Virtual screening applications in short-chain dehydrogenase/reductase research

In silico and in vitro assessment of drugs potentially causing adverse effects by inhibiting CYP17A1

Cytochrome P450 enzymes (CYPs) play a crucial role in the metabolism and synthesis of various compound classes. While drug-metabolizing CYP enzymes are frequently investigated as anti-targets, the inhibition of CYP enzymes involved in adrenal steroidogenesis is not well studied. The steroidogenic enzyme CYP17A1 is a dual-function enzyme catalyzing hydroxylase and lyase reactions relevant for the biosynthesis of adrenal glucocorticoids and androgens. Inhibition of CYP17A1-hydroxylase leads to pseudohyperaldosteronism with subsequent excessive mineralocorticoid receptor activation, hypertension and hypokalemia. In contrast, specific inhibition of the lyase function might be beneficial for the treatment of prostate cancer by decreasing adrenal androgen levels. This study combined in silico and in vitro methods to identify drugs inhibiting CYP17A1. The most potent CYP17A1 inhibitors identified are serdemetan, mocetinostat, nolatrexed, liarozole, and talarozole. While some of these drugs are currently under investigation for the treatment of various cancers, their potential for the treatment of prostate cancer is yet to be explored. The DrugBank database was screened for CYP17A1 inhibitors, to increase the awareness for the risk of drug-induced pseudohyperaldosteronism and to highlight drugs so far unknown for their potential to cause side effects resulting from CYP17A1 inhibition.

Screening androgen receptor agonists of fish species using machine learning and molecular model in NORMAN water-relevant list

Androgen receptor (AR) agonists have strong endocrine disrupting effects in fish. Most studies mainly investigate AR binding capacity using human AR in vitro. However, there is still few methods to rapidly predict AR agonists in aquatic organisms. This study aimed to screen AR agonists of fish species using machine learning and molecular models in water-relevant list from NORMAN, a network of reference laboratories for monitoring contaminants of emerging concern in the environment. In this study, machine learning approaches (e.g., Deep Forest (DF)), Random Forests and artificial neural networks) were applied to predict AR agonists. Zebrafish, fathead minnow, mosquitofish, medaka fish and grass carp are all important aquatic model organisms widely used to evaluate the toxicity of new pollutants, and the molecular models of ARs from these five fish species were constructed to further screen AR agonists using AlphaFold2. The DF method showed the best performances with 0.99 accuracy, 0.97 sensitivity and 1 precision. The Asn705, Gln711, Arg752, and Thr877 residues in human AR and the corresponding sites in ARs from the five fish species were responsible for agonist binding. Overall, 245 substances were predicted as suspect AR agonists in the five fish species, including, certain glucocorticoids, cholesterol metabolites, and cardiovascular drugs in the NORMAN list. Using machine learning and molecular modeling hybrid methods rapidly and accurately screened AR agonists in fish species, and helping evaluate their ecological risk in fish populations.

In silico characterization of the novel SDR42E1 as a potential vitamin D modulator

The short-chain dehydrogenase/reductase (SDR) superfamily encompasses enzymes that play essential roles in the metabolism of steroid hormones and lipids. Despite an enigmatic function, recent genetic studies have linked the novel SDR 42 extended-1 (SDR42E1) gene to 25-hydroxyvitamin D levels. This study investigated the potential SDR42E1 functions and interactions with vitamin D using bioinformatics and molecular docking studies. Phylogenetic analysis unveiled that the nucleotide sequences of human SDR42E1 exhibit high evolutionary conservation across nematodes and fruit flies. Molecular docking analysis identified strong binding affinities between SDR42E1 and its orthologs with vitamin D3 and essential precursors, 8-dehydrocholesterol, followed by 7-dehydrocholesterol and 25-hydroxyvitamin D. The hydrophobic interactions observed between the protein residues and vitamin D compounds supported the predicted transmembrane localization of SDR42E1. Our investigation provides valuable insights into the potential role of SDR42E1 in skin vitamin D biosynthesis throughout species. This provides the foundation for future research and development of targeted therapies for vitamin D deficiency and related health conditions.

Deciphering the structure of a multi-drug resistant Acinetobacter baumannii short-chain dehydrogenase reductase

The rapidly increasing threat of multi-drug-resistant Acinetobacter baumannii infections globally, encompassing a range of clinical manifestations from skin and soft tissue infections to life-threatening conditions like meningitis and pneumonia, underscores an urgent need for novel therapeutic strategies. These infections, prevalent in both hospital and community settings, present a formidable challenge to the healthcare system due to the bacterium's widespread nature and dwindling effective treatment options. Against this backdrop, the exploration of bacterial short-chain dehydrogenase reductases (SDRs) emerges as a promising avenue. These enzymes play pivotal roles in various critical bacterial processes, including fatty acid synthesis, homeostasis, metabolism, and contributing to drug resistance mechanisms. In this study, we present the first examination of the X-ray crystallographic structure of an uncharacterized SDR enzyme from A. baumannii. The tertiary structure of this SDR is distinguished by a central parallel β-sheet, consisting of seven strands, which is flanked by eight α-helices. This configuration exhibits structural parallels with other enzymes in the SDR family, underscoring a conserved architectural theme within this enzyme class. Despite the current ambiguity regarding the enzyme's natural substrate, the importance of many SDR enzymes as targets in anti-bacterial agent design is well-established. Therefore, the detailed structural insights provided in this study open new pathways for the in-silico design of therapeutic agents. By offering a structural blueprint, our findings may provide a platform for future research aimed at developing targeted treatments against this and other multi-drug-resistant infections.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

Expression, Purification, and Bioinformatic Prediction of Mycobacterium tuberculosis Rv0439c as a Potential NADP+-Retinol Dehydrogenase

Although the genome of Mycobacterium tuberculosis (Mtb) H37Rv, the causative agent of tuberculosis, has been repeatedly annotated and updated, a range of proteins from this human pathogen have unknown functions. Mtb Rv0439c, a member of the short-chain dehydrogenase/reductases superfamily, has yet to be cloned and characterized, and its function remains unclear. In this work, we present for the first time the optimized expression and purification of this enzyme, as well as bioinformatic analysis to unveil its potential coenzyme and substrate. Optimized expression in Escherichia coli yielded soluble Rv0439c, while certain tag fusions resulted in insolubility. Sequence and docking analyses strongly suggested that Rv0439c has a clear preference for NADP+, with Arg53 being a key residue that confers coenzyme specificity. Furthermore, functional prediction using CLEAN and DEEPre servers suggested that this protein is a potential NADP+-retinol dehydrogenase (EC No. 1.1.1.300) in retinol metabolism, and this was supported by a BLASTp search and docking studies. Collectively, our findings provide a solid basis for future functional characterization and structural studies of Rv0439c, which will contribute to enhanced understanding of Mtb biology.

Assessment of the inhibitory potential of anabolic steroids towards human AKR1D1 by computational methods and in vitro evaluation

Exposure to xenobiotics can adversely affect biochemical reactions, including hepatic bile acid synthesis. Bile acids are essential for dissolving lipophilic compounds in the hydrophilic environment of the gastrointestinal tract. The critical micellar concentration of bile acids depends on the Δ4-reduction stereochemistry, with the 3-oxo-5β-steroid-Δ4-dehydrogenase (AKR1D1) introducing the cis ring A/B conformation. Loss-of-function mutations in AKR1D1 cause hepatic cholestasis, which, if left untreated can progress into steatosis and liver cirrhosis. Furthermore, AKR1D1 is involved in clearing steroids with an A-ring Δ4-double bond. Here, we tested whether anabolic-androgenic steroids (AAS), often taken off-label at high doses, might inhibit AKR1D1, thereby potentially causing hepatotoxicity. A computational molecular model was established and used for virtual screening of the DrugBank database consisting of 2740 molecules, yielding mainly steroidal hits. Fourteen AAS were selected for in vitro evaluation, as such compounds can reach high hepatic concentrations in an abuse situation. Nandrolone, clostebol, methasterone, drostanolone, and methenolone inhibited to various extent the AKR1D1-mediated reduction of testosterone. Molecular modeling suggests that 9 out of 14 investigated AAS are competitive inhibitors. Moreover quantum mechanical calculations show that nadrolone and clostebol are substrates of AKR1D1 with different activation energy barriers for the hydrogen transfer from cofactor to the C5 position affecting their turnover. In this multidisciplinary approach, we established a molecular model of AKR1D1, identified several AAS as inhibitors, and described their binding mode. This approach may be applied to study other classes of inhibitors including non-steroidal compounds.

Theoretical and Experimental Studies on Plant Light-Dependent Protochlorophyllide Oxidoreductase as a Novel Target for Searching Potential Herbicides

Herbicide resistance is a prevalent problem that has posed a foremost challenge to crop production worldwide. Light-dependent enzyme NADPH: protochlorophyllide oxidoreductase (LPOR) in plants is a metabolic target that could satisfy this unmet demand. Herein, for the first time, we embarked on proposing a new mode of action of herbicides by performing structure-based virtual screening targeting multiple LPOR binding sites, with the determination of further bioactivity on the lead series. The feasibility of exploiting high selectivity and safety herbicides targeting LPOR was discussed from the perspective of the origin and phylogeny. Besides, we revealed the structural rearrangement and the selection key for NADPH cofactor binding to LPOR. Based on these, multitarget virtual screening was performed and the result identified compounds 2 affording micromolar inhibition, in which the IC₅₀ reached 4.74 μM. Transcriptome analysis revealed that compound 2 induced more genes related to chlorophyll synthesis in Arabidopsis thaliana, especially the LPOR genes. Additionally, we clarified that these compounds binding to the site enhanced the overall stability and local rigidity of the complex systems from molecular dynamics simulation. This study delivers a guideline on how to assess activity-determining features of inhibitors to LPOR and how to translate this knowledge into the design of novel and effective inhibitors against malignant weed that act by targeting LPOR.

Characterization of 17β-estradiol-degrading enzyme from Microbacterium sp. MZT7 and its function on E2 biodegradation in wastewater

BACKGROUND

17β-estradiol (E2) residues exhibit harmful effects both for human and animals and have got global attention of the scientific community. Microbial enzymes are considered as one of the effective strategies having great potential for removal E2 residues from the environment. However, limited literature is available on the removal of E2 from wastewater using short-chain dehydrogenase.

RESULTS

In this study, 17β-estradiol degrading enzyme (17β-HSD-0095) was expressed and purified from Microbacterium sp. MZT7. The optimal pH and temperature for reaction was 7 and 40 °C, respectively. Molecular docking studies have shown that the ARG215 residue form a hydrogen bond with oxygen atom of the substrate E2. Likewise, the point mutation results have revealed that the ARG215 residue play an important role in the E2 degradation by 17β-HSD-0095. In addition, 17β-HSD-0095 could remediate E2 contamination in synthetic livestock wastewater.

CONCLUSIONS

These findings offer some fresh perspectives on the molecular process of E2 degradation and the creation of enzyme preparations that can degrade E2.

Short-chain dehydrogenases in Haemonchus contortus: changes during life cycle and in relation to drug-resistance

Short-chain dehydrogenases/reductases (SDRs) regulate the activities of many hormones and other signaling molecules and participate in the deactivation of various carbonyl-bearing xenobiotics. Nevertheless, knowledge about these important enzymes in helminths remains limited. The aim of our study was to characterize the SDR superfamily in the parasitic nematode Haemonchus contortus. Genome localization of SDRs was explored, and phylogenetic analysis in comparison with SDRs from free-living nematode Caenorhabditis elegans and the domestic sheep (Ovis aries, a typical host of H. contortus) was constructed. The expression profile of selected SDRs during the life cycle along with differences between the drug-susceptible and drug-resistant strains, were also studied. Genome sequencing enabled the identification of 46 members of the SDR family in H. contortus. A number of genes have no orthologue in the sheep genome. In all developmental stages of H. contortus, SDR1, SDR3, SDR5, SDR6, SDR14, and SDR18 genes were the most expressed, although in individual stages, huge differences in expression levels were observed. A comparison of SDRs expression between the drug-susceptible and drug-resistant strains of H. contortus revealed several SDRs with changed expression in the resistant strain. Specifically, SDR1, SDR12, SDR13, SDR16 are SDR candidates related to drug-resistance, as the expression of these SDRs is consistently increased in most stages of the drug-resistant H. contortus. These findings revealing several SDR enzymes of H. contortus warrant further investigation.

Flavonoid Production: Current Trends in Plant Metabolic Engineering and De Novo Microbial Production

Flavonoids are secondary metabolites that represent a heterogeneous family of plant polyphenolic compounds. Recent research has determined that the health benefits of fruits and vegetables, as well as the therapeutic potential of medicinal plants, are based on the presence of various bioactive natural products, including a high proportion of flavonoids. With current trends in plant metabolite research, flavonoids have become the center of attention due to their significant bioactivity associated with anti-cancer, antioxidant, anti-inflammatory, and anti-microbial activities. However, the use of traditional approaches, widely associated with the production of flavonoids, including plant extraction and chemical synthesis, has not been able to establish a scalable route for large-scale production on an industrial level. The renovation of biosynthetic pathways in plants and industrially significant microbes using advanced genetic engineering tools offers substantial promise for the exploration and scalable production of flavonoids. Recently, the co-culture engineering approach has emerged to prevail over the constraints and limitations of the conventional monoculture approach by harnessing the power of two or more strains of engineered microbes to reconstruct the target biosynthetic pathway. In this review, current perspectives on the biosynthesis and metabolic engineering of flavonoids in plants have been summarized. Special emphasis is placed on the most recent developments in the microbial production of major classes of flavonoids. Finally, we describe the recent achievements in genetic engineering for the combinatorial biosynthesis of flavonoids by reconstructing synthesis pathways in microorganisms via a co-culture strategy to obtain high amounts of specific bioactive compounds.

The 3-Oxoacyl-(Acyl-Carrier-Protein) Reductase HSD-X1 of Pseudomonas Citronellolis SJTE-3 Catalyzes the Conversion of 17β-estradiol to Estrone

BACKGROUND

Pseudomonas citronellolis SJTE-3 can efficiently degrade 17β-estradiol (E2) and other estrogenic chemicals. However, the enzyme responsible for E2 metabolism within strain SJTE-3 has remained unidentified.

OBJECTIVE

Here, a novel 3-oxoacyl-(acyl-carrier protein) (ACP) reductase, HSD-X1 (WP_ 009617962.1), was identified in SJTE-3 and its enzymatic characteristics for the transformation of E2 were investigated.

METHODS

Multiple sequence alignment and homology modelling were used to predict the protein structure of HSD-X1. The concentrations of different steroids in the culture of recombinant strains expressing HSD-X1 were determined by high performance liquid chromatography. Additionally, the transcription of hsd-x1 gene was investigated using reverse transcription and quantitative PCR analysis. Heterologous expression and affinity purification were used to obtain recombinant HSD- X1.

RESULTS

The transcription of hsd-x1 gene in P. citronellolis SJTE-3 was induced by E2. Multiple sequence alignment (MSA) indicated that HSD-X1 contained the two consensus regions and conserved residues of short-chain dehydrogenase/reductases (SDRs) and 17β-hydroxysteroid dehydrogenases (17β-HSDs). Over-expression of hsd-x1 gene allowed the recombinant strain to degrade E2. Recombinant HSD-X1 was purified with a yield of 22.15 mg/L and used NAD+ as its cofactor to catalyze the oxidization of E2 into estrone (E1) while exhibiting a K_m value of 0.025 ± 0.044 mM and a V_max value of 4.92 ± 0.31 mM/min/mg. HSD-X1 could tolerate a wide range of temperature and pH, while the presence of divalent ions exerted little influence on its activity. Further, the transformation efficiency of E2 into E1 was over 98.03% across 15 min.

CONCLUSION

Protein HSD-X1 efficiently catalyzed the oxidization of E2 and participated in estrogen degradation by P. citronellolis SJTE-3.

Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries

To attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.

With Chitosan and PLGA as the Delivery Vehicle, Toxoplasma gondii Oxidoreductase-Based DNA Vaccines Decrease Parasite Burdens in Mice

Toxoplasma gondii (T. gondii) is an intracellular parasitic protozoan that can cause serious public health problems. However, there is no effectively preventive or therapeutic strategy available for human and animals. In the present study, we developed a DNA vaccine encoding T. gondii oxidoreductase from short-chain dehydrogenase/reductase family (TgSDRO-pVAX1) and then entrapped in chitosan and poly lactic-co-glycolic acid (PLGA) to improve the efficacy. When encapsulated in chitosan (TgSDRO-pVAX1/CS nanospheres) and PLGA (TgSDRO-pVAX1/PLGA nanospheres), adequate plasmids were loaded and released stably. Before animal immunizations, the DNA vaccine was transfected into HEK 293-T cells and examined by western blotting and laser confocal microscopy. Th1/Th2 cellular and humoral immunity was induced in immunized mice, accompanied by modulated secretion of antibodies and cytokines, promoted the maturation and MHC expression of dendritic cells, and enhanced the percentages of CD4+ and CD8+ T lymphocytes. Immunization with TgSDRO-pVAX1/CS and TgSDRO-pVAX1/PLGA nanospheres conferred significant immunity with lower parasite burden in the mice model of acute toxoplasmosis. Furthermore, our results also lent credit to the idea that TgSDRO-pVAX1/CS and TgSDRO-pVAX1/PLGA nanospheres are substitutes for each other. In general, the current study proposed that TgSDRO-pVAX1 with chitosan or PLGA as the delivery vehicle is a promising vaccine candidate against acute toxoplasmosis.

Characterization of an efficient estrogen-degrading bacterium Stenotrophomonas maltophilia SJTH1 in saline-, alkaline-, heavy metal-contained environments or solid soil and identification of four 17β-estradiol-oxidizing dehydrogenases

The efficient bioremediation of estrogen contamination in complex environments is of great concern. Here the strain Stenotrophomonas maltophilia SJTH1 was found with great and stable estrogen-degradation efficiency even under stress environments. The strain could utilize 17β-estradiol (E2) as a carbon source and degrade 90% of 10 mg/L E2 in a week; estrone (E1) was the first degrading intermediate of E2. Notably, diverse pH conditions (3.0-11.0) and supplements of 4% salinity, 6.25 mg/L of heavy metal (Cd²⁺ or Cu²⁺), or 1 CMC of surfactant (Tween 80/ Triton X-100) had little effect on its cell growth and estrogen degradation. The addition of low concentrations of copper and Tween 80 even promoted its E2 degradation. Bioaugmentation of strain SJTH1 into solid clay soil achieved over 80% removal of E2 contamination (10 mg/kg) within two weeks. Further, the whole genome sequence of S. maltophilia SJTH1 was obtained, and a series of potential genes participating in stress-tolerance and estrogen-degradation were predicted. Four dehydrogenases similar to 17β-hydroxysteroid dehydrogenases (17β-HSDs) were found to be induced by E2, and the four heterogenous-expressed enzymes could oxidize E2 into E1 efficiently. This work could promote bioremediation appliance potential with microorganisms and biodegradation mechanism study of estrogens in complex real environments.

Characterization of an 17β-estradiol-degrading bacterium Stenotrophomonas maltophilia SJTL3 tolerant to adverse environmental factors

Bioremediation of environmental estrogens requires microorganisms with stable degradation efficiency and great stress tolerance in complex environments. In this work, Stenotrophomonas maltophilia SJTL3 isolated from wastewater was found to be able to degrade over 90% of 10 μg/mL 17β-estradiol (E2) in a week and the degradation dynamic was fitted by the first-order kinetic equations. Estrone was the first and major intermediate of E2 biodegradation. Strain SJTL3 exhibited strong tolerance to several adverse conditions like extreme pH (3.0-11.0), high osmolality (2%), co-existing heavy metals (6.25 μg/mL of Cu²⁺) and surfactants (5 CMC of Tween 80), and retained normal cell vitality and stable E2-degradaing efficiency. In solid soil, strain SJTL3 could remove nearly 100% of 1 μg/mL of E2 after the bacteria inoculation and 8-day culture. As to the contamination of 10 μg/mL E2 in soil, the biodegradation efficiency was about 90%. The further obtainment of the whole genome of strain SJTL3 and genome analysis revealed that this strain contained not only the potential genes responsible for estrogen degradation, but also the genes encoding proteins involved in stress tolerance. This work could promote the estrogen-biodegrading mechanism study and provide insights into the bioremediation application.

Identification of the fungicide epoxiconazole by virtual screening and biological assessment as inhibitor of human 11β-hydroxylase and aldosterone synthase

Humans are constantly exposed to a multitude of environmental chemicals that may disturb endocrine functions. It is crucial to identify such chemicals and uncover their mode-of-action to avoid adverse health effects. 11β-hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) catalyze the formation of cortisol and aldosterone, respectively, in the adrenal cortex. Disruption of their synthesis by exogenous chemicals can contribute to cardio-metabolic diseases, chronic kidney disease, osteoporosis, and immune-related disorders. This study applied in silico screening and in vitro evaluation for the discovery of xenobiotics inhibiting CYP11B1 and CYP11B2. Several databases comprising environmentally relevant pollutants, chemicals in body care products, food additives and drugs were virtually screened using CYP11B1 and CYP11B2 pharmacophore models. A first round of biological testing used hamster cells overexpressing human CYP11B1 or CYP11B2 to analyze 25 selected virtual hits. Three compounds inhibited CYP11B1 and CYP11B2 with IC50 values below 3 μM. The most potent inhibitor was epoxiconazole (IC50 value of 623 nM for CYP11B1 and 113 nM for CYP11B2, respectively); flurprimidol and ancymidol were moderate inhibitors. In a second round, these three compounds were tested in human adrenal H295R cells endogenously expressing CYP11B1 and CYP11B2, confirming the potent inhibition by epoxiconazole and the more moderate effects by flurprimidol and ancymidol. Thus, the in silico screening, prioritization of chemicals for initial biological tests and use of H295R cells to provide initial mechanistic information is a promising strategy to identify potential endocrine disruptors inhibiting corticosteroid synthesis. A critical assessment of human exposure levels and in vivo evaluation of potential corticosteroid disrupting effects by epoxiconazole is required.

Targeting pteridine reductase 1 and dihydrofolate reductase: the old is a new trend for leishmaniasis drug discovery

Leishmaniasis is one of the major neglected tropical diseases in the world and it is considered endemic in 88 countries. This disease is transmitted by a Leishmania spp. infected sandfly and it may lead to cutaneous or systemic manifestations. The preconized treatment has low efficacy and there are cases of resistance to some drugs. Therefore, the search for new efficient molecular targets that can lead to the preparation of new drugs must be pursued. This review aims to evaluate both Leishmania enzymes PTR1 and DHFR-TS as potential drug targets, highlight their inhibitors and to discuss critically the use of chemoinformatics to elucidate interactions and propose new molecules against these enzymes.

Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking

Docking calculations can accelerate drug discovery by predicting the bound poses of ligands for a targeted protein. However, it is not clear which docking methods work best. Furthermore, predicting poses requires steps outside the docking algorithm itself, such as preparation of the protein and ligand, and it is not known which components are most in need of improvement. The Continuous Evaluation of Ligand Protein Predictions (CELPP) is a blinded prediction challenge designed to address these issues. Participants create a workflow to predict protein-ligand binding poses, which is then tasked with predicting 10-100 new protein-ligand crystal structures each week. CELPP evaluates the accuracy of each workflow's predictions and posts the scores online. The results can be used to identify the strengths and weaknesses of current approaches, help map docking problems to the algorithms most likely to overcome them, and illuminate areas of unmet need in structure-guided drug design.