Molecular Energy Calculations Research Articles

Prediction of Drug Potencies of BACE1 Inhibitors: A Molecular Dynamics Simulation and MM_GB(PB)SA Scoring

Alzheimer’s disease (AD) is a progressive neurodegenerative brain disorder. One of the important therapeutic approaches of AD is the inhibition of β-site APP cleaving enzyme-1 (BACE1). This enzyme plays a central role in the synthesis of the pathogenic β-amyloid peptides (Aβ) in Alzheimer’s disease. A group of potent BACE1 inhibitors with known X-ray structures (PDB ID 5i3X, 5i3Y, 5iE1, 5i3V, 5i3W, 4LC7, 3TPP) were studied by molecular dynamics simulation and binding energy calculation employing MM_GB(PB)SA. The calculated binding energies gave Kd values of 0.139 µM, 1.39 nM, 4.39 mM, 24.3 nM, 1.39 mM, 29.13 mM, and 193.07 nM, respectively. These inhibitors showed potent inhibitory activities in enzymatic and cell assays. The Kd values are compared with experimental values and the structures are discussed in view of the energy contributions to binding. Drug likeness of these inhibitors is also discussed. Accommodation of ligands in the catalytic site of BACE1 is discussed depending on the type of fragment involved in each structure. Molecular dynamics (MD) simulations and energy studies were used to explore the recognition of the selected BACE1 inhibitors by Asp32, Asp228, and the hydrophobic flap. The results show that selective BACE1 inhibition may be due to the formation of strong electrostatic interactions with Asp32 and Asp228 and a large number of hydrogen bonds, in addition to π–π and van der Waals interactions with the amino acid residues located inside the catalytic cavity. Interactions with the ligands show a similar binding mode with BACE1. These results help to rationalize the design of selective BACE1 inhibitors.

Quantum equation of motion for computing molecular excitation energies on a noisy quantum processor

The computation of molecular excitation energies is essential for predicting photo-induced reactions of chemical and technological interest. While the classical computing resources needed for this task scale poorly, quantum algorithms emerge as promising alternatives. In particular, the extension of the variational quantum eigensolver algorithm to the computation of the excitation energies is an attractive option. However, there is currently a lack of such algorithms for correlated molecular systems that is amenable to near-term, noisy hardware. In this work, we propose an extension of the well-established classical equation of motion approach to a quantum algorithm for the calculation of molecular excitation energies on noisy quantum computers. In particular, we demonstrate the efficiency of this approach in the calculation of the excitation energies of the LiH molecule on an IBM Quantum computer.3 MoreReceived 22 January 2020Accepted 23 September 2020DOI:https://doi.org/10.1103/PhysRevResearch.2.043140Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasQuantum algorithmsQuantum simulationQuantum Information

Structural and molecular basis of the interaction mechanism of selected drugs towards multiple targets of SARS-CoV-2 by molecular docking and dynamic simulation studies- deciphering the scope of repurposed drugs

The repurposing of FDA approved drugs is presently receiving attention for COVID-19 drug discovery. Previous studies revealed the binding potential of several FDA-approved drugs towards specific targets of SARS-CoV-2; however, limited studies are focused on the structural and molecular basis of interaction of these drugs towards multiple targets of SARS-CoV-2. The present study aimed to predict the binding potential of six FDA drugs towards fifteen protein targets of SARS-CoV-2 and propose the structural and molecular basis of the interaction by molecular docking and dynamic simulation. Based on the literature survey, fifteen potential targets of SARS-CoV-2, and six FDA drugs (Chloroquine, Hydroxychloroquine, Favipiravir, Lopinavir, Remdesivir, and Ritonavir) were selected. The binding potential of individual drug towards the selected targets was predicted by molecular docking in comparison with the binding of the same drugs with their usual targets. The stabilities of the best-docked conformations were confirmed by molecular dynamic simulation and energy calculations. Among the selected drugs, Ritonavir and Lopinavir showed better binding towards the prioritized targets with minimum binding energy (kcal/mol), cluster-RMS, number of interacting residues, and stabilizing forces when compared with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, later drugs demonstrated better binding when compared to the binding with their usual targets. Remdesvir showed better binding to the prioritized targets in comparison with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, but showed lesser binding potential when compared to the interaction between Ritonavir and Lopinavir and the prioritized targets. The structural and molecular basis of interactions suggest that the FDA drugs can be repurposed towards multiple targets of SARS-CoV-2, and the present computational models provide insights on the scope of repurposed drugs against COVID-19.

Discovery of a Novel Natural Allosteric Inhibitor That Targets NDM-1 Against Escherichia coli.

At present, the resistance of New Delhi metallo-β-lactamase-1 (NDM-1) to carbapenems and cephalosporins, one of the mechanisms of bacterial resistance against β-lactam antibiotics, poses a threat to human health. In this work, based on the virtual ligand screen method, we found that carnosic acid1 (CA), a natural compound, exhibited a significant inhibitory effect against NDM-1 (IC50 = 27.07 μM). Although carnosic acid did not display direct antibacterial activity, the combination of carnosic acid and meropenem still showed bactericidal activity after the loss of bactericidal effect of meropenem. The experimental results showed that carnosic acid can enhance the antibacterial activity of meropenem against Escherichia coli ZC-YN3. To explore the inhibitory mechanism of carnosic acid against NDM-1, we performed the molecular dynamics simulation and binding energy calculation for the NDM-1-CA complex system. Notably, the 3D structure of the complex obtained from molecular modeling indicates that the binding region of carnosic acid with NDM-1 was not situated in the active region of protein. Due to binding to the allosteric pocket of carnosic acid, the active region conformation of NDM-1 was observed to have been altered. The distance from the active center of the NDM-1-CA complex was larger than that of the free protein, leading to loss of activity. Then, the mutation experiments showed that carnosic acid had lower inhibitory activity against mutated protein than wild-type proteins. Fluorescence experiments verified the results reported above. Thus, our data indicate that carnosic acid is a potential NDM-1 inhibitor and is a promising drug for the treatment of NDM-1 producing pathogens.

Identification of potential inhibitors of coronavirus hemagglutinin-esterase using molecular docking, molecular dynamics simulation and binding free energy calculation.

The pandemic outbreak of the Corona viral infection has become a critical global health issue. Biophysical and structural evidence shows that spike protein possesses a high binding affinity towards host angiotensin-converting enzyme 2 and viral hemagglutinin-acetylesterase (HE) glycoprotein receptor. We selected HE as a target in this study to identify potential inhibitors using a combination of various computational approaches such as molecular docking, ADMET analysis, dynamics simulations and binding free energy calculations. Virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin as potential HE inhibitors with better binding energy. Furthermore, molecular dynamics simulations for 100 ns time scale revealed that most of the key HE contacts were retained throughout the simulations trajectories. Binding free energy calculations using MM/PBSA approach ranked the top-five potential NPACT compounds which can act as effective HE inhibitors.Graphic abstract Electronic supplementary materialThe online version of this article (10.1007/s11030-020-10135-w) contains supplementary material, which is available to authorized users.

Computational investigation of the selectivity mechanisms of PI3Kδ inhibition with marketed idelalisib: combined molecular dynamics simulation and free energy calculation

Phosphoinositide 3-kinase (PI3K) has been considered to be a potential drug target for the treatment of several human body diseases. Nowadays, great efforts have been made on the development of selective PI3Kδ inhibitors because of the FDA approval of idelalisib, which is the first listed PI3K inhibitor. But serious side effects occur during the use of idelalisib that greatly promotes the development of novel PI3Kδ inhibitors. Nevertheless, idelalisib is still an important milestone in the development of selective PI3Kδ inhibitors, but the detailed selective binding mechanisms between idelalisib and PI3Ks have not been well elucidated. Therefore, in this study, an integrated modeling strategy combining molecular docking, molecular dynamics simulation, and free energy calculation was performed to reveal the molecular-level binding mechanisms of idelalisib and class I PI3K. First, molecular docking was carried on to obtain a reasonable binding posture of idelalisib in different PI3K isoforms. Then, key residues for selective inhibition of PI3Kδ were highlighted by molecular dynamics simulation and energy calculations. Finally, idelalisib was also compared with its lead compound, IC87114, to reveal the reason for the higher potency of Idelalisib for PI3Kδ. We hope that this study would provide some guidance for the rational design of selective PI3Kδ inhibitors.

Molecular modelling study on pyrrolo[2,3-b]pyridine derivatives as c-Met kinase inhibitors: a combined approach using molecular docking, 3D-QSAR modelling and molecular dynamics simulation

ABSTRACT Mesenchymal-epithelial transition factor (c-Met), also known as hepatocyte growth factor receptor (HGFR) is a unique member of receptor tyrosine kinase (RTKs) family. Dysregulation of c-Met/HGF signalling pathway is validated in a variety of human proliferative diseases. Therefore, targeting c-Met has become a promising strategy in anti-proliferative drug discovery. In this work, an integrated computational approaches were performed on 67 c-Met inhibitors to explore the structural requirements for their activity. Molecular docking was performed to elucidate their binding mode in c-Met active site. Subsequently, 3D-QSAR models were constructed using comparative molecular filed analysis (CoMFA q2 = 0.692, r2 = 0.912 and r2 pred = 0.897) and comparative molecular similarity indices analysis (CoMSIA q2 = 0.751, r2 = 0.946 and r2 pred = 0.944) techniques. The CoMSIA map analysis showed that hydrophobic contours play key role for inhibitory activity. According to docking and 3D-QSAR results, A total of 31 novel c-Met inhibitors with predicted improved activity were designed. A 100 ns molecular dynamics simulation and binding free energy calculations using the MM-PBSA method revealed the stability of the designed compound D12 inside the c-Met active site. In summary , the results of our study could provide significant insight for future design and development of novel c-Met kinase inhibitors.

Potential protease inhibitors and their combinations to block SARS-CoV-2

COVID-19, which has emerged recently as a pandemic viral infection caused by SARS-coronavirus 2 has spread rapidly around the world, creating a public health emergency. The current situation demands an effective therapeutic strategy to control the disease using drugs that are approved, or by inventing new ones. The present study examines the possible repurposing of existing anti-viral protease inhibitor drugs. For this, the structural features of the viral spike protein, the substrate for host cell protease and main protease of the available SARS CoV-2 isolates were established by comparing with related viruses for which antiviral drugs are effective. The results showed 97% sequence similarity among SARS and SARS-CoV-2 main protease and has same cleavage site positions and ACE2 receptor binding region as in the SARS–CoV spike protein. Though both are N-glycosylated, unlike SARS-CoV, human SARS-CoV-2 S-protein was O-glycosylated as well. Molecular docking studies were done to explore the role of FDA approved protease inhibitors to control SARS-CoV-2 replication. The results indicated that, Ritonavir has the highest potency to block SARS-CoV-2 main protease and human TMPRSS2, a host cell factor that aids viral infection. Other drugs such as Indinavir and Atazanavir also showed favourable binding with Cathepsin B/L that helped viral fusion with the host cell membrane. Further molecular dynamics simulation and MM-PBSA binding free energy calculations confirmed the stability of protein-drug complexes. These results suggest that protease inhibitors particularly Ritonavir, either alone or in combination with other drugs such as Atazanavir, have the potential to treat COVID 19. Communicated by Ramaswamy H. Sarma

Double grain boundary configurations on graphite surfaces

We investigated the atomic structure of different kinds of grain boundaries on highly oriented pyrolytic graphite (HOPG) by scanning tunneling microscopy. We categorized several grain boundary configurations as a function of the misorientation angle between the adjacent grains, highlighting the occurrence of double grain boundaries (i.e., systems of two grain boundaries separated by a nanometric-scale inner region with specific atomic arrangement) for misorientation angles in the range 22°–32°. By using Molecular Dynamics simulations, we analyzed the structure and energy stability of single and double grain boundaries according to the misorientation angle. The experimental evidence is corroborated by Molecular Dynamics results and total energy calculations, which found a comparable stability between single and double grain boundaries for the same misorientation angle range. Our combination of experimental measurements and theoretical calculation extends the understanding of the structural configuration of large angle grain boundaries beyond the range of misorientation angles reported to date.

Designing novel inhibitors against cyclopropane mycolic acid synthase 3 (PcaA): targeting dormant state of Mycobacterium tuberculosis

Mycobacterium tuberculosis can sustain inside the host in dormant (non-replicating) state for years. It suppresses the host immune system by residing in the host alveolar macrophage, resulting in the development of latent tuberculosis. Despite many antibiotics available for the treatment of tuberculosis, the major hurdle in complete elimination is the ability of the bacilli to undergo dormancy and develop resistance against the existing drugs. Cyclopropanation of mycolic acids present in the cell wall of mycobacteria is required for its persistence and virulence. Cyclopropane synthases such as PcaA, CmaA1 and CmaA2, introduce site-specific modifications in mycolic acids. PcaA expression levels are high during dormancy and the gene mutants fails to persist, showing reduced survival in host macrophage. Hence, PcaA appears as a potential target to develop inhibitors against the dormant bacilli. In this study, we have identified compounds with maximum binding affinity against PcaA by in-silico virtual screening of anti-tuberculosis compounds and their structural analogues. In-silico docking followed molecular dynamic simulations and free energy calculations of the compounds with highest docking score in their respective libraries. This study reports novel inhibitors that can act as better anti-tuberculosis compounds targeting PcaA. Communicated by Ramaswamy H. Sarma

A comparative study of the binding modes of SLC-0111 and its analogues in the hCA II and hCA IX active sites using QM/MM, molecular docking, MM-GBSA and MD approaches

Human carbonic anhydrase IX (hCA IX) is over-expressed in many tumor types and serves as an important target for the discovery of novel anticancer agents. However, development of compounds that can selectively inhibit hCA IX over its widespread cytosolic isoform human carbonic anhydrase II (hCA II) is a major challenge. This work focuses on recognizing the structural features of the hCA IX receptor that could help in achieving its selective inhibition. Tools such as protein structure alignment, rigid as well as flexible docking, QM/MM calculations and molecular dynamics simulations on SLC-0111, a selective hCA IX inhibitor, in complexation with each receptor, have been used to differentiate the receptor-ligand interactions in the two complexes. It is found that the ligand shows better binding to hCA IX due to stronger coordination to the Zn (II) ion. The ligand provides bidentate coordination through its negatively charged nitrogen and an oxygen of the sulfonamide zinc binding group. Binding energy calculations show that the potency of this ligand is due to the hydrophobic contacts, whereas the selectivity is due to the electrostatic interactions. Molecular docking and binding energy calculations for three different series of SLC-0111 analogs have identified a few molecules that show high potency and selectivity toward hCA IX. It is found that both hydrophobic and polar contacts contribute to the potency and selectivity of the ligands.

Insights into the mechanism of inhibition of phospholipase A2 by resveratrol: An extensive molecular dynamics simulation and binding free energy calculation

Phospholipase A2 (PLA2) is one of the enzymes involved in the development of cardiovascular diseases, vascular inflammation, risk of heart attacks, and strokes. This enzyme is responsible for catalyzing the hydrolytic cleavage of ester bonds of phospholipids in the biological pathway of inflammation. To prevent the undesired hydrolysis of phospholipids, the catalytic activity of PLA2 needs to be blocked. Resveratrol is a plant-derived polyphenol inhibitor, proven to have anti-inflammatory properties. However, there is still substantial ambiguity about its inhibitory function. The present study uncovers a detailed molecular mechanism behind the resveratrol action in inhibition of PLA2, by applying and comparing two 200-ns molecular dynamics simulations. The results of structural analyses revealed that the binding of resveratrol to PLA2 reduces the content of β-sheets and increases a 5-helix to PLA2 structure, producing more folding and stability in protein. In the active site, the resveratrol is placed between the N-terminal α-helix and the newly formed 5-helix through the hydrophobic interactions with ILE19 and LEU3 residues, as well as the hydrogen bond interactions. These interactions play the role of a network at the entrance of the enzyme active site and prevent the penetration of water molecules into the PLA2 cavity. A high occupancy hydrogen bonding has been identified between SER23 of the protein and hydroxyl group of resveratrol. Furthermore, the estimation of binding free energy verified the binding affinity of resveratrol is thermodynamically sufficient to be stably bounded to PLA2. It also proved that the van der Waals interactions, particularly hydrophobic interactions, have the most significant role in PLA2-resveratrol binding and stability. Overall, our results provide useful information on the stepwise mechanism of the inhibition of PLA2 enzyme by resveratrol, as a target for improving the pharmacological applications.

Epigenetic TET-Catalyzed Oxidative Products of 5-Methylcytosine Impede Z-DNA Formation of CG Decamers.

Methylation of cytosine has been known to play a significant role in epigenetic regulation. 5-Methylcytosine was among the first base modification that was discovered for the capability to facilitate B/Z-DNA transition as observed in CG repeated tracks. A study on gene repression by Z-DNA prone sequence as in ADAM-12 has ignited our research interest for the Z-DNA role in epigenetics. Ten eleven translocation family proteins are responsible to catalyze 5-methylcytosine to produce oxidative products including 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxycytosine, which each may have unique function rather than the sole purpose of 5-methylcytosine clearance. Although the Z-DNA-promoting effect of 5-methylcytosine was well established, the effect of its oxidative products on Z-DNA remain unknown. In this study, the Z-DNA-promoting effect of 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxycytosine on the CG decamer model were investigated along with known Z-DNA stabilizers, 5-methylcytosine and 8-oxoguanine. Experimental results from circular dichroism (CD) and NMR indicates that all oxidative products of 5-methylcytosine hinder B/Z-DNA transition as high salt concentration suitable to stabilize and convert unmodified CG decamer to Z-DNA conformation is insufficient to facilitate the B/Z-DNA transition of CG decamer containing 5-hydroxymethylcytosine, 5-formylcytosine, or 5-carboxycytosine. Molecular dynamic simulation and free energy calculation by MM-PBSA are in agreement with the experimental finding that 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxycytosine destabilize Z-DNA conformation of CG decamer, in contrast to its precursor. Investigation of Z-DNA switch-on/switch-off regulated by 5-methylcytosine and its oxidative products is a further step to elucidate the potential of epigenetic regulated via Z-DNA.

Lauryl Phosphate Flotation Chemistry in Barite Flotation

Barite has numerous applications including barium mud for oil well drilling, manufacture of elemental barium, filler for paper and rubber industries, and contrast material for X-ray radiology for the digestive system. Currently, froth flotation is the main method for the beneficiation of barite using fatty acid as a typical collector. In this research, it was found that lauryl phosphate is also a promising collector for barite flotation. Results from microflotation, contact angle, and zeta potential indicate that lauryl phosphate is adsorbed on the barite surface and thus achieves superior flotation efficiency at a wide pH range. The interfacial water structure and wetting characteristics of barite surface with/without lauryl phosphate adsorption were also evaluated by molecular dynamics simulations (MDS). The results from molecular dynamics simulations and interaction energy calculations are in accord with the experimental results, which suggest that lauryl phosphate might be a potential collector for the flotation of barite.

Computational insights into the sorption mechanism of polycyclic aromatic hydrocarbons by carbon nanotube through density functional theory calculation and molecular dynamics simulation

Potential for increased toxicity known for polycyclic aromatic hydrocarbons (PAHs) is associated with adverse effects on growth, reproduction and mutagenicity. Carbon nanotube (CNT) could significantly enhance PAHs sorption in aqueous solutions, which offers a promising opportunity in water and air purification for the removal of environmental contaminants. Although the sorption of PAHs by carbon nanotube has been reported in many studies, the knowledge regarding their molecular mechanism at atomic level is still very limited. In this study, we integrate density functional theory (DFT) calculation, fully atomistic molecular dynamics (MD) simulation and binding free energy calculation to investigate the sorption mechanism of PAHs by carbon nanotube. The results would have important implications for the future application of carbon nanotube in the environmental pollution cleanup.

Refined pharmacophore features for virtual screening of human thromboxane A2 receptor antagonists

For a long time, the structural basis of TXA2 receptor is limited due to the lack of crystal structure information, till the release of the crystal structure of TXA2 receptor, which deepens our understanding about ligand recognition and selectivity mechanisms of this physiologically important receptor. In this research, we report the successful implementation in the discovery of an optimal pharmacophore model of human TXA2 receptor antagonists through virtual screening. Structure-based pharmacophore models were generated based on two crystal structures of human TXA2 receptor (PDB entry 6IIU and 6IIV). Docking simulation revealed interaction modes of the virtual screening hits against TXA2 receptor, which was validated through molecular dynamics simulation and binding free energy calculation. ADMET properties were also analyzed to evaluate the toxicity and physio-chemical characteristics of the hits. The research would provide valuable insight into the binding mechanisms of TXA2 receptor antagonists and thus be helpful for designing novel antagonists.

Bond correction factors and their applications to the calculation of molecular mean excitation energies

We report bond correction factors that can be used to calculate molecular mean excitation energies including the effects of chemical bonding. The calculations are based on an extension of Bragg’s rule. We report results for several bonds – neutral and charged - involving gas phase atoms in the first, second and third row of the periodic system. The bond correction factors are dimensionless and turn out to be nearly constant and of the order 1–2. The method is applied to the calculations of mean excitation energies of linear hydrocarbons, amino acids and molecules and molecular ions of astrophysical interest. Examples show that chemical binding effects increase the molecular mean excitation energies with between 4% and 15 %, smallest for linear, unsaturated molecules and largest for molecules with longer aliphatic chains.

Novel androgen receptor antagonist identified by structure-based virtual screening, structural optimization, and biological evaluation

Androgen receptor (AR) plays important roles in the development of prostate cancer (PCa), and therefore it has been regarded as the most important therapeutic target for both hormone-sensitive prostate cancer (HSPC) and advanced PCa. In this study, a novel hit (C18) with IC50 of 2.4 μM against AR transcriptional activity in LNCaP cell was identified through structure-based virtual screening based on molecular docking and free energy calculations. The structure-activity relationship analysis and structural optimization of C18 resulted in the discovery of a structural analogue (AT2), a more potent AR antagonist with 16-fold improved anti-AR potency. Further assays indicated that AT2 was capable of effectively inhibiting the transcriptional function of AR and blocking the nuclear translocation of AR like the second-generation AR antagonists. The antagonists discovered in this study may be served as the promising lead compounds for the development of AR-driven PCa therapeutics.

Advances in Docking.

Design of small molecules which are able to bind to the protein responsible for a disease is the key step of the entire process of the new medicine discovery. Atomistic computer modeling can significantly improve effectiveness of such design. The accurate calculation of the free energy of binding a small molecule (a ligand) to the target protein is the most important problem of such modeling. Docking is one of the most popular molecular modeling methods for finding ligand binding poses in the target protein and calculating the protein-ligand binding energy. This energy is used for finding the most active compounds for the given target protein. This short review aims to give a concise description of distinctive features of docking programs focusing on computation methods and approximations influencing their accuracy. This review is based on the peer-reviewed research literature including author's own publications. The main features of several representative docking programs are briefly described focusing on their characteristics influencing docking accuracy: force fields, energy calculations, solvent models, algorithms of the best ligand pose search, global and local optimizations, ligand and target protein flexibility, and the simplifications made for the docking accelerating. Apart from other recent reviews focused mainly on the performance of different docking programs, in this work, an attempt is made to extract the most important functional characteristics defining the docking accuracy. Also a roadmap for increasing the docking accuracy is proposed. This is based on the new generation of docking programs which have been realized recently. These programs and respective new global optimization algorithms are described shortly. Several popular conventional docking programs are considered. Their search of the best ligand pose is based explicitly or implicitly on the global optimization problem. Several algorithms are used to solve this problem, and among them, the heuristic genetic algorithm is distinguished by its popularity and an elaborate design. All conventional docking programs for their acceleration use the preliminary calculated grids of protein-ligand interaction potentials or preferable points of protein and ligand conjugation. These approaches and commonly used fitting parameters restrict strongly the docking accuracy. Solvent is considered in exceedingly simplified approaches in the course of the global optimization and the search for the best ligand poses. More accurate approaches on the base of implicit solvent models are used frequently for more careful binding energy calculations after docking. The new generation of docking programs are developed recently. They find the spectrum of low energy minima of a protein-ligand complex including the global minimum. These programs should be more accurate because they do not use a preliminary calculated grid of protein-ligand interaction potentials and other simplifications, the energy of any conformation of the molecular system is calculated in the frame of a given force field and there are no fitting parameters. A new docking algorithm is developed and fulfilled specially for the new docking programs. This algorithm allows docking a flexible ligand into a flexible protein with several dozen mobile atoms on the base of the global energy minimum search. Such docking results in improving the accuracy of ligand positioning in the docking process. The adequate choice of the method of molecular energy calculations also results in the better docking positioning accuracy. An advancement in the application of quantum chemistry methods to docking and scoring is revealed. The findings of this review confirm the great demand in docking programs for discovery of new medicine substances with the help of molecular modeling. New trends in docking programs design are revealed. These trends are focused on the increase of the docking accuracy at the expense of more accurate molecular energy calculations without any fitting parameters, including quantum-chemical methods and implicit solvent models, and by using new global optimization algorithms which make it possible to treat flexibility of ligands and mobility of protein atoms simultaneously. Finally, it is shown that all the necessary prerequisites for increasing the docking accuracy can be accomplished in practice.

Theoretical Studies on the Selectivity Mechanisms of Glycogen Synthase Kinase 3β (GSK3β) with Pyrazine ATP-competitive Inhibitors by 3DQSAR, Molecular Docking, Molecular Dynamics Simulation and Free Energy Calculations.

Background Glycogen synthase kinase-3 (GSK3) is associated with various key biological processes and has been considered as an important therapeutic target for the treatment of many diseases. Great efforts have been made on the development of GSK3 inhibitors, especially ATP-competitive GSK3β inhibitor, but it is still a great challenge to develop selective GSK3β inhibitors because of the high sequence homology with other kinases.Objective In order to reveal the selectivity mechanisms of GSK3β inhibition at the molecular level, a series of ATP-competitive GSK3β inhibitor was analyzed by a systematic computational method, combining 3D-QSAR, molecular docking, molecular dynamic simulations and free energy calculations.Methods Firstly, 3D-QSAR with CoMFA was built to explore the general structure activity relationships. Secondly, CDOCKER and Flexible docking were employed to predicted the reasonable docking poses of all studied inhibitors. And then, both GSK3β and CDK2 complexes were selected to conduct molecular dynamics simulations. Finally, the free energy calculations were employed to find the key selective-residues.Results CoMFA model suggested the steric, hydrophobic fields play key roles in the bioactivities of inhibitors, and the binding mechanisms were well analyzed through molecular docking. The binding free energies predicted are in good agreement with the experimental bioactivities and the free energy calculations showed that the binding of GSK3β/inhibitors was mainly contributed from hydrogen bonding and hydrophobic interaction.Conclusion Some key residues for selective binding were highlighted, which may afford important guidance for the rational design of novel ATP-competitive GSK3β inhibitors.