Molecular Simulation Techniques Research Articles

Subdiffusive Reaction Model of Molecular Species in Liquid Layers: Fractional Reaction-Telegraph Approach

In recent years, different experimental works with molecular simulation techniques have been developed to study the transport of plasma-generated reactive species in liquid layers. Here, we improve the classical transport model that describes the molecular species movement in liquid layers via considering the fractional reaction–telegraph equation. We have considered the fractional equation to describe a non-Brownian motion of molecular species in a liquid layer, which have different diffusivities. The analytical solution of the fractional reaction–telegraph equation, which is defined in terms of the Caputo fractional derivative, is obtained by using the Laplace–Fourier technique. The profiles of species density with the mean square displacement are discussed in each case for different values of the time-fractional order and relaxation time.

Analysis of Charged Peptide Loop-Flipping across a Lipid Bilayer Using the String Method with Swarms of Trajectories.

The hydrophobic core of the lipid bilayer is conventionally considered a barrier to the translocation of charged species such that the translocation of even single ions occurs on long time scales. In contrast, experiments have revealed that some materials, including peptides, proteins, and nanoparticles, can translocate multiple charged moieties across the bilayer on experimentally relevant time scales. Understanding the molecular mechanisms underlying this behavior is challenging because resolving corresponding free-energy landscapes with molecular simulation techniques is computationally expensive. To address this challenge, we use atomistic molecular dynamics simulations with the swarms-of-trajectories (SOT) string method to analyze charge translocation pathways across single-component lipid bilayers as a function of multiple collective variables. We first demonstrate that the SOT string method can reproduce the free-energy barrier for the translocation of a charged lysine amino acid analogue in good agreement with the literature. We then obtain minimum free-energy pathways for the translocation, or flipping, of charged peptide loops across the lipid bilayer by utilizing trajectories from prior temperature-accelerated molecular dynamics (TAMD) simulations as initial configurations. The corresponding potential of mean force calculations reveal that the protonation of a central membrane-exposed aspartate residue substantially reduces the free-energy barrier for flipping charged loops by modulating the water content of the bilayer. These results provide new insight into the thermodynamics underlying loop-flipping processes and highlight how the combination of TAMD and the SOT string method can be used to understand complex charge translocation mechanisms.

Biomolecular Simulations with the Three-Dimensional Reference Interaction Site Model with the Kovalenko-Hirata Closure Molecular Solvation Theory.

The statistical mechanics-based 3-dimensional reference interaction site model with the Kovalenko-Hirata closure (3D-RISM-KH) molecular solvation theory has proven to be an essential part of a multiscale modeling framework, covering a vast region of molecular simulation techniques. The successful application ranges from the small molecule solvation energy to the bulk phase behavior of polymers, macromolecules, etc. The 3D-RISM-KH successfully predicts and explains the molecular mechanisms of self-assembly and aggregation of proteins and peptides related to neurodegeneration, protein-ligand binding, and structure-function related solvation properties. Upon coupling the 3D-RISM-KH theory with a novel multiple time-step molecular dynamic (MD) of the solute biomolecule stabilized by the optimized isokinetic Nosé–Hoover chain thermostat driven by effective solvation forces obtained from 3D-RISM-KH and extrapolated forward by generalized solvation force extrapolation (GSFE), gigantic outer time-steps up to picoseconds to accurately calculate equilibrium properties were obtained in this new quasidynamics protocol. The multiscale OIN/GSFE/3D-RISM-KH algorithm was implemented in the Amber package and well documented for fully flexible model of alanine dipeptide, miniprotein 1L2Y, and protein G in aqueous solution, with a solvent sampling rate ~150 times faster than a standard MD simulation in explicit water. Further acceleration in computation can be achieved by modifying the extent of solvation layers considered in the calculation, as well as by modifying existing closure relations. This enhanced simulation technique has proven applications in protein-ligand binding energy calculations, ligand/solvent binding site prediction, molecular solvation energy calculations, etc. Applications of the RISM-KH theory in molecular simulation are discussed in this work.

Multi-Spectroscopic and Molecular Simulation Approaches to Characterize the Intercalation Binding of 1-Naphthaleneacetic Acid With Calf Thymus DNA

1–Naphthaleneacetic acid (NAA), having high-quality biological activity and great yield-increasing potential in agricultural production, is a broad-spectrum plant growth regulator. Although NAA is of low toxicity, it can affect the balance of the human metabolism and damage the body if it is used in high quantity for a long time. In this study, the interaction of NAA with calf thymus DNA (ctDNA) was investigated under simulated human physiological acidity (pH 7.4) using fluorescence, ultraviolet-visible absorption, and circular dichroism spectroscopy combined with viscosity measurements and molecular simulation techniques. The quenching of the endogenous fluorescence of NAA by ctDNA, observed in the fluorescence spectrum experiment, was a mixed quenching process that mainly resulted from the formation of the NAA–ctDNA complex. NAA mainly interacted with ctDNA through hydrophobic interaction, and the binding constant and quenching constant at room temperature (298 K) were 0.60 × 105 L mol−1 and 1.58 × 104 L mol−1, respectively. Moreover, the intercalation mode between NAA and ctDNA was verified in the analysis of melting point, KI measurements, and the viscosity of ctDNA. The results were confirmed by molecular simulation, and it showed that NAA was enriched near the C–G base of ctDNA. As shown in circular dichroism spectra, the positive peak intensity of ctDNA intensified along with a certain degree of redshift, while the negative peak intensity decreased after binding with NAA, suggesting that the binding of NAA induced the transformation of the secondary structure of ctDNA from B-form to A-form. These researches will help to understand the hazards of NAA to the human body more comprehensively and concretely, to better guide the use of NAA in industry and agriculture.

Study on the Regulation of Piracetam Crystallization Behavior

AbstractPowder X‐ray diffraction, scanning electron microscopy, and molecular simulation techniques are used to analyze the crystallization of piracetam under different solvents and different cooling rates. The crystallization of piracetam in methanol system is controlled by thermodynamics, and it is easy to form stable polymorph. The crystallization of piracetam in isopropanol system is controlled by kinetics and forms metastable polymorph. The crystallization of piracetam in the ethanol system is controlled by thermodynamics and kinetics, and the cooling rate affects the formation of the crystal polymorphs, which is easy to be mixed. Dmol3 is used to calculate the energy, electrostatic potential, and frontier orbital energy of piracetam molecules in form II and form III configurations molecules in different systems. The results show that the methanol system is easier to form stable polymorph than the ethanol system.

In silico studies on stilbenolignan analogues as SARS-CoV-2 Mpro inhibitors

COVID-19, a new strain of coronavirus family, was identified at the end of 2019 in China. The COVID-19 virus spread rapidly all over the world. Scientists strive to find virus-specific antivirals for the treatment of COVID-19. The present study reports a molecular docking study of the stilbenolignans and SARS-CoV-2 main protease (SARS-CoV-2 Mpro) inhibitors. The detailed interactions between the stilbenolignan analogues and SARS-CoV-2 Mpro inhibitors were determined as hydrophobic bonds, hydrogen bonds and electronic bonds, inhibition activity, ligand efficiency, bonding type and distance and etc. The binding energies of the stilbenolignan analogues were obtained from the molecular docking of SARS-CoV-2 Mpro. Lehmbachol D, Maackolin, Gnetucleistol, Gnetifolin F, Gnetofuran A and Aiphanol were found to be −7.7, −8.2, −7.3, −8.5, −8.0 and −7.3 kcal/mol, respectively. Osirus, Molinspiration and SwissADME chemoinformatic tools were used to examine ADMET properties, pharmacokinetic parameters and toxicological characteristics of the stilbenolignan analogues. All analogues obey the Lipinski’s rule of five. Furthermore, stilbenolignan analogues were studied to predict their binding affinities against SARS-CoV-2 Mpro using molecular modeling and simulation techniques, and the binding free energy calculations of all complexes were calculated using the molecular mechanics/Poisson–Boltzmann surface area (MM-PBSA) method. With the data presented here it has been observed that these analogues may be a good candidate for SARS-CoV-2 Mpro in vivo studies, so more research can be done on stilbenolignan analogues.

Experimental and computational study for X-65 steel corrosion mitigation effect of a synthesized cationic surfactant in 1 M HCl.

New cationic surfactant, named as N-(2-hydroxypropyl)-N, N-dimethyldodecan-1-aminium bromide (DPC12), was prepared, followed by characterization using FT-IR and 1HNMR spectroscopic techniques. DPC12 performance evaluated by several electrochemical analyses, including potentiodynamic polarization and AC impedance methods, confirmed the inhibition proprieties of the prepared cationic surfactant. Tafel curves presented that the prepared DPC12 served as a corrosion inhibitor with mixed-type. Inhibition efficiency is directly proportional to cationic surfactant concentration. By increasing concentration, efficiency increases until reaching 72.27% at 10-4M. DPC12 inhibition action was due to its adsorption over X65 surface and followed Langmuir isotherm model having chemisorption adsorption mode as provided by values of standard free energy (ΔG°ads).cationic adsorption affinity over X-65 steel corrosion in HCl (1 M) was proved via surface morphology studies with SEM analyses. Finally, the quantum chemical calculations supported the experimental findings with Materials Studio software 6.0 using density function (DFT) theory and monte carlo molecular simulation technique (MC).

How \u03bc-opioid receptor recognizes fentanyl

Roughly half of the drug overdose-related deaths in the United States are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, X-ray crystal structures of mOR in complex with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like opioids remains lacking. Exploiting the X-ray structure of BU72-bound mOR and several molecular simulation techniques, we elucidated the detailed binding mechanism of fentanyl. Surprisingly, in addition to the salt-bridge binding mode common to morphinan opiates, fentanyl can move deeper and form a stable hydrogen bond with the conserved His2976.52, which has been suggested to modulate mOR’s ligand affinity and pH dependence by previous mutagenesis experiments. Intriguingly, this secondary binding mode is only accessible when His2976.52 adopts a neutral HID tautomer. Alternative binding modes may represent a general mechanism in G protein-coupled receptor-ligand recognition.

Repurposing drugs and identification of inhibitors of integral proteins (spike protein and main protease) of SARS-CoV-2

The outbreak of Coronavirus infection (COVID-19) has prompted the World Health Organisation (WHO) to declare the outbreak, a Public Health Emergency of International concern. As part of the efforts to discover lead compounds for clinical use, 53 molecules were screened using molecular docking and dynamic simulations (MDS) techniques to identify potential inhibitors of SARS-CoV-2 spike protein (COVID-19 Sgp) and main protease (COVID-19 Mpro) or both. Lopinavir (LPV), nelfinavir (NEF), hydroxychloroquine (HCQ), remdesivir (RDV) and an irreversible inhibitor of SARS-CoV (N3) were used as standard drugs for COVID-19 Mpro, while zafirlukast (ZFK) and cefoperazone (CSP)) as standard drugs for COVID-19 Sgp. After 100 ns of MDS, with reference to standard drugs (N3, −52.463 Kcal/mol, NEF, −51.618 Kcal/mol, RDV, −48.780 Kcal/mol, LPV, −46.788 Kcal/mol, DRV, −33.655 Kcal/mol and HCQ, −21.065 Kcal/mol), five molecules, HCR, GRN, C3G, EGCG, and K7G were predicted to be promising inhibitors of COVID-19 Mpro with binding energies of −53.877 kcal/mol, −50.653 Kcal/mol, −48.600 kcal/mol, −47.798 kcal/mol and −46.902 kcal/mol, respectively. These lead molecules were then docked at receptor-binding domain (RBD) of COVID-19 Sgp to examine their inhibitory effects. C3G, GRN and K7G exhibited higher binding energies of −42.310 kcal/mol, −32.210 kcal/mol, −26.922 kcal/mol than the recorded values for the reference drugs (CSP, −35.509 kcal/mol, ZFK, −24.242 kcal/mol), respectively. The results of the binding energy and structural analyses from this study revealed that C3G, GRN and K7G could serve as potential dual inhibitors of COVID-19 Sgp and COVID-19 Mpro, while HCR and EGCG would be inhibitors of COVID-19 Mpro. Communicated by Ramaswamy H. Sarma

Influence of Water Molecules on Polarization Behavior and Time–Frequency Dielectric Properties of Cellulose Insulation

Oil-immersed power transformer plays an important role in power transmission and transformation engineering. Moisture is one of the important factors to determine its insulation performance. Molecular simulation technique is used to study the mechanism of water molecules on the micro polarization behavior of cellulose insulation materials. The number of hydrogen bonds, solubility parameters, total dipole moment and polarizability are analyzed. These characteristics explain the action mechanism of water molecules on cellulose insulation. At the same time, the time domain and frequency dielectric response of cellulose insulation materials with different moisture content are explored. The dielectric modulus spectrum is introduced to replace the traditional frequency dielectric spectroscopy to characterize the micro relaxation process of cellulose insulation under different moisture content. Finally, the characteristic parameters are extracted from the polarization, depolarization current and dielectric modulus spectrum curves to evaluate the moisture content of cellulose insulation materials. The results show that the number of hydrogen bonds, binding energy density, solubility parameter, total dipole moment and polarizability increase with the increase of water content. It should be noted that dielectric modulus spectroscopy can effectively characterize the relaxation behavior of cellulose insulation materials. The moisture content of cellulose insulation can be quantitatively evaluated by DC conductivity, insulation resistance, imaginary part relaxation peak of dielectric modulus and integral value of real part and imaginary part of dielectric modulus.

Insight into Rare Structurally Characterized Homotrinuclear CuII Non-Symmetric Salamo-Based Complex

A rare homotrinuclear CuII salamo-based complex [Cu3(L)2(μ-OAc)2(H2O)2]·2CHCl3·5H2O was prepared through the reaction of a non-symmetric salamo-based ligand H2L and Cu(OAc)2·H2O, and validated by elemental analyses, UV-Visible absorption, fluorescence and infrared spectra, molecular simulation and single-crystal X-ray analysis techniques. It is shown that three CuII atoms and two wholly deprotonated ligand (L)2− moieties form together a trinuclear 3:2 (M:L) complex with two coordination water molecules and two bi-dentate briging μ-acetate groups (μ-OAc−). Besides, the Hirshfeld surface analysis of the CuII complex was investigated. Compared with other ligands, the fluorescent strength of the CuII complex was evidently lowered, showing that the CuII ions possess fluorescent quenching effect.

Ab Initio Evaluation of the Redox Potential of Cytochrome c.

Various biochemical activities of metabolism and biosynthesis are fulfilled by redox processes with explicit electron exchange, which furnish redox enzymes with high chemical reactivity. However, theoretical investigation of a redox process, which simultaneously involves a complex electronic change at a redox metal center and conformational reorganization of the surrounding protein environment coupled to the electronic change, requires computationally conflicting approaches, highly accurate quantum chemical calculations, and long-time molecular dynamics (MD) simulations, limiting the physicochemical understanding of biological redox processes. Here, we theoretically examined a redox process of cytochrome c by means of a hybrid molecular simulation technique, which enables one to consistently treat the redox center at the ab initio quantum chemistry level of theory and the protein reorganization with long-time MD simulations on the microsecond timescale. The calculations successfully evaluated a large absolute redox potential, 4.34 eV, with errors of only 0.03 to 0.34 eV to the experimental ones without any problem-specific empirical parameters. Through the long-time MD sampling, large and nonlinear reorganization of the protein environment was unveiled and the molecular determinants for the redox potential were identified. The present ab initio approach significantly expands the applicability of theoretical investigation to biological redox systems with more electronically complicated redox centers such as polynuclear transition metal complexes.

Mreža protein-protein interakcija i protein-ligand doking - trenutno stanje i perspektive

Traditional research means, such as in vitro and in vivo models, have consistently been used by scientists to test hypotheses in biochemistry. Computational (in silico) methods have been increasingly devised and applied to testing and hypothesis development in biochemistry over the last decade. The aim of in silico methods is to analyze the quantitative aspects of scientific (big) data, whether these are stored in databases for large data or generated with the use of sophisticated modeling and simulation tools; to gain a fundamental understanding of numerous biochemical processes related, in particular, to large biological macromolecules by applying computational means to big biological data sets, and by computing biological system behavior. Computational methods used in biochemistry studies include proteomics-based bioinformatics, genome-wide mapping of protein-DNA interaction, as well as high-throughput mapping of the protein-protein interaction networks. Some of the vastly used molecular modeling and simulation techniques are Monte Carlo and Langevin (stochastic, Brownian) dynamics, statistical thermodynamics, molecular dynamics, continuum electrostatics, protein-ligand docking, protein-ligand affinity calculations, protein modeling techniques, and the protein folding process and enzyme action computer simulation. This paper presents a short review of two important methods used in the studies of biochemistry - protein-ligand docking and the prediction of protein-protein interaction networks.

Research on the application of molecular simulation technology in enhanced oil-gas recovery engineering

In recent years, molecular simulations have received extensive attention in the study of reservoir fluid and rock properties, interactions, and related phenomena at the atomistic scale. For example, in molecular dynamics simulation, interesting properties are taken out of the time evolution analysis of atomic positions and velocities by numerical solution of Newtonian equations for all atomic motion in the system. These technologies assists conducting “computer experiments” that might instead of be impossible, very costly, or even extremely perilous to carry out. Whether it is from the primary oil recovery to the tertiary oil recovery or from laboratory experiment to field test, it is difficult to clarify the oil displacement flow mechanism of underground reservoirs. Computer molecular simulation reveals the seepage mechanism of a certain oil displacement at the microscopic scale, and enriches the specific oil displacement flow theory system. And the molecular design and effect prediction of a certain oil-displacing agent were studied, and its role in the reservoir was simulated, and the most suitable oil-displacing agent and the best molecular structure of the most suitable oil-displacing agent were obtained. To give a theoretical basic for the development of oilfield flooding technology and enhanced oil/gas recovery. This paper presents an overview of molecular simulation techniques and its applications to explore enhanced oil/gas recovery engineering research, which will provide useful instructions for characterizing the reservoir fluid and rock and their behaviors in various oil-gas reserves, and it greatly contribute to perform optimal operation and better design of production plants.

Proton transfer in bulk water using the full adaptive QM/MM method: integration of solute- and solvent-adaptive approaches.

The quantum mechanical/molecular mechanical (QM/MM) method is a hybrid molecular simulation technique that increases the accessibility of local electronic structures of large systems. The technique combines the benefit of accuracy found in the QM method and that of cost efficiency found in the MM method. However, it is difficult to directly apply the QM/MM method to the dynamics of solution systems, particularly for proton transfer. As explained in the Grotthuss mechanism, proton transfer is a structural interconversion between hydronium ions and solvent water molecules. Hence, when the QM/MM method is applied, an adaptive treatment, namely on-the-fly revisions on molecular definitions, is required for both the solute and solvent. Although several solvent-adaptive methods have been proposed, a full adaptive framework, which is an approach that also considers adaptation for solutes, remains untapped. In this paper, we propose a new numerical expression for the coordinates of the excess proton and its control algorithm. Furthermore, we confirm that this method can stably and accurately simulate proton transfer dynamics in bulk water.

Molecular simulation and the collaborative computational projects

In the late 1970s, the embryonic UK research community in molecular simulation – physicists and physical chemists – organised itself around CCP5, one of a set of Collaborative Computational Projects in different fields. CCP5 acted to develop and use the software required by an evolving and expanding scientific agenda, to exploit quickly and efficiently the revolution in computing hardware and to educate and nurture the careers of future generations of researchers in the field. This collaboration formally began in 1980, and is still fully active now, 40 years later. Today, molecular simulation techniques, many of them pioneered by CCP5, are now used very widely, including in several other CCPs in the UK’s current family of Collaborative Computational Projects. This article tells the story of molecular simulation in the UK, with CCP5 itself at centre stage, using the written records in the CCP archives. The authors were, or are, all personally involved in this story.

Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations.

Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with the drugs in clinical use. Most of the drug-induced cardiotoxicity is associated with an off-target pharmacological blockade of K+ currents carried out by the cardiac Human-Ether-a-go-go-Related (hERG1) potassium channel. There is a compulsory preclinical stage safety assessment for the hERG1 blockade for all classes of drugs, which adds substantially to the cost of drug development. The availability of a high-resolution cryogenic electron microscopy (cryo-EM) structure for the channel in its open/depolarized state solved in 2017 enabled the application of molecular modeling for rapid assessment of drug blockade by molecular docking and simulation techniques. More importantly, if successful, in silico methods may allow a path to lead-compound salvaging by mapping out key block determinants. Here, we report the blind application of the site identification by the ligand competitive saturation (SILCS) protocol to map out druggable/regulatory hotspots in the hERG1 channel available for blockers and activators. The SILCS simulations use small solutes representative of common functional groups to sample the chemical space for the entire protein and its environment using all-atom simulations. The resulting chemical maps, FragMaps, explicitly account for receptor flexibility, protein-fragment interactions, and fragment desolvation penalty allowing for rapid ranking of potential ligands as blockers or nonblockers of hERG1. To illustrate the power of the approach, SILCS was applied to a test set of 55 blockers with diverse chemical scaffolds and pIC50 values measured under uniform conditions. The original SILCS model was based on the all-atom modeling of the hERG1 channel in an explicit lipid bilayer and was further augmented with a Bayesian-optimization/machine-learning (BML) stage employing an independent literature-derived training set of 163 molecules. BML approach was used to determine weighting factors for the FragMaps contributions to the scoring function. pIC50 predictions from the combined SILCS/BML approach to the 55 blockers showed a Pearson correlation (PC) coefficient of >0.535 relative to the experimental data. SILCS/BML model was shown to yield substantially improved performance as compared to commonly used rigid and flexible molecular docking methods for a well-established cohort of hERG1 blockers, where no correlation with experimental data was recorded. SILCS/BML results also suggest that a proper weighting of protonation states of common blockers present at physiological pH is essential for accurate predictions of blocker potency. The precalculated and optimized SILCS FragMaps can now be used for the rapid screening of small molecules for their cardiotoxic potential as well as for exploring alternative binding pockets in the hERG1 channel with applications to the rational design of activators.

Molecular simulation studies to reveal the binding mechanisms of shikonin derivatives inhibiting VEGFR-2 kinase

Traditional vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitors can manage angiogenesis; however, severe toxicity and resistance limit their long-term applications in clinical therapy. Shikonin (SHK) and its derivatives could be promising to inhibit the VEGFR-2 mediated angiogenesis, as they are reported to bind in the catalytic kinase domain with low affinity. However, the detailed molecular insights and binding dynamics of these natural inhibitors are unknown, which is crucial for potential SHK based lead design. Therefore, the present study employed molecular modeling and simulations techniques to get insight into the binding behaviors of SHK and its two derivates, β-hydroxyisovalerylshikonin (β-HIVS) and acetylshikonin (ACS). Here the intermolecular interactions between protein and ligands were studied by induced fit docking approach, which were further evaluated by treating QM/MM (quantum mechanics/molecular mechanics) and molecular dynamics (MD) simulation. The result showed that the naphthazarin ring of the SHK derivates is vital for strong binding to the catalytic domain; however, the binding stability can be modulated by the side chain modification. Because of having electrostatic potential, this ring makes essential interactions with the DFG (Asp1046 and Phe1047) motif and also allows interacting with the allosteric binding site. Taken together, the studies will advance our knowledge and scope for the development of new selective VEGFR-2 inhibitors based on SHK and its analogs.

A comprehensive methodology to screen metal-organic frameworks towards sustainable photofixation of nitrogen

Distinct photoactive material compositions have been investigated starting from the mid-70s to reduce energy and pollution associated with ammonia synthesis. Hitherto, photocatalysts suffer from low ammonia yield and incomprehensive understanding of the mechanisms. The target of this research is to develop a systematic and comprehensive approach to screen and design durable and efficient metal-organic frameworks (MOFs) as catalysts to drive the photofixation of nitrogen at atmospheric conditions. This work discusses the available databases in the context of photocatalysis for the first time and reviews essential descriptors by incorporating Quantum Mechanics and molecular simulation techniques, taking into consideration sustainability aspects. As a result of a study on Hypothetical MOFs, Zn3(BTC)2(C6H5) has shown to satisfy the requirement for photofixation of nitrogen, using hydrogen and nitrogen as inputs, to ammonia. Comparison between Zn3(BTC)2(C6H5) and NH2-MIL-125(Ti) has been made based on geometrical, bandgap, diffusion coefficients, adsorption properties and life cycle assessment analysis of the production phase.

Dihydroartemisinin as a potential drug candidate for cancer therapy: a structural-based virtual screening for multitarget profiling

Cancer is a rapidly growing non-communicable disease worldwide that is responsible for high mortality rates, which account for 9.6 million death in 2018. Dihydroartemisinin (DHA) is an active metabolite of artemisinin, an active principle present in the Chinese medicinal plant Artemisia annua used for malaria treatment. Dihydroartemisinin possesses remarkable and selective anticancer properties however the underlying mechanism of the antitumor effects of DHA from the structural point of view is still not yet elucidated. In the present study, we employed molecular docking simulation techniques using Autodock suits to access the binding properties of dihydroartemisinin to multiple protein targets implicated in cancer pathogenesis. Its potential targets with comprehensive pharmacophore were predicted using a PharmMapper database. The co-crystallised structures of the protein were obtained from a Protein Data Bank and prepared for molecular docking simulation. Out of the 24 selected protein targets, DHA has shown about 29% excellent binding to the targets compared to their co-crystallised ligand. Additionally, 75% of the targets identified for dihydroartemisinin binding are protein kinases, and 25% are non-protein kinases. Hydroxyl functional group of dihydroartemisinin contributed to 58.5% of the total hydrogen interactions, while pyran (12.2%), endoperoxide (9.8%), and oxepane (19.5%) contributed to the remaining hydrogen bonding. The present findings have elucidated the possible antitumor properties of dihydroartemisinin through the structural-based virtual studies, which provides a lead to a safe and effective anticancer agent useful for cancer therapy. Communicated by Ramaswamy H. Sarma