Methods of protein structure comparison

The antimicrobial potential and pharmacokinetic profiles of novel quinoline-based scaffolds: synthesis and in silico mechanistic studies as dual DNA gyrase and DHFR inhibitors

The resistance of pathogenic microbes to currently available antimicrobial agents has been considered a global alarming concern.

Interactive Molecular Dynamics in Virtual Reality Is an Effective Tool for Flexible Substrate and Inhibitor Docking to the SARS-CoV-2 Main Protease

The main protease (Mpro) of the SARS-CoV-2 virus is one focus of drug development efforts for COVID-19. Here, we show that interactive molecular dynamics in virtual reality (iMD-VR) is a useful and effective tool for creating Mpro complexes. We make these tools and models freely available. iMD-VR provides an immersive environment in which users can interact with MD simulations and so build protein complexes in a physically rigorous and flexible way. Recently, we have demonstrated that iMD-VR is an effective method for interactive, flexible docking of small molecule drugs into their protein targets (Deeks et al. PLoS One 2020, 15, e0228461). Here, we apply this approach to both an Mpro inhibitor and an oligopeptide substrate, using experimentally determined crystal structures. For the oligopeptide, we test against a crystallographic structure of the original SARS Mpro. Docking with iMD-VR gives models in agreement with experimentally observed (crystal) structures. The docked structures are also tested in MD simulations and found to be stable. Different protocols for iMD-VR docking are explored, e.g., with and without restraints on protein backbone, and we provide recommendations for its use. We find that it is important for the user to focus on forming binding interactions, such as hydrogen bonds, and not to rely on using simple metrics (such as RMSD), in order to create realistic, stable complexes. We also test the use of apo (uncomplexed) crystal structures for docking and find that they can give good results. This is because of the flexibility and dynamic response allowed by the physically rigorous, atomically detailed simulation approach of iMD-VR. We make our models (and interactive simulations) freely available. The software framework that we use, Narupa, is open source, and uses commodity VR hardware, so these tools are readily accessible to the wider research community working on Mpro (and other COVID-19 targets). These should be widely useful in drug development, in education applications, e.g., on viral enzyme structure and function, and in scientific communication more generally.

Computational and network pharmacology analysis of bioflavonoids as possible natural antiviral compounds in COVID-19

Bioflavonoids are the largest group of plant-derived polyphenolic compounds with diverse biological potential and have also been proven efficacious in the treatment of Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). The present investigation validates molecular docking, simulation, and MM-PBSA studies of fifteen bioactive bioflavonoids derived from plants as a plausible potential antiviral in the treatment of COVID-19. Molecular docking studies for 15 flavonoids on the three SARS CoV-2 proteins, non-structural protein-15 Endoribonuclease (NSP15), the receptor-binding domain of spike protein (RBD of S protein), and main protease (M^pro/3CL^pro) were performed and selected protein-ligand complexes were subjected to Molecular Dynamics simulations. The molecular dynamics trajectories were subjected to free energy calculation by the MM-PBSA method. All flavonoids were further assessed for their effectiveness as adjuvant therapy by network pharmacology analysis on the target proteins. The network pharmacology analysis suggests the involvement of selected bioflavonoids in the modulation of multiple signaling pathways like p53, FoxO, MAPK, Wnt, Rap1, TNF, adipocytokine, and leukocyte transendothelial migration which plays a significant role in immunomodulation, minimizing the oxidative stress and inflammation. Molecular docking and molecular dynamics simulation studies illustrated the potential of glycyrrhizic acid, amentoflavone, and mulberroside in inhibiting key SARS-CoV-2 proteins and these results could be exploited further in designing future ligands from natural sources.

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Bioflavonoids are potential antiviral secondary metabolites.

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Docking, MD and network pharmacology demonstrated antiviral & adjuvant potential.

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MM-PBSA calculations and network pharmacology identified key bioflavonoids.

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Mulberroside, Glycyrrhizic acid and Amentoflavone may hold promise in COVID-19.

Iron(III)-Oxo Cluster Chemistry with Dimethylarsinate Ligands: Structures, Magnetic Properties, and Computational Studies

A program has been initiated to develop Fe^III/oxo cluster chemistry with the "pseudocarboxylate" ligand dimethylarsinate (Me₂AsO₂^-) for comparison with the well investigated Fe^III/oxo/carboxylate cluster area. The synthesis and characterization of three polynuclear Fe^III complexes are reported, [Fe₁₂O₄(O₂C^tBu)₈(O₂AsMe₂)₁₇(H₂O)₃]Cl₃ (1), Na₂[Fe₁₂Na₂O₄(O₂AsMe₂)₂₀(NO₃)₆(Me₂AsO₂H)₂(H₂O)₄](NO₃)₆ (2), and [Fe₃(O₂AsMe₂)₆(Me₂AsO₂H)₂(hqn)₂](NO₃) (3), where hqnH is 8-hydroxyquinoline. The Fe₁₂ core of 1 is a type never previously encountered in Fe^III carboxylate chemistry, consisting of two Fe₆ units each of which comprises two {Fe₃(μ₃-O^2-)} units bridged by three Me₂AsO₂^- groups and linked into an Fe₁₂ loop structure by two anti-anti η¹:η¹:μ Me₂AsO₂^- groups, a bridging mode extremely rare with carboxylates. 2 also consists of two Fe₆ units, differing in their ligation from those in 1, and this time linked together into a linear structure by a central {Na₂(NO₃)₂} bridging unit. 3 is a linear Fe₃ complex with no monatomic bridges between Fe^III ions, a very rare situation in Fe^III chemistry with any ligands and unprecedented in Fe carboxylate chemistry. The distinct differences observed in arsinate vs carboxylate ligation modes are rationalized largely based on the greater basicity of the former vs the latter. Variable-temperature dc and ac magnetic susceptibility data reveal all Fe₂ pairwise interactions to be antiferromagnetic. For 1 and 2, the different J_ij couplings were estimated by use of a magnetostructural correlation for high nuclearity Fe^III-oxo clusters and by density functional theory calculations using broken symmetry methods, allowing identification of their relative spin vector alignments and thus rationalization of their S = 0 ground states. The J_ij values were then used as input values to give excellent fits of the experimental χ_MT vs T data. For 3, the fits of the experimental χ_MT vs T data to the Van Vleck equation or with PHI gave a very weak J₁₂ = -0.8(1) cm^-1 (H = -2JŜ_i·Ŝ_j convention) between adjacent Fe^III ions and an S = ⁵/₂ ground state. These initial Fe^III arsinate complexes also provide structural parameters that help validate literature assignments of arsinate binding modes to iron oxide/hydroxide minerals as part of environmental concerns of using arsenic-containing herbicides in agriculture.

High-Level Antibiotic Tolerance of a Clinically Isolated Enterococcus faecalis Strain

Bacteria can survive antibiotic treatment both by acquiring antibiotic resistance genes and through mechanisms of tolerance that are based on phenotypic changes and the formation of metabolically inactive cells. Here, we report an Enterococcus faecalis strain (E. faecalis UM001B) that was isolated from a cystic fibrosis patient and had no increase in resistance but extremely high-level tolerance to ampicillin, vancomycin, and tetracycline. Specifically, the percentages of cells that survived 3.5-h antibiotic treatment (at 100 μg · ml^-1) were 25.4% ± 4.3% and 51.9% ± 4.0% for ampicillin and tetracycline, respectively; vancomycin did not exhibit any significant killing. Consistent with the changes in antibiotic susceptibility, UM001B was found to have reduced penetration of ampicillin and vancomycin and accumulation of tetracycline compared to the reference strain ATCC 29212. Based on whole-genome sequencing, four amino acid substitutions were identified in one of the tetracycline efflux pump repressors (TetRs), compared to ATCC 29212. Results of molecular simulations and experimental assays revealed that these mutations could lead to higher levels of tetracycline efflux activity. Consistently, replicating these mutations in Escherichia coli MG1655 increased its tolerance to tetracycline. Overall, these findings provide new insights into the development of multidrug tolerance in E. faecalis, which can facilitate future studies to better control enterococcal infections.IMPORTANCE Enterococcus faecalis represents a major group of pathogens causing nosocomial infections that are resistant to multiple classes of antibiotics. An important challenge associated with E. faecalis infection is the emergence of multidrug-tolerant strains, which have normal MICs but do not respond to antibiotic treatment. Here, we report a strain of E. faecalis that was isolated from a cystic fibrosis patient and demonstrated high-level tolerance to ampicillin, vancomycin, and tetracycline. Whole-genome sequencing revealed critical substitutions in one of the tetracycline efflux pump repressors that are consistent with the increased tolerance of E. faecalis UM001B to tetracycline. These findings provide new information about bacterial antibiotic tolerance and may help develop more effective therapeutics.

In Ovo and In Silico Evaluation of the Anti-Angiogenic Potential of Syringin

INTRODUCTION

Cancer is considered as one of the deadliest human diseases today. Angiogenesis, the propagation of new blood vessels from pre-existing vasculature, is a critical step in the progression of cancer as it is essential in the growth and metastasis of tumors. Hence, suppression of angiogenesis is a promising approach in cancer therapy. Syringin, a phenylpropanoid glycoside with a molecular formula of C17H24O9, has been found to exhibit chemopreventive effects. However, its anti-angiogenic activity and the underlying mechanism of action are still unknown.

METHODS

In this work, in ovo chorioallantoic membrane (CAM) assay has been conducted to evaluate the effect of syringin on neovascularization. Additionally, reverse molecular docking studies have been performed in order to identify the probable enzyme targets in the angiogenesis pathway.

RESULTS

Treatment with syringin showed significant dose-dependent inhibition of blood vessel length and junctions in the CAM of duck eggs; the anti-angiogenic activity of syringin at 100 µM and 200 µM is comparable with 200 µM of the positive control celecoxib. The results of reverse docking studies indicate that syringin binds the strongest to dihydrofolate reductase (DHFR) and, to some extent, with transforming growth factor-beta receptor type 1 (TGF-βR1), vascular endothelial growth factor receptor 2 (VEGFR2), and matrix metalloproteinase-2 (MMP-2). Furthermore, ADMET models revealed that syringin potentially possesses excellent pharmacokinetic and toxicity profiles.

CONCLUSION

This study demonstrates the potential of syringin as an anti-angiogenic agent and elicits further investigations to establish its application in cancer suppression.

Computational investigation for identification of potential phytochemicals and antiviral drugs as potential inhibitors for RNA-dependent RNA polymerase of COVID-19

Since the SARS/MERS epidemic, scientists across the world have been racing to identify the novel-CoVs as it has been predicted that next epidemic can very well be a result from a new mutation of CoV, for which hundred mutations have already been discovered, and the same fear has come true with world facing a raging pandemic due to COVID-19, an infectious disease caused by a newly discovered coronavirus. COVID-19 or Severe acute respiratory syndrome coronavirus2 (SARS-CoV-2), is a single stranded RNA virus. COVID −19 is highly contagious and has resulted in current global pandemic with almost no country of the world unaffected by this virus. Owing to the lack of effective therapeutics or vaccines, the best measures to control human coronaviruses remain a strong public health surveillance system coupled with rapid diagnostic testing and quarantine/social; distancing/lockdowns as and when necessary. In the present study, we have used the insilico approach for the prediction of novel drug molecules from available antiviral drugs and also from natural compounds that can be best target against RNA-dependent RNA-polymerase (Pol/RdRp) protein of SARS-CoV-2 which can be suitable drugs for the treatment of COVID-19 virus. From the current study we observed that three antiviral and three phyto-chemicals have minimum binding energy with the target protein which were further evaluated in molecular dynamics studies and could specifically bind to RdRp protein of COVID-19. Based on results we suggest that these drugs may act as best or novel inhibitor that may be used for the treatment of SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Including residual contact information into replica-exchange MD simulations significantly enriches native-like conformations

Proteins are complex biomolecules which perform critical tasks in living organisms. Knowledge of a protein's structure is essential for understanding its physiological function in detail. Despite the incredible progress in experimental techniques, protein structure determination is still expensive, time-consuming, and arduous. That is why computer simulations are often used to complement or interpret experimental data. Here, we explore how in silico protein structure determination based on replica-exchange molecular dynamics (REMD) can benefit from including contact information derived from theoretical and experimental sources, such as direct coupling analysis or NMR spectroscopy. To reflect the influence from erroneous and noisy data we probe how false-positive contacts influence the simulated ensemble. Specifically, we integrate varying numbers of randomly selected native and non-native contacts and explore how such a bias can guide simulations towards the native state. We investigate the number of contacts needed for a significant enrichment of native-like conformations and show the capabilities and limitations of this method. Adhering to a threshold of approximately 75% true-positive contacts within a simulation, we obtain an ensemble with native-like conformations of high quality. We find that contact-guided REMD is capable of delivering physically reasonable models of a protein's structure.

l-3,4-Dihydroxyphenylalanine templated anisotropic gold nano/micro-roses as potential disrupters/inhibitors of α-crystallin protein and its gleaned model peptide aggregates

Cataract, the major cause of blindness worldwide occurs due to the misfolding and aggregation of the protein crystallin, which constitute a major portion of the lens protein. Other than the whole protein crystallin, the peptide sequences generated from crystallin as a result of covalent protein damage have also been shown to possess and foster protein aggregation, which can be established as crystallin aggregation models. Thus, the disaggregation or inhibition of these protein aggregates could be a viable approach to combat cataract and preserve lens proteostasis. Herein, we tried to explore the disruption as well as inhibition of the intact α-crystallin protein and α-crystallin derived model peptide aggregates by l-3,4-dihydroxyphenylalanine (levodopa) coated gold (Au) nano/micro-roses as modulators. Thioflavin T fluorescence enhancement assay, and electron microscopic analysis were being employed to probe the anti-aggregation behavior of the Au nano/micro-roses towards the aggregating α-crystallin peptides/protein. Further, computational studies were performed to reveal the nature of molecular interactions between the levodopa molecule and the α-crystallin derived model peptides. Interestingly, both levodopa coated Au nano/micro-roses were found to be capable of inhibiting as well as preventing the aggregation of the intact α-crystallin protein and other model peptides derived from it.

An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets

Notch family proteins play a key role in a variety of developmental processes by controlling cell fate decisions and operating in a great number of biological processes in several organ systems, such as hematopoiesis, somatogenesis, vasculogenesis, neurogenesis and homeostasis. The Notch signaling pathway is crucial for the majority of developmental programs and regulates multiple pathogenic processes. Notch family receptors' activation has been largely related to its multiple effects in sustaining oncogenesis. The Notch signaling pathway constitutes an ancient and conserved mechanism for cell to cell communication. Much of what is known about Notch family proteins function comes from studies done in Caenorhabditis Elegans and Drosophila Melanogaster. Although, human Notch homologs had also been identified, the molecular mechanisms which modulate the Notch signaling pathway remained substantially unknown. In this study, an updated evolutionary analysis of the Notch family members among 603 different organisms of all kingdoms, from bacteria to humans, was performed in order to discover key regions that have been conserved throughout evolution and play a major role in the Notch signaling pathway. The major goal of this study is the presentation of a novel updated phylogenetic tree for the Notch family as a reliable phylogeny "map", in order to correlate information of the closely related members and identify new possible pharmacological targets that can be used in pathogenic cases, including cancer.

Comparative Proteome Analysis of Mycobacterium Tuberculosis Strains - H37Ra, H37Rv, CCDC5180, and CAS/NITR204: A Step Forward to Identify Novel Drug Targets

Background:

Mycobacterium tuberculosis is a causative agent of tuberculosis. It is a non-motile, acid-fast, obligatory aerobic bacterium. Finding novel drug targets in Mycobacterium tuberculosis has become extremely important as the bacterium is evolving into a more dangerous multi-drug resistant pathogen. The predominant strains in India belong to the Central-Asian, East- African Indian, and Beijing clad. For the same reason, the whole proteomes of a non-virulent strain (H37Ra), a virulent (H37Rv) and two clinical strains, a Central-Asian clad (CAS/NITR204) and a Beijing clad (CCDC5180) have been selected for comparative study. Selecting a phylogenetically close and majorly studied non-virulent strain is helpful in removing the common and undesired proteins from the study.

Objective:

The study compares the whole proteome of non-virulent strain with the other three virulent strains to find a unique protein responsible for virulence in virulent strains. It is expected that the drugs developed against identified targets will be specific to the virulent strains. Additionally, to assure minimal toxicity to the host, we also screened the human proteome.

Methods:

Comparative proteome analysis was used for target identification and in silico validation of identified target protein Rv2466c, identification of the respective ligand of the identified target protein and binding interaction study using Molecular docking and Molecular Dynamic Simulation study were used in this study.

Results and Discussion:

Finally, eleven proteins were found to be unique in virulent strain only and out of which, Rv2466c (PDB-ID: 4ZIL) was found to be an essential protein and identified as a putative drug target protein for further study. The compound glutathione was found to be a suitable inhibitor for Rv2466c. In this study, we used a comparative proteomics approach to identify novel target proteins.

Conclusion:

This study is unique as we are assured that the study will move forward the research in a new direction to cure the deadly disease (tuberculosis) caused by Mycobacterium tuberculosis. Rv2466c was identified as a novel drug target and glutathione as a respective ligand of Rv2466c. Discovery of the novel drug target as well as the drug will provide a solution to drug resistance as well as the infection caused by Mycobacterium tuberculosis.

Structure Prediction of a Thermostable SR74 α-Amylase from Geobacillus stearothermophilus Expressed in CTG-Clade Yeast Meyerozyma guilliermondii Strain SO

α-amylase which catalyzes the hydrolysis of α-1,4-glycosidic bonds in starch have frequently been cloned into various microbial workhorses to yield a higher recombinant titer. A thermostable SR74 α-amylase from Geobacillus stearothermophilus was found to have a huge potential in detergent industries due to its thermostability properties. The gene was cloned into a CTG-clade yeast Meyerozyma guilliermondii strain SO. However, the CUG ambiguity present in the strain SO has possibly altered the amino acid residues in SR74 amylase wild type (WT) encoded by CUG the codon from the leucine to serine. From the multiple sequence alignment, six mutations were found in recombinant SR74 α-amylase (rc). Their effects on SR74 α-amylase structure and function remain unknown. Herein, we predicted the structures of the SR74 amylases (WT and rc) using the template 6ag0.1.A (PDB ID: 6ag0). We sought to decipher the possible effects of CUG ambiguity in strain SO via in silico analysis. They are structurally identical, and the metal triad (CaI–CaIII) might contribute to the thermostability while CaIV was attributed to substrate specificity. Since the pairwise root mean square deviation (RMSD) between the WT and rc SR74 α-amylase was lower than the template, we suggest that the biochemical properties of rc SR74 α-amylase were better deduced from its WT, especially its thermostability.

A new Piper nigrum cysteine proteinase inhibitor, PnCPI, with antifungal activity: molecular cloning, recombinant expression, functional analyses and molecular modeling

A new Piper nigrum cysteine proteinase inhibitor, PnCPI, belonging to group I of phytocystatins, with inhibitory activity against papain and growth of Fusarium solani f. sp. piperis, was isolated and characterized. Previous studies (de Souza et al. 2011) have identified a partial cDNA sequence of putative cysteine proteinase inhibitor differentially expressed in roots of black pepper (P. nigrum L.) infected by F. solani f. sp. piperis. Here, we aimed to isolate the full-length cDNA and genomic sequences of the P. nigrum cysteine proteinase inhibitor gene, named PnCPI. Sequence analyses showed that the PnCPI gene encodes a deduced protein of 108 amino acid residues with a predicted molecular mass of 12.3 kDa and isoelectric point of 6.51. Besides the LARFAV-like sequence, common to all phytocystatins, PnCPI contains three conserved motifs of the superfamily cystatin: a glycine residue at the N-terminal region, the QxVxG reactive site more centrally positioned, and one tryptophan in the C-terminal region. PnCPI, belonging to group I of phytocystatins, showed high identity with cystatins isolated from several plant species. Sequence analyses also revealed no putative signal peptide at the N-terminal of PnCPI, as well as no introns within the genomic sequence corresponding to the PnCPI coding region. Molecular modeling showed the ability of PnCPI to interact with papain, while its inhibitory activity against this protease was confirmed after heterologous expression in Escherichia coli. The effects of heat treatments on the inhibitory activity of recombinant PnCPI, rPnCPI, were evaluated. In addition, rPnCPI exhibited in vitro activity against F. solani f. sp. piperis, revealing a new cystatin with the potential antifungal application. The identification of PnCPI as a functional cystatin able to inhibit the in vitro growth of F. solani f. sp. piperis indicates other factors contributing to in vivo susceptibility of black pepper to root rot disease.

Understanding the Binding Mechanism of Antagonist (AZD3293) Against BACE-1: Molecular Insights into Alzheimer’s Drug Discovery

Background:

β-site amyloid precursor protein cleaving enzyme (BACE 1) is the ratelimiting enzyme in the formation of neurotoxic β-amyloid (Aβ) residues (Aβ1-40 or Aβ1-42) considered as key players in the onset of Alzheimer’s Disease (AD). Consequently, BACE 1 is one of the principal targets of anti-AD therapy with many small molecule BACE 1 inhibitors (BACE 1Is) in clinical trials. AZD3293 (Lanabecestat) is a BACE 1I that concluded in phase 2/3 clinical trials. Due to the limited knowledge about the interaction of this drug with the BACE 1 enzyme, in the present study, we performed comprehensive Molecular Dynamics (MD) analysis to understand the binding mechanism of AZD3293 to BACE 1.

Methods:

A production run of 120 ns is carried out and results are analysed using Root Mean Square Deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) to explain the stability of enzyme ligand complex. Further, the distance (d1) between the flap tip (Thr72) and the hinge residue of the flexible loop (Thr328), in relation to θ1 (Thr72–Asp228- Thr328), and to the dihedral angle δ (Thr72-Asp35-Asp228-Thr328) were measured.

Results:

The presence of the ligand within the active site restricted conformational changes as shown by decreased values of RMSF and average RMSD of atomic positions when compared to the values of the apoenzyme. Further analysis via the flap dynamics approach revealed that the AZD3293 decreases the flexibility of binding residues and made them rigid by altering the conformational changes.

Conclusion:

The prospective binding modes of AZD3293 from this study may extend the knowledge of the BACE 1-drug interaction and pave the way to design analogues with similar inhibitory properties needed to slow the progression of Alzheimer’s disease.

Interactions of the α3β2 Nicotinic Acetylcholine Receptor Interfaces with α-Conotoxin LsIA and its Carboxylated C-terminus Analogue: Molecular Dynamics Simulations

Notably, α-conotoxins with carboxy-terminal (C-terminal) amidation are inhibitors of the pentameric nicotinic acetylcholine receptors (nAChRs), which are therapeutic targets for neurological diseases and disorders. The (α3)₂(β2)₃ nAChR subunit arrangement comprises a pair of α3(+)β2(−) and β2(+)α3(−) interfaces, and a β2(+)β2(−) interface. The β2(+)β2(−) interface has been suggested to have higher agonist affinity relative to the α3(+)β2(−) and β2(+)α3(−) interfaces. Nevertheless, the interactions formed by these subunit interfaces with α-conotoxins are not well understood. Therefore, in order to address this, we modelled the interactions between α-conotoxin LsIA and the α3β2 subtype. The results suggest that the C-terminal carboxylation of LsIA predominantly influenced the enhanced contacts of the conotoxin via residues P7, P14 and C17 on LsIA at the α3(+)β2(−) and β2(+)α3(−) interfaces. However, this enhancement is subtle at the β2(+)β2(−) site, which can compensate the augmented interactions by LsIA at α3(+)β2(−) and β2(+)α3(−) binding sites. Therefore, the divergent interactions at the individual binding interface may account for the minor changes in binding affinity to α3β2 subtype by C-terminal carboxylation of LsIA versus its wild type, as shown in previous experimental results. Overall, these findings may facilitate the development of new drug leads or subtype-selective probes.

In silico analysis and identification of promising hits against 2019 novel coronavirus 3C-like main protease enzyme

The recent outbreak of the 2019 novel coronavirus disease (COVID-19) has been proved as a global threat. No particular drug or vaccine has not yet been discovered which may act specifically against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and causes COVID-19. For this highly infectious virus, 3CL-like main protease (3CL^pro) plays a key role in the virus life cycle and can be considered as a pivotal drug target. Structure-based virtual screening of DrugBank database resulted in 20 hits against 3CL^pro. Atomistic 100 ns molecular dynamics of five top hits and binding energy calculation analyses were performed for main protease-hit complexes. Among the top five hits, Nafarelin and Icatibant affirmed the binding energy (g_MMPBSA) of -712.94 kJ/mol and -851.74 kJ/mol, respectively. Based on binding energy and stability of protein-ligand complex; the present work reports these two drug-like hits against SARS-CoV-2 main protease.Communicated by Ramaswamy H. Sarma.

Distance-Based Metrics for Comparing Conformational Ensembles of Intrinsically Disordered Proteins

Intrinsically disordered proteins are proteins whose native functional states represent ensembles of highly diverse conformations. Such ensembles are a challenge for quantitative structure comparisons because their conformational diversity precludes optimal superimposition of the atomic coordinates necessary for deriving common similarity measures such as the root mean-square deviation of these coordinates. Here, we introduce superimposition-free metrics that are based on computing matrices of the Cα-Cα distance distributions within ensembles and comparing these matrices between ensembles. Differences between two matrices yield information on the similarity between specific regions of the polypeptide, whereas the global structural similarity is captured by the root mean-square difference between the medians of the Cα-Cα distance distributions of two ensembles. Together, our metrics enable rigorous investigations of structure-function relationships in conformational ensembles of intrinsically disordered proteins derived using experimental restraints or by molecular simulations and for proteins containing both structured and disordered regions.

Meridianins and Lignarenone B as Potential GSK3β Inhibitors and Inductors of Structural Neuronal Plasticity

Glycogen Synthase Kinase 3 (GSK3) is an essential protein, with a relevant role in many diseases such as diabetes, cancer and neurodegenerative disorders. Particularly, the isoform GSK3β is related to pathologies such as Alzheimer's disease (AD). This enzyme constitutes a very interesting target for the discovery and/or design of new therapeutic agents against AD due to its relation to the hyperphosphorylation of the microtubule-associated protein tau (MAPT), and therefore, its contribution to neurofibrillary tangles (NFT) formation. An in silico target profiling study identified two marine molecular families, the indole alkaloids meridianins from the tunicate genus Aplidium, and lignarenones, the secondary metabolites of the shelled cephalaspidean mollusc Scaphander lignarius, as possible GSK3β inhibitors. The analysis of the surface of GSK3β, aimed to find possible binding regions, and the subsequent in silico binding studies revealed that both marine molecular families can act over the ATP and/or substrate binding regions. The predicted inhibitory potential of the molecules from these two chemical families was experimentally validated in vitro by showing a ~50% of increased Ser9 phosphorylation levels of the GSK3β protein. Furthermore, we determined that molecules from both molecular families potentiate structural neuronal plasticity in vitro. These results allow us to suggest that meridianins and lignarenone B could be used as possible therapeutic candidates for the treatment of GSK3β involved pathologies, such as AD.

Whole exome sequencing of a Saudi family and systems biology analysis identifies CPED1 as a putative causative gene to Celiac Disease

Celiac disease (CD) is a gastrointestinal disorder whose genetic basis is not fully understood. Therefore, we studied a Saudi family with two CD affected siblings to discover the causal genetic defect. Through whole exome sequencing (WES), we identified that both siblings have inherited an extremely rare and deleterious CPED1 genetic variant (c.241 A > G; p.Thr81Ala) segregating as autosomal recessive mutation, suggesting its putative causal role in the CD. Saudi population specific minor allele frequency (MAF) analysis has confirmed its extremely rare prevalence in homozygous condition (MAF is 0.0004). The Sanger sequencing analysis confirmed the absence of this homozygous variant in 100 sporadic Saudi CD cases. Genotype-Tissue Expression (GTEx) data has revealed that CPED1 is abundantly expressed in gastrointestinal mucosa. By using a combination of systems biology approaches like protein 3D modeling, stability analysis and nucleotide sequence conservation analysis, we have further established that this variant is deleterious to the structural and functional aspects of CPED1 protein. To the best of our knowledge, this variant has not been previously reported in CD or any other gastrointestinal disease. The cell culture and animal model studies could provide further insight into the exact role of CPED1 p.Thr81Ala variant in the pathophysiology of CD. In conclusion, by using WES and systems biology analysis, present study for the first-time reports CPED1 as a potential causative gene for CD in a Saudi family with potential implications to both disease diagnosis and genetic counseling.

Effects of unsaturated fatty acids (Arachidonic/Oleic Acids) on stability and structural properties of Calprotectin using molecular docking and molecular dynamics simulation approach

Calprotectin is a heterodimeric protein complex with two subunits called S100A8/A9. The protein has an essential role in inflammation process and various human diseases. It has the ability to bind to unsaturated fatty acids including Arachidonic acid, Oleic acid and etc., which could be considered as a major carrier for fatty acids. In this study we aimed to appraise the thermodynamics and structural changes of Calprotectin in presence of Arachidonic acid/Oleic acid) using docking and molecular dynami simulation method. To create the best conformation of Calprotectin-Oleic acid/Arachidonic acid complexes, the docking process was performed. The complexes with the best binding energy were selected as the models for molecular dynamics simulation process. Furthermore, the structural and thermodynamics properties of the complexes were evaluated too. The Root Mean Square Deviation and Root Mean Square Fluctuation results showed that the binding of Arachidonic acid/Oleic acid to Calprotectin can cause the protein structural changes which was confirmed by Define Secondary Structure of Proteins results. Accordingly, the binding free energy results verified that binding of Oleic acid to Calprotectin leads to instability of S100A8/A9 subunits in the protein. Moreover, the electrostatic energy contribution of the complexes (Calprotectin-Oleic acid/Arachidonic acid) was remarkably higher than van der Waals energy. Thus, the outcome of this study confirm that Oleic acid has a stronger interaction with Calprotectin in comparison with Arachidonic acid. Our findings indicated that binding of unsaturated fatty acids to Calprotectin leads to structural changes of the S100A8/A9 subunits which could be beneficial to play a biological role in inflammation process.

In silico identification of novel 5-HT2A antagonists supported with ligand- and target-based drug design methodologies

A wide range of neuropsychological disorders is caused by serotonin 5-HT_2A receptor (5-HT_2AR) malfunction. Therefore, this receptor had been frequently used as target in CNS drug research. To design novel potent 5-HT_2AR antagonists, we have combined ligand-based and target-based approaches. This study was performed on wide range of structurally diverse antagonists that were divided into three different clusters: clozapine, ziprasidone, and ChEMBL240876 derivatives. By performing the 50 ns long molecular dynamic simulations with each cluster representative in complex with 5-HT_2A receptor, we have obtained virtually bioactive conformations of the ligands and three different antagonist-bound, inactive, conformations of the 5-HT_2AR. These three 5-HT_2AR conformations were further used for docking studies and generation of the bioactive conformations of the data set ligands in each cluster. Subsequently, selected conformers were used for 3D-Quantitative Structure Activity Relationship (3D-QSAR) modelling and pharmacophore analysis. The reliability and predictive power of the created model was assessed using an external test set compounds and showed reasonable external predictability. Statistically significant variables were used to define the most important structural features required for 5-HT_2A antagonistic activity. Conclusions obtained from performed ligand-based (3D-QSAR) and target-based (molecular docking and molecular dynamics) methods were compiled and used as guidelines for rational drug design of novel 5-HT_2AR antagonists.Communicated by Ramaswamy H. Sarma.

Discrete analysis of camelid variable domains: sequences, structures, and in-silico structure prediction

Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only three CDR loops from the single variable domain (V_HH) at the N-terminus of each heavy chain. This feature of the V_HH, along with their other important features, e.g., easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better V_HH domains, it is important to thoroughly understand their sequence and structure characteristics and relationship. In this study, sequence characteristics of V_HH domains have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of V_HH domains showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of V_HH, an exciting view of various factors in structure prediction of V_HH, like template framework selection, is also discussed.

Phosphoinositide-binding proteins mark, shape and functionally modulate highly-diverged endocytic compartments in the parasitic protist Giardia lamblia

Phosphorylated derivatives of phosphatidylinositol (PIPs) are key membrane lipid residues involved in clathrin-mediated endocytosis (CME). CME relies on PIP species PI(4,5)P₂ to mark endocytic sites at the plasma membrane (PM) associated to clathrin-coated vesicle (CCV) formation. The highly diverged parasitic protist Giardia lamblia presents disordered and static clathrin assemblies at PM invaginations, contacting specialized endocytic organelles called peripheral vacuoles (PVs). The role for clathrin assemblies in fluid phase uptake and their link to internal membranes via PIP-binding adaptors is unknown. Here we provide evidence for a robust link between clathrin assemblies and fluid-phase uptake in G. lamblia mediated by proteins carrying predicted PX, FYVE and NECAP1 PIP-binding modules. We show that chemical and genetic perturbation of PIP-residue binding and turnover elicits novel uptake and organelle-morphology phenotypes. A combination of co-immunoprecipitation and in silico analysis techniques expands the initial PIP-binding network with addition of new members. Our data indicate that, despite the partial conservation of lipid markers and protein cohorts known to play important roles in dynamic endocytic events in well-characterized model systems, the Giardia lineage presents a strikingly divergent clathrin-centered network. This includes several PIP-binding modules, often associated to domains of currently unknown function that shape and modulate fluid-phase uptake at PVs.

In well-characterized model eukaryotes, clathrin-mediated endocytosis is a key process for uptake of extracellular material and is regulated by more than 50 known proteins. A large number of these carry phosphoinositide (PIP)-binding domains and play a central role in the regulation of endocytosis. Here, we report on the detailed functional characterization of PIP-binding proteins in the intestinal parasitic protist Giardia lamblia. We show evidence that proteins carrying specific PIP-binding domains are directly involved in fluid-phase uptake. Furthermore, using co-immunoprecipitation assays, we confirm these proteins’ association to G. lamblia’s clathrin assemblies. In addition, using state-of-the-art imaging strategies, we demonstrate a previously unappreciated level of complexity involving PIPs and their partner proteins in marking and shaping G. lamblia’s unique endocytic compartments. Our data contribute substantially to an updated working model for G. lamblia’s host-parasite interface, demonstrating how uptake in this parasite is directly regulated by a variety of PIP residues and PIP-binding modules, which have been re-routed from conserved pathways, likely as a result of host-parasite co-evolution.

Obtaining Tertiary Protein Structures by the ab Initio Interpretation of Small Angle X-ray Scattering Data

Small angle X-ray scattering (SAXS) is an important tool for investigating the structure of proteins in solution. We present a novel ab initio method representing polypeptide chains as discrete curves used to derive a meaningful three-dimensional model from only the primary sequence and SAXS data. High resolution structures were used to generate probability density functions for each common secondary structural element found in proteins, which are used to place realistic restraints on the model curve’s geometry. This is coupled with a novel explicit hydration shell model in order to derive physically meaningful three-dimensional models by optimizing against experimental SAXS data. The efficacy of this model is verified on an established benchmark protein set, and then it is used to predict the lysozyme structure using only its primary sequence and SAXS data. The method is used to generate a biologically plausible model of the coiled-coil component of the human synaptonemal complex central element protein.

SPECS: Integration of side-chain orientation and global distance-based measures for improved evaluation of protein structural models

Significant advancements in the field of protein structure prediction have necessitated the need for objective and robust evaluation of protein structural models by comparing predicted models against the experimentally determined native structures to quantitate their structural similarities. Existing protein model versus native similarity metrics either consider the distances between alpha carbon (Cα) or side-chain atoms for computing the similarity. However, side-chain orientation of a protein plays a critical role in defining its conformation at the atomic-level. Despite its importance, inclusion of side-chain orientation in structural similarity evaluation has not yet been addressed. Here, we present SPECS, a side-chain-orientation-included protein model-native similarity metric for improved evaluation of protein structural models. SPECS combines side-chain orientation and global distance based measures in an integrated framework using the united-residue model of polypeptide conformation for computing model-native similarity. Experimental results demonstrate that SPECS is a reliable measure for evaluating structural similarity at the global level including and beyond the accuracy of Cα positioning. Moreover, SPECS delivers superior performance in capturing local quality aspect compared to popular global Cα positioning-based metrics ranging from models at near-experimental accuracies to models with correct overall folds-making it a robust measure suitable for both high- and moderate-resolution models. Finally, SPECS is sensitive to minute variations in side-chain χ angles even for models with perfect Cα trace, revealing the power of including side-chain orientation. Collectively, SPECS is a versatile evaluation metric covering a wide spectrum of protein modeling scenarios and simultaneously captures complementary aspects of structural similarities at multiple levels of granularities. SPECS is freely available at http://watson.cse.eng.auburn.edu/SPECS/.

Protein Thermodynamic Destabilization in the Assessment of Pathogenicity of a Variant of Uncertain Significance in Cardiac Myosin Binding Protein C

In the era of next generation sequencing (NGS), genetic testing for inherited disorders identifies an ever-increasing number of variants whose pathogenicity remains unclear. These variants of uncertain significance (VUS) limit the reach of genetic testing in clinical practice. The VUS for hypertrophic cardiomyopathy (HCM), the most common familial heart disease, constitute over 60% of entries for missense variants shown in ClinVar database. We have studied a novel VUS (c.1809T>G-p.I603M) in the most frequently mutated gene in HCM, MYBPC3, which codes for cardiac myosin-binding protein C (cMyBPC). Our determinations of pathogenicity integrate bioinformatics evaluation and functional studies of RNA splicing and protein thermodynamic stability. In silico prediction and mRNA analysis indicated no alteration of RNA splicing induced by the variant. At the protein level, the p.I603M mutation maps to the C4 domain of cMyBPC. Although the mutation does not perturb much the overall structure of the C4 domain, the stability of C4 I603M is severely compromised as detected by circular dichroism and differential scanning calorimetry experiments. Taking into account the highly destabilizing effect of the mutation in the structure of C4, we propose reclassification of variant p.I603M as likely pathogenic. Looking into the future, the workflow described here can be used to refine the assignment of pathogenicity of variants of uncertain significance in MYBPC3.

Multi-state design of flexible proteins predicts sequences optimal for conformational change

Computational protein design of an ensemble of conformations for one protein–i.e., multi-state design–determines the side chain identity by optimizing the energetic contributions of that side chain in each of the backbone conformations. Sampling the resulting large sequence-structure search space limits the number of conformations and the size of proteins in multi-state design algorithms. Here, we demonstrated that the REstrained CONvergence (RECON) algorithm can simultaneously evaluate the sequence of large proteins that undergo substantial conformational changes. Simultaneous optimization of side chain conformations across all conformations increased sequence conservation when compared to single-state designs in all cases. More importantly, the sequence space sampled by RECON MSD resembled the evolutionary sequence space of flexible proteins, particularly when confined to predicting the mutational preferences of limited common ancestral descent, such as in the case of influenza type A hemagglutinin. Additionally, we found that sequence positions which require substantial changes in their local environment across an ensemble of conformations are more likely to be conserved. These increased conservation rates are better captured by RECON MSD over multiple conformations and thus multiple local residue environments during design. To quantify this rewiring of contacts at a certain position in sequence and structure, we introduced a new metric designated ‘contact proximity deviation’ that enumerates contact map changes. This measure allows mapping of global conformational changes into local side chain proximity adjustments, a property not captured by traditional global similarity metrics such as RMSD or local similarity metrics such as changes in φ and ψ angles.

Multi-state design can be used to engineer proteins that need to exist in multiple conformations or that bind to multiple partner molecules. In essence, multi-state design selects a compromise of protein sequences that allow for an ensemble of protein conformations, or states, associated with a particular biological function. In this paper, we used the REstrained CONvergence (RECON) algorithm with Rosetta to show that multi-state design of flexible proteins predicts sequences optimal for conformational change, mimicking mutation preferences sampled in evolution. Modeling optimal local side chain physicochemical environments within an ensemble selected significantly more native-like sequences than selections performed when all conformations states are designed independently. This outcome was particularly true for amino acids whose local side chain environment change between conformations. To quantify such contact map changes, we introduced a novel metric to show that sequence conservation is dependent on protein flexibility, i.e., changes in local side chain environments between stated limit the space of tolerated mutations. Additionally, such positions in sequence and structure are more likely to be energetically frustrated, at least in some states. Importantly, we showed that multi-state design over an ensemble of conformations (space) can explore evolutionary tolerated sequence space (time), thus enabling RECON to not only design proteins that require multiple states for function but also predict mutations that might be tolerated in native proteins but have not yet been explored by evolution. The latter aspect can be important to anticipate escape mutations, for example in pathogens or oncoproteins.

Elucidating Binding Sites and Affinities of ERα Agonists and Antagonists to Human Alpha-Fetoprotein by In Silico Modeling and Point Mutagenesis

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting a variety of hydrophobic ligands, including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth, which can be attributed to its estrogen-binding ability. Despite AFP having long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP–ligand interaction remains obscure. In our study, we constructed a homology-based 3D model of human AFP (HAFP) with the purpose of molecular docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol), and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on the ligand-docked scoring functions, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity binding sites were located (i) in a tunnel formed within HAFP subdomains IB and IIA and (ii) on the opposite side of the molecule in a groove originating from a cavity formed between domains I and III, while (iii) the third low-affinity binding site was found at the bottom of the cavity. Here, 100 ns molecular dynamics (MD) simulation allowed us to study their geometries and showed that HAFP–estrogen interactions were caused by van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP–antiestrogen binding. Molecular mechanics/Generalized Born surface area (MM/GBSA) rescoring method exploited for estimation of binding free energies (ΔG_bind) showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP–ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues, along with two disulfide bonds (Cys224–Cys270 and Cys269–Cys277), have key roles in both HAFP–estrogen and HAFP–antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein–ligand interactions and anticancer therapy strategies based on ERα-binding ligands.

CD4 T Cell Determinants in West Nile Virus Disease and Asymptomatic Infection

West Nile (WN) virus infection of humans is frequently asymptomatic, but can also lead to WN fever or neuroinvasive disease. CD4 T cells and B cells are critical in the defense against WN virus, and neutralizing antibodies, which are directed against the viral glycoprotein E, are an accepted correlate of protection. For the efficient production of these antibodies, B cells interact directly with CD4 helper T cells that recognize peptides from E or the two other structural proteins (capsid-C and membrane-prM/M) of the virus. However, the specific protein sites yielding such helper epitopes remain unknown. Here, we explored the CD4 T cell response in humans after WN virus infection using a comprehensive library of overlapping peptides covering all three structural proteins. By measuring T cell responses in 29 individuals with either WN virus disease or asymptomatic infection, we showed that CD4 T cells focus on peptides in specific structural elements of C and at the exposed surface of the pre- and postfusion forms of the E protein. Our data indicate that these immunodominant epitopes are recognized in the context of multiple different HLA molecules. Furthermore, we observed that immunodominant antigen regions are structurally conserved and similarly targeted in other mosquito-borne flaviviruses, including dengue, yellow fever, and Zika viruses. Together, these findings indicate a strong impact of virion protein structure on epitope selection and antigenicity, which is an important issue to consider in future vaccine design.

Comparative analysis of methods for evaluation of protein models against native structures

MOTIVATION

Measuring discrepancies between protein models and native structures is at the heart of development of protein structure prediction methods and comparison of their performance. A number of different evaluation methods have been developed; however, their comprehensive and unbiased comparison has not been performed.

RESULTS

We carried out a comparative analysis of several popular model assessment methods (RMSD, TM-score, GDT, QCS, CAD-score, LDDT, SphereGrinder and RPF) to reveal their relative strengths and weaknesses. The analysis, performed on a large and diverse model set derived in the course of three latest community-wide CASP experiments (CASP10-12), had two major directions. First, we looked at general differences between the scores by analyzing distribution, correspondence and correlation of their values as well as differences in selecting best models. Second, we examined the score differences taking into account various structural properties of models (stereochemistry, hydrogen bonds, packing of domains and chain fragments, missing residues, protein length and secondary structure). Our results provide a solid basis for an informed selection of the most appropriate score or combination of scores depending on the task at hand.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploration of the effects of sequence variations between HIV-1 and HIV-2 proteases on their three-dimensional structures

HIV protease inhibitors (PIs) approved by the FDA (US Food and Drug Administration) are a major class of antiretroviral. HIV-2 protease (PR2) is naturally resistant to most of them as PIs were designed for HIV-1 protease (PR1). In this study, we explored the impact of amino-acid substitutions between PR1 and PR2 on the structure of protease (PR) by comparing the structural variability of 13 regions using 24 PR1 and PR2 structures complexed with diverse ligands. Our analyses confirmed structural rigidity of the catalytic region and highlighted the important role of three regions in the conservation of the catalytic region conformation. Surprisingly, we showed that the flap region, corresponding to a flexible region, exhibits similar conformations in PR1 and PR2. Furthermore, we identified regions exhibiting different conformations in PR1 and PR2, which could be explained by the intrinsic flexibility of these regions, by crystal packing, or by PR1 and PR2 substitutions. Some substitutions induce structural changes in the R2 and R4 regions that could have an impact on the properties of PI-binding site and could thus modify PI binding mode. Substitutions involved in structural changes in the elbow region could alter the flexibility of the PR2 flap regions relative to PR1, and thus play a role in the transition from the semi-open form to the closed form, and have an impact on ligand binding. These results improve the understanding of the impact of sequence variations between PR1 and PR2 on the natural resistance of HIV-2 to commercially available PIs.Communicated by Ramaswamy H. Sarma.

Induced fit for cytochrome P450 3A4 based on molecular dynamics

The present study aims at numerically describing to what extent substrate - enzyme complexes in solution may change over time as a natural process of conformational changes for a liganded enzyme in comparison to those movements which occur independently from substrate interaction, i.e. without a ligand. To this end, we selected structurally known pairs of liganded / unliganded CYP450 3A4 enzymes with different geometries hinting at induced fit events. We carried out molecular dynamics simulations (MD) comparing the trajectories in a “cross-over” protocol: (i) we added the ligand to the unliganded crystal form which should adopt geometries similar to the known geometry of the liganded crystal structure during MD, and – conversely – (ii) we removed the bound ligand form the known liganded complex to test if a geometry similar to the known unliganded (apo-) form can be adopted during MD. To compare continues changes we measured root means square deviations and frequencies. Results for case (i) hint at larger conformational changes required for accepting the substrate during its approach to final position – in contrast to case (ii) when mobility is fairly reduced by ligand binding (strain energy). In conclusion, a larger conformational sampling prior to ligand binding and the freezing-in (rigidity) of conformations for bound ligands can be interpreted as two conditions linked to induced-fit.

Degradation of High Energy Materials Using Biological Reduction: A Rational Way to Reach Bioremediation

Explosives molecules have been widely used since World War II, leading to considerable contamination of soil and groundwater. Recently, bioremediation has emerged as an environmentally friendly approach to solve such contamination issues. However, the 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) explosive, which has very low solubility in water, does not provide satisfying results with this approach. In this study, we used a rational design strategy for improving the specificity of the nitroreductase from E. Cloacae (PDB ID 5J8G) toward HMX. We used the Coupled Moves algorithm from Rosetta to redesign the active site around HMX. Molecular Dynamics (MD) simulations and affinity calculations allowed us to study the newly designed protein. Five mutations were performed. The designed nitroreductase has a better fit with HMX. We observed more H-bonds, which productively stabilized the HMX molecule for the mutant than for the wild type enzyme. Thus, HMX’s nitro groups are close enough to the reductive cofactor to enable a hydride transfer. Also, the HMX affinity for the designed enzyme is better than for the wild type. These results are encouraging. However, the total reduction reaction implies numerous HMX derivatives, and each of them has to be tested to check how far the reaction can’ go.

Exploring the Conformational Space of Bcl-2 Protein Variants: Dynamic Contributions of the Flexible Loop Domain and Transmembrane Region

Members of the Bcl-2 protein family regulate apoptosis through interactions with several proteins. A critical intrinsically disordered region (IDR) present in some members of the Bcl-2 family is essential for their function. Also, the structural and conformational plasticity of disordered regions is essential for the regulation of the Bcl-2 protein’s activity. Further, some proteins of the family contain transmembrane-helical regions, which anchor them into organelle membranes. Bcl-2, the archetypical member of the family, is characterized by an IDR labeled as a flexible loop domain (FLD) and a transmembrane domain (TMD). Another member of this family is the Bcl-2A1 protein, containing a TMD but lacking the FLD. To our knowledge, this is the first report which characterizes the individual and simultaneous dynamical contributions of FLD and TMD in Bcl-2 and Bcl-2A1 using molecular dynamics simulations (MDS). We examined the conformational spaces of Bcl-2, Bcl-2A1, and two artificial constructs lacking the TMD (Bcl-2ΔTM and Bcl-2A1ΔTM). As the results show, FLD and TMD stabilized each protein independently when they are present. When they coincided, such as in Bcl-2, an additive stabilizing effect is observed. This information is crucial for understanding the structural mechanisms of interaction in the Bcl-2 family.

Mutations in the Scn8a DIIS4 voltage sensor reveal new distinctions among hypomorphic and null Nav 1.6 sodium channels

Mutations in the voltage-gated sodium channel gene SCN8A cause a broad range of human diseases, including epilepsy, intellectual disability, and ataxia. Here we describe three mouse lines on the C57BL/6J background with novel, overlapping mutations in the Scn8a DIIS4 voltage sensor: an in-frame 9 bp deletion (Δ9), an in-frame 3 bp insertion (∇3) and a 35 bp deletion that results in a frameshift and the generation of a null allele (Δ35). Scn8a ^Δ9/+ and Scn8a ^∇3/+ heterozygous mutants display subtle motor deficits, reduced acoustic startle response, and are resistant to induced seizures, suggesting that these mutations reduce activity of the Scn8a channel protein, Na_v 1.6. Heterozygous Scn8a ^Δ35/+ mutants show no alterations in motor function or acoustic startle response, but are resistant to induced seizures. Homozygous mutants from each line exhibit premature lethality and severe motor impairments, ranging from uncoordinated gait with tremor (Δ9 and ∇3) to loss of hindlimb control (Δ35). Scn8a ^Δ9/Δ9 and Scn8a ^∇3/∇3 homozygous mutants also exhibit impaired nerve conduction velocity, while normal nerve conduction was observed in Scn8a ^Δ35/Δ35 homozygous mice. Our results suggest that hypomorphic mutations that reduce Na_v 1.6 activity will likely result in different clinical phenotypes compared to null alleles. These three mouse lines represent a valuable opportunity to examine the phenotypic impacts of hypomorphic and null Scn8a mutations without the confound of strain-specific differences.

Molecular Dynamics Studies on COX-2 Protein-tyrosine Analogue Complex and Ligand-based Computational Analysis of Halo-substituted Tyrosine Analogues

Background:

The quest for new drug entities and novel structural fragments with applications in therapeutic areas is always at the core of medicinal chemistry.

Methods:

As part of our efforts to develop novel selective cyclooxygenase-2 (COX-2) inhibitors containing tyrosine scaffold. The objective of this study was to identify potent COX-2 inhibitors by dynamic simulation, pharmacophore and 3D-QSAR methodologies. Dynamics simulation was performed for COX-2/tyrosine derivatives complex to characterise structure validation and binding stability. Certainly, Arg120 and Tyr355 residue of COX-2 protein formed a constant interaction with tyrosine inhibitor throughout the dynamic simulation phase. A four-point pharmacophore with one hydrogen bond acceptor, two hydrophobic and one aromatic ring was developed using the HypoGen algorithm. The generated, statistically significant pharmacophore model, Hypo 1 with a correlation coefficient of r2, 0.941, root mean square deviation, 1.15 and total cost value of 96.85.

Results:

The QSAR results exhibited good internal (r2, 0.992) and external predictions (r2pred, 0.814). The results of this study concluded the COX-2 docked complex was stable and interactive like experimental protein structure. Also, it offered vital chemical features with geometric constraints responsible for the inhibition of the selective COX-2 enzyme by tyrosine derivatives.

Conclusion:

In principle, this work offers significant structural understandings to design and develop novel COX-2 inhibitors.

Elevated level of arsenic negatively influences nifH gene expression of isolated soil bacteria in culture condition as well as soil system

Comprehensive studies on the effect of arsenic (As) on free-living diazotrophs that play a crucial role in soil fertility by nitrogen fixation are still scanty. Here, we isolated three free-living bacteria from rice field with potential nitrogen-fixing ability and investigated the impact of As on their nifH gene expression and extracellular polysaccharide (EPS) production in culture condition and soil system. 16S rRNA sequence analysis showed that the isolated bacteria were affiliated to β-Proteobacteria, γ-Proteobacteria and Firmicutes. As(III) exposure to bacterial isolates followed by RT-qPCR analysis revealed that elevated levels of As reduced the expression of nifH gene in selective bacteria, both in culture medium and soil condition. We also noticed reduced production of EPS under higher concentration of As. All the three bacteria showed high tolerance to As(III), able to oxidize As and exhibited significant plant growth-promoting traits. This investigation indicated that an environment exposed with higher concentration of As might perturbed the activity of free-living diazotrophs in agricultural soil system.

Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases

The identification of interactions between drugs/compounds and their targets is crucial for the development of new drugs. In vitro screening experiments (i.e. bioassays) are frequently used for this purpose; however, experimental approaches are insufficient to explore novel drug-target interactions, mainly because of feasibility problems, as they are labour intensive, costly and time consuming. A computational field known as 'virtual screening' (VS) has emerged in the past decades to aid experimental drug discovery studies by statistically estimating unknown bio-interactions between compounds and biological targets. These methods use the physico-chemical and structural properties of compounds and/or target proteins along with the experimentally verified bio-interaction information to generate predictive models. Lately, sophisticated machine learning techniques are applied in VS to elevate the predictive performance. The objective of this study is to examine and discuss the recent applications of machine learning techniques in VS, including deep learning, which became highly popular after giving rise to epochal developments in the fields of computer vision and natural language processing. The past 3 years have witnessed an unprecedented amount of research studies considering the application of deep learning in biomedicine, including computational drug discovery. In this review, we first describe the main instruments of VS methods, including compound and protein features (i.e. representations and descriptors), frequently used libraries and toolkits for VS, bioactivity databases and gold-standard data sets for system training and benchmarking. We subsequently review recent VS studies with a strong emphasis on deep learning applications. Finally, we discuss the present state of the field, including the current challenges and suggest future directions. We believe that this survey will provide insight to the researchers working in the field of computational drug discovery in terms of comprehending and developing novel bio-prediction methods.

Characterization of gonadotropin releasing hormone receptor gene in Sokoto and Kalahari Red goats

The objective of this study was to characterize GnRHR gene in Sokoto (n = 70) and Kalahari Red (n = 70) goats. Three SNPs, (g.-29T > G, g.48 G > A and g.209 T > G), were detected in Sokoto Red (SR) and one (g.48 G > A) in Kalahari Red (KR) goats. All the mutations occurred within the 5'UTR and Exon one of the gene and the g.209 T > G was non-synonymous and, therefore, resulted in an amino acid change from methionine to arginine at Position 70 of the GnRHR polypeptide. The homozygous mutant genotypes at the three SNP loci were not detected in both breeds but minor allele frequencies were ≥ 0.1 for the three SNP loci in SR goats. Frequency of the T allele, however, was 0.93 at the only SNP locus detected in KR goats. There was a strong linkage disequilibrium (LD; r²>0.98) among the detected mutations in SR goats resulting in two haplotypes (T-G-T and G-A-G) with a frequency of 86% and 13%, respectively. There was no significant association between genotypes at the polymorphic loci and litter size (P > 0.05) in the two breeds. The non-synonymous mutation (g.209T>G) appears to have changed the nucleotide binding region and area spanning exposed/buried regions on the predicted secondary structure of the two variants of the receptor. This change led to variation in the tertiary structure between the two variants of the receptor and can influence the function of the transmembrane receptor. Comparison of the GnRH receptor domains for goats, sheep, cattle and swine confirmed that the seven transmembrane domains of the receptor are conserved in all the farm animals considered.

A model to study the inhibition of nsP2B-nsP3 protease of dengue virus with imidazole, oxazole, triazole thiadiazole, and thiazolidine based scaffolds

A theoretical model was developed to allosterically inhibit the biological activity of dengue virus (DENV) by targeting the non-structural protein ns2B-nsP3 protease based on the in silico studies. The imidazole, oxazole, triazole, thiadiazole, and thiazolidine based scaffolds were imported from the ZINC database, reported by various research group with different biological activity. They were found biologically active as they contain heterocyclic fragments. Generic evolutionary based molecular docking was performed to screen the highly potent molecule. The docking results show that the molecule having ZINC ID-633972 is best inhibitor. Further, the bioavailability and other physiochemical parameters were also calculated for the top four molecule. The highly potent molecule was further refined by the density functional theory and molecular dynamic (MD) simulation. The MD analysis coroborate the successful docking of the molecule in the binding cavity of nsP2B-nsP3 protease of DENV. The Molecular Mechanics Poisson-Boltzmann Surface Area approach was also applied and result coroborate the docking and MD result.

A Probabilistic Programming Approach to Protein Structure Superposition

Optimal superposition of protein structures or other biological molecules is crucial for understanding their structure, function, dynamics and evolution. Here, we investigate the use of probabilistic programming to superimpose protein structures guided by a Bayesian model. Our model THESEUS-PP is based on the THESEUS model, a probabilistic model of protein superposition based on rotation, translation and perturbation of an underlying, latent mean structure. The model was implemented in the probabilistic programming language Pyro. Unlike conventional methods that minimize the sum of the squared distances, THESEUS takes into account correlated atom positions and heteroscedasticity (ie. atom positions can feature different variances). THESEUS performs maximum likelihood estimation using iterative expectation-maximization. In contrast, THESEUS-PP allows automated maximum a-posteriori (MAP) estimation using suitable priors over rotation, translation, variances and latent mean structure. The results indicate that probabilistic programming is a powerful new paradigm for the formulation of Bayesian probabilistic models concerning biomolecular structure. Specifically, we envision the use of the THESEUS-PP model as a suitable error model or likelihood in Bayesian protein structure prediction using deep probabilistic programming.