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

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.

Umbrella Sampling Simulations of Cardiac Thin Filament Reveal Thermodynamic Consequences of Troponin I Inhibitory Peptide Mutations

The cardiac thin filament comprises F-actin, tropomyosin, and troponin (cTn). cTn is composed of three subunits: troponin C (cTnC), troponin I (cTnI), and troponin T (cTnT). To computationally study the effect of the thin filament on cTn activation events, we employed targeted molecular dynamics followed by umbrella sampling using a model of the thin filament to measure the thermodynamics of cTn transition events. Our simulations revealed that the thin filament causes an increase in the free energy required to open the cTnC hydrophobic patch and causes a more favorable interaction between this region and the cTnI switch peptide. Mutations to the cTn complex can lead to cardiomyopathy, a collection of diseases that present clinically with symptoms of hypertrophy or dilation of the cardiac muscle, leading to impairment of the heart's ability to function normally and ultimately myocardial infarction or heart failure. Upon introduction of cardiomyopathic mutations to R145 of cTnI, we observed a general decrease in the free energy of opening the cTnC hydrophobic patch, which is on par with previous experimental results. These mutations also exhibited a decrease in electrostatic interactions between cTnI-R145 and actin-E334. After introduction of a small molecule to the wild-type cTnI-actin interface to intentionally disrupt intersubunit contacts, we successfully observed similar thermodynamic consequences and disruptions to the same protein-protein contacts as observed with the cardiomyopathic mutations. Computational studies utilizing the cTn complex in isolation would have been unable to observe these effects, highlighting the importance of using a more physiologically relevant thin-filament model to investigate the global consequences of cardiomyopathic mutations to the cTn complex.

Molecular docking in organic, inorganic, and hybrid systems: a tutorial review

Molecular docking simulation is a very popular and well-established computational approach and has been extensively used to understand molecular interactions between a natural organic molecule (ideally taken as a receptor) such as an enzyme, protein, DNA, RNA and a natural or synthetic organic/inorganic molecule (considered as a ligand). But the implementation of docking ideas to synthetic organic, inorganic, or hybrid systems is very limited with respect to their use as a receptor despite their huge popularity in different experimental systems. In this context, molecular docking can be an efficient computational tool for understanding the role of intermolecular interactions in hybrid systems that can help in designing materials on mesoscale for different applications. The current review focuses on the implementation of the docking method in organic, inorganic, and hybrid systems along with examples from different case studies. We describe different resources, including databases and tools required in the docking study and applications. The concept of docking techniques, types of docking models, and the role of different intermolecular interactions involved in the docking process to understand the binding mechanisms are explained. Finally, the challenges and limitations of dockings are also discussed in this review.

Graphical abstract

Binding pocket dynamics along the recovery stroke of human β-cardiac myosin

The druggability of small-molecule binding sites can be significantly affected by protein motions and conformational changes. Ligand binding, protein dynamics and protein function have been shown to be closely interconnected in myosins. The breakthrough discovery of omecamtiv mecarbil (OM) has led to an increased interest in small molecules that can target myosin and modulate its function for therapeutic purposes (myosin modulators). In this work, we use a combination of computational methods, including steered molecular dynamics, umbrella sampling and binding pocket tracking tools, to follow the evolution of the OM binding site during the recovery stroke transition of human β-cardiac myosin. We found that steering two internal coordinates of the motor domain can recapture the main features of the transition and in particular the rearrangements of the binding site, which shows significant changes in size, shape and composition. Possible intermediate conformations were also identified, in remarkable agreement with experimental findings. The differences in the binding site properties observed along the transition can be exploited for the future development of conformation-selective myosin modulators.

Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2

When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts' angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein's crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport^®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of -8.645 kcal·mol^-1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC₅₀ values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation.

Kinetic and structural studies of Mycobacterium tuberculosis dihydroorotate dehydrogenase reveal new insights into class 2 DHODH inhibition

Tuberculosis (TB) is a leading cause of death worldwide. TB represents a serious public health threat, and it is characterized by high transmission rates, prevalence in impoverished regions, and high co-infection rates with HIV. Moreover, the serious side effects of long-term treatment that decrease patient adherence, and the emergence of multi-resistant strains of Mycobacterium tuberculosis, the causing agent of TBs, pose several challenges for its eradication. The search for a new TB treatment is necessary and urgent. Dihydroorotate dehydrogenase (DHODH) is responsible for the stereospecific oxidation of (S)-dihydroorotate (DHO) to orotate during the fourth and only redox step of the de novo pyrimidine nucleotide biosynthetic pathway. DHODH has been considered an attractive target against infectious diseases. As a first step towards exploiting DHODH as a drug target against TB, we performed a full kinetic characterization of both bacterial MtDHODH and its human ortholog (HsDHDOH) using both substrates coenzyme Q0 (Q0) and vitamin K3 (K3). MtDHODH follows a ping-pong mechanism of catalysis and shares similar catalytic parameters with the human enzyme. Serendipitously, Q0 was found to inhibit MtDHODH (K_I (Q0) = 138 ± 31 μM). To the best of our knowledge, Q0 is the first non-orotate like dihydroorotate-competitive inhibitor for class 2 DHODHs ever described. Molecular dynamics simulations along with in silico solvent mapping allowed us to successfully probe protein flexibility and correlate it with the druggability of binding sites. Together, our results provide the starting point for the design of a new generation of potent and selective inhibitors against MtDHODH.

Application of Mixed-Solvent Molecular Dynamics Simulations for Prediction of Allosteric Sites on G Protein-Coupled Receptors

The development of small molecule allosteric modulators acting at G protein-coupled receptors (GPCRs) is becoming increasingly attractive. Such compounds have advantages over traditional drugs acting at orthosteric sites on these receptors, in particular target specificity. However, the number and locations of druggable allosteric sites within most clinically relevant GPCRs are unknown. In the present study, we describe the development and application of a mixed-solvent molecular dynamics (MixMD)-based method for the identification of allosteric sites on GPCRs. The method employs small organic probes with druglike qualities to identify druggable hotspots in multiple replicate short-timescale simulations. As proof of principle, we first applied the method retrospectively to a test set of five GPCRs (cannabinoid receptor type 1, C-C chemokine receptor type 2, M2 muscarinic receptor, P2Y purinoceptor 1, and protease-activated receptor 2) with known allosteric sites in diverse locations. This resulted in the identification of the known allosteric sites on these receptors. We then applied the method to the μ-opioid receptor. Several allosteric modulators for this receptor are known, although the binding sites for these modulators are not known. The MixMD-based method revealed several potential allosteric sites on the mu-opioid receptor. Implementation of the MixMD-based method should aid future efforts in the structure-based drug design of drugs targeting allosteric sites on GPCRs. SIGNIFICANCE STATEMENT: Allosteric modulation of G protein-coupled receptors (GPCRs) has the potential to provide more selective drugs. However, there are limited structures of GPCRs bound to allosteric modulators, and obtaining such structures is problematic. Current computational methods utilize static structures and therefore may not identify hidden or cryptic sites. Here we describe the use of small organic probes and molecular dynamics to identify druggable allosteric hotspots on GPCRs. The results reinforce the importance of protein dynamics in allosteric site identification.

Recombinant Production and Biochemical Characterization of Thermostable Arabinofuranosidase from Acidothermophilic Alicyclobacillus Acidocaldarius

The complete enzymatic degradation of lignocellulosic biomass requires the cooperative action of cellulosic, hemicellulosic, and lignolytic enzymes such as cellulase, xylanase, laccase, galactosidase, and arabinofuranosidase. Arabinofuranosidases (E.C 3.2.1.55), which belong to the glycoside hydrolase family of enzymes, hydrolyze the 1,3- and 1,5-α-arabinosyl bonds in L-arabinose- containing molecules. L-arabinoses are present in hemicellulosic part of lignocellulosic biomass. Arabinofuranosidases also play an important role in the complete hydrolysis of arabinoxylans. Analysis of the genome project and CAZY database revealed two putative arabinofuranosidase genes in the A. acidocaldarius genome. The aim of the study was cloning, heterologous expression, purification and biochemical characterization of the arabinofuranosidase enzyme encoded in A. acidocaldarius genome. For this purpose, the AbfA gene of the arabinofuranosidase protein was cloned into the pQE-40 vector, heterologously expressed in E. coli BL21 GOLD (DE3) and successfully purified using His-Tag. Biochemical characterization of the purified enzyme revealed that A. acidocaldarius arabinofuranosidase exhibited activity over a wide pH and temperature range with optimum activity at 45 ºC and pH 6.5 in phosphate buffer towards 4-nitrophenyl-α-L-arabinofuranoside as the substrate. In addition, the enzyme is highly stable over wide range of temperature and maintaining 60% of its activity after 90 min of incubation at 80 ºC. Through the bioinformatics studies, the homology model of A. acidocaldarius arabinofuranosidase was generated and the substrate binding site and residues located in this site were identified. Further molecular docking analysis revealed that the substrate located in the catalytically active pose and, residues N174, E175, and E294 have direct interaction with 4-nitrophenyl-α-L-arabinofuranoside. Moreover, based on phylogenetic analysis, A. acidocaldarius arabinofuranosidase exists in the sub-group of intracellular arabinofuranosidases, and G. stearothermophilus and B.subtilis arabinofuranosidases are close relatives of A. acidocaldarius arabinofuranosidase. This is the first study to report the gene cloning, recombinant expression and biochemical and bioinformatic characterization of an auxiliary GH51 arabinofuranosidase from an acidothermophilic bacterium A. acidocaldarius.

Computer-aided de novo design and optimization of novel potential inhibitors of HIV-1 Nef protein

Nef is a small accessory protein pivotal in the HIV-1 viral replication cycle. It is a multifunctional protein and its interactions with kinases in host cells have been well characterized through many in vitro and structural studies. Nef forms a homodimer to activate the kinases and subsequently the phosphorylation pathways. The disruption of its homodimerization represents a valuable approach in the search for novel classes of antiretroviral. However, this research avenue is still underdeveloped as just a few Nef inhibitors have been reported so far, with very limited structural information about their mechanism of action. To address this issue, we have employed an in silico structure-based drug design strategy that combines de novo ligand design with molecular docking and extensive molecular dynamics simulations. Since the Nef pocket involved in homodimerization has high lipophilicity, the initial de novo-designed structures displayed poor drug-likeness and solubility. Taking information from the hydration sites within the homodimerization pocket, structural modifications in the initial lead compound have been introduced to improve the solubility and drug-likeness, without affecting the binding profile. We propose lead compounds that can be the starting point for further optimizations to deliver long-awaited, rationally designed Nef inhibitors.

Structural analysis of factors related to FAM3C/ILEI dimerization and identification of inhibitor candidates targeting cancer treatment

FAM3 is a superfamily of four cytokines that maintain a single globular structure β -β -α of three classes: FAM3A, B, C and D. FAM3C was the first member of this family related to cancer and is functionally characterized as an essential factor for the epithelial-mesenchymal transition (EMT), leading to late delays in tumor progression. Due to its crucial role in EMT and metastasis, FAM3C has been termed an interleukin-like EMT (ILEI) inducer. There are several studies on the part of FAM3C in the progression of cancer and other diseases. However, little is known about its cellular receptors and possible inhibitors. In this study, based on in silico approaches, we performed structural analyses of factors related to FAM3C/ILEI dimerization. We also identified four possible inhibitor candidates, expected to be exciting prototypes and could be submitted to future biological tests targeting cancer treatment.

Identification of Fungal and Bacterial Denitrification Inhibitors Targeting Copper Nitrite Reductase

The usage of nitrification inhibitors is one of the strategies that reduce or slow down the denitrification process to prevent nitrogen loss to the atmosphere in the form of N₂O. Directly targeting microbial denitrification could be one of the mitigation strategies; however, until now little efforts have been devoted toward the development of denitrification inhibitors. Here, we have identified small-molecule inhibitors of one of the proteins involved in the fungal denitrification pathway. Specifically, virtual screening was employed to identify the inhibitors of copper-containing nitrite reductase (FoNirK) of the filamentous fungus Fusarium oxysporum. Three series of chemical compounds were identified, out of which compounds belonging to two chemical scaffolds inhibited FoNirK enzymatic activity in low micromolar ranges. Several compounds also displayed moderate inhibition of fungal denitrification activity in vivo. Evaluation of in vitro activity against NirK from denitrifying bacterium Achromobacter xylosoxidans (AxNirK) and in vivo bacterial denitrification revealed a similar inhibitory profile.

Conformation-dependent ligand hot spots in the spliceosomal RNA helicase BRR2

The conversion of hits to leads in drug discovery involves the elaboration of chemical core structures to increase their potency. In fragment-based drug discovery, low-molecular-weight compounds are tested for protein binding and are subsequently modified, with the tacit assumption that the binding mode of the original hit will be conserved among the derivatives. However, deviations from binding mode conservation are rather frequently observed, but potential causes of these alterations remain incompletely understood. Here, two crystal forms of the spliceosomal RNA helicase BRR2 were employed as a test case to explore the consequences of conformational changes in the target protein on the binding behaviour of fragment derivatives. The initial fragment, sulfaguanidine, bound at the interface between the two helicase cassettes of BRR2 in one crystal form. Second-generation compounds devised by structure-guided docking were probed for their binding to BRR2 in a second crystal form, in which the original fragment-binding site was altered due to a conformational change. While some of the second-generation compounds retained binding to parts of the original site, others changed to different binding pockets of the protein. A structural bioinformatics analysis revealed that the fragment-binding sites correspond to predicted binding hot spots, which strongly depend on the protein conformation. This case study offers an example of extensive binding-mode changes during hit derivatization, which are likely to occur as a consequence of multiple binding hot spots, some of which are sensitive to the flexibility of the protein.

Small-molecule modulators of tumor necrosis factor signaling

Tumor necrosis factor (TNF) is a pleiotropic cytokine with a major role in immune system homeostasis and is involved in many inflammatory and autoimmune diseases, such as rheumatoid arthritis (RA), psoriasis, Alzheimer's disease (AD), and multiple sclerosis (MS). Thus, TNF and its receptors, TNFR1 and TNFR2, are relevant pharmacological targets. Biologics have been developed to block TNF-dependent signaling cascades, but they display serious side effects, and their pharmacological effectiveness decreases over time because of their immunogenicity. In this review, we present recent discoveries in small molecules targeting TNF and its receptors and discuss alternative strategies for modulating TNF signaling. Teaser: This review presents several recent and innovative strategies for the modulation of tumor necrosis factor function, with a focus on small molecules.

Structural and Phylogenetic Analysis of CXCR4 Protein Reveals New Insights into Its Role in Emerging and Re-Emerging Diseases in Mammals

Chemokine receptor type 4 (CXCR4) is a G protein-coupled receptor that plays an essential role in immune system function and disease processes. Our study aims to conduct a comparative structural and phylogenetic analysis of the CXCR4 protein to gain insights into its role in emerging and re-emerging diseases that impact the health of mammals. In this study, we analyzed the evolution of CXCR4 genes across a wide range of mammalian species. The phylogenetic study showed species-specific evolutionary patterns. Our analysis revealed novel insights into the evolutionary history of CXCR4, including genetic changes that may have led to functional differences in the protein. This study revealed that the structural homologous human proteins and mammalian CXCR4 shared many characteristics. We also examined the three-dimensional structure of CXCR4 and its interactions with other molecules in the cell. Our findings provide new insights into the genomic landscape of CXCR4 in the context of emerging and re-emerging diseases, which could inform the development of more effective treatments or prevention strategies. Overall, our study sheds light on the vital role of CXCR4 in mammalian health and disease, highlighting its potential as a therapeutic target for various diseases impacting human and animal health. These findings provided insight into the study of human immunological disorders by indicating that Chemokines may have activities identical to or similar to those in humans and several mammalian species.

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 models named CArbohydrate-Protein interaction Site IdentiFier (CAPSIF) that predict 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.

Protein-protein interfaces in molecular glue-induced ternary complexes: classification, characterization, and prediction

Molecular glues are a class of small molecules that stabilize the interactions between proteins. Naturally occurring molecular glues are present in many areas of biology where they serve as central regulators of signaling pathways. Importantly, several clinical compounds act as molecular glue degraders that stabilize interactions between E3 ubiquitin ligases and target proteins, leading to their degradation. Molecular glues hold promise as a new generation of therapeutic agents, including those molecular glue degraders that can redirect the protein degradation machinery in a precise way. However, rational discovery of molecular glues is difficult in part due to the lack of understanding of the protein-protein interactions they stabilize. In this review, we summarize the structures of known molecular glue-induced ternary complexes and the interface properties. Detailed analysis shows different mechanisms of ternary structure formation. Additionally, we also review computational approaches for predicting protein-protein interfaces and highlight the promises and challenges. This information will ultimately help inform future approaches for rational molecular glue discovery.

Computational approaches for the design of modulators targeting protein-protein interactions

BACKGROUND

Protein-protein interactions (PPIs) are intriguing targets for designing novel small-molecule inhibitors. The role of PPIs in various infectious and neurodegenerative disorders makes them potential therapeutic targets . Despite being portrayed as undruggable targets, due to their flat surfaces, disorderedness, and lack of grooves. Recent progresses in computational biology have led researchers to reconsider PPIs in drug discovery.

AREAS COVERED

In this review, we introduce in-silico methods used to identify PPI interfaces and present an in-depth overview of various computational methodologies that are successfully applied to annotate the PPIs. We also discuss several successful case studies that use computational tools to understand PPIs modulation and their key roles in various physiological processes.

EXPERT OPINION

Computational methods face challenges due to the inherent flexibility of proteins, which makes them expensive, and result in the use of rigid models. This problem becomes more significant in PPIs due to their flexible and flat interfaces. Computational methods like molecular dynamics (MD) simulation and machine learning can integrate the chemical structure data into biochemical and can be used for target identification and modulation. These computational methodologies have been crucial in understanding the structure of PPIs, designing PPI modulators, discovering new drug targets, and predicting treatment outcomes.

Structural and dynamic determinants for highly selective RET kinase inhibition reveal cryptic druggability

INTRODUCTION

The structural and dynamic determinants that confer highly selective RET kinase inhibition are poorly understood.

OBJECTIVES

To explore the druggability landscape of the RET active site in order to uncover structural and dynamic vulnerabilities that can be therapeutically exploited.

METHODS

We apply an integrated structural, computational and biochemical approach in order to explore the druggability landscape of the RET active site.

RESULTS

We demonstrate that the that the druggability landscape of the RET active site is determined by the conformational setting of the ATP-binding (P-) loop and its coordination with the αC helix. Open and intermediate P-loop structures display additional druggable vulnerabilities within the active site that were not exploited by first generation RET inhibitors. We identify a cryptic pocket adjacent to the catalytic lysine formed by K758, L760, E768 and L772, that we name the post-lysine pocket, with higher druggability potential than the adenine-binding site and with important implications in the regulation of the phospho-tyrosine kinase activity. Crystal structure and simulation data show that the binding mode of highly-selective RET kinase inhibitors LOXO-292 and BLU-667 is controlled by a synchronous open P-loop and αC-in configuration that allows accessibility to the post-lysine pocket. Molecular dynamics simulations show that these inhibitors efficiently occupy the post-lysine pocket with high stability through the simulation time-scale (300 ns), with both inhibitors forming hydrophobic contacts further stabilized by pi-cation interactions with the catalytic K758. Engineered mutants targeting the post-lysine pocket impact on inhibitor binding and sensitivity, as well as RET tyrosine kinase activity.

CONCLUSIONS

The identification of the post-lysine pocket as a new druggable vulnerability in the RET kinase and its exploitation by second generation RET inhibitors have important implications for future drug design and the development of personalized therapies for patients with RET-driven cancers.

In silico investigation of binding propensity of hematoxylin derivative and damnacanthal for their potential inhibitory effect on HIV-1 Vpr from different subtypes

HIV-1, the causative agent of AIDS leads to many deaths worldwide though few options are available as therapeutics. To deal with the continuous mutation in the virus genome, requirement of new drugs is always there. Subtype variation plays a crucial role in case of HIV-1 therapeutics development. In this study, we want to investigate some pre examined molecules that can be effective for HIV-1 VPR. Inhibition of several protein-protein interactions with the small molecules will lead to identify some molecules as therapeutics other than the conventional drugs. We retrieved the sequences of different subtypes from the database and representative sequences were identified. Representative structures were modelled and validated using MD simulations. Forty molecules, showing anti Vpr activity in vitro were identified from literature survey and those were docked with each subtype representative structures. Two molecules a stable Hematoxylin Derivative (SHD) and Damnacanthal (D3), these were shown to be bind more effectively for all the subtypes. The stability of the protein and those two small molecule complexes were identified again with MD simulation followed by the binding energy calculation. Thus, these molecules can be thought as any option other than the conventional drug targeting HIV-1 Vpr.Communicated by Ramaswamy H. Sarma.

Unbiased molecular dynamics simulation of a first-in-class small molecule inhibitor binds to oncostatin M

Small molecule inhibitors (SMIs) targeting oncostatin M (OSM) signaling pathway represent new therapeutics to combat cancer, inflammatory bowel disease (IBD) and CNS disease. Recently, the first-in-class SMI named SMI-10B that target OSM and block its interaction with receptor (OSMR) were reported. However, the binding pocket and interaction mode of the compound on OSM remain poorly understood, which hampering the rational design of SMIs that target OSM. Here, using SMI-10B as a probe, the multiple pockets on OSM for small molecules binding were extensively explored by unbiased molecular dynamics (MD) simulations. Then, the near-native structure of the complex was identified by molecular mechanics generalized Born surface area (MM/GBSA) binding energy funnel. Moreover, the binding stabilities of the protein-ligand complexes in near- and non-native conformations were verified by additional independent MD runs and absolute free energy perturbation (FEP) calculation. In summary, the unique feature of SMI-10B spontaneously binds to OSM characterized here not only provide detailed information for understanding the molecular mechanism of SMI-10B binding to OSM, but also will facilitate the rational design of novel and more potent SMIs to block OSM signaling.

Application of computational methods for class A GPCR Ligand discovery

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development due to their role in transmitting cellular signals in a multitude of biological processes. Of the six classes categorizing GPCR (A, B, C, D, E, and F), class A contains the largest number of therapeutically relevant GPCR. Despite their importance as drug targets, many challenges exist for the discovery of novel class A GPCR ligands serving as drug precursors. Though knowledge of the structural and functional characteristics of GPCR has grown significantly over the past 20 years, a large portion of GPCR lack reported, experimentally determined structures. Furthermore, many GPCR have no known endogenous and/or synthetic ligands, limiting further exploration of their biochemical, cellular, and physiological roles. While many successes in GPCR ligand discovery have resulted from experimental high-throughput screening, computational methods have played an increasingly important role in GPCR ligand identification in the past decade. Here we discuss computational techniques applied to GPCR ligand discovery. This review summarizes class A GPCR structure/function and provides an overview of many obstacles currently faced in GPCR ligand discovery. Furthermore, we discuss applications and recent successes of computational techniques used to predict GPCR structure as well as present a summary of ligand- and structure-based methods used to identify potential GPCR ligands. Finally, we discuss computational hit list generation and refinement and provide comprehensive workflows for GPCR ligand identification.

Crystal structure of the CoV-Y domain of SARS-CoV-2 nonstructural protein 3

Replication of the coronavirus genome starts with the formation of viral RNA-containing double-membrane vesicles (DMV) following viral entry into the host cell. The multi-domain nonstructural protein 3 (nsp3) is the largest protein encoded by the known coronavirus genome and serves as a central component of the viral replication and transcription machinery. Previous studies demonstrated that the highly-conserved C-terminal region of nsp3 is essential for subcellular membrane rearrangement, yet the underlying mechanisms remain elusive. Here we report the crystal structure of the CoV-Y domain, the most C-terminal domain of the SARS-CoV-2 nsp3, at 2.4 Å-resolution. CoV-Y adopts a previously uncharacterized V-shaped fold featuring three distinct subdomains. Sequence alignment and structure prediction suggest that this fold is likely shared by the CoV-Y domains from closely related nsp3 homologs. NMR-based fragment screening combined with molecular docking identifies surface cavities in CoV-Y for interaction with potential ligands and other nsps. These studies provide the first structural view on a complete nsp3 CoV-Y domain, and the molecular framework for understanding the architecture, assembly and function of the nsp3 C-terminal domains in coronavirus replication. Our work illuminates nsp3 as a potential target for therapeutic interventions to aid in the on-going battle against the COVID-19 pandemic and diseases caused by other coronaviruses.

Assessing protein homology models with docking reproducibility

Results of the recent Critical Assessment of Protein Structure (CASP) competitions demonstrate that protein backbones can be predicted with very high accuracy. In particular, the artificial intelligence methods of AlphaFold 2 from DeepMind were able to produce structures that were similar enough to experimental structures that many described the problem of protein prediction solved. However, for such structures to be used for drug docking studies requires precision in the placement of side chain atoms as well. Here we built a library of 1334 small molecules and examined how reproducibly they bound to the same site on a protein using QuickVina-W, a branch of the program Autodock that is optimized for blind searches. We discovered that the higher the backbone quality of the homology model the greater the similarity between the small molecule docking to the experimental and modeled structures. Furthermore, we found that specific subsets of this library were particularly useful for identifying small differences between the best of the best modeled structures. Specifically, when the number of rotatable bonds in the small molecule increased, differences in binding sites became more apparent.

Structural Insights into the Substrate Range of a Bacterial Monoamine Oxidase

Monoamine oxidases (MAOs) play a key role in the breakdown of primary and secondary amines. In eukaryotic organisms, these enzymes are vital to the regulation of monoamine neurotransmitters and the degradation of dietary monoamines. MAOs have also been identified in prokaryotic species, although their role in these organisms is not well understood. Here, we report the biophysical and structural properties of a promiscuous, bacterial MAO from Corynebacterium ammoniagenes (caMAO). caMAO catalyzes the oxidation of a number of monoamine substrates including dopamine and norepinephrine, as well as exhibiting some activity with polyamine substrates such as cadaverine. The X-ray crystal structures of Michaelis complexes with seven substrates show that conserved hydrophobic interactions and hydrogen-bonding pattern (for polar substrates) allow the broad specificity range. The structure of caMAO identifies an unusual cysteine (Cys424) residue in the so-called "aromatic cage", which flanks the flavin isoalloxazine ring in the active site. Site-directed mutagenesis, steady-state kinetics in air-saturated buffer, and UV-vis spectroscopy revealed that Cys424 plays a role in the pH dependence and modulation of electrostatics within the caMAO active site. Notably, bioinformatic analysis shows a propensity for variation at this site within the "aromatic cage" of the flavin amine oxidase (FAO) superfamily. Structural analysis also identified the conservation of a secondary substrate inhibition site, present in a homologous member of the superfamily. Finally, genome neighborhood diagram analysis of caMAO in the context of the FAO superfamily allows us to propose potential roles for these bacterial MAOs in monoamine and polyamine degradation and catabolic pathways related to scavenging of nitrogen.

Targeting Troponin C with Small Molecules Containing Diphenyl Moieties: Calcium Sensitivity Effects on Striated Muscle 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 systolic calcium concentration, thereby strengthening 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 led to the identification of three novel low affinity binders, which had similar binding affinities to known positive inotrope trifluoperazine. The most potent identified calcium sensitizer was compound 16 with an apparent affinity of 117 ± 17 μM .

Druggable sites identification in Streptococcus mutans VicRK system evaluated by catechols

Dental caries is a global public health problem, being the most common non-communicable disease. Streptococcus mutans, the causative agent of human cariogenic dental biofilms, produce glycosyltransferases (Gtfs) whose gene expression is modulated by the VicRK system, which makes them a promising target for dental biofilm inhibitor developments. Bioinformatics have playing a significant role in drug discovery programs mainly in novel hit identification. In this study, potential inhibitors against the S. mutans VicK system have been identified through Structure-based Virtual Screening performed between the VicK druggable sites followed byMolecular Dynamic simulations (MD) with binding affinity analysis by MM-PBSA approach. First, VicK protein was downloaded from PDB, and druggability analyses were performed by PockDrug and FTMap servers describing three interaction sites (S1, S2, and S3) that covered the most important domains for stability and activity. Next, a catechol virtual screening (n = 383) was performed on AutoDock4.2, and better-docked catechols showed strong binding affinity interaction through hydrogen bonding, hydrophobic interactions, and π-stacking with VicK auto kinase and phosphatase activity sites. Ligand efficiency indexes were also calculated (LE, LELP, LLE, and BEI) and showed optimal values. Furthermore, a 200 ns MD simulation run showed stability (RMSD and RMSF) and a high number of hydrogen bonds into peltatoside and maritimein, the two best VicK complexes. These results supported that catechols could potentially inhibit exopolysaccharides synthesis and be used in the biofilm management of new anti-cariogenic and antimicrobial agents.

Fragment screening libraries for the identification of protein hot spots and their minimal binding pharmacophores

Fragment-based drug design relies heavily on structural information for the elaboration and optimisation of hits. The ability to identify neighbouring binding hot spots, energetically favourable interactions and conserved binding motifs in protein structures through X-ray crystallography can inform the evolution of fragments into lead-like compounds through structure-based design. The composition of fragment libraries can be designed and curated to fit this purpose and herein, we describe and compare screening libraries containing compounds comprising between 2 and 18 heavy atoms. We evaluate the properties of the compounds in these libraries and assess their ability to probe protein surfaces for binding hot spots.

In silico prediction of molecular mechanisms of toxicity mediated by the leptospiral PF07598 gene family-encoded virulence-modifying proteins

Mechanisms of leptospirosis pathogenesis remain unclear despite the identification of a number of potential leptospiral virulence factors. We recently demonstrated potential mechanisms by which the virulence-modifying (VM) proteins-defined as containing a Domain of Unknown function (DUF1561), encoded by the PF07598 gene family-found only in group 1 pathogenic Leptospira-might mediate the clinical pathogenesis of leptospirosis. VM proteins belongs to classical AB toxin paradigm though have a unique AB domain architecture, unlike other AB toxins such as diphtheria toxin, pertussis toxin, shiga toxin, or ricin toxin which are typically encoded by two or more genes and self-assembled into a multi-domain holotoxin. Leptospiral VM proteins are secreted R-type lectin domain-containing exotoxins with discrete N-terminal ricin B-like domains involved in host cell surface binding, and a C-terminal DNase/toxin domain. Here we use the artificial intelligence-based AlphaFold algorithm and other computational tools to predict and elaborate on details of the VM protein structure-function relationship. Comparative AlphaFold and CD-spectroscopy defined the consistent secondary structure (Helix and ß-sheet) content, and the stability of the functional domains were further supported by molecular dynamics simulation. VM proteins comprises distinctive lectic family (QxW)₃ motifs, the Mycoplasma CARDS toxin (D3 domain, aromatic patches), C-terminal similarity with mammalian DNase I. In-silico study proposed that Gln412, Gln523, His533, Thr59 are the high binding energy or ligand binding residues plausibly anticipates in the functional activities. Divalent cation (Mg⁺²-Gln412) and phosphate ion (PO₄]^-3-Arg615) interaction further supports the functional activities driven by C-terminal domain. Computation-driven structure-function studies of VM proteins will guide experimentation towards mechanistic understandings of leptospirosis pathogenesis, which underlie development of new therapeutic and preventive measures for this devastating disease.

In Silico Structural and Functional Analyses of NLRP3 Inflammasomes to Provide Insights for Treating Neurodegenerative Diseases

Inflammasomes are cytoplasmic intracellular multiprotein complexes that control the innate immune system's activation of inflammation in response to derived chemicals. Recent advancements increased our molecular knowledge of activation of NLRP3 inflammasomes. Although several studies have been done to investigate the role of inflammasomes in innate immunity and other diseases, structural, functional, and evolutionary investigations are needed to further understand the clinical consequences of NLRP3 gene. The purpose of this study is to investigate the structural and functional impact of the NLRP3 protein by using a computational analysis to uncover putative protein sites involved in the stabilization of the protein-ligand complexes with inhibitors. This will allow for a deeper understanding of the molecular mechanism underlying these interactions. It was found that human NLRP3 gene coexpresses with PYCARD, NLRC4, CASP1, MAVS, and CTSB based on observed coexpression of homologs in other species. The NACHT, LRR, and PYD domain-containing protein 3 is a key player in innate immunity and inflammation as the sensor subunit of the NLRP3 inflammasome. The inflammasome polymeric complex, consisting of NLRP3, PYCARD, and CASP1, is formed in response to pathogens and other damage-associated signals (and possibly CASP4 and CASP5). Comprehensive structural and functional analyses of NLRP3 inflammasome components offer a fresh approach to the development of new treatments for a wide variety of human disorders.

Galantamine Based Novel Acetylcholinesterase Enzyme Inhibitors: A Molecular Modeling Design Approach

Acetylcholinesterase (AChE) enzymes play an essential role in the development of Alzheimer's disease (AD). Its excessive activity causes several neuronal problems, particularly psychopathies and neuronal cell death. A bioactive pose on the hAChE B site of the human acetylcholinesterase (hAChE) enzyme employed in this investigation, which was obtained from the Protein Data Bank (PDB ID 4EY6), allowed for the prediction of the binding affinity and free binding energy between the protein and the ligand. Virtual screening was performed to obtain structures similar to Galantamine (GNT) with potential hAChE activity. The top 200 hit compounds were prioritized through the use of filters in ZincPharmer, with special features related to the pharmacophore. Critical analyses were carried out, such as hierarchical clustering analysis (HCA), ADME/Tox predictions, molecular docking, molecular simulation studies, synthetic accessibility (SA), lipophilicity, water solubility, and hot spots to confirm the stable binding of the two promising molecules (ZINC16951574-LMQC2, and ZINC08342556-LMQC5). The metabolism prediction, with metabolites M3-2, which is formed by Glutathionation reaction (Phase II), M1-2, and M2-2 formed from the reaction of S-oxidation and Aliphatic hydroxylation (Phase I), were both reactive but with no side effects. Theoretical synthetic routes and prediction of synthetic accessibility for the most promising compounds are also proposed. In conclusion, this study shows that in silico modeling can be used to create new drug candidate inhibitors for hAChE. The compounds ZINC16951574-LMQC2, and ZINC08342556-LMQC5 are particularly promising for oral administration because they have a favorable drug-likeness profile, excellent lipid solubility, high bioavailability, and adequate pharmacokinetics.

Water Leakage Pathway Leads to Internal Hydration of the p53 Core Domain

The gene encoding the p53 tumor suppressor protein is the most frequently mutated oncogene in cancer patients; yet, generalized strategies for rescuing the function of different p53 mutants remain elusive. This work investigates factors that may contribute to the low inherent stability of the wild-type p53 core domain (p53C) and structurally compromised Y220C mutant. Pressure-induced unfolding of p53C was compared to p63C, the p53 family member with the highest stability, the engineered superstable p53C hexamutant (p53C HM), and lower stability p53C Y220C cancer-associated mutant. The following pressure unfolding values (P50% bar) were obtained: p53C 3346, p53C Y220C 2217, p53C HM 3943, and p63C 4326. Molecular dynamics (MD) simulations revealed that p53C Y220C was most prone to water infiltration, followed by p53C, whereas the interiors of p53C HM and p63C remained comparably dry. A strong correlation (r² = 0.92) between P50% and extent of interior hydration was observed. The pathways of individual water molecule entry and exit were mapped and analyzed, revealing a common route preserved across the p53 family involving a previously reported pocket, along with a novel surface cleft, both of which appear to be targetable by small molecules. Potential determinants of propensity to water incursion were assessed, including backbone hydrogen bond protection and combined sequence and structure similarity. Collectively, our results indicate that p53C has an intrinsic susceptibility to water leakage, which is exacerbated in a structural class mutant, suggesting that there may be a common avenue for rescuing p53 function.

The CDR3 region as the major driver of TREM-1 interaction with its ligands, an in silico characterization

The triggering receptor expressed on myeloid cells-1 (TREM-1) is a pattern recognition receptor heavily investigated in infectious and non-infectious diseases. Because of its role in amplifying inflammation, TREM-1 has been explored as a diagnostic/prognostic biomarker. Further, as the receptor has been implicated in the pathophysiology of several diseases, therapies aiming at modulating its activity represent a promising strategy to constrain uncontrolled inflammatory or infectious diseases. Despite this, several aspects concerning its interaction with ligands and activation process, remain unclear. Although many molecules have been suggested as TREM-1 ligands, only five have been confirmed to interact with the receptor: actin, eCIRP, HMGB1, Hsp70 and PGLYRP1. However, the domains involved in the interaction between the receptor and these proteins are not clarified yet. Therefore, here we used in silico approaches to investigate the putative binding domains in the receptor, using hot spots analysis, molecular docking and molecular dynamics simulations between TREM-1 and its five known ligands. Our results indicated the complementarity-determining regions (CDRs) of the receptor as the main mediators of antigen recognition, especially the CDR3 loop. We believe that our study could be used as structural basis for the elucidation of TREM-1's recognition process, and may be useful for prospective in silico and biological investigations exploring the receptor in different contexts.