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PubMed1999

Docking of hydrophobic ligands with interaction-based matching algorithms.

MOTIVATION: Matching of chemical interacting groups is a common concept for docking and fragment placement algorithms in computer-aided drug design. These algorithms have been proven to be reliable and fast if at least a certain number of hydrogen bonds or salt bridges occur. However, the algorithms typically run into problems if hydrophobic fragments or ligands should be placed. In order to dock hydrophobic fragments without significant loss of computational efficiency, we have extended the interaction model and placement algorithms in our docking tool FlexX. The concept of multi-level interactions is introduced into the algorithms for automatic selection and placement of base fragments. RESULTS: With the multi-level interaction model and the corresponding algorithmic extensions, we were able to improve the overall performance of FlexX significantly. We tested the approach with a set of 200 protein-ligand complexes taken from the Brookhaven Protein Data Bank (PDB). The number of test cases which can be docked within 1.5 A RMSD from the crystal structure can be increased from 58 to 64%. The performance gain is paid for by an increase in computation time from 73 to 91 s on average per protein-ligand complex. AVAILABILITY: The FlexX molecular docking software is available for UNIX platforms IRIX, Solaris and Linux. See http://cartan.gmd.de/FlexX for additional information.

Algorithms↗
PubMed2001

Rsk2 allosterically activates estrogen receptor alpha by docking to the hormone-binding domain.

We describe a novel mechanism for transcriptional regulation, in which docking of p90 ribosomal S6 kinase 2 (Rsk2) to the hormone-binding domain (HBD) of estrogen receptor alpha (ERalpha) induces a conformational change that enhances the transcriptional activation function contained in the HBD. A constitutively active mutant of Rsk2 specifically enhances ERalpha-mediated transcription by phosphorylation of Ser167 in ERalpha and by physically associating with residues 326-394 of the ERalpha HBD. The anti-estrogen 4-hydroxytamoxifen blocks Rsk2-mediated activation of ERalpha, by inducing a conformation of ERalpha in which the Rsk2 docking site is masked. Transcriptional activation and docking are specific for ERalpha and do not occur with the related isoform, ERbeta. ERalpha phosphorylation, docking and transcriptional activation are regulated by the Rsk2 N-terminal kinase domain. The allosteric regulation of a target protein, independent of phosphorylation, may be paradigmatic of a general function for protein kinase docking sites.

Allosteric Regulation↗
PubMed2003

A docking site determining specificity of Pbs2 MAPKK for Ssk2/Ssk22 MAPKKKs in the yeast HOG pathway.

Mitogen-activated protein kinase (MAPK) cascades are conserved signaling modules composed of three sequentially activated kinases (MAPKKK, MAPKK and MAPK). Because individual cells contain multiple MAPK cascades, mechanisms are required to ensure the fidelity of signal transmission. In yeast, external high osmolarity activates the HOG (high osmolarity glycerol) MAPK pathway, which consists of two upstream branches (SHO1 and SLN1) and common downstream elements including the Pbs2 MAPKK and the Hog1 MAPK. The Ssk2/Ssk22 MAPKKKs in the SLN1 branch, when activated, exclusively phosphorylate the Pbs2 MAPKK. We found that this was due to an Ssk2/Ssk22-specific docking site in the Pbs2 N-terminal region. The Pbs2 docking site constitutively bound the Ssk2/Ssk22 kinase domain. Docking site mutations drastically reduced the Pbs2-Ssk2/Ssk22 interaction and hampered Hog1 activation by the SLN1 branch. Fusion of the Pbs2 docking site to a different MAPKK, Ste7, allowed phosphorylation of Ste7 by Ssk2/Ssk22. Thus, the docking site contributes to both the efficiency and specificity of signaling. During these analyses, we also found a nuclear export signal and a possible nuclear localization signal in Pbs2.

Amino Acid Sequence↗
PubMed1990

Distance-constrained molecular docking by simulated annealing.

An optimized method based on the principle of simulated annealing is presented for determining the relative position and orientation of interacting molecules. The spatial relationships of these molecules are described by intermolecular distance constraints between specific pairs of atoms, such as found in hydrogen bonds or from experimentally determined data. The method makes use of a random walk through six rotational and translational degrees of freedom where the constituent molecules are treated as rigid bodies. Van der Waals repulsions are used only to define a lower bound on distances between constrained atom pairs within the docking procedure. A cost function comprised of purely geometric constraints is optimized via simulated annealing, in order to search for the best orientation and position of the two molecules. Our docking procedure is applied to eight serine proteinase complexes from the Brookhaven Protein Data Bank. For each simulation 100 computations were performed. A typical docking computation requires only a few seconds of CPU time on a VAXserver 3500. The influence of the number of constraints on the final docked positions was studied. The sensitivity of the docking procedure to a ligand structure which is not well defined is also addressed. Possible applications of this method include using approximate distances incorporating complete energy functions.

Aspartic Acid Endopeptidases↗
PubMed2002

Efficient docking of peptides to proteins without prior knowledge of the binding site.

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.

Algorithms↗
PubMed2001

A novel approach for assessing macromolecular complexes combining soft-docking calculations with NMR data.

We present a novel and efficient approach for assessing protein-protein complex formation, which combines ab initio docking calculations performed with the protein docking algorithm BiGGER and chemical shift perturbation data collected with heteronuclear single quantum coherence (HSQC) or TROSY nuclear magnetic resonance (NMR) spectroscopy. This method, termed "restrained soft-docking," is validated for several known protein complexes. These data demonstrate that restrained soft-docking extends the size limitations of NMR spectroscopy and provides an alternative method for investigating macromolecular protein complexes that requires less experimental time, effort, and resources. The potential utility of this novel NMR and simulated docking approach in current structural genomic initiatives is discussed.

Bacterial Proteins↗
PubMed2001

Electrostatic contributions to protein-protein interactions: fast energetic filters for docking and their physical basis.

The methods of continuum electrostatics are used to calculate the binding free energies of a set of protein-protein complexes including experimentally determined structures as well as other orientations generated by a fast docking algorithm. In the native structures, charged groups that are deeply buried were often found to favor complex formation (relative to isosteric nonpolar groups), whereas in nonnative complexes generated by a geometric docking algorithm, they were equally likely to be stabilizing as destabilizing. These observations were used to design a new filter for screening docked conformations that was applied, in conjunction with a number of geometric filters that assess shape complementarity, to 15 antibody-antigen complexes and 14 enzyme-inhibitor complexes. For the bound docking problem, which is the major focus of this paper, native and near-native solutions were ranked first or second in all but two enzyme-inhibitor complexes. Less success was encountered for antibody-antigen complexes, but in all cases studied, the more complete free energy evaluation was able to identify native and near-native structures. A filter based on the enrichment of tyrosines and tryptophans in antibody binding sites was applied to the antibody-antigen complexes and resulted in a native and near-native solution being ranked first and second in all cases. A clear improvement over previously reported results was obtained for the unbound antibody-antigen examples as well. The algorithm and various filters used in this work are quite efficient and are able to reduce the number of plausible docking orientations to a size small enough so that a final more complete free energy evaluation on the reduced set becomes computationally feasible.

Amino Acids↗
PubMed2000

EEG changes in 4-week-old lambs in response to castration, tail docking and mulesing.

OBJECTIVE: To interpret changes in EEG in relation to perceived pain of castration, mulesing and docking in lambs. DESIGN: Analysis of covariance (randomised block design) to determine the effects of treatment on eight bandwidths of the EEG frequency spectrum. PROCEDURE: Ninety-eight, 3- to 4-week-old lambs were subjected to one of seven treatments: castration, tail docking, mulesing, ear tagging, sham shearing, formalin injection (to induce lameness) and handling. EEG was recorded for 15 min before treatment, during treatment, and for 15 min after treatment. RESULTS: Consistently lower mean power values across all bandwidths of the EEG were found at the time of mulesing and docking than at handling and shearing (P < 0.01). Formalin injection resulted in lower power values than handling and shearing (P < 0.01). Castration had lower power values than handling and shearing. Similarly, for 15 min after treatment, mulesing and formalin injection had significantly lower power values than handling, shearing, ear tagging and castration (P < 0.05). CONCLUSION: The consistent effects associated with mulesing, docking and castration compared to handling, shearing and ear tagging suggest that mulesing at both the time of treatment and during 15 min after treatment results in a response that is similar to that of induced lameness. Docking and castration result in a response at the time of treatment that is similar to induced lameness and mulesing, but during 15 min after treatment is similar to the non-noxious control treatments. However, the depressing effects on the mean power values are the reverse of that anticipated from a previously developed pain model, highlighting the need for further research to develop this technology to evaluate pain associated with husbandry procedures.

Animal Husbandry↗
PubMed2000

Acute cortisol responses and wound healing in lambs after ring castration plus docking with or without application of a castration clamp to the scrotum.

OBJECTIVE: To test whether the cortisol response to ring castration plus docking is reduced by additional application of a castration clamp across the full width of the scrotum distal to the ring. DESIGN: A physiological study with controls. PROCEDURE: Lambs, 3 to 6 weeks of age, were castrated using a ring or ring plus castration clamp applied for 6 or 10 s and docked using a ring. Blood samples were taken before and regularly for about 4 h after treatment and analysed for plasma cortisol concentrations. The healing of the scrotal wounds was monitored for 6 weeks after castration. RESULTS: The plasma cortisol concentrations were lower only at 60 min after treatment in lambs castrated with a clamp placed on the scrotum for 10 s after ring castration and docking than in lambs castrated and docked by ring alone. Scrotal wounds healed more quickly after ring plus clamp than after ring only castration. CONCLUSIONS: The castration clamp had at most a marginal effect on the cortisol response to ring castration and docking of 3- to 6-week-old lambs, but it did seem to improve the rate of healing.

Animals↗
PubMed1999

Identification of the docked granule pool responsible for the first phase of glucose-stimulated insulin secretion.

The mechanisms underlying the first phase of glucose-stimulated insulin release, the deterioration of which marks the early stages of both type 1 and type 2 diabetes, are essentially unknown. Among many hypotheses, one holds that the first phase is due to a readily releasable pool of insulin-containing granules. We used current knowledge of the mechanisms of exocytosis and the proteins involved in docking granules at the plasma membrane to test this hypothesis. A docked pool of readily releasable granules was identified by immunoprecipitation of the plasma membrane protein syntaxin with a specific antibody and by co-immunoprecipitation of soluble N-ethylmaleimide-sensitive factor attachment protein-25 (SNAP-25) and the granule proteins synaptobrevin and synaptotagmin. The four SNARE proteins co-immunoprecipitated each other, thus identifying the core complex associated with docked granules. Using co-immunoprecipitation as a marker for docked granules, we found that the docked pool was rapidly discharged during the first phase of glucose-stimulated insulin release and refilled during the second phase. Other secretagogues also released the pool, whereas the physiological inhibitor norepinephrine blocked its release. Further studies on the nature of this pool of granules should shed light on the causes of its deterioration in the early stages of diabetes and the reasons for deficient insulin release.

Animals↗
PubMed2000

BiGGER: a new (soft) docking algorithm for predicting protein interactions.

A new computationally efficient and automated "soft docking" algorithm is described to assist the prediction of the mode of binding between two proteins, using the three-dimensional structures of the unbound molecules. The method is implemented in a software package called BiGGER (Bimolecular Complex Generation with Global Evaluation and Ranking) and works in two sequential steps: first, the complete 6-dimensional binding spaces of both molecules is systematically searched. A population of candidate protein-protein docked geometries is thus generated and selected on the basis of the geometric complementarity and amino acid pairwise affinities between the two molecular surfaces. Most of the conformational changes observed during protein association are treated in an implicit way and test results are equally satisfactory, regardless of starting from the bound or the unbound forms of known structures of the interacting proteins. In contrast to other methods, the entire molecular surfaces are searched during the simulation, using absolutely no additional information regarding the binding sites. In a second step, an interaction scoring function is used to rank the putative docked structures. The function incorporates interaction terms that are thought to be relevant to the stabilization of protein complexes. These include: geometric complementarity of the surfaces, explicit electrostatic interactions, desolvation energy, and pairwise propensities of the amino acid side chains to contact across the molecular interface. The relative functional contribution of each of these interaction terms to the global scoring function has been empirically adjusted through a neural network optimizer using a learning set of 25 protein-protein complexes of known crystallographic structures. In 22 out of 25 protein-protein complexes tested, near-native docked geometries were found with C(alpha) RMS deviations < or =4.0 A from the experimental structures, of which 14 were found within the 20 top ranking solutions. The program works on widely available personal computers and takes 2 to 8 hours of CPU time to run any of the docking tests herein presented. Finally, the value and limitations of the method for the study of macromolecular interactions, not yet revealed by experimental techniques, are discussed.

Algorithms↗
PubMed2025

Investigating the molecular mechanism of Yangxin decoction in treating major depressive disorder using network pharmacology and molecular docking technology approaches.

Yangxin decoction has been used to treat major depressive disorder (MDD). This study aims to identify the active components and potential mechanisms of Yangxin decoction in treating MDD using network pharmacology and molecular docking technology. The active components and targets of Yangxin decoction were screened, and MDD-related targets were predicted. Networks of "herbal medicine-active components-potential targets" and protein-protein interaction were constructed. Core components and core targets were identified through network topology analysis. Gene ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on candidate genes. Molecular docking was conducted using AutoDock software (Olson Laboratory of the Scripps Research Institute, San Diego) to explore the interactions between core targets and active components, and the results were visualized using PyMOL (DeLano Scientific LLC, South San Francisco). A total of 433 active components and 392 targets of Yangxin decoction were identified, along with 11,796 MDD-related targets. There were 680 overlapping targets between Yangxin decoction and MDD, associated with 104 active components. Core targets identified through network topology analysis and molecular docking included serine/threonine kinase 1 (AKT1), tumor necrosis factor, interleukin-6, tumor protein P53, and proto-oncogene tyrosine-protein kinase Src. Gene ontology enrichment analysis revealed 1606 biological processes, 191 cellular components, and 373 molecular functions. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified 212 signaling pathways, with significant enrichment in caffeine metabolism, bladder cancer, advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications, and vascular endothelial growth factor signaling pathway. Molecular docking results showed strong binding energy between core active components and core targets. Yangxin decoction exhibits multi-component, multi-pathway, and multi-target therapeutic characteristics. It primarily regulates targets such as AKT1, tumor necrosis factor, interleukin-6, tumor protein P53, and proto-oncogene tyrosine-protein kinase Src through advanced glycation end products-receptor for advanced glycation end products, vascular endothelial growth factor, and ErbB signaling pathways, exerting anti-inflammatory, immune-regulating, and oxidative stress-inhibiting effects to alleviate MDD.

Molecular Docking Simulation↗
PubMed2026

Analysis of the molecular mechanism underlying di(2-ethylhexyl) phthalate-induced bladder carcinogenesis via network toxicology and molecular docking approaches: An observational study.

This study aims to investigate the toxicity of di(2-ethylhexyl) phthalate (DEHP) and the potential molecular mechanisms of DEHP-induced bladder cancer (BLCA) using network toxicology and molecular docking strategies. The toxicity of DEHP was assessed using Prox-II software, and potential targets for DEHP-induced BLCA were identified by integrating data from ChEMBL database, Search Tool for Interactions of Chemicals, SwissTargetPrediction, GeneCards, Therapeutic Target Database, Online Mendelian Inheritance in Man, and The Cancer Genome Atlas. STRING database and Cytoscape were employed to construct target networks and determine core targets. The expression levels of core targets were analyzed using R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on potential and core targets. Molecular docking was carried out using CB-Dock 2 to verify the interactions between DEHP and core targets. A total of 105 potential targets related to DEHP-induced BLCA were identified, from which 7 core targets were selected: cyclin-dependent kinase 1, interleukin 6, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, cyclin B2, and B-cell lymphoma 2. IL-6 and B-cell lymphoma 2 showed downregulated expression in tumor tissues, while cyclin-dependent kinase 1, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, and cyclin B2 were upregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these targets were enriched in cell signaling and cancer-related pathways. Molecular docking confirmed that DEHP interacts with these core targets. DEHP may promote the development of BLCA by interacting with key proteins and signaling pathways. This study provides a theoretical basis for understanding the molecular mechanisms of DEHP-induced BLCA and offers references for future prevention and treatment strategies.

Diethylhexyl Phthalate↗
PubMed2026

Elucidating the Mechanism of Xiaoqinglong Decoction in Chronic Urticaria Treatment: An Integrated Approach of Network Pharmacology, Bioinformatics Analysis, Molecular Docking, and Molecular Dynamics Simulations.

INTRODUCTION: Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application. METHODS: The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database. RESULTS: A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses. DISCUSSION: This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions. CONCLUSION: This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.

Molecular Docking Simulation↗
PubMed2026

A Network Pharmacology and Molecular Docking Study of TongBi Formula for Osteoarthritis.

This study applied network pharmacology combined with molecular docking to predict the potential therapeutic targets and molecular mechanisms of TongBi Formula (TBF) in osteoarthritis (OA). Active components and corresponding targets of TBF were retrieved from the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform, while OA-related targets were collected from Online Mendelian Inheritance in Man, GeneCards, DrugBank, and Therapeutic Target Database. A network visualization and analysis software was used to construct compound-target and protein-protein interaction (PPI) networks. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery platform. Molecular docking analysis was conducted using a molecular docking software to evaluate the predicted binding affinity between key active compounds and core target proteins. A total of 47 overlapping targets between TBF and OA were identified. PPI network analysis highlighted JUN, RELA, IL6, MAPK1, and IL10 as potential hub targets. Enrichment analysis suggested that TBF may regulate inflammation, lipid metabolism, and multiple intracellular signaling pathways associated with OA progression. Molecular docking results demonstrated favorable predicted binding affinities between core active compounds and key OA-related protein targets. These findings provide a computational framework for understanding the potential mechanisms of TBF against OA and support further experimental validation.

Molecular Docking Simulation↗
PubMed2026

Integrated Network Pharmacology and Molecular Docking Analysis of Sishen Decoction Identifies Potential Targets and Pathways in Gout.

Gout is a disease characterized by hyperuricemia and the deposition of urate crystals in joints and soft tissues, leading to recurrent acute arthritis. Its increasing prevalence imposes substantial clinical and socioeconomic burdens. Sishen Decoction (SSD) has been used in the treatment of gout, but its potential molecular mechanisms remain unclear. This study applied an integrated network pharmacology and molecular docking approach to identify potential targets and signaling pathways associated with SSD in gout. Active compounds and corresponding targets of SSD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), while gout-related targets were collected from the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Overlapping targets were identified and used to construct a drug-component-target-disease network. A protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed, followed by molecular docking using the docking server analysis module. A total of 37 bioactive compounds were associated with 116 overlapping gout-related targets. The top hub targets included TP53, IL6, IL1B, TNF, AKT1, EGFR, CASP3, JUN, BCL2, and MMP9. GO analysis suggested that these targets are involved in gene expression regulation and signal transduction. KEGG enrichment analysis indicated significant associations with the mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase/protein kinase B (PI3K-Akt), interleukin-17 (IL-17), and tumor necrosis factor (TNF) signaling pathways. Molecular docking predicted favorable interactions between key compounds and hub targets, with all binding energies of &#x2264;-5 kcal/mol. These computational findings provide potential mechanistic hypotheses for the action of SSD in gout and may support future experimental validation.

Molecular Docking Simulation↗
PubMed1997

Automated docking of monosaccharide substrates and analogues and methyl alpha-acarviosinide in the glucoamylase active site.

Glucoamylase is an important industrial glucohydrolase with a large specificity range. To investigate its interaction with the monosaccharides D-glucose, D-mannose, and D-galactose and with the substrate analogues 1-deoxynojirimycin, D-glucono-1,5-lactone, and methyl alpha-acarviosinide, MM3(92)-optimized structures were docked into its active site using AutoDock 2.1. The results were compared to structures of glucoamylase complexes obtained by protein crystallography. Charged forms of some substrate analogues were also docked to assess the degree of protonation possessed by glucoamylase inhibitors. Many forms of methyl alpha-acarviosinide were conformationally mapped by using MM3(92), characterizing the conformational pH dependence found for the acarbose family of glucosidase inhibitors. Their significant conformers, representing the most common states of the inhibitor, were used as initial structures for docking. This constitutes a new approach for the exploration of binding modes of carbohydrate chains. Docking results differ slightly from x-ray crystallographic data, the difference being of the order of the crystallographic error. The estimated energetic interactions, even though agreeing in some cases with experimental binding kinetics, are only qualitative due to the large approximations made by AutoDock force field.

1-Deoxynojirimycin↗
PubMedDate not supplied

Molecular docking of superantigens with class II major histocompatibility complex proteins.

The molecular recognition of two superantigens with class II major histocompatibility complex molecules was simulated by using protein-protein docking. Superantigens studied were staphylococcal enterotoxin B (SEB) and toxic shock syndrome toxin-1 (TSST-1) in their crystallographic assemblies with HLA-DR1. Rigid-body docking was performed sampling configurational space of the interfacial surfaces by employing a strategy of partitioning the contact regions on HLA-DR1 into separate molecular recognition units. Scoring of docked conformations was based on an electrostatic continuum model evaluated with the finite-difference Poisson-Boltzmann method. Estimates of nonpolar contributions were derived from the buried molecular surface areas. We found for both superantigens that docking the HLA-DR1 surface complementary with the SEB and TSST-1 contact regions containing a homologous hydrophobic surface loop provided sufficient recognition for the reconstitution of native-like conformers exhibiting the highest-scoring free energies. For the SEB complex, the calculations were successful in reproducing the total association free energy. A comparison of the free-energy determinants of the conserved hydrophobic contact residue indicates functional similarity between the two proteins for this interface. Though both superantigens share a common global association mode, differences in binding topology distinguish the conformational specificities underlying recognition.

Algorithms↗