Combining molecular docking and molecular dynamics studies for modelling Staphylococcus aureus MurD inhibitory activity

The ATP-dependent bacterial MurD enzyme catalyses the formation of the peptide bond between cytoplasmic intermediate UDP-N-acetylmuramoyl-L-alanine and D-glutamic acid. This is essential for bacterial cell wall peptidoglycan synthesis in both Gram-positive and Gram-negative bacteria. MurD is recognized as an important target for the development of new antibacterial agents. In the present study we prepared the 3D-stucture of the catalytic pocket of the Staphylococcus aureus MurD enzyme by homology modelling. Extra-precision docking, binding free energy calculation by the MM–GBSA approach and a 40 ns molecular dynamics (MD) simulation of 2-thioxothiazolidin-4-one based inhibitor $1 was carried out to elucidate its inhibition potential for the S. aureus MurD enzyme. Molecular docking results showed that Lys19, Gly147, Tyr148, Lys328, Thr330 and Phe431 residues are responsible for the inhibitor–protein complex stabilization. Binding free energy calculation revealed electrostatic solvation and van der Waals energy components as major contributors for the inhibitor binding. The inhibitor-modelled S. aureus protein complex had a stable conformation in response to the atomic flexibility and interaction, when subjected to MD simulation at 40 ns in aqueous solution. We designed some molecules as potent inhibitors of S. aureus MurD, and to validate the stability of the designed molecule D1-modelled protein complex we performed a 20 ns MD simulation. Results obtained from this study can be utilized for the design of potent S. aureus MurD inhibitors.     

Identification of critical chemical features for Aurora kinase-B inhibitors using Hip-Hop, virtual screening and molecular docking

This study was performed to find the selective chemical features for Aurora kinase-B inhibitors using the potent methods like Hip-Hop, virtual screening, homology modeling, molecular dynamics and docking. The best hypothesis, Hypo1 was validated toward a wide range of test set containing the selective inhibitors of Aurora kinase-B. Homology modeling and molecular dynamics studies were carried out to perform the molecular docking studies. The best hypothesis Hypo1 was used as a 3D query to screen the chemical databases. The screened molecules from the databases were sorted based on ADME and drug like properties. The selective hit compounds were docked and the hydrogen bond interactions with the critical amino acids present in Aurora kinase-B were compared with the chemical features present in the Hypo1. Finally, we suggest that the chemical features present in the Hypo1 are vital for a molecule to inhibit the Aurora kinase-B activity.     

Virtual Screening with Gnina 1.0

Virtual screening—predicting which compounds within a specified compound library bind to a target molecule, typically a protein—is a fundamental task in the field of drug discovery. Doing virtual screening well provides tangible practical benefits, including reduced drug development costs, faster time to therapeutic viability, and fewer unforeseen side effects. As with most applied computational tasks, the algorithms currently used to perform virtual screening feature inherent tradeoffs between speed and accuracy. Furthermore, even theoretically rigorous, computationally intensive methods may fail to account for important effects relevant to whether a given compound will ultimately be usable as a drug. Here we investigate the virtual screening performance of the recently released Gnina molecular docking software, which uses deep convolutional networks to score protein-ligand structures. We find, on average, that Gnina outperforms conventional empirical scoring. The default scoring in Gnina outperforms the empirical AutoDock Vina scoring function on 89 of the 117 targets of the DUD-E and LIT-PCBA virtual screening benchmarks with a median 1% early enrichment factor that is more than twice that of Vina. However, we also find that issues of bias linger in these sets, even when not used directly to train models, and this bias obfuscates to what extent machine learning models are achieving their performance through a sophisticated interpretation of molecular interactions versus fitting to non-informative simplistic property distributions.     

Extra precision docking,free energy calculation and molecular dynamics studies on glutamic acid derivatives as MurD inhibitors

The binding modes of well known MurD inhibitors have been studied using molecular docking and molecular dynamics (MD) simulations. The docking results of inhibitors 1-30 revealed similar mode of interaction with Escherichia coli-MurD. Further, residues Thr36, Arg37, His183, Lys319, Lys348, Thr321, Ser415 and Phe422 are found to be important for inhibitors and E. coli-MurD interactions. Our docking procedure precisely predicted crystallographic bound inhibitor 7 as evident from root mean square deviation (0.96 Å). In addition inhibitors 2 and 3 have been successfully cross-docked within the MurD active site, which was pre-organized for the inhibitor 7. Induced fit best docked poses of 2, 3, 7 and 15/2Y1O complexes were subjected to 10 ns MD simulations to determine the stability of the predicted binding conformations. Induce fit derived docked complexes were found to be in a state of near equilibrium as evident by the low root mean square deviations between the starting complex structure and the energy minimized final average MD complex structures. The results of molecular docking and MD simulations described in this study will be useful for the development of new MurD inhibitors with high potency.     

Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase

The biosynthetic pathway of the bacterial peptidoglycan, where MurD is an enzyme involved at the intracellular stage of its construction, represents a collection of highly selective macromolecular targets for novel antibacterial drug design. In this study as part of our investigation of the MurD bacterial target two recently discovered classes of the MurD ligase inhibitors were investigated resulting from the lead optimization phases of the N-sulfonamide d-Glu MurD inhibitors. Molecular dynamics simulations, based on novel structural data, in conjunction with the linear interaction energy (LIE) method suggested the transferability of our previously obtained LIE coefficients to further d-Glu based classes of MurD inhibitors. Analysis of the observed dynamical behavior of these compounds in the MurD active site was supported by static drug design techniques. These results complement the current knowledge of the MurD inhibitory mechanism and provide valuable support for the d-Glu paradigm of the inhibitor design.     

Calcium ions tune the zinc-sequestering properties and antimicrobial activity of human S100A12

Human S100A12 is a host-defense protein expressed and released by neutrophils that contributes to innate immunity. Apo S100A12 is a 21 kDa antiparallel homodimer that harbors two Ca(ii)-binding EF-hand domains per subunit and exhibits two His₃Asp motifs for chelating transition metal ions at the homodimer interface. In this work, we present results from metal-binding studies and microbiology assays designed to ascertain whether Ca(ii) ions modulate the Zn(ii)-binding properties of S100A12 and further evaluate the antimicrobial properties of this protein. Our metal-depletion studies reveal that Ca(ii) ions enhance the ability of S100A12 to sequester Zn(ii) from microbial growth media. We report that human S100A12 has antifungal activity against Candida albicans, C. krusei, C. glabrata and C. tropicalis, all of which cause human disease. This antifungal activity is Ca(ii)-dependent and requires the His₃Asp metal-binding sites. We expand upon prior studies of the antibacterial activity of S100A12 and report Ca(ii)-dependent and strain-selective behavior. S100A12 exhibits in vitro growth inhibitory activity against Listeria monocytogenes. In contrast, S100A12 has negligible effect on the growth of Escherichia coli K-12 and Pseudomonas aeruginosa PAO1. Loss of functional ZnuABC, a high-affinity Zn(ii) import system, increases the susceptibility of E. coli and P. aeruginosa to S100A12, indicating that S100A12 deprives these mutant strains of Zn(ii). To evaluate the Zn(ii)-binding sites of S100A12 in solution, we present studies using Co(ii) as a spectroscopic probe and chromophoric small-molecule chelators in Zn(ii) competition titrations. We confirm that S100A12 binds Zn(ii) with a 2 : 1 stoichiometry, and our data indicate sub-nanomolar affinity binding. Taken together, these data support a model whereby S100A12 uses Ca(ii) ions to tune its Zn(ii)-chelating properties and antimicrobial activity.     

Identification of potential Tpx inhibitors against pathogen-host interactions

Yersinia organisms cause many infectious diseases by invading human cells and delivering their virulence factors via the type three secretion system (T3SS). One alternative strategy in the fight against these pathogenic organisms is to interfere with their T3SS. Previous studies demonstrated that thiol peroxidase, Tpx is functional in the assembly of T3SS and its inhibition by salicylidene acylhydrazides prevents the secretion of pathogenic effectors. In this study, the aim was to identify potential inhibitors of Tpx using an integrated approach starting with high throughput virtual screening and ending with molecular dynamics simulations of selected ligands. Virtual screening of ZINC database of 500,000 compounds via ligand-based and structure-based pharmacophore models retrieved 10,000 hits. The structure-based pharmacophore model was validated using high-throughput virtual screening (HTVS). After multistep docking (SP and XP), common scaffolds were used to find common substructures and the ligand binding poses were optimized using induced fit docking. The stability of the protein–ligand complex was examined with molecular dynamics simulations and the binding free energy of the complex was calculated. As a final outcome eight compounds with different chemotypes were proposed as potential inhibitors for Tpx. The eight ligands identified by a detailed virtual screening protocol can serve as leads in future drug design efforts against the destructive actions of pathogenic bacteria.     

Pharmacophore-Based Virtual Screening,Quantum Mechanics Calculations,and Molecular Dynamics Simulation Approaches Identified Potential Natural Antiviral Drug Candidates against MERS-CoV S1-NTD

Middle East respiratory syndrome coronavirus (MERS-CoV) is a highly infectious zoonotic virus first reported into the human population in September 2012 on the Arabian Peninsula. The virus causes severe and often lethal respiratory illness in humans with an unusually high fatality rate. The N-terminal domain (NTD) of receptor-binding S1 subunit of coronavirus spike (S) proteins can recognize a variety of host protein and mediates entry into human host cells. Blocking the entry by targeting the S1-NTD of the virus can facilitate the development of effective antiviral drug candidates against the pathogen. Therefore, the study has been designed to identify effective antiviral drug candidates against the MERS-CoV by targeting S1-NTD. Initially, a structure-based pharmacophore model (SBPM) to the active site (AS) cavity of the S1-NTD has been generated, followed by pharmacophore-based virtual screening of 11,295 natural compounds. Hits generated through the pharmacophore-based virtual screening have re-ranked by molecular docking and further evaluated through the ADMET properties. The compounds with the best ADME and toxicity properties have been retrieved, and a quantum mechanical (QM) based density-functional theory (DFT) has been performed to optimize the geometry of the selected compounds. Three optimized natural compounds, namely Taiwanhomoflavone B (Amb23604132), 2,3-Dihydrohinokiflavone (Amb23604659), and Sophoricoside (Amb1153724), have exhibited substantial docking energy >−9.00 kcal/mol, where analysis of frontier molecular orbital (FMO) theory found the low chemical reactivity correspondence to the bioactivity of the compounds. Molecular dynamics (MD) simulation confirmed the stability of the selected natural compound to the binding site of the protein. Additionally, molecular mechanics generalized born surface area (MM/GBSA) predicted the good value of binding free energies (ΔG bind) of the compounds to the desired protein. Convincingly, all the results support the potentiality of the selected compounds as natural antiviral candidates against the MERS-CoV S1-NTD.     

Phenolic Compounds from Mori Cortex Ameliorate Sodium Oleate-Induced Epithelial–Mesenchymal Transition and Fibrosis in NRK-52e Cells through CD36

Lipid deposition in the kidney can cause serious damage to the kidney, and there is an obvious epithelial–mesenchymal transition (EMT) and fibrosis in the late stage. To investigate the interventional effects and mechanisms of phenolic compounds from Mori Cortex on the EMT and fibrosis induced by sodium oleate-induced lipid deposition in renal tubular epithelial cells (NRK-52e cells), and the role played by CD36 in the adjustment process, NRK-52e cells induced by 200 μmol/L sodium oleate were given 10 μmoL/L moracin-P-2″-O-β-d-glucopyranoside (Y-1), moracin-P-3′-O-β-d-glucopyranoside (Y-2), moracin-P-3′-O-α-l-arabinopyranoside (Y-3), and moracin-P-3′-O-[β-glucopyranoside-(1→2)arabinopyranoside] (Y-4), and Oil Red O staining was used to detect lipid deposition. A Western blot was used to detect lipid deposition-related protein CD36, inflammation-related protein (p-NF-κB-P65, NF-κB-P65, IL-1β), oxidative stress-related protein (NOX1, Nrf2, Keap1), EMT-related proteins (CD31, α-SMA), and fibrosis-related proteins (TGF-β, ZEB1, Snail1). A qRT-PCR test detected inflammation, EMT, and fibrosis-related gene mRNA levels. The TNF-α levels were detected by ELISA, and the colorimetric method was used to detects SOD and MDA levels. The ROS was measured by flow cytometry. A high-content imaging analysis system was applied to observe EMT and fibrosis-related proteins. At the same time, the experiment silenced CD36 and compared the difference between before and after drug treatment, then used molecular docking technology to predict the potential binding site of the active compounds with CD36. The research results show that sodium oleate can induce lipid deposition, inflammation, oxidative stress, and fibrosis in NRK-52e cells. Y-1 and Y-2 could significantly ameliorate the damage caused by sodium oleate, and Y-2 had a better ameliorating effect, while there was no significant change in Y-3 or Y-4. The amelioration effect of Y-1 and Y-2 disappeared after silencing CD36. Molecular docking technology showed that the Y-1 and Y-2 had hydrogen bonds to CD36 and that, compared with Y-1, Y-2 requires less binding energy. In summary, moracin-P-2″-O-β-d-glucopyranoside and moracin-P-3′-O-β-d-glucopyranoside from Mori Cortex ameliorated lipid deposition, EMT, and fibrosis induced by sodium oleate in NRK-52e cells through CD36.     

Pharmacophore modeling,atom based 3D-QSAR,molecular docking and molecular dynamics studies on Escherichia coli ParE inhibitors

ATP dependent ParE enzyme is as an attractive target for the development of antibacterial agents. Atom based 3D-QSAR model AADHR.187 was developed based on the thirty eight Escherichia coli ParE inhibitors. The generated model showed statistically significant coefficient of determinations for the training (R² = 0.985) and test (R² = 0.86) sets. The cross-validated correlation coefficient (q2) was 0.976. The utility of the generated model was validated by the enrichment study. The model was also validated with structurally diverse external test set of ten compounds. Contour plot analysis of the generated model unveiled the chemical features necessary for the E. coli ParE enzyme inhibition. Extra-precision docking result revealed that hydrogen bonding and ionic interactions play a major role in ParE protein-ligand binding. Binding free energy was computed for the data set inhibitors to validate the binding affinity. A 30-ns molecular dynamics simulation showed high stability and effective binding of inhibitor 34 within the active site of ParE enzyme. Using the best fitted model AADHR.187, pharmacophore-based high-throughput virtual screening was performed to identify virtual hits. Based on the above studies three new molecules are proposed as E. coli ParE inhibitors with high binding affinity and favourable ADME properties.     

DFT insight into asymmetric alkyl–alkyl bond formation via nickel-catalysed enantioconvergent reductive coupling of racemic electrophiles with olefins

A DFT study has been conducted to understand the asymmetric alkyl–alkyl bond formation through nickel-catalysed reductive coupling of racemic alkyl bromide with olefin in the presence of hydrosilane and K₃PO₄. The key findings of the study include: (i) under the reductive experimental conditions, the Ni(ii) precursor is easily activated/reduced to Ni(0) species which can serve as an active species to start a Ni(0)/Ni(ii) catalytic cycle. (ii) Alternatively, the reaction may proceed via a Ni(i)/Ni(ii)/Ni(iii) catalytic cycle starting with a Ni(i) species such as Ni(i)–Br. The generation of a Ni(i) active species via comproportionation of Ni(ii) and Ni(0) species is highly unlikely, because the necessary Ni(0) species is strongly stabilized by olefin. Alternatively, a cage effect enabled generation of a Ni(i) active catalyst from the Ni(ii) species involved in the Ni(0)/Ni(ii) cycle was proposed to be a viable mechanism. (iii) In both catalytic cycles, K₃PO₄ greatly facilitates the hydrosilane hydride transfer for reducing olefin to an alkyl coupling partner. The reduction proceeds by converting a Ni–Br bond to a Ni–H bond via hydrosilane hydride transfer to a Ni–alkyl bond via olefin insertion. On the basis of two catalytic cycles, the origins for enantioconvergence and enantioselectivity control were discussed.

The enantioconvergent alkyl–alkyl coupling involves two competitive catalytic cycles with nickel(0) and nickel(i) active catalysts, respectively. K₃PO₄ plays a crucial role to enable the hydride transfer from hydrosilane to nickel–bromine species.     

Complexation and redox chemistry of neptunium,plutonium and americium with a hydroxylaminato ligand

There is significant interest in ligands that can stabilize actinide ions in oxidation states that can be exploited to chemically differentiate 5f and 4f elements. Applications range from developing large-scale actinide separation strategies for nuclear industry processing to carrying out analytical studies that support environmental monitoring and remediation efforts. Here, we report syntheses and characterization of Np(iv), Pu(iv) and Am(iii) complexes with N-tert-butyl-N-(pyridin-2-yl)hydroxylaminato, [2-(^tBuNO)py]⁻(interchangeable hereafter with [(^tBuNO)py]⁻), a ligand which was previously found to impart remarkable stability to cerium in the +4 oxidation state. An[(^tBuNO)py]₄ (An = Pu, 1; Np, 2) have been synthesized, characterized by X-ray diffraction, X-ray absorption, ¹H NMR and UV-vis-NIR spectroscopies, and cyclic voltammetry, along with computational modeling and analysis. In the case of Pu, oxidation of Pu(iii) to Pu(iv) was observed upon complexation with the [(^tBuNO)py]⁻ ligand. The Pu complex 1 and Np complex 2 were also isolated directly from Pu(iv) and Np(iv) precursors. Electrochemical measurements indicate that a Pu(iii) species can be accessed upon one-electron reduction of 1 with a large negative reduction potential (E_1/2 = −2.26 V vs. Fc^+/0). Applying oxidation potentials to 1 and 2 resulted in ligand-centered electron transfer reactions, which is different from the previously reported redox chemistry of U^IV[(^tBuNO)py]₄ that revealed a stable U(v) product. Treatment of an anhydrous Am(iii) precursor with the [(^tBuNO)py]⁻ ligand did not result in oxidation to Am(iv). Instead, the dimeric complex [Am^III(μ₂-(^tBuNO)py)((^tBuNO)py)₂]₂ (3) was isolated. Complex 3 is a rare example of a structurally characterized non-aqueous Am-containing molecular complex prepared using inert atmosphere techniques. Predicted redox potentials from density functional theory calculations show a trivalent accessibility trend of U(iii) < Np(iii) < Pu(iii) and that the higher oxidation states of actinides (i.e., +5 for Np and Pu and +4 for Am) are not stabilized by [2-(^tBuNO)py]⁻, in good agreement with experimental observations.

The coordination modes and electronic properties of a strongly coordinating hydroxylaminato ligand with Np, Pu and Am were investigated.Complexes were characterized by a range of experimental and computational techniques.     

Total synthesis and biochemical characterization of mirror image barnase

In this study we synthesized and characterized mirror image barnase (B. amyloliquefaciens ribonuclease). d-Barnase was identical to l-barnase, when analyzed by liquid chromatography and mass-spectrometry. Proteolysis of the mirror image enzyme revealed that in contrast to its native counterpart, d-barnase was completely stable to digestive proteases. In enzymatic assays, d-barnase had the reciprocal chiral specificity and was fully active towards mirror image substrates. Interestingly, d-barnase also hydrolyzed the substrate of the native chirality, albeit 4000 times less efficiently. This effect was further confirmed by digesting a native 112-mer RNA with the enzyme. Additional studies revealed that barnase accommodates a range of substrates with various chiralities, but the prime requirement for guanosine remains. These studies point toward using mirror image enzymes as modern agents in biotechnology.     

Identification of Novel Antistaphylococcal Hit Compounds Targeting Sortase A

Staphylococcus aureus (S. aureus) is a causative agent of many hospital- and community-acquired infections with the tendency to develop resistance to all known antibiotics. Therefore, the development of novel antistaphylococcal agents is of urgent need. Sortase A is considered a promising molecular target for the development of antistaphylococcal agents. The main aim of this study was to identify novel sortase A inhibitors. In order to find novel antistaphylococcal agents, we performed phenotypic screening of a library containing 15512 compounds against S. aureus ATCC43300. The molecular docking of hits was performed using the DOCK program and 10 compounds were selected for in vitro enzymatic activity inhibition assay. Two inhibitors were identified, N,N-diethyl-N′-(5-nitro-2-(quinazolin-2-yl)phenyl)propane-1,3-diamine (1) and acridin-9-yl-(1H-benzoimidazol-5-yl)-amine (2), which decrease sortase A activity with IC₅₀ values of 160.3 µM and 207.01 µM, respectively. It was found that compounds 1 and 2 possess antibacterial activity toward 29 tested multidrug resistant S. aureus strains with MIC values ranging from 78.12 to 312.5 mg/L. These compounds can be used for further structural optimization and biological research.     

Artificial intelligence-aided discovery of prolyl hydroxylase 2 inhibitors to stabilize hypoxia inducible factor-1α and promote angiogenesis

From ZINC database with a total of 1.8 million small molecules, four compounds are identified as prolyl hydroxylase 2 inhibitors through a virtual screening workflow that sequentially incorporates machine learning, molecular docking, and molecular dynamics. Among them, compound 103, (E)-5-(5-((2-(1H-tetrazol-5-yl)hydrazineylidene)methyl)furan-2-yl)isoindoline-1,3-dione, promotes the migration and capillary tube formation capacity of human umbilical vein endothelial cells through enhancing the stability of hypoxia inducible factor-1α and increasing the level of vascular endothelial growth factor.     

Surflex-Dock: Docking benchmarks and real-world application

Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein-ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.     

Screening of Potential Anti-Thrombotic Ingredients from Salvia miltiorrhiza in Zebrafish and by Molecular Docking

Background: Danshen (DS), the dry root of Salvia miltiorrhiza Bge., has been used in traditional Chinese medicine (TCM) for many years to promote blood circulation and to inhibit thrombosis. However, the active ingredients responsible for the anti-thrombotic effect and the underlying mechanisms are yet to be fully elucidated. Methods: Molecular docking was used to predict the active ingredients in DS and their potential targets by calculating the scores of docking between DS ingredients and thrombosis-related proteins. Then, a chemical-induced zebrafish thrombosis model was applied to confirm their anti-thrombotic effects. Result: The molecular docking results indicated that compared to the control ligand, higher docking scores were observed for several compounds in DS, among which salvianolic acid B (SAB), lithospermic acid (LA), rosmarinic acid (MA), and luteolin-7-O-β-d-glucoside (LG) could attenuate zebrafish caudal vein thrombosis and recover the decrease in heart red blood cells (RBCs) in a dose-dependent manner. Conclusions: Our study showed that it is possible to screen the potential active components in natural products by combining the molecular docking method and zebrafish in vivo model.     

Luminescence switch-on detection of protein tyrosine kinase-7 using a G-quadruplex-selective probe

A series of luminescent iridium(iii) complexes were synthesised and evaluated for their ability to act as luminescent G-quadruplex-selective probes. The iridium(iii) complex 9 [Ir(pbi)₂(5,5-dmbpy)]PF₆ (where pbi = 2-phenyl-1H-benzo[d]imidazole; 5,5-dmbpy = 5,5′-dimethyl-2,2′-bipyridine) exhibited high luminescence for G-quadruplex DNA compared to dsDNA and ssDNA, and was employed to construct a G-quadruplex-based assay for protein tyrosine kinase-7 (PTK7) in aqueous solution. PTK7 is an important biomarker for a range of leukemias and solid tumors. In the presence of PTK7, the specific binding of the sgc8 aptamer sequence triggers a structural transition and releases the G-quadruplex-forming sequence. The formation of the nascent G-quadruplex structure is then detected by the G-quadruplex-selective iridium(iii) complex with an enhanced luminescent response. Moreover, the application of the assay for detecting PTK7 in cellular debris and membrane protein extract was demonstrated. To our knowledge, this is the first G-quadruplex-based assay for PTK7.     

SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

Structure‐based virtual screening usually involves docking of a library of chemical compounds onto the functional pocket of the target receptor so as to discover novel classes of ligands. However, the overall success rate remains low and screening a large library is computationally intensive. An alternative to this “ab initio” approach is virtual screening by binding homology search. In this approach, potential ligands are predicted based on similar interaction pairs (similarity in receptors and ligands). SPOT‐Ligand is an approach that integrates ligand similarity by Tanimoto coefficient and receptor similarity by protein structure alignment program SPalign. The method was found to yield a consistent performance in DUD and DUD‐E docking benchmarks even if model structures were employed. It improves over docking methods (DOCK6 and AUTODOCK Vina) and has a performance comparable to or better than other binding‐homology methods (FINDsite and PoLi) with higher computational efficiency. The server is available at http://sparks-lab.org . © 2016 Wiley Periodicals, Inc.