Precision Docking Research Articles

Lateral Control in Precision Docking Using RTK-GNSS/INS and LiDAR for Localization

This article describes the design of a lateral control method for precision docking using GNSS/INS and LiDAR for localization. The aim of this study is to verify whether an automated driving bus can achieve the requirement of standard deviation of the lateral error (1.25 cm) using onboard sensors without additional infrastructure. To design the controller and decide the conditions of pilot tests on public roads, the vehicle dynamics, steering system, sensor dynamics, and disturbances are modelled. The steering system of the vehicle can be approximated as a second-order system, and the measuring time of the sensors are considered, which cause reduction of damping ratio in lateral dynamics. The numerical analysis revealed that the vehicle speed should be reduced to under 4.2 m/s (15 km/h) before precision docking starts, to make the lateral motion of the vehicle more stable. Experimental results show that the standard deviation of lateral error in precision docking using LiDAR for localization is 1.2 cm, which is slightly under the criterion threshold. The results also verify that the vehicle and sensor model describes the vehicle lateral motion appropriately.

Binding of agonist WAY-267,464 and antagonist WAY-methylated to oxytocin receptor probed by all-atom molecular dynamics simulations

AimsNon-peptide ligands of oxytocin receptor (OTR) have promising potentialities as therapeutic agents with improved pharmacological properties. WAY-267,464 is a non-peptide agonist which loses its agonist activity when its resorcinol moiety is methylated, yielding a partial antagonist (denoted here, WAY-Methylated). This study attempts to rationalize these opposing activities by comparative analyses of structural dynamicsof OTR in complex with these ligands. Main methodsGlide extra precision (XP) docking with and without positional constraints was employed to probe alternative binding poses of both WAY-267,464 and WAY-Methylated. The more preferred configuration of each system was subjected to an extended 2 μs MD simulation and the physics-based Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) binding energy was used to rank the complexes with improved accuracy, in addition to empirical-based Glide docking score. Network analysis was performed, and the identified critical residues were cross-referenced with the experimental mutagenesis data. Key findingsThe added methyl groups in the antagonist WAY-Methylated enhanced hydrophobicity, resulting in a flipped binding pose deeper in the binding pocket. Interestingly, OTR responded to the methylation by stabilizing the initial inactive conformation, decreasing fluctuations and increasing the overall secondary structural composition. Conversely, the agonist WAY-267,464 produced larger fluctuations to allow the receptor to change from the default inactive state to a state of partial activation. These transitions were further supported by the identified critical residues overlapping with experimental mutagenesis data. SignificanceThese findings provide insights into the activation mechanism of OTR by WAY-267.464 and its antagonism by WAY-Methylated.

Structure-based screening and validation of bioactive compounds as Zika virus methyltransferase (MTase) inhibitors through first-principle density functional theory, classical molecular simulation and QM/MM affinity estimation

Recent Zika virus (ZIKV) outbreak and association with human diseases such as neurological disorders have raised global health concerns. However, in the absence of an approved anti-ZIKV drug has generated urgency for the drug development against ZIKV infection. Here, structure-based virtual screening of 8589 bioactive compounds, screened at the substrate-binding site of ZIKV nonstructural 5 (NS5)-based structure N-terminal methyltransferase (MTase) domain followed by ADMET (absorption, distribution, metabolism, excretion and toxicity) profiling concluded the four potential lead inhibitors, i.e. (4-acetylamino-benzenesulfonylamino)-acetic acid (F3342-0450), 3-(5-methylfuran-2-yl)-N-(4-sulfamoylphenyl)propanamide (F1736-0142), 8-(2-hydroxy-ethylamino)-1,3-dimethyl-7-(3-methyl-benzyl)-3,7-dihydro-purine-2,6-dione (F0886-0080) and N-[4-(aminosulfonyl)phenyl]-2,3-dihydro-1,4-benzodioxine-2-carboxamide (F0451-2187). Collectively, extra precision docking and Density Functional Theory(DFT) calculations studies identified the F3342-0450 molecule, having strong interactions on the active site of MTase, further supported by molecular dynamics simulation, binding affinity and hybrid QM/MM calculations, suggest a new drug molecule for the antiviral drug development against ZIKV infection. Communicated by Ramaswamy H. Sarma

Anticoagulant activity screening of an in-house database of natural compounds for discovering novel selective factor Xa inhibitors; a combined in silico and in vitro approach

Traditional edible natural products enclose a wealth of anticoagulants that can be prospected for new selective factor Xa inhibitors. Unlike multitargeted anticoagulants, selective factor Xa inhibitors effectively block coagulation cascade with a broader therapeutic window. In the present study, an in-house database comprises 3D structures of 1571 compounds from 26 natural products previously reported to enhance the bleeding tendency was compiled. Virtual screening (VS) of the constructed database to discover active FXa inhibitors was performed using sequential structure-based VS by Glide extra precision docking followed by ligand-based VS through pharmacophore modeling and 3D-QSAR. The implemented approach provoked liquorice, trifolium and olive as candidates for chromogenic in vitro FXa inhibitory assay with IC50 values of 0.363, 0.729, and 0.866 mg/mL, respectively. Evaluation of liquorice solvent fractions revealed that ethyl acetate fraction produced 97.93 ± 0.019% inhibition of FXa. The adopted integrated strategy can be implemented for isolation of potent, selective nature-based FXa inhibitors.

Pharmacophore-guided fragment-based design of novel mammalian target of rapamycin inhibitors: extra precision docking, fingerprint-based 2D and atom-based 3D-QSAR modelling

Rapamycin and their derivatives known as rapalogs were the first-generation mTOR inhibitors which interacted with mTORC1 but not with the mTORC2 protein. Second-generation inhibitors could bind with both and showed excellent anti-proliferative activity. Our aim was to design novel mTOR inhibitors which could bind at both the allosteric and the kinase site. The FRB domain is present in both the mTORC1 and mTORC2 protein complexes. We have employed e-pharmacophore-guided fragment-based design to develop novel mTOR inhibitors. The affinity of designed molecules at both the sites was analysed using molecular docking in extra precision mode. The atom-based 3D-QSAR model was developed to predict the activity while the fingerprint-based 2D-QSAR model was employed to refine an identified hit as potent dual mTOR inhibitor. Ligand ASK23 showed a docking score of −15.452 kcal/mol at the allosteric site (PDB ID 5GPG) while ASK38 showed a docking score of −11.535 kcal/mol at the kinase site (PDB ID 4JT6). Ligand ASK12 showed binding energy of −106.23 kcal/mol at the allosteric site. Refined molecule ASK12a from ASK12 showed the highest predicted activity (pIC50: 6.512). The stability of the best hits and receptor complex was analysed using molecular dynamics simulation studies. Herein we report five potential mTOR dual inhibitors based on the predicted activity, drug-likeness analysis and off-target effects. To the best of our knowledge, this is the first report on pharmacophore-guided fragment-based drug design for mTOR inhibitors. This design strategy can be used for the rational drug design against other proteins for which only apo-structures are available. Communicated by Ramaswamy H. Sarma

Structure-guided screening of chemical database to identify NS3-NS2B inhibitors for effective therapeutic application in dengue infection.

Dengue infection is the most common arthropod-borne disease caused by dengue viruses, predominantly affecting millions of human beings annually. To find out promising chemical entities for therapeutic application in Dengue, in the current research, a multi-step virtual screening effort was conceived to screen out the entire "screening library" of the Asinex database. Initially, through "Lipinski rule of five" filtration criterion almost 0.6 million compounds were collected and docked with NS3-NS2B protein. Thereby, the chemical space was reduced to about 3500 compounds through the analysis of binding affinity obtained from molecular docking study in AutoDock Vina. Further, the "Virtual Screening Workflow" (VSW) utility of Schrödinger suite was used, which follows a stepwise multiple docking programs such as - high-throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking, and in postprocessing analysis the MM-GBSA based free binding energy calculation. Finally, five potent molecules were proposed as potential inhibitors for the dengue NS3-NS2B protein based on the investigation of molecular interactions map and protein-ligand fingerprint analyses. Different pharmacokinetics and drug-likeness parameters were also checked, which favour the potentiality of selected molecules for being drug-like candidates. The molecular dynamics (MD) simulation analyses of protein-ligand complexes were explained that NS3-NS2B bound with proposed molecules quite stable in dynamic states as observed from the root means square deviation (RMSD) and root means square fluctuation (RMSF) parameters. The binding free energy was calculated using MM-GBSA method from the MD simulation trajectories revealed that all proposed molecules possess such a strong binding affinity towards the dengue NS3-NS2B protein. Therefore, proposed molecules may be potential chemical components for effective inhibition of dengue NS3-NS2B protein subjected to experimental validation.

Structure-based screening and molecular dynamics simulation studies for the identification of potential acetylcholinesterase inhibitors

ABSTRACTAlzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disease characterised by the appearance of amyloid β plaques and neurofibrillary tangles in the brain. The loss of cholinergic neurons is considered to be one of the contributing factors for cognitive and memory deficits in the disease. Donepezil, the most successful and prescribed drug to treat the symptoms of AD, is acetylcholinesterase (AChE) inhibitor that improves the memory and brain’s cognitive functions. In this study, the pharmacophoric features of donepezil were mapped from its cocrystal with AChE and were used to screen the Zinc15 database. The obtained hits were subjected to molecular properties and PAINS filter. The homology modelling and molecular dynamics (MD) were performed to prepare selected AChE protein model (PDB id 4EY7) for advanced studies. The virtual screening and precision docking led to the identification of five compounds. The ADMET property prediction and free energy calculations were carried out to obtain three final compounds. The Alanine scanning and MD study of the compounds viz. ZINC000013719534, ZINC000035551243 and ZINC000035596918 produced stable complexes of the ligands. The identified virtual leads have the potential for better AChE inhibition.HighlightsPharmacophore mapping of donepezil was developed from PDB id 4EY7.Pharmacophore-based screening yielded 601 compounds with RMSD < 0.5 Å.PAINS and Drug likeliness filtration resulted in 199 compounds for further virtual screening and precision docking studies.Free binding energy and ADMET studies provided three active compounds.The molecular dynamics study indicated that the compounds ZINC000013719534, ZINC000035551243 and ZINC000035596918 formed stable interactions with the protein.

Exploring the potent inhibitors and binding modes of phospholipase A2 through in silico investigation

Snake venom of Naja naja comprises of several types of enzymes, and among them, water-soluble proteolytic enzyme, phospholipase A2 (PLA2), is noteworthy for its numerous adverse effects, such as cytotoxicity, cardiotoxicity, hemolytic, anti-coagulant, and hypotensive effects, including being highly potent as a neurotoxin. Limited anti-venom therapy (with their lower efficacy) has attracted considerable pharmacological interest to develop potent inhibitors of PLA2. Thus, 34 experimentally proven and diverse synthetic inhibitors of PLA2 were screened primarily on the basis of Glide extra precision docking and MM-GBSA rescoring function. Then, ten potential hits were subjected to induced fit docking, in which top three potential inhibitors were considered, and those were found to interact with Ca2+, disulfide binding site, and phosphatidylcholine activation sites, thereby, possibly disrupting the catalytic activity of Ca2+ as well as the inflammatory functions of PLA2. These compounds showed positive remarks on various physiochemical properties and pharmacologically relevant descriptors. Gap energy and thermodynamic properties were investigated by employing density functional theory for all compounds to understand their chemical reactivity and thermodynamic stability. Molecular dynamics simulation was performed for 100 ns in order to evaluate the stability and binding modes of docked complexes, and the energy of binding was calculated through MM-PBSA analysis. On the whole, the proposed compounds could be used for targeted inhibition. Communicated by Ramaswamy H. Sarma

Novel docking controller for autonomous aerial refueling with probe direct control and learning-based preview method

Abstract Autonomous aerial refueling (AAR) has always been a hot research area due to its significant application and complicated control problem. In order to improve the docking precision of AAR, a novel docking controller with probe direct control and learning-based preview method is proposed. Firstly, the controlled object is transformed from receiver barycenter to probe tactfully. Then, a suitable probe direct controller designed via the combination of reference-observer-based tracking control method and the high order sliding mode control method is proposed for the probe direct control. Furthermore, a learning-based preview method is introduced to solve the tracking lag problem. The prediction of drogue motion is considered in the reference signal. Then, a novel learning algorithm, named deep learning and reinforcement learning (DLRL), which combines deep learning (DL) and reinforcement learning (RL) spatially rather than structurally like deep reinforcement learning (DRL) is proposed to generate the preview time adaptively. And a novel preview index is proposed to adapt for it. Through the combination of probe direct controller and learning-based preview method, the proposed docking controller could improve the tracking precision largely. Effectiveness of the proposed method is demonstrated by the simulations.

A study on large parts precision docking method based on 6-axis industrial robot

In view of the docking assembly difficulties of spacecraft large parts, resulting from the irregular contour and the inadequacy of process clamping points, this paper puts forward a method fitting the attitude relations of the docking parts based on the coordinates of the feature points, obtaining the target attitude of the docking parts based on the process constraints, and controlling 6-axis industrial robot achieves precise docking of large parts. Firstly, the composition of the large parts docking system is introduced, and the docking model is described by the selection of the measurement feature points and the establishment of the coordinate system. After that, a docking control algorithm based on the attitude constraints of large parts is established. Finally, In the RobotStudio and Matlab co-simulation environment, the attitude adjustment process of the large parts is simulated. The simulation results show that this study provides an effective method for precision docking of spacecraft engine large parts based on feature points, which is completed by 6-axis industrial robot.

Research and Development of High Precision Robot Automatic Docking System Based on mxAutomation

In this paper we designs an automatic docking system to simulate the precision docking of the key components in aerospace assembly line. By using the robot to make the actual measurement of the experimental workpiece, we figure out the spatial coordinate system of the workpiece which correspond to the robot world coordinate system. This coordinate system is used to automatically control the robot to calculate the motion trajectory and complete the precision docking work. This system is characterized by the use of Siemens PLC to control the KUKA robot dynamically through the KUKA-TIA-Library interface, which can meet the requirements of flexibility and customization in aerospace industry.

Drug repurposing against arabinosyl transferase (EmbC) of Mycobacterium tuberculosis: Essential dynamics and free energy minima based binding mechanics analysis

Arabinosyl tranferases (embA, embB, embC) are the key enzymes responsible for biogenesis of arabinan domain of arabinogalactan (AG) and lipoarabinomannan (LAM), two major heteropolysaccharide constituents of the peculiar mycobacterial cell envelope. EmbC is predominantly responsible for LAM synthesis and has been commonly associated with Ethambutol resistance. We have screened the FDA library against EmbC to reposition a drug better than Ethambutol with higher binding affinity to Embc. High throughput virtual screening followed by extra precision docking using Glide gave two best leads i.e. Terlipressin and Amikacin with docking score of −11.39 kcal/mol and −10.71 kcal/mol, respectively. Binding mechanics of the selected drugs was elucidated through long range molecular dynamics simulations (100 ns) using binding free energy rescoring, essential dynamics and free energy minima based approaches, thus revealing the most stable binding modes of Terlipressin with EmbC. Our study establishes the EmbC binding potential of the repurposed drugs Terlipressin and Amikacin.

An in silico approach to discover the best molecular modeling strategy for designing novel CDK4 inhibitors.

Designing of new potential specific inhibitors for CDK4 is very important in cancer therapy. The imperative features that can inhibit CDK4 were identified and refined by docking under standard precision mode, extra precision mode, extra precision mode with core constraints, and induced fit using extra precision protocol. Statistically significant correlation was observed when docking experiments in the extra precision mode carried out by applying core constraints in the ligand molecule which forms two specific hydrogen bonds with Val 96 of CDK4. Importance of solvent molecule was understood by molecular dynamic simulation studies. The presence of a water molecule which forms a hydrogen bond with Asp158 increased the binding affinity between the ligand and CDK4. Hydrogen bonding interactions, pi-pi stacking interactions, and salt bridge formation were the key interactions contributing to the increased inhibitory value. All these findings were supported by the high correlation between pIC50 and glide emodel values. Binding energy determinations under various conditions also support these findings. Thus, extra precision docking with ligand constraints through the insertion of water molecule effectively classified the actives and inactives of given set of molecules and can be used for virtual screening of new molecules for promising biological activity.

Asymmetric glycan recognition among α-β monomers of Spatholobus parviflorus lectin: an insilico insight

Protein-carbohydrate recognition, an important form of inter-cell communication, plays promising role in biological events. Extensive studies were already done in areas of protein-carbohydrate recognition using legume lectins for drug targeting. In this study, an attempt was made to reveal the interaction homogeneity of carbohydrates and their comparative analysis of binding modes towards α and β monomers of Spatholobus parviflorus lectin (SPL). The sugars, based on their structural diversity in information coding were selected for virtual screening. Based on the glidescores, 20 sugars were screened and extra precision docking exercises were carried out to explore the variabilities in their binding affinities exhibited by SPL monomers. Among the sugars, raffinose exhibited highest affinity towards the α and β monomers. These alterations exhibited by α and β monomers may be due to its asymmetry in the pairing of subunits. This prediction, deciphered the in silico binding report of sugars with SPL, along with their inconsistency in binding with monomeric units.

Asymmetric glycan recognition among α-β monomers of Spatholobus parviflorus lectin: an insilico insight

Protein-carbohydrate recognition, an important form of inter-cell communication, plays promising role in biological events. Extensive studies were already done in areas of protein-carbohydrate recognition using legume lectins for drug targeting. In this study, an attempt was made to reveal the interaction homogeneity of carbohydrates and their comparative analysis of binding modes towards α and β monomers of Spatholobus parviflorus lectin (SPL). The sugars, based on their structural diversity in information coding were selected for virtual screening. Based on the glidescores, 20 sugars were screened and extra precision docking exercises were carried out to explore the variabilities in their binding affinities exhibited by SPL monomers. Among the sugars, raffinose exhibited highest affinity towards the α and β monomers. These alterations exhibited by α and β monomers may be due to its asymmetry in the pairing of subunits. This prediction, deciphered the in silico binding report of sugars with SPL, along with their inconsistency in binding with monomeric units.

Photophysical and thermodynamic evaluation on the in vitro and in silico binding profile of Camptothecin with DNA

Camptothecin (CMT) is an anti-tumour alkaloid drug exhibiting selective topoisomerase-I inhibitory activity by eventually hindering dynamic functions of DNA duplex via initiating apoptosis. Unravelling the binding mechanism of CMT with bio macromolecular systems can offer fundamental information regarding the mechanism of actions which can lead to the design of rational proactive drugs. This study endeavoured the binding interactions of CMT with calf thymus DNA (ct-DNA) along with the structural alterations attained by the DNA duplex owing to CMT interactions through multi-spectroscopic, calorimetric and molecular docking studies. The UV–visible absorbance and fluorescence quenching studies revealed the binding strength of CMT with ct-DNA, evident from the binding constants K1 = 3.79 × 103 M−1 and Kq = 2 × 103 M−1. The time-resolved lifetime measurements inferred that the quenching was static due to the non-fluorescent ground state complex formation. The dye displacement study, temperature melting and viscosity measurements established a typical non-intercalative binding mode of CMT with ct-DNA. The binding isotherm deduced from ITC was found to be spontaneous and exothermic exerting a promising ΔG value of −6.2 kcal mol−1. The thermal kinetic parameters implied that the forces primarily involved in the CMT-ct-DNA complexation are hydrogen bonding and van der Waals interactions. Moreover, the structural alterations of DNA duplex reflected in the CD and FTIR spectra could undeniably confirm the groove binding manner of CMT. The in silico extra precision docking study explored more accurate molecular illustrations of sequence specific minor groove binding mechanism evolved between CMT and DNA corroborating well with the experimental results. These innovative findings may shorten the path towards the development of novel and more effective CMT drug derivatives.

Random drift particle swarm optimisation algorithm for highly flexible protein-ligand docking

Molecular docking has emerged as an important tool in drug design and development. Currently, there is a relatively large and ever-increasing number of molecular docking programs. However, despite the great advances in the docking technique over the last decade, most methods cannot be used to dock highly flexible ligands successfully. In this study, based on the Autodock software, a new search algorithm, hybrid algorithm of Random Drift Particle Swarm Optimisation and local search (LRDPSO), that focuses on protein-ligand applications was presented. In our approach, we considered the ligand flexibility and strategies that aimed to improve binding affinity prediction in the context of a docking-based investigation. The experimental results revealed that our approach led to a substantially lower docking energy and higher docking precision in comparison to the LGA, PSO and QPSO algorithms. The LRDPSO algorithm was able to identify the correct binding mode of 83.6% of the complexes. In comparison, the accuracy of QPSO, PSO and LGA is 73.1%, 68.7% and 68.7%, respectively. For LRDPSO docking, satisfactory docking results can be obtained when relatively big ligands with many rotatable bonds are docked against protein binding pockets in which flexibility does play an important role. Thus, the novel LRDPSO algorithm predictions for highly flexible ligands are more reliable, and would increase the predictive power and widen the applications of this important computational tool.

In Silico approach for the Rational Design of Tankyrase I Inhibitors-A Case Study on Flavone based Anticancer Leads

In the present study, a series flavones were selected form the literature. The selected compounds were docked at the active site of Tankyrase I utilizing extra precision docking protocol. The docking scores of the selected compounds were then compared with a standard reported in the literature. The compounds showed comparable binding affinity at the active site of Tankyrase I. The study also enabled us in identifying the possible substitution sites to enhance the activity as well as selectivity towards the enzyme Tankyrase I. This could help the researchers in identifying lead molecule for colorectal cancer.

Development of an Integrated Laser Sensors Based Measurement System for Large-Scale Components Automated Assembly Application

In the field of precision docking or assembly of large scale, the orientation and position measurement system is quite demanding. This paper proposes a long-range measuring system with the combination of low-cost tilt sensor and laser sensors to achieve orientation and position deviation during the process of docking in the outdoor environment. The measuring principle and the system construction of the integrated system are introduced in detail. Subsequently, the geometric measurement model for each assembly stage is established. The measurement system is dividing the whole measuring process into six major alignment steps to complete the automated assembly task. Then, the proposed measuring system is applied to an automated antenna assembly system to demonstrate its effectiveness in large-scale measurement. Validation experiments were performed and the preliminary result shows that the proposed system could achieve high efficiency and accuracy for large volume components automated assembly. Our main contribution is developing a new orientation and position measuring method for 6-DOF automated assembly in the outdoor environment and proposing a new approach to reduce the errors in each direction based on the step-by-step adjustment, which provides a new idea for docking and assembly in complex environment.

Identification of novel scaffolds to inhibit human mitotic kinesin Eg5 targeting the second allosteric binding site using in silico methods

Human mitotic kinesins are potential anticancer drug targets because of their essential role in mitotic cell division. The kinesin Eg5 (Kinesin-5, kif11) has gained much attention in this regard and has many inhibitors in different phases of clinical trials. All drug candidates considered for Eg5 so far binds to the binding site (Site 1) formed by the loop L5, helices α2 and α3 and are uncompetitive to ATP/ADP. Recently, it has been reported that Eg5 also has a second binding site (Site 2) formed by helices α4 and α6. In the current work, we have screened the compounds in the diversity set-III from National Cancer Institute (NCI) and Zinc database to identify potential inhibitors for Eg5 that specifically binds to the site 2. The compounds were ranked based on the glide extra precision docking scores and the top ranked compounds were found to have pyridazine scaffold. The top five compounds were further evaluated for other drug like properties. Stability of protein-ligand complexes were analyzed using molecular dynamic simulations. Our studies suggest that pyridazine analogs have good MDCK, permeability properties and high binding affinity to the human Eg5.