A Consistent Scheme for Gradient-Based Optimization of ProteinLigand Poses

Evaluations of the Perturbation Resistance of the Deep-Learning-Based Ligand Conformation Optimization Algorithm

In recent years, the deep learning (DL) technique has rapidly developed and shown great success in scoring the protein-ligand binding affinities. The protein-ligand conformation optimization based on DL-derived scoring functions holds broad application prospects, for instance, drug design and enzyme engineering. In this study, we evaluated the robustness of a DL-based ligand conformation optimization protocol (DeepRMSD+Vina) for optimizing structures with input perturbations by examining the predicted ligand binding poses and scoring. Our results clearly indicated that compared to traditional optimization algorithms (such as Prime MM-GBSA and Vina optimization), DeepRMSD+Vina exhibits higher performance when treating diverse protein-ligand cases. The DeepRMSD+Vina is robust and can always generate the correct binding structures even if perturbations (up to 3 Å) are introduced to the input structure. The success rate is 62% for perturbation with a RMSD within 2-3 Å. However, the success rate dramatically drops to 11% for large perturbations, with RMSD extending to 3-4 Å. Furthermore, compared to the widely used optimization protocol of AutoDock Vina, the DL-generated conformation shows a balanced performance for all of the systems under examination. Overall, the DL-based DeepRMSD+Vina is unarguably more reliable than the traditional methods, which is attributed to the physically inspired design of the neural networks in DeepRMSD+Vina where the distance-transformed features describing the atomic interactions between the protein and the ligand have been explicitly considered and modeled. The outstanding robustness of the DL-based ligand conformational optimization algorithm further validates its superiority in the field of conformational optimization.

Molecular Docking: An Emerging Tool for Target-Based Cancer Therapy

Molecular docking is a structure-based computational technique that plays a major role in drug discovery. Molecular docking enhances the efficacy of determining the metabolic interaction between two molecules, i.e., the small molecule (ligand) and the target molecule (protein), to find the best orientation of a ligand to its target molecule with minimal free energy in forming a stable complex. By stimulating drug-target interactions, docking helps identify small molecules that might inhibit cancer-promoting proteins, aiding in the development of novel targeted therapies. Molecular docking enables researchers to screen vast reorganization, identifying potential anti-cancer drugs with enhanced specificity and reduced toxicity. The growing importance of molecular docking underscores its potential to revolutionize cancer treatment by accelerating the identification of novel drugs and improving clinical outcomes. As a wide approach, this computational drug design technique can be considered more effective and timesaving than other cancer treatment methods. In this review, we showcase brief information on the role of molecular docking and its importance in cancer research for drug discovery and target identification. Therefore, in recent years, it can be concluded that molecular docking can be scrutinized as one of the novel strategies at the leading edge of cancer-targeting drug discovery.

Identification and development of TRPM4 antagonists to counteract neuronal excitotoxicity

Neurodegeneration in central nervous system disorders is linked to dysregulated neuronal calcium. Direct inhibition of glutamate-induced neuronal calcium influx, particularly via N-methyl-D-aspartate receptors (NMDAR), has led to adverse effects and clinical trial failures. A more feasible approach is to modulate NMDAR activity or calcium signaling indirectly. In this respect, the calcium-activated non-selective cation channel transient receptor potential melastatin 4 (TRPM4) has been identified as a promising target. However, high affinity and specific antagonists are lacking. Here, we conducted high-throughput screening of a compound library to identify high affinity TRPM4 antagonists. This yielded five lead compound series with nanomolar half-maximal inhibitory concentration values. Through medicinal chemistry optimization of two series, we established detailed structure-activity relationships and inhibition of excitotoxicity in neurons. Moreover, we identified their potential binding site supported by electrophysiological measurements. These potent TRPM4 antagonists are promising drugs for treating neurodegenerative disorders and TRPM4-related pathologies, potentially overcoming previous therapeutic challenges.

Azolopyrimidine-Based Thioethers: Synthesis via Cross-Dehydrogenative C-S Coupling and In Silico Evaluation of Anti-SARS-CoV-2 Activity

Azoloazine derivatives are known as promising small molecules that are potentially able to counteract a broad spectrum of RNA viruses including SARS-CoV-2. However, a pool of synthetic pathways to provide convenient structural modification of such compounds without de novo construction of the heterocyclic scaffold is rather limited so far. This work proposes an approach to the direct C(sp2)-H functionalization of azolopyrimidine substrates with aromatic thiol residues, mediated by the iodine/persulfate reagent system. The reported herein sulfenylation protocol has afforded a series of previously undescribed azolopyrimidine-based thioethers obtained in yields of up to 87 %. Applicability of the approach to the selenium-centered synthons has been demonstrated as well. Besides, the in silico study with regard to the achieved cross-coupling products has suggested the possible affinity to the SARS-CoV-2 main protease (Mpro), as follows from the conducted pharmacophore search and the molecular docking experiments. As a result, the developed synthetic transformation is expected to be of utility in the design of novel antiviral agents based on small azaheterocyclic molecules.

PheSA: An Open-Source Tool for Pharmacophore-Enhanced Shape Alignment

PheSA is an open-source pharmacophore- and shape-based screening and molecular alignment tool that is fully open-source as part of OpenChemLib. Supporting standard ligand-based screening, flexible refinement of alignments, and receptor-guided shape docking, PheSA is a very flexible tool and can be used for different use cases in structure-based drug design. We present the algorithm and different benchmark studies that investigate the screening performance and also the quality of the generated alignments and the pose prediction performance of the receptor-guided PheSA algorithm. An important finding is the effect of the type of similarity metric used for measuring screening enrichment (symmetric Tanimoto versus asymmetric Tversky), whereby we could observe improved enrichment rates by using Tversky. PheSA exhibits enrichments on the DUD-E that are on par with commercial methods.

User-centric design of a 3D search interface for protein-ligand complexes

In this work, we present the frontend of GeoMine and showcase its application, focusing on the new features of its latest version. GeoMine is a search engine for ligand-bound and predicted empty binding sites in the Protein Data Bank. In addition to its basic text-based search functionalities, GeoMine offers a geometric query type for searching binding sites with a specific relative spatial arrangement of chemical features such as heavy atoms and intermolecular interactions. In contrast to a text search that requires simple and easy-to-formulate user input, a 3D input is more complex, and its specification can be challenging for users. GeoMine's new version aims to address this issue from the graphical user interface perspective by introducing an additional visualization concept and a new query template type. In its latest version, GeoMine extends its query-building capabilities primarily through input formulation in 2D. The 2D editor is fully synchronized with GeoMine's 3D editor and provides the same functionality. It enables template-free query generation and template-based query selection directly in 2D pose diagrams. In addition, the query generation with the 3D editor now supports predicted empty binding sites for AlphaFold structures as query templates. GeoMine is freely accessible on the ProteinsPlus web server ( https://proteins.plus ).

A comprehensive assessment of the cholinergic-supporting and cognitive-enhancing effects of Rosa damascena Mill. (Damask rose) essential oil on scopolamine-induced amnestic rats

INTRODUCTION

Alzheimer's disease (AD) is a neurodegenerative condition characterized by gradual loss of cognitive abilities (dementia) and is a major public health problem. Here, we aimed at investigating the effects of Rosa damascena essential oil (RDEO) on learning and memory functions in a rat model of amnesia induced by scopolamine, as well as on changes in acetylcholinesterase (AChE) activity, M1 muscarinic acetylcholine receptor (mAChR) expression, and brain-derived neurotrophic factor (BDNF) levels in the extracted brain tissues.

METHODS

The control, amnesia (scopolamine, 1 mg/kg/i.p.) and treatment (RDEO, 100 μL/kg/p.o. or galantamine, 1.5 mg/kg/i.p.) groups were subjected to Morris water maze and new object recognition tests. AChE activity was assayed by ELISA, and M1 mAChR and BDNF concentration changes were determined by western blotting. Also, using computational tools, human M1 mAChR was modeled in an active conformation, and the major components of RDEO were docked onto this receptor.

RESULTS

According to our behavioral tests, RDEO was able to mitigate the learning and memory impairments caused by scopolamine in vivo. Our in vitro assays showed that the observed positive effects correlated well with a decrease in AChE activity and an increase in M1 mAChR and BDNF levels in amnestic rat brains. We also demonstrated in an in silico setting that the major components of RDEO, specifically -citronellol, geraniol, and nerol, could be accommodated favorably within the allosteric binding pocket of active-state human M1 mAChR and anchored here chiefly by hydrogen-bonding and alkyl-π interactions.

CONCLUSION

Our findings offer a solid experimental foundation for future RDEO-based medicinal product development for patients suffering from AD.

Investigating the association between CYP2J2 inhibitors and QT prolongation: a literature review

Drug withdrawal post-marketing due to cardiotoxicity is a major concern for drug developers, regulatory agencies, and patients. One common mechanism of cardiotoxicity is through inhibition of cardiac ion channels, leading to prolongation of the QT interval and sometimes fatal arrythmias. Recently, oxylipin signaling compounds have been shown to bind to and alter ion channel function, and disruption in their cardiac levels may contribute to QT prolongation. Cytochrome P450 2J2 (CYP2J2) is the predominant CYP isoform expressed in cardiomyocytes, where it oxidizes arachidonic acid to cardioprotective epoxyeicosatrienoic acids (EETs). In addition to roles in vasodilation and angiogenesis, EETs bind to and activate various ion channels. CYP2J2 inhibition can lower EET levels and decrease their ability to preserve cardiac rhythm. In this review, we investigated the ability of known CYP inhibitors to cause QT prolongation using Certara's Drug Interaction Database. We discovered that among the multiple CYP isozymes, CYP2J2 inhibitors were more likely to also be QT-prolonging drugs (by approximately 2-fold). We explored potential binding interactions between these inhibitors and CYP2J2 using molecular docking and identified four amino acid residues (Phe61, Ala223, Asn231, and Leu402) predicted to interact with QT-prolonging drugs. The four residues are located near the opening of egress channel 2, highlighting the potential importance of this channel in CYP2J2 binding and inhibition. These findings suggest that if a drug inhibits CYP2J2 and interacts with one of these four residues, then it may have a higher risk of QT prolongation and more preclinical studies are warranted to assess cardiovascular safety.

Bioinspired Pyrano[2,3-f]chromen-8-ones: Ring C-Opened Analogues of Calanolide A: Synthesis and Anti-HIV-1 Evaluation

We have designed and synthesized a series of bioinspired pyrano[2,3-f]coumarin-based Calanolide A analogs with anti-HIV activity. The design of these new calanolide analogs involved incorporating nitrogen heterocycles or aromatic groups in lieu of ring C, effectively mimicking and preserving their bioactive properties. Three directions for the synthesis were explored: reaction of 5-hydroxy-2,2-dimethyl-10-propyl-2H,8H-pyrano[2,3-f]chromen-8-one with (i) 1,2,4-triazines, (ii) sulfonylation followed by Suzuki cross-coupling with (het)aryl boronic acids, and (iii) aminomethylation by Mannich reaction. Antiviral assay of the synthesized compounds showed that compound 4 has moderate activity against HIV-1 on enzymes and poor activity on the cell model. A molecular docking study demonstrates a good correlation between in silico and in vitro HIV-1 reverse transcriptase (RT) activity of the compounds when docked to the nonnucleoside RT inhibitor binding site, and alternative binding modes of the considered analogs of Calanolide A were established.

Redocking the PDB

Molecular docking is a standard technique in structure-based drug design (SBDD). It aims to predict the 3D structure of a small molecule in the binding site of a receptor (often a protein). Despite being a common technique, it often necessitates multiple tools and involves manual steps. Here, we present the JAMDA preprocessing and docking workflow that is easy to use and allows fully automated docking. We evaluate the JAMDA docking workflow on binding sites extracted from the complete PDB and derive key factors determining JAMDA's docking performance. With that, we try to remove most of the bias due to manual intervention and provide a realistic estimate of the redocking performance of our JAMDA preprocessing and docking workflow for any PDB structure. On this large PDBScan22 data set, our JAMDA workflow finds a pose with an RMSD of at most 2 Å to the crystal ligand on the top rank for 30.1% of the structures. When applying objective structure quality filters to the PDBScan22 data set, the success rate increases to 61.8%. Given the prepared structures from the JAMDA preprocessing pipeline, both JAMDA and the widely used AutoDock Vina perform comparably on this filtered data set (the PDBScan22-HQ data set).

Arylureidoaurones: Synthesis, in vitro α-glucosidase, and α-amylase inhibition activity

Because of the colossal global burden of diabetes, there is an urgent need for more effective and safer drugs. We designed and synthesized a new series of aurone derivatives possessing phenylureido or bis-phenylureido moieties as α-glucosidase and α-amylase inhibitors. Most of the synthesized phenylureidoaurones have demonstrated superior inhibition activities (IC50s of 9.6-339.9 μM) against α-glucosidase relative to acarbose (IC50 = 750.0 μM) as the reference drug. Substitution of aurone analogues with two phenylureido substituents at the 5-position of the benzofuranone moiety and the 3' or 4' positions of the 2-phenyl ring resulted in compounds with almost 120-180 times more potent inhibitory activities than acarbose. The aurone analogue possessing two phenylureido substitutions at 5 and 4' positions (13) showed the highest inhibition activity with an IC50 of 4.2 ± 0.1 μM. Kinetic studies suggested their inhibition mode to be competitive. We also investigated the binding mode of the most potent compounds using the consensually docked 4D-QSAR methodology. Furthermore, these analogues showed weak-to-moderate non-competitive inhibitory activity against α-amylase. 5-Methyl substituted aurone with 4'-phenylureido moiety (6e) demonstrated the highest inhibition activity on α-amylase with an IC50 of 142.0 ± 1.6 μM relative to acarbose (IC50 = 108 ± 1.2 μM). Our computational studies suggested that these analogues interact with a hydrophilic allosteric site in α-amylase, located far from the enzyme active site at the N-terminal.

Mechanistic insights into the inhibition of human placental glutathione S-transferase P1-1 by abscisic and gibberellic acids: An integrated experimental and computational study

The interactions of the classic phytohormones gibberellic acid (gibberellin A3 , GA3 ) and abscisic acid (dormin, ABA), which antagonistically regulate several developmental processes and stress responses in higher plants, with human placental glutathione S-transferase P1-1 (hpGSTP1-1), an enzyme that plays a role in endo- or xenobiotic detoxification and regulation of cell survival and apoptosis, were investigated. The inhibitory potencies of ABA and GA3 against hpGSTP1, as well as the types of inhibition and the kinetic parameters, were determined by making use of both enzyme kinetic graphs and SPSS nonlinear regression models. The structural basis for the interaction between hpGSTP1-1 and phytohormones was predicted with the aid of molecular docking simulations. The IC50 values of ABA and GA3 were 5.3 and 5.0 mM, respectively. Both phytohormones inhibited hpGSTP1-1 in competitive manner with respect to the cosubstrates GSH and CDNB. When ABA was the inhibitor at [CDNB]f -[GSH]v and at [GSH]f -[CDNB]v , Vm , Km , and Ki values were statistically estimated to be 205 ± 16 μmol/min-mg protein, 1.32 ± 0.18 mM, 1.95 ± 0.25 mM and 175 ± 6 μmol/min-mg protein, 0.85 ± 0.06 mM, 1.85 ± 0.16 mM, respectively. On the other hand, the kinetic parameters Vm , Km , and Ki obtained with GA3 at [CDNB]f -[GSH]v and at [GSH]f -[CDNB]v were found to be 303 ± 14 μmol/min-mg protein, 1.77 ± 0.13 mM, 3.38 ± 0.26 mM and 249 ± 7 μmol/min-mg protein, 1.43 ± 0.07 mM, 2.89 ± 0.19 mM, respectively. Both phytohormones had the potential to engage in hydrogen-bonding and electrostatic interactions with the key residues that line the G- and H-sites of the enzyme's catalytic center. Inhibitory actions of ABA/GA3 on hpGSTP1-1 may guide medicinal chemists through the structure-based design of novel antineoplastic agents. It should be noted, however, that the same interactions may also render fetuses vulnerable to the potentially toxic effects of xenobiotics and noxious endobiotics.

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein-Ligand Binding Affinity Prediction

Accurate prediction of the protein-ligand binding affinity (PLBA) with an affordable cost is one of the ultimate goals in the field of structure-based drug design (SBDD), as well as a great challenge in the computational and theoretical chemistry. Herein, we have systematically addressed the complicated solvation and desolvation effects on the PLBA brought by the difference of the explicit water in the protein cavity before and after ligands bind to the protein-binding site. Based on the new solvation model, a nonfitting method at the first-principles level for the PLBA prediction was developed by taking the bridging and displaced water (BDW) molecules into account simultaneously. The newly developed method, DOX_BDW, was validated against a total of 765 noncovalent and covalent protein-ligand binding pairs, including the CASF2016 core set, Cov_2022 covalent binding testing set, and six testing sets for the hit and lead compound optimization (HLO) simulation. In all of the testing sets, the DOX_BDW method was able to produce PLBA predictions that were strongly correlated with the corresponding experimental data (R = 0.66-0.85). The overall performance of DOX_BDW is better than the current empirical scoring functions that are heavily parameterized. DOX_BDW is particularly outstanding for the covalent binding situation, implying the need for considering an electronic structure in covalent drug design. Furthermore, the method is especially recommended to be used in the HLO scenario of SBDD, where hundreds of similar derivatives need to be screened and refined. The computational cost of DOX_BDW is affordable, and its accuracy is remarkable.

Modeling with Alternate Locations in X-ray Protein Structures

In many molecular modeling applications, the standard procedure is still to handle proteins as single, rigid structures. While the importance of conformational flexibility is widely known, handling it remains challenging. Even the crystal structure of a protein usually contains variability exemplified in alternate side chain orientations or backbone segments. This conformational variability is encoded in PDB structure files by so-called alternate locations (AltLocs). Most modeling approaches either ignore AltLocs or resolve them with simple heuristics early on during structure import. We analyzed the occurrence and usage of AltLocs in the PDB and developed an algorithm to automatically handle AltLocs in PDB files enabling all structure-based methods using rigid structures to take the alternative protein conformations described by AltLocs into consideration. A respective software tool named AltLocEnumerator can be used as a structure preprocessor to easily exploit AltLocs. While the amount of data makes it difficult to show impact on a statistical level, handling AltLocs has a substantial impact on a case-by-case basis. We believe that the inspection and consideration of AltLocs is a very valuable approach in many modeling scenarios.

Protective effects of Rubus tereticaulis leaves ethanol extract on rats with ulcerative colitis and bio-guided isolation of its active compounds: A combined in silico, in vitro and in vivo study

The aim of this study was to evaluate the therapeutic effect of active ethanol extract obtained from the leaves of Rubus tereticaulis (RTME) against colitis, and to purify major compounds from this extract by bioassay-directed isolation. Rats with colitis induced via intra-rectal acetic acid administration (5%, v/v) received RTME or sulfasalazine for three consecutive days. On day four, all rats were decapitated, and the colonic tissue samples were collected for macroscopic score, colon weight, reduced glutathione (GSH), myeloperoxidase (MPO), and malondialdehyde (MDA) analyses. The active compounds and chemical composition of RTME were determined by bio-guided isolation and LC-MS/MS, respectively. Compared to the colitis group, the rats treated with RTME displayed significantly lowered macroscopic scores and colon wet weights (p < 0.001). These effects were confirmed biochemically by a decrease in colonic MPO activity (p < 0.001), MDA levels (p < 0.001), and an increase in GSH levels (p < 0.001). Kaempferol-3-O-β-d-glucuronide (RT1) and quercetin-3-O-β-d-glucuronide (RT2) were found to be the major compounds of RTME, as evidenced by in vitro anti-inflammatory and antioxidant activity-guided isolation. Their anti-inflammatory/antioxidant activities were also predicted by docking simulations. Additionally, quinic acid, 5-caffeoylquinic acid, quercetin pentoside, quercetin glucoside, quercetin-3-O-β-d-glucuronide, kaempferol-3-O-β-d-glucuronide, and kaempferol rutinoside were identified in RTME via using LC-MS/MS. RT2, along with other compounds, may be responsible for the observed protective action of RTME against colitis. This study represents the first report on the beneficial effects of RTME in an experimental model of colitis and highlights the potential future use of RTME as a natural alternative to alleviate colitis.

In Vitro and In Silico Evaluation of ACE2 and LOX Inhibitory Activity of Origanum Essential Oils and Carvacrol

Origanum spp. are used both for culinary purposes and for their biological activities. In this study, commercial Origanum majorana, Origanum minutiflorum, Origanum vulgare, and Origanum onites essential oils and their prominent constituent carvacrol were evaluated for their in vitro and in silico angiotensin-converting enzyme 2 and lipoxygenase enzyme inhibitory potentials. The essential oils were analysed by gas chromatography-flame ionisation detection and gas chromatography-mass spectrometry, where carvacrol was identified as the major component (62 - 81%), confirming the quality. In vitro enzyme inhibition assays were conducted both with the essential oils (20 µg/mL) and with carvacrol (5 µg/mL). The comparative values of angiotensin-converting enzyme 2 percent inhibition for O. majorana, O. minutiflorum, O. vulgare, and O. onites essential oils were determined as 85.5, 79.1, 74.3, and 42.8%, respectively. As a result of the enzyme assays, carvacrol showed 90.7% in vitro angiotensin-converting enzyme 2 inhibitory activity. The in vitro lipoxygenase inhibition of the essential oils (in the same order) was 89.4, 78.9, 81.1, and 73.5%, respectively, where carvacrol showed 74.8% inhibition. In addition, protein-ligand docking and interaction profiling was used to gain structural and mechanistic insights into the angiotensin-converting enzyme 2 and lipoxygenase inhibitory potentials of major Origanum essential oil constituents. The in silico findings agreed with the significant enzyme inhibition activity observed in vitro. Further in vivo studies are suggested to confirm the safety and efficacy of the oils.

FastGrow: on-the-fly growing and its application to DYRK1A

Fragment-based drug design is an established routine approach in both experimental and computational spheres. Growing fragment hits into viable ligands has increasingly shifted into the spotlight. FastGrow is an application based on a shape search algorithm that addresses this challenge at high speeds of a few milliseconds per fragment. It further features a pharmacophoric interaction description, ensemble flexibility, as well as geometry optimization to become a fully fledged structure-based modeling tool. All features were evaluated in detail on a previously reported collection of fragment growing scenarios extracted from crystallographic data. FastGrow was also shown to perform competitively versus established docking software. A case study on the DYRK1A kinase, using recently reported new chemotypes, illustrates FastGrow's features in practice and its ability to identify active fragments. FastGrow is freely available to the public as a web server at https://fastgrow.plus/ and is part of the SeeSAR 3D software package.

Analyzing structural features of proteins from deep-sea organisms

Protein adaptations to extreme environmental conditions are drivers in biotechnological process optimization and essential to unravel the molecular limits of life. Most proteins with such desirable adaptations are found in extremophilic organisms inhabiting extreme environments. The deep sea is such an environment and a promising resource that poses multiple extremes on its inhabitants. Conditions like high hydrostatic pressure and high or low temperature are prevalent and many deep-sea organisms tolerate multiple of these extremes. While molecular adaptations to high temperature are comparatively good described, adaptations to other extremes like high pressure are not well-understood yet. To fully unravel the molecular mechanisms of individual adaptations it is probably necessary to disentangle multifactorial adaptations. In this study, we evaluate differences of protein structures from deep-sea organisms and their respective related proteins from nondeep-sea organisms. We created a data collection of 1281 experimental protein structures from 25 deep-sea organisms and paired them with orthologous proteins. We exhaustively evaluate differences between the protein pairs with machine learning and Shapley values to determine characteristic differences in sequence and structure. The results show a reasonable discrimination of deep-sea and nondeep-sea proteins from which we distinguish correlations previously attributed to thermal stability from other signals potentially describing adaptions to high pressure. While some distinct correlations can be observed the overall picture appears intricate.

Violacein switches off low molecular weight tyrosine phosphatase and rewires mitochondria in colorectal cancer cells

In the last decade, emerging evidence has shown that low molecular weight protein tyrosine phosphatase (LMWPTP) not only contributes to the progression of cancer but is associated with prostate low survival rate and colorectal cancer metastasis. We report that LMWPTP favors the glycolytic profile in some tumors. Therefore, the focus of the present study was to identify metabolic enzymes that correlate with LMWPTP expression in patient samples. Exploratory data analysis from RNA-seq, proteomics, and histology staining, confirmed the higher expression of LMWPTP in CRC. Our descriptive statistical analyses indicate a positive expression correlation between LMWPTP and energy metabolism enzymes such as acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN). In addition, we examine the potential of violacein to reprogram energetic metabolism and LMWPTP activity. Violacein treatment induced a shift of glycolytic to oxidative metabolism associated with alteration in mitochondrial efficiency, as indicated by higher oxygen consumption rate. Particularly, violacein treated cells displayed higher proton leak and ATP-linked oxygen consumption rate (OCR) as an indicator of the OXPHOS preference. Notably, violacein is able to bind and inhibit LMWPTP. Since the LMWPTP acts as a hub of signaling pathways that offer tumor cells invasive advantages, such as survival and the ability to migrate, our findings highlight an unexplored potential of violacein in circumventing the metabolic plasticity of tumor cells.

Exploration of chalcones as 3-chymotrypsin-like protease (3CLpro) inhibitors of SARS-CoV-2 using computational approaches

The main protease 3CL^pro is one of the potential targets against coronavirus. Inhibiting this enzyme leads to the interruption of viral replication. Chalcone and its derivatives were reported to possess the ability to bind to 3CL^pro protease in the binding pocket. This study explored an in-house database of 269 chalcones as 3CL^pro inhibitors using in silico screening models, including molecular docking, molecular dynamics simulation, binding free energy calculation, and ADME prediction. C264 and C235 stand out as the two most potential structures. The top hit compound C264 was with the Jamda score of −2.8329 and the MM/GBSA binding energy mean value of −28.23 ± 3.53 kcal/mol, which was lower than the reference ligand. Despite the lower mean binding energy (−22.07 ± 3.39 kcal/mol), in-depth analysis of binding interaction suggested C235 could be another potential candidate. Further, in vitro and in vivo experiments are required to confirm the inhibitory ability.

ProteinsPlus: a comprehensive collection of web-based molecular modeling tools

Upon the ever-increasing number of publicly available experimentally determined and predicted protein and nucleic acid structures, the demand for easy-to-use tools to investigate these structural models is higher than ever before. The ProteinsPlus web server (https://proteins.plus) comprises a growing collection of molecular modeling tools focusing on protein-ligand interactions. It enables quick access to structural investigations ranging from structure analytics and search methods to molecular docking. It is by now well-established in the community and constantly extended. The server gives easy access not only to experts but also to students and occasional users from the field of life sciences. Here, we describe its recently added new features and tools, beyond them a novel method for on-the-fly molecular docking and a search method for single-residue substitutions in local regions of a protein structure throughout the whole Protein Data Bank. Finally, we provide a glimpse into new avenues for the annotation of AlphaFold structures which are directly accessible via a RESTful service on the ProteinsPlus web server.

In vitro and in silico Evaluation of ACE2 and LOX Inhibitory Activity of Eucalyptus Essential Oils, 1,8-Cineole, and Citronellal

Eucalyptus essential oils are well-known and used especially in upper respiratory tract pathologies or diseases as herbal drug preparations. In the present study, the in vitro angiotensin-converting enzyme 2 (ACE2) and lipoxygenase (LOX) enzyme inhibitory potentials of commercial Eucalyptus globulus Labill. and Eucalyptus citriodora Hook. essential oils were evaluated for their potential anti-coronavirus disease 2019 (COVID-19), and anti-inflammatory effects. In addition, the major components, 1,8-cineole and citronellal, were evaluated for their ability to bind at the active site of either human ACE2 or human 5-LOX using an in silico setting. Before activity evaluation, Eucalyptus globulus and E citriodora essential oils were analysed by GC/FID and GC/MS, where 1,8-cineole (30%), and citronellal (80%) were identified as the major components, respectively. The in vitro ACE2 inhibition was calculated as 94.9% for E globulus, and that of E citriodora essential oil as 83.4%. In vitro LOX inhibition experiments for essential oils in the same order showed inhibitions of 71.3 and 91.4%, respectively, at 20 µg/mL test concentrations in microplate-based fluorometric assays. In addition, protein–ligand docking, and interaction profiling was used to gain structural and mechanistic insights into the in silico ACE2 and LOX inhibitory potentials of the major Eucalyptus essential oil constituents, 1,8-cineole as well as citronellal. The resulting data supported the in vitro findings; however, further in vivo studies are needed to confirm the activity.

Anti-Virulence Activity of 3,3′-Diindolylmethane (DIM): A Bioactive Cruciferous Phytochemical with Accelerated Wound Healing Benefits

Antimicrobial resistance is among the top global health problems with antibacterial resistance currently representing the major threat both in terms of occurrence and complexity. One reason current treatments of bacterial diseases are ineffective is the occurrence of protective and resistant biofilm structures. Phytochemicals are currently being reviewed for newer anti-virulence agents. In the present study, we aimed to investigate the anti-virulence activity of 3,3′-diindolylmethane (DIM), a bioactive cruciferous phytochemical. Using a series of in vitro assays on major Gram-negative pathogens, including transcriptomic analysis, and in vivo porcine wound studies as well as in silico experiments, we show that DIM has anti-biofilm activity. Following DIM treatment, our findings show that biofilm formation of two of the most prioritized bacterial pathogens Acinetobacter baumannii and Pseudomonas aeruginosa was inhibited respectively by 65% and 70%. Combining the antibiotic tobramycin with DIM enabled a high inhibition (94%) of P. aeruginosa biofilm. A DIM-based formulation, evaluated for its wound-healing efficacy on P. aeruginosa-infected wounds, showed a reduction in its bacterial bioburden, and wound size. RNA-seq was used to evaluate the molecular mechanism underlying the bacterial response to DIM. The gene expression profile encompassed shifts in virulence and biofilm-associated genes. A network regulation analysis showed the downregulation of 14 virulence-associated super-regulators. Quantitative real-time PCR verified and supported the transcriptomic results. Molecular docking and interaction profiling indicate that DIM can be accommodated in the autoinducer- or DNA-binding pockets of the virulence regulators making multiple non-covalent interactions with the key residues that are involved in ligand binding. DIM treatment prevented biofilm formation and destroyed existing biofilm without affecting microbial death rates. This study provides evidence for bacterial virulence attenuation by DIM.

A multi-parameter evaluation of the neuroprotective and cognitive-enhancing effects of Origanum onites L. (Turkish Oregano) essential oil on scopolamine-induced amnestic rats

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive deterioration of cognitive functions (dementia) and represents a growing public health concern since the population in the age groups at risk is increasing. The latter raises an urgent need to translate research findings in the basic brain and behavioral sciences into anti-AD drugs and disease-modifying therapies. Origanum onites (L.), also called Turkish oregano, is a perennial and herbaceous plant species grown for centuries for medicinal, cosmetic and culinary purposes. This is the first study to investigate the putative neuroprotective and pro-cognitive activities of O. onites essential oil (OOEO) against scopolamine-induced amnesia of AD-type in Wistar albino rats. The results of behavioral tests revealed that OOEO administration was able to significantly alleviate learning and memory impairments induced by scopolamine in vivo. The observed effects could be attributed to inhibition of acetylcholinesterase activity, attenuation of oxidative stress and prevention of neuronal apoptosis in the hippocampus and frontal cortex of AD rats. Modulation of pro-inflammatory enzymes, including cyclooxygenase-2, inducible nitric oxide synthase and myeloperoxidase, might further contribute to the neuroprotective properties of OEOO, as predicted by our in silico models. These findings offer novel insights into the therapeutic potential of OEOO in patients with AD.

The Torsion Library: Semiautomated Improvement of Torsion Rules with SMARTScompare

The Torsion Library is a collection of torsion motifs associated with angle distributions, derived from crystallographic databases. It is used in strain assessment, conformer generation, and geometry optimization. A hierarchical structure of expert curated SMARTS defines the chemical environments of rotatable bonds and associates these with preferred angles. SMARTS can be very complex and full of implications, which make them difficult to maintain manually. Recent developments in automatically comparing SMARTS patterns can be applied to the Torsion Library to ensure its correctness. We specifically discuss the implementation and the limits of such a procedure in the context of torsion motifs and show several examples of how the Torsion Library benefits from this. All automated changes are validated manually and then shown to have an effect on the angle distributions by correcting matching behavior. The corrected Torsion Library itself is available including both PDB as well as CSD histograms in the Supporting Information and can be used to evaluate rotatable bonds at https://torsions.zbh.uni-hamburg.de.

Isolation, Characterization and In Silico Studies of Secondary Metabolites from the Whole Plant of Polygala inexpectata Peşmen & Erik

Polygala species are frequently used worldwide in the treatment of various diseases, such as inflammatory and autoimmune disorders as well as metabolic and neurodegenerative diseases, due to the large number of secondary metabolites they contain. The present study was performed on Polygala inexpectata, which is a narrow endemic species for the flora of Turkey, and resulted in the isolation of nine known compounds, 6,3'-disinapoyl-sucrose (1), 6-O-sinapoyl,3'-O-trimethoxy-cinnamoyl-sucrose (tenuifoliside C) (2), 3'-O-(O-methyl-feruloyl)-sucrose (3), 3'-O-(sinapoyl)-sucrose (4), 3'-O-trimethoxy-cinnamoyl-sucrose (glomeratose) (5), 3'-O-feruloyl-sucrose (sibiricose A5) (6), sinapyl alcohol 4-O-glucoside (syringin or eleutheroside B) (7), liriodendrin (8), and 7,4'-di-O-methylquercetin-3-O-β-rutinoside (ombuin 3-O-rutinoside or ombuoside) (9). The structures of the compounds were determined by the spectroscopic methods including 1D-NMR (1H NMR, 13C NMR, DEPT-135), 2D-NMR (COSY, NOESY, HSQC, HMBC), and HRMS. The isolated compounds were shown in an in silico setting to be accommodated well within the inhibitor-binding pockets of myeloperoxidase and inducible nitric oxide synthase and anchored mainly through hydrogen-bonding interactions and π-effects. It is therefore plausible to suggest that the previously established anti-inflammatory properties of some Polygala-derived phytochemicals may be due, in part, to the modulation of pro-inflammatory enzyme activities.

ATPdock: a template-based method for ATP-specific protein-ligand docking

MOTIVATION

Accurately identifying protein-ATP binding poses is significantly valuable for both basic structure biology and drug discovery. Although many docking methods have been designed, most of them require a user-defined binding site and are difficult to achieve a high-quality protein-ATP docking result. It is critical to develop a protein-ATP-specific blind docking method without user-defined binding sites.

RESULTS

Here, we present ATPdock, a template-based method for docking ATP into protein. For each query protein, if no pocket site is given, ATPdock first identifies its most potential pocket using ATPbind, an ATP-binding site predictor; then, the template pocket, which is most similar to the given or identified pocket, is searched from the database of pocket-ligand structures using APoc, a pocket structural alignment tool; thirdly, the rough docking pose of ATP (rdATP) is generated using LS-align, a ligand structural alignment tool, to align the initial ATP pose to the template ligand corresponding to template pocket; finally, the Metropolis Monte Carlo simulation is used to fine-tune the rdATP under the guidance of AutoDock Vina energy function. Benchmark tests show that ATPdock significantly outperforms other state-of-the-art methods in docking accuracy.

AVAILABILITY AND IMPLEMENTATION

https://jun-csbio.github.io/atpdock/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Lin_F9: A Linear Empirical Scoring Function for Protein-Ligand Docking

Molecular docking is one of the most widely used computational tools in structure-based drug design and is critically dependent on accuracy and robustness of the scoring function. In this work, we introduce a new scoring function Lin_F9, which is a linear combination of nine empirical terms, including a unified metal bond term to specifically describe metal-ligand interactions. Parameters in Lin_F9 are obtained with a multistage fitting protocol using explicit water-included structures. For the CASF-2016 benchmark test set, Lin_F9 achieves the top scoring power among all 34 classical scoring functions for both original crystal poses and locally optimized poses with Pearson correlation coefficients (R) of 0.680 and 0.687, respectively. Meanwhile, in comparison with Vina, Lin_F9 achieves consistently better scoring power and ranking power with various types of protein-ligand complex structures that mimic real docking applications, including end-to-end flexible docking for the CASF-2016 benchmark test set using a single or an ensemble of protein receptor structures, as well as for D3R Grand Challenge (GC4) test sets. Lin_F9 has been implemented in a fork of Smina as an optional built-in scoring function that can be used for docking applications as well as for further improvement of scoring functions and docking protocols. Lin_F9 is accessible through https://yzhang.hpc.nyu.edu/Lin_F9/.

LSLOpt: An open-source implementation of the step-length controlled LSL-BFGS algorithm

Numerical optimization is a common technique in various areas of computational chemistry, molecular modeling and drug design. It is a key element of 3D techniques, for example, the optimization of protein-ligand poses and small-molecule conformers. Here, often the BFGS algorithm or variants thereof are used. However, the BFGS algorithm tends to make unreasonable large changes to the optimized system under certain circumstances. This behavior has been known for a long time and different solutions have been suggested. Recently, we have analyzed the optimization behavior of our novel JAMDA scoring function in detail and proposed the limited step length (LSL)-BFGS algorithm as a new solution to the problem of excessively large steps during optimization. The LSL-BFGS algorithm allows to control the step sizes during optimization. Its unique feature is the inclusion of arbitrary domain knowledge into the selection of the step sizes. Here, we introduce the open-source LSLOpt C++ library that implements this LSL-BFGS algorithm and demonstrate its usage.

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput x-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (Mpro), which is essential for viral replication. In contrast to commonly applied x-ray fragment screening experiments with molecules of low complexity, our screen tested already-approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to Mpro In subsequent cell-based viral reduction assays, one peptidomimetic and six nonpeptidic compounds showed antiviral activity at nontoxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2.

Assessing the Molecular Targets and Mode of Action of Furanone C-30 on Pseudomonas aeruginosa Quorum Sensing

Quorum sensing (QS), a sophisticated system of bacterial communication that depends on population density, is employed by many pathogenic bacteria to regulate virulence. In view of the current reality of antibiotic resistance, it is expected that interfering with QS can address bacterial pathogenicity without stimulating the incidence of resistance. Thus, harnessing QS inhibitors has been considered a promising approach to overriding bacterial infections and combating antibiotic resistance that has become a major threat to public healthcare around the globe. Pseudomonas aeruginosa is one of the most frequent multidrug-resistant bacteria that utilize QS to control virulence. Many natural compounds, including furanones, have demonstrated strong inhibitory effects on several pathogens via blocking or attenuating QS. While the natural furanones show no activity against P. aeruginosa, furanone C-30, a brominated derivative of natural furanone compounds, has been reported to be a potent inhibitor of the QS system of the notorious opportunistic pathogen. In the present study, we assess the molecular targets and mode of action of furanone C-30 on P. aeruginosa QS system. Our results suggest that furanone C-30 binds to LasR at the ligand-binding site but fails to establish interactions with the residues crucial for the protein's productive conformational changes and folding, thus rendering the protein dysfunctional. We also show that furanone C-30 inhibits RhlR, independent of LasR, suggesting a complex mechanism for the agent beyond what is known to date.