CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction

In Silico Screening of Synthetic and Natural Compounds to Inhibit the Binding Capacity of Heavy Metal Compounds against EGFR Protein of Lung Cancer

Inorganic pollutant, specifically heavy metals’ contamination, is a significant matter of concern and is one of the key contributors in various health disorders including cancer. However, the interaction of heavy metals (HMs) with lung cancer has rarely been explored yet. Therefore, the present study was intended with the aim to identify the interactions of HMs with the target protein “epidermal growth factor receptor (EGFR)” of lung cancer and explore potential drug candidates, which could inhibit the active site of EGFR against HM exposure. The molecular operating environment (MOE) tool was used to study the interactions of HMs with EGFR protein. The drug-drug interaction (DDI) network approach was used to identify the potential drug candidates, which were further confirmed and compared with the commercial medicines/control group. Various compounds of twenty-three HMs were docked with EGFR protein. Out of which tinidazole, thallium bromodimethyl, and silver acetate (Sn, Ti, and Ag compounds) showed strong interactions with EGFR based on lowest-scoring values (-20.42, -7.86, and -7.74 kcal/mol, respectively). Among 1280 collected drug candidates, three synthetic compounds viz., ZINC00602803, ZINC00602685, and ZINC06718468 and three natural compounds (berberine chloride, transresveratrol, and ellagic acid) depicted strong binding capacity with EGFR. Specifically, the scoring value of ZINC00602803 (-30.99 kcal/mol) was even lowest than standard lung cancer drugs (afatinib, erlotinib, and gefitinib). Our findings revealed that both natural and synthetic compounds having strong associations with EGFR protein could be potential candidates to inhibit the interaction between HMs and lung cancer protein and can also be used as an alternative for the prevention and treatment of lung cancer. However, in vitro and in vivo studies should be conducted to validate the aforementioned natural and synthetic compounds.

Targeting allosteric regulation of cancer metabolism

Metabolic reprogramming is observed across all cancer types. Indeed, the success of many classic chemotherapies stems from their targeting of cancer metabolism. Contemporary research in this area has refined our understanding of tumor-specific metabolic mechanisms and has revealed strategies for exploiting these vulnerabilities selectively. Based on this growing understanding, new small-molecule tools and drugs have been developed to study and target tumor metabolism. Here, we highlight allosteric modulation of metabolic enzymes as an attractive mechanism of action for small molecules that target metabolic enzymes. We then discuss the mechanistic insights garnered from their application in cancer studies and highlight the achievements of this approach in targeting cancer metabolism. Finally, we discuss technological advances in drug discovery for allosteric modulators of enzyme activity.

ELIXIR-A: An Interactive Visualization Tool for Multi-Target Pharmacophore Refinement

Pharmacophore modeling is an important step in computer-aided drug design for identifying interaction points between the receptor and ligand complex. Pharmacophore-based models can be used for de novo drug design, lead identification, and optimization in virtual screening as well as for multi-target drug design. There is a need to develop a user-friendly interface to filter the pharmacophore points resulting from multiple ligand conformations. Here, we present ELIXIR-A, a Python-based pharmacophore refinement tool, to help refine the pharmacophores between multiple ligands from multiple receptors. Furthermore, the output can be easily used in virtual pharmacophore-based screening platforms, thereby contributing to the development of drug discovery.

Identification of novel saltiness-enhancing peptides from yeast extract and their mechanism of action for transmembrane channel-like 4 (TMC4) protein through experimental and integrated computational modeling

Excessive consumption of sodium salt is one of the important inducers of cardiovascular and cerebrovascular diseases. The reduction of physical labor and attention to health make research on low-sodium salt imminent. Ultrafiltration, gel filtration, preparative high-performance liquid chromatography, and liquid chromatography with tandem mass spectrometry were employed for further purification and identification of the salty enhancing peptides in yeast extracts. Moreover, human transmembrane channel-like 4 (TMC4) was constructed and evaluated by computer-based methods, and salt-enhancing peptides were identified based on its allosteric sites. PN, NSE, NE and SPE were further determined to be salty enhancing peptides through sensory evaluation, and their taste mechanism was investigated. The results presented here suggest that silicon screening focused on TMC4 allosteric sites and sensory evaluation experiments can greatly increase the discoverability and identifiability of salty enhancer peptides, and this strategy is the first to be applied to the development of salty enhancer peptides.

Unraveling the Roles of Protein Kinases in Autophagy: An Update on Small-Molecule Compounds for Targeted Therapy

Protein kinases, which catalyze the phosphorylation of proteins, are involved in several important cellular processes, such as autophagy. Of note, autophagy, originally described as a mechanism for intracellular waste disposal and recovery, has been becoming a crucial biological process closely related to many types of human diseases. More recently, the roles of protein kinases in autophagy have been gradually elucidated, and the design of small-molecule compounds to modulate targets to positively or negatively interfere with the cytoprotective autophagy or autophagy-associated cell death may provide a new clue on the current targeted therapy. Thus, in this Perspective, we focus on summarizing the different roles of protein kinases, including positive, negative, and bidirectional regulations of autophagy. Moreover, we discuss several small-molecule compounds targeting these protein kinases in human diseases, highlighting their pivotal roles in autophagy for targeted therapeutic purposes.

Novel inhibitors of the STAT3 signaling pathway: an updated patent review (2014-present)

INTRODUCTION

STAT3 is a critical transcription factor that transmits signals from the cell surface to the nucleus, thus influencing the transcriptional regulation of some oncogenes. The inhibition of the activation of STAT3 is considered a promising strategy for cancer therapy. Numerous STAT3 inhibitors bearing different scaffolds have been reported to date, with a few of them having been considered in clinical trials.

AREAS COVERED

This review summarizes the advances on STAT3 inhibitors with different structural skeletons, focusing on the structure-activity relationships in the related patent literature published from 2014 to date.

EXPERT OPINION

Since the X-ray crystal structure of STAT3β homo dimer bound to DNA was solved in 1998, the development of STAT3 inhibitors has gone through a boom in recent years. However, none of them have been approved for marketing, probably due to the complex biological functions of the STAT3 signaling pathway, including its character and the poor drug-like physicochemical properties of its inhibitors. Nonetheless, targeting STAT3 continues to be an exciting field for the development of anti-tumor agents along with the emergence of new STAT3 inhibitors with unique mechanisms of action.

Ponicidin suppresses pancreatic cancer growth by inducing ferroptosis: Insight gained by mass spectrometry-based metabolomics

BACKGROUND

Pancreatic cancer is one of the most common malignant tumors of the digestive tract. Ponicidin, a tetracyclic diterpenoid active ingredient extracted from the traditional phytomedicine Rubescens, has high safety and great inhibitory effect on the proliferation of a variety of cancer cells, especially malignant tumor cells of the digestive tract. However, the inhibitory effect and mechanism of ponicidin on pancreatic cancer cells is still unclear. Our study aimed to use metabonomics technology to analyze and explore the suppressive effect of ponidicin against pancreatic cancer cells.

METHODS

MTT and flow cytometry were conducted to study the potential effect of ponicidin on SW1990 cells. Secondly, UPLC-MS/MS was used to analyze the small molecule metabolites and relevant differential metabolic pathways induced by ponicidin treatment. Furthermore, through the determination of glutathione peroxidase 4 (GPX4) activity and molecular docking simulation experiments, the effects of intracellular GPX4 activity and GSH/GSSG ratio after ponicidin were evaluated. Finally, the determination of the content of iron ions and malondialdehyde in cells, and the experiment of the effect of ferroptosis inhibitors on cell viability, the effect of ponicidin on the induction of ferroptosis in SW1990 cells was also detected.

RESULTS

The IC50 of ponicidin on SW1990 cells was 20 μM, which could significantly induce cell apoptosis and arrest the cells in G2/M phase. Metabolomics results showed that the contents of endogenous small molecules such as gamma-glutamylcysteine, 5-oxoproline, glutamic acid, reduced glutathione (GSH), oxidized glutathione (GSSG) and arachidonic acid have changed significantly. Main differential compounds were involved in the gamma-glutamyl cycle and polyunsaturated fatty acid metabolism of pancreatic cancer cell lines. Additionally, ponicidin could covalently bind to GSH in SW1990 cells to form a conjugate Pon-GSH, which further reduced the content of free GSH and GPX4 activity in cells. Notably, ponicidin dose-dependently increased levels of iron ions, malondialdehyde and reactive oxygen species in SW1990 cells, and the ferroptosis inhibitors could significantly block the effects of ponicidin on the proliferation of SW1990 cells.

CONCLUSION

Ponicidin could suppress the pancreatic cancer cell proliferation via inducing ferroptosis by inhibiting the gamma-glutamyl cycle and regulating the polyunsaturated fatty acid metabolism in SW1990 cells.

Discovery of human pancreatic lipase inhibitors from root of Rhodiola Crenulata via integrating bioactivity-guided fractionation, chemical profiling and biochemical assay

Although herbal medicines (HMs) are widely used in the prevention and treatment of obesity and obesity-associated disorders, the key constituents exhibiting anti-obesity activity and their molecular mechanisms are poorly understood. Recently, we assessed the inhibitory potentials of several HMs against human pancreatic lipase (hPL, a key therapeutic target for human obesity), among which the root-extract of Rhodiola crenulata (ERC) showed the most potent anti-hPL activity. In this study, we adopted an integrated strategy, involving bioactivity-guided fractionation techniques, chemical profiling, and biochemical assays, to identify the key anti-hPL constituents in ERC. Nine ERC fractions (retention time = 12.5–35 min), obtained using reverse-phase liquid chromatography, showed strong anti-hPL activity, while the major constituents in these bioactive fractions were subsequently identified using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS/MS). Among the identified ERC constituents, 1,2,3,4,6-penta-O-galloyl-β-d-glucopyranose (PGG) and catechin gallate (CG) showed the most potent anti-hPL activity, with pIC₅₀ values of 7.59 ± 0.03 and 7.68 ± 0.23, respectively. Further investigations revealed that PGG and CG potently inhibited hPL in a non-competitive manner, with inhibition constant (K_i) values of 0.012 and 0.082 μM, respectively. Collectively, our integrative analyses enabled us to efficiently identify and characterize the key anti-obesity constituents in ERC, as well as to elucidate their anti-hPL mechanisms. These findings provide convincing evidence in support of the anti-obesity and lipid-lowering properties of ERC.

•

The root-extract of Rhodiola crenulata (ERC) potently inhibits hPL.

•

The hPL inhibitors in ERC were characterized using an integrated panel of assays.

•

Six constituents in ERC were identified as hPL inhibitors.

•

PGG and CG are potent non-competitive hPL inhibitors (K_i < 0.1 μM).

•

The binding modes of PGG and CG were examined based on docking simulations.

Pyrido[1,2-e]purine: Design and Synthesis of Appropriate Inhibitory Candidates against the Main Protease of COVID-19

A series of tricyclic and polycyclic pyrido[1,2-e]purine derivatives were designed and synthesized via a two-step, one-pot reaction of 2,4-dichloro-5-amino-6-methylpyrimidine with pyridine under reflux conditions. Various derivatives of pyrido[1,2-e]purine were also synthesized by substituting the chlorine atom with secondary amines. After careful physiochemical and pharmacokinetic predictions, the inhibitory effects of the synthesized compounds against the main protease of SARS-CoV-2 have been evaluated by molecular docking and molecular dynamics approaches. The in silico results revealed that among all of the studied compounds, the morpholine/piperidine-substituted pyrido[1,2-e]purine derivatives are the best candidates as effective inhibitors of SARS-CoV-2.

Discovery and Characterization of the Key Constituents in Ginkgo biloba Leaf Extract With Potent Inhibitory Effects on Human UDP-Glucuronosyltransferase 1A1

Human UDP-glucuronosyltransferase 1A1 (hUGT1A1) is one of the most essential phase II enzymes in humans. Dysfunction or strong inhibition of hUGT1A1 may result in hyperbilirubinaemia and clinically relevant drug/herb-drug interactions (DDIs/HDIs). Recently, a high-throughput fluorescence-based assay was constructed by us to find the compounds/herbal extracts with strong inhibition against intracellular hUGT1A1. Following screening of over one hundred of herbal products, the extract of Ginkgo biloba leaves (GBL) displayed the most potent hUGT1A1 inhibition in HeLa-UGT1A1 cells (Hela cells overexpressed hUGT1A1). Further investigations demonstrated that four biflavones including bilobetin, isoginkgetin, sciadopitysin and ginkgetin, are key constituents responsible for hUGT1A1 inhibition in living cells. These biflavones potently inhibit hUGT1A1 in both human liver microsomes (HLM) and living cells, with the IC₅₀ values ranging from 0.075 to 0.41 μM in living cells. Inhibition kinetic analyses and docking simulations suggested that four tested biflavones potently inhibit hUGT1A1-catalyzed NHPN-O-glucuronidation in HLM via a mixed inhibition manner, showing the K_i values ranging from 0.07 to 0.74 μM. Collectively, our findings uncover the key constituents in GBL responsible for hUGT1A1 inhibition and decipher their inhibitory mechanisms against hUGT1A1, which will be very helpful for guiding the rational use of GBL-related herbal products in clinical settings.

Inhibition of Human UGT1A1-Mediated Bilirubin Glucuronidation by the Popular Flavonoids Baicalein, Baicalin and Hyperoside is responsible for Herbs (Shuang-huang-lian) -Induced Jaundice

Bilirubin-related adverse drug reactions (ADRs) or malady (e.g., jaundice) induced by some herbs rich in certain flavonoids have been widely reported. However, the causes and mechanisms of the ADRs are not well understood. The aim of this paper was to explore the mechanism of Shuang-huang-lian injections (SHL) and its major constituents-induced jaundice via inhibiting human UDP-glucuronosyltransferases1A1 (hUGT1A1)-mediated bilirubin glucuronidation. The inhibitory effects of SHL and its major constituents in the herbal medicine including baicalein (BAI), baicalin (BA) and hyperoside (HYP) on bilirubin glucuronidation were investigated. This study indicated that the average formation rates of bilirubin glucuronides (i.e., BMG1, BMG2, BDG) displayed significant differences (P <0.05), specially, the formation of mono-glucuronides (BMGs) was favored regardless whether an inhibitor was absent or presence. SHL, BAI, BA and HYP dose-dependently inhibit bilirubin glucuronidation, showing the IC₅₀ values against total bilirubin glucuronidation (TBG) were in the range of (7.69 {plus minus} 0.94) μg/mL - (37.09 {plus minus} 2.03) μg/mL, (4.51 {plus minus} 0.27) μM - (20.84 {plus minus} 1.99) μM, (22.36 {plus minus} 5.74) μM - (41.35 {plus minus} 2.40) μM, and (15.16 {plus minus} 1.12) μM - (42.80 {plus minus} 2.63) μM for SHL, BAI, BA, and HYP, respectively. Both inhibition kinetics assays and molecular docking simulations suggested that SHL, BAI, BA, and HYP significantly inhibited hUGT1A1-mediated bilirubin glucuronidation via a mixed-type inhibition. Collectively, some naturally occurring flavonoids (BAI, BA and HYP) in SHL have been identified as the inhibitors against hUGT1A1-mediated bilirubin glucuronidation, which well-explains the bilirubin-related ADRs or malady triggered by SHL in clinical settings. Significance Statement Herbal products and their components (e.g., flavonoids), which been widely used in the whole world, may cause liver injury. As a commonly used herbal products rich in flavonoids, Shuang-huang-lian injections (SHL), easily lead to symptoms of liver injury (e.g., jaundice) owing to significant inhibition of hUGT1A1-mediated bilirubin glucuronidation by its flavonoid components (i.e., baicalein, baicalin, hyperoside). Herbs-induced bilirubin-related ADRs and its associated clinical significance should be seriously considered.

Discovery and Characterization of the Naturally Occurring Inhibitors Against Human Pancreatic Lipase in Ampelopsis grossedentata

Pancreatic lipase (PL) inhibitor therapy has been validated as an efficacious way for preventing and treating obesity and overweight. In the past few decades, porcine PL (pPL) is widely used as the enzyme source for screening the PL inhibitors, which generates a wide range of pPL inhibitors. By contrast, the efficacious inhibitors against human PL (hPL) are rarely reported. This study aims to discover the naturally occurring hPL inhibitors from edible herbal medicines (HMs) and to characterize the inhibitory mechanisms of the newly identified hPL inhibitors. Following the screening of the inhibition potentials of more than 100 HMs against hPL, Ampelopsis grossedentata extract (AGE) displayed the most potent hPL inhibition activity. After that, the major constituents in AGE were identified and purified, while their anti-hPL effects were assayed in vitro. The results clearly showed that two abundant constituents in AGE (dihydromyricetin and iso-dihydromyricetin) were moderate hPL inhibitors, while myricetin and quercetin were strong hPL inhibitors [half-maximal inhibitory concentration (IC50) values were around 1.5 μM]. Inhibition kinetic analyses demonstrated that myricetin and quercetin potently inhibited hPL-catalyzed near-infrared fluorogenic substrate of human pancreatic lipase (DDAO-ol) hydrolysis in a non-competitive inhibition manner, with Ki values of 2.04 and 2.33 μM, respectively. Molecular dynamics simulations indicated that myricetin and quercetin could stably bind on an allosteric site of hPL. Collectively, this study reveals the key anti-obesity constituents in AGE and elucidates their inhibitory mechanisms against hPL, which offers convincing evidence to support the anti-obesity and lipid-lowering effects of this edible herb.

Theta-Defensins to Counter COVID-19 as Furin Inhibitors: In Silico Efficiency Prediction and Novel Compound Design

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was characterized as a pandemic by the World Health Organization (WHO) in Dec. 2019. SARS-CoV-2 binds to the cell membrane through spike proteins on its surface and infects the cell. Furin, a host-cell enzyme, possesses a binding site for the spike protein. Thus, molecules that block furin could potentially be a therapeutic solution. Defensins are antimicrobial peptides that can hypothetically inhibit furin because of their arginine-rich structure. Theta-defensins, a subclass of defensins, have attracted attention as drug candidates due to their small size, unique structure, and involvement in several defense mechanisms. Theta-defensins could be a potential treatment for COVID-19 through furin inhibition and an anti-inflammatory mechanism. Note that inflammatory events are a significant and deadly condition that could happen at the later stages of COVID-19 infection. Here, the potential of theta-defensins against SARS-CoV-2 infection was investigated through in silico approaches. Based on docking analysis results, theta-defensins can function as furin inhibitors. Additionally, a novel candidate peptide against COVID-19 with optimal properties regarding antigenicity, stability, electrostatic potential, and binding strength was proposed. Further in vitro/in vivo investigations could verify the efficiency of the designed novel peptide.

Structure-Guided Discovery of the Novel Covalent Allosteric Site and Covalent Inhibitors of Fructose-1,6-Bisphosphate Aldolase to Overcome the Azole Resistance of Candidiasis

Fructose-1,6-bisphosphate aldolase (FBA) represents an attractive new antifungal target. Here, we employed a structure-based optimization strategy to discover a novel covalent binding site (C292 site) and the first-in-class covalent allosteric inhibitors of FBA from Candida albicans (CaFBA). Site-directed mutagenesis, liquid chromatography-mass spectrometry, and the crystallographic structures of APO-CaFBA, CaFBA-G3P, and C157S-2a4 revealed that S268 is an essential pharmacophore for the catalytic activity of CaFBA, and L288 is an allosteric regulation switch for CaFBA. Furthermore, most of the CaFBA covalent inhibitors exhibited good inhibitory activity against azole-resistant C. albicans, and compound 2a11 can inhibit the growth of azole-resistant strains 103 with the MIC₈₀ of 1 μg/mL. Collectively, this work identifies a new covalent allosteric site of CaFBA and discovers the first generation of covalent inhibitors for fungal FBA with potent inhibitory activity against resistant fungi, establishing a structural foundation and providing a promising strategy for the design of potent antifungal drugs.

Computational prediction of protein functional sites-Applications in biotechnology and biomedicine

There are many computational approaches for predicting protein functional sites based on different sequence and structural features. These methods are essential to cope with the sequence deluge that is filling databases with uncharacterized protein sequences. They complement the more expensive and time-consuming experimental approaches by pointing them to possible candidate positions. In many cases they are jointly used to characterize the functional sites in proteins of biotechnological and biomedical interest and eventually modify them for different purposes. There is a clear trend towards approaches based on machine learning and those using structural information, due to the recent developments in these areas. Nevertheless, "classic" methods based on sequence and evolutionary features are still playing an important role as these features are strongly related to functionality. In this review, the main approaches for predicting general functional sites in a protein are discussed, with a focus on sequence-based approaches.

Allosteric binding on nuclear receptors: Insights on screening of non-competitive endocrine-disrupting chemicals

Endocrine-disrupting chemicals (EDCs) can compete with endogenous hormones and bind to the orthosteric site of nuclear receptors (NRs), affecting normal endocrine system function and causing severe symptoms. Recently, a series of pharmaceuticals and personal care products (PPCPs) have been discovered to bind to the allosteric sites of NRs and induce similar effects. However, it remains unclear how diverse EDCs work in this new way. Therefore, we have systematically summarized the allosteric sites and underlying mechanisms based on existing studies, mainly regarding drugs belonging to the PPCP class. Advanced methods, classified as structural biology, biochemistry and computational simulation, together with their advantages and hurdles for allosteric site recognition and mechanism insight have also been described. Furthermore, we have highlighted two available strategies for virtual screening of numerous EDCs, relying on the structural features of allosteric sites and lead compounds, respectively. We aim to provide reliable theoretical and technical support for a broader view of various allosteric interactions between EDCs and NRs, and to drive high-throughput and accurate screening of potential EDCs with non-competitive effects.

In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators

Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future.

Discovery and characterization of amentoflavone as a naturally occurring inhibitor against the bile salt hydrolase produced by Lactobacillus salivarius

Bile salt hydrolases (BSHs), a group of cysteine-hydrolases produced by the gut microbes, which play a crucial role in hydrolysis of the glycine- or taurine-conjugated bile acids, have been validated...

Uncovering the Dominant Motion Modes of Allosteric Regulation Improves Allosteric Site Prediction

Allostery is an important mechanism that biological systems use to regulate function at a distant site. Allosteric drugs have attracted much attention in recent years due to their high specificity and the possibility of overcoming existing drug-resistant mutations. However, the discovery of allosteric drugs remains challenging as allosteric regulation mechanisms are not clearly understood and allosteric sites cannot be accurately predicted. In this study, we analyzed the dominant modes that determine motion correlations between allosteric and orthosteric sites using the Gaussian network model and found that motion correlations between allosteric and orthosteric sites are dominated by either fast or slow vibrational modes. This dependence of modes results from the relative locations of the two sites and local secondary structures. Based on these analyses, we developed CorrSite2.0 to predict allosteric sites by taking the maximum of the Z-scores calculated from using either slow or fast modes. The prediction accuracy of CorrSite2.0 outperformed other commonly used allosteric site prediction methods with prediction accuracy over 90.0%. Our study uncovers the relationship of protein structure, dynamics, and allosteric regulation and demonstrates that using the dominant motion modes greatly improves allosteric site prediction accuracy. CorrSite2.0 has been integrated into the CavityPlus web server, which can be accessed at http://www.pkumdl.cn/cavityplus. CorrSite2.0 provides a powerful and user-friendly tool for allosteric drug and protein design.

Dietary Intake of Flavonoids and Carotenoids Is Associated with Anti-Depressive Symptoms: Epidemiological Study and In Silico-Mechanism Analysis

Flavonoids and carotenoids are bioactive compounds that have protective effects against depressive symptoms. Flavonoids and carotenoids are the two main types of antioxidant phytochemicals. This study investigated the association between flavonoid and carotenoid intake and depressive symptoms in middle-aged Korean females. We analyzed the mechanism of these associations using an in silico method. Depressive symptoms were screened using the Beck Depression Inventory-II (BDI-II), and flavonoid and carotenoid intake were assessed using a semi-quantitative food frequency questionnaire. Using a multivariate logistic regression model, we found that flavones, anthocyanins, individual phenolic compounds, lycopene, and zeaxanthin were negatively associated with depressive symptoms. In silico analysis showed that most flavonoids have high docking scores for monoamine oxidase A (MAOA) and monoamine oxidase B (MAOB), which are two important drug targets in depression. The results of the docking of brain-derived neurotrophic factor (BDNF) and carotenoids suggested the possibility of allosteric activation of BDNF by carotenoids. These results suggest that dietary flavonoids and carotenoids can be utilized in the treatment of depressive symptoms.

In Silico Characterization and Virtual Screening of GntR/HutC Family Transcriptional Regulator MoyR: A Potential Monooxygenase Regulator in Mycobacterium tuberculosis

Simple Summary

In an era where the world faces new diseases and pathogens, another emerging challenge is neglected pathogens becoming more notorious. Transcriptional regulators play a vital role in the pathogenesis and survival of these pathogens. Hence, characterizing transcriptional regulators, either in vitro or in silico, is of great importance. Here, we present the first structural characterization of a GntR/HutC regulator in Mycobacterium tuberculosis via in silico methods. We have suggested its possible role and potential as a drug target as well as identified possible drug leads that can be used for further improvements.

Abstract

Mycobacterium tuberculosis is a well-known pathogen due to the emergence of drug resistance associated with it, where transcriptional regulators play a key role in infection, colonization and persistence. The genome of M. tuberculosis encodes many transcriptional regulators, and here we report an in-depth in silico characterization of a GntR regulator: MoyR, a possible monooxygenase regulator. Homology modelling provided a reliable structure for MoyR, showing homology with a HutC regulator DasR from Streptomyces coelicolor. In silico physicochemical analysis revealed that MoyR is a cytoplasmic protein with higher thermal stability and higher pI. Four highly probable binding pockets were determined in MoyR and the druggability was higher in the orthosteric binding site consisting of three conserved critical residues: TYR179, ARG223 and GLU234. Two highly conserved leucine residues were identified in the effector-binding region of MoyR and other HutC homologues, suggesting that these two residues can be crucial for structure stability and oligomerization. Virtual screening of drug leads resulted in four drug-like compounds with greater affinity to MoyR with potential inhibitory effects for MoyR. Our findings support that this regulator protein can be valuable as a therapeutic target that can be used for developing drug leads.

ePharmer: An integrated and graphical software for pharmacophore-based virtual screening

Pharmacophore-based virtual screening (VS) has emerged as an efficient computer-aided drug design technique when appraising multiple ligands with similar structures or targets with unknown crystal structures. Current pharmacophore modeling and analysis software suffers from inadequate integration of mainstream methods and insufficient user-friendly program interface. In this study, we propose a stand-alone, integrated, graphical software for pharmacophore-based VS, termed ePharmer. Both ligand-based and structure-based pharmacophore generation methods were integrated into a compact architecture. Fine-grained modules were carefully organized into the computing, integration, and visualization layers. Graphical design covered the global user interface and specific user operations including editing, evaluation, and task management. Metabolites prediction analysis with the chosen VS result is provided for preselection of wet experiments. Moreover, the underlying computing units largely adopted the preliminary work of our research team. The presented software is currently in client use and will be released for both professional and nonexpert users. Experimental results verified the favorable computing capability, user convenience, and case performance of the proposed software.

Insights into the structure and function of the rate-limiting enzyme of chlorophyll degradation through analysis of a bacterial Mg-dechelatase homolog

The Mg-dechelatase enzyme encoded by the Stay-Green (SGR) gene catalyzes Mg²⁺ dechelation from chlorophyll a. This reaction is the first committed step of chlorophyll degradation pathway in plants and is thus indispensable for the process of leaf senescence. There is no structural information available for this or its related enzymes. This study aims to provide insights into the structure and reaction mechanism of the enzyme through biochemical and computational analysis of an SGR homolog from the Chloroflexi Anaerolineae (AbSGR-h). Recombinant AbSGR-h with its intact sequence and those with mutations were overexpressed in Escherichia coli and their Mg-dechelatase activity were compared. Two aspartates - D34 and D62 were found to be essential for catalysis, while R26, Y28, T29 and D114 were responsible for structural maintenance. Gel filtration analysis of the recombinant AbSGR-h indicates that it forms a homo-oligomer. The three-dimensional structure of AbSGR-h was predicted by a deep learning-based method, which was evaluated by protein structure quality evaluation programs while structural stability of wild-type and mutant forms were investigated through molecular dynamics simulations. Furthermore, in concordance with the results of enzyme assay, molecular docking concluded the significance of D34 in ligand interaction. By combining biochemical analysis and computational prediction, this study unveils the detailed structural characteristics of the enzyme, including the probable pocket of interaction and the residues of structural and functional importance. It also serves as a basis for further studies on Mg-dechelatase such as elucidation of its reaction mechanism or inhibitor screening.

The tumor suppressor activity of DLC1 requires the interaction of its START domain with Phosphatidylserine, PLCD1, and Caveolin-1

BACKGROUND

DLC1, a tumor suppressor gene that is downregulated in many cancer types by genetic and nongenetic mechanisms, encodes a protein whose RhoGAP and scaffolding activities contribute to its tumor suppressor functions. The role of the DLC1 START (StAR-related lipid transfer; DLC1-START) domain, other than its binding to Caveolin-1, is poorly understood. In other START domains, a key function is that they bind lipids, but the putative lipid ligand for DLC1-START is unknown.

METHODS

Lipid overlay assays and Phosphatidylserine (PS)-pull down assays confirmed the binding of DLC1-START to PS. Co-immunoprecipitation studies demonstrated the interaction between DLC1-START and Phospholipase C delta 1 (PLCD1) or Caveolin-1, and the contribution of PS to those interactions. Rho-GTP, cell proliferation, cell migration, and/or anchorage-independent growth assays were used to investigate the contribution of PS and PLCD1, or the implications of TCGA cancer-associated DLC1-START mutants, to DLC1 functions. Co-immunoprecipitations and PS-pull down assays were used to investigate the molecular mechanisms underlying the impaired functions of DLC1-START mutants. A structural model of DLC1-START was also built to better understand the structural implications of the cancer-associated mutations in DLC1-START.

RESULTS

We identified PS as the lipid ligand for DLC1-START and determined that DLC1-START also binds PLCD1 protein in addition to Caveolin-1. PS binding contributes to the interaction of DLC1 with Caveolin-1 and with PLCD1. The importance of these activities for tumorigenesis is supported by our analysis of 7 cancer-associated DLC1-START mutants, each of which has reduced tumor suppressor function but retains wildtype RhoGAP activity. Our structural model of DLC1-START indicates the mutants perturb different elements within the structure, which is correlated with our experimental findings that the mutants are heterogenous with regard to the deficiency of their binding properties. Some have reduced PS binding, others reduced PLCD1 and Caveolin-1 binding, and others are deficient for all of these properties.

CONCLUSION

These observations highlight the importance of DLC1-START for the tumor suppressor function of DLC1 that is RhoGAP-independent. They also expand the versatility of START domains, as DLC1-START is the first found to bind PS, which promotes the binding to other proteins.

Targeting RAS phosphorylation in cancer therapy: Mechanisms and modulators

RAS, a member of the small GTPase family, functions as a binary switch by shifting between inactive GDP-loaded and active GTP-loaded state. RAS gain-of-function mutations are one of the leading causes in human oncogenesis, accounting for ∼19% of the global cancer burden. As a well-recognized target in malignancy, RAS has been intensively studied in the past decades. Despite the sustained efforts, many failures occurred in the earlier exploration and resulted in an ‘undruggable’ feature of RAS proteins. Phosphorylation at several residues has been recently determined as regulators for wild-type and mutated RAS proteins. Therefore, the development of RAS inhibitors directly targeting the RAS mutants or towards upstream regulatory kinases supplies a novel direction for tackling the anti-RAS difficulties. A better understanding of RAS phosphorylation can contribute to future therapeutic strategies. In this review, we comprehensively summarized the current advances in RAS phosphorylation and provided mechanistic insights into the signaling transduction of associated pathways. Importantly, the preclinical and clinical success in developing anti-RAS drugs targeting the upstream kinases and potential directions of harnessing allostery to target RAS phosphorylation sites were also discussed.

Methylophiopogonanone A is a naturally occurring broad-spectrum inhibitor against human UDP-glucuronosyltransferases: Inhibition behaviours and implication in herb-drug interactions

Methylophiopogonanone A (MOA) is an abundant homoisoflavonoid in the Chinese herb Ophiopogonis Radix. Recent investigations revealed that MOA inhibited several human cytochrome P450 enzymes (CYPs) and stimulated OATP1B1. However, the inhibitory effects of MOA on phase II drug-metabolizing enzymes, such as human UDP-glucuronosyltransferases (hUGTs), have not been well investigated. Herein, the inhibition potentials of MOA on hUGTs were assessed. The results clearly demonstrated that MOA dose-dependently inhibited all tested hUGTs including UGT1A1 (IC₅₀  = 1.23 μM), one of the most important detoxification enzymes in humans. Further investigations showed that MOA strongly inhibited UGT1A1-catalysed NHPH-O-glucuronidation in a range of biological settings including hUGT1A1, human liver microsomes (HLM) and HeLa cells overexpressing UGT1A1. Inhibition kinetic analyses demonstrated that MOA competitively inhibited UGT1A1-catalysed NHPH-O-glucuronidation in both hUGT1A1 and HLM, with K_i values of 0.52 and 1.22 μM, respectively. Collectively, our findings expanded knowledge of the interactions between MOA and human drug-metabolizing enzymes, which would be very helpful for guiding the use of MOA-related herbal products in clinical settings.

Improved machine learning scoring functions for identification of Electrophorus electricus's acetylcholinesterase inhibitors

Structure-based drug design (SBDD) is an important in silico technique, used for the identification of enzyme inhibitors. Acetylcholinesterase (AChE), obtained from Electrophorus electricus (ee), is widely used for the screening of AChE inhibitors. It shares structural homology with the AChE of human and other organisms. Till date, the three-dimensional crystal structure of enzyme from ee is not available that makes it challenging to use the SBDD approach for the identification of inhibitors. A homology model was developed for eeAChE in the present study, followed by its structural refinement through energy minimisation. The docking protocol was developed using a grid dimension of 84 × 66 × 72 and grid point spacing of 0.375 Å for eeAChE. The protocol was validated by redocking a set of co-crystallised inhibitors obtained from mouse AChE, and their interaction profiles were compared. The results indicated a poor performance of the Autodock scoring function. Hence, a batch of machine learning-based scoring functions were developed. The validation results displayed an accuracy of 81.68 ± 1.73% and 82.92 ± 3.05% for binary and multiclass classification scoring function, respectively. The regression-based scoring function produced [Formula: see text] and [Formula: see text] values of 0.94, 0.635 and 0.634, respectively.

In Silico Structural Modeling and Analysis of Interactions of Tremellomycetes Cytochrome P450 Monooxygenases CYP51s with Substrates and Azoles

Cytochrome P450 monooxygenase CYP51 (sterol 14α-demethylase) is a well-known target of the azole drug fluconazole for treating cryptococcosis, a life-threatening fungal infection in immune-compromised patients in poor countries. Studies indicate that mutations in CYP51 confer fluconazole resistance on cryptococcal species. Despite the importance of CYP51 in these species, few studies on the structural analysis of CYP51 and its interactions with different azole drugs have been reported. We therefore performed in silico structural analysis of 11 CYP51s from cryptococcal species and other Tremellomycetes. Interactions of 11 CYP51s with nine ligands (three substrates and six azoles) performed by Rosetta docking using 10,000 combinations for each of the CYP51-ligand complex (11 CYP51s × 9 ligands = 99 complexes) and hierarchical agglomerative clustering were used for selecting the complexes. A web application for visualization of CYP51s' interactions with ligands was developed (http://bioshell.pl/azoledocking/). The study results indicated that Tremellomycetes CYP51s have a high preference for itraconazole, corroborating the in vitro effectiveness of itraconazole compared to fluconazole. Amino acids interacting with different ligands were found to be conserved across CYP51s, indicating that the procedure employed in this study is accurate and can be automated for studying P450-ligand interactions to cater for the growing number of P450s.

Probe into the Molecular Mechanism of Ibuprofen Interaction with Warfarin Bound to Human Serum Albumin in Comparison to Ascorbic and Salicylic Acids: Allosteric Inhibition of Anticoagulant Release

The release of anticoagulant drugs such as warfarin from human serum albumin (HSA) has been important not only mechanistically but also clinically for patients who take multiple drugs simultaneously. In this study, the role of some commonly used drugs, including s-ibuprofen, ascorbic acid, and salicylic acid, was investigated in the release of warfarin bound to HSA in silico. The effects of the aforementioned drugs on the HSA-warfarin complex were investigated with molecular dynamics (MD) simulations using two approaches; in the first perspective, molecular docking was used to model the interaction of each drug with the HSA-warfarin complex, and in the second approach, drugs were positioned randomly and distant from the binary complex (HSA-warfarin) in a physiologically relevant concentration. The results obtained from both approaches indicated that s-ibuprofen and ascorbic acid both displayed allosteric effects on the release of warfarin from HSA. Although ascorbic acid aided in warfarin release, leading to destabilization of HSA, ibuprofen demonstrated a stabilizing effect on releasing the anticoagulant drug through several noncovalent interactions, including hydrophobic, electrostatic, and hydrogen-bonding interactions with the protein. The calculated binding free energy and energy contribution of involved residues using the molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) method, along with root mean square deviation (RMSD) values, protein gyration, and free energy surface (FES) mapping of the protein, provided valuable details on the nature of the interactions of each drug on the release of warfarin from HSA. These results can provide important information on the mechanisms of anticoagulant release that has not been revealed in molecular details previously.

Computational approaches to predict protein functional families and functional sites

Understanding the mechanisms of protein function is indispensable for many biological applications, such as protein engineering and drug design. However, experimental annotations are sparse, and therefore, theoretical strategies are needed to fill the gap. Here, we present the latest developments in building functional subclassifications of protein superfamilies and using evolutionary conservation to detect functional determinants, for example, catalytic-, binding- and specificity-determining residues important for delineating the functional families. We also briefly review other features exploited for functional site detection and new machine learning strategies for combining multiple features.

ProteinLens: a web-based application for the analysis of allosteric signalling on atomistic graphs of biomolecules

The investigation of allosteric effects in biomolecular structures is of great current interest in diverse areas, from fundamental biological enquiry to drug discovery. Here we present ProteinLens, a user-friendly and interactive web application for the investigation of allosteric signalling based on atomistic graph-theoretical methods. Starting from the PDB file of a biomolecule (or a biomolecular complex) ProteinLens obtains an atomistic, energy-weighted graph description of the structure of the biomolecule, and subsequently provides a systematic analysis of allosteric signalling and communication across the structure using two computationally efficient methods: Markov Transients and bond-to-bond propensities. ProteinLens scores and ranks every bond and residue according to the speed and magnitude of the propagation of fluctuations emanating from any site of choice (e.g. the active site). The results are presented through statistical quantile scores visualised with interactive plots and adjustable 3D structure viewers, which can also be downloaded. ProteinLens thus allows the investigation of signalling in biomolecular structures of interest to aid the detection of allosteric sites and pathways. ProteinLens is implemented in Python/SQL and freely available to use at: www.proteinlens.io.

A new non-classical fold of varroa odorant-binding proteins reveals a wide open internal cavity

Odorant-binding proteins (OBPs), as they occur in insects, form a distinct class of proteins that apparently has no closely related representatives in other animals. However, ticks, mites, spiders and millipedes contain genes encoding proteins with sequence similarity to insect OBPs. In this work, we have explored the structure and function of such non-insect OBPs in the mite Varroa destructor, a major pest of honey bee. Varroa OBPs present six cysteines paired into three disulphide bridges, but with positions in the sequence and connections different from those of their insect counterparts. VdesOBP1 structure was determined in two closely related crystal forms and appears to be a monomer. Its structure assembles five α-helices linked by three disulphide bridges, one of them exhibiting a different connection as compared to their insect counterparts. Comparison with classical OBPs reveals that the second of the six α-helices is lacking in VdesOBP1. Ligand-binding experiments revealed molecules able to bind only specific OBPs with a moderate affinity, suggesting that either optimal ligands have still to be identified, or post-translational modifications present in the native proteins may be essential for modulating binding activity, or else these OBPs might represent a failed attempt in evolution and are not used by the mites.

Design, Synthesis and Evaluation of a Series of 1,5-Diaryl-1,2,3-triazole-4-carbohydrazones as Inhibitors of the YAP-TAZ/TEAD Complex

Starting from our previously reported hit, a series of 1,5-diaryl-1,2,3-triazole-4-carbohydrazones were synthesized and evaluated as inhibitors of the YAP/TAZ-TEAD complex. Their binding to hTEAD2 was confirmed by nanodifferential scanning fluorimetry, and some of the compounds were also found to moderately disrupt the YAP-TEAD interaction, as assessed by a fluorescence polarization assay. A TEAD luciferase gene reporter assay performed in HEK293T cells and RTqPCR measurements in MDA-MB231 cells showed that these compounds inhibit YAP/TAZ-TEAD activity to cells in the micromolar range. In spite of the cytotoxic effects displayed by some of the compounds of this series, they are still good starting points and can be suitably modified into an effective and viable YAP-TEAD disruptor in the future.

Druggability of cavity pockets within SARS-CoV-2 spike glycoprotein and pharmacophore-based drug discovery

Aim: Virus spike glycoprotein of SARS-CoV-2 is a good target for drug discovery. Objective: To examine the potential for druggability of spike protein for pharmacophore-based drug discovery and to investigate the binding affinity of natural products with SARS-CoV-2 spike protein. Methods: Druggable cavities were searched though CavityPlus. A pharmacophore was built and used for hit identification. Autodock Vina was used to evaluate the hits' affinities. 10 chemical derivatives were also made from the chemical backbone to optimize the lead compound. Results: 10 druggable cavities were found within the glycoprotein spike. Only one cavity with the highest score at the binding site was selected for pharmacophore extraction. Hit identification resulted in the identification of 410 hits. Discussion: This study provides a druggable region within viral glycoprotein and a candidate compound to block viral entry.

Computational Identification of a Putative Allosteric Binding Pocket in TMPRSS2

Camostat, nafamostat, and bromhexine are inhibitors of the transmembrane serine protease TMPRSS2. The inhibition of TMPRSS2 has been shown to prevent the viral infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other viruses. However, while camostat and nafamostat inhibit TMPRSS2 by forming a covalent adduct, the mode of action of bromhexine remains unclear. TMPRSS2 is autocatalytically activated from its inactive form, zymogen, through a proteolytic cleavage that promotes the binding of Ile256 to a putative allosteric pocket (A-pocket). Computer simulations, reported here, indicate that Ile256 binding induces a conformational change in the catalytic site, thus providing the atomistic rationale to the activation process of the enzyme. Furthermore, computational docking and molecular dynamics simulations indicate that bromhexine competes with the N-terminal Ile256 for the same binding site, making it a potential allosteric inhibitor. Taken together, these findings provide the atomistic basis for the development of more selective and potent TMPRSS2 inhibitors.

Discovery of naturally occurring inhibitors against SARS-CoV-2 3CLpro from Ginkgo biloba leaves via large-scale screening

3-Chymotrypsin-like protease (3CL^pro) is a virally encoded main proteinase that is pivotal for the viral replication across a broad spectrum of coronaviruses. This study aims to discover the naturally occurring SARS-CoV-2 3CL^pro inhibitors from herbal constituents, as well as to investigate the inhibitory mechanism of the newly identified efficacious SARS-CoV-2 3CL^pro inhibitors. Following screening of the inhibitory potentials of eighty herbal products against SARS-CoV-2 3CL^pro, Ginkgo biloba leaves extract (GBLE) was found with the most potent SARS-CoV-2 3CL^pro inhibition activity (IC₅₀ = 6.68 μg/mL). Inhibition assays demonstrated that the ginkgolic acids (GAs) and the bioflavones isolated from GBLE displayed relatively strong SARS-CoV-2 3CL^pro inhibition activities (IC₅₀ < 10 μM). Among all tested constituents, GA C15:0, GA C17:1 and sciadopitysin displayed potent 3CL^pro inhibition activities, with IC₅₀ values of less than 2 μM. Further inhibition kinetic studies and docking simulations clearly demonstrated that two GAs and sciadopitysin strongly inhibit SARS-CoV-2 3CL^provia a reversible and mixed inhibition manner. Collectively, this study found that both GBLE and the major constituents in this herbal product exhibit strong SARS-CoV-2 3CL^pro inhibition activities, which offer several promising leading compounds for developing novel anti-COVID-19 medications via targeting on 3CL^pro.

Multiple Target Drug Design Using LigBuilder 3

Designing drugs that directly interact with multiple targets is a promising approach for treating complicated diseases. In order to successfully bind to multiple targets of different families and achieve the desired ligand efficiency, multi-target-directed ligands (MTDLs) require a higher level of diversity and complexity. De novo design strategies for creating more diverse chemical entities with desired properties may present an improved approach for developing MTDLs. In this chapter, we describe a computational protocol for developing MTDLs using the first reported multi-target de novo program, LigBuilder 3, which combines a binding site prediction module with de novo drug design and optimization modules. As an illustration of each detailed procedure, we design dual-functional compounds of two well-characterized virus enzymes, HIV protease and reverse transcriptase (PR and RT, respectively), using fragments extracted from known inhibitors. LigBuilder 3 is accessible at http://www.pkumdl.cn/ligbuilder3/ .

Transcriptome Expression of Biomineralization Genes in Littoraria flava Gastropod in Brazilian Rocky Shore Reveals Evidence of Local Adaptation

Understanding how selection shapes population differentiation and local adaptation in marine species remains one of the greatest challenges in the field of evolutionary biology. The selection of genes in response to environment-specific factors and microenvironmental variation often results in chaotic genetic patchiness, which is commonly observed in rocky shore organisms. To identify these genes, the expression profile of the marine gastropod Littoraria flava collected from four Southeast Brazilian locations in ten rocky shore sites was analyzed. In this first L. flava transcriptome, 250,641 unigenes were generated, and 24% returned hits after functional annotation. Independent paired comparisons between 1) transects, 2) sites within transects, and 3) sites from different transects were performed for differential expression, detecting 8,622 unique differentially expressed genes. Araçá (AR) and São João (SJ) transect comparisons showed the most divergent gene products. For local adaptation, fitness-related differentially expressed genes were chosen for selection tests. Nine and 24 genes under adaptative and purifying selection, respectively, were most related to biomineralization in AR and chaperones in SJ. The biomineralization-genes perlucin and gigasin-6 were positively selected exclusively in the site toward the open ocean in AR, with sequence variants leading to pronounced protein structure changes. Despite an intense gene flow among L. flava populations due to its planktonic larva, gene expression patterns within transects may be the result of selective pressures. Our findings represent the first step in understanding how microenvironmental genetic variation is maintained in rocky shore populations and the mechanisms underlying local adaptation in marine species.

Identification of novel allosteric binding sites and multi-targeted allosteric inhibitors of receptor and non-receptor tyrosine kinases using a computational approach

EGFR1, VEGFR2, Bcr-Abl and Src kinases are key drug targets in non-small cell lung cancer (NSCLC), bladder cancer, pancreatic cancer, CML, ALL, colorectal cancer, etc. The available drugs targeting these kinases have limited therapeutic efficacy due to novel mutations resulting in drug resistance and toxicity, as they target ATP binding site. Allosteric drugs have shown promising results in overcoming drug resistance, but the discovery of allosteric drugs is challenging. The allosteric binding pockets are difficult to predict, as they are generally associated with high energy conformations and regulate protein function in yet unknown mechanisms. In addition, the discovery of drugs using conventional methods takes long time and goes through several challenges, putting the lives of many cancer patients at risk. Therefore, the aim of the present work was to apply the most successful, drug repurposing approach in combination with computational methods to identify kinase inhibitors targeting novel allosteric sites on protein structure and assess their potential multi-kinase binding affinity. Multiple crystal structures belonging to EGFR1, VEGFR2, Bcr-Abl and Src tyrosine kinases were selected, including mutated, inhibitor bound and allosteric conformations to identify potential leads, close to physiological conditions. Interestingly the potential inhibitors identified were peptides. The drugs identified in this study could be used in therapy as a single multi-kinase inhibitor or in a combination of single kinase inhibitors after experimental validation. In addition, we have also identified new hot spots that are likely to be druggable allosteric sites for drug discovery of kinase-specific drugs in the future.Communicated by Ramaswamy H. Sarma.

Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy

Probing protein surfaces to accurately predict the binding site and conformation of a small molecule is a challenge currently addressed through mainly two different approaches: blind docking and cavity detection-guided docking. Although cavity detection-guided blind docking has yielded high success rates, it is less practical when a large number of molecules must be screened against many detected binding sites. On the other hand, blind docking allows for simultaneous search of the whole protein surface, which however entails the loss of accuracy and speed. To bridge this gap, in this study, we developed and tested BLinDPyPr, an automated pipeline which uses FTMap and DOCK6 to perform a hybrid blind docking strategy. Through our algorithm, FTMap docked probe clusters are converted into DOCK6 spheres for determining binding regions. Because these spheres are solely derived from FTMap probes, their locations are contained in and specific to multiple potential binding pockets, which become the regions that are simultaneously probed and chosen by the search algorithm based on the properties of each candidate ligand. This method yields pose prediction results (45.2–54.3% success rates) comparable to those of site-specific docking with the classic DOCK6 workflow (49.7–54.3%) and is half as time-consuming as the conventional blind docking method with DOCK6.

Insights on 3D Structures of Potential Drug-targeting Proteins of SARS-CoV-2: Application of Cavity Search and Molecular Docking

The emergence of the COVID-19 has caused public health problems worldwide and there is no effective pharmacological treatment for this disease. Research on 3D models of proteins and the search for active molecular sites are important tools to assist in the discovery of effective antiviral drugs to combat COVID-19. To address this problem, the 3D protein structures of SARS-CoV 2 were analyzed and submitted to cavities research, evaluation of their druggabillity and liganbility, and applied to molecular docking studies with potential ligand candidates actually assayed against COVID-19. Eight druggable potential cavity sites were determined in model structures' PDB code, 6W4B, 6VWW, 6W01, 6M3M, and 6VYO, and these are the good alternatives to be characterized as targets for antiviral compounds. The good cavity model of the protease 3D structure was used in molecular docking, and this allowed verifying the theoric interactions of this protein and lopinavir and ritonavir antiviral drugs. These results may assist in the use of 3D protein models in drug design studies aiming to develop drugs against the COVID-19 pandemic.