are undergoing very slow change, such as (relatively) slow change in ambient temperature or pressure, or otherwise homogeneous internal and external boundary conditions. However, for the majority of applications described above, including coating deposition and additive manufacturing, the proposed methodology will yield substantial increase in both simulation size and accuracy, since in the aforementioned processes kinetic and potential energy gradients across the simulation are typically very significant

scholarly journals Molecular-dynamics investigation of molecular flexibility in ligand binding

1992 ◽  
Vol 288 (1) ◽  
pp. 109-116 ◽  
Author(s):  
B Mao
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Ligand Binding ◽  
Molecular Dynamics Simulations ◽  
Computational Method ◽  
Conformational Space ◽  
Dynamics Simulation ◽  
General Notion ◽  
Molecular Flexibility ◽  
Dynamics Simulations

The molecular flexibility of an inhibitor in ligand-binding process has been investigated by the mass-weighted molecular-dynamics simulation, a computational method adopted from the standard molecular-dynamics simulation and one by which the conformational space of a biomolecular system over potential energy barriers can be sampled effectively. The bimolecular complex of the aspartyl proteinase from Rhizopus chinensis, rhizopuspepsin, and an octapeptide inhibitor was previously studied in a mass-weighted molecular-dynamics simulation; the study has been extended for investigating the molecular flexibility in ligand binding. A series of mass-weighted molecular-dynamics simulations was carried out in which libration of the inhibitor dihedral angles was parametrically controlled, and threshold values of dihedral angle libration amplitudes were observed from monitoring the sampling of the enzyme binding pocket by the inhibitor in the simulations. The computational results are consistent with the general notion of molecular-flexibility requirement for ligand binding; the freedom of dihedral rotations of side-chain groups was found to be particularly important for ligand binding. Thus the critical degree of molecular flexibility which would contribute to effective enzyme inhibition can be obtained precisely from the modified molecular-dynamics simulations; the procedure described herein represents a first step toward providing quantitative measures of such a molecular-flexibility index for inhibitor molecules that have been otherwise targeted for optimal protein-ligand interactions.

scholarly journals Variable time domain discretization methodology for molecular dynamics simulation of metallic compounds

2021 ◽  
Author(s):  
Jamal Zeinalov
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Molecular Dynamics Simulations ◽  
Dynamics Simulation ◽  
Time Step ◽  
Variable Time ◽  
Metallic Compounds ◽  
Dynamics Simulations ◽  
Computational Resources

The present work proposes a methodology to improve the computational requirements of molecular dynamics simulations while maintaining or improving the fidelity of the obtained results. The most common method of molecular dynamics simulation at present is the multi-force, constant time-step, explicit computation, which advances a single time step at a time to determine the next state of the system. The present work proposes a variable time-step strategy, where a single large simulation is subdivided into multiple time domains which redistribute computational resources where they are needed the most: in areas of higher than average potential or kinetic energy or highly dynamic areas around impurity clusters, void formations and crack propagations. The research focuses on the simulation of metallic compounds, as these form the basis of most common molecular dynamics simulations, and have been very thoroughly investigated over the years, thus providing a very extensive body of work for the purpose of comparison and validation of the proposed methodology. The novel methodology presented in this work allows to alleviate some of the limitations associated with the molecular dynamics methodologies and go beyond traditional scales of simulation. The proposed method has been observed to deliver 5 to 20 percent increase in simulation size domain while maintaining or improving the accuracy and computational cycle time. The benefits were observed to be greater for large simulations with one or more areas of higher than average kinetic or potential energy levels, such as those found during crack initiation and propagation, coating-substrate interface, localized pressure application or large thermal gradient. The large difference allows for very clear prioritization of computational resources for high energy areas and as a result provides for faster and more accurate simulation even with increased domain size. Conversely, this method has been observed to provide little to no benefit when simulating stable systems that are undergoing very slow change, such as (relatively) slow change in ambient temperature or pressure, or otherwise homogeneous internal and external boundary conditions. However, for the majority of applications described above, including coating deposition and additive manufacturing, the proposed methodology will yield substantial increase in both simulation size and accuracy, since in the aforementioned processes kinetic and potential energy gradients across the simulation are typically very significant

scholarly journals Reactive molecular dynamics simulation of the high-temperature pyrolysis of 2,2′,2′′,4,4′,4′′,6,6′,6′′-nonanitro-1,1′:3′,1′′-terphenyl (NONA)

RSC Advances ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 5507-5515
Author(s):  
Liang Song ◽  
Feng-Qi Zhao ◽  
Si-Yu Xu ◽  
Xue-Hai Ju
Keyword(s):  
Molecular Dynamics ◽  
High Temperature ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Dynamics Simulation ◽  
Reactive Molecular Dynamics ◽  
Ring Compounds ◽  
Fused Ring ◽  
Dynamics Simulations

The bimolecular and fused ring compounds are found in the high-temperature pyrolysis of NONA using ReaxFF molecular dynamics simulations.

scholarly journals The Interplay of Cholesterol and Ligand Binding in hTSPO from Classical Molecular Dynamics Simulations

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1250
Author(s):  
Hien T. T. Lai ◽  
Alejandro Giorgetti ◽  
Giulia Rossetti ◽  
Toan T. Nguyen ◽  
Paolo Carloni ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Molecular Dynamics Simulations ◽  
Binding Site ◽  
Transmembrane Protein ◽  
Free Form ◽  
Experimental Investigations ◽  
Terminal Part ◽  
Dynamics Simulations ◽  
Cholesterol Binding

The translocator protein (TSPO) is a 18kDa transmembrane protein, ubiquitously present in human mitochondria. It is overexpressed in tumor cells and at the sites of neuroinflammation, thus representing an important biomarker, as well as a promising drug target. In mammalian TSPO, there are cholesterol–binding motifs, as well as a binding cavity able to accommodate different chemical compounds. Given the lack of structural information for the human protein, we built a model of human (h) TSPO in the apo state and in complex with PK11195, a molecule routinely used in positron emission tomography (PET) for imaging of neuroinflammatory sites. To better understand the interactions of PK11195 and cholesterol with this pharmacologically relevant protein, we ran molecular dynamics simulations of the apo and holo proteins embedded in a model membrane. We found that: (i) PK11195 stabilizes hTSPO structural fold; (ii) PK11195 might enter in the binding site through transmembrane helices I and II of hTSPO; (iii) PK11195 reduces the frequency of cholesterol binding to the lower, N–terminal part of hTSPO in the inner membrane leaflet, while this impact is less pronounced for the upper, C–terminal part in the outer membrane leaflet, where the ligand binding site is located; (iv) very interestingly, cholesterol most frequently binds simultaneously to the so-called CRAC and CARC regions in TM V in the free form (residues L150–X–Y152–X(3)–R156 and R135–X(2)–Y138–X(2)–L141, respectively). However, when the protein is in complex with PK11195, cholesterol binds equally frequently to the CRAC–resembling motif that we observed in TM I (residues L17–X(2)–F20–X(3)–R24) and to CRAC in TM V. We expect that the CRAC–like motif in TM I will be of interest in future experimental investigations. Thus, our MD simulations provide insight into the structural features of hTSPO and the previously unknown interplay between PK11195 and cholesterol interactions with this pharmacologically relevant protein.

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