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Mycobacterium neoaurum DSM 1381 originated from Mycobacterium neoaurum ATCC 25790 by mutagenesis screening is a strain of degrading phytosterols and accumulating important C22 steroid intermediates, including 22-hydroxy-23, 24-bisnorchola-4-en-3-one (4-HP) and 22-hydroxy-23, 24-bisnorchola-1,4-dien-3-one (HPD). However, the metabolic mechanism of these C22 products in M. neoaurum DSM 1381 remains unknown. Therefore, the whole-genome sequencing and comparative genomics analysis of M. neoaurum DSM 1381 and its parent strain M. neoaurum ATCC 25790 were performed to figure out the mechanism. As a result, 28 nonsynonymous single nucleotide variants (SNVs), 17 coding region Indels, and eight non-coding region Indels were found between the genomes of the two strains. When the wild-type 3-ketosteroid-9α-hydroxylase subunit A1 (KshA1) and β-hydroxyacyl-CoA dehydrogenase (Hsd4A) were overexpressed in M. neoaurum DSM 1381, the steroids were transformed into the 4-androstene-3, 17- dione (AD) and 1,4-androstadiene-3,17-dione (ADD) instead of C22 intermediates. This result indicated that 173N of KshA1 and 171K of Hsd4A are indispensable to maintaining their activity, respectively. Amino acid sequence alignment analysis show that both N173D in KshA1 and K171E in Hsd4A are conservative sites. The 3D models of these two enzymes were predicted by SWISS-MODEL and AlphaFold2 to understand the inactivation of the two key enzymes. These results indicate that K171E in Hsd4A may destroy the inaction between the NAD+ with the NH3+ and N173D in KshA1 and may disrupt the binding of the catalytic domain to the substrate. A C22 steroid intermediates–accumulating mechanism in M. neoaurum DSM 1381 is proposed, in which the K171E in Hsd4A leads to the enzyme’s inactivation, which intercepts the C19 sub-pathways and accelerates the C22 sub-pathways, and the N173D in KshA1 leads to the enzyme’s inactivation, which blocks the degradation of C22 intermediates. In conclusion, this study explained the reasons for the accumulation of C22 intermediates in M. neoaurum DSM 1381 by exploring the inactivation mechanism of the two key enzymes.

Machine learning (ML), an emerging field in drug design, has the potential to predict in silico toxicity, shape-based analysis of inhibitors, scoring function (SF) etc. In the present study, a homology model, docking protocol, and a dedicated SF have been developed to identify the inhibitors of horse butyrylcholinesterase (BChE) enzyme. Horse BChE enzyme has homology with human BChE and is a substitute for the screening of in vitro inhibitors. The developed homology model was validated and the active site residues were identified from Cavityplus to generate grid box for docking. The validation of docking involved comparison of interactions of ligands co-crystallised with human BChE and the docked poses of the corresponding ligands with horse BChE. A high degree of similarity in the interaction profiles of generated poses validated the docking protocol. Scoring of ligands was further validated by docking with known BChE inhibitors. The binding energies obtained from SF was correlated with IC50 values of inhibitors through classification and regression-based methods, which indicated poor predictivity of native SF. Therefore, protein-ligand binding energy, interaction profile, and ligand descriptors were used to develop and validate the classification and regression-based models. The validated extra tree binary classifier, random forest and extra tree regression-based models were compiled as a protein-ligand SF and were made available to the users through web application and python library. ML models exhibited improved area under the curve for ROC and good correlation between the predicted and observed IC50 values, than the Autodock SF. Communicated by Ramaswamy H. Sarma

Salinomycin (SAL) and lasalocid (LAS) are widely used as ionophore antibiotics for coccidiosis control. However, their common use as feed additives has led to the occurrence of feed cross-contamination, which has toxic effects on non-target animals. There have been few reports on multiple-residue detection for SAL and LAS in recent years. In this study, two single-chain antibody fragments (scFvs) capable of specifically recognizing SAL and LAS were constructed. Using LAS-scFv and SAL-scFv as parent antibodies, a complete bispecific single-chain diabody (scDb) against both LAS and SAL was built using splicing by overlap extension polymerase chain reaction (SOE-PCR). In addition, the key amino acid sites and interaction energy of antibody variable regions for small-molecule recognition were preliminarily studied by homology modeling and molecular docking. Finally, IC50 values of 12.9 and 8.6 ng/mL, with a linear range of 6.9–24.0 and 4.7–16.0 ng/mL, were obtained for LAS-scFv and SAL-scFv, respectively. An indirect competitive enzyme-linked immunosorbent assay (icELISA) method was established using scDb to obtain an IC50 of 3.5 ng/mL for LAS and 4.1 ng/mL for SAL, which showed better sensitivity and specificity than those of the parent scFv antibodies. The recoveries of LAS and SAL in chicken liver were 89.2–92.7%(CV

Escherichia coli (E. coli) and Enterococcus faecalis (E. faecalis) are pathogenic strains that often coexist as an intestinal flora in humans and are prone to cause biofilm-associated infections such as gastrointestinal tract and urinary tract infections. Earlier studies have demonstrated that E. faecalis biofilm can metabolize ferrous ions in iron-rich environments and promote biofilm growth under in-vivo conditions. However, the influence of iron transporters on dual-species biofilm growth and the nature of molecular-level interactions between iron transporter proteins and Fe2+ remains unknown. Therefore, we performed co-culture studies and found that Fe2+ at concentrations of 50 to 150 µM promotes the colonization of E. coli, and Fe2+ concentrations of 50 to 200 µM promote the growth of E. faecalis and dual-species colonies. Similarly, Fe2+ at concentrations of 50 to 250 µM promotes E. coli and E. faecalis biofilm formation 50 to 300 µM promotes biofilm formation of dual-species biofilms. Atomic absorption spectroscopy results reveal that Fe2+ ion augmentation in bacterial cells was increased to 4 folds in the single-species model and 11 folds in the dual-species model under iron-supplemented conditions. Furthermore, Fe2+ augmentation increased the antibiotic resistance of E. faecalis in both single and dual-species bacterial cultures. In addition, we have performed in-silico studies to determine a three-dimensional (3D) structure of ferrous iron-transporter proteins FeoB of E. faecalis and its affinity to extracellular Fe2+. Our model suggests that the FeoB facilitates the Fe2+ uptake in E. faecalis cells in the absence of iron chelator, 2,2-bipyridyl.

Microalgae as an alternative renewable resource for biofuel production have captured much significance. Nonetheless, its economic viability is a field of major concern for researchers. Unraveling the lipid catabolic pathway and gaining insights into the sequence-structural features of its primary functioning enzyme, Triacylglycerol lipase, will impart valuable information to target microalgae for augmented lipid content. In the present study, a genome-wide comparative study on putative Triacylglycerol lipase (TAGL) enzyme from algal species belonging to varied phylogenetic lineages was performed. The comprehensive sequence analysis revealed that TAGL comprises of three distinct conserved domains, such as, Patatin, Class III Lipase, and Abhydro_lipase, and also confirmed the ubiquitous presence of GXSXG motif in the sequences analyzed. In the absence of a crystal structure of algal TAGL till date, we developed the first 3D model of patatin domain of TAGL from an oleaginous microalga, Phaedactylum tricornutum, employing homology modeling, docking and molecular dynamic simulations methods. The domain-substrate complex having the low-ranking docking score revealed the binding of palmitic acid to the TAGL patatin domain surface with strong hydrogen bond interactions. The simulation results implied that the substrate-complexed patatin domain and the free enzyme adopted a more stable conformation after 40 ns. This is the first ever attempt to provide in-silico insights into the structural and dynamical insights on catalytic mechanism of the TAGL patatin domain. Subsequently, these findings aided our understanding on their structural stability, folding mechanism and protein-substrate interactions, which could be further utilized to design site-specific mutagenic experiments for engineering microalgal strains.Communicated by Ramaswamy H. Sarma.

The pharmacologically characterized receptor subtype of the serotonin family, the 5HT1A receptor is implicated in the pathophysiology and treatment of depression and anxiety-related disorders. Being the most extensively targeted receptor for developing novel antidepressants and anxiolytics, a near-ideal theoretical model can aid in high-throughput screening of promising drug candidates. However, the design of potential drug candidates suffers owing to a lack of complete structural information. In this work, homology models of 5-HT1A receptor are generated using two distinct alignments (CW and PSTA) and model building methods (KB and EB). The developed models are validated for virtual screening using a ligand dataset of agonists and antagonists. The best-suited model was efficient in discriminating agonist/antagonist binding. Correlation plots between pKi and docking (R2agonist≥ 0.6, R2antagonist≥ 0.7) and MM-GBSA dG bind values (R2agonist≥ 0.5, R2antagonist≥ 0.7) revealed optimum corroboration between in vitro and in silico outcomes, which further suggested the usefulness of the developed model for the design of high-affinity probes for the neurological disorders.Communicated by Ramaswamy H. Sarma.

Structure-based drug design (SBDD) is an important in silico technique, used for the identification of enzyme inhibitors. Acetylcholinesterase (AChE), obtained from Electrophorus electricus (ee), is widely used for the screening of AChE inhibitors. It shares structural homology with the AChE of human and other organisms. Till date, the three-dimensional crystal structure of enzyme from ee is not available that makes it challenging to use the SBDD approach for the identification of inhibitors. A homology model was developed for eeAChE in the present study, followed by its structural refinement through energy minimisation. The docking protocol was developed using a grid dimension of 84 × 66 × 72 and grid point spacing of 0.375 A for eeAChE. The protocol was validated by redocking a set of co-crystallised inhibitors obtained from mouse AChE, and their interaction profiles were compared. The results indicated a poor performance of the Autodock scoring function. Hence, a batch of machine learning-based scoring functions were developed. The validation results displayed an accuracy of 81.68 ± 1.73% and 82.92 ± 3.05% for binary and multiclass classification scoring function, respectively. The regression-based scoring function produced $$r^{2} ,\;Q^{2}_{f1}$$ and $$Q^{2}_{f2}$$ values of 0.94, 0.635 and 0.634, respectively.

Antibody-antigen co-crystal structures are a valuable resource for the fundamental understanding of antibody-mediated immunity. Determination of structures with antibodies in complex with their antigens, however, is a laborious task without guarantee of success. Therefore, homology modeling of antibodies and docking to their respective-antigens has become a very important technique to drive antibody and vaccine design. The quality of the antibody modeling process is critical for the success of these endeavors. Here, we compare different computational protocols for predicting antibody structure from sequence in the biomolecular modeling software Rosetta - all of which use multiple existing antibody structures to guide modeling. Specifically, we compare protocols developed solely to predict antibody structure (RosettaAntibody, AbPredict) with a universal homology modeling protocol (RosettaCM). Following recent advances in homology modeling with multiple templates simultaneously, we propose that the use of multiple templates over the same antibody regions may improve modeling performance. To evaluate whether multi-template comparative modeling with RosettaCM can improve the modeling accuracy of antibodies over existing methods, this study compares the performance of the three modeling algorithms when modeling human antibodies taken from antibody-antigen co-crystal structures. In these benchmarking experiments, RosettaCM outperformed other methods when modeling antibodies with long HCDR3s and few available templates.

GPR17, a G protein-coupled receptor, is a pivotal regulator of myelination. Its endogenous ligands trigger receptor desensitization and downregulation allowing oligodendrocyte terminal maturation. In addition to its endogenous agonists, GPR17 could be promiscuously activated by pro-inflammatory oxysterols and chemokines released at demyelinating lesions. Herein, the chemokine receptors CXCR2 and CXCR4 were selected to perform both in silico modelling and in vitro experiments to establish their structural and functional interactions with GPR17. The relative propensity of GPR17 and CXCR2 or CXCR4 to form homo- and hetero-dimers was assessed by homology modelling and molecular dynamics (MD) simulations, and co-immunoprecipitation and immunoenzymatic assay. The interaction between chemokine receptors and GPR17 was investigated by determining receptor-mediated modulation of intracellular cyclic adenosine monophosphate (cAMP). Our data show the GPR17 association with CXCR2 or CXCR4 and the negative regulation of these interactions by CXCR agonists or antagonists. Moreover, GPR17 and CXCR2 heterodimers can functionally influence each other. In contrast, CXCR4 can influence GPR17 functionality, but not vice versa. According to MD simulations, all the dimers reached conformational stability and negative formation energy, confirming the experimental observations. The cross-talk between these receptors could play a role in the development of the neuroinflammatory milieu associated with demyelinating events.

The World Health Organization declared monkeypox a global public health emergency on 23 July 2022. This disease was caused by the monkeypox virus (MPXV), which was first identified in 1958 in Denmark. The MPXV is a member of the Poxviridae family, the Chordopoxvirinae subfamily, and the genus Orthopoxvirus, which share high similarities with the vaccinia virus (the virus used to produce the smallpox vaccine). For the initial stage of infection, the MPXV needs to attach to the human cell surface glycosaminoglycan (GAG) adhesion molecules using its E8 protein. However, up until now, neither a structure for the MPXV E8 protein nor a specific cure for the MPXV exists. This study aimed to search for small molecules that inhibit the MPXV E8 protein, using computational approaches. In this study, a high-quality three-dimensional structure of the MPXV E8 protein was retrieved by homology modeling using the AlphaFold deep learning server. Subsequent molecular docking and molecular dynamics simulations (MDs) for a cumulative duration of 2.1 microseconds revealed that ZINC003977803 (Diosmin) and ZINC008215434 (Flavin adenine dinucleotide-FAD) could be potential inhibitors against the E8 protein with the MM/GBSA binding free energies of −38.19 ± 9.69 and −35.59 ± 7.65 kcal·mol−1, respectively.

ApoB-100 is a member of a large lipid transfer protein superfamily and is one of the main apolipoproteins found on low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) particles. Despite its clinical significance for the development of cardiovascular disease, there is limited information on apoB-100 structure. We have developed a novel method based on the “divide and conquer” algorithm, using PSIPRED software, by dividing apoB-100 into five subunits and 11 domains. Models of each domain were prepared using I-TASSER, DEMO, RoseTTAFold, Phyre2, and MODELLER. Subsequently, we used disuccinimidyl sulfoxide (DSSO), a new mass spectrometry cleavable cross-linker, and the known position of disulfide bonds to experimentally validate each model. We obtained 65 unique DSSO cross-links, of which 87.5% were within a 26 Å threshold in the final model. We also evaluated the positions of cysteine residues involved in the eight known disulfide bonds in apoB-100, and each pair was measured within the expected 5.6 Å constraint. Finally, multiple domains were combined by applying constraints based on detected long-range DSSO cross-links to generate five subunits, which were subsequently merged to achieve an uninterrupted architecture for apoB-100 around a lipoprotein particle. Moreover, the dynamics of apoB-100 during particle size transitions was examined by comparing VLDL and LDL computational models and using experimental cross-linking data. In addition, the proposed model of receptor ligand binding of apoB-100 provides new insights into some of its functions.

Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) is an innate immune pattern recognition receptor responsible for the recognition of bacterial peptidoglycan fragments. Given its central role in the formation of innate and adaptive immune responses, NOD2 represents a valuable target for modulation with agonists and antagonists. A major challenge in the discovery of novel small-molecule NOD2 modulators is the lack of a co-crystallized complex with a ligand, which has limited previous progress to ligand-based design approaches and high-throughput screening campaigns. To that end, a hybrid docking and pharmacophore modeling approach was used to identify key interactions between NOD2 ligands and residues in the putative ligand-binding site. Following docking of previously reported NOD2 ligands to a homology model of human NOD2, a structure-based pharmacophore model was created and used to virtually screen a library of commercially available compounds. Two compounds, 1 and 3, identified as hits by the pharmacophore model, exhibited NOD2 antagonist activity and are the first small-molecule NOD2 modulators identified by virtual screening to date. The newly identified NOD2 antagonist scaffolds represent valuable starting points for further optimization. Nasl. z nasl. zaslona. Opis vira z dne 8. 8. 2022. Št. članka: 1054. Abstract. Bibliografija: str. 15-17. ARRS, program ARRS, program ARRS, projekt

The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.

Anterior Gradient 2 (AGR2) has recently been reported as a tumor biomarker in various cancers, i.e., breast, prostate and lung cancer. Predominantly, AGR2 exists as a homodimer via a dimerization domain (E60-K64); after it is self-dimerized, it helps FGF2 and VEGF to homo-dimerize and promotes the angiogenesis and the invasion of vascular endothelial cells and fibroblasts. Up till now, no small molecule has been discovered to inhibit the AGR2–AGR2 homodimer. Therefore, the present study was performed to prepare a validated 3D structure of AGR2 by homology modeling and discover a small molecule by screening the FDA-approved drugs library on AGR2 homodimer as a target protein. Thirteen different homology models of AGR2 were generated based on different templates which were narrowed down to 5 quality models sorted by their overall Z-scores. The top homology model based on PDB ID = 3PH9 was selected having the best Z-score and was further assessed by Verify-3D, ERRAT and RAMPAGE analysis. Structure-based virtual screening narrowed down the large library of FDA-approved drugs to ten potential AGR2–AGR2 homodimer inhibitors having FRED score lower than − 7.8 kcal/mol in which the top 5 drugs’ binding stability was counter-validated by molecular dynamic simulation. To sum up, the present study prepared a validated 3D structure of AGR2 and, for the first time reported the discovery of 5 FDA-approved drugs to inhibit AGR2–AGR2 homodimer by using structure-based virtual screening. Moreover, the binding of the top 5 hits with AGR2 was also validated by molecular dynamic simulation. A validated 3D structure of Anterior Gradient 2 (AGR2) was prepared by homology modeling, which was used in virtual screening of FDA-approved drugs library for the discovery of prospective inhibitors of AGR2–AGR2 homodimer.

Sickle cell disease (SCD) is a disease resulting from mutation in the globin portion of hemoglobin caused by the replacement of adenine for thymine in the codon of the β globin gene. In Brazil, SCD affects about 0.3% of the black and Caucasian population. Until now, there is no specific treatment and the available drugs have several serious adverse effects which makes the search for new drugs an emergently need. The use of computational techniques can accelerate the drug development process by prioritization of molecules with affinity against essential targets. Adenosine A2b receptor (rA2b) has been studied in SCD due to its relationship with red blood cells concentration of 2,3-diphosphoglycerate which reduces the hemoglobin affinity for oxygen (O2), facilitating its availability for the tissues. Then, development of rA2b antagonists could be helpful for the treatment of SCD. However, there is still no 3D structure of rA2b and to overcome this limitation, homology modeling should be applied. In this scenario, this study aims to build a suitable 3D model of rA2b by SWISS MODEL and to evaluate the structural aspects of rA2b with known antagonists that may be useful for the identification of new potential antagonists by molecular dynamics on a lipid bilayer environment using GROMACS 5.1.4. The complexes with antagonists ZINC223070016 and ZINC17974526 interacted with key residues by hydrophobic contacts and hydrogen bonds which stabilized them at the rA2b binding site. This intermolecular profile can contribute to the development of more potent rA2b antagonists. Communicated by Ramaswamy H. Sarma.

NaCT (SLC13A5) is a Na+-coupled transporter for citrate, which is expressed in the liver, brain, testes, and bone. It is the mammalian homolog of Drosophila INDY, a cation-independent transporter for citrate, whose partial loss extends lifespan in the organism. In humans, loss-of-function mutations in NaCT cause a disease with severe neurological dysfunction, characterized by neonatal epilepsy and delayed brain development. In contrast with humans, deletion of NaCT in mice results in a beneficial metabolic phenotype with protection against diet-induced obesity and metabolic syndrome; the brain dysfunction is not readily noticeable. The disease-causing mutations are located in different regions of human NaCT protein, suggesting that different mutations might have different mechanisms for the loss of function. The beneficial effects of NaCT loss in the liver versus the detrimental effects of NaCT loss in the brain provide an opportunity to design high-affinity inhibitors for the transporter that do not cross the blood-brain barrier so that only the beneficial effects could be harnessed. To realize these goals, we need a detailed knowledge of the 3D structure of human NaCT. The recent report by Sauer et al. in Nature describing the cryo-EM structure of human NaCT represents such a milestone, paving the way for a better understanding of the structure-function relationship for this interesting and clinically important transporter.

Chlamydia felis is the primary cause of chronic conjunctivitis without respiratory infections in cats, making conjunctiva as its primary target. It is a Gram-negative obligate intracellular bacterium that cannot survive outside the host cell. C. felis can be found worldwide and its zoonotic potential is a known phenomenon. The scope of zoonoses, its scale, and their impact experiencing today has no historical precedence. Among the identified 1415 human pathogens 868 have a zoonotic origin making it to 61%. Although with appropriate drug administration there are instances of re-occurrence of chlamydial infections, the emergence of heterotypic antimicrobial resistance to antibiotics targeting rRNA due to mutations has further complicated the diagnosis and treatment of chlamydial infections. Ribonucleotide-diphosphate reductase subunit beta (RNR) is one of the crucial target proteins of the bacterial pathogens essential in the synthesis of deoxyribonucleotides. Our current study primarily focuses on modeling the target structure through homology modeling. Further, the validated model is complexed with the specific inhibitor Cladribine through sequence-based ligand search. Docking of the identified ligand was performed to identify the different modes of interactions with amino acids present in the prioritized binding pockets. Validation of the binding modes is carried out through molecular dynamics (MD) simulations for the best binding pose with a high binding score. MD simulation study demonstrated the stability of the docked complex considered in this study. The findings from this study may be helpful in drug repurposing and novel drug research in the scenario of resistance to currently practiced antibiotics.Communicated by Ramaswamy H. Sarma.

A basic sPLA2 (D49) from the venom of snake Agkistrodon piscivorus leucostoma (AplTX-II) was isolated, purified and characterized. We determined the enzymatic and pharmacological profiles of this toxin. AplTX-II was isolated with a high level of purity through reverse phase chromatography and molecular exclusion. The enzyme showed pI 9.48 and molecular weight of 14,003 Da. The enzymatic activity of the AplTX-II depended on Ca2+ pH and temperature. The comparison of the primary structure with other sPLA2s revealed that AplTX-II presented all the structural reasons expected for a basic sPLA2s. Additionally, we have resolved its structure with the docked synthetic substrate NOBA (4-nitro-3-octanoyloxy benzoic acid) by homology modeling, and performed MD simulations with explicit solvent. Structural similarities were found between the enzyme's modeled structure and other snake sPLA2 X-Ray structures, available in the PDB database. NOBA and active-site water molecules spontaneously adopted stable positions and established interactions in full agreement with the reaction mechanism, proposed for the physiological substrate, suggesting that NOBA hydrolysis is an excellent model to study phospholipid hydrolysis.

G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.

The latest monkeypox virus outbreak in 2022 showcased the potential threat of this viral zoonosis to public health. The lack of specific treatments against this infection and the success of viral protease inhibitors-based treatments against HIV, Hepatitis C, and SARS-CoV-2, brought the monkeypox virus I7L protease under the spotlight as a potential target for the development of specific and compelling drugs against this emerging disease. In the present work, the structure of the monkeypox virus I7L protease was modeled and thoroughly characterized through a dedicated computational study. Furthermore, structural information gathered in the first part of the study was exploited to virtually screen the DrugBank database, consisting of drugs approved by the Food and Drug Administration (FDA) and clinical-stage drug candidates, in search for readily repurposable compounds with similar binding features as TTP-6171, the only non-covalent I7L protease inhibitor reported in the literature. The virtual screening resulted in the identification of 14 potential inhibitors of the monkeypox I7L protease. Finally, based on data collected within the present work, some considerations on developing allosteric modulators of the I7L protease are reported.

We report structural characterization of proteases mined in silico from solid tannery waste (STW) metagenome. The physico-chemical analysis revealed the molecular weight of selected query proteases in the range of 34–43 kDa except 52.46 kDa for Cp-6. Secondary structure analysis suggested the dominance of α-helices (26–51 %) followed by β-sheets (13–34 %). Conserved regions in the selected proteases were identified using multiple sequence alignment. Diversity analysis of the proteases was performed by aligning with their best hits and already characterized proteases of similar families. The 3D structures of 19 selected amino acid sequences were deduced using homology modeling and evaluated following Ramachandran plots (R-plots), stability of the 3D conformation, and overall quality factor (G factor). The R-plots of all structures had 96.4–98.9 % residues in the favoured region, whereas 0-0.8 % lied in the outlier region. Fifteen modeled protein structures passed the quality assessment criteria and were subsequently used for molecular docking. All models showed two domains except Cp-6, which had an extra domain. Ligand binding sites and active sites were identified using sequence and structural homologs of the respective protease molecules. Serine, lysine, and serine of different conserved motifs were specified as the active site residues in carboxypeptidases, whereas serine, aspartate, and histidine were specific to aminopeptidases Ap-1, Ap-2, and Ap-4. Further, Ap-8 and Ap-9 required Mn2+ for enzyme activity along with histidine and glutamate in their active sites. These 3D structures were used for molecular docking with their specific peptide ligands to obtain stable docked conformations. Successfully docked complexes indicated the catalytic activity of these enzymes in hydrolyzing the peptide ligand. The structural and functional insights gained from our study may help in the identification of novel industrially important proteases after validation through experimental studies.

Plasmodium falciparum harbors a unique type II topoisomerase, Topoisomerase VIB (PfTopoVIB), expressed specifically at the actively replicating stage of the parasite. An earlier study showed that Radicicol inhibits the decatenation activity of PfTopoVIB and thereby arrests the parasites at the schizont stage. Radicicol targets a unique ATP-binding fold called the Bergerat fold, which is also present in the N-terminal domain of the heat shock protein 90 (PfHsp90). Hence, Radicicol may manifest off-target activity within the parasite. We speculate that the affinity of Radicicol towards PfTopoVIB could be enhanced by modifying its structure so that it shows preferential binding towards PfTopoVIB but not to PfHsp90. Here, we have performed the docking and affinity studies of 97 derivatives (structural analogs) of Radicicol and have identified 3 analogs that show selective binding only to PfTopoVIB and no binding with PfHsp90 at all. Molecular dynamics simulation study was performed for 50 ns in triplicate with those 3 analogs and we find that one of them shows a stable association with Radicicol. This study identifies the structural molecule which could be instrumental in blocking the function of PfTopoVIB and hence can serve as an important inhibitor for malaria pathogenesis. Communicated by Ramaswamy H. Sarma

Antiviral drug discovery continues to be an essential complement to vaccine development for overcoming the global pandemic caused by SARS-CoV-2. The genomic RNA of SARS-CoV-2 contains structural elements important for viral replication and/or pathogenesis making them potential therapeutic targets. Here we report on the stem-loop II motif, a highly conserved noncoding RNA element. Based on our homology model we determined that the G to U transversion in the SARS-CoV-2 stem-loop II motif (S2MG35U) forms a C–U base-pair isosteric to the C-G base-pair in the early 2000’s SARS-CoV (S2M). In addition, chemo-enzymatic probing and molecular dynamics simulations indicate the S2MG35U conformational profile is altered compared to S2M in the apical loop region. We explored S2MG35U as a potential drug target by docking a library of FDA approved drugs. Enzymatic probing of the best docking ligands (aminoglycosides and polymyxins) indicated that polymyxin binding alters the conformational profile and/or secondary structure of the RNA. The SARS-CoV-2 stem-loop II motif conformational differences due to nucleotide transversion and ligand binding are highly significant and provide insight for future drug discovery efforts since the conformation of noncoding RNA elements affects their function., Highlights • Central core of stem-loop-II motif in SARS-CoV-2 genomic RNA >98% conserved. • Stem-loop II motif RNA conformation altered by mutation present in all SARS-CoV-2. • Ligand-induced structural changes consistent with stem-loop II motif druggability.

Rhipicephalus microplus is an important ectoparasite of cattle, causing considerable economical losses. Resistance to chemical acaricides has stimulated the search for new antiparasitic drugs, incl...

In hemolytic disorders, erythrocyte lysis results in massive release of hemoglobin and, subsequently, toxic heme. Hemopexin is the major protective factor against heme toxicity in human blood and currently considered for therapeutic use. It has been widely accepted that hemopexin binds heme with extraordinarily high affinity of K D value of 0.32 ± 0.04 nM and the ratio for the interaction was determined to be 1:1 at low heme concentrations and at least 2:1 (heme:hemopexin) at high concentrations. We were able to identify two yet unknown potential heme-binding sites on hemopexin. Furthermore, molecular modelling with a newly created homology model of human hemopexin suggested a possible recruiting mechanism by which heme could consecutively bind several histidine residues on its way into the binding pocket. Our findings have direct implications for the potential administration of hemopexin in hemolytic disorders.

Human multidrug resistance protein 1 (hMRP1) is an important member of the ATP-binding cassette (ABC) transporter superfamily. It can extrude a variety of anticancer drugs and physiological organic anions across the plasma membrane, which is activated by substrate binding, and is accompanied by large-scale cooperative movements between different domains. Currently, it remains unclear completely about how the specific interactions between hMRP1 and its substrate are and which critical residues are responsible for allosteric signal transduction. To the end, we first construct an inward-facing state of hMRP1 using homology modeling method, and then dock substrate proinflammatory agent leukotriene C4 (LTC4) to hMRP1 pocket. The result manifests LTC4 interacts with two parts of hMRP1 pocket, namely the positively charged pocket (P pocket) and hydrophobic pocket (H pocket), similar to its binding mode with bMRP1 (bovine MRP1). Additionally, we use the Gaussian network model (GNM)-based thermodynamic method proposed by us to identify the key residues whose perturbations markedly alter their binding free energy. Here the conventional GNM is improved with covalent/non-covalent interactions and secondary structure information considered (denoted as sscGNM). In the result, sscGNM improves the flexibility prediction, especially for the nucleotide binding domains with rich kinds of secondary structures. The 46 key residue clusters located in different subdomains are identified which are highly consistent with experimental observations. Furtherly, we explore the long-range cooperation within the transporter. This study is helpful for strengthening the understanding of the work mechanism in ABC exporters and can provide important information to scientists in drug design studies.

A Martelella endophytica (M. endophytica) strain YC6887 was previously isolated from the roots of a halophyte, Rosa rugosa, which was sequenced and characterized. The genomic and proteomic analysis showed a carbohydrate-degrading enzyme, endoglucanase Cel5A which was further characterized. The protein analysis revealed that this endoglucanase belongs to glycosidic hydrolase family 5 (GH5) with catalytic domain. This gene encodes 349-residue polypeptide and shows closest similarity with cellulases of other Martelella species. The protein was purified to homogeneity and shown that it was a 39 kDa protein. The purified recombinant Cel5A endoglucanase exhibited maximum activity at 50 °C and pH 4.5. The enzyme was salt tolerant and retained more than 50% residual activity up to 15% NaCl. The homology model structure of Cel5A displayed that it is stable and compact protein structure consisting of eleven α-helical structures and eight β-sheets. According to the predicted ligand binding site after superimposition with Pseudomonas stutzeri endoglucanase Cel5A (PDB ID: 4LX4), it consisted of five amino acid Asn157, Tyr116, Glu158, Glu270 and Trp303 that may be the expected active site of Cel5A from YC6887. This presented that our strain M. endophytica YC6887 that produces cellulase partially degrade the insoluble polysaccharides into reducing sugars.

Aims: In hemolysis, which is accompanied by increased levels of labile redox-active heme and is often associated with hemostatic abnormalities, a decreased activity of activated protein C (APC) is routinely detected. APC is a versatile enzyme that exerts its anticoagulant function through inactivation of clotting factors Va and VIIIa. APC has not been demonstrated to be affected by heme as described for other clotting factors and, thus, is a subject of investigation. Results: We report the interaction of heme with APC and its impact on the protein function by employing spectroscopic and physiologically relevant methods. Binding of heme to APC results in inhibition of its amidolytic and anticoagulant activity, increase of the peroxidase-like activity of heme, and protection of human umbilical vein endothelial cells from heme-induced hyperpermeability. To define the sites that are responsible for heme binding, we mapped the surface of APC for potential heme-binding motifs. T285GWGYHSSR293 and W387IHGHIRDK395, both located on the basic exosite, turned out as potential heme-binding sites. Molecular docking employing a homology model of full-length APC indicated Tyr289 and His391 as the Fe(III)-coordinating amino acids. Innovation: The results strongly suggest that hemolysis-derived heme may directly influence the protein C pathway through binding to APC, conceivably explaining the decreased activity of APC under hemolytic conditions. Further, these results extend our understanding of heme as a multifaceted effector molecule within coagulation and may allow for an improved understanding of disease development in hemostasis under hemolytic conditions. Conclusion: Our study identifies APC as a heme-binding protein and provides insights into the functional consequences.

Structural discovery of guanine nucleotide exchange factor (GEF) protein complexes is likely to become increasingly relevant with the development of new therapeutics targeting small GTPases and development of new classes of small molecules that inhibit protein-protein interactions. Syx (also known as PLEKHG5 in humans) is a RhoA GEF implicated in the pathology of glioblastoma (GBM). Here we investigated protein expression and purification of ten different human Syx constructs and performed biophysical characterizations and computational studies that provide insights into why expression of this protein was previously intractable. We show that human Syx can be expressed and isolated and Syx is folded as observed by circular dichroism (CD) spectroscopy and actively binds to RhoA as determined by co-elution during size exclusion chromatography (SEC). This characterization may provide critical insights into the expression and purification of other recalcitrant members of the large class of oncogenic — Diffuse B-cell lymphoma (Dbl) homology GEF proteins. In addition, we performed detailed homology modeling and molecular dynamics simulations on the surface of a physiologically realistic membrane. These simulations reveal novel insights into GEF activity and allosteric modulation by the plekstrin homology (PH) domain. These newly revealed interactions between the GEF PH domain and the membrane embedded region of RhoA support previously unexplained experimental findings regarding the allosteric effects of the PH domain from numerous activity studies of Dbl homology GEF proteins. This work establishes new hypotheses for structural interactivity and allosteric signal modulation in Dbl homology RhoGEFs.

EGFR receptors play an important role in the growth of cancer cells, and these receptors have undergone various types of mutations. At this time, the effect of the L718Q / T790M point mutation on the EGFR receptor is not known, therefore the aim of this study is to predict the EGFR structure with the L718Q / T790M point mutation using in silico homology modeling. The mutant protein was successfully modeled using SWISS-Model expasy webserver and showed good evaluation results after the protein was minimized as indicated by the results of the Ramachandran outlier score of 0%, clashscore 0.98, and MolProbity 1.15. Identification of the active site of the mutant protein shows a conformational change of the active site that causes a steric collision between the inhibitor group and the amino acid side chain of the mutant protein. Keywords: EGFR, mutation, homology modeling, in silico.

Inhibitor K562 (IK) protein was first isolated from the culture medium of K562 cells, a leukemia cell line, and is an inhibitory regulator of interferon-γ-induced major histocompatibility complex class II expression. Recently, exogenous truncated IK (tIK) protein showed potential as a therapeutic agent for inflammation-related diseases. In this study, we designed a novel putative anti-inflammatory peptide derived from tIK protein based on homology modeling of the human interleukin-10 (hIL-10) structure, and investigated whether the peptide exerted inhibitory effects against proinflammatory cytokines such as IL-17 and tumor necrosis factor-α (TNF-α). The peptide contains key residues involved in binding hIL-10 to the IL-10 receptor, and exerted strong inhibitory effects on IL- 17 (43.8%) and TNF-α (50.7%). In addition, we used circular dichroism spectroscopy to confirm that the peptide is usually present in a random coil configuration in aqueous solution. In terms of toxicity, the peptide was found to be biologically safe. The mechanisms by which the short peptide derived from human tIK protein exerts inhibitory effects against IL-17 and TNF-α should be explored further. We also evaluated the feasibility of using this novel peptide in skincare products.

The World Health Organization has declared COVID-19 as a global health emergency. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and highlights an urgent need for therapeutics. Here, we have employed a series of computer-aided drug repurposing campaign to discover inhibitors of RNA dependent RNA polymerase (RdRp) and Nsp15/EndoU. Subsequently, MD simulation has been performed to observe dynamic behavior of identified leads at the active site of RdRp and Nsp15. We successfully identified novel lead molecule such as Alectinib for RdRp while Naldemedine and Ergotamine for NSP15. These lead molecules were accommodated in the active site of the enzyme and stabilized by the networks of the hydrogen bond, pi type and hydrophobic interaction with key residues of either target. Interestingly, identified compounds show molecular mimicry in terms of molecular interactions with key residues of RdRp and Nsp15 essential for catalysis and substrate interaction. Previously, Alectinib, Naldemedine and Ergotamine were used as drug in different diseases might be repurposed against selected protein targets of COVID19. Finally, we propose that the identified inhibitors represent a novel lead molecule to design a more effective inhibitor to stop the progress of pathogen. Communicated by Ramaswamy H. Sarma

The phylum cyanobacteria are one of the most ancient groups of organisms on the planet and are well recognized due to its wide distribution, ecological role, and biotechnological potential. Cyanobacterial lectins are being extensively explored due to their antiviral activity, mainly because of their capacity of inhibiting HIV strains from infecting human cells by gp120 and gp41 binding. Cianovirin-N from Nostoc ellipsosporum was the first lectin isolated with this property. Since then, various homologs have been discovered and characterized. In this article, we present results of a genomic screening to find cyanovirin-N homologs (CVNH) in all cyanobacteria genomes available in the GenBank, resulting in 155 CVNH proteins with 63 presenting significant identity differences of cyanovirin-N. Homology modeling and molecular dynamics were employed to characterize 18 unexplored models and their functional capacity of binding to Manα(1-2)Man. Results presented here support the hypothesis of multiple ligand recognition for the CVNH family and may help to understand the function of these lectins for the producer cyanobacteria. Additionally, the theoretical results observed here justify carrying out experimental investigations that can expand the therapeutic potential of cyanobacterial lectins.

Fusarium oxysporum causes significant economic losses in many crop plants by causing root rot, necrosis, and wilting symptoms. Homology and molecular dynamics studies are promising tools for the detection in F. oxysporum of the systemic resistance compound, salicylic acid, for control of the SKP1-CUL1-F-box protein complex. The structure of SKP1-CUL1-F-box subunit Skp1 from F. oxysporum is produced by Modeler 9v7 for the conduct of docking studies. The Skp1 structure is based on the yeast Cdc4/Skp1 (PDB ID: 3MKS A) crystal structure collected by the Protein data bank. Applying molecular dynamic model simulation methods to the final predicted structure and further evaluated by 3D and PROCHECK test programmers, the final model is verified to be accurate. Applying GOLD 3.0.1, SCF Complex Skp1 is used to prevent stress-tolerant operation. The SKP1-CUL1-F-box model is predicted to be stabilized and tested as a stable docking structure. The predicted model of the SCF structure has been stabilized and confirmed to be a reliable structure for docking studies. The results indicated that GLN8, LYS9, VAL10, TRP11, GLU48, ASN49 in SCF complex are important determinant residues in binding as they have strong hydrogen bonding with salicylic acid, which showed best docking results with SKP1-CUL1-F-box complex subunit Skp1 with docking score 25.25KJ/mol. Insilco studies have been used to determine the mode of action of salicylic acid for Fusarium control. Salicylic acid hinders the SKP1-CUL1-F-box complex, which is important in protein-like interactions through hydrogen bodings. Results from docking studies have shown that the best energy for SKP1-CUL1-F-box was salicylic acid.Communicated by Ramaswamy H. Sarma.

Olfactory receptor (OR) 1A2 is the member of largest superfamily of G protein-coupled receptors (GPCRs). OR1A2 is an ectopically expressed receptor with only 13 known ligands, implicated in reducing hepatocellular carcinoma progression, with enormous therapeutic potential. We have developed a two-stage screening approach to identify novel putative ligands of OR1A2. We first used a pharmacophore model based on atomic property field (APF) to virtually screen a library of 5942 human metabolites. We then carried out structure-based virtual screening (SBVS) for predicting the potential agonists, based on a 3D homology model of OR1A2. This model was developed using a biophysical approach for template selection, based on multiple parameters including hydrophobicity correspondence, applied to the complete set of available GPCR structures to pick the most appropriate template. Finally, the membrane-embedded 3D model was refined by molecular dynamics (MD) simulations in both the apo and holo forms. The refined model in the apo form was selected for SBVS. Four novel small molecules were identified as strong binders to this olfactory receptor on the basis of computed binding energies., Graphical abstract Image 1, Highlights • A two-stage screening has led to the prediction of structurally similar ligands for OR1A2. • A biophysical approach, including a novel parameter of hydrophobicity correspondence, is presented for template selection. • Available GPCR templates for OR1A2 have been comprehensively compared using our proposed biophysical approach. • 1U19 is suggested to be the best template for OR1A2 on the basis of biophysical properties. • Combining ligand-based and structure-based screening might facilitate decoding of ORs molecular receptive code.

Fungi produce several toxins active against plants, animal or humans. Among them, ribotoxins are enzymes that specifically attack ribosomes irreparably compromising protein synthesis, useful as insecticides or as anticancer agents. Here, a novel ribotoxin from the edible mushroom Pleurotus ostreatus has been purified and characterized. This ribotoxin, named Ostreatin, is a specific ribonuclease releasing α-fragment when incubated with yeast or rabbit ribosomes. Ostreatin shows IC50 of 234 pM in rabbit reticulocyte lysate, and metal dependent endonuclease activity. Following the completion of Ostreatin primary structure, we ascertained that this toxin is homologous to Ageritin, the first ribotoxin-like protein from the basidiomycete Agrocybe aegerita, with which it shares 38.8% amino acid sequence identity. Ostreatin consists of 131 amino acid residues with an experimental molecular mass of 14,263.51 Da ([M+H+]+). Homology modeling revealed that Ostreatin and Ageritin share a similar fold in which the common catalytic triad is conserved. Purified Ostreatin lacks N-terminal and C-terminal peptides, which instead are present in the Ostreatin coding sequence. Such peptides are probably involved in protein sorting and for this they could be removed. Our findings confirm the presence of ribotoxin-like proteins in basidiomycetes edible mushrooms, that we propose as novel tool for biotechnological applications.

We investigated the biochemical and biophysical properties of one of the four alternative exon-encoded regions within the Drosophila myosin catalytic domain. This region is encoded by alternative exons 3a and 3b and includes part of the N-terminal β-barrel. Chimeric myosin constructs (IFI-3a and EMB-3b) were generated by exchanging the exon 3–encoded areas between native slow embryonic body wall (EMB) and fast indirect flight muscle myosin isoforms (IFI). We found that this exchange alters the kinetic properties of the myosin S1 head. The ADP release rate (k-D) in the absence of actin is completely reversed for each chimera compared with the native isoforms. Steady-state data also suggest a reciprocal shift, with basal and actin-activated ATPase activity of IFI-3a showing reduced values compared with wild-type (WT) IFI, whereas for EMB-3b these values are increased compared with wild-type (WT) EMB. In the presence of actin, ADP affinity (KAD) is unchanged for IFI-3a, compared with IFI, but ADP affinity for EMB-3b is increased, compared with EMB, and shifted toward IFI values. ATP-induced dissociation of acto-S1 (K1k+2) is reduced for both exon 3 chimeras. Homology modeling, combined with a recently reported crystal structure for Drosophila EMB, indicates that the exon 3–encoded region in the myosin head is part of the communication pathway between the nucleotide binding pocket (purine binding loop) and the essential light chain, emphasizing an important role for this variable N-terminal domain in regulating actomyosin crossbridge kinetics, in particular with respect to the force-sensing properties of myosin isoforms.

Although genome-wide association studies (GWAS) have identified hundreds of autoimmune disease-associated loci, much of the genetics underlying these diseases remains unknown. In an attempt to identify potential causal variants, previous studies have determined that the rs35677470 missense variant of the Deoxyribonuclease I-like 3 (DNASE1L3) gene was associated with the development of systemic lupus erythematosus (SLE), rheumatoid arthritis (RA) and systemic sclerosis (SSc). DNase1L3 is a member of the human DNase I family, representing a nuclease that cleaves double-stranded DNA during apoptosis and serving a role in the development of autoimmune diseases. The present study aimed to determine the role of the rs35677470 variant at the DNASE1L3 gene leading to the R206C mutation in SLE, RA and SSc. The underlying mechanism potentially affecting protein structure loss of function was also assessed. DNASE1L3 evolution was investigated to define conservation elements in the protein sequence. Additionally, 3D homology modeling and in silico mutagenesis was performed to localize the polymorphism under investigation. Evolutionary analysis revealed heavily conserved sequence elements among species, indicating structural/functional importance. In silico mutagenesis and 3D protein structural analysis also demonstrated the potentially varied impact of the DNASE1L3 (rs35677470) single nucleotide polymorphism (SNP), providing an explanation for its effect on the R206C variant. Structural analysis demonstrated that the rs35677470 SNP encodes a non-conservative amino acid variation, R206C, which disrupted the conserved electrostatic network holding secondary protein structure elements in position. Specifically, the R206 to E170 interaction forming part of a salt bridge network stabilizing two α-helices was interrupted, thereby affecting the molecular architecture. Previous studies on the effect of this SNP in Caucasian populations demonstrated lower DNAse1L3 activity levels, which is consistent with the current results. The present study comprehensively evaluated the shared autoimmune locus of DNASE1L3 (rs35677470), which produced an inactive form of DNaseIL3. Furthermore, structural analysis explained the potential role of the produced mutation by modifying the placement of structural elements and consequently introducing disorder in protein folding, affecting biological function.

Identification of the molecular networks that facilitated the evolution of multicellular animals from their unicellular ancestors is a fundamental problem in evolutionary cellular biology. Choanoflagellates are recognized as the closest extant nonmetazoan ancestors to animals. These unicellular eukaryotes can adopt a multicellular‐like “rosette” state. Therefore, they are compelling models for the study of early multicellularity. Comparative studies revealed that a number of putative human orthologs are present in choanoflagellate genomes, suggesting that a subset of these genes were necessary for the emergence of multicellularity. However, previous work is largely based on sequence alignments alone, which does not confirm structural nor functional similarity. Here, we focus on the PDZ domain, a peptide‐binding domain which plays critical roles in myriad cellular signaling networks and which underwent a gene family expansion in metazoan lineages. Using a customized sequence similarity search algorithm, we identified 178 PDZ domains in the Monosiga brevicollis proteome. This includes 11 previously unidentified sequences, which we analyzed using Rosetta and homology modeling. To assess conservation of protein structure, we solved high‐resolution crystal structures of representative M. brevicollis PDZ domains that are homologous to human Dlg1 PDZ2, Dlg1 PDZ3, GIPC, and SHANK1 PDZ domains. To assess functional conservation, we calculated binding affinities for mbGIPC, mbSHANK1, mbSNX27, and mbDLG‐3 PDZ domains from M. brevicollis. Overall, we find that peptide selectivity is generally conserved between these two disparate organisms, with one possible exception, mbDLG‐3. Overall, our results provide novel insight into signaling pathways in a choanoflagellate model of primitive multicellularity.

Leishmaniasis refers to a complex of diseases, caused by the intracellular parasitic protozoans belonging to the genus Leishmania. Among the three types of disease manifestations, the most severe type is visceral leishmaniasis, which is caused by Leishmania donovani, and is diagnosed in more than 20,000 cases annually, worldwide. Because the current therapeutic options for disease treatment are associated with several limitations, the identification of new potential leads/drugs remains necessary. In this study, a combined approach was used, based on two different virtual screening (VS) methods, which were designed to select promising antileishmanial agents from among the entire sesquiterpene lactone (SL) dataset registered in SistematX, a web interface for managing a secondary metabolite database that is accessible by multiple platforms on the Internet. Thus, a ChEMBL dataset, including 3159 and 1569 structures that were previously tested against L. donovani amastigotes and promastigotes in vitro, respectively, was used to develop two random forest models, which performed with greater than 74% accuracy in both the cross-validation and test sets. Subsequently, a ligand-based VS assay was performed against the 1306 SistematX-registered SLs. In parallel, the crystal structures of three L. donovani target proteins, N-myristoyltransferase, ornithine decarboxylase, and mitogen-activated protein kinase 3, and a homology model of pteridine reductase 1 were used to perform a structure-based VS, using molecular docking, of the entire SistematX SL dataset. The consensus analysis of these two VS approaches resulted in the normalization of probability scores and identified 13 promising, enzyme-targeting, antileishmanial SLs from SistematX that may act against L. donovani. A combined approach based on two different virtual screening methods (structure-based and ligand-based) was performed using an in-house dataset composed of 1306 sesquiterpene lactones to identify potential antileishmanial (Leishmania donovani) structures.

Protein–protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state‐of‐the‐art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state‐of‐art methods.

We report the synthesis of seven new proluciferins for convenient activity determination of enzymes belonging to the cytochrome P450 (CYP) 4 family. Biotransformation of these probe substrates was monitored using each of the twelve human CYP4 family members, and eight were found to act at least on one of them. For all substrates, activity of CYP4Z1 was always highest, while that of CYP4F8 was always second highest. Site of metabolism (SOM) predictions involving SMARTCyp and docking experiments helped to rationalize the observed activity trends linked to substrate accessibility and reactivity. We further report the first homology model of CYP4F8 including suggested substrate recognition residues in a catalytically competent conformation accessed by replica exchange solute tempering (REST) simulations.

Our present work studies the structure-based pharmacophore modeling and designing inhibitor against Gal3 receptor through molecular dynamics (MD) simulations extensively. Pharmacophore models play a key role in computer-aided drug discovery like in the case of virtual screening of chemical databases, de novo drug design and lead optimization. Structure-based methods for developing pharmacophore models are important, and there have been a number of studies combining such methods with the use of MD simulations to model protein’s flexibility. The two potential antagonists SNAP 37889 and SNAP 398299 were docked and simulated for 250 ns and the results are analyzed and carried for the structure-based pharmacophore studies. This helped in identification of the subtype selectivity of the binding sites of the Gal3 receptor. Our work mainly focuses on identifying these binding site residues and to design more potent inhibitors compared to the previously available inhibitors through pharmacophore models. The study provides crucial insight into the binding site residues Ala2, Asp3, Ala4, Gln5, Phe24, Gln79, Ala80, Ile82, Tyr83, Trp88, His99, Ile102, Tyr103, Met106, Tyr157, Tyr161, Pro174, Trp176, Arg181, Ala183, Leu184, Asp185, Thr188, Trp248, His251, His252, Ile255, Leu256, Phe258, Trp259, Tyr270, Arg273, Leu274 and His277, which plays a significant role in the conformational changes of the receptor and helps to understand the inhibition mechanism. Communicated by Ramaswamy H. Sarma

Background Type A influenza viruses circulate and spread among wild birds and mostly consist of low pathogenic strains. However, fast genome variation timely results in the insurgence of high pathogenic strains, which when infecting poultry birds may cause a million deaths and strong commercial damage. More importantly, the host shift may concern these viruses and sustained human-to-human transmission may result in a dangerous pandemic outbreak. Therefore, fingerprints specific to either low or high pathogenic strains may represent a very important tool for global surveillance. Results We combined Normal Modes Analysis and surface electrostatic analysis of a mixed strain dataset of influenza A virus haemagglutinins from high and low pathogenic strains in order to infer specific fingerprints. Normal Modes Analysis sorted the strains in two different, homogeneous clusters; sorting was independent of clades and specific instead to high vs low pathogenicity. A deeper analysis of fluctuations and flexibility regions unveiled a special role for the 110-helix region. Specific sorting was confirmed by surface electrostatics analysis, which further allowed to focus on regions and mechanisms possibly crucial to the low-to-high transition. Conclusions Evidence from previous work demonstrated that changes in surface electrostatics are associated with the evolution and spreading of avian influenza A virus clades, and seemingly involved also in the avian to mammalian host shift. This work shows that a combination of electrostatics and Normal Modes Analysis can also identify fingerprints specific to high and low pathogenicity. The possibility to predict which specific mutations may result in a shift to high pathogenicity may help in surveillance and vaccine development.

Leishmaniasis is one of the most neglected tropical diseases that demand immediate attention to the identification of new drug targets and effective drug candidates. The present study demonstrates the possibility of using threonine synthase (TS) as a putative drug target in leishmaniasis disease management. We report the construction of an effective homology model of the enzyme that appears to be structurally as well as functionally well conserved. The 200 nanosecond molecular dynamics data on TS with and without pyridoxal phosphate (PLP) shed light on mechanistic details of PLP-induced conformational changes. Moreover, we address some important structural and dynamic interactions in the PLP binding region of TS that are in good agreement with previously speculated crystallographic estimations. Additionally, after screening more than 44,000 compounds, we propose 10 putative inhibitor candidates for TS based on virtual screening data and refined Molecular Mechanics Generalized Born Surface Area calculations. We expect that structural and functional dynamics data disclosed in this study will help initiate experimental endeavors toward establishing TS as an effective antileishmanial drug target.

In present work, we describe a methodology for prediction of an enzymatic reaction for which no experimental data are available except for a gene sequence. As a challenging case, we have developed ...