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PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗

PubMed2001

Molecular docking-based test for affinities of two ligands toward vasopressin and oxytocin receptors.

Molecular docking simulations are now fast developing area of research. In this work we describe an effective procedure of preparation of the receptor-ligand complexes. The amino-acid residues involved in ligand binding were identified and described.

Amino Acids↗

PubMed2026

Sanguinarine as a multi-target therapeutic candidate for laryngeal cancer: insights from network pharmacology, molecular dynamics and in vitro validation.

OBJECTIVE: To identify the core targets and elucidate the potential molecular mechanisms of sanguinarine (SA) against laryngeal squamous cell carcinoma (LSCC), and to validate its antitumor effects in vitro. METHODS: Potential targets of SA were predicted using SwissTargetPrediction, TargetNet, and SuperPred and intersected with LSCC-related targets obtained from the GeneCards, OMIM, and DISEASES databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. A protein-protein interaction (PPI) network was constructed using the STRING database (combined score > 0.900), and topological parameters including degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), eigenvector centrality (EC), and local average connectivity (LAC) were calculated in Cytoscape to identify core genes based on median thresholds. Molecular docking and 100-ns molecular dynamics (MD) simulations were conducted for epidermal growth factor receptor (EGFR), Phosphatidylinositide-3-kinase catalytic subunit alpha (PIK3CA), phosphatidylinositol-4,5-biphosphate 3-kinase catalytic subunit β (PIK3CB), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta (PIK3CD), and Non-Receptor Tyrosine Kinase (SRC). The effects of SA on LSCC were evaluated using CCK-8, colony formation, Transwell migration, and wound-healing assays in TU177 cells and TU212. RESULTS: A total of 213 common targets were identified, which were significantly enriched in PI3K-Akt signaling, EGFR tyrosine kinase inhibitor resistance, and adhesion- and migration-related pathways. The PPI network comprised 259 nodes and 259 edges, from which five core genes-PIK3CA, PIK3CB, PIK3CD, EGFR, and SRC-were identified. Molecular docking revealed strong binding affinities between SA and the PI3K family proteins (- 9.79 to - 10.96 kcal/mol), as well as EGFR (- 8.58 kcal/mol) and SRC (- 6.77 kcal/mol). MD simulations indicated greater stability of SA complexes with EGFR and PI3K family members compared with SRC. In vitro assays demonstrated that SA significantly inhibited TU177 cell and TU212 cell proliferation, colony formation, and migration. CONCLUSION: SA may exert anti-laryngeal cancer effects through synergistic multi-target inhibition centered on the EGFR/SRC/PI3K signaling axis, highlighting its potential as a promising therapeutic candidate for LSCC.

Humans↗

PubMed2026

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↗

PubMed2004

Combining pharmacophore search, automated docking, and molecular dynamics simulations as a novel strategy for flexible docking. Proof of concept: docking of arginine-glycine-aspartic acid-like compounds into the alphavbeta3 binding site.

A novel and highly efficient flexible docking approach is presented where the conformations (internal degrees of freedom) and orientations (external degrees of freedom) of the ligands are successively considered. This hybrid method takes advantage of the synergistic effects of structure-based and ligand-based drug design techniques. Preliminary antagonist-derived pharmacophore determination provides the postulated bioactive conformation. Subsequent docking of this pharmacophore to the receptor crystal structure results in a postulated pharmacophore/receptor binding mode. Pharmacophore-oriented docking of antagonists is subsequently achieved by matching ligand interacting groups with pharmacophore points. Molecular dynamics in water refines the proposed complexes. To validate the method, arginine-glycine-aspartic acid (RGD) containing peptides, pseudopeptides, and RGD-like antagonists were docked to the crystal structure of alphavbeta3 holoprotein and apoprotein. The proposed directed docking was found to be more accurate, faster, and less biased with respect to the protein structure (holo and apoprotein) than DOCK, Autodock, and FlexX docking methods. The successful docking of an antagonist recently cocrystallized with the receptor to both apo and holoprotein is particularly appealing. The results summarized in this report illustrated the efficiency of our light CoMFA/rigid body docking hybrid method.

Apoproteins↗

PubMed2006

Parallelized-over-parts computation of absolute binding free energy with docking and molecular dynamics.

We present a technique for biomolecular free energy calculations that exploits highly parallelized sampling to significantly reduce the time to results. The technique combines free energies for multiple, nonoverlapping configurational macrostates and is naturally suited to distributed computing. We describe a methodology that uses this technique with docking, molecular dynamics, and free energy perturbation to compute absolute free energies of binding quickly compared to previous methods. The method does not require a priori knowledge of the binding pose as long as the docking technique used can generate reasonable binding modes. We demonstrate the method on the protein FKBP12 and eight of its inhibitors.

Biophysics↗

PubMed2003

Implicit solvent models for flexible protein-protein docking by molecular dynamics simulation.

The suitability of three implicit solvent models for flexible protein-protein docking by procedures using molecular dynamics simulation is investigated. The three models are (i) the generalized Born (GB) model implemented in the program AMBER6.0; (ii) a distance-dependent dielectric (DDD) model; and (iii) a surface area-dependent model that we have parameterized and call the NPSA model. This is a distance-dependent dielectric model modified by neutralizing the ionizable side-chains and adding a surface area-dependent solvation term. These solvent models were first tested in molecular dynamics simulations at 300 K of the native structures of barnase, barstar, segment B1 of protein G, and three WW domains. These protein structures display a range of secondary structure contents and stabilities. Then, to investigate the performance of the implicit solvent models in protein docking, molecular dynamics simulations of barnase/barstar complexation, as well as PIN1 WW domain/peptide complexation, were conducted, starting from separated unbound structures. The simulations show that the NPSA model has significant advantages over the DDD and GB models in maintaining the native structures of the proteins and providing more accurate docked complexes.

Bacterial Proteins↗

PubMed2005

Application of molecular modeling to analysis of inhibition of kinesin motor proteins of the BimC subfamily by monastrol and related compounds.

Application of molecular modeling approaches has potential to contribute to rational drug design. These approaches may be especially useful when attempting to elucidate the structural features associated with novel drug targets. In this study, molecular docking and molecular dynamics were applied to studies of inhibition of the human motor protein denoted HsEg5 and other homologues in the BimC subfamily. These proteins are essential for mitosis, so compounds that inhibit their activity may have potential as anticancer therapeutics. The discovery of a small-molecule cell-permeable inhibitor, monastrol, has stimulated research in this area. Interestingly, monastrol is reported to inhibit the human and Xenopus forms of Eg5, but not those from Drosophila and Aspergillus. In this study, homology modeling was used to generate models of the Xenopus, Drosophila, and Aspergillus homologues, using the crystal structure of the human protein in complex with monastrol as a template. A series of known inhibitors was docked into each of the homologues, and the differences in binding energies were consistent with reported experimental data. Molecular dynamics revealed significant changes in the structure of the Aspergillus homologue that may contribute to its relative insensitivity to monastrol and related compounds.

Animals↗

PubMed2026

Cross-tissue Mendelian randomization prioritizes RAB27B as a brain-derived candidate protein for postpartum depression.

OBJECTIVE: Postpartum depression (PPD) is one of the most common and debilitating complications of childbirth, yet the candidate proteins linking genetic risk to disease remain poorly defined. Building on recent genome-wide association studies (GWAS), we sought to integrate cross-tissue proteogenomic data to identify candidate proteins for PPD and explore therapeutic opportunities. METHODS: We conducted two-sample Mendelian randomization (MR) using genome-wide significant cis-protein QTLs from brain (n = 608 proteins), cerebrospinal fluid (CSF; n = 214), and plasma (n = 612). PPD summary statistics were obtained from FinnGen R8 (13,657 cases, 236,178 controls) and replicated in an independent GWAS. Phenome-wide association (PheWAS) was used to assess pleiotropy. Potential therapeutic targets were evaluated through DSigDB drug repurposing, molecular docking, and molecular dynamics simulations. RESULTS: Among all proteins tested, RAB27B was the only brain-derived protein surpassing Bonferroni correction (OR = 1.60; 95% CI: 1.30-1.96; P = 6.6 × 10⁻⁶), whereas no significant proteins were identified in CSF or plasma. This association was replicated in an independent GWAS (OR = 1.27; 95% CI: 1.02-1.58; P = 0.037). PheWAS identified no pleiotropic associations at genome-wide significance. In silico drug repurposing identified pregnenolone as a candidate ligand with computationally predicted stable binding to RAB27B, providing a starting point for future experimental validation. CONCLUSION: This study provides the first cross-tissue proteogenomic evidence that RAB27B is a brain-derived, reproducible candidate protein genetically associated with PPD. By extending GWAS signals to functional protein-level mechanisms and therapeutic inference, our findings nominate RAB27B and pregnenolone as promising directions for postpartum psychiatric research.

Humans↗

PubMed2005

Computational studies and drug design for HIV-1 reverse transcriptase inhibitors of 3',4'-di-O-(S)-camphanoyl-(+)-cis-khellactone (DCK) analogs.

Molecular docking and molecular dynamics simulation were applied to study the binding mode of 3',4'-di-O-(S)-camphanoyl-(+)-cis-khellactone (DCK) analogs anti-HIV inhibitors with HIV-1 RT. The results suggest that there is a strong hydrogen bond between DCK O16 and NH of Lys101, and that DCK analogues might act similarly as other types of HIV-1 RT inhibitors. The investigation about drug resistance for DCK shows no remarkable influence on the most frequently observed mutation K103N of HIV-1 RT. Based on the proposed mechanism, some new structures were designed and predicted by a SVM model. All compounds exhibited potent inhibitory activities against HIV replication in H9 lymphocytes with EC50 values lower than 1.95 microM. The rationality of the method was validated by experimental results.

Camphor↗

PubMed2004

A novel hIL-6 antagonist peptide from computer-aided design contributes to suppression of apoptosis in M1 cells.

Based on the complex crystal structure of human interleukin-6 (hIL-6) and its receptor (hIL-6R), a novel hIL-6 antagonist peptide (named PT) was designed using computer-guided design method. Dealing with molecular docking and molecular dynamics methods, the interaction between PT and hIL-6R was analyzed. The theoretical studies showed that PT possessed very high affinity to hIL-6R and offered a practical means of imposing long-term blockade of hIL-6 activity in vivo. This effect was examined due to growth arrest and apoptosis induced by hIL-6 in myeloblastic cell line M1 cells in a dose-dependent manner. The findings demonstrate that PT could also act as an excellent antagonist candidate for the induction of growth arrest and apoptosis. Furthermore, murine M1 myeloid cell line, which was induced by the physiological inducer hIL-6 to undergo apoptosis and growth arrest, could be used as a subtle model system to test hIL-6 antagonist.

Animals↗

PubMed2006

The rational designed antagonist derived from the complex structure of interleukin-6 and its receptor affectively blocking interleukin-6 might be a promising treatment in multiple myeloma.

Human interleukin-6 is involved in the maintenance and progression of several diseases such as multiple myeloma (MM), rheumatoid arthritis, or osteoporosis. Our previous work demonstrated that an interleukin-6 antagonist peptide (named PT) possessed potential bioactivity to antagonize the function of hIL-6 and could efficiently induce the growth arrest and apoptosis of XG-7 and M1 cells in a dose-dependent manner. In this study, the theoretical interaction of the peptide PT with its receptor was analyzed further more with molecular docking and molecular dynamics methods. The theoretical studies showed that PT possessed very high affinity to interleukin-6R and offered a practical means of imposing long-term blockade of interleukin-6 activity in vivo. According to the theoretical results, the biological evaluation of PT was researched on two different cells models with more sensitive approaches: (1) The antagonist activity of PT was studied on the interleukin-6 dependent MM cells (XG-7) cultured with interleukin-6. In the other interleukin-6 dependent MM cells (SKO-007), they survived themselves by auto/paracrine without the exogenous interleukin-6, and also could be antagonized by PT. The therapeutic value of PT only limited on the interleukin-6 dependent category in MM. (2) Myeloid leukemia M1 cells were induced for growth arrest and apoptosis in response to interleukin-6. The results supported our previous findings and showed that PT could be evaluated by protecting the cells from interleukin-6 induced apoptosis. In conclusion, PT could induce interleukin-6-dependent XG-7 and SKO-007 cells to apoptosis while inhibit interleukin-6-stimulated apoptosis in M1 cells.

Antineoplastic Agents↗

PubMed2026

CCT2 defines a highly cisplatin-resistant and poor-prognosis subtype of lung adenocarcinoma.

Cisplatin-based chemotherapy is a standard treatment for lung adenocarcinoma (LUAD), yet acquired cisplatin resistance remains a marked cause of treatment failure. The molecular mechanisms driving cisplatin resistance in LUAD have not been fully elucidated. The present study integrated bulk transcriptomic data, genomic mutation profiles and single-cell RNA sequencing data to systematically investigate cisplatin resistance in LUAD. Resistance-associated genes were identified through differential expression, survival analysis and database integration. Unsupervised clustering was used to define cisplatin resistance-associated subtypes. Functional characteristics were explored using pathway enrichment, immune infiltration, tumor mutation burden and weighted gene co-expression network analysis. A machine learning framework incorporating 101 algorithms was applied to identify key genes and construct a prognostic model. Single-cell analyses and in vitro experiments were performed to validate the biological role of the core gene. Molecular docking and molecular dynamics simulations were conducted to identify potential therapeutic compounds. A total of two molecular subtypes with distinct cisplatin resistance levels and prognostic outcomes were identified. The high-resistance subtype exhibited enhanced cell cycle activity, DNA repair signaling and immune heterogeneity. Machine learning analysis revealed a five-gene signature, with chaperonin-containing TCP1 subunit 2 (CCT2) emerging as a key regulator of cisplatin resistance. Single-cell analyses showed that CCT2 was predominantly enriched in resistant epithelial cell subpopulations. Functional experiments demonstrated that CCT2 knockdown significantly inhibited cell proliferation and enhanced cisplatin sensitivity in LUAD cell lines. A number of candidate compounds targeting CCT2 exhibited stable binding in silico. The present findings identified CCT2 as a key mediator of cisplatin resistance in LUAD and provided potential therapeutic strategies to overcome chemotherapy resistance.

chaperonin-containing TCP-1 subunit 2↗

PubMed2002

SOFTDOCK: understanding of molecular recognition through a systematic docking study.

Molecular recognition and docking are essential to the biological functions of proteins. SOFTDOCK was one of the first molecular docking methods developed for protein-protein docking. Its ability to represent the molecular surface with different shapes and properties and to dock a variety of molecular complexes with certain conformational changes was demonstrated in a previous study. In the present work, we studied the effects of the docking parameters through statistical analysis. Seventy one typical binary complexes of different categories in PDB were also systematically docked for a test; 57 of them produced correct solutions with one set of docking parameters whereas the other 14 complexes required adjustment of the docking parameters, by decreasing the softness of the recognition and hence the background noise. We found that these 14 complexes had special structural features. Our results suggest that a variety of mechanisms may be involved in molecular recognition rather than the shape complementarity only, which is very helpful in developing more powerful methods for predicting molecular recognition.

Binding Sites↗

PubMed2026

Polyphenol-Rich Opuntia ficus-indica Cladodes: An Integrated Metabolomic, In Vivo and In Silico Study Supporting Their Hypolipidemic and Hepatoprotective Effects.

Background: Hyperlipidemia is a major risk factor for cardiometabolic disorders, including non-alcoholic fatty liver disease (NAFLD), and is closely associated with oxidative stress. Opuntia ficus-indica (OFI) cladodes are recognized as a rich source of bioactive phytochemicals; however, the molecular mechanisms underlying their metabolic benefits remain incompletely understood. Objectives: This study aimed to comprehensively evaluate the hypolipidemic and hepatoprotective potential of a polyphenol-rich O. ficus-indica cladode extract (OCE) using an integrated approach combining in vivo evaluation, untargeted metabolomics (UHPLC-Orbitrap-MS/MS), molecular docking, and ADMET prediction. Methods: Hyperlipidemic mice fed a high-fat diet (HFD) were treated with OCE, while molecular docking was performed on ten major annotated phytochemicals against twelve key proteins involved in lipid metabolism and cholesterol homeostasis, including HMGCR, FAS, PPARα, PCSK9, and NPC1L1, using simvastatin as the reference compound. Results: OCE treatment significantly improved plasma and hepatic lipid profiles, improved glucose homeostasis, and markedly reduced hepatic malondialdehyde (MDA) levels, indicating attenuation of oxidative stress. Histopathological analysis further supported a pronounced hepatoprotective effect, with a substantial reduction in hepatic steatosis. Untargeted metabolomics enabled the annotation of 102 metabolites, putatively identifying piscidic acid as the predominant phenolic constituent together with a diverse profile of flavonoids and phenolic acids. Molecular docking supported the potential contribution of these phytochemicals to the regulation of lipid metabolism through favorable interactions with multiple therapeutic targets, while ADMET prediction suggested an overall favorable pharmacokinetic and toxicity profile despite the lower intestinal permeability predicted for glycosylated derivatives. Conclusions: Overall, these findings support O. ficus-indica cladodes as a promising source of dietary bioactive compounds with potential applications in the nutritional management and prevention of hyperlipidemia and related cardiometabolic disorders.

Animals↗

PubMed2026

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↗

PubMed2005

Combined target-based and ligand-based drug design approach as a tool to define a novel 3D-pharmacophore model of human A3 adenosine receptor antagonists: pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine derivatives as a key study.

A combined target-based and ligand-based drug design approach has been carried out to define a novel pharmacophore model of the human A(3) receptor antagonists. High throughput molecular docking and comparative molecular field analysis (CoMFA) have been used in tandem to assemble a new target based pharmacophore model. In parallel, to provide more accurate information about the putative binding site of these A(3) inhibitors, a rhodopsin-based model of the human A(3) receptor was built and a novel Y-shape binding motif has been proposed. Docking-based structure superimposition has been used to perform a quantitative study of the structure-activity relationships for binding of these pyrazolo-triazolo-pyrimidines to adenosine A(3) receptor using CoMFA. Both steric and the electrostatic contour plots obtained from the CoMFA analysis nicely fit on the hypothetical binding site obtained by molecular docking. On the basis of the combined hypothesis, we have designed, synthesized, and tested 17 new derivatives. Consistently, the predicted K(i) values were very close to the experimental values.

Adenosine A3 Receptor Antagonists↗

PubMed1998

Flexible ligand docking using conformational ensembles.

Molecular docking algorithms suggest possible structures for molecular complexes. They are used to model biological function and to discover potential ligands. A present challenge for docking algorithms is the treatment of molecular flexibility. Here, the rigid body program, DOCK, is modified to allow it to rapidly fit multiple conformations of ligands. Conformations of a given molecule are pre-calculated in the same frame of reference, so that each conformer shares a common rigid fragment with all other conformations. The ligand conformers are then docked together, as an ensemble, into a receptor binding site. This takes advantage of the redundancy present in differing conformers of the same molecule. The algorithm was tested using three organic ligand protein systems and two protein-protein systems. Both the bound and unbound conformations of the receptors were used. The ligand ensemble method found conformations that resembled those determined in X-ray crystal structures (RMS values typically less than 1.5 A). To test the method's usefulness for inhibitor discovery, multi-compound and multi-conformer databases were screened for compounds known to bind to dihydrofolate reductase and compounds known to bind to thymidylate synthase. In both cases, known inhibitors and substrates were identified in conformations resembling those observed experimentally. The ligand ensemble method was 100-fold faster than docking a single conformation at a time and was able to screen a database of over 34 million conformations from 117,000 molecules in one to four CPU days on a workstation.

Algorithms↗