The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins

Anti-inflammatory and antiophidic effects of extract of Hymenaea eriogyne benth and structure-activity relationship prediction of the major markers in silico

ETHNOPHARMACOLOGICAL RELEVANCE

Hymenaea eriogyne Benth (Fabaceae) is popularly known as "Jatobá". Despite its use in folk medicine to treat inflammatory disorders, there are no descriptions that show its anti-inflammatory potential.

AIM OF THE STUDY

In this sense, this study aimed to evaluate the anti-inflammatory and antivenom action of bark and leaves extract of H. eriogyne.

MATERIALS AND METHODS

The in vivo anti-inflammatory activity was conducted by carrageenan-induced paw edema and zymosan-induced air pouch models, evaluating the edematogenic effect, leukocyte migration, protein concentration, levels of pro-inflammatory cytokines, malondialdehyde (MDA) and myeloperoxidase (MPO) activity. The antivenom potential was investigated in vitro on the enzymatic action (proteolytic, phospholipase and hyaluronidase) of Bothrops brazili and B. leucurus venom, as well as in vivo on the paw edema model induced by B. leucurus. Furthermore, the influence of its markers (astilbin and rutin) on MPO activity was investigated in silico. For molecular docking, AutodockVina, Biovia Discovery Studio, and Chimera 1.16 software were used.

RESULTS

The extracts and bark and leaves of H. eriogyne revealed a high anti-inflammatory effect, with a reduction in all inflammatory parameters evaluated. The bark extract showed superior results when compared to the leaf extract, suggesting the influence of the astilbin concentration, higher in the bark, on the anti-inflammatory action. In addition, only the H. eriogyne bark extract was able to reduce MDA, indicating an associated antioxidant effect. Regarding the in vitro antivenom action, the extracts (bark and leaves) revealed the ability to inhibit the proteolytic, phospholipase and hyaluronidase action of both bothropic venom, with a greater effect against B. leucurus venom. In vivo, extracts from the bark and leaves of H. eriogyne (50-200 mg/kg) showed antiedematogenic activity, reducing the release of MPO and pro-inflammatory cytokines, indicating the presence of bioactive components useful in controlling the inflammatory process induced by the venom. In the in silico assays, astilbin and rutin showed reversible interactions of 9 possible positions and orientations towards MPO, with affinities of -9.5 and -10.4 kcal/mol and interactions with Phe407, Gln91, His95 and Arg239, important active pockets of MPO. Rutin demonstrated more effective types of interactions with MPO.

CONCLUSION

This approach reveals for the first time the anti-inflammatory action of H. eriogyne bark and leaf extracts in vivo, as well as its antiophidic potential. Moreover, the distinct effect of pharmacogens as antioxidant agents and distinct effect of astilbin and rutin under MPO sheds light on the different anti-inflammatory mechanisms of bioactive compounds present in H. eriogyne extracts, with high potential for the prospection of new pharmacological agents.

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

Toward Unveiling Putative Binding Sites of Interleukin-33: Insights from Mixed-Solvent Molecular Dynamics Simulations of the Interleukin-1 Family

The interleukin (IL)-1 family is a major proinflammatory cytokine family, ranging from the well-studied IL-1s to the most recently discovered IL-33. As a new focus, IL-33 has attracted extensive research for its crucial immunoregulatory roles, leading to the development of notable monoclonal antibodies as clinical candidates. Efforts to develop small molecules disrupting IL-33/ST2 interaction remain highly desired but encounter challenges due to the shallow and featureless interfaces. The information from relative cytokines has shown that traditional binding site identification methods still struggle in mapping cryptic sites, necessitating dynamic approaches to uncover druggable pockets on IL-33. Here, we employed mixed-solvent molecular dynamics (MixMD) simulations with diverse-property probes to map the hotspots of IL-33 and identify potential binding sites. The protocol was first validated using the known binding sites of two IL-1 family members and then applied to the structure of IL-33. Our simulations revealed several binding sites and proposed side-chain rearrangements essential for the binding of a known inhibitor, aligning well with experimental NMR findings. Further microsecond-time scale simulations of this IL-33-protein complex unveiled distinct binding modes with varying occurrences. These results could facilitate future efforts in developing ligands to target challenging flexible pockets of IL-33 and IL-1 family cytokines in general.

In silico identification of putative druggable pockets in PRL3, a significant oncology target

Protein tyrosine phosphatases (PTP) have emerged as targets in diseases characterized by aberrant phosphorylations such as cancers. The activity of the phosphatase of regenerating liver 3, PRL3, has been linked to several oncogenic and metastatic pathways, particularly in breast, ovarian, colorectal, and blood cancers. Development of small molecules that directly target PRL3, however, has been challenging. This is partly due to the lack of structural information on how PRL3 interacts with its inhibitors. Here, computational methods are used to bridge this gap by evaluating the druggability of PRL3. In particular, web-based pocket prediction tools, DoGSite3 and FTMap, were used to identify binding pockets using structures of PRL3 currently available in the Protein Data Bank. Druggability assessment by molecular dynamics simulations with probes was also performed to validate these results and to predict the strength of binding in the identified pockets. While several druggable pockets were identified, those in the closed conformation show more promise given their volume and depth. These two pockets flank the active site loops and roughly correspond to pockets predicted by molecular docking in previous papers. Notably, druggability simulations predict the possibility of low nanomolar affinity inhibitors in these sites implying the potential to identify highly potent small molecule inhibitors for PRL3. Putative pockets identified here can be leveraged for high-throughput virtual screening to further accelerate the drug discovery against PRL3 and development of PRL3-directed therapeutics.

Unveiling crucial amino acids in the carbohydrate recognition domain of a viral protein through a structural bioinformatic approach

Carbohydrate binding modules (CBMs) are protein domains that typically reside near catalytic domains, increasing substrate-protein proximity by constraining the conformational space of carbohydrates. Due to the flexibility and variability of glycans, the molecular details of how these protein regions recognize their target molecules are not always fully understood. Computational methods, including molecular docking and molecular dynamics simulations, have been employed to investigate lectin-carbohydrate interactions. In this study, we introduce a novel approach that integrates multiple computational techniques to identify the critical amino acids involved in the interaction between a CBM located at the tip of bacteriophage J-1's tail and its carbohydrate counterparts. Our results highlight three amino acids that play a significant role in binding, a finding we confirmed through in vitro experiments. By presenting this approach, we offer an intriguing alternative for pinpointing amino acids that contribute to protein-sugar interactions, leading to a more thorough comprehension of the molecular determinants of protein-carbohydrate interactions.

The PARP inhibitor rucaparib blocks SARS-CoV-2 virus binding to cells and the immune reaction in models of COVID-19

BACKGROUND AND PURPOSE

To date, there are limited options for severe Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2 virus. As ADP-ribosylation events are involved in regulating the life cycle of coronaviruses and the inflammatory reactions of the host; we have, here, assessed the repurposing of registered PARP inhibitors for the treatment of COVID-19.

EXPERIMENTAL APPROACH

The effects of PARP inhibitors on virus uptake were assessed in cell-based experiments using multiple variants of SARS-CoV-2. The binding of rucaparib to spike protein was tested by molecular modelling and microcalorimetry. The anti-inflammatory properties of rucaparib were demonstrated in cell-based models upon challenging with recombinant spike protein or SARS-CoV-2 RNA vaccine.

KEY RESULTS

We detected high levels of oxidative stress and strong PARylation in all cell types in the lungs of COVID-19 patients, both of which negatively correlated with lymphocytopaenia. Interestingly, rucaparib, unlike other tested PARP inhibitors, reduced the SARS-CoV-2 infection rate through binding to the conserved 493-498 amino acid region located in the spike-ACE2 interface in the spike protein and prevented viruses from binding to ACE2. In addition, the spike protein and viral RNA-induced overexpression of cytokines was down-regulated by the inhibition of PARP1 by rucaparib at pharmacologically relevant concentrations.

CONCLUSION AND IMPLICATIONS

These results point towards repurposing rucaparib for treating inflammatory responses in COVID-19.

Exploring an Intracellular Allosteric Site of CC-Chemokine Receptor 4 from 3D Models, Probe Simulations, and Mutagenesis

We applied our previously developed probe confined dynamic mapping protocol, which combines enhanced sampling molecular dynamics (MD) simulations and fragment-based approaches, to identify the binding site of GSK2239633A (N-[[3-[[3-[(5-chlorothiophen-2-yl)sulfonylamino]-4-methoxyindazol-1-yl]methyl]phenyl]methyl]-2-hydroxy-2-methylpropanamide), a selective CC-chemokine receptor type 4 (CCR4) negative allosteric modulator, using CCR4 homology and AlphaFold models. By comparing the performance across five computational models, we identified conserved (K3108.49 and Y3047.53) and non-conserved (M2436.36) residue hotspots for GSK2239633A binding, which were validated by mutagenesis and bioluminescence resonance energy transfer assay. Further analysis of 3D models and MD simulations highlighted the pair of residues 6.36 and 7.56 that might account for antagonist selectivity among chemokine receptors. Our in silico protocol provides a promising approach for characterizing ligand binding sites in membrane proteins, considering receptor dynamics and adaptability and guiding protein template selection for ligand design.

Ciwujianoside E inhibits Burkitt lymphoma cell proliferation and invasion by blocking ENO1-plasminogen interaction and TGF-β1 activation

Burkitt's lymphoma (BL) is a rare and highly aggressive B-cell non-Hodgkin lymphoma. Although the outcomes of patients with BL have greatly improved, options for patients with relapsed and refractory BL are limited. Therefore, there is an urgent need to improve BL therapeutics and to develop novel drugs with reduced toxicity. In this study, we demonstrated that enolase 1 (ENO1) is a potential novel drug target for BL treatment. We determined that ENO1 was aberrantly upregulated in BL, which was closely related to its invasiveness and poor clinical outcomes. Furthermore, using RNA interference, we demonstrated that ENO1 depletion significantly inhibited cell proliferation and invasion both in vitro and in vivo. Mechanistically, we established that ENO1 knockdown suppressed the PI3K-AKT and epithelial-mesenchymal transition (EMT) signaling pathways by reducing plasminogen (PLG) recruitment, plasmin (PL) generation, and TGF-β1 activation. Addition of activated TGF-β1 protein to the culture medium of shENO1 cells reversed the inhibitory effects on cell proliferation and invasion, as well as those on the PI3K-AKT and EMT signaling pathways. Notably, our research led to the discovery of a novel ENO1-PLG interaction inhibitor, Ciwujianoside E (L-06). L-06 effectively disrupts the interaction between ENO1 and PLG, consequently reducing PL generation and suppressing TGF-β1 activation. In both in vitro and in vivo experiments, L-06 exerted impressive antitumor effects. In summary, our study elucidated the critical role of ENO1 in BL cell proliferation and invasion and introduced a novel ENO1 inhibitor, which holds promise for improving the treatment of patients with BL in the future.

Targeting z-Crystallin by aspirin restores the sensitivity to cisplatin in resistant A2780 ovarian cancer cells

Ovarian cancer is the deadliest gynaecologic malignancies worldwide. Platinum based chemotherapy is the mainstay treatment for ovarian cancer; however, frequent recurrence and chemoresistance onset in patients with advanced diseases remain a therapeutic challenge. Although mechanisms underlying the development of chemoresistance are still ambiguous, the B-cell lymphoma-2 (Bcl-2) family is closely associated with chemoresistance in ovarian cancer. We previously disclosed that Zeta-Crystallin (CryZ) is a post-transcriptional regulator of Bcl-2 gene expression, by binding to Bcl-2 mRNA and increasing its half-life. Here, we investigated the role of CryZ as a novel therapeutic target in A2780 ovarian carcinoma cells by modulating the protein activity with acetylsalicylic acid (ASA) to restore chemosensitivity. Molecular docking and fragment-mapping based approach revealed potential interaction of ASA within CryZ protein. Inhibition of CryZ binding activity to Bcl-2 and Bcl-xl mRNA targets by ASA was demonstrated in A375 cells. Cytotoxicity assays were conducted in A2780S and A2780R ovarian cancer cells to evaluate if CryZ binding activity inhibition and CryZ silencing were able to reverse cisplatin resistance. ASA-treatment determined a downregulation of Bcl-2 and Bcl-xl mRNA levels in A2780S and A2780R cells. ASA-treatment or CryZ silencing were able to increase and restore the chemosensitivity in both sensitive and resistant A2780 ovarian cancer cells, respectively. In this research article we demonstrated that the pharmacological or genetic inhibition of CryZ restores the sensitivity to cisplatin in a model of sensitive or resistant ovarian cancer cells. These findings suggest a new gene-targeted chemotherapeutic approach to restore the cytotoxicity in drug-resistant ovarian cancers and increase the sensitivity in non-resistant cells.

Identification of a Cryptic Pocket in Methionine Aminopeptidase-II Using Adaptive Bandit Molecular Dynamics Simulations and Markov State Models

Methionine aminopeptidase-II (MetAP-II) is a metalloprotease, primarily responsible for the cotranslational removal of the N-terminal initiator methionine from the nascent polypeptide chain during protein synthesis. MetAP-II has been implicated in angiogenesis and endothelial cell proliferation and is therefore considered a validated target for cancer therapeutics. However, there is no effective drug available against MetAP-II. In this study, we employ Adaptive Bandit molecular dynamics simulations to investigate the structural dynamics of the apo and ligand-bound MetAP-II. Our results focus on the dynamic behavior of the disordered loop that is not resolved in most of the crystal structures. Further analysis of the conformational flexibility of the disordered loop reveals a hidden cryptic pocket that is predicted to be potentially druggable. The network analysis indicates that the disordered loop region has a direct signaling route to the active site. These findings highlight a new way to target MetAP-II by designing inhibitors for the allosteric site within this disordered loop region.

Epigenetic target identification strategy based on multi-feature learning

The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development.Communicated by Ramaswamy H. Sarma.

In Silico-Based Identification of Natural Inhibitors from Traditionally Used Medicinal Plants that can Inhibit Dengue Infection

Dengue fever (DF) is an endemic disease that has become a public health concern around the globe. The NS3 protease-helicase enzyme is an important target for the development of antiviral drugs against DENV (dengue virus) due to its impact on viral replication. Inhibition of the activity of the NS3 protease-helicase enzyme complex significantly inhibits the infection associated with DENV. Unfortunately, there are no scientifically approved antiviral drugs for its prevention. However, this study has been developed to find natural bioactive molecules that can block the activity of the NS3 protease-helicase enzyme complex associated with DENV infection through molecular docking, MM-GBSA (molecular mechanics-generalized born surface area), and molecular dynamics (MD) simulations. Three hundred forty-two (342) compounds selected from twenty traditional medicinal plants were retrieved and screened against the NS3 protease-helicase protein by molecular docking and MM-GBSA studies, where the top six phytochemicals have been identified based on binding affinities. The six compounds were then subjected to pharmacokinetics and toxicity analysis, and we conducted molecular dynamics simulations on three protein-ligand complexes to validate their stability. Through computational analysis, this study revealed the potential of the two selected natural bioactive inhibitors (CID-440015 and CID-7424) as novel anti-dengue agents.

Repurposing of drug molecules from FDA database against Hepatitis C virus E2 protein using ensemble docking approach

Hepatitis C virus, a member of the Flaviviridae family and genus Hepacivirus, is an enveloped, positively single stranded RNA virus. Its surface consists of a heterodimer of E1 and E2 proteins which play a crucial role in receptor binding and membrane fusion. In this study we have used in silico virtual screening by utilizing ensemble docking on the approved drugs. These drugs can bind with high efficiency to the 36 prominent conformations of the CD81 binding site clustered from a total of 3 µs MD simulation data on the E2 protein. We started with 9213 compounds from the FDA list of drugs and progressively came down to 5 compounds which have been seen to bind with very high efficiency to not only all the conformations but also the two predicted druggable pockets that encompass the CD81 binding site. MM/PBSA binding energy calculations also point to the highly stable interaction of the compounds to the E2 protein. This study may in future broaden the arsenal of therapeutics for use against HCV infection and lead to more effective care against the virus.

Unveiling potential repurposed drug candidates for Plasmodium falciparum through in silico evaluation: A synergy of structure-based approaches, structure prediction, and molecular dynamics simulations

The rise of drug resistance in Plasmodium falciparum, rendering current treatments ineffective, has hindered efforts to eliminate malaria. To address this issue, the study employed a combination of Systems Biology approach and a structure-based pharmacophore method to identify a target against P. falciparum. Through text mining, 448 genes were extracted, and it was discovered that plasmepsins, found in the Plasmodium genus, play a crucial role in the parasite's survival. The metabolic pathways of these proteins were determined using the PlasmoDB genomic database and recreated using CellDesigner 4.4.2. To identify a potent target, Plasmepsin V (PF13_0133) was selected and examined for protein-protein interactions (PPIs) using the STRING Database. Topological analysis and global-based methods identified PF13_0133 as having the highest centrality. Moreover, the static protein knockout PPIs demonstrated the essentiality of PF13_0133 in the modeled network. Due to the unavailability of the protein's crystal structure, it was modeled and subjected to a molecular dynamics simulation study. The structure-based pharmacophore modeling utilized the modeled PF13_0133 (PfPMV), generating 10 pharmacophore hypotheses with a library of active and inactive compounds against PfPMV. Through virtual screening, two potential candidates, hesperidin and rutin, were identified as potential drugs which may be repurposed as potential anti-malarial agents.

Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors

Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC50 values. The molecular docking study identified the favorable hydrophobicity contribution of phenyl and cyclohexyl groups as substituents in the enzyme allosteric site. Molecular dynamics simulations of selected protein-ligand complexes were conducted to understand derivatives' interaction modes and affinity in both active and allosteric sites. Two cinnamide compounds, 7g and 7k, were identified, with similar structures to the reference 4h allosteric site inhibitor. These compounds can guide the development of more effective arginase inhibitors as potential antileishmanial drugs.

Genetic analysis of PALB2 gene WD40 domain in canine mammary tumour patients

BACKGROUND

DNA repair mechanisms are essential for tumorigenesis and disruption of HR mechanism is an important predisposing factor of human breast cancers (BC). PALB2 is an important part of the HR. There are similarities between canine mammary tumours (CMT) and BCs. As its human counterpart, PALB2 mutations could be a predisposing factor of CMT.

OBJECTIVES

In this study, we aimed to investigate the impacts of PALB2 variants on tumorigenesis and canine mammary tumor (CMT) malignancy.

METHODS

We performed Sanger sequencing to detect germline mutations in the WD40 domain of the canine PALB2 gene in CMT patients. We conducted in silico analysis to investigate the variants, and compared the germline PALB2 mutations in humans that cause breast cancer (BC) with the variants detected in dogs with CMT.

RESULTS

We identified an intronic (c.3096+8C>G) variant, two exonic (p.A1050V and p.R1354R) variants, and a 3' UTR variant (c.4071T>C). Of these, p.R1354R and c.4071T>C novel variants were identified for the first time in this study. We found that the p.A1050V mutation had a significant effect. However, we could not determine sufficient similarity due to the differences in nucleotide/amino acid sequences between two species. Nonetheless, possible variants of human sequences in the exact location as their dog counterparts are associated with several cancer types, implying that the variants could be crucial for tumorigenesis in dogs. Our results did not show any effect of the variants on tumor malignancy.

CONCLUSIONS

The current project is the first study investigating the relationship between the PALB2 gene WD40 domain and CMTs. Our findings will contribute to a better understanding of the pathogenic mechanism of the PALB2 gene in CMTs. In humans, variant positions in canines have been linked to cancer-related phenotypes such as familial BC, endometrial tumor, and hereditary cancer predisposition syndrome. The results of bioinformatics analyses should be investigated through functional tests or case-control studies.

Simulation and Computational Study of RING Domain Mutants of BRCA1 and Ube2k in AD/PD Pathophysiology

Lysine-based post-translational modification (PTM) such as acylation, acetylation, deamination, methylation, SUMOylation, and ubiquitination has proven to be a major regulator of gene expression, chromatin structure, protein stability, protein-protein interaction, protein degradation, and cellular localization. However, besides all the PTMs, ubiquitination stands as the second most common PTM after phosphorylation that is involved in the etiology of neurodegenerative diseases (NDDs) namely, Alzheimer's disease (AD) and Parkinson's disease (PD). NDDs are characterized by the accumulation of misfolded protein aggregates in the brain that lead to disease-related gene mutation and irregular protein homeostasis. The ubiquitin-proteasome system (UPS) is in charge of degrading these misfolded proteins, which involve an interplay of E1, E2, E3, and deubiquitinase enzymes. Impaired UPS has been commonly observed in NDDs and E3 ligases are the key members of the UPS, thus, dysfunction of the same can accelerate the neurodegeneration process. Therefore, the aim of this study is firstly, to find E3 ligases that are common in both AD and PD through data mining. Secondly, to study the impact of mutation on its structure and function. The study deciphered 74 E3 ligases that were common in both AD and PD. Later, 10 hub genes were calculated of which protein-protein interaction, pathway enrichment, lysine site prediction, domain, and motif analysis were performed. The results predicted BRCA1, PML, and TRIM33 as the top three putative lysine-modified E3 ligases involved in AD and PD pathogenesis. However, based on structural characterization, BRCA1 was taken further to study RING domain mutation that inferred K32Y, K32L, K32C, K45V, K45Y, and K45G as potential mutants that alter the structural and functional ability of BRCA1 to interact with Ube2k, E2-conjugating enzyme. The most probable mutant observed after molecular dynamics simulation of 50 ns is K32L. Therefore, our study concludes BRCA1, a potential E3 ligase common in AD and PD, and RING domain mutation at sites K32 and K45 possibly disturbs its interaction with its E2, Ube2k.

Development of Allosteric Small Molecule APOBEC3B Inhibitors from In Silico Screening

APOBEC3B cytosine deaminase contributes to the mutational burdens of tumors, resulting in tumor progression and therapy resistance. Small molecule APOBEC3B inhibitors have potential to slow or mitigate these detrimental outcomes. Through molecular dynamics (MD) simulations and computational solvent mapping analysis, we identified a novel putative allosteric pocket on the C-terminal domain of APOBEC3B (A3Bctd), and virtually screened the ChemBridge Diversity Set (N~110,000) against both the active and potential allosteric sites. Selected high-scoring compounds were subsequently purchased, characterized for purity and composition, and tested in biochemical assays, which yielded 13 hit compounds. Orthogonal NMR assays verified binding to the target protein. Initial selectivity studies suggest these compounds preferentially target A3Bctd over related deaminase APOBEC3A (A3A), and MD simulations indicate this selectivity may be due to the steric repulsion from H56 that is unique to A3A. Taken together, our studies represent the first virtual screening effort against A3Bctd that has yielded candidate inhibitors suitable for further development.

SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein-Protein Interfaces

Protein-protein interactions mediate most molecular processes in the cell, offering a significant opportunity to expand the set of known druggable targets. Unfortunately, targeting these interactions can be challenging due to their typically flat and featureless interaction surfaces, which often change as the complex forms. Such surface changes may reveal hidden (cryptic) druggable pockets. Here, we analyze a set of well-characterized protein-protein interactions harboring cryptic pockets and investigate the predictive power of current computational methods. Based on our observations, we developed a new computational strategy, SWISH-X (SWISH Expanded), which combines the established cryptic pocket identification capabilities of SWISH with the rapid temperature range exploration of OPES MultiThermal. SWISH-X is able to reliably identify cryptic pockets at protein-protein interfaces while retaining its predictive power for revealing cryptic pockets in isolated proteins, such as TEM-1 β-lactamase.

Colabind: A Cloud-Based Approach for Prediction of Binding Sites Using Coarse-Grained Simulations with Molecular Probes

Binding site prediction is a crucial step in understanding protein-ligand and protein-protein interactions (PPIs) with broad implications in drug discovery and bioinformatics. This study introduces Colabind, a robust, versatile, and user-friendly cloud-based approach that employs coarse-grained molecular dynamics simulations in the presence of molecular probes, mimicking fragments of drug-like compounds. Our method has demonstrated high effectiveness when validated across a diverse range of biological targets spanning various protein classes, successfully identifying orthosteric binding sites, as well as known druggable allosteric or PPI sites, in both experimentally determined and AI-predicted protein structures, consistently placing them among the top-ranked sites. Furthermore, we suggest that careful inspection of the identified regions with a high affinity for specific probes can provide valuable insights for the development of pharmacophore hypotheses. The approach is available at https://github.com/porekhov/CG_probeMD.

Design, development, and validation of multi-epitope proteins for serological diagnosis of Zika virus infections and discrimination from dengue virus seropositivity

Zika virus (ZIKV), an arbovirus from the Flaviviridae family, is the causative agent of Zika fever, a mild and frequent oligosymptomatic disease in humans. Nonetheless, on rare occasions, ZIKV infection can be associated with Guillain-Barré Syndrome (GBS), and severe congenital complications, such as microcephaly. The oligosymptomatic disease, however, presents symptoms that are quite similar to those observed in infections caused by other frequent co-circulating arboviruses, including dengue virus (DENV). Moreover, the antigenic similarity between ZIKV and DENV, and even with other members of the Flaviviridae family, complicates serological testing due to the high cross-reactivity of antibodies. Here, we designed, produced in a prokaryotic expression system, and purified three multiepitope proteins (ZIKV-1, ZIKV-2, and ZIKV-3) for differential diagnosis of Zika. The proteins were evaluated as antigens in ELISA tests for the detection of anti-ZIKV IgG using ZIKV- and DENV-positive human sera. The recombinant proteins were able to bind and detect anti-ZIKV antibodies without cross-reactivity with DENV-positive sera and showed no reactivity with Chikungunya virus (CHIKV)- positive sera. ZIKV-1, ZIKV-2, and ZIKV-3 proteins presented 81.6%, 95%, and 66% sensitivity and 97%, 96%, and 84% specificity, respectively. Our results demonstrate the potential of the designed and expressed antigens in the development of specific diagnostic tests for the detection of IgG antibodies against ZIKV, especially in regions with the circulation of multiple arboviruses.

Guided diffusion for molecular generation with interaction prompt

Molecular generative models have exhibited promising capabilities in designing molecules from scratch with high binding affinities in a predetermined protein pocket, offering potential synergies with traditional structural-based drug design strategy. However, the generative processes of such models are random and the atomic interaction information between ligand and protein are ignored. On the other hand, the ligand has high propensity to bind with residues called hotspots. Hotspot residues contribute to the majority of the binding free energies and have been recognized as appealing targets for designed molecules. In this work, we develop an interaction prompt guided diffusion model, InterDiff to deal with the challenges. Four kinds of atomic interactions are involved in our model and represented as learnable vector embeddings. These embeddings serve as conditions for individual residue to guide the molecular generative process. Comprehensive in silico experiments evince that our model could generate molecules with desired ligand-protein interactions in a guidable way. Furthermore, we validate InterDiff on two realistic protein-based therapeutic agents. Results show that InterDiff could generate molecules with better or similar binding mode compared to known targeted drugs.

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Conservation of Hot Spots and Ligand Binding Sites in Protein Models by AlphaFold2

The neural network-based program AlphaFold2 (AF2) provides high accuracy structure prediction for a large fraction of globular proteins. An important question is whether these models are accurate enough for reliably docking small ligands. Several recent papers and the results of CASP15 reveal that local conformational errors reduce the success rates of direct ligand docking. Here, we focus on the ability of the models to conserve the location of binding hot spots, regions on the protein surface that significantly contribute to the binding free energy of the protein-ligand interaction. Clusters of hot spots predict the location and even the druggability of binding sites, and hence are important for computational drug discovery. The hot spots are determined by protein mapping that is based on the distribution of small fragment-sized probes on the protein surface and is less sensitive to local conformation than docking. Mapping models taken from the AlphaFold Protein Structure Database show that identifying binding sites is more reliable than docking, but the success rates are still 5% to 10% lower than based on mapping X-ray structures. The drop in accuracy is particularly large for models of multidomain proteins. However, both the model binding sites and the mapping results can be substantially improved by generating AF2 models for the ligand binding domains of interest rather than the entire proteins and even more if using forced sampling with multiple initial seeds. The mapping of such models tends to reach the accuracy of results obtained by mapping the X-ray structures.

Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches

Leishmania donovani is the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to control leishmaniasis. The mitochondrial primase of Leishmania donovani (LdmtPRI1) is a vital cog in the DNA replication mechanism, as the enzyme initiates the replication of the mitochondrial genome of Leishmania donovani. Hence, we target this protein as a probable drug target against leishmaniasis. The de-novo approach enabled computational prediction of the three-dimensional structure of LdmtPRI1, and its active sites were identified. Ligands from commercially available drug compounds were selected and docked against LdmtPRI1. The compounds were chosen for pharmacokinetic study and molecular dynamics simulation based on their binding energies and protein interactions. The LdmtPRI1 gene was cloned, overexpressed, and purified, and a primase activity assay was performed. The selected compounds were verified experimentally by the parasite and primase inhibition assay. Capecitabine was observed to be effective against the promastigote form of Leishmania donovani, as well as inhibiting primase activity. This study's findings suggest capecitabine might be a potential anti-leishmanial drug candidate after adequate further studies.

Tunnel-like region observed as a potential allosteric site in Staphylococcus aureus Glyceraldehyde-3-phosphate dehydrogenase

Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) catalyzing the sixth step of glycolysis has been investigated for allosteric features that might be used as potential target for specific inhibition of Staphylococcus aureus (S.aureus). X-ray structure of bacterial enzyme for which a tunnel-like opening passing through the center previously proposed as an allosteric site has been subjected to six independent 500 ns long Molecular Dynamics simulations. Harmonic bond restraints were employed at key residues to underline the allosteric feature of this region. A noticeable reduction was observed in the mobility of NAD+ binding domains when restrictions were applied. Also, a substantial decrease in cross-correlations between distant Cα fluctuations was detected throughout the structure. Mutual information (MI) analysis revealed a similar decrease in the degree of correspondence in positional fluctuations in all directions everywhere in the receptor. MI between backbone and side-chain torsional variations changed its distribution profile and decreased considerably around the catalytic sites when restraints were employed. Principal component analysis clearly showed that the restrained state sampled a narrower range of conformations than apo state, especially in the first principal mode due to restriction in the conformational flexibility of NAD+ binding domain. Clustering the trajectory based on catalytic site residues displayed a smaller repertoire of conformations for restrained state compared to apo. Representative snapshots subjected to k-shortest pathway analysis revealed the impact of bond restraints on the allosteric communication which displayed distinct optimal and suboptimal pathways for two states, where observed frequencies of critical residues Gln51 and Val283 at the proposed site changed considerably.

Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface

SARS-CoV-2, the virus that causes COVID-19, led to a global health emergency that claimed the lives of millions. Despite the widespread availability of vaccines, the virus continues to exist in the population in an endemic state which allows for the continued emergence of new variants. Most of the current vaccines target the spike glycoprotein interface of SARS-CoV-2, creating a selection pressure favoring viral immune evasion. Antivirals targeting other molecular interactions of SARS-CoV-2 can help slow viral evolution by providing orthogonal selection pressures on the virus. GRP78 is a host auxiliary factor that mediates binding of the SARS-CoV-2 spike protein to human cellular ACE2, the primary pathway of cell infection. As GRP78 forms a ternary complex with SARS-CoV-2 spike protein and ACE2, disrupting the formation of this complex is expected to hinder viral entry into host cells. Here, we developed a model of the GRP78-Spike RBD-ACE2 complex. We then used that model together with hot spot mapping of the GRP78 structure to identify the putative binding site for spike protein on GRP78. Next, we performed structure-based virtual screening of known drug/candidate drug libraries to identify binders to GRP78 that are expected to disrupt spike protein binding to the GRP78, and thereby preventing viral entry to the host cell. A subset of these compounds has previously been shown to have some activity against SARS-CoV-2. The identified hits are starting points for the further development of novel SARS-CoV-2 therapeutics, potentially serving as proof-of-concept for GRP78 as a potential drug target for other viruses.

Aminopyrimidine Derivatives as Multiflavivirus Antiviral Compounds Identified from a Consensus Virtual Screening Approach

Around three billion people are at risk of infection by the dengue virus (DENV) and potentially other flaviviruses. Worldwide outbreaks of DENV, Zika virus (ZIKV), and yellow fever virus (YFV), the lack of antiviral drugs, and limitations on vaccine usage emphasize the need for novel antiviral research. Here, we propose a consensus virtual screening approach to discover potential protease inhibitors (NS3pro) against different flavivirus. We employed an in silico combination of a hologram quantitative structure-activity relationship (HQSAR) model and molecular docking on characterized binding sites followed by molecular dynamics (MD) simulations, which filtered a data set of 7.6 million compounds to 2,775 hits. Lastly, docking and MD simulations selected six final potential NS3pro inhibitors with stable interactions along the simulations. Five compounds had their antiviral activity confirmed against ZIKV, YFV, DENV-2, and DENV-3 (ranging from 4.21 ± 0.14 to 37.51 ± 0.8 μM), displaying aggregator characteristics for enzymatic inhibition against ZIKV NS3pro (ranging from 28 ± 7 to 70 ± 7 μM). Taken together, the compounds identified in this approach may contribute to the design of promising candidates to treat different flavivirus infections.

Fragment library screening by X-ray crystallography and binding site analysis on thioredoxin glutathione reductase of Schistosoma mansoni

Schistosomiasis is caused by parasites of the genus Schistosoma, which infect more than 200 million people. Praziquantel (PZQ) has been the main drug for controlling schistosomiasis for over four decades, but despite that it is ineffective against juvenile worms and size and taste issues with its pharmaceutical forms impose challenges for treating school-aged children. It is also important to note that PZQ resistant strains can be generated in laboratory conditions and observed in the field, hence its extensive use in mass drug administration programs raises concerns about resistance, highlighting the need to search for new schistosomicidal drugs. Schistosomes survival relies on the redox enzyme thioredoxin glutathione reductase (TGR), a validated target for the development of new anti-schistosomal drugs. Here we report a high-throughput fragment screening campaign of 768 compounds against S. mansoni TGR (SmTGR) using X-ray crystallography. We observed 49 binding events involving 35 distinct molecular fragments which were found to be distributed across 16 binding sites. Most sites are described for the first time within SmTGR, a noteworthy exception being the "doorstop pocket" near the NADPH binding site. We have compared results from hotspots and pocket druggability analysis of SmTGR with the experimental binding sites found in this work, with our results indicating only limited coincidence between experimental and computational results. Finally, we discuss that binding sites at the doorstop/NADPH binding site and in the SmTGR dimer interface, should be prioritized for developing SmTGR inhibitors as new antischistosomal drugs.

Electrophilic MiniFrags Revealed Unprecedented Binding Sites for Covalent HDAC8 Inhibitors

Screening of ultra-low-molecular weight ligands (MiniFrags) successfully identified viable chemical starting points for a variety of drug targets. Here we report the electrophilic analogues of MiniFrags that allow the mapping of potential binding sites for covalent inhibitors by biochemical screening and mass spectrometry. Small electrophilic heterocycles and their N-quaternized analogues were first characterized in the glutathione assay to analyze their electrophilic reactivity. Next, the library was used for systematic mapping of potential covalent binding sites available in human histone deacetylase 8 (HDAC8). The covalent labeling of HDAC8 cysteines has been proven by tandem mass spectrometry measurements, and the observations were explained by mutating HDAC8 cysteines. As a result, screening of electrophilic MiniFrags identified three potential binding sites suitable for the development of allosteric covalent HDAC8 inhibitors. One of the hit fragments was merged with a known HDAC8 inhibitor fragment using different linkers, and the linker length was optimized to result in a lead-like covalent inhibitor.

Molecular docking and simulation studies of Chloroquine, Rimantadine and CAP-1 as potential repurposed antivirals for decapod iridescent virus 1 (DIV1)

Drug repurposing is a methodology of identifying new therapeutic use for existing drugs. It is a highly efficient, time and cost-saving strategy that offers an alternative approach to the traditional drug discovery process. Past in-silico studies involving molecular docking have been successful in identifying potential repurposed drugs for the various treatment of diseases including aquaculture diseases. The emerging shrimp hemocyte iridescent virus (SHIV) or Decapod iridescent virus 1 (DIV1) is a viral pathogen that causes severe disease and high mortality (80 %) in farmed shrimps caused serious economic losses and presents a new threat to the shrimp farming industry. Therefore, effective antiviral drugs are critically needed to control DIV1 infections. The aim of this study is to investigate the interaction of potential existing antiviral drugs, Chloroquine, Rimantadine, and CAP-1 with DIV1 major capsid protein (MCP) with the intention of exploring the potential of drug repurposing. The interaction of the DIV1 MCP and three antivirals were characterised and analysed using molecular docking and molecular dynamics simulation. The results showed that CAP-1 is a more promising candidate against DIV1 with the lowest binding energy of -8.46 kcal/mol and is more stable compared to others. We speculate that CAP-1 binding may induce the conformational changes in the DIV1 MCP structure by phosphorylating multiple residues (His123, Tyr162, and Thr395) and ultimately block the viral assembly and maturation of DIV1 MCP. To the best of our knowledge, this is the first report regarding the structural characterisation of DIV1 MCP docked with repurposing drugs.

Accurate ligand-protein docking in CASP15 using the ClusPro LigTBM server

In the ligand prediction category of CASP15, the challenge was to predict the positions and conformations of small molecules binding to proteins that were provided as amino acid sequences or as models generated by the AlphaFold2 program. For most targets, we used our template-based ligand docking program ClusPro ligTBM, also implemented as a public server available at https://ligtbm.cluspro.org/. Since many targets had multiple chains and a number of ligands, several templates, and some manual interventions were required. In a few cases, no templates were found, and we had to use direct docking using the Glide program. Nevertheless, ligTBM was shown to be a very useful tool, and by any ranking criteria, our group was ranked among the top five best-performing teams. In fact, all the best groups used template-based docking methods. Thus, it appears that the AlphaFold2-generated models, despite the high accuracy of the predicted backbone, have local differences from the x-ray structure that make the use of direct docking methods more challenging. The results of CASP15 confirm that this limitation can be frequently overcome by homology-based docking.

Salazinic Acid and Norlobaridone from the Lichen Hypotrachyna cirrhata: Antioxidant Activity, α-Glucosidase Inhibitory and Molecular Docking Studies

The present study was intended for the identification of secondary metabolites in acetone extract of the lichen Hypotrachyna cirrhata using UPLC-ESI-QToF-MS/MS and the detection of bioactive compounds. This study led to the identification of 22 metabolites based on their MS/MS spectra, accurate molecular masses, molecular formula from a comparison of the literature database (DNP), and fragmentation patterns. In addition, potent antioxidant and α-glucosidase inhibitory potentials of acetone extract of H. cirrhata motivated us to isolate 10 metabolites, which were characterized as salazinic acid (11), norlobaridone (12), atranorin (13), lecanoric acid (14), lichesterinic acid (15), protolichesterinic acid (16), methyl hematommate (17), iso-rhizonic acid (18), atranol (19), and methylatratate (20) based on their spectral data. All these isolates were assessed for their free radicals scavenging, radical-induced DNA damage, and intestinal α-glucosidase inhibitory activities. The results indicated that norlobaridone (12), lecanoric acid (14), methyl hematommate (17), and atranol (19) showed potent antioxidant activity, while depsidones (salazinic acid (11), norlobaridone (12)) and a monophenolic compound (iso-rhizonic acid, (18)) displayed significant intestinal α-glucosidase inhibitory activities (p < 0.001), which is comparable to standard acarbose. These results were further correlated with molecular docking studies, which indicated that the alkyl chain of norlobaridione (12) is hooked into the finger-like cavity of the allosteric pocket; moreover, it also established Van der Waals interactions with hydrophobic residues of the allosteric pocket. Thus, the potency of norlobaridone to inhibit α-glucosidase enzyme might be associated with its allosteric binding. Also, MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) binding free energies of salazinic acid (11) and norlobaridone (12) were superior to acarbose and may have contributed to their high activity compared to acarbose.

FASTDock: A Pipeline for Allosteric Drug Discovery

Allostery is involved in innumerable biological processes and plays a fundamental role in human disease. Thus, the exploration of allosteric modulation is crucial for research on biological mechanisms and in the development of novel therapeutics. The development of small-molecule allosteric effectors can be used as tools to probe biological mechanisms of interest. One of the main limitations in targeting allosteric sites is the difficulty in uncovering them for specific receptors. Furthermore, upon discovery of novel allosteric modulation, early lead generation is made more difficult as compared to that at orthosteric sites because there is likely no information about the types of molecules that can bind at the site. In the work described here, we present a novel drug discovery pipeline, FASTDock, which allows one to uncover ligandable sites as well as small molecules that target the given site without requiring pre-existing knowledge of ligands that can bind in the targeted site. By using a hierarchical screening strategy, this method has the potential to enable high-throughput screens of an exceptionally large database of targeted ligand space.

An Integrative Approach to Study the Inhibition of Providencia vermicola FabD Using C2-Quaternary Indolinones

Background

The present study investigates the potential bioactivity of twelve experimentally designed C-2 quaternary indolinones against Providencia spp., a bacterial group of the Enterobacteriaceae family known to cause urinary tract infections. The study aims to provide insights into the bioactive properties of the investigated compounds and their potential use in developing novel treatments against Providencia spp. The experimental design of indolinones, combined with their unique chemical structure, makes them attractive candidates for further investigation. The results of this research may contribute to the development of novel therapeutic agents to combat Providencia spp. infections.

Methods

The synthesized indolinones (moL1-moL12) are evaluated to identify any superior activity, particularly focusing on moL12, which possesses aza functionality. The antimicrobial activities of all twelve compounds are tested in triplicates against six different Gram-positive and Gram-negative organisms, including P. vermicola (P<0.05). Computational methods have been employed to assess the pharmacokinetic properties of the compounds.

Results

Among the synthesized indolinones, moL12 exhibits superior activity compared to the other compounds with similar skeleton but different functional moieties. All six strains tested, including P. vermicola, demonstrated sensitivity to moL12. Computational studies support the pharmacokinetic properties of moL12, indicating acceptable absorption, distribution, metabolism, excretion, and toxicity characteristics.

Conclusion

Utilizing the PPI approach, we have identified a promising target, FabD, in Gram-negative bacteria. Our analysis has shown that moL12 exhibits significant potential in binding with FabD, thereby, might inhibit cell wall formation, and display superior antimicrobial activity compared to other compounds. Consequently, moL12 may be a potential therapeutic agent that could be used to combat urinary tract infections caused by Providencia spp. The findings of this research hold significant promise for the development of new and effective treatments for bacterial infections.

In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases.

Therapeutic Study of Cinnamic Acid Derivative for Oxidative Stress Ablation: The Computational and Experimental Answers

This study aimed to examine the therapeutic activity of the cinnamic acid derivative KAD-7 (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) on Fe2+-induced oxidative hepatic injury via experimental and computational models. In addition, the role of ATPase and ectonucleoside triphosphate diphosphohydrolase (ENTPDase) in the coordination of cellular signals is speculated upon to proffer suitable therapeutics for metabolic stress disorder upon their inhibition. While we know little about therapeutics with flexible dual inhibitors for these protein targets, this study was designed to screen KAD-7's (N'-(2,4-dichlorobenzylidene)-3-(4-methoxyphenyl) acrylohydrazide) inhibitory potential for both protein targets. We induced oxidative hepatic damage via the incubation of hepatic tissue supernatant with 0.1 mM FeSO4 for 30 min at 37 °C. We achieved the treatment by incubating the hepatic tissues with KAD-7 under the same conditions. The catalase (CAT), glutathione (GSH), malondialdehyde (MDA), ATPase, and ENTPDase activity were all measured in the tissues. We predicted how the drug candidate would work against ATPase and ENTPDase targets using molecular methods. When hepatic injury was induced, there was a significant decrease in the levels of the GSH, CAT, and ENTPDase (p < 0.05) activities. In contrast, we found a noticeable rise in the MDA levels and ATPase activity. KAD-7 therapy resulted in lower levels of these activities overall (p < 0.05), as compared to the control levels. We found the compound to have a strong affinity for ATPase (-7.1 kcal/mol) and ENTPDase (-7.4 kcal/mol), and a better chemical reactivity than quercetin. It also met all drug-likeness parameters. Our study shows that KAD-7 can protect the liver from damage caused by FeSO4 by reducing oxidative stress and purinergic actions. Our studies indicate that KAD-7 could be developed as a therapeutic option since it can flexibly inhibit both ATPase and ENTPDase.

Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

In Silico Prediction and Biophysical Validation of Novel 14-3-3σ Homodimer Stabilizers

14-3-3σ plays an important role in controlling tumor metabolic reprogramming and cancer cell growth. However, its function is often compromised in many cancers due to its downregulation. Previous studies found that homodimerization of 14-3-3σ is critical for its activity. However, to date, it is not known if stabilization of 14-3-3σ homodimers can improve its activity or prevent its degradation. In our previous work, we have showed that GCP-Lys-OMe is a potential 14-3-3σ homodimer stabilizer. However, its stabilizing effect was not experimentally validated. Therefore, in this study, we have attempted to predict few potential peptides that can stabilize the dimeric form of 14-3-3σ using similar in silico techniques as described previously for GCP-Lys-OMe. Subsequent [1H]-CPMG NMR experiments confirmed the binding of the peptides (peptides 3, 5, 9, and 16) on 14-3-3σ, with peptide 3 showing the strongest binding. Competitive [1H]-CPMG assays further revealed that while peptide 3 does not compete with a 14-3-3σ binding peptide (ExoS) for the protein's amphipathic groove, it was found to improve ExoS binding on 14-3-3σ. When 14-3-3σ was subjected to dynamic light scattering experiments, the 14-3-3σ homodimer was found to undergo dissociation into monomers prior to aggregation. Intriguingly, the presence of peptide 3 increased 14-3-3σ stability against aggregation. Overall, our findings suggest that (1) docking accompanied by MD simulations can be used to identify potential homodimer stabilizing compounds of 14-3-3σ and (2) peptide 3 can slow down 14-3-3σ aggregation (presumably by preventing its dissociation into monomers), as well as improving the binding of 14-3-3σ to ExoS protein.

Inhibitors of Aspartate Transcarbamoylase Inhibit Mycobacterium tuberculosis Growth

Aspartate transcarbamoylase (ATCase) plays a key role in the second step of de novo pyrimidine biosynthesis in eukaryotes and has been proposed to be a target to suppress cell proliferation in E. coli, human cells and the malarial parasite. We hypothesized that a library of ATCase inhibitors developed for malarial ATCase (PfATCase) may also contain inhibitors of the tubercular ATCase and provide a similar inhibition of cellular proliferation. Of the 70 compounds screened, 10 showed single-digit micromolar inhibition in an in vitro activity assay and were tested for their effect on M. tuberculosis cell growth in culture. The most promising compound demonstrated a MIC90 of 4 μM. A model of MtbATCase was generated using the experimental coordinates of PfATCase. In silico docking experiments showed this compound can occupy a similar allosteric pocket on MtbATCase to that seen on PfATCase, explaining the observed species selectivity seen for this compound series.

Identification of novel Zika virus NS3 protease inhibitors with different inhibition modes by integrative experimental and computational approaches

Zika virus (ZIKV) infection is associated with severe neurological disorders and congenital malformation. Despite efforts to eradicate the disease, there is still neither vaccine nor approved drugs to treat ZIKV infection. The NS2B-NS3 protease is a validated drug target since it is essential to polyprotein virus maturation. In the present study, we describe an experimental screening of 2,320 compounds from the chemical library of the Muséum National d'Histoire Naturelle of Paris on ZIKV NS2B-NS3 protease. A total of 96 hits were identified with 90% or more of inhibitory activity at 10 μM. Amongst the most active compounds, five were analyzed for their inhibitory mechanisms by kinetics assays and computational approaches such as molecular docking. 2-(3-methoxyphenoxy) benzoic acid (compound 945) show characteristics of a competitive inhibition (Ki = 0.49 μM) that was corroborated by its molecular docking at the active site of the NS2B-NS3 protease. Taxifolin (compound 2292) behaves as an allosteric inhibitor whereas 3,8,9-trihydroxy-2-methyl-1H-phenalen-1-one (compound 128), harmol (compound 368) and anthrapurpurin (compound 1499) show uncompetitive inhibitions. These new NS2B-NS3 protease inhibitors are valuable hits to further hit-to-lead optimization.

Biocomputational characterisation of MBO_200107 protein of Mycobacterium tuberculosis variant caprae: a molecular docking and simulation study

The principal objective of this study was to delineate the potentiality of the MBO_200107 protein from the Mycobacterium tuberculosis variant caprae in cancer research. It is a cytoplasmic protein, comprised of a 354-long amino acid chain, alkaline, had a molecular weight of 39089.37 Da, an isoelectric point of 9.62 and a grand average of hydropathicity of -0.345. One of the functional domains was predicted as Gammaglutamylcyclotransferase (GGCT). Among tertiary structures, the Modeller and Phyre2 model satisfied all the quality parameters, though they are truncated; contrarily, the I-TASSER model is full length and contains the sequence for the GGCT domain, though it did not meet all the quality parameters. It also has significant sequence similarities (47.5% by EMBOSS Water and 72.4% by EMBOSS Matcher) with a human GGCT, and the conserved sequences are confined to the GGCT domain of the MBO_200107. According to molecular docking analyses, the protein has a binding affinity of -4.8 kcal/mol by Autodock Vina and -56.465 kcal/mol by HPEPDOCK to the human glutathione (GSH), an essential metabolite for GGCT metabolism. The Molecular dynamic simulation of the docked complex showed the binding efficiency of the GSH to MBO_200107 with a minimal structural alteration. The in silico findings mentioned above revealed that the protein could be used as a supplementary tool in cancer research, such as designing vaccines or drugs where the role of GGCT has been implicated. Further, we recommend fully characterising the protein and conducting essential in vitro and in vivo experiments to determine its detailed usefulness.Communicated by Ramaswamy H. Sarma.

Crystal structure of domain of unknown function 507 (DUF507) reveals a new protein fold

The crystal structure of the domain of unknown function family 507 protein from Aquifex aeolicus is reported (AaDUF507, UniProt O67633, 183 residues). The structure was determined in two space groups (C2221 and P3221) at 1.9 Å resolution. The phase problem was solved by molecular replacement using an AlphaFold model as the search model. AaDUF507 is a Y-shaped α-helical protein consisting of an anti-parallel 4-helix bundle base and two helical arms that extend 30-Å from the base. The two crystal structures differ by a 25° rigid body rotation of the C-terminal arm. The tertiary structure exhibits pseudo-twofold symmetry. The structural symmetry mirrors internal sequence similarity: residues 11-57 and 102-148 are 30% identical and 53% similar with an E-value of 0.002. In one of the structures, electron density for an unknown ligand, consistent with nicotinamide or similar molecule, may indicate a functional site. Docking calculations suggest potential ligand binding hot spots in the region between the helical arms. Structure-based query of the Protein Data Bank revealed no other protein with a similar tertiary structure, leading us to propose that AaDUF507 represents a new protein fold.

Repurposing miconazole and tamoxifen for the treatment of Mycobacterium abscessus complex infections through in silico chemogenomics approach

Drug repositioning is an alternative to overcome the complexity of the drug discovery and approval procedures for the treatment of Mycobacterium abscessus Complex (MABSC) infections that are increasing globally due to the emergency of antimicrobial resistance mechanisms. Here, an in silico chemogenomics approach was performed to compare the sequences from 4942 M. abscessus subsp. abscessus (M. abscessus) proteins with 5258 or 3473 therapeutic targets registered in the DrugBank or Therapeutic Target Database, respectively. This comparison identified 446 drugs or drug candidates whose targets were homologous to M. abscessus proteins. These identified drugs were considered potential inhibitors of MABSC (anti-MABSC activity). Further screening and inspection resulted in the selection of ezetimibe, furosemide, itraconazole, miconazole (MCZ), tamoxifen (TAM), and thiabendazole (THI) for experimental validation. Among them, MCZ and TAM showed minimum inhibitory concentrations (MIC) of 32 and 24 µg mL-1 against M. abscessus, respectively. For M. bolletii and M. massiliense strains, MCZ and TAM showed MICs of 16 and 24 µg mL-1, in this order. Subsequently, the antibacterial activity of MCZ was confirmed in vivo, indicating its potential to reduce the bacterial load in the lungs of infected mice. These results show that MCZ and TAM can serve as molecular scaffolds for the prospective hit-2-lead optimization of new analogs with greater potency, selectivity, and permeability.

Virtual screening of natural ligands from five resources to target Ralstonia solanacearum polygalacturonase and endoglucanase

The present computational study explores novel herbal compounds with potent inhibitory activity against polygalacturonase (PG) and endoglucanase (EG), the extracellular cell wall-degrading enzymes of Ralstonia solanacearum causing crops' bacterial wilt. Phytocompounds of Rosmarinus officinalis L., Coriandrum sativum L., Ocimum basilicum, Cymbopogon citratus, and Thymus vulgaris were first checked to be pharmacokinetically safe and nontoxic. The ligands were then docked to predicted and validated structural models of PG and EG. Molecular dynamic simulations were performed to ensure the dynamic stability of protein-ligand complexes. Carvone and citronellyl acetate were identified to have the best docking energy in binding and inhibiting PG and EG, respectively. In molecular dynamics, root-mean-square deviations of PG-Carvone and EG-Citronellyl acetate complexes indicated the high stability of the ligands in their corresponding cavities. Root-mean-square fluctuations of both proteins indicated unchanged mobility of the binding site residues due to a stable interaction with their ligands. Functional groups on both ligands contributed to the formation of hydrogen bonds with their respective proteins, which were preserved throughout the simulation time. The nonpolar energy component was revealed to significantly contribute to the stability of the docked protein-ligand complexes. Overall, our findings imply the high capability of Carvone and Citronellyl acetate as strong pesticides against the R. solanacearum-caused wilt. This study highlighted the potential of natural ligands in controlling the agricultural bacterial infections, as well as the utility of computational screening techniques in discovering appropriate and potent lead compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03683-z.

Computational and experimental analyses of alanine racemase suggest new avenues for developing allosteric small-molecule antibiotics

Given the ever-present threat of antibacterial resistance, there is an urgent need to identify new antibacterial drugs and targets. One such target is alanine racemase (Alr), an enzyme required for bacterial cell-wall biosynthesis. Alr is an attractive drug target because it is essential for bacterial survival but is absent in humans. Existing drugs targeting Alr lack specificity and have severe side effects. We here investigate alternative mechanisms of Alr inhibition. Alr functions exclusively as an obligate homodimer, so we probed seven conserved interactions on the dimer interface, distant from the enzymatic active site, to identify possible allosteric influences on activity. Using the Alr from Mycobacterium tuberculosis (MT) as a model, we found that the Lys261/Asp135 salt bridge is critical for catalytic activity. The Lys261Ala mutation completely inactivated the enzyme, and the Asp135Ala mutation reduced catalytic activity eight-fold. Further investigation suggested a potential drug-binding site near the Lys261/Asp135 salt bridge that may be useful for allosteric drug discovery.

BMaps: A Web Application for Fragment-Based Drug Design and Compound Binding Evaluation

Fragment-based drug design uses data about where, and how strongly, small chemical fragments bind to proteins, to assemble new drug molecules. Over the past decade, we have been successfully using fragment data, derived from thermodynamically rigorous Monte Carlo fragment-protein binding simulations, in dozens of preclinical drug programs. However, this approach has not been available to the broader research community because of the cost and complexity of doing simulations and using design tools. We have developed a web application, called BMaps, to make fragment-based drug design widely available with greatly simplified user interfaces. BMaps provides access to a large repository (>550) of proteins with 100s of precomputed fragment maps, druggable hot spots, and high-quality water maps. Users can also employ their own structures or those from the Protein Data Bank and AlphaFold DB. Multigigabyte data sets are searched to find fragments in bondable orientations, ranked by a binding-free energy metric. The designers use this to select modifications that improve affinity and other properties. BMaps is unique in combining conventional tools such as docking and energy minimization with fragment-based design, in a very easy to use and automated web application. The service is available at https://www.boltzmannmaps.com.

Structure-based neural network protein-carbohydrate interaction predictions at the residue level

Carbohydrates dynamically and transiently interact with proteins for cell-cell recognition, cellular differentiation, immune response, and many other cellular processes. Despite the molecular importance of these interactions, there are currently few reliable computational tools to predict potential carbohydrate-binding sites on any given protein. Here, we present two deep learning (DL) models named CArbohydrate-Protein interaction Site IdentiFier (CAPSIF) that predicts non-covalent carbohydrate-binding sites on proteins: (1) a 3D-UNet voxel-based neural network model (CAPSIF:V) and (2) an equivariant graph neural network model (CAPSIF:G). While both models outperform previous surrogate methods used for carbohydrate-binding site prediction, CAPSIF:V performs better than CAPSIF:G, achieving test Dice scores of 0.597 and 0.543 and test set Matthews correlation coefficients (MCCs) of 0.599 and 0.538, respectively. We further tested CAPSIF:V on AlphaFold2-predicted protein structures. CAPSIF:V performed equivalently on both experimentally determined structures and AlphaFold2-predicted structures. Finally, we demonstrate how CAPSIF models can be used in conjunction with local glycan-docking protocols, such as GlycanDock, to predict bound protein-carbohydrate structures.

Analyzing the Geometry and Dynamics of Viral Structures: A Review of Computational Approaches Based on Alpha Shape Theory, Normal Mode Analysis, and Poisson-Boltzmann Theories

The current SARS-CoV-2 pandemic highlights our fragility when we are exposed to emergent viruses either directly or through zoonotic diseases. Fortunately, our knowledge of the biology of those viruses is improving. In particular, we have more and more structural information on virions, i.e., the infective form of a virus that includes its genomic material and surrounding protective capsid, and on their gene products. It is important to have methods that enable the analyses of structural information on such large macromolecular systems. We review some of those methods in this paper. We focus on understanding the geometry of virions and viral structural proteins, their dynamics, and their energetics, with the ambition that this understanding can help design antiviral agents. We discuss those methods in light of the specificities of those structures, mainly that they are huge. We focus on three of our own methods based on the alpha shape theory for computing geometry, normal mode analyses to study dynamics, and modified Poisson-Boltzmann theories to study the organization of ions and co-solvent and solvent molecules around biomacromolecules. The corresponding software has computing times that are compatible with the use of regular desktop computers. We show examples of their applications on some outer shells and structural proteins of the West Nile Virus.

Targeting Troponin C with Small Molecules Containing Diphenyl Moieties: Calcium Sensitivity Effects on Striated Muscles and Structure-Activity Relationship

Despite large investments from academia and industry, heart failure, which results from a disruption of the contractile apparatus, remains a leading cause of death. Cardiac muscle contraction is a calcium-dependent mechanism, which is regulated by the troponin protein complex (cTn) and specifically by the N-terminal domain of its calcium-binding subunit (cNTnC). There is an increasing need for the development of small molecules that increase calcium sensitivity without altering the systolic calcium concentration, thereby strengthening the cardiac function. Here, we examined the effect of our previously identified calcium-sensitizing small molecule, ChemBridge compound 7930079, in the context of several homologous muscle systems. The effect of this molecule on force generation in isolated cardiac trabeculae and slow skeletal muscle fibers was measured. Furthermore, we explored the use of Gaussian accelerated molecular dynamics in sampling highly predictive receptor conformations based on NMR-derived starting structures. Additionally, we took a rational computational approach for lead optimization based on lipophilic diphenyl moieties. This integrated structural-biochemical-physiological approach led to the identification of three novel low-affinity binders, which had similar binding affinities to the known positive inotrope trifluoperazine. The most potent identified calcium sensitizer was compound 16 with an apparent affinity of 117 ± 17 μM.