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Molecular docking of balanol to dynamics snapshots of protein kinase A.

Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.

Azepines↗

Molecular dynamics simulations of lignin peroxidase in solution.

The dynamical and structural properties of lignin peroxidase and its Trp171Ala mutant have been investigated in aqueous solution using molecular dynamics (MD) simulations. In both cases, the enzyme retained its overall backbone structure and all its noncovalent interactions in the course of the MD simulations. Very interestingly, the analysis of the MD trajectories showed the presence of large fluctuations in correspondence of the residues forming the heme access channel; these movements enlarge the opening and facilitate the access of substrates to the enzyme active site. Moreover, steered molecular dynamics docking simulations have shown that lignin peroxidase natural substrate (veratryl alcohol) can easily approach the heme edge through the access channel.

Benzyl Alcohols↗

Structure of Thermus thermophilus type 2 isopentenyl diphosphate isomerase inferred from crystallography and molecular dynamics.

Crystal structures of Thermus thermophilus and Bacillus subtilis type 2 IPP isomerases were combined to generate an almost complete model of the FMN-bound structure of the enzyme. In contrast to previous studies, positions of flexible loops were obtained and carefully analyzed by molecular dynamics. Docking simulations find a unique putative binding site for the IPP substrate.

Carbon-Carbon Double Bond Isomerases↗

Molecular dynamics simulation of the docking of substrates to proteins.

A simple method is described to perform docking of substrates to proteins or probes to receptor molecules by a modification of molecular dynamics simulations. The method consists of a separation of the center-of-mass motion of the substrate from its internal and rotational motions, and a separate coupling to different thermal baths for both types of motion of the substrate and for the motion of the receptor. Thus the temperatures and the time constants of coupling to the baths can be arbitrarily varied for these three types of motion, allowing either a frozen or a flexible receptor and allowing control of search rate without disturbance of internal structure. In addition, an extra repulsive term between substrate and protein was applied to smooth the interaction. The method was applied to a model substrate docking onto a model surface, and to the docking of phosphocholine onto immunoglobulin McPC603, in both cases with a frozen receptor. Using translational temperatures of the substrate in the range of 1300-1700 K and room temperature for the internal degrees of freedom of the substrate, an efficient nontrapping exploratory search ("helicopter view") is obtained which visits the correct binding sites. Low energy conformations can then be further investigated by separate search or by dynamic simulated annealing. In both cases the correct minima were identified. The possibility to work with flexible receptors is discussed.

Antibodies↗

Integrated immunoinformatics for the design of novel multi-epitope vaccine and identification of new drug targets against Stenotrophomonas maltophilia, a multidrug-resistant superbug.

BACKGROUND: Stenotrophomonas maltophilia is a multidrug-resistant opportunistic pathogen causing severe hospital-acquired infections, especially in immunocompromised patients. The absence of an effective vaccine and rising antibiotic resistance underscore the need for novel interventions. This study employed an integrated reverse vaccinology and computational analyses to identify new immunogenic targets, design a multi-epitope vaccine (MEV), and propose potential drug targets. METHODS: A comprehensive immunoinformatics pipeline was employed to assess antigenicity, allergenicity, human similarity, and physicochemical properties of S. maltophilia proteins. Both B- and T-cell epitopes were screened; however, only the top B-cell epitopes were selected for MEV construction, given the extracellular nature of S. maltophilia. MEV-TLR interactions were analyzed through molecular docking and dynamics simulations. In parallel, cytoplasmic proteins were screened via a subtractive genomics approach to identify essential, non-human homologous, and non-microbiome-similar proteins, which were further evaluated for druggability and interaction networks to propose novel therapeutic targets. RESULTS: From a total of 4111 proteins, seven potential immunogenic targets were identified: GspD (WP_108270537.1), FhuE (WP_049451370.1), fimbrial protein (WP_012479122.1), TonB-dependent receptor (WP_169448402.1), TolC family protein (WP_108270106.1), autotransporter beta-barrel OMP (WP_169448945.1), and a hypothetical protein (WP_005407892.1). Subsequently, an MEV was designed using five immunogenic epitopes derived from four of these targets: WP_005407892.1 (ADQDSSNM), WP_049451370.1 (SGKAEQ and GEESKTPS), WP_108270537.1 (GVTSTQSDSERT), and WP_169448945.1 (RELGGDRNE). Molecular docking and molecular dynamics simulations demonstrated strong, stable, and feasible interactions between the MEV and TLR-2 and TLR-4 receptors. Moreover, nine novel drug targets were predicted for S. maltophilia, providing new therapeutic insights. CONCLUSION: The designed MEV and identified immunogenic targets represent promising vaccine candidates against S. maltophilia. Further in vitro and in vivo studies are essential to confirm their safety, immunogenicity, and protective efficacy. Additionally, subtractive genomics analysis revealed nine novel, non-homologous drug targets, offering safer and more specific therapeutic avenues.

Drug targets↗

LARS promotes hepatocellular carcinoma progression via the PI3K/AKT/mTOR pathway and interaction with RPS5, and serves as a prognostic biomarker.

BACKGROUND: Hepatocellular carcinoma (HCC) caused many cancer deaths around the world. Its progression involves complex mechanisms, creating an urgent need to identify new therapeutic targets. Leucine-tRNA synthetase (LARS) is a key enzyme for protein synthesis, but its specific role and mechanism in HCC are not well understood. PURPOSE: This research aims to investigate the biological function, molecular mechanism, and clinical relevance of the LARS gene in HCC progression, to assess its potential as a treatment target. METHODS: LARS expression was assessed in HCC cell lines (PLC-PRF-5, HCC-LM3) and in mouse subcutaneous tumor models using siRNA and adeno-associated virus (AAV). Techniques including Cell Counting Kit-8(CCK-8), colony formation, EdU, Transwell, wound healing, and flow cytometry were used to measure cell proliferation, migration, invasion, and apoptosis. RNA-seq, proteomics (TMT), western blot, co-immunoprecipitation (Co-IP) with mass spectrometry, molecular docking, and molecular dynamics simulation were employed to study the affected signaling pathway (PI3K/AKT/mTOR) and interacting protein (RPS5). The TCGA (The Cancer Genome Atlas) database and UALCAN platform were used to analyze links between LARS expression and clinicopathological features or prognosis in HCC patients. RESULTS: Reducing LARS expression significantly inhibited the proliferation, colony formation, migration, and invasion of HCC cells, while promoting apoptosis. In mice, LARS knockdown markedly slowed tumor growth. Mechanistic studies showed that reducing LARS expression levels affected the PI3K/AKT/mTOR signaling pathway and led to decreased levels of the key interacting protein RPS5. Overexpressing RPS5 partly reversed the proliferation inhibition caused by LARS depletion. Molecular docking and dynamics simulations suggested that the environmental contaminant triphenyl phosphate (TPP) might bind to the LARS protein. Clinical data analysis revealed that LARS expression is higher in HCC tissues. High LARS expression was significantly associated with shorter overall survival (OS) in patients and correlated positively with various clinical features like tumor stage, grade, and TP53 mutation status. CONCLUSION: LARS helped HCC become worse by affecting the PI3K/AKT/mTOR pathway and working with RPS5. High LARS meant a worse outcome for patients. This suggested LARS could be used to predict disease or as a treatment target in HCC.

Carcinoma, Hepatocellular↗

Evidence for a strong selenium-aromatic interaction derived from crystallographic data and ab initio quantum chemical calculations.

Increasing attention is being paid to the role of selenium, both as an essential component required for the activity of many enzymes and in the context of selenium-based pharmaceutical agents. A wide range of therapeutics that include selenium are on the market and under development, such as antihypertensive, anticancerogenic, antiviral, and immunosuppressive agents. Computer-aided drug design (CADD) has proven to be an important tool for the development of new drugs. Many CADD techniques, including docking, molecular dynamics simulation, and other receptor-based approaches, require an accurate understanding of the nature of the intermolecular forces that act to stabilize protein-ligand complexes; moreover, a quantitative assessment of these interactions furthers our efforts to rationalize the drug design process. In this paper, we consider one class of interaction involving selenium, that between Se and aromatic rings. Prior work has shown that interactions between divalent sulfur and aromatic rings are observed much more frequently than would be expected on the basis of chance, both in protein structures and the crystal structures of organic compounds that include these moieties. Recent studies on the optimization of inhibitor-protein binding also suggest that sulfur-aromatic interactions are important in stabilizing these complexes and may be crucial focal point for CADD. Given that selenium and sulfur have similar chemistry, and that selenium is significantly more polarizable, we propose that Se-aromatic interactions may also play an important stabilizing role in the structure of folded proteins and in drug-protein complexes. We have tested this hypothesis against data from the Cambridge Crystallographic Database and ab initio quantum chemical calculations. We have found evidence that selenium does interact strongly with aromatic rings and may play a role analogous to sulfur in stabilizing protein folds. In addition, selenium should be considered along with sulfur in rational drug design strategies that seek to improve binding to target protein sites that include aromatic rings.

Crystallography, X-Ray↗

Comparative analysis of putative agonist-binding modes in the human A1 adenosine receptor.

A recent study reported a model of the human A(1) adenosine receptor and its agonist binding site, proposing two putative binding modes in the same binding site for the natural agonist, adenosine. The present work investigates the flexibility of this binding site by exhaustive exploration with the natural agonist and with three other adenosine derivatives: N6-cyclopentyladenosine (CPA), 2-chloro-N6-cyclopentyladenosine (CCPA), and 5'-N-ethylcarboxamidoadenosine (NECA). Our aim was to find a common binding mode for agonists that would explain the role in the binding process of the different substitutions allowed at the 2, N6, and 5' positions of adenosine. This problem was addressed through docking simulations, molecular dynamics studies, and estimations of the ligand-binding free energy with both the AUTODOCK scoring function and the linear interaction energy (LIE) approach. The results point to a single receptor-binding position that explains the effects of the different chemical modifications on the adenosine derivatives considered here.

Adenosine↗

The X-ray structure of Aspergillus aculeatus polygalacturonase and a modeled structure of the polygalacturonase-octagalacturonate complex.

Polygalacturonases hydrolyze the alpha-(1-4) glycosidic bonds of de-esterified pectate in the smooth region of the plant cell wall. Crystal structures of polygalacturonase from Aspergillus aculeatus were determined at pH 4.5 and 8.5 both to 2.0 A resolution. A. aculeatus polygalacturonase is a glycoprotein with one N and ten O-glycosylation sites and folds into a right-handed parallel beta-helix. The structures of the three independent molecules are essentially the same, showing no dependency on pH or crystal packing, and are very similar to that of Aspergillus niger polygalacturonase. However, the structures of the long T1 loop containing a catalytic tyrosine residue are significantly different in the two proteins. A three-dimensional model showing the substrate binding mode for a family 28 hydrolase was obtained by a combined approach of flexible docking, molecular dynamics simulations, and energy minimization. The octagalacturonate substrate was modeled as an unbent irregular helix with the -1 ring in a half-chair ((4)H(3)) form that approaches the transition state conformation. A comparative modeling of the three polygalacturonases with known structure shows that six subsites ranging from -4 to +2 are clearly defined but subsites -5 and +3 may or may not be shaped depending on the nearby amino acid residues. Both distal subsites are mostly exposed to the solvent region and have weak binding affinity even if they exist. The complex model provides a clear explanation for the functions, either in catalysis or in substrate binding, of all conserved amino acid residues in the polygalacturonase family of proteins. Modeling suggests that the role of the conserved Asn157 and Tyr270, which had previously been unidentified, may be in transition state stabilization. In A. niger polygalacturonase, the long T1 loop may have to undergo conformational change upon binding of the substrate to bring the tyrosine residue close to subsite -1.

Amino Acid Sequence↗

The thioesterase domain of the fengycin biosynthesis cluster: a structural base for the macrocyclization of a non-ribosomal lipopeptide.

Many secondary metabolic peptides from bacteria and fungi are produced by non-ribosomal peptide synthetases (NRPS) where the final step of biosynthesis is often catalysed by designated thioesterase domains. Here, we report the 1.8A crystal structure of the fengycin thioesterase (FenTE) from Bacillus subtilis F29-3, which catalyses the regio- and stereoselective release and macrocyclization of the antibiotic fengycin from the NRPS template. A structure of the PMSF-inactivated FenTE domain suggests the location of the oxyanion hole and the binding site of the C-terminal residue l-Ile11 of the lipopeptide. Using a combination of docking, molecular dynamics simulations and in vitro activity assays, a model of the FenTE-fengycin complex was derived in which peptide cyclization requires strategic interactions with residues lining the active site canyon.

Amino Acid Sequence↗

Impact of induced fit on ligand binding to the androgen receptor: a multidimensional QSAR study to predict endocrine-disrupting effects of environmental chemicals.

We investigated the influence of induced fit of the androgen receptor binding pocket on free energies of ligand binding. On the basis of a novel alignment procedure using flexible docking, molecular dynamics simulations, and linear-interaction energy analysis, we simulated the binding of 119 molecules representing six compound classes. The superposition of the ligand molecules emerging from the combined protocol served as input for Raptor, a receptor-modeling tool based on multidimensional QSAR allowing for ligand-dependent induced fit. Throughout our study, protein flexibility was explicitly accounted for. The model converged at a cross-validated r(2) = 0.858 (88 training compounds) and yielded a predictive r(2) = 0.792 (26 test compounds), thereby predicting the binding affinity of all compounds close to their experimental value. We then challenged the model by testing five molecules not belonging to compound classes used to train the model: the IC(50) values were predicted within a factor of 4.5 compared to the experimental data. The demonstrated predictivity of the model suggests that our approach may well be beneficial for both drug discovery and the screening of environmental chemicals for endocrine-disrupting effects, a problem that has recently become a cause for concern among scientists, environmental advocates, and politicians alike.

Benzhydryl Compounds↗

How can (-)-epigallocatechin gallate from green tea prevent HIV-1 infection? Mechanistic insights from computational modeling and the implication for rational design of anti-HIV-1 entry inhibitors.

Possible inhibitors preventing human immunodeficiency virus type 1 (HIV-1) entry into the cells are recognized as hopeful next-generation anti-HIV-1 drugs. It is highly desirable to develop a potent inhibitor blocking binding of glycoprotein CD4 of the cell with glycoprotein gp120 of HIV-1, because the gp120-CD4 binding is the initial step of HIV-1 entry into the cells. It has been recently reported that (-)-epigallocatechin gallate (EGCG) from green tea is an inhibitor blocking gp120-CD4 binding. But the inhibitory mechanism remains unknown. For understanding the inhibitory mechanism, extensive molecular docking, molecular dynamics simulations, and binding free-energy calculations have been performed in this study to predict the most favorable structures of CD4-EGCG, gp120-CD4, and gp120-CD4-EGCG binding complexes in water. The results reveal that EGCG binds with CD4 in such a way that the calculated binding affinity of gp120 with the CD4-EGCG complex is negligible. So, the favorable binding of EGCG with CD4 can effectively block gp120-CD4 binding. The calculated CD4-EGCG binding affinity (DeltaG(bind) = -5.5 kcal/mol, K(d) = 94 microM) is in excellent agreement with available experimental data suggesting IC(50) approximately 100 microM for EGCG-blocking CD4-gp120 binding. These results and insights provide a rational basis for future design of novel, more potent inhibitors to block gp120-CD4 binding.

Anti-HIV Agents↗

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome↗

Molecular dynamics simulation and automated docking of the pro-apoptotic Bax protein and its complex with a peptide designed from the Bax-binding domain of anti-apoptotic Ku70.

Bax, a multi-domain protein belonging to the large family of Bcl-2 proteins, has a pivotal role for the initiation of the cytochrome c-mediated apoptosis, a vital physiologic process to eliminate damaged or unwanted cells. In response to specific stimuli Bax translocates from cytosol to mitochondria outer membrane where a process of oligomerization occurs with pore formation through which cytochrome c and other death molecules escape. The pro-death action of Bax is regulated by the interaction with other pro-survival proteins. However, the conformational changes and the structural details necessary for homo and hetero interaction with other regulating proteins are largely unknown. This article reports a combined investigation of molecular dynamics (MD) simulation and automated docking that evidence the molecular regions of Bax involved in the binding with anti-apoptotic exapeptide (Bip) designed from Ku70, a subunit of the protein complex essential for non-homologous DNA repair but that inhibits also the Bax translocation to mitochondria. Since Bip suppresses apoptosis induced by several anti-cancer drugs, it appears relevant to achieve a better understanding of the structural and dynamical aspects that characterize the Bip-Bax complex in view of potential therapeutic implications. The present results show that the Bax region with the highest affinity for Bip is located in proximity of BH3 homology domain of Bax and also involves the alpha-helices 1 and 8. Moreover, the comparison of essential motions of Bax at 300 and 400 K before and after the formation of the complex with Bip evidences how the binding with the exa-peptide affects the collective motions of specific molecular districts of Bax considered to have functional relevance.

Amino Acid Sequence↗

Molecular dynamics simulations of the docking of substituted N5-deazapterins to dihydrofolate reductase.

Orientations of the deazapterin ring and the conformational preferences of groups appended to the deazapterin ring in a set of 8-substituted deazapterin cations docked into the dihydrofolate reductase (DHFR) binding site have been investigated using a methodology based on the simulated annealing technique within molecular dynamics (MD) simulations. Of five possible binding pockets for the 8-substituents, identified from a preliminary manual docking study, one has been definitively eliminated after an analysis of MD trajectories, while another remains uncertain. Using a new method based on standard thermodynamic cycles and a linear approximation of polar and non-polar free energy contributions from MD averages, binding affinities of the different ligands in each binding site have been correlated with experimental dissociation constants. The study has provided insights into structure-activity relationships for use in the design of modified inhibitors of DHFR.

Binding Sites↗

Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.

6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116 cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460 cells showed no increase in EdU incorporation at 10 or 100 nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.

Humans↗

Molecular dynamics simulations on SDF-1alpha: binding with CXCR4 receptor.

Insights into the interacting mode of CXCR4 with SDF-1alpha are crucial in understanding the structural and functional characteristics of CXCR4 receptor. In this paper a computational pipeline, integrating protein structure prediction, molecular dynamics simulations, automated molecular docking, and Brownian dynamics simulations were employed to investigate the dynamic and energetic aspects of CXCR4 associating with SDF-1alpha. The entire simulation revealed the surface distribution feature of electrostatic potentials and conformational "open-close" process of the receptor. The possible binding conformation of CXCR4 was identified, and the CXCR4-SDF-1alpha binding complex was generated. Arg188-Glu277 salt bridge plays an important role for both the extracellular domain conformational change and SDF-1alpha binding. Two binding sites were mapped at the extracellular domain (Site 1) and inside the transmembrane domain (Site 2), which are composed of conserved residues. Sites 1 and 2 contribute approximately 60% and 40% to the binding affinity with SDF-1alpha, respectively. The binding model is in agreement with most of the experimental data. Transmembrane VI has more significant motion in the harmonious conformational transition of CXCR4 during SDF-1alpha binding, which may be possibly associated with signal transduction. Based on the modeling and simulation, a binding mechanism hypothesis between CXCR4 and SDF-1alpha and its relationship to the signal transduction has been proposed.

Algorithms↗

Toward selective histone deacetylase inhibitor design: homology modeling, docking studies, and molecular dynamics simulations of human class I histone deacetylases.

Histone deacetylases (HDACs) play an important role in gene transcription. Inhibitors of HDACs induce cell differentiation and suppress cell proliferation in tumor cells. Although many HDAC inhibitors have been designed and synthesized, selective inhibition for class I HDAC isoforms is a goal that has yet to be achieved. To understand the difference between class I HDAC isoforms that could be exploited for the design of isoform-specific HDAC inhibitors, we have built three-dimensional models of four class I histone deacetylases, HDAC1, HDAC2, HDAC3, and HDAC8. Comparison of the homology model of HDAC8 with the recently published X-ray structure shows excellent agreement and validates the approach. A series of HDAC inhibitors were docked to the homology models to understand the similarities and differences between the binding modes. Molecular dynamic simulations of these HDAC-inhibitor complexes indicate that the interaction between the protein surface and inhibitor is playing an important role; also some active site residues show some flexibility, which is usually not included in routine docking protocols. The implications of these results for the design of isoform-selective HDAC inhibitors are discussed.

Amino Acid Sequence↗