Methods of protein structure comparison

Design, synthesis, and biological evaluation of isatin-indole-3-carboxaldehyde hybrids as a new class of xanthine oxidase inhibitors

A novel series of triazole-linked isatin-indole-3-carboxaldehyde hybrids based on the febuxostat skeleton and its binding site interactions were rationally designed and synthesized as potential xanthine oxidase inhibitors. Among the synthesized hybrids, A19 showed the most potent xanthine oxidase inhibition (IC₅₀  = 0.37 µM) with the mixed-type inhibitory scenario. Structure-activity relationship studies revealed that methoxy (OCH₃ ) substitution on position 5 of the isatin nucleus and a two-carbon distance between isatin and the triazole moiety is most tolerable for the inhibitory potential. Various binding interactions of A19 with the binding site of xanthine oxidase are also streamlined by molecular docking studies, which showcase the favorable binding pattern for xanthine oxidase inhibition by the hybrid. Furthermore, molecular dynamic studies were performed that suggest the stability of the enzyme-hybrid complex. Overall, the study suggests that hybrid A19 can act as an effective hit lead for further development of potent xanthine oxidase inhibitors.

Nature-Inspired O-Benzyl Oxime-Based Derivatives as New Dual-Acting Agents Targeting Aldose Reductase and Oxidative Stress

Aldose reductase (ALR2) is the enzyme in charge of developing cellular toxicity caused by diabetic hyperglycemia, which in turn leads to the generation of reactive oxygen species triggering oxidative stress. Therefore, inhibiting ALR2 while pursuing a concomitant anti-oxidant activity through dual-acting agents is now recognized as the gold standard treatment for preventing or at least delaying the progression of diabetic complications. Herein we describe a novel series of (E)-benzaldehyde O-benzyl oximes 6a–e, 7a–e, 8a–e, and 9–11 as ALR2 inhibitors endowed with anti-oxidant properties. Inspired by the natural products, the synthesized derivatives are characterized by a different polyhydroxy substitution pattern on their benzaldehyde fragment, which proved crucial for both the enzyme inhibitory activity and the anti-oxidant capacity. Derivatives (E)-2,3,4-trihydroxybenzaldehyde O-(3-methoxybenzyl) oxime (7b) and (E)-2,3,4-trihydroxybenzaldehyde O-(4-methoxybenzyl) oxime (8b) turned out to be the most effective dual-acting products, proving to combine the best ALR2 inhibitory properties with significant anti-oxidant efficacy.

Inhibitory Effect of Polyphenols from the Whole Green Jackfruit Flour against α-Glucosidase, α-Amylase, Aldose Reductase and Glycation at Multiple Stages and Their Interaction: Inhibition Kinetics and Molecular Simulations

For the first time, α-glucosidase, α-amylase, aldose reductase, and glycation at multiple stages inhibitory assays were used to explore the antidiabetic potential of whole unripe jackfruit (peel with pulp, flake, and seed). Two polyphenols (phenolic acids) with strong antihyperglycaemic activity were isolated from the methanol extract of whole jackfruit flour (MJ) using activity-guided repeated fractionation on a silica gel column chromatography. The bioactive compounds isolated were identified as 3-(3,4-Dihydroxyphenyl)-2-propenoic acid (caffeic acid: CA) and 4-Hydroxy-3,5-dimethoxybenzoic acid (syringic acid: SA) after various physicochemical and spectroscopic investigations. CA (IC₅₀: 8.0 and 26.90 µg/mL) and SA (IC₅₀: 7.5 and 25.25 µg/mL) were identified to inhibit α-glucosidase and α-amylase in a competitive manner with low Ki values. In vitro glycation experiments further revealed that MJ and its components inhibited each stage of protein glycation as well as the generation of intermediate chemicals. Furthermore, CA (IC₅₀: 3.10) and SA (IC₅₀: 3.0 µg/mL) inhibited aldose reductase effectively in a non-competitive manner, respectively. The binding affinity of these substances towards the enzymes examined has been proposed by molecular docking and molecular dynamics simulation studies, which may explain their inhibitory activities. The found potential of MJ in antihyperglycaemic activity via inhibition of α-glucosidase and in antidiabetic action via inhibition of the polyol pathway and protein glycation is more likely to be related to the presence of the phenolic compounds, according to our findings.

Rethinking Protein Drug Design with Highly Accurate Structure Prediction of Anti-CRISPR Proteins

Protein therapeutics play an important role in controlling the functions and activities of disease-causing proteins in modern medicine. Despite protein therapeutics having several advantages over traditional small-molecule therapeutics, further development has been hindered by drug complexity and delivery issues. However, recent progress in deep learning-based protein structure prediction approaches, such as AlphaFold2, opens new opportunities to exploit the complexity of these macro-biomolecules for highly specialised design to inhibit, regulate or even manipulate specific disease-causing proteins. Anti-CRISPR proteins are small proteins from bacteriophages that counter-defend against the prokaryotic adaptive immunity of CRISPR-Cas systems. They are unique examples of natural protein therapeutics that have been optimized by the host-parasite evolutionary arms race to inhibit a wide variety of host proteins. Here, we show that these anti-CRISPR proteins display diverse inhibition mechanisms through accurate structural prediction and functional analysis. We find that these phage-derived proteins are extremely distinct in structure, some of which have no homologues in the current protein structure domain. Furthermore, we find a novel family of anti-CRISPR proteins which are structurally similar to the recently discovered mechanism of manipulating host proteins through enzymatic activity, rather than through direct inference. Using highly accurate structure prediction, we present a wide variety of protein-manipulating strategies of anti-CRISPR proteins for future protein drug design.

Enhancing the Antipsychotic Effect of Risperidone by Increasing Its Binding Affinity to Serotonin Receptor via Picric Acid: A Molecular Dynamics Simulation

The aim of this study was to assess the utility of inexpensive techniques in evaluating the interactions of risperidone (Ris) with different traditional -acceptors, with subsequent application of the findings into a Ris pharmaceutical formulation with improved therapeutic properties. Molecular docking calculations were performed using Ris and its different charge-transfer complexes (CT) with picric acid (PA), 2,3-dichloro-5,6-dicyanop-benzoquinon (DDQ), tetracyanoquinodimethane (TCNQ), tetracyano ethylene (TCNE), tetrabromo-pquinon (BL), and tetrachloro-p-quinon (CL), as donors, and three receptors (serotonin, dopamine, and adrenergic) as acceptors to study the comparative interactions among them. To refine the docking results and further investigate the molecular processes of receptor–ligand interactions, a molecular dynamics simulation was run with output obtained from AutoDock Vina. Among all investigated complexes, the [(Ris) (PA)]-serotonin (CTcS) complex showed the highest binding energy. Molecular dynamics simulation of the 100 ns run revealed that both the Ris-serotonin (RisS) and CTcS complexes had a stable conformation; however, the CTcS complex was more stable.

Identification of potential inhibitors of SARS-CoV-2 main protease and spike receptor from 10 important spices through structure-based virtual screening and molecular dynamic study

The outbreak of novel coronavirus disease (COVID-19) caused by SARS-CoV-2 poses a serious threat to human health and world economic activity. There is no specific drug for the treatment of COVID-19 patients at this moment. Traditionally, people have been using spices like ginger, fenugreek and onion, etc. for the remedy of a common cold. This work identifies the potential inhibitors of the main protease (Mpro) and spike (S) receptor of SARS-CoV-2 from 10 readily available spices. These two proteins, S and Mpro, play an important role during the virus entry into the host cell, and replication and transcription processes of the virus, respectively. To identify potential molecules an in-house databank containing 1040 compounds was built-up from the selected spices. Structure-based virtual screening of this databank was performed with two important SARS-CoV-2 proteins using Glide. Top hits resulted from virtual screening (VS) were subjected to molecular docking using AutoDock 4.2 and AutoDock Vina to eliminate false positives. The top six hits against Mpro and top five hits against spike receptor subjected to 130 ns molecular dynamic simulation using GROMACS. Finally, the compound 1-, 2-, 3- and 5-Mpro complexes, and compound 17-, 18-, 19-, 20- and 21- spike receptor complexes showed stability throughout the simulation time. The ADME values also supported the drug-like nature of the selected hits. These nine compounds are available in onion, garlic, ginger, peppermint, chili and fenugreek. All the spices are edible and might be used as home remedies against COVID-19 after proper biological evaluation.

In silico comparative analysis of KRAS mutations at codons 12 and 13: Structural modifications of P-Loop, switch I&II regions preventing GTP hydrolysis

KRAS mutation is prevalent in around 30% of all cancers and is an undruggable molecular target. Of seven mutations at codon 12 and 13, only one, the G12C mutant is finally proven to be druggable, as evidenced by the recent USFDA approval of sotorasib. Investigation of other small molecules targeting G12C and G12D are undergoing clinical trials. Understanding the fine structural details is a prerequisite to design specific inhibitors which also requires in depth molecular exploration. We used bioinformatics as a tool to analyze the KRAS protein's GTP (guanosine triphosphate) binding dynamics when mutated. KRAS undergoes significant conformational changes, affecting GTP binding conformation within the active site pocket of KRAS due to high torsional strains, hydrophobicity, and altered Switch I and II regions. GTP molecule for wildtype had a low torsional strain of 10.71, and is the only molecule, in comparison to KRAS mutant bound GTP, to have a glycine at position 10 interacting with its nitrogenous base. All mutant KRAS proteins lacked the interaction of glycine with the nitrogenous base. The binding affinity of wildtype (WT) KRAS for the gamma-phosphate was lower in scoring compared to the mutated KRAS protein in multiple analyses. This study provides an insight to the GTP-KRAS protein binding details that are important to define parameters required to be explored to design the appropriate inhibitor for each different type of mutant KRAS protein.

New Imidazole-Based N-Phenylbenzamide Derivatives as Potential Anticancer Agents: Key Computational Insights

An efficient atom-economical synthetic protocol to access new imidazole-based N-phenylbenzamide derivatives is described. A one-pot three-component reaction was utilized to provide a series of N-phenylbenzamide derivatives in a short reaction time (2–4 h) with an 80–85% yield. The cytotoxic evaluation revealed that derivatives 4e and 4f exhibited good activity, with IC₅₀ values between 7.5 and 11.1 μM against the tested cancer cell lines. Computational studies revealed interesting insights: the docking of the active derivatives (4e and 4f) showed a higher affinity toward the target receptor protein than the control. Molecular dynamic simulations revealed that the active derivatives form stable complexes with the ABL1 kinase protein. Moreover, the ADME and drug-likeness of the derivatives reinforced the potential of the derivatives to be taken up for further development as anticancer agents.

Methyltransferase as Antibiotics Against Foodborne Pathogens: An In Silico Approach for Exploring Enzyme as Enzymobiotics

The development of resistance in microbes against antibiotics and limited choice for the use of chemical preservatives in food lead the urgent need to search for an alternative to antibiotics. The enzymes are catalytic proteins that catalyze digestion of bacterial cell walls and protein requirements for the survival of the cell. To study methyltransferase as antibiotics against foodborne pathogen, the methyltransferase enzyme sequence was modeled and its interactions were analyzed against a membrane protein of the gram-positive and gram-negative bacteria through in silico protein-protein interactions. The methyltransferase interaction with cellular protein was found to be maximum, due to the maximum PatchDock Score (15808), which was followed by colicin (12864) and amoxicillin (4122). The modeled protein has found to be interact more significantly to inhibit the indicator bacteria than the tested antibiotics and antimicrobial colicin protein. Thus, model enzyme methyltransferase could be used as enzymobiotics. Moreover, peptide sequences similar to this enzyme sequence need to be designed and evaluated against the microbial pathogen.

In silico prediction of amino acids involved in cCPE290-319 interaction with claudin 4

Among the 26 human claudin proteins, the food-poisoning bacterium Clostridium perfringens produces an enterotoxin (~ 35.00 kDa) that specifically targets human claudin 4, causing diarrhea by fluid accumulation in the intestinal cavity. The Clostridium perfringens enterotoxin (CPE) C-terminal domain (cCPE ~ 15.00 kDa) tightly binds to claudin 4 and disrupts the tight junction barriers in the intestines. In this study, we aimed to determine the contribution and type of amino acid interactions involved in association between claudin 4 and the C-terminal CPE. First, the three-dimensional format of claudin 4 was downloaded from RCSB. Then, during 60.00 nanoseconds (nsec), molecular dynamics simulation was conducted using the GROMACS package on CPE of crystallographic structure. The results indicated that the simulations performed well during the simulation times and there were no noticeable problems or artifacts. We found that Coulombic (glycine 317, proline 311 and serine 313) and Lennard-Jones (tyrosine 310, leucine 315, serine 313 and glycine 317) interactions played a significant role in complex stability. This information localized the C-terminal of CPE as a linear sequence sufficient for recognition and binding to the eukaryotic CPE receptor. A detailed description of the dissociation process brings valuable insight into the interaction of the claudin 4-cCPE_290-319 complexes, which could help in the future to design more potent drugs.

Impact of Drug Repurposing on SARS-Cov-2 Main Protease

The recent emergence of the severe acute respiratory disease caused by a novel coronavirus remains a concern posing many challenges to public health and the global economy. The resolved crystal structure of the main protease of SARS-CoV-2 or SCV2 (M^pro) has led to its identification as an attractive target for designing potent antiviral drugs. Herein, we provide a comparative molecular impact of hydroxychloroquine (HCQ), remdesivir, and β-D-N⁴-Hydroxycytidine (NHC) binding on SCV2 M^pro using various computational approaches like molecular docking and molecular dynamics (MD) simulation. Data analyses showed that HCQ, remdesivir, and NHC binding to SARS-CoV-2 M^pro decrease the protease loop capacity to fluctuate. These binding influences the drugs’ optimum orientation in the conformational space of SCV2 M^pro and produce noticeable steric effects on the interactive residues. An increased hydrogen bond formation was observed in SCV2 M^pro–NHC complex with a decreased receptor residence time during NHC binding. The binding mode of remdesivir to SCV2 M^pro differs from other drugs having van der Waals interaction as the force stabilizing protein–remdesivir complex. Electrostatic interaction dominates in the SCV2 M^pro−HCQ and SCV2 M^pro–NHC. Residue Glu166 was highly involved in the stability of remdesivir and NHC binding at the SCV2 M^pro active site, while Asp187 provides stability for HCQ binding.

Correlated Motions and Dynamics in Different Domains of Epidermal Growth Factor Receptor With L858R and T790M Mutations

Non-small cell lung cancer with an activating epidermal growth factor receptor (EGFR) mutation responds well to targeted drugs. In most cases, drug resistance appears after about a year. Several studies have been conducted on the kinase domain of EGFR to understand the drug resistance mechanism. Since EGFR is a multi-domain protein, mutation in the kinase domain may affect the other domains as well. In this study, we examine the complete structure of the multi-domain EGFR protein and its mutants. We performed molecular dynamics simulations for wildtype EGFR, EGFR with L858R mutation, and EGFR with L858R and T790M mutations. We applied normal mode analysis and complex network analysis to extract the correlated motions in the domains of EGFR. The normal modes are used to construct the dynamic cross-correlation map (DCCM). Simulation results show different patterns of correlated motions in each domain of EGFR mutants compared to the wildtype. In Domains 1 and 3 of the extracellular region, a small number of weak positively correlated motions are extracted. Domains 2 and 4 show large numbers of both positive and negative motions. However, the negatively correlated motions are stronger in mutant structures compared to the wildtype. In Domain 7, some residues showed a positive correlation around the main diagonal. We also identified different communities, nodes and crucial residues in the domains of the structures, which can be important for the function of EGFR. Moreover, hydrogen bond analysis is performed for the stability analysis. The mutant structures have fewer hydrogen bonds compared to the wildtype. Overall, these findings are useful for understanding the dynamics and communications in EGFR domains.

RBD Double Mutations of SARS-CoV-2 Strains Increase Transmissibility through Enhanced Interaction between RBD and ACE2 Receptor

The COVID-19 pandemic, caused by SARS-CoV-2, has led to catastrophic damage for global human health. The initial step of SARS-CoV-2 infection is the binding of the receptor-binding domain (RBD) in its spike protein to the ACE2 receptor in the host cell membrane. Constant evolution of SARS-CoV-2 generates new mutations across its genome including the coding region for the RBD in the spike protein. In addition to the well-known single mutation in the RBD, the recent new mutation strains with an RBD "double mutation" are causing new outbreaks globally, as represented by the delta strain containing RBD L452R/T478K. Although it is considered that the increased transmissibility of double-mutated strains could be attributed to the altered interaction between the RBD and ACE2 receptor, the molecular details remain to be elucidated. Using the methods of molecular dynamics simulation, superimposed structural comparison, free binding energy estimation, and antibody escaping, we investigated the relationship between the ACE2 receptor and the RBD double mutants of L452R/T478K (delta), L452R/E484Q (kappa), and E484K/N501Y (beta, gamma). The results demonstrated that each of the three RBD double mutants altered the RBD structure and enhanced the binding of the mutated RBD to ACE2 receptor. Together with the mutations in other parts of the virus genome, the double mutations increase the transmissibility of SARS-CoV-2 to host cells.

Novel thiophene Chalcones-Coumarin as acetylcholinesterase inhibitors: Design, synthesis, biological evaluation, molecular docking, ADMET prediction and molecular dynamics simulation

A series of around eight novel chalcone based coumarin derivatives (23a-h) was designed, subjected to in-silico ADMET prediction, synthesized, characterized by IR, NMR, Mass analytical techniques and evaluated as acetylcholinesterase (AChE) inhibitor for the treatment of Alzheimer's disease (AD). The results of predicted ADMET study demonstrated the drug-likeness properties of the titled compounds with developmental challenges in lipophilicity and solubility parameters. The in vitro assessment of the synthesized compounds revealed that all of them showed significant activity (IC₅₀ ranging from 0.42 to 1.296 µM) towards AChE compared to the standard drug, galantamine (IC₅₀ = 1.142 ± 0.027 µM). Among these, compound 23e displayed the most potent inhibitory activity with IC₅₀ value of 0.42 ± 0.019 µM. Cytotoxicity of all compounds was tested on normal human hepatic (THLE-2) cell lines at three different concentrations using the MTT assay, in which none of the compound showed significant toxicity at the highest concentration of 1000 µg/ml compared to the control group. Based on the docking study against AChE, the most active derivative 23e was orientated towards the active site and occupied both catalytic anionic site (CAS) and peripheral anionic site (PAS) of the target enzyme. In-silico studies revealed tested showed better inhibition activity of AChE compared to Butyrylcholinesterase (BuChE). Molecular dynamics simulation explored the stability and dynamic behavior of 23e- AChE complex.

In silico assessment of chronic toxicity of a combination drug namely ‘Olmesartan medoxomil and Hydrochlorothiazide’, marketed in Bangladesh

Background

Nowadays combination therapy has become more popular due to their additional effect, synergistic effect and antagonistic effect. Any of these can influence the treatment profile. Combination therapy is used to treat some chronic diseases like diabetes, hypertension, cancer etc. But recently India has banned some fixed dose drug combinations due to their increased chances of adverse drug effects and drug interactions. So it is the time to take a look on the present drug combinations available in Bangladesh. An in silico study may provide important information about their probable toxicities. Drugs available in the combination may deposit slowly in the body and may lead to toxicities. Here an antihypertensive drug combination ‘Olmesartan medoxomil and Hydrochlorothiazide’ had been studied.

Results

Olmesartan medoxomil and Hydrochlorothiazide have not been found to comply any similar protein to interact with each other, thus no possible chance of additional toxicity of the combination in case of long term use.

Conclusions

At first, using PubChem the ligand was searched for a canonical SMILE. By inputting the canonical SMILE in Protox, a basic information about toxicities was predicted. From Swiss Target Prediction, target proteins responsible for both efficacy and toxicity were identified. These protein structures were downloaded from Protein Data Bank and edited with Flare. Undesired amino acid, ligand–ligand complex, fatty acid, and water molecules were removed by PyMOL. Structurally modified proteins and ligands were inputted in Swiss PDB viewer for energy minimization. Energy minimization is a very important step because unfavorable bond length, bond strength and torsion angle between protein and ligand may interfere with docking procedure. Then docking between Olmesartan medoxomil (ligand) and the proteins responsible for efficacy and toxicity was performed by PyRx. Vina binding affinity provided the value of binding strength between the ligand and the proteins, which determines how strong the bond is. The more negative the vina binding affinity, the stronger the bond. Discovery studio software was used to visualize the docking complexes. Same steps were followed for Hydrochlorothiazide to identify proteins responsible for desired and undesired effects, but no toxic effect was found from protox.

Exploiting Structural Modelling Tools to Explore Host-Translocated Effector Proteins

Oomycete and fungal interactions with plants can be neutral, symbiotic or pathogenic with different impact on plant health and fitness. Both fungi and oomycetes can generate so-called effector proteins in order to successfully colonize the host plant. These proteins modify stress pathways, developmental processes and the innate immune system to the microbes' benefit, with a very different outcome for the plant. Investigating the biological and functional roles of effectors during plant-microbe interactions are accessible through bioinformatics and experimental approaches. The next generation protein modeling software RoseTTafold and AlphaFold2 have made significant progress in defining the 3D-structure of proteins by utilizing novel machine-learning algorithms using amino acid sequences as their only input. As these two methods rely on super computers, Google Colabfold alternatives have received significant attention, making the approaches more accessible to users. Here, we focus on current structural biology, sequence motif and domain knowledge of effector proteins from filamentous microbes and discuss the broader use of novel modelling strategies, namely AlphaFold2 and RoseTTafold, in the field of effector biology. Finally, we compare the original programs and their Colab versions to assess current strengths, ease of access, limitations and future applications.

An online GPCR structure analysis platform

We present an online, interactive platform for comparative analysis of all available G-protein coupled receptor (GPCR) structures while correlating to functional data. The comprehensive platform encompasses structure similarity, secondary structure, protein backbone packing and movement, residue-residue contact networks, amino acid properties and prospective design of experimental mutagenesis studies. This lets any researcher tap the potential of sophisticated structural analyses enabling a plethora of basic and applied receptor research studies.

Structural Insights on the SARS-CoV-2 Variants of Concern Spike Glycoprotein: A Computational Study With Possible Clinical Implications

Coronavirus disease 2019 (COVID-19) pandemic has been attributed to SARS-CoV-2 (SARS2) and, consequently, SARS2 has evolved into multiple SARS2 variants driving subsequent waves of infections. In particular, variants of concern (VOC) were identified to have both increased transmissibility and virulence ascribable to mutational changes occurring within the spike protein resulting to modifications in the protein structural orientation which in-turn may affect viral pathogenesis. However, this was never fully elucidated. Here, we generated spike models of endemic HCoVs (HCoV 229E, HCoV OC43, HCoV NL63, HCoV HKU1, SARS CoV, MERS CoV), original SARS2, and VOC (alpha, beta, gamma, delta). Model quality check, structural superimposition, and structural comparison based on RMSD values, TM scores, and contact mapping were all performed. We found that: 1) structural comparison between the original SARS2 and VOC whole spike protein model have minor structural differences (TM > 0.98); 2) the whole VOC spike models putatively have higher structural similarity (TM > 0.70) to spike models from endemic HCoVs coming from the same phylogenetic cluster; 3) original SARS2 S1-CTD and S1-NTD models are structurally comparable to VOC S1-CTD (TM = 1.0) and S1-NTD (TM > 0.96); and 4) endemic HCoV S1-CTD and S1-NTD models are structurally comparable to VOC S1-CTD (TM > 0.70) and S1-NTD (TM > 0.70) models belonging to the same phylogenetic cluster. Overall, we propose that structural similarities (possibly ascribable to similar conformational epitopes) may help determine immune cross-reactivity, whereas, structural differences (possibly associated with varying conformational epitopes) may lead to viral infection (either reinfection or breakthrough infection).

Potential efficacy of existing drug molecules against severe fever with thrombocytopenia syndrome virus: an in silico study

Severe fever with thrombocytopenia syndrome (SFTS) is a zoonotic disease caused by the SFTS virus (SFTSV). SFTS can be considered a life-threatening notifiable infectious disease. The unavailability of specific therapeutics encourages the investigation of potential efficacy of existing drugs against this infection. Drug repurposing was done by performing  virtual screening of already established drug molecules followed by 100 ns molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area-based binding-energy calculation by targeting the SFTS L protein. On the basis of binding energy and protein-ligand interactions, top 10 promising hits were identified, showing stable binding with SFTS L protein. Further 100 ns atomistic MD simulation refined the hits from top 10 to top 4 with docking-based binding energy lesser than -8.0 kcal/mol toward the SFTS L protein and engaged in π-π interactions with pivotal amino acid residues. Various parameters and binding affinity of top 4 ligands towards L protein was computed. Ligand zaltoprofen exhibited best binding energy -220.095 kJ/mol. The present work is the first in silico study to assess bromfenac, cinchophen, elliptinium, and zaltoprofen; four promising hits against SFTS. Nonetheless, further proper biological evaluation is necessary to determine their efficacy against SFTS.

Marine Brominated Tyrosine Alkaloids as Promising Inhibitors of SARS-CoV-2

There have been more than 150 million confirmed cases of SARS-CoV-2 since the beginning of the pandemic in 2019. By June 2021, the mortality from such infections approached 3.9 million people. Despite the availability of a number of vaccines which provide protection against this virus, the evolution of new viral variants, inconsistent availability of the vaccine around the world, and vaccine hesitancy, in some countries, makes it unreasonable to rely on mass vaccination alone to combat this pandemic. Consequently, much effort is directed to identifying potential antiviral treatments. Marine brominated tyrosine alkaloids are recognized to have antiviral potential. We test here the antiviral capacity of fourteen marine brominated tyrosine alkaloids against five different target proteins from SARS-CoV-2, including main protease (M^pro) (PDB ID: 6lu7), spike glycoprotein (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17), and non-structural protein 10 (nsp10) (PDB ID: 6W4H). These marine alkaloids, particularly the hexabrominated compound, fistularin-3, shows promising docking interactions with predicted binding affinities (S-score = −7.78, −7.65, −6.39, −6.28, −8.84 Kcal/mol) for the main protease (M^pro) (PDB ID: 6lu7), spike glycoprotein (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17), and non-structural protein 10 (nsp10) (PDB ID: 6W4H), respectively, where it forms better interactions with the protein pockets than the native interaction. It also shows promising molecular dynamics, pharmacokinetics, and toxicity profiles. As such, further exploration of the antiviral properties of fistularin-3 against SARS-CoV-2 is merited.

Context-Specific Function of the Engineered Peptide Domain of PHP.B

One approach to improve the utility of adeno-associated virus (AAV)-based gene therapy is to engineer the AAV capsid to 1) overcome poor transport through tissue barriers and 2) redirect the broadly tropic AAV to disease-relevant cell types. Peptide- or protein-domain insertions into AAV surface loops can achieve both engineering goals by introducing a new interaction surface on the AAV capsid. However, we understand little about the impact of insertions on capsid structure and the extent to which engineered inserts depend on a specific capsid context to function. Here, we examine insert-capsid interactions for the engineered variant AAV9-PHP.B. The 7-amino-acid peptide insert in AAV9-PHP.B facilitates transport across the murine blood-brain barrier via binding to the receptor Ly6a. When transferred to AAV1, the engineered peptide does not bind Ly6a. Comparative structural analysis of AAV1-PHP.B and AAV9-PHP.B revealed that the inserted 7-amino-acid loop is highly flexible and has remarkably little impact on the surrounding capsid conformation. Our work demonstrates that Ly6a binding requires interactions with both the PHP.B peptide and specific residues from the AAV9 HVR VIII region. An AAV1-based vector that incorporates a larger region of AAV9-PHP.B-including the 7-amino-acid loop and adjacent HVR VIII amino acids-can bind to Ly6a and localize to brain tissue. However, unlike AAV9-PHP.B, this AAV1-based vector does not penetrate the blood-brain barrier. Here we discuss the implications for AAV capsid engineering and the transfer of engineered activities between serotypes. Importance Targeting AAV vectors to specific cellular receptors is a promising strategy for enhancing expression in target cells or tissues while reducing off-target transgene expression. The AAV9-PHP.B/Ly6a interaction provides a model system with a robust biological readout that can be interrogated to better understand the biology of AAV vectors' interactions with target receptors. In this work, we analyzed the sequence and structural features required to successfully transfer the Ly6a receptor-binding epitope from AAV9-PHP.B to another capsid of clinical interest: AAV1. We found that AAV1- and AAV9-based vectors targeted to the same receptor exhibited different brain-transduction profiles. Our work suggests that, in addition to attachment-receptor binding, the capsid context in which this binding occurs is important for a vector's performance.

Camptothecin shows better promise than Curcumin in the inhibition of the Human Telomerase: A computational study

OBJECTIVES

The Human Telomerase enzyme has become a drug target in the treatment of cancers and age-related disorders. This study aims to identify potential natural inhibitors of the Human Telomerase from compounds derived from edible African plants.

MATERIALS AND METHODS

A library of 1,126 natural compounds was molecularly docked against the Telomerase Reverse Transcriptase (PDB ID: 5ugw), the catalytic subunit of the target protein. Curcumin, a known Telomerase inhibitor was used as the standard. The front-runner compounds were screened for bioavailability, pharmacokinetic properties, and bioactivity using the SWISSADME, PKCSM, and Molinspiration webservers respectively. The molecular dynamic simulation and analyses of the apo and holo proteins were performed by the Galaxy supercomputing webserver.

RESULTS

The results of the molecular docking and virtual screening reveal Augustamine and Camptothecin as lead compounds. Augustamine has better drug-likeness and pharmacokinetic properties while Camptothecin showed better bioactivity and stronger binding affinity (-8.2 kcal/mol) with the target. The holo structure formed by Camptothecin showed greater inhibitory activity against the target with a total RMSF of 169.853, B-Factor of 20.164, and 108 anti-correlating residues.

CONCLUSION

Though they both act at the same binding site, Camptothecin induces greater Telomerase inhibition and better molecular stability than the standard, Curcumin. Further tests are required to investigate the inhibitory activities of the lead compounds.

Therapeutic development by repurposing drugs targeting SARS-CoV-2 spike protein interactions by simulation studies

The human-to-human transmitted respiratory illness in COVID-19 affected by the pathogenic Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2), which appeared in the last of December 2019 in Wuhan, China, and rapidly spread in many countries. Thereon, based on the urgent need for therapeutic molecules, we conducted in silico based docking and simulation molecular interaction studies on repurposing drugs, targeting SARS-CoV-2 spike protein. Further, the best binding energy of doxorubicin interacting with virus spike protein (PDB: 6VYB) was observed to be -6.38 kcal/mol and it was followed by exemestane and gatifloxacin. The molecular simulation dynamics analysis of doxorubicin, Reference Mean Square Deviation (RMSD), Root Mean Square fluctuation (RMSF), Radius of Gyration (Rg), and formation of hydrogen bonds plot interpretation suggested, a significant deviation and fluctuation of Doxorubicin-Spike RBD complex during the whole simulation period. The Rg analysis has stated that the Doxorubicin-Spike RBD complex was stable during 15,000-35,000 ps MDS. The results have suggested that doxorubicin could inhibit the virus spike protein and prevent the access of the SARS-CoV-2 to the host cell. Thus, in-vitro/in-vivo research on these drugs could be advantageous to evaluate significant molecules that control the COVID-19 disease.

Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions

Molecular simulations are a powerful tool to complement and interpret ambiguous experimental data on biomolecules to obtain structural models. Such data-assisted simulations often rely on parameters, the choice of which is highly non-trivial and crucial to performance. The key challenge is weighting experimental information with respect to the underlying physical model. We introduce FLAPS, a self-adapting variant of dynamic particle swarm optimization, to overcome this parameter selection problem. FLAPS is suited for the optimization of composite objective functions that depend on both the optimization parameters and additional, a priori unknown weighting parameters, which substantially influence the search-space topology. These weighting parameters are learned at runtime, yielding a dynamically evolving and iteratively refined search-space topology. As a practical example, we show how FLAPS can be used to find functional parameters for small-angle X-ray scattering-guided protein simulations.

Biophysical applications in structural and molecular biology

The main objective of structural biology is to model proteins and other biological macromolecules and link the structural information to function and dynamics. The biological functions of protein molecules and nucleic acids are inherently dependent on their conformational dynamics. Imaging of individual molecules and their dynamic characteristics is an ample source of knowledge that brings new insights about mechanisms of action. The atomic-resolution structural information on most of the biomolecules has been solved by biophysical techniques; either by X-ray diffraction in single crystals or by nuclear magnetic resonance (NMR) spectroscopy in solution. Cryo-electron microscopy (cryo-EM) is emerging as a new tool for analysis of a larger macromolecule that couldn't be solved by X-ray crystallography or NMR. Now a day's low-resolution Cryo-EM is used in combination with either X-ray crystallography or NMR. The present review intends to provide updated information on applications like X-ray crystallography, cryo-EM and NMR which can be used independently and/or together in solving structures of biological macromolecules for our full comprehension of their biological mechanisms.

Criteria for Engineering Cutinases: Bioinformatics Analysis of Catalophores

Cutinases are bacterial and fungal enzymes that catalyze the hydrolysis of natural cutin, a three-dimensional inter-esterified polyester with epoxy-hydroxy fatty acids with chain lengths between 16 and 18 carbon atoms. Due to their ability to accept long chain substrates, cutinases are also effective in catalyzing in vitro both the degradation and synthesis of several synthetic polyesters and polyamides. Here, we present a bioinformatics study that intends to correlate the structural features of cutinases with their catalytic properties to provide rational basis for their effective exploitation, particularly in polymer synthesis and biodegradation. The bioinformatics study used the BioGPS method (Global Positioning System in Biological Space) that computed molecular descriptors based on Molecular Interaction Fields (MIFs) described in the GRID force field. The information was used to generate catalophores, spatial representations of the ability of each enzymatic active site to establish hydrophobic and electrostatic interactions. These tools were exploited for comparing cutinases to other serine-hydrolases enzymes, namely lipases, esterases, amidases and proteases, and for highlighting differences and similarities that might guide rational engineering strategies. Structural features of cutinases with their catalytic properties were correlated. The “catalophore” of cutinases indicate shared features with lipases and esterases.

Mechanistic insights into TNFR1/MADD death domains in Alzheimer's disease through conformational molecular dynamic analysis

Proteins are tiny players involved in the activation and deactivation of multiple signaling cascades through interactions in cells. The TNFR1 and MADD interact with each other and mediate downstream protein signaling pathways which cause neuronal cell death and Alzheimer’s disease. In the current study, a molecular docking approach was employed to explore the interactive behavior of TNFR1 and MADD proteins and their role in the activation of downstream signaling pathways. The computational sequential and structural conformational results revealed that Asp400, Arg58, Arg59 were common residues of TNFR1 and MADD which are involved in the activation of downstream signaling pathways. Aspartic acid in negatively charged residues is involved in the biosynthesis of protein. However, arginine is a positively charged residue with the potential to interact with oppositely charged amino acids. Furthermore, our molecular dynamic simulation results also ensured the stability of the backbone of TNFR1 and MADD death domains (DDs) in binding interactions. This DDs interaction mediates some conformational changes in TNFR1 which leads to the activation of mediators proteins in the cellular signaling pathways. Taken together, a better understanding of TNFR1 and MADD receptors and their activated signaling cascade may help treat Alzheimer’s disease. The death domains of TNFR1 and MADD could be used as a novel pharmacological target for the treatment of Alzheimer’s disease by inhibiting the MAPK pathway.

A novel P38α MAPK activator Bruceine A exhibits potent anti-pancreatic cancer activity

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Bruceine A displays potent anti-pancreatic cancer activity in vitro and in vivo.

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Phosphoproteomic analyses identify bruceine A induces phosphorylation of p38α MAPK.

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Octet system and microscale thermophoresis reveal p38α MAPK has high affinity for bruceine A.

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Molecular simulations illustrate determinants of bruceine A binding with p38α MAPK.

Pancreatic cancer remains one of the cancers with the poorest prognosis bearing an overall 5-year survival rate of about 5%. Efficient new chemotherapic drugs are still highly desired. Here, bruceine A, a quassinoid identified from the dried fruits of Brucea javanica (L.) Merr., displayed the most potent anti-proliferation activity against pancreatic cancer in vitro and in vivo. Phosphoproteomic analysis revealed p38α MAPK phosphorylation was involved in bruceine A’s action in MIA PaCa-2 cells. Utilizing fortebio octet system and microscale thermophoresis, we found p38α MAPK had high affinity for bruceine A. Molecular docking and molecular dynamic simulations showed that bruceine A widely bound to residues (Leu171, Ala172, Met179, Thr180, Val183) in P-loop of p38α MAPK. Key determinants of bruceine A binding with P-loop of p38α MAPK were 19-C Created by potrace 1.16, written by Peter Selinger 2001-2019 ]]>O, 22-CH₃, 32-CH₃, and 34-CH₃. Taken together, our findings demonstrate that bruceine A binds directly to p38α MAPK, which can be used to probe the role of p38α MAPK phosphorylation in pancreatic cancer progression, and as a novel lead compound for pancreatic cancer therapy.

Yeast-based screening of cancer mutations in the DNA damage response protein Mre11 demonstrates importance of conserved capping domain residues

DNA damage response (DDR) pathways are initiated to prevent mutations from being passed on in the event of DNA damage. Mutations in DDR proteins can contribute to the development and maintenance of cancer cells, but many mutations observed in human tumors have not been functionally characterized. Because a proper response to DNA damage is fundamental to living organisms, DDR proteins and processes are often highly conserved. The goal of this project was to use Saccharomyces cerevisiae as a model for functional screening of human cancer mutations in conserved DDR proteins. After comparing the cancer mutation frequency and conservation of DDR proteins, Mre11 was selected for functional screening. A subset of mutations in conserved residues was analyzed by structural modeling and screened for functional effects in yeast Mre11. Yeast expressing wild type or mutant Mre11 were then assessed for DNA damage sensitivity using hydroxyurea (HU) and methyl methanesulfonate (MMS). The results were further validated in human cancer cells. The N-terminal point mutations tested in yeast Mre11 do not confer sensitivity to DNA damage sensitivity, suggesting that these residues are dispensable for yeast Mre11 function and may have conserved sequence without conserved function. However, a mutation near the capping domain associated with breast and colorectal cancers compromises Mre11 function in both yeast and human cells. These results provide novel insight into the function of this conserved capping domain residue and demonstrate a framework for yeast-based screening of cancer mutations.

Binding interaction of protoberberine alkaloids against acetylcholinesterase (AChE) using molecular dynamics simulations and QM/MM calculations

Acetylcholinesterase (AChE) plays a vital role in Alzheimer's disease (AD), which is one of the most common causes of dementia. Discovering new effective inhibitors against AChE activity is seen to be one of the effective approaches to reduce the suffering from AD. Protoberberine alkaloids isolated from natural resources have previously been reported as potent AChE inhibitors. In order to gain insights into how these alkaloids could inhibit AChE, berberine, palmatine, and cyclanoline were selected to investigate in terms of binding orientation and their key interactions with AChE using molecular docking and molecular dynamics simulations and quantum chemical calculations. The results revealed that the molecular dynamics structures of palmatine and berberine indicated that their equilibrated structures did not occupy the gorge but they slightly moved away from the catalytic site (CAS). For cyclanoline, the binding mode was quite different from those of donepezil and the other protoberberine alkaloids: it preferred to stay deeper in the CAS site. Interaction energies and residual interaction energies confirmed that the key interactions for palmatine and berberine were π-π interactions with Trp286 and Tyr341 and H-bond interactions with Tyr124. Cyclanoline formed π-π interactions with Trp86 and H-bonds to the amino acids in the CAS site. The results suggested the importance of aromaticity in the core structure and the flexibility of the core structure or the substituents in order to fit into the narrow gorge. The HOMO, LUMO, bioavailability, drug-likeness and pharmacokinetics were also predicted. The results obtained will be useful for further AD drug development.

HEMNMA-3D: Cryo Electron Tomography Method Based on Normal Mode Analysis to Study Continuous Conformational Variability of Macromolecular Complexes

Cryogenic electron tomography (cryo-ET) allows structural determination of biomolecules in their native environment (in situ). Its potential of providing information on the dynamics of macromolecular complexes in cells is still largely unexploited, due to the challenges of the data analysis. The crowded cell environment and continuous conformational changes of complexes make difficult disentangling the data heterogeneity. We present HEMNMA-3D, which is, to the best of our knowledge, the first method for analyzing cryo electron subtomograms in terms of continuous conformational changes of complexes. HEMNMA-3D uses a combination of elastic and rigid-body 3D-to-3D iterative alignments of a flexible 3D reference (atomic structure or electron microscopy density map) to match the conformation, orientation, and position of the complex in each subtomogram. The elastic matching combines molecular mechanics simulation (Normal Mode Analysis of the 3D reference) and experimental, subtomogram data analysis. The rigid-body alignment includes compensation for the missing wedge, due to the limited tilt angle of cryo-ET. The conformational parameters (amplitudes of normal modes) of the complexes in subtomograms obtained through the alignment are processed to visualize the distribution of conformations in a space of lower dimension (typically, 2D or 3D) referred to as space of conformations. This allows a visually interpretable insight into the dynamics of the complexes, by calculating 3D averages of subtomograms with similar conformations from selected (densest) regions and by recording movies of the 3D reference's displacement along selected trajectories through the densest regions. We describe HEMNMA-3D and show its validation using synthetic datasets. We apply HEMNMA-3D to an experimental dataset describing in situ nucleosome conformational variability. HEMNMA-3D software is available freely (open-source) as part of ContinuousFlex plugin of Scipion V3.0 (http://scipion.i2pc.es).

Phytochemical Moieties From Indian Traditional Medicine for Targeting Dual Hotspots on SARS-CoV-2 Spike Protein: An Integrative in-silico Approach

SARS-CoV-2 infection across the world has led to immense turbulence in the treatment modality, thus demanding a swift drug discovery process. Spike protein of SARS-CoV-2 binds to ACE2 receptor of human to initiate host invasion. Plethora of studies demonstrate the inhibition of Spike-ACE2 interactions to impair infection. The ancient Indian traditional medicine has been of great interest of Virologists worldwide to decipher potential antivirals. Hence, in this study, phytochemicals (1,952 compounds) from eight potential medicinal plants used in Indian traditional medicine were meticulously collated, based on their usage in respiratory disorders, along with immunomodulatory and anti-viral potential from contemporary literature. Further, these compounds were virtually screened against Receptor Binding Domain (RBD) of Spike protein. The potential compounds from each plant were prioritized based on the binding affinity, key hotspot interactions at ACE2 binding region and glycosylation sites. Finally, the potential hits in complex with spike protein were subjected to Molecular Dynamics simulation (450 ns), to infer the stability of complex formation. Among the compounds screened, Tellimagrandin-II (binding energy of −8.2 kcal/mol and binding free energy of −32.08 kcal/mol) from Syzygium aromaticum L. and O-Demethyl-demethoxy-curcumin (binding energy of −8.0 kcal/mol and binding free energy of −12.48 kcal/mol) from Curcuma longa L. were found to be highly potential due to their higher binding affinity and significant binding free energy (MM-PBSA), along with favorable ADMET properties and stable intermolecular interactions with hotspots (including the ASN343 glycosylation site). The proposed hits are highly promising, as these are resultant of stringent in silico checkpoints, traditionally used, and are documented through contemporary literature. Hence, could serve as promising leads for subsequent experimental validations.

Stereochemical Trajectories of a Two-Component Regulatory System PmrA/B in a Colistin-Resistant Acinetobacter baumannii Clinical Isolate

Background:

There is limited information on the 3D prediction and modeling of the colistin resistance-associated proteins PmrA/B TCS in Acinetobacter baumannii. We aimed to evaluate the stereochemical structure and domain characterization of PmrA/B in an A. baumannii isolate resistant to high-level colistin, using bioinformatics tools.

Methods:

The species of the isolate and its susceptibility to colistin were confirmed by PCR-sequencing and MIC assay, respectively. For 3D prediction of the PmrA/B, we used 16 template models with the highest quality (e-value <1 × 10−50).

Results:

Prediction of the PmrA structure revealed a monomeric non-redundant protein consisting of 28 α-helices and 22 β-sheets. The PmrA DNA-binding motif displayed three antiparallel α-helices, followed by three β-sheets, and was bond to the major groove of DNA by intermolecular van der Waals bonds through amino acids Lys, Asp, His, and Arg, respectively. Superimposition of the deduced PmrA 3D structure with the closely related PmrA protein model (GenBank no. WP_071210493.1) revealed no distortion in conformation, due to Glu→Lys substitution at position 218. Similarly, the PmrB protein structure displayed 24 α-helices and 13 β-sheets. In our case, His251 acted as a phosphate receptor in the HisKA domain. The amino acid substitutions were mainly observed at the putative N-terminus region of the protein. Furthermore, two substitutions (Lys21→Ser and Ser28→Arg) in the transmembrane domain were detected.

Conclusion:

TheDNA-binding motif of PmrA is highly conserved, though the N-terminal fragment of PmrB showed a high rate of base substitutions. This research provides valuable insights into the mechanism of colistin resistance in A. baumannii.

Computational Screening of Potential Inhibitors of Desulfobacter postgatei for Pyrite Scale Prevention in Oil and Gas Wells

Sulfate-reducing bacteria (SRB), such as Desulfobacter postgatei are found in oil wells. However, they lead to the release of hydrogen sulfide. This in turn leads to the iron sulfide scale formation (pyrite). ATP sulfurylase is an enzyme present in SRB, which catalyzes the formation of adenylyl sulfate (APS) and inorganic pyrophosphatase (PPi) from ATP and sulfate. This reaction is the first among many in hydrogen sulfide production by D. postgatei . Consensus scoring using molecular docking and machine learning was used to identify three potential inhibitors of ATP sulfurylase from a database of about 40 million compounds. These selected hits ((S,E)-1-(4-methoxyphenyl)-3-(9-((m-tolylimino)methyl)-9,10-dihydroanthracen-9-yl)pyrrolidine-2,5-dione; methyl 2-[[(1S)-5-cyano-2-imino-1-(4-phenylthiazol-2-yl)-3-azaspiro[5.5]undec-4-en-4-yl]sulfanyl]acetate; and (4S)-4-(3-chloro-4-hydroxy-phenyl)-1-(6-hydroxypyridazin-3-yl)-3-methyl-4,5-dihydropyrazolo[3,4-b]pyridin-6-ol), known as A, B, and C, respectively) all had good binding affinities with ATP sulfurylase and were further analyzed for their toxicological properties. Compound A had the highest docking score. However, based on the physicochemical and toxicological properties, only compound C was predicted to be both safe and effective as a potential inhibitor of ATP sulfurylase, hence the preferred choice. The molecular interactions of compound C revealed favorable interactions with the following residues: LEU213, ASP308, ARG307, TRP347, LEU224, GLN212, MET211, and HIS309.

Effect of molecular properties of the protein-ligand complex on the prediction accuracy of AutoDock

Molecular docking approach has been extensively used to predict the ligand's binding conformation in the binding pocket of protein. However, its prediction accuracy is still limited and highly dependent on target protein-ligand complexes. In this study, we investigated the effects of ligand torsion number, ligand hydrophobicity, and binding-site hydrophobicity on the prediction accuracy of Autodock, a popular molecular docking tool, combinatorially as well as respectively. A clear understanding of how these properties affect the prediction accuracy was observed when these properties were studied combinatorially rather than individually. The combination of low ligand torsion number-hydrophilic ligand-hydrophobic binding site provided the best prediction accuracy while the high ligand torsion number-hydrophilic ligand-hydrophobic binding pocket combination showed the least prediction accuracy. This study allowed us to determine the molecular properties of complex, showing relatively higher or low prediction accuracy and can be employed as a reference in the molecular docking studies using Autodock.

A Novel Automated Screening Method for Combinatorially Generated Small Molecules

A main challenge in the enumeration of small-molecule chemical spaces for drug design is to quickly and accurately differentiate between possible and impossible molecules. Current approaches for screening enumerated molecules (e.g., 2D heuristics and 3D force fields) have not been able to achieve a balance between accuracy and speed. We have developed a new automated approach for fast and high-quality screening of small molecules, with the following steps: (1) for each molecule in the set, an ensemble of 2D descriptors as feature encoding is computed; (2) on a random small subset, classification (feasible/infeasible) targets via a 3D-based approach are generated; (3) a classification dataset with the computed features and targets is formed and a machine learning model for predicting the 3D approach's decisions is trained; and (4) the trained model is used to screen the remainder of the enumerated set. Our approach is ≈8× (7.96× to 8.84×) faster than screening via 3D simulations without significantly sacrificing accuracy; while compared to 2D-based pruning rules, this approach is more accurate, with better coverage of known feasible molecules. Once the topological features and 3D conformer evaluation methods are established, the process can be fully automated, without any additional chemistry expertise.

Collagen IVα345 dysfunction in glomerular basement membrane diseases. II. Crystal structure of the α345 hexamer

Our recent work identified a genetic variant of the α345 hexamer of the collagen IV scaffold that is present in patients with glomerular basement membrane diseases, Goodpasture’s disease (GP) and Alport syndrome (AS), and phenocopies of AS in knock-in mice. To understand the context of this “Zurich” variant, an 8-amino acid appendage, we developed a construct of the WT α345 hexamer using the single-chain NC1 trimer technology, which allowed us to solve a crystal structure of this key connection module. The α345 hexamer structure revealed a ring of 12 chloride ions at the trimer–trimer interface, analogous to the collagen α121 hexamer, and the location of the 170 AS variants. The hexamer surface is marked by multiple pores and crevices that are potentially accessible to small molecules. Loop-crevice-loop features constitute bioactive sites, where pathogenic pathways converge that are linked to AS and GP, and, potentially, diabetic nephropathy. In Pedchenko et al., we demonstrate that these sites exhibit conformational plasticity, a dynamic property underlying assembly of bioactive sites and hexamer dysfunction. The α345 hexamer structure is a platform to decipher how variants cause AS and how hypoepitopes can be triggered, causing GP. Furthermore, the bioactive sites, along with the pores and crevices on the hexamer surface, are prospective targets for therapeutic interventions.

In silico studies reveal structural deviations of mutant profilin-1 and interaction with riluzole and edaravone in amyotrophic lateral sclerosis

This study aimed to investigate four of the eight PFN-1 mutations that are located near the actin-binding domain and determine the structural changes due to each mutant and unravel how these mutations alter protein structural behavior. Swapaa's command in UCSF chimera for generating mutations, FTMAP were employed and the data was analyzed by RMSD, RMSF graphs, Rg, hydrogen bonding analysis, and RRdisMaps utilizing Autodock4 and GROMACS. The functional changes and virtual screening, structural dynamics, and chemical bonding behavior changes, molecular docking simulation with two current FDA-approved drugs for ALS were investigated. The highest reduction and increase in Rg were found to exist in the G117V and M113T mutants, respectively. The RMSF data consistently shows changes nearby to this site. The in silico data described indicate that each of the mutations is capable of altering the structure of PFN-1 in vivo. The potential effect of riluzole and edaravone two FDA approved drugs for ALS, impacting the structural deviations and stabilization of the mutant PFN-1 is evaluated using in silico tools. Overall, the analysis of data collected reveals structural changes of mutant PFN-1 protein that may explain the neurotoxicity and the reason(s) for possible loss and gain of function of PFN-1 in the neurotoxic model of ALS.

In silico design of bioisosteric modifications of drugs for the treatment of diabetes

Aim: To identify virtual bioisosteric replacements of two GPR40 agonists. Materials & methods: Bioinformatic docking of candidate molecules featuring a wide range of carboxylic acid bioisosteres into complex with GPR40 was performed using TAK-875 and GW9508 templates. Results: This study suggests that 2,6-difluorophenol and squaric acid motifs are the preferred bioisosteric groups for conferring GPR40 affinity. Conclusion: This study suggests that compounds 10 and 20 are worthy synthetic targets.

Interaction between LINC-ROR and Stemness State in Gastric Cancer Cells with Helicobacter pylori Infection

BACKGROUND

Large intergenic non-coding RNA regulator of reprogramming (LINC-ROR), as a cancer-related Long non-coding RNA, has vital roles in stem cell survival, pluripotency, differentiation, and self-renewal in human embryonic stem cell. However, cancer-related molecular mech¬anisms, its functional roles, and clinical value of LINC-ROR in gastric cancer (GC) remain unclear. In this study, we aimed to investigate probable interplay between LINC-ROR with SALL4 stemness regulator and their role with the development of the disease.

METHODS

The mRNA expression profile of LINC-ROR and SALL4 was assessed in tumoral and adjacent non-cancerous tissues of GC patients, using quantitative real-time PCR.

RESULTS

Significant LINC-ROR underexpression and SALL4 overexpression were observed in 55.81% and 75.58% (p < 0.0001) of samples, respectively. The expression of LINC-ROR and SALL4 were significantly correlated with each other (p = 0.044). There was an association between the underexpression of LINC-ROR and sex, stage of tumor progression, tumor type, and location of tumor (p < 0.05), and Helicobacter pylori infection with SALL4 expression (p = 0.036). There were also significant correlations between concomitant mRNA expression of SALL4 and LINC-ROR in tumors located at distal noncardiac, positive for H. pylori infection, tumors with invasion into the muscle layer of the stomach, and grade II tumor (p < 0.05).

CONCLUSION

The clinical results of the SALL4-LINC-ROR association propose a probable functional interaction between these markers in tumor maintenance and aggressiveness. Our study can help to understand one of the mechanisms involved in the progression of gastric cancer through the function of these regulators.

Functional and conformational impact of cancer-associated SF3B1 mutations depends on the position and the charge of amino acid substitution

The hotspot mutations of SF3B1, the most frequently mutated splicing gene in cancers, contribute to oncogenesis by corrupting the mRNA splicing. Further SF3B1 mutations have been reported in cancers but their consequences remain unclear. Here, we screened for SF3B1 mutations in the vicinity of the hotspot region in tumors. We then performed in-silico prediction of the functional outcome followed by in-cellulo modelling of different SF3B1 mutants. We show that cancer-associated SF3B1 mutations present varying functional consequences that are loosely predicted by the in-silico algorithms. Analysis of the tertiary structure of SF3B1 mutants revealed that the resulting splicing errors may be due to a conformational change in SF3B1 N-terminal region, which mediates binding with other splicing factors. Our study demonstrates a varying functional impact of SF3B1 mutations according to the mutated codon and the amino acid substitution, implying unequal pathogenic and prognostic potentials of SF3B1 mutations in cancers.

S-(+)-Pentedrone and R-(+)-methylone as the most oxidative and cytotoxic enantiomers to dopaminergic SH-SY5Y cells: Role of MRP1 and P-gp in cathinones enantioselectivity

Cathinone derivatives are the most representative group within new drugs market, which have been described as neurotoxic. Since cathinones, as pentedrone and methylone, are available as racemates, it is our aim to study the neuronal cytotoxicity induced by each enantiomer. Therefore, a dopaminergic SH-SY5Y cell line was used to evaluate the hypothesis of enantioselectivity of pentedrone and methylone enantiomers on cytotoxicity, oxidative stress, and membrane efflux transport (confirmed by in silico studies). Our study demonstrated enantioselectivity of these cathinones, being the S-(+)-pentedrone and R-(+)-methylone the most oxidative enantiomers and also the most cytotoxic, suggesting the oxidative stress as main cytotoxic mechanism, as previously described in in vitro studies. Additionally, the efflux transporter multidrug resistance associated protein 1 (MRP1) seems to play, together with GSH, a selective protective role against the cytotoxicity induced by R-(-)-pentedrone enantiomer. It was also observed an enantioselectivity in the binding to P-glycoprotein (P-gp), another efflux protein, being the R-(-)-pentedrone and S-(-)-methylone the most transported enantiomeric compounds. These results were confirmed, in silico, by docking studies, revealing that R-(-)-pentedrone is the enantiomer with highest affinity to MRP1 and S-(-)-methylone and R-(-)-pentedrone are the enantiomers with highest affinity to P-gp. In conclusion, our data demonstrated that pentedrone and methylone present enantioselectivity in their cytotoxicity, which seems to involve different oxidative reactivity as well as different affinity to the P-gp and MRP1 that together with GSH play a protective role.

Relation between glycosidic linkage, structure and dynamics of α- and β-glucans in water

In a molecular dynamics simulation study of several oligosaccharides comprising of the very basic building block of carbohydrate, the α- or β-d glucopyranose units, linked by any one of the 1-3/1-4 or 1-6 glycosidic linkages, we compare and contrast their structural and dynamical properties. Results indicate that the litheness of the oligosaccharide chain is noticeably controlled by the composition, anomeric nature and glycosidic linkage type of the units. In mixed β 1-4/1-3 d-glucopyranosides, as those found in oats and barley, the ratio of the β 1-4 and β 1-3 linked residues is crucial in determining the structural and dynamical attributes. Principal component analysis (PCA) using the internal coordinates of torsion angles subtended by glycosidic oxygen atoms and subsequent K-means clustering of the dynamical space spanned by PC1 to PC2 point to the dynamical and structural disparity in the various types of oligosaccharides studied. The properties simulated in this work are meant to provide a systematic yet comparative understanding of the importance of linkage and anomericity on the oligosaccharide chain properties and are in line with some experimental structural attributes.

Repurposing of FDA approved drugs and their validation against potential drug targets for Salmonella enterica through molecular dynamics simulation

Salmonella is a widely distributed pathogen causing infection of intestinal tract, typhoid, and paratyphoid fever. Number of drugs was developed against salmonella, but in the last few decades due to the emergence of drug resistant strains, most of these drugs became dormant. As a result Salmonellosis emerges as a trivial cause of human mortality worldwide; therefore, there is an urgent need for unexploited drug targets and drugs to treat Salmonellosis. As development of new drug molecules is very time consuming and costly, drug repurposing is in consideration as a better alternative. With the aim to identify a new drug molecule against the Salmonella through repurposing approach, we utilized 14 well reported druggable targets known to play a vital role in the life cycle of pathogens. These targets were used to screen DrugBank and got 53 FDA approved drugs against them. To find the interaction between considered target proteins and screened drugs, molecular docking was performed. Fourteen docked drug-target complexes with reasonable binding affinities were subjected to Molecular Dynamics Simulation (MDS) at 150 ns, using Amber18. At the end MMPBSA and MMGBSA calculations were performed for all stable complexes and finally, got 3 precise and favourable complexes, i.e. ArcB-Cefpiramide, MrcB-Cefoperazone, and PhoQ-Carindacillin. Rigorous structural and energetic analysis for these complexes validates the potential of drug molecules to act as therapeutic drugs against Salmonella enterica. With this study we hypothesize that the drugs Cefpiramide (DB00430), Cefoperazone (DB01329) and Carindacillin (DB09319) will be the good repurposed-drugs for the treatment of Salmonellosis.Communicated by Ramaswamy H. Sarma.

Structural Comparison of the SARS CoV 2 Spike Protein Relative to Other Human-Infecting Coronaviruses

Coronaviruses (CoV) are enveloped positive-stranded RNA viruses and, historically, there are seven known human-infecting CoVs with varying degrees of virulence. CoV attachment to the host is the first step of viral pathogenesis and mainly relies on the spike glycoprotein located on the viral surface. Among the human-infecting CoVs, only the infection of SARS CoV 2 (SARS2) among humans resulted to a pandemic which would suggest that the protein structural conformation of SARS2 spike protein is distinct as compared to other human-infecting CoVs. Surprisingly, the possible differences and similarities in the protein structural conformation between the various human-infecting CoV spike proteins have not been fully elucidated. In this study, we utilized a computational approach to generate models and analyze the seven human-infecting CoV spike proteins, namely: HCoV 229E, HCoV OC43, HCoV NL63, HCoV HKU1, SARS CoV, MERS CoV, and SARS2. Model quality assessment of all CoV models generated, structural superimposition of the whole protein model and selected S1 domains (S1-CTD and S1-NTD), and structural comparison based on RMSD values, Tm scores, and contact mapping were all performed. We found that the structural orientation of S1-CTD is a potential structural feature associated to both the CoV phylogenetic cluster and lineage. Moreover, we observed that spike models in the same phylogenetic cluster or lineage could potentially have similar protein structure. Additionally, we established that there are potentially three distinct S1-CTD orientation (Pattern I, Pattern II, Pattern III) among the human-infecting CoVs. Furthermore, we postulate that human-infecting CoVs in the same phylogenetic cluster may have similar S1-CTD and S1-NTD structural orientation. Taken together, we propose that the SARS2 spike S1-CTD follows a Pattern III orientation which has a higher degree of similarity with SARS1 and some degree of similarity with both OC43 and HKU1 which coincidentally are in the same phylogenetic cluster and lineage, whereas, the SARS2 spike S1-NTD has some degree of similarity among human-infecting CoVs that are either in the same phylogenetic cluster or lineage.

1,2,4-Triazolo[4,3-c]quinazolines: a bioisosterism-guided approach towards the development of novel PCAF inhibitors with potential anticancer activity

Targeting PCAF with small inhibitor molecules has emerged as a potential therapeutic strategy for the treatment of cancer.