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PubMed2024

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN. METHODS: We analyzed two DN microarray datasets (GSE96804 and GSE30528) for differentially expressed genes (DEGs) using the Limma package, overlapping them with immune-related genes from ImmPort and InnateDB. LASSO regression, SVM-RFE, and random forest analysis identified four hub genes (EGF, PLTP, RGS2, PTGDS) as proficient predictors of DN. The model achieved an AUC of 0.995 and was validated on GSE142025. Single-cell RNA data (GSE183276) revealed increased hub gene expression in epithelial cells. CIBERSORT analysis showed differences in immune cell proportions between DN patients and controls, with the hub genes correlating positively with neutrophil infiltration. Molecular docking identified potential drugs: cysteamine, eltrombopag, and DMSO. And qPCR and western blot assays were used to confirm the expressions of the four hub genes. RESULTS: Analysis found 95 and 88 distinctively expressed immune genes in the two DN datasets, with 14 consistently differentially expressed immune-related genes. After machine learning algorithms, EGF, PLTP, RGS2, PTGDS were identified as the immune-related hub genes associated with DN. In addition, the mRNA and protein levels of them were obviously elevated in HK-2 cells treated with glucose for 24 h, as well as their mRNA expressions in kidney tissues of mice with DN. CONCLUSION: This study identified 4 hub immune-related genes (EGF, PLTP, RGS2, PTGDS), as well as their expression profiles and the correlation with immune cell infiltration in DN.

Diabetic Nephropathies↗

PubMed2026

In-Silico and Functional Characterization of EcdLp, an ABC Transporter of Aspergillus nidulans NRRL11440.

Echinocandin B (ECB) biosynthesis in Aspergillus nidulans is primarily governed by multiple genes located within the biosynthetic echinocandin (ecd) gene cluster. The contributory functions of many genes, including transcription factors and tailoring enzymes of the ecd gene cluster, have been previously studied. The present study focused on determining the role of transporter proteins, EcdLp, EcdCp, and EcdDp, in ECB efflux using in silico and biochemical approaches. The molecular docking analysis revealed that ECB relatively showed higher binding affinity for EcdLp than the other co-clustered MFS transporters EcdCp and EcdDp, suggesting a preferred substrate of EcdLp. These results were further confirmed by heterologous integration of the ecdL gene in the ABC transporters-deficient Saccharomyces cerevisiae AD1-8u⁻, confirming active efflux. However, the binding of ECB in EcdLp is distinct from the R6G binding, overlapping the promiscuous site of farnesol, resulting in inhibition of R6G efflux in a dose-dependent manner. In conclusion, these results decipher the ECB binding and efflux mechanism and unveil the evolutionarily specialized architecture of EcdLp that permits targeted metabolite export in addition to environmental responsiveness, and lay the groundwork for optimizing ECB production via transporter engineering.

Aspergillus nidulans↗

PubMed2025

Caffeic acid phenethyl ester protects renal tubular epithelial cells against ferroptosis in diabetic kidney disease via restoring PINK1-mediated mitophagy.

Mounting evidence indicates that renal tubular ferroptosis plays a crucial role in the progression of diabetic kidney disease (DKD). Caffeic acid phenethyl ester (CAPE), derived from propolis, a precious resinous substance synthesized by various bee species, has garnered broad attention in biomedical research. This study aims to explore the mechanism by which CAPE protects renal tubular epithelial cells (TECs) against ferroptosis in DKD. DBA/2J mice were administered streptozotocin (STZ) by intraperitoneal injection, fed a high-fat diet (HFD) and treated with CAPE. The findings revealed significant changes in ferroptosis markers. In diabetic mice and TECs under high-glucose (HG) conditions, levels of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) decreased, while transferrin receptor 1 (TFR1) increased. These changes were accompanied by a reduction in antioxidant capability and the accumulation of malondialdehyde (MDA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the intersection targets of CAPE and ferroptosis were mainly located in the mitochondria and exhibited high enrichment values in mitophagy. Further investigations revealed that HG induced a depolarization of mitochondrial membrane potential and an excessive level of mitochondrial reactive oxygen species (ROS), accompanied by defective mitophagy. The administration of CAPE inhibited exacerbated ferroptosis and rescued defective mitophagy induced by DKD. In addition, CAPE restored PTEN-induced putative kinase 1 (PINK1) levels, which were markedly diminished in the kidneys of DKD mice and TECs subjected to HG. Molecular docking simulation experiments suggested that CAPE is steadily bound to the PINK1 active pocket. Cellular Thermal Shift Assay (CETSA) and Drug Affinity Responsive Target Stability assay (DARTS) showed that CAPE enhances the thermal stability of the PINK1 protein within a specific temperature range and protects the PINK1 protein from degradation by proteolytic enzymes. These results confirm that CAPE interacts with PINK1 as its specific target. However, the positive outcomes of CAPE treatment on ferroptosis were nullified by the PINK1 siRNA. This research indicates that CAPE has potential therapeutic benefits for DKD by protecting renal TECs against ferroptosis via rescuing PINK1-mediated mitophagy. These findings suggest that CAPE shows potential as a therapeutic agent to prevent tubular injury in DKD.

Animals↗

PubMed2025

Characterization of blaOXA-542-mediated carbapenem resistance in Acinetobacter baumannii.

BACKGROUND: Carbapenem-resistant Acinetobacter baumannii (CRAB) causes multiple anatomical site infections, representing a significant public health threat. AIM: This study reports the isolation and characterization of a carbapenem-resistant A. baumannii harbouring blaOXA-542, followed by a comprehensive investigation of its antimicrobial resistance mechanisms and genomic characteristics. METHODS: Firstly, antimicrobial susceptibility testing was performed using the broth microdilution method. Subsequently, whole-genome sequencing was employed to identify and characterize the resistance and virulence determinants. The functional validation of resistance mechanisms was performed by gene knockdown and construction of expression vectors. The fitness cost of β-lactamase expression was identified by a bacterial growth kinetic test. Molecular docking was utilized to predict potential binding sites of β-lactamase and carbapenems. Finally, the genetic characteristics of the isolates were analysed through comparative genomics analyses and phylogenetic tree construction. RESULTS AND CONCLUSIONS: The results demonstrated that blaOXA-542 confers resistance to carbapenem and penicillin in A. baumannii and Escherichia coli while exhibiting no significant impact on cephalosporins. The ability of blaOXA-542 to hydrolyze meropenem was further confirmed by modified carbapenem inactivation assay (mCIM). Expression of blaOXA-542 in E. coli BL21 showed no significant growth rate alteration. Comparative analysis of the blaOXA-542 genetic environment revealed a close association with Acinetobacter pitti. This study reports the emergence of blaOXA-542-mediated carbapenem and penicillin resistance in a novel A. baumannii lineage (ST2795Pas/ST3464Oxf), highlighting the urgent need for rational antibiotic use against specific pathogens.

Acinetobacter baumannii↗

PubMed2025

Heme oxygenase 1 (HO-1) is a drug target for reversing cisplatin resistance in non-small cell lung cancer.

INTRODUCTION: Platinum-based drugs, the most widely used chemotherapeutic drugs in clinical oncology, have long faced the problem of drug resistance, which is urgently in need of resolution. Identifying biomarkers of drug resistance may help reduce platinum resistance and improve therapeutic efficacy. OBJECTIVES: This study aims to identify potential biomarkers associated with the development of cisplatin resistance in non-small cell lung cancer (NSCLC) and explore mechanisms to overcome chemoresistance. METHODS: NSCLC cisplatin resistance cell lines were constructed, and transcriptome sequencing was performed. Results were validated using Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Molecular docking, proteomics sequencing, and in vitro and in vivo experiments were conducted to evaluate the role of Heme Oxygenase 1 (HO-1) in cisplatin resistance. RESULTS: NSCLC cisplatin resistance cell lines, GEO and TCGA data identified HMOX1, downstream of Nrf2, as a key drug resistance gene induced by cisplatin. Activation of the Nrf2/HO-1 pathway was found to induce ferroptosis resistance, a critical mechanism of cisplatin resistance. Candidate compounds SB 202190 and Nordihydroguaiaretic acid (NDGA) effectively reactivated ferroptosis by inhibiting HO-1, thereby increasing cisplatin sensitivity. CONCLUSION: The Nrf2/HO-1 pathway is a significant contributor to cisplatin resistance in NSCLC. Targeting HO-1 with SB 202190 and NDGA presents a promising strategy to overcome resistance and improve chemotherapy outcomes.

Cisplatin↗

PubMed2025

Phytocompounds of Honey mesquite (Prosopis glandulosa) and Lodhra (Symplocos racemosa) in the management of COVID-19 associated rheumatoid arthritis (CARA).

COVID-19 persists globally with profound social and economic consequences, and its complex interplay with other diseases makes it a syndemic. Rheumatoid arthritis (RA), a chronic autoimmune disorder, has shown increased incidence during the pandemic, with patients displaying higher susceptibility to COVID-19. This overlap prompted the hypothesis of 'COVID-19-associated rheumatoid arthritis (CARA)'. The present study explores phytocompounds with anti-inflammatory and immunomodulatory properties as potential CARA therapeutics. Compounds from Prosopis glandulosa and Symplocos racemosa, both used in traditional medicine, were evaluated through molecular docking and simulation studies. Six inflammatory targets relevant to RA and COVID-19 -interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), granulocyte-macrophage colony-stimulating factor (GM-CSF), human leukocyte antigen DR4 (HLA-DR4), signal transducer and activator of transcription 4 (STAT4), and peptidyl arginine deiminase 4 (PAD4) were selected. Among the tested ligands, salidroside showed the strongest binding affinity, with energies of - 8.20 kcal/mol (IL-6), - 7.67 kcal/mol (TNF-α), - 8.53 kcal/mol (GM-CSF), - 8.80 kcal/mol (HLA-DR4), - 8.18 kcal/mol (STAT4), and - 7.91 kcal/mol (PAD4), indicating stable interactions. These findings suggest salidroside could modulate key inflammatory pathways and potentially reduce cytokine storms in COVID-19 patients. Existing RA and COVID-19 treatments often cause immunosuppression, increasing vulnerability to opportunistic infections (Datta et al in J Biomol Struct Dyn 41(8):3281-3294, 2022). Immunomodulatory phytocompounds like salidroside may offer safer, targeted alternatives without compromising immune defenses. However, this study is based on in silico analyses, and warrants in vitro and in vivo validation. Nevertheless, present work may represent an important step towards novel therapeutic strategies for COVID-19 Associated Rheumatoid Arthritis (CARA).

COVID-19↗

PubMed2025

Construction and accuracy assessment of an efferocytosis-related prognostic model for ovarian cancer: A diagnostic accuracy study.

The study aimed to investigate the prognostic significance of efferocytosis-related genes in ovarian cancer (OC) with regard to cancer development, progression, invasion, and metastasis. OC cohorts were assembled from bioinformatics repositories. Utilizing consensus clustering analysis, distinct clusters were delineated based on the intersection of OC-related genes and efferocytosis-related genes. A prognostic signature specific to efferocytosis in OC was developed using data from The Cancer Genome Atlas, validated against the gene expression omnibus database, and subjected to independent prognostic analysis. Subsequently, a nomogram model was formulated. Moreover, investigations encompassed the immune microenvironment, immunotherapy, mutation profiling, drug sensitivity assessments, drug prediction models, and molecular docking analyses. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to ascertain the mRNA expression levels of key genes. Five key genes, FCGBP, BTN3A3, WDR91, SLC25A45, and BTNL3, were identified as significantly associated with OC. Both datasets and qRT-PCR demonstrated elevated expression levels of FCGBP and WDR91 in OC. Notably, AFLATOXIN B1 exhibited strong binding affinity to SLC25A45, ciclopirox to BTN3A3, and irinotecan to WDR91. The risk score, age, and stage were identified as independent prognostic factors, with the nomogram displaying efficacy in predicting OC patient survival. Variations in the immune cell infiltration profiles, including naive B cells, and expression levels of 6 immune checkpoint genes, such as CTLA4, were notable. High tumor mutation burden scores were associated with improved survival outcomes. Additionally, significant differences in the IC50 values of 123 anticancer drugs were observed between the 2 risk groups. This findings of this study highlight the efficacy of the efferocytosis-associated risk model in predicting the survival outcomes of OC patients, thus providing a novel reference for prognostic prediction in OC patients.

Humans↗

PubMed2026

Effects and mechanisms of Stauntonia brachyanthera Hand.-Mazz against Alzheimer's disease through network pharmacology and experimental validation.

Stauntonia brachyanthera Hand.-Mazz. (SB), a traditional medicinal plant of the Dong ethnic group with nutraceutical applications, exhibits broad-spectrum pharmacological activity. However, the therapeutic effects and mechanisms of SB on Alzheimer's disease (AD) remain unclear. This study aims to investigate the neuroprotective potential and underlying mechanisms of SB against AD. We utilized network pharmacology and molecular docking to predict the active components, targets, and pathways of SB associated with AD treatment. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were further used to identify potential therapeutic targets and underlying mechanisms of SB in relation to AD. Then, the neuroprotective effects, neuronal differentiation-promoting activity and potential mechanism of key active components of SB on the main therapeutic targets were verified by in vitro experiments. The network pharmacological prediction results showed that the treatment of AD with SB was closely related to MAPK and PI3K/Akt pathways. Further experiments showed that the SB active component kaempferol (KMF) alleviated Aβ1-42-induced injury and promoted neuronal differentiation. Additionally, we found that KMF-mediated promotion of neuronal differentiation in N2a cells was dependent on the PI3K/Akt and MAPK pathways. In this study, we employed a combined computational-experimental approach to elucidate the neuroprotective mechanisms of SB against Alzheimer's disease. We further validated KMF as a key active component of SB that alleviates Aβ1-42-induced injury and promotes neuronal differentiation through the PI3K/Akt and MAPK pathways.

Alzheimer's disease↗

PubMed2016

Characterization of Class III Peroxidases from Switchgrass.

Class III peroxidases (CIIIPRX) catalyze the oxidation of monolignols, generate radicals, and ultimately lead to the formation of lignin. In general, CIIIPRX genes encode a large number of isozymes with ranges of in vitro substrate specificities. In order to elucidate the mode of substrate specificity of these enzymes, we characterized one of the CIIIPRXs (PviPRX9) from switchgrass (Panicum virgatum), a strategic plant for second-generation biofuels. The crystal structure, kinetic experiments, molecular docking, as well as expression patterns of PviPRX9 across multiple tissues and treatments, along with its levels of coexpression with the majority of genes in the monolignol biosynthesis pathway, revealed the function of PviPRX9 in lignification. Significantly, our study suggested that PviPRX9 has the ability to oxidize a broad range of phenylpropanoids with rather similar efficiencies, which reflects its role in the fortification of cell walls during normal growth and root development and in response to insect feeding. Based on the observed interactions of phenylpropanoids in the active site and analysis of kinetics, a catalytic mechanism involving two water molecules and residues histidine-42, arginine-38, and serine-71 was proposed. In addition, proline-138 and gluntamine-140 at the 137P-X-P-X140 motif, leucine-66, proline-67, and asparagine-176 may account for the broad substrate specificity of PviPRX9. Taken together, these observations shed new light on the function and catalysis of PviPRX9 and potentially benefit efforts to improve biomass conservation properties in bioenergy and forage crops.

Amino Acid Sequence↗

PubMed2005

Molecular mechanics PBSA ligand binding energy and interaction of Efavirenz derivatives with HIV-1 reverse transcriptase.

In order to evaluate the properties of several HIV-1 reverse transcripase(RT) inhibitors, Efavirenz (SUSTIVA) and a set of its derivatives (benzoxazinones) have been placed into the nonnucleoside analogue binding site of the enzyme by molecular docking. The resulting geometries were used for a molecular dynamics simulation and binding energy calculations. The enzyme-inhibitor binding energies were estimated from experimental inhibitory activities (IC90). The correlation of the predicted and experimental binding energies were satisfactory acceptable as indicated by r2 = 0.865. Based on MD simulations, the obtained results indicate that the tight association of the ligand to the HIV-1 RT binding pocket was based on hydrogen bonding between Efavirenz's N1 and the oxygen of the backbone of Lys 101, with an estimated average distance of 1.88 A. Moreover, electrostatic interaction was mainly contributed by two amino acid residues in the binding site; Lys 101 and His 235. MD simulations open the possibility to study the reaction of the flexible enzyme to those substances as well as the overall affinity.

Adipates↗

PubMed2004

Simulation of the interaction between ScyTx and small conductance calcium-activated potassium channel by docking and MM-PBSA.

Computational methods are employed to simulate interaction of scorpion toxin ScyTx in complex with the small conductance calcium-activated potassium channel rsk2. All of available 25 structures of ScyTx in the Protein Data Bank determined by NMR were considered for improving performance of rigid protein docking of ZDOCK. Four main binding modes were found among a large number of predicted complexes by using clustering analysis, screening with expert knowledge, energy minimization, and molecular dynamics simulations. The quality and validity of the resulting complexes were further evaluated by molecular dynamics simulations with the generalized Born solvation model and by calculation of relative binding free energies with the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) in the AMBER 7 suit of programs. The complex formed by the 22nd structure of the ScyTx and rsk2 channel was identified as the most favorable complex by using a combination of computational methods, which contain further introduction of flexibility without restraining residue side chain. From the resulted spatial structure of the ScyTx and rsk2 channel, ScyTx associates the mouth of the rsk2 channel with alpha-helix rather than beta-sheet. Structural analysis first revealed that Arg(13) played a novel and vital role of blocking the pore of the rsk2 channel, whose role is remarkably different from that of highly homologous scorpion toxin P05. Between the interfaces in the ScyTx-rsk2 complex, strong electrostatic interaction and hydrogen bonds exist between Arg(13) of ScyTx and Gly-Tyr-Gly-Asp sequential residues located in the four symmetrical chains of the pore region. Simultaneously, five hydrogen bonds between Arg(6) of ScyTx and Asp(341)(C), Val(366)(C), and Pro(367)(C), and electrostatic interaction between Arg(6) of ScyTx and Asp(364)(B) and Asp(341)(C) are also found by structural analysis. In addition, His(31) located at the C-terminal of ScyTx is surrounded by Val(342)(A), Asp(364)(A), Met(365)(A), Pro(367)(B), and Asn(366)(B) within a contact distance of 4.0 A. These simulation results are in good agreement with experimental data and can effectively explain the binding phenomena between ScyTx and the potassium channel at the level of molecular spatial structure. The consistency between results of molecular modeling and experimental data strongly suggests that our spatial structure model of the ScyTx-rsk2 complex is reasonable. Therefore, molecular docking combined with molecular dynamics simulations followed by molecular mechanics Poisson-Boltzmann surface area analysis is an attractive approach for modeling scorpion toxin-potassium channel complexes a priori for further biological studies.

Animals↗

PubMed1995

An automated computer vision and robotics-based technique for 3-D flexible biomolecular docking and matching.

The generation of binding modes between two molecules, also known as molecular docking, is a key problem in rational drug design and biomolecular recognition. Docking a ligand, e.g., a drug molecule or a protein molecule, to a protein receptor, involves recognition of molecular surfaces as molecules interact at their surface. Recent studies report that the activity of many molecules induces conformational transitions by 'hinge-bending', which involves movements of relatively rigid parts with respect to each other. In ligand-receptor binding, relative rotational movements of molecular substructures about their common hinges have been observed. For automatically predicting flexible molecular interactions, we adapt a new technique developed in Computer Vision and Robotics for the efficient recognition of partially occluded articulated objects. These type of objects consist of rigid parts which are connected by rotary joints (hinges). Our approach is based on an extension and generalization of the Geometric Hashing and Generalized Hough Transform paradigm for rigid object recognition. Unlike other techniques which match each part individually, our approach exploits forcefully and efficiently enough the fact that the different rigid parts do belong to the same flexible molecule. We show experimental results obtained by an implementation of the algorithm for rigid and flexible docking. While the 'correct', crystal-bound complex is obtained with a small RMSD, additional, predictive 'high scoring' binding modes are generated as well. The diverse applications and implications of this general, powerful tool are discussed.

Algorithms↗

PubMed2003

Comparative study of several algorithms for flexible ligand docking.

We have performed a comparative assessment of several programs for flexible molecular docking: DOCK 4.0, FlexX 1.8, AutoDock 3.0, GOLD 1.2 and ICM 2.8. This was accomplished using two different studies: docking experiments on a data set of 37 protein-ligand complexes and screening a library containing 10,037 entries against 11 different proteins. The docking accuracy of the methods was judged based on the corresponding rank-one solutions. We have found that the fraction of molecules docked with acceptable accuracy is 0.47, 0.31, 0.35, 0.52 and 0.93 for, respectively, AutoDock, DOCK, FlexX, GOLD and ICM. Thus ICM provided the highest accuracy in ligand docking against these receptors. The results from the other programs are found to be less accurate and of approximately the same quality. A speed comparison demonstrated that FlexX was the fastest and AutoDock was the slowest among the tested docking programs. The database screening was performed using DOCK, FlexX and ICM. ICM was able to identify the original ligands within the top 1% of the total library in 17 cases. The corresponding number for DOCK and FlexX was 7 and 8, respectively. We have estimated that in virtual database screening, 50% of the potentially active compounds will be found among approximately 1.5% of the top scoring solutions found with ICM and among approximately 9% of the top scoring solutions produced by DOCK and FlexX.

Algorithms↗

PubMed2006

Docking studies of nickel-peptide deformylase (PDF) inhibitors: exploring the new binding pockets.

The binding modes of a series of known activity inhibitors docking to Peptide deformylase (PDF) have been studied using molecular docking software AutoDock3.0.5. In this study, good correlation (R(2)=0.894) between calculated binding energies and experimental inhibitory activities is obtained. We find that some shallow pockets near the known active pocket are very important which can accommodate the side-chains of the inhibitor. Moreover, a new binding pocket is also explored. All these may provide something useful for designing the potent inhibitors.

Amidohydrolases↗

PubMed2006

Docking of secretory vesicles is syntaxin dependent.

Secretory vesicles dock at the plasma membrane before they undergo fusion. Molecular docking mechanisms are poorly defined but believed to be independent of SNARE proteins. Here, we challenged this hypothesis by acute deletion of the target SNARE, syntaxin, in vertebrate neurons and neuroendocrine cells. Deletion resulted in fusion arrest in both systems. No docking defects were observed in synapses, in line with previous observations. However, a drastic reduction in morphologically docked secretory vesicles was observed in chromaffin cells. Syntaxin-deficient chromaffin cells showed a small reduction in total and plasma membrane staining for the docking factor Munc18-1, which appears insufficient to explain the drastic reduction in docking. The sub-membrane cortical actin network was unaffected by syntaxin deletion. These observations expose a docking role for syntaxin in the neuroendocrine system. Additional layers of regulation may have evolved to make syntaxin redundant for docking in highly specialized systems like synaptic active zones.

Animals↗

PubMed2007

Complementarity of hydrophobic properties in ATP-protein binding: a new criterion to rank docking solutions.

ATP is an important substrate of numerous biochemical reactions in living cells. Molecular recognition of this ligand by proteins is very important for understanding enzymatic mechanisms. Considerable insight into the problem may be gained via molecular docking simulations. At the same time, standard docking protocols are often insufficient to predict correct conformations for protein-ATP complexes. Thus, in most cases the native-like solutions can be found among the docking poses, but current scoring functions have only limited ability to discriminate them from false positives. To improve the selection of correct docking solutions obtained with the GOLD software, we developed a new ranking criterion specific for ATP-protein binding. The method is based on detailed analysis of the intermolecular interactions in 40 high-resolution 3D structures of ATP-protein complexes (the training set). We found that the most important factors governing this recognition are hydrogen-bonding, stacking between adenine and aromatic protein residues, and hydrophobic contacts between adenine and protein residues. To address the latter, we applied the formalism of 3D molecular hydrophobicity potential. The results obtained were used to construct an ATP-oriented scoring criterion as a linear combination of the terms describing these intermolecular interactions. The criterion was then validated using the test set of 10 additional ATP-protein complexes. As compared with the standard scoring functions, the new ranking criterion significantly improved the selection of correct docking solutions in both sets and allowed considerable enrichment at the top of the list containing docking poses with correct solutions.

Adenine↗

PubMed2005

Hierarchical docking of databases of multiple ligand conformations.

Ligand flexibility is an important problem in molecular docking and virtual screening. To address this challenge, we investigate a hierarchical pre-organization of multiple conformations of small molecules. Such organization of pre-calculated conformations removes the exploration of ligand conformational space from the docking calculation and allows for concise representation of what can be thousands of conformations. The hierarchy also recognizes and prunes incompatible conformations early in the calculation, eliminating redundant calculations of fit. We investigate the method by docking the MDL Drug Data Report (MDDR), an annotated database of 100,000 molecules, into apo and holo forms of seven unrelated targets. This annotated database allows us to track the ranking of tens to hundreds of annotated ligands in each of the docking systems. The binding sites and database are prepared in an automated fashion in an attempt to remove some human bias from the calculations. Many thousands of explicit and implicit ligand conformations may be docked in calculations not much longer than required for single conformer docking. As long as internal energies are not considered, recombination with the hierarchy is additive as the number of degrees of freedom is increased. Molecules with even millions of conformations can be docked in a few minutes on a single desktop computer.

Computer Simulation↗

PubMed1997

Multiple automatic base selection: protein-ligand docking based on incremental construction without manual intervention.

A possible way of tackling the molecular docking problem arising in computer-aided drug design is the use of the incremental construction method. This method consists of three steps: the selection of a part of a molecule, a so-called base fragment, the placement of the base fragment into the active site of a protein, and the subsequent reconstruction of the complete drug molecule. Assuming that a part of a drug molecule is known, which is specific enough to be a good base fragment, the method is proven to be successful for a large set of docking examples. In addition, it leads to the fastest algorithms for flexible docking published so far. In most real-world applications of docking, large sets of ligands have to be tested for affinity to a given protein. Thus, manual selection of a base fragment is not practical. On the other hand, the selection of a base fragment is critical in that only few selections lead to a low-energy structure. We overcome this limitation by selecting a representative set of base fragments instead of a single one. In this paper, we present a set of rules and algorithms to automate this selection. In addition, we extend the incremental construction method to deal with multiple fragmentations of the drug molecule. Our results show that with multiple automated base selection, the quality of the docking predictions is almost as good as with one manually preselected base fragment. In addition, the set of solutions is more diverse and alternative binding modes with low scores are found. Although the run time of the overall algorithm increases, the method remains fast enough to search through large ligand data sets.

Automation↗