A strategy for theoretical binding constant, Ki, calculations for neuraminidase aromatic inhibitors designed on the basis of the active site structure of influenza virus neuraminidase

Computational investigation of Moringa oleifera phytochemicals targeting EGFR: molecular docking, molecular dynamics simulation and density functional theory studies

Epidermal growth factor receptor (EGFR) is a prominent target for anticancer therapy due to its role in activating several cell signaling cascades. Clinically approved EGFR inhibitors are reported to show treatment resistance and toxicity, this study, therefore, investigates Moringa oleifera phytochemicals to find potent and safe anti-EGFR compounds. For that, phytochemicals were screened based on drug-likeness and molecular docking analysis followed by molecular dynamics simulation, density functional theory analysis and ADMET analysis to identify the effective inhibitors of EGFR tyrosine kinase (EGFR-TK) domain. Known EGFR-TK inhibitors (1-4 generations) were used as control. Among 146 phytochemicals, 136 compounds showed drug-likeness, of which Delta 7-Avenasterol was the most potential EGFR-TK inhibitor with a binding energy of -9.2 kcal/mol followed by 24-Methylenecholesterol (-9.1 kcal/mol), Campesterol (-9.0 kcal/mol) and Ellagic acid (-9.0 kcal/mol). In comparison, the highest binding affinity from control drugs was displayed by Rociletinib (-9.0 kcal/mol). The molecular dynamics simulation (100 ns) exhibited the structural stability of native EGFR-TK and protein-inhibitor complexes. Further, MM/PBSA computed the binding free energies of protein complex with Delta 7-Avenasterol, 24-Methylenecholesterol, Campesterol and Ellagic acid as -154.559 ± 18.591 kJ/mol, -139.176 ± 19.236 kJ/mol, -136.212 ± 17.598 kJ/mol and -139.513 ± 23.832 kJ/mol, respectively. Non-polar interactions were the major contributors to these energies. The density functional theory analysis also established the stability of these inhibitor compounds. ADMET analysis depicted acceptable outcomes for all top phytochemicals without displaying any toxicity. In conclusion, this report has identified promising EGFR-TK inhibitors to treat several cancers that can be further investigated through laboratory and clinical tests.

Systematic investigation of the multi-scale mechanisms of herbal medicine on treating ventricular remodeling: Theoretical and experimental studies

BACKGROUND

To explore the underlying molecule mechanism of herbal medicine in preventing ventricular remodeling (VR), we take a herbal formula that is clinically effective for preventing VR as an example, which composed of Pachyma hoelen Rumph, Atractylodes macrocephala Koidz., Cassia Twig and Licorice. Due to multi-components and multi-targets in herbal medicine, it is extremely difficult to systematically explain its mechanisms of action.

METHODS

An innovative systematic investigation framework which combines with pharmacokinetic screening, target fishing, network pharmacology, DeepDDI algorithm, computational chemistry, molecular thermodynamics, in vivo and in vitro experiments was performed for deciphering the underlying molecular mechanisms of herbal medicine for treating VR.

RESULTS

ADME screening and SysDT algorithm determined 75 potentially active compounds and 109 corresponding targets. Then, systematic analysis of networks reveals the crucial active ingredients and key targets in herbal medicine. Additionally, transcriptomic analysis identifies 33 key regulators during VR progression. Moreover, PPI network and biological function enrichment present four crucial signaling pathways, i.e. NF-κB and TNF, PI3K-AKT and C-type lectin receptor signaling pathways involved in VR. Besides, both molecular experiments at animal and cell levels reveal the beneficial effect of herbal medicine on preventing VR. Finally, MD simulations and binding free energy validate the reliability of drug-target interactions.

CONCLUSION

Our novelty is to build a systematic strategy which combines various theoretical methods combined with experimental approaches. This strategy provides a deep understanding for the study of molecular mechanisms of herbal medicine on treating diseases from systematic level, and offers a new idea for modern medicine to explore drug interventions for complex diseases as well.

Systematic investigation of the mechanism of herbal medicines for the treatment of prostate cancer

Due to various unpleasant side effects and general ineffectiveness of current treatments for prostate cancer (PCa), more and more people with PCa try to look for complementary and alternative medicine such as herbal medicine. However, since herbal medicine has multi-components, multi-targets and multi-pathways features, its underlying molecular mechanism of action is not yet known and still needs to be systematically explored. Presently, a comprehensive approach consisting of bibliometric analysis, pharmacokinetic assessment, target prediction and network construction is firstly performed to obtain PCa-related herbal medicines and their corresponding candidate compounds and potential targets. Subsequently, a total of 20 overlapping genes between DEGs in PCa patients and the target genes of the PCa-related herbs, as well as five hub genes, i.e., CCNA2, CDK2, CTH, DPP4 and SRC were determined employing bioinformatics analysis. Further, the roles of these hub genes in PCa were also investigated through survival analysis and tumour immunity analysis. Moreover, to validate the reliability of the C-T interactions and to further explore the binding modes between ingredients and their targets, the molecular dynamics (MD) simulations were carried out. Finally, based on the modularization of the biological network, four signaling pathways, i.e., PI3K-Akt, MAPK, p53 and cell cycle were integrated to further analyze the therapeutic mechanism of PCa-related herbal medicine. All the results show the mechanism of action of herbal medicines on treating PCa from the molecular to systematic levels, providing a reference for the treatment of complex diseases using TCM.

Systematic analyses on the potential immune and anti-inflammatory mechanisms of Shufeng Jiedu Capsule against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)-caused pneumonia

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A systematic study integrated is proposed to illustrate the potential immune and anti-inflammatory mechanisms of SFJDC against SARS-CoV-2.

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SFJDC regulates related targets, showing the potential anti-novel coronavirus effect.

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The work can provide a better understanding of the therapeutic mechanism of SFJDC for treating SARS-CoV-2.

The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)-caused pneumonia (Coronavirus disease −19, COVID-19), has resulted in a global health emergency. However, there is no vaccine or effective antiviral treatment against the newly emerged coronavirus and identifying the available therapeutics as soon as possible is critical for the response to the spread of SARS-CoV-2. Shufeng Jiedu Capsule (SFJDC), a well-known prescription of Traditional Chinese Medicine (TCM) in China, has been widely used in treating upper respiratory tract infections and acute lung injury, owing to its immunomodulatory and anti-inflammatory effects. Despite the definite evidence of effective use of SFJDC in the diagnosis and treatment of pneumonia caused by SARS-CoV-2, the underlying action mechanism remains unknown. Currently, a systematic study integrated with absorption, distribution, metabolism and excretion (ADME) evaluation, target prediction, network construction and functional bioinformatics analyses is proposed to illustrate the potential immune and anti-inflammatory mechanisms of SFJDC against SARS-CoV-2. Additionally, to further validate the reliability of the interactions and binding affinities between drugs and targets, docking, Molecular dynamics Simulations (MD) simulations and Molecular Mechanics/Poisson-Boltzmann Surface Area approach (MM-PBSA) calculations were carried out. The results demonstrate that SFJDC regulates the immunomodulatory and anti-inflammatory related targets on multiple pathways through its active ingredients, showing the potential anti-novel coronavirus effect. Overall, the work can provide a better understanding of the therapeutic mechanism of SFJDC for treating SARS-CoV-2 pneumonia from multi-scale perspectives, and may also offer a valuable clue for developing novel pharmaceutical strategies to control the current coronavirus.

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.

Identification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies

Methionine Aminopeptidases MetAPs are divalent-cofactor dependent enzymes that are responsible for the cleavage of the initiator Methionine from the nascent polypeptides. MetAPs are classified into two isoforms: namely, MetAP1 and MetAP2. Several studies have revealed that MetAP2 is upregulated in various cancers, and its inhibition has shown to suppress abnormal or excessive blood vessel formation and tumor growth in model organisms. Clinical studies show that the natural product fumagillin, and its analogs are potential inhibitors of MetAP2. However, due to their poor pharmacokinetic properties and neurotoxicities in clinical studies, their further developments have received a great setback. Here, we apply structure-based virtual screening and molecular dynamics methods to identify a new class of potential inhibitors for MetAP2. We screened Otava's Chemical Library, which consists of about 3 200 000 tangible-chemical compounds, and meticulously selected the top 10 of these compounds based on their inhibitory potentials against MetAP2. The top hit compounds subjected to ADMET predictor using 3 independent ADMET prediction programs, were found to be drug-like. To examine the stability of ligand binding mode, and efficacy, the unbound form of MetAP2, its complexes with fumagillin, spiroepoxytriazole, and the best promising compounds compound-3369841 and compound-3368818 were submitted to 100 ns molecular dynamics simulation. Like fumagillin, spiroepoxytriazole, and both compound-3369841 and compound-3368818 showed stable binding mode over time during the simulations. Taken together, these uninherited-fumagillin compounds may serve as new class of inhibitors or provide scaffolds for further optimization towards the design of more potent MetAP2 inhibitors -development of such inhibitors would be essential strategy against various cancer types.

Identification of promising anti-DNA gyrase antibacterial compounds using de novo design, molecular docking and molecular dynamics studies

The rapidly increasing rate of antibiotic resistance is of great concern. Approximately two million deaths result annually from bacterial infections worldwide. Therefore, there is a paramount requirement to develop innovative and novel antibacterial agents with new mechanisms of action and activity against resistant bacterial strains. For this purpose, a set of benzothiazole and N-phenylpyrrolamides derivatives reported as DNA Gyrase B (GyrB) inhibitors were collected from the literature and docked inside the receptor cavity of DNA Gyrase B (PDB ID: 5L3J). The best 10 docked complexes were used to identify novel antibacterial chemical agents through a de novo design approach. Out of initial 300 chemical analogues, the best six analogues were identified using screening with a set of criteria followed by pharmacokinetic analysis. The binding interactions of the best six analogues revealed that all molecules formed a number of critical interactions with catalytic amino residues of DNA Gyrase B with high binding energy. The predicted inhibitory constant biological activity based on binding energy supported the potential of the molecules as DNA Gyrase B ligands. The RMSD, RMSF, and radius of gyration parameters obtained from the 100 ns molecular dynamics simulation study clearly demonstrated that all six analogues were efficient enough to form stable complexes with DNA Gyrase B. High negative binding energy of all ligands obtained from MM-GBSA approach undoubtedly explained the strong affinity toward the DNA Gyrase B. Therefore, the proposed de novo designed molecules can be considered as promising antibacterial chemical agents subject to experimental validation, in vitro.Communicated by Ramaswamy H. Sarma.

Molecular dynamics and combined docking studies for the identification of Zaire ebola virus inhibitors

Ebola virus (EBOV) is a lethal human pathogen with a risk of global spread of its zoonotic infections, and Ebolavirus Zaire specifically has the highest fatality rate amongst other species. There is a need for continuous effort towards having therapies, as a single licensed treatment to neutralize the EBOV is yet to come into reality. This present study virtually screened the MCULE database containing almost 36 million compounds against the structure of a Zaire Ebola viral protein (VP) 35 and a consensus scoring of both MCULE and CLCDDW docking programs remarked five compounds as potential hits. These compounds, with binding energies ranging from -7.9 to -8.9 kcal/mol, were assessed for predictions of their physicochemical and bioactivity properties, as well as absorption, distribution, metabolism, excretion, and toxicity (ADMET) criteria. The results of the 50 ns molecular dynamics simulations showed the presence of dynamic stability between ligand and protein complexes, and the structures remained significantly unchanged at the ligand-binding site throughout the simulation period. Both docking analysis and molecular dynamics simulation studies suggested strong binding affinity towards the receptor cavity and these selected compounds as potential inhibitors against the Zaire Ebola VP 35. With respect to inhibition constant values, bioavailability radar and other physicochemical properties, compound A (MCULE-1018045960-0-1) appeared to be the most promising hit compound. However, the ligand efficiency and ligand efficiency scale need improvement during optimization, and also validation via in vitro and in vivo studies are necessary to finally make a lead compound in treating Ebola virus diseases. Communicated by Ramaswamy H. Sarma.

Crystal structure of a new benzoic acid inhibitor of influenza neuraminidase bound with a new tilt induced by overpacking subsite C6

Background

Influenza neuraminidase (NA) is an important target for antiviral inhibitors since its active site is highly conserved such that inhibitors can be cross-reactive against multiple types and subtypes of influenza. Here, we discuss the crystal structure of neuraminidase subtype N9 complexed with a new benzoic acid based inhibitor (2) that was designed to add contacts by overpacking one side of the active site pocket. Inhibitor 2 uses benzoic acid to mimic the pyranose ring, a bis-(hydroxymethyl)-substituted 2-pyrrolidinone ring in place of the N-acetyl group of the sialic acid, and a branched aliphatic structure to fill the sialic acid C6 subsite.

Results

Inhibitor 2 {4-[2,2-bis(hydroxymethyl)-5-oxo-pyrrolidin-1-yl]-3-[(dipropylamino)methyl)]benzoic acid} was soaked into crystals of neuraminidase of A/tern/Australia/G70c/75 (N9), and the structure refined with 1.55 Å X-ray data. The benzene ring of the inhibitor tilted 8.9° compared to the previous compound (1), and the number of contacts, including hydrogen bonds, increased. However, the IC₅₀ for compound 2 remained in the low micromolar range, likely because one propyl group was disordered. In this high-resolution structure of NA isolated from virus grown in chicken eggs, we found electron density for additional sugar units on the N-linked glycans compared to previous neuraminidase structures. In particular, seven mannoses and two N-acetylglucosamines are visible in the glycan attached to Asn200. This long, branched high-mannose glycan makes significant contacts with the neighboring subunit.

Conclusions

We designed inhibitor 2 with an extended substituent at C4-corresponding to C6 of sialic acid-to increase the contact surface in the C6-subsite and to force the benzene ring to tilt to maximize these interactions while retaining the interactions of the carboxylate and the pyrolidinone substituents. The crystal structure at 1.55 Å showed that we partially succeeded in that the ring in 2 is tilted relative to 1 and the number of contacts increased, but one hydrophobic branch makes no contacts, perhaps explaining why the IC₅₀ did not decrease. Future design efforts will include branches of unequal length so that both branches may be accommodated in the C6-subsite without conformational disorder. The high-mannose glycan attached to Asn200 makes several inter-subunit contacts and appears to stabilize the tetramer.

Combining crystallographic information and an aspherical-atom data bank in the evaluation of the electrostatic interaction energy in an enzyme-substrate complex: influenza neuraminidase inhibition

Although electrostatic interactions contribute only a part of the interaction energies between macromolecules, unlike dispersion forces they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In the reported study, a wide range of complexes of influenza neuraminidases with inhibitor molecules (sialic acid derivatives and others) have been analyzed using charge densities from a transferable aspherical-atom data bank. The strongest interactions of the residues are with the acidic group at the C2 position of the inhibitor ( approximately -300 kJ mol(-1) for -COO(-) in non-aromatic inhibitors, approximately -120-210 kJ mol(-1) for -COO(-) in aromatic inhibitors and approximately -450 kJ mol(-1) for -PO(3)(2-)) and with the amino and guanidine groups at C4 ( approximately -250 kJ mol(-1)). Other groups contribute less than approximately 100 kJ mol(-1). Residues Glu119, Asp151, Glu227, Glu276 and Arg371 show the largest variation in electrostatic energies of interaction with different groups of inhibitors, which points to their important role in the inhibitor recognition. The Arg292-->Lys mutation reduces the electrostatic interactions of the enzyme with the acidic group at C2 for all inhibitors that have been studied (SIA, DAN, 4AM, ZMR, G20, G28, G39 and BCZ), but enhances the interactions with the glycerol group at C6 for inhibitors that contain it. This is in agreement with the lower level of resistance of the mutated virus to glycerol-containing inhibitors compared with the more hydrophobic derivatives.

Understanding of known drug-target interactions in the catalytic pocket of neuraminidase subtype N1

To provide detailed information and insight into the drug-target interaction, structure, solvation, and dynamic and thermodynamic properties, the three known-neuraminidase inhibitors-oseltamivir (OTV), zanamivir (ZNV), and peramivir (PRV)-embedded in the catalytic site of neuraminidase (NA) subtype N1 were studied using molecular dynamics simulations. In terms of ligand conformation, there were major differences in the structures of the guanidinium and the bulky groups. The atoms of the guanidinium group of PRV were observed to form many more hydrogen bonds with the surrounded residues and were much less solvated by water molecules, in comparison with the other two inhibitors. Consequently, D151 lying on the 150-loop (residues 147-152) of group-1 neuraminidase (N1, N4, N5, and N8) was considerably shifted to form direct hydrogen bonds with the --OH group of the PRV, which was located rather far from the 150-loop. For the bulky group, direct hydrogen bonds were detected only between the hydrophilic side chain of ZNV and residues R224, E276, and E277 of N1 with rather weak binding, 20-70% occupation. This is not the case for OTV and PRV, in which flexibility and steric effects due to the hydrophobic side chain lead to the rearrangement of the surrounded residues, that is, the negatively charged side chain of E276 was shifted and rotated to form hydrogen bonds with the positively charged moiety of R224. Taking into account all the ligand-enzyme interaction data, the gas phase MM interaction energy of -282.2 kcal/mol as well as the binding free energy (DeltaG(binding)) of -227.4 kcal/mol for the PRV-N1 are significantly lower than those of the other inhibitors. The ordering of DeltaG(binding) of PRV < ZNV < OTV agrees well with the ordering of experimental IC(50) value.

Structural glycobiology: a game of snakes and ladders

Oligo- and polysaccharides are infamous for being extremely flexible molecules, populating a series of well-defined rotational isomeric states under physiological conditions. Characterization of this heterogeneous conformational ensemble has been a major obstacle impeding high-resolution structure determination of carbohydrates and acting as a bottleneck in the effort to understand the relationship between the carbohydrate structure and function. This challenge has compelled the field to develop and apply theoretical and experimental methods that can explore conformational ensembles by both capturing and deconvoluting the structural and dynamic properties of carbohydrates. This review focuses on computational approaches that have been successfully used in combination with experiment to detail the three-dimensional structure of carbohydrates in a solution and in a complex with proteins. In addition, emerging experimental techniques for three-dimensional structural characterization of carbohydrate-protein complexes and future challenges in the field of structural glycobiology are discussed. The review is divided into five sections: (1) The complexity and plasticity of carbohydrates, (2) Predicting carbohydrate-protein interactions, (3) Calculating relative and absolute binding free energies for carbohydrate-protein complexes, (4) Emerging and evolving techniques for experimental characterization of carbohydrate-protein structures, and (5) Current challenges in structural glycoscience.

Molecular dynamics and free energy analysis of neuraminidase-ligand interactions

We report molecular dynamics calculations of neuraminidase in complex with an inhibitor, 4-amino-2-deoxy-2,3-didehydro-N-acetylneuraminic acid (N-DANA), with subsequent free energy analysis of binding by using a combined molecular mechanics/continuum solvent model approach. A dynamical model of the complex containing an ionized Glu119 amino acid residue is found to be consistent with experimental data. Computational analysis indicates a major van der Waals component to the inhibitor-neuraminidase binding free energy. Based on the N-DANA/neuraminidase molecular dynamics trajectory, a perturbation methodology was used to predict the binding affinity of related neuraminidase inhibitors by using a force field/Poisson-Boltzmann potential. This approach, incorporating conformational search/local minimization schemes with distance-dependent dielectric or generalized Born solvent models, correctly identifies the most potent neuraminidase inhibitor. Mutation of the key ligand four-substituent to a hydrogen atom indicates no favorable binding free energy contribution of a hydroxyl group; conversely, cationic substituents form favorable electrostatic interactions with neuraminidase. Prospects for further development of the method as an analysis and rational design tool are discussed.

Investigation of neuraminidase-substrate recognition using molecular dynamics and free energy calculations

Development of the new generation of therapeutics against the influenza viral coat protein neuraminidase is a response to the continuing threat of influenza epidemics. A variety of structurally similar compounds have been reported that vary greatly in their ability to inhibit neuraminidase, a critical enzyme that cleaves sialic acid and promotes virion release. To determine how neuraminidase exhibits this wide range of affinities with structurally similar compounds, molecular dynamic simulations, coupled with free energy calculations, were used to determine the binding components of a series of neuraminidase inhibitors. Using four cocrystal structures of neuraminidase-inhibitor complexes, we examined the structural and energetic components of ligand potency and selectivity. An in-depth energetic analysis, including internal energy, entropy, and nonbonded interactions, reveals that potency of ligand binding is governed by nonpolar contacts. Electrostatic components generally oppose binding, although two of the best inhibitors use electrostatic interactions to orient the ligand. This investigation suggests that the enhanced selectivity and potency of the better ligands may arise from an improved positioning of their ligand atoms in the active site due to polar and hydrophobic functionalities. Simulations that included crystal water molecules in the active site indicate that the more potent ligands make less use of water-mediated interactions.

Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 2. Computational titration and pH effects in molecular models of neuraminidase-inhibitor complexes

One factor that can strongly influence predicted free energy of binding is the ionization state of functional groups on the ligands and at the binding site at which calculations are performed. This analysis is seldom performed except in very detailed computational simulations. In this work, we address the issues of (i) modeling the complexity resulting from the different ionization states of ligand and protein residues involved in binding, (ii) if, and how, computational methods can evaluate the pH dependence of ligand inhibition constants, and (iii) how to score the protonation-dependent models. We developed a new and fairly rapid protocol called "computational titration" that enables parallel modeling of multiple ionization ensembles for each distinct protonation level. Models for possible protonation combinations for site/ligand ionizable groups are built, and the free energy of interaction for each of them is quantified by the HINT (Hydropathic INTeractions) software. We applied this procedure to the evaluation of the binding affinity of nine inhibitors (six derived from 2,3-didehydro-2-deoxy-N-acetylneuraminic acid, DANA) of influenza virus neuraminidase (NA), a surface glycoprotein essential for virus replication and thus a pharmaceutically relevant target for the design of anti-influenza drugs. The three-dimensional structures of the NA enzyme-inhibitor complexes indicate considerable complexity as the ligand-protein recognition site contains several ionizable moieties. Each computational titration experiment reveals a peak HINT score as a function of added protons. This maximum HINT score indicates the optimum pH (or the optimum protonation state of each inhibitor-protein binding site) for binding. The pH at which inhibition is measured and/or crystals were grown and analyzed can vary from this optimum. A protonation model is proposed for each ligand that reconciles the experimental complex structure with measured inhibition and the free energy of binding. Computational titration methods allow us to analyze the effect of pH in silico and may be helpful in improving ligand binding free energy prediction when protonation or deprotonation of the residues or ligand functional groups at the binding site might be significant.

Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase

Many proteins undergo small side chain or even backbone movements on binding of different ligands into the same protein structure. This is known as induced fit and is potentially problematic for virtual screening of databases against protein targets. In this report we investigate the limits of the rigid protein approximation used by the docking program, GOLD, through cross-docking using protein structures of influenza neuraminidase. Neuraminidase is known to exhibit small but significant induced fit effects on ligand binding. Some neuraminidase crystal structures caused concern due to the bound ligand conformation and GOLD performed poorly on these complexes. A 'clean' set, which contained unique, unambiguous complexes, was defined. For this set, the lowest energy structure was correctly docked (i.e. RMSD < 1.5 A away from the crystal reference structure) in 84% of proteins, and the most promiscuous protein (1mwe) was able to dock all 15 ligands accurately including those that normally required an induced fit movement. This is considerably better than the 70% success rate seen with GOLD against general validation sets. Inclusion of specific water molecules involved in water-mediated hydrogen bonds did not significantly improve the docking performance for ligands that formed water-mediated contacts but it did prevent docking of ligands that displaced these waters. Our data supports the use of a single protein structure for virtual screening with GOLD in some applications involving induced fit effects, although care must be taken to identify the protein structure that performs best against a wide variety of ligands. The performance of GOLD was significantly better than the GOLD implementation of ChemScore and the reasons for this are discussed. Overall, GOLD has shown itself to be an extremely good, robust docking program for this system.

Functional group placement in protein binding sites: a comparison of GRID and MCSS

One approach to combinatorial ligand design begins by determining optimal locations (i.e., local potential energy minima) for functional groups in the binding site of a target macromolecule. MCSS and GRID are two methods, based on significantly different algorithms, which are used for this purpose. A comparison of the two methods for the same functional groups is reported. Calculations were performed for nonpolar and polar functional groups in the internal hydrophobic pocket of the poliovirus capsid protein, and on the binding surface of the src SH3 domain. The two approaches are shown to agree qualitatively; i.e., the global characteristics of the functional group maps generated by MCSS and GRID are similar. However, there are significant differences in the relative interaction energies of the two sets of minima, a consequence of the different functional form used to evaluate polar interactions (electrostatics and hydrogen bonding) in the two methods. The single sphere representation used by GRID affords only positional information, supplemented by the identification of hydrogen bonding interactions. By contrast, the multi-atom representation of most MCSS groups yields in both positional and orientational information. The two methods are most similar for small functional groups, while for larger functional groups MCSS yields results consistent with GRID but superior in detail. These results are in accord with the somewhat different purposes for which the two methods were developed. GRID has been used mainly to introduce functionalities at specific positions in lead compounds, in which case the orientation is predetermined by the structure of the latter. The orientational information provided by MCSS is important for its use in the de novo design of large, multi-functional ligands, as well as for improving lead compounds.

Analysis of inhibitor binding in influenza virus neuraminidase

2,3-didehydro-2-deoxy-N:-acetylneuraminic acid (DANA) is a transition state analog inhibitor of influenza virus neuraminidase (NA). Replacement of the hydroxyl at the C9 position in DANA and 4-amino-DANA with an amine group, with the intention of taking advantage of an increased electrostatic interaction with a conserved acidic group in the active site to improve inhibitor binding, significantly reduces the inhibitor activity of both compounds. The three-dimensional X-ray structure of the complexes of these ligands and NA was obtained to 1.4 A resolution and showed that both ligands bind isosterically to DANA. Analysis of the geometry of the ammonium at the C4 position indicates that Glu119 may be neutral when these ligands bind. A computational analysis of the binding energies indicates that the substitution is successful in increasing the energy of interaction; however, the gains that are made are not sufficient to overcome the energy that is required to desolvate that part of the ligand that comes in contact with the protein.

Novel aromatic inhibitors of influenza virus neuraminidase make selective interactions with conserved residues and water molecules in the active site

The active site of type A or B influenza virus neuraminidase is composed of 11 conserved residues that directly interact with the substrate, sialic acid. An aromatic benzene ring has been used to replace the pyranose of sialic acid in our design of novel neuraminidase inhibitors. A bis(hydroxymethyl)pyrrolidinone ring was constructed in place of the N-acetyl group on the sialic acid. The hydroxymethyl groups replace two active site water molecules, which resulted in the high affinity of the nanomolar inhibitors. However, these inhibitors have greater potency for type A influenza virus than for type B influenza virus. To resolve the differences, we determined the X-ray crystal structure of three benzoic acid substituted inhibitors bound to the active site of B/Lee/40 neuraminidase. The investigation of a hydrophobic aliphatic group and a hydrophilic guanidino group on the aromatic inhibitors shows changes in the interaction with the active site residue Glu275. The results provide an explanation for the difference in efficacy of these inhibitors against types A and B viruses, even though the 11 active site residues of the neuraminidase are conserved.

A new method for predicting binding free energy between receptor and ligand

A practical method to estimate binding free energy, deltaG(bind), of a given ligand structure to the target receptor has been developed. The method assumes that deltaG(bind) is given by the summation of intermolecular interaction energy, deltaG(inter), and partial desolvation energy, deltaG(desolv). DeltaG(desolv) is calculated from the buried surface area in the complex between the ligand and receptor, based on solvation energy, deltaG(solv), formulated by an equation which can be calibrated with observed values. Then, the method was applied to arabinose-binding protein (ABP) and dihydrofolate reductase (DHFR), after recalibrating the weights for deltaG(inter) and each term of deltaG(desolv) using observed deltaG(bind) data for 29 known ligands to avidin (AV). The usefulness of our method was confirmed by the fact that correlation coefficients between the calculated and observed deltaG(bind)'s in AV, ABP and DHFR were 0.92, 0.77, and 0.88, whereas the corresponding values obtained by simple force field calculation were 0.79, 0.30, and 0.79, respectively. Further investigations to improve the method and validate the parameters are in progress.

Prediction of binding constants of protein ligands: a fast method for the prioritization of hits obtained from de novo design or 3D database search programs

A dataset of 82 protein-ligand complexes of known 3D structure and binding constant Ki was analysed to elucidate the important factors that determine the strength of protein-ligand interactions. The following parameters were investigated: the number and geometry of hydrogen bonds and ionic interactions between the protein and the ligand, the size of the lipophilic contact surface, the flexibility of the ligand, the electrostatic potential in the binding site, water molecules in the binding site, cavities along the protein-ligand interface and specific interactions between aromatic rings. Based on these parameters, a new empirical scoring function is presented that estimates the free energy of binding for a protein-ligand complex of known 3D structure. The function distinguishes between buried and solvent accessible hydrogen bonds. It tolerates deviations in the hydrogen bond geometry of up to 0.25 A in the length and up to 30 degrees in the hydrogen bond angle without penalizing the score. The new energy function reproduces the binding constants (ranging from 3.7 x 10(-2) M to 1 x 10(-14) M, corresponding to binding energies between -8 and -80 kJ/mol) of the dataset with a standard deviation of 7.3 kJ/mol corresponding to 1.3 orders of magnitude in binding affinity. The function can be evaluated very fast and is therefore also suitable for the application in a 3D database search or de novo ligand design program such as LUDI. The physical significance of the individual contributions is discussed.

Generation and characterization of a mutant of influenza A virus selected with the neuraminidase inhibitor BCX-140

Influenza neuraminidase (NA) plays an important role in viral replication, and characterization of viruses resistant to NA inhibitors will help elucidate the role of active-site residues. This information will assist in designing better inhibitors targeted to essential active-site residues that cannot generate drug-resistant mutations. In the present study we used the benzoic acid-based inhibitor BCX-140 to select and characterize resistant viruses. BCX-140 binds to the NA active site in an orientation that is opposite that of a sialic acid-based compound, 4-guanidino-2,4-dideoxy-2,3-dehydro-N-acetylneuraminic acid (GANA). Thus, the guanidino group of BCX-140 binds to Glu-276, whereas in GANA the guanidino group binds to Glu-119. We passaged influenza A/Singapore/1/57 (H2N2) in Madin-Darby canine kidney cells in the presence of BCX-140, and virus resistant to this inhibitor was selected after six passages. The NA of this mutant was still sensitive to inhibition by BCX-140. However, the mutant virus was resistant to BCX-140 in plaque and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. Sequence analysis of hemagglutinin (HA) and NA genes revealed changes in both, although none were in the active site of the NA. Depending on the method of selection of the resistant virus, two types of changes associated with the sialic acid binding site were seen in the HA. One is a change in HA1 of Ala-133 to Thr, a residue close to the binding site, while the other change was Arg-132 of HA1 to Gln, which in HA1 of serotype H3 is a sialic acid contact (Asn-137). Binding studies revealed that both types of resistant viruses had reduced receptor binding affinity compared to that of the wild type. Thus, resistance to BCX-140 was generated by modifying the HA. NA active-site residue 276 may be essential for activity, and thus, it cannot be changed to generate resistance. However, drug-induced changes in the HA can result in a virus that is less dependent on NA activity for growth in cells and, hence, resistant to NA inhibitors.

'Flu' and structure-based drug design

The threat of a catastrophic outbreak of influenza is ever present. Vaccines are only partially effective and the two compounds, amantidine and rimantidine, used clinically against influenza A cause side-effects and rapid viral resistance. Recent advances bring hope that specific and potent drugs against influenza may soon be available in the clinic. These compounds were designed to inhibit influenza neuraminidase (NA), one of the viral coat glycoproteins, using the crystal structure of NA which was first published in 1983. In this review, the application of structure-based drug design approaches to the design of anti-influenza agents targeted at NA and haemagglutinin (HA), the other viral surface glycoprotein, is discussed.

Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes

This paper describes the development of a simple empirical scoring function designed to estimate the free energy of binding for a protein-ligand complex when the 3D structure of the complex is known or can be approximated. The function uses simple contact terms to estimate lipophilic and metal-ligand binding contributions, a simple explicit form for hydrogen bonds and a term which penalises flexibility. The coefficients of each term are obtained using a regression based on 82 ligand-receptor complexes for which the binding affinity is known. The function reproduces the binding affinity of the complexes with a cross-validated error of 8.68 kJ/mol. Tests on internal consistency indicate that the coefficients obtained are stable to changes in the composition of the training set. The function is also tested on two test sets containing a further 20 and 10 complexes, respectively. The deficiencies of this type of function are discussed and it is compared to approaches by other workers.

Guanidinobenzoic acid inhibitors of influenza virus neuraminidase

The active site of influenza virus neuraminidase (NA) is formed by 11 universally conserved residues. A guanidino group incorporated into two unrelated NA inhibitors was previously reported to occupy different negatively charged sites in the NA active site, A new inhibitor containing two guanidino groups was synthesized in order to utilize both sites in an attempt to acquire a combined increase in affinity. The X-ray crystal structures of the complexes show that the expected increase in affinity could not be achieved even though the added guanidino group binds to the negatively charged site as designed. This suggests that the ligand affinity to the target protein is contributed both from ligand-protein interactions and solvation/conformation energy of the ligand.

Sialidases: structures, biological significance and therapeutic potential

The structure-based design of a potent inhibitor of the influenza-virus neuraminidase (sialidase) is one of the outstanding successes of rational drug design. Recent clinical trials of the drug have stimulated many companies to seek a share of the potentially huge flu market. Sialidases, however, are involved in the pathogenesis of a whole range of other diseases, so perhaps the knowledge and expertise gained from the influenza story can be used in the design of other drugs, given that they all share certain structural features.