Homology Modeling of Protein Targets with MODELLER

A Study on the Binding Mechanism and the Impact of Key Residue Mutations between SND1 and MTDH Peptide through Molecular Dynamics Simulations

Metastasis of breast cancer is the main cause of death for patients with breast cancer. The interaction between metadherin (MTDH) and staphylococcal nuclease domain 1 (SND1) plays a pivotal role in promoting breast cancer development. However, the binding details between MTDH and SND1 remain unclear. In this study, we employed all-atom molecular dynamics simulations (MDs) and conducted binding energy calculations to investigate the binding details and the impact of key residue mutations on binding. The mutations in key residues have not significantly affected the overall stability of the structure and the fluctuation of residues near the binding site; they have exerted a substantial impact on the binding of SND1 and MTDH peptide. The electrostatic interactions and van der Waals interactions play an important role in the binding of SND1 and the MTDH peptide. The mutations in the key residues have a significant impact on electrostatic and van der Waals interactions, resulting in weakened binding. The energy contributions of key residues mainly come from the electrostatic energy and van der Waals interactions of the side chain. In addition, the key residues form an intricate and stable network of hydrogen bonds and salt-bridge interactions with the MTDH peptide. The mutations in key residues have directly disrupt the interactions formed between SND1 and MTDH peptide, consequently leading to changes in the binding mode of the MTDH peptide. These analyses unveil the detailed atomic-level interaction mechanism between SND1 and the MTDH peptide, providing a molecular foundation for the development of antibreast cancer drugs.

Variations of VEGFR2 Chemical Space: Stimulator and Inhibitory Peptides

The kinase pathway plays a crucial role in blood vessel function. Particular attention is paid to VEGFR type 2 angiogenesis and vascular morphogenesis as the tyrosine kinase pathway is preferentially activated. In silico studies were performed on several peptides that affect VEGFR2 in both stimulating and inhibitory ways. This investigation aims to examine the molecular properties of VEGFR2, a molecule primarily involved in the processes of vasculogenesis and angiogenesis. These relationships were defined by the interactions between Vascular Endothelial Growth Factor receptor 2 (VEGFR2) and the structural features of the systems. The chemical space of the inhibitory peptides and stimulators was described using topological and energetic properties. Furthermore, chimeric models of stimulating and inhibitory proteins (for VEGFR2) were computed using the protein system structures. The interaction between the chimeric proteins and VEGFR was computed. The chemical space was further characterized using complex manifolds and high-dimensional data visualization. The results show that a slightly similar chemical area is shared by VEGFR2 and stimulating and inhibitory proteins. On the other hand, the stimulator peptides and the inhibitors have distinct chemical spaces.

Exploring binding modes of the selected inhibitors to SND1 by all-atom molecular dynamics simulations

Breast cancer is the leading cause of cancer-related deaths in women. Previous studies have indicated that disrupting the interaction between Metadherin (MTDH) and Staphylococcal nuclease domain containing 1 (SND1) can inhibit breast cancer development. Understanding the binding mode of small molecule inhibitors with SND1 is of great significance for designing drugs targeting the MTDH-SND1 complex. In this study, we conducted all-atom molecular dynamics (MD) simulations in solution and performed binding energy calculations to gain insights into the binding mechanism of small molecules to SND1. The binding site of SND1 for small molecules is relatively rigid, and the binding of the small molecule and the mutation of key residues have little effect on the conformation of the binding site. SND1 binds more tightly to C26-A6 than to C26-A2, as C26-A2 undergoes a 180° directional change during the simulation process. The key residue mutations have a direct effect on the position and orientation of small molecule in the binding site. The key residues make primary contributions to the binding energy through van der Waals interaction and nonpolar solvation energy, although the contribution from nonpolar solvation is relatively minor. The key residue mutations also affect the formation of hydrogen bonds and ultimately the stability of the small molecule-SND1 complex.Communicated by Ramaswamy H. Sarma.

Bioinformatics approach for structure modeling, vaccine design, and molecular docking of Brucella candidate proteins BvrR, OMP25, and OMP31

Brucellosis is a zoonotic disease with significant economic and healthcare costs. Despite the eradication efforts, the disease persists. Vaccines prevent disease in animals while antibiotics cure humans with limitations. This study aims to design vaccines and drugs for brucellosis in animals and humans, using protein modeling, epitope prediction, and molecular docking of the target proteins (BvrR, OMP25, and OMP31). Tertiary structure models of three target proteins were constructed and assessed using RMSD, TM-score, C-score, Z-score, and ERRAT. The best models selected from AlphaFold and I-TASSER due to their superior performance according to CASP 12 - CASP 15 were chosen for further analysis. The motif analysis of best models using MotifFinder revealed two, five, and five protein binding motifs, however, the Motif Scan identified seven, six, and eight Post-Translational Modification sites (PTMs) in the BvrR, OMP25, and OMP31 proteins, respectively. Dominant B cell epitopes were predicted at (44-63, 85-93, 126-137, 193-205, and 208-237), (26-46, 52-71, 98-114, 142-155, and 183-200), and (29-45, 58-82, 119-142, 177-198, and 222-251) for the three target proteins. Additionally, cytotoxic T lymphocyte epitopes were detected at (173-181, 189-197, and 202-210), (61-69, 91-99, 159-167, and 181-189), and (3-11, 24-32, 167-175, and 216-224), while T helper lymphocyte epitopes were displayed at (39-53, 57-65, 150-158, 163-171), (79-87, 95-108, 115-123, 128-142, and 189-197), and (39-47, 109-123, 216-224, and 245-253), for the respective target protein. Furthermore, structure-based virtual screening of the ZINC and DrugBank databases using the docking MOE program was followed by ADMET analysis. The best five compounds of the ZINC database revealed docking scores ranged from (- 16.8744 to - 15.1922), (- 16.0424 to - 14.1645), and (- 14.7566 to - 13.3222) for the BvrR, OMP25, and OMP31, respectively. These compounds had good ADMET parameters and no cytotoxicity, while DrugBank compounds didn't meet Lipinski's rule criteria. Therefore, the five selected compounds from the ZINC20 databases may fulfill the pharmacokinetics and could be considered lead molecules for potentially inhibiting Brucella's proteins.

Revealing the binding mechanism of BACE1 inhibitors through molecular dynamics simulations

Alzheimer's disease is a debilitating neurodegenerative disorder, and the Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE1) is a key therapeutic target in its treatment. This study employs molecular dynamics simulations and binding energy analysis to investigate the binding interactions between BACE1 and four selected small molecules: CNP520, D9W, NB641, and NB360. The binding model analysis indicates that the binding of BACE1 with four molecules are stable, except the loop regions show significant fluctuation. The binding free energy analyses reveal that NB360 exhibits the highest binding affinity with BACE1, surpassing other molecules (CNP520, D9W, and NB641). Detailed energy component assessments highlight the critical roles of electrostatic interactions and van der Waals forces in the binding process. Furthermore, residue contribution analysis identifies key amino acids influencing the binding process across all systems. Hydrogen bond analysis reveals a limited number of bonds between BACE1 and each small molecule, highlighting the importance of structural modifications to enable more stable hydrogen bonds. This research provides valuable insights into the molecular mechanisms of potential Alzheimer's disease therapeutics, guiding the way for improved drug design and the development of effective treatments targeting BACE1.Communicated by Ramaswamy H. Sarma.

Structure-based drug discovery to identify SARS-CoV2 spike protein-ACE2 interaction inhibitors

After the emergence of the COVID-19 pandemic in late 2019, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has undergone a dynamic evolution driven by the acquisition of genetic modifications, resulting in several variants that are further classified as variants of interest (VOIs), variants under monitoring (VUM) and variants of concern (VOC) by World Health Organization (WHO). Currently, there are five SARS-CoV-2 VOCs (Alpha, Beta, Delta, Gamma and Omicron), two VOIs (Lambda and Mu) and several other VOIs that have been reported globally. In this study, we report a natural compound, Curcumin, as the potential inhibitor to the interactions between receptor binding domain (RBD(S1)) and human angiotensin-converting enzyme 2 (hACE2) domains and showcased its inhibitory potential for the Delta and Omicron variants through a computational approach by implementing state of the art methods. The study for the first time revealed a higher efficiency of Curcumin, especially for hindering the interaction between RBD(S1) and hACE-2 domains of Delta and Omicron variants as compared to other lead compounds. We investigated that the mutations in the RBD(S1) of VOC especially Delta and Omicron variants affect its structure compared to that of the wild type and other variants and therefore altered its binding to the hACE2 receptor. Molecular docking and molecular dynamics (MD) simulation analyses substantially supported the findings in terms of the stability of the docked complexes. This study offers compelling evidence, warranting a more in-depth exploration into the impact of these alterations on the binding of identified drug molecules with the Spike protein. Further investigation into their potential therapeutic effects in vivo is highly recommended.Communicated by Ramaswamy H. Sarma.

Role of environmental specificity in CASP results

BACKGROUND

Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Prediction) competition. However, the question of the mechanism behind the protein folding process itself remains unanswered. Correctly predicting the structure also does not solve the problem of, for example, amyloid proteins, where a polypeptide chain with an unaltered sequence adopts a different 3D structure.

RESULTS

This work was an attempt at explaining the structural variation by considering the contribution of the environment to protein structuring. The application of the fuzzy oil drop (FOD) model to assess the validity of the selected models provided in the CASP13, CASP14 and CASP15 projects reveals the need for an environmental factor to determine the 3D structure of proteins. Consideration of the external force field in the form of polar water (Fuzzy Oil Drop) and a version modified by the presence of the hydrophobic compounds, FOD-M (FOD-Modified) reveals that the protein folding process is environmentally dependent. An analysis of selected models from the CASP competitions indicates the need for structure prediction as dependent on the consideration of the protein folding environment.

CONCLUSIONS

The conditions governed by the environment direct the protein folding process occurring in a certain environment. Therefore, the variation of the external force field should be taken into account in the models used in protein structure prediction.

Computational approaches for molecular characterization and structure-based functional elucidation of a hypothetical protein from Mycobacterium tuberculosis

Adaptation of infections and hosts has resulted in several metabolic mechanisms adopted by intracellular pathogens to combat the defense responses and the lack of fuel during infection. Human tuberculosis caused by Mycobacterium tuberculosis (MTB) is the world's first cause of mortality tied to a single disease. This study aims to characterize and anticipate potential antigen characteristics for promising vaccine candidates for the hypothetical protein of MTB through computational strategies. The protein is associated with the catalyzation of dithiol oxidation and/or disulfide reduction because of the protein's anticipated disulfide oxidoreductase properties. This investigation analyzed the protein's physicochemical characteristics, protein-protein interactions, subcellular locations, anticipated active sites, secondary and tertiary structures, allergenicity, antigenicity, and toxicity properties. The protein has significant active amino acid residues with no allergenicity, elevated antigenicity, and no toxicity.

Structural and functional characterization of RNA dependent RNA polymerase of Macrobrachium rosenbergii nodavirus (MnRdRp)

Macrobrachium rosenbergii is a highly valued farmed freshwater species and its production has been affected globally by white tail disease caused by M. rosenbergii nodavirus (MrNV). MrNV is a single stranded positive sense RNA virus encoding RNA-dependent RNA polymerase (RdRp) for genome replication. Due to its essentiality for pathogenesis, it is an important drug target. The domain prediction of the complete sequence revealed the presence of two enzymatic regions namely methyl transferase and RdRp separated by transmembrane region. The predicted three-dimensional (3D) structure of MnRdRp using AlphaFold 2 shows that the structure is composed of three major sub-domains common for other polymerases namely fingers, palm and thumb. Structural similarity search revealed its similarity with other flaviviridea members especially with BVDV RdRp (BvdvRdRp). The structure of fingers and palm sub-domains is more conserved than the thumb sub-domain. A small α-helix named 'priming helix' having conserve Tyr was identified at position 829-833 with a potential role in de novo initiation. Analysis of electrostatic potential revealed that nucleotide and template channels are electropositive. Metal binding residues were identified as Asp599, Asp704 and Asp705. The α and β phosphates of incoming nucleotide interact with two Mn2+, Arg455 and Arg537. For recognition of 2'-OH of incoming rNTP, Asp604, Ser661 and Asn670 were identified which can form H-bond network with 2'-OH group. Docking study revealed that Dasabuvir can potentially inhibit MnRdRp. The study concluded that the overall structure and function of MnRdRp are similar to Flaviviridae polymerases and their inhibitors can work against this enzyme.Communicated by Ramaswamy H. Sarma.

Widespread amyloidogenicity potential of multiple myeloma patient-derived immunoglobulin light chains

BACKGROUND

In a range of human disorders such as multiple myeloma (MM), immunoglobulin light chains (IgLCs) can be produced at very high concentrations. This can lead to pathological aggregation and deposition of IgLCs in different tissues, which in turn leads to severe and potentially fatal organ damage. However, IgLCs can also be highly soluble and non-toxic. It is generally thought that the cause for this differential solubility behaviour is solely found within the IgLC amino acid sequences, and a variety of individual sequence-related biophysical properties (e.g. thermal stability, dimerisation) have been proposed in different studies as major determinants of the aggregation in vivo. Here, we investigate biophysical properties underlying IgLC amyloidogenicity.

RESULTS

We introduce a novel and systematic workflow, Thermodynamic and Aggregation Fingerprinting (ThAgg-Fip), for detailed biophysical characterisation, and apply it to nine different MM patient-derived IgLCs. Our set of pathogenic IgLCs spans the entire range of values in those parameters previously proposed to define in vivo amyloidogenicity; however, none actually forms amyloid in patients. Even more surprisingly, we were able to show that all our IgLCs are able to form amyloid fibrils readily in vitro under the influence of proteolytic cleavage by co-purified cathepsins.

CONCLUSIONS

We show that (I) in vivo aggregation behaviour is unlikely to be mechanistically linked to any single biophysical or biochemical parameter and (II) amyloidogenic potential is widespread in IgLC sequences and is not confined to those sequences that form amyloid fibrils in patients. Our findings suggest that protein sequence, environmental conditions and presence and action of proteases all determine the ability of light chains to form amyloid fibrils in patients.

A universal stress protein upregulated by hypoxia has a role in Burkholderia cenocepacia intramacrophage survival: Implications for chronic infection in cystic fibrosis

Universal stress proteins (USPs) are ubiquitously expressed in bacteria, archaea, and eukaryotes and play a lead role in adaptation to environmental conditions. They enable adaptation of bacterial pathogens to the conditions encountered in the human niche, including hypoxia, oxidative stress, osmotic stress, nutrient deficiency, or acid stress, thereby facilitating colonization. We previously reported that all six USP proteins encoded within a low-oxygen activated (lxa) locus in Burkholderia cenocepacia showed increased abundance during chronic colonization of the cystic fibrosis (CF) lung. However, the role of USPs in chronic cystic fibrosis infection is not well understood. Structural modeling identified surface arginines on one lxa-encoded USP, USP76, which suggested it mediated interactions with heparan sulfate. Using mutants derived from the B. cenocepacia strain, K56-2, we show that USP76 is involved in host cell attachment. Pretreatment of lung epithelial cells with heparanase reduced the binding of the wild-type and complement strains but not the Δusp76 mutant strain, indicating that USP76 is directly or indirectly involved in receptor recognition on the surface of epithelial cells. We also show that USP76 is required for growth and survival in many conditions associated with the CF lung, including acidic conditions and oxidative stress. Moreover, USP76 also has a role in survival in macrophages isolated from people with CF. Overall, while further elucidation of the exact mechanism(s) is required, we can conclude that USP76, which is upregulated during chronic infection, is involved in bacterial survival within CF macrophages, a hallmark of Burkholderia infection.

Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: Implications for future surveillance programmes

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the SARS-CoV-2 spike protein can bind to a wide range of vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures

Changes in protein sequence can have dramatic effects on how proteins fold, their stability and dynamics. Over the last 20 years, pioneering methods have been developed to try to estimate the effects of missense mutations on protein stability, leveraging growing availability of protein 3D structures. These, however, have been developed and validated using experimentally derived structures and biophysical measurements. A large proportion of protein structures remain to be experimentally elucidated and, while many studies have based their conclusions on predictions made using homology models, there has been no systematic evaluation of the reliability of these tools in the absence of experimental structural data. We have, therefore, systematically investigated the performance and robustness of ten widely used structural methods when presented with homology models built using templates at a range of sequence identity levels (from 15% to 95%) and contrasted performance with sequence-based tools, as a baseline. We found there is indeed performance deterioration on homology models built using templates with sequence identity below 40%, where sequence-based tools might become preferable. This was most marked for mutations in solvent exposed residues and stabilizing mutations. As structure prediction tools improve, the reliability of these predictors is expected to follow, however we strongly suggest that these factors should be taken into consideration when interpreting results from structure-based predictors of mutation effects on protein stability.

P2X3-selective mechanism of Gefapixant, a drug candidate for the treatment of refractory chronic cough

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The mechanism by which Gefapixant/AF-219 selectively acts on the P2X3 receptor is unclear.

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The negative allosteric site of AF-219 at P2X3 is also a potent allosteric site for other P2X subtypes.

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The selectivity of AF-219 for P2X3 is determined by the accessibility of binding site and the internal shape of this pocket.

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The finding will provide new perspectives for drug design against P2X3-mediated diseases such as RCC.

Gefapixant/AF-219, a selective inhibitor of the P2X3 receptor, is the first new drug other than dextromethorphan to be approved for the treatment of refractory chronic cough (RCC) in nearly 60 years. To date, seven P2X subtypes (P2X1-7) activated by extracellular ATP have been cloned, and subtype selectivity of P2X inhibitors is a prerequisite for reducing side effects. We previously identified the site and mechanism of action of Gefapixant/AF-219 on the P2X3 receptor, which occupies a pocket consisting of the left flipper (LF) and lower body (LB) domains. However, the mechanism by which AF-219 selectively acts on the P2X3 receptor is unknown. Here, we combined mutagenesis, chimera construction, molecular simulations, covalent occupation and chemical synthesis, and find that the negative allosteric site of AF-219 at P2X3 is also present in other P2X subtypes, at least for P2X1, P2X2 and P2X4. By constructing each chimera of AF-219 sensitive P2X3 and insensitive P2X2 subtypes, the insensitive P2X2 subtype was made to acquire the inhibitory properties of AF-219 and AF-353, an analog of AF-219 with higher affinity. Our results suggest that the selectivity of AF-219/AF-353 for P2X3 over the other P2X subtypes is determined by a combination of the accessibility of P2X3 binding site and the internal shape of this pocket, a finding that could provide new perspectives for drug design against P2X3-mediated diseases such as RCC, idiopathic pulmonary fibrosis, hypertension and overactive bladder disorder.

Protein with negative surface charge distribution, Bnr1, shows characteristics of a DNA-mimic protein and may be involved in the adaptation of Burkholderia cenocepacia

Adaptation of opportunistic pathogens to their host environment requires reprogramming of a vast array of genes to facilitate survival in the host. Burkholderia cenocepacia, a Gram-negative bacterium with a large genome of ∼8 Mb that colonizes environmental niches, is exquisitely adaptable to the hypoxic environment of the cystic fibrosis lung and survives in macrophages. We previously identified an immunoreactive acidic protein encoded on replicon 3, BCAS0292. Deletion of the BCAS0292 gene significantly altered the abundance of 979 proteins by 1.5-fold or more; 19 proteins became undetectable while 545 proteins showed ≥1.5-fold reduced abundance, suggesting the BCAS0292 protein is a global regulator. Moreover, the ∆BCAS0292 mutant showed a range of pleiotropic effects: virulence and host-cell attachment were reduced, antibiotic susceptibility was altered, and biofilm formation enhanced. Its growth and survival were impaired in 6% oxygen. In silico prediction of its three-dimensional structure revealed BCAS0292 presents a dimeric β-structure with a negative surface charge. The ΔBCAS0292 mutant displayed altered DNA supercoiling, implicated in global regulation of gene expression. Three proteins were identified in pull-downs with FLAG-tagged BCAS0292, including the Histone H1-like protein, HctB, which is recognized as a global transcriptional regulator. We propose that BCAS0292 protein, which we have named Burkholderia negatively surface-charged regulatory protein 1 (Bnr1), acts as a DNA-mimic and binds to DNA-binding proteins, altering DNA topology and regulating the expression of multiple genes, thereby enabling the adaptation of B. cenocepacia to highly diverse environments.

Simulation studies, 3D QSAR and molecular docking on a point mutation of protein kinase B with flavonoids targeting ovarian Cancer

BACKGROUND

Ovarian cancer is the world's dreaded disease and its prevalence is expanding globally. The study of integrated molecular networks is crucial for the basic mechanism of cancer cells and their progression. During the present investigation, we have examined different flavonoids that target protein kinases B (AKT1) protein which exerts their anticancer efficiency intriguing the role in cross-talk cell signalling, by metabolic processes through in-silico approaches.

METHOD

Molecular dynamics simulation (MDS) was performed to analyze and evaluate the stability of the complexes under physiological conditions and the results were congruent with molecular docking. This investigation revealed the effect of a point mutation (W80R), considered based on their frequency of occurrence, with AKT1 protein.

RESULTS

The ligand with high docking scores and favourable behaviour on dynamic simulations are proposed as potential W80R inhibitors. A virtual screening analysis was performed with 12,000 flavonoids satisfying Lipinski's rule of five according to which drug-likeness is predicted based on its pharmacological and biological properties to be active and taken orally. The pharmacokinetic ADME (adsorption, digestion, metabolism, and excretion) studies featured drug-likeness. Subsequently, a statistically significant 3D-QSAR model of high correlation coefficient (R2) with 0.822 and cross-validation coefficient (Q2) with 0.6132 at 4 component PLS (partial least square) were used to verify the accuracy of the models. Taxifolin holds good interactions with the binding domain of W80R, highest Glide score of - 9.63 kcal/mol with OH of GLU234 and H bond ASP274 and LEU156 amino acid residues and one pi-cation interaction and one hydrophobic bond with LYS276.

CONCLUSION

Natural compounds have always been a richest source of active compounds with a wide variety of structures, therefore, these compounds showed a special inspiration for medical chemists. The present study has aimed molecular docking and molecular dynamics simulation studies on taxifolin targeting W80R mutant protein of protein kinase B/serine- threonine kinase/AKT1 (EC:2.7.11.1) protein of ovarian cancer for designing therapeutic intervention. The expected result supported the molecular cause in a mutant form which resulted in a gain of ovarian cancer. Here we discussed validations computationally and yet experimental evaluation or in vivo studies are endorsed for further study. Several of these compounds should become the next marvels for early detection of ovarian cancer.

Excavating the functionally crucial active-site residues of the DXS protein of Bacillus subtilis by exploring its closest homologues

Background

To achieve a high yield of terpenoid-based therapeutics, 1-deoxy-d-xylulose-5-phosphate (DXP) pathway has been significantly exploited for the production of downstream enzymes. The DXP synthase (DXS) enzyme, the initiator of this pathway, is pivotal for the convergence of carbon flux, and is computationally studied well for the industrially utilized generally regarded as safe (GRAS) bacterium Bacillus subtilis to decode its vital regions for aiding the construction of a functionally improved mutant library.

Results

For the 546 sequence dataset of DXS sequences, a representative set of 108 sequences is created, and it shows a significant evolutionary divergence across different species clubbed into 37 clades, whereas three clades are observed for the 76 sequence dataset of Bacillus subtilis. The DXS enzyme, sharing a statistically significant homology to transketolase, is shown to be evolutionarily too distant. By the mutual information-based co-evolutionary network and hotspot analysis, the most crucial loci within the active site are deciphered. The 650-residue representative structure displays a complete conservation of 114 loci, and only two co-evolving residues ASP154 and ILE371 are found to be the conserved ones. Lastly, P318D is predicted to be the top-ranked mutation causing the increase in the thermodynamic stability of 6OUW.

Conclusion

The study excavates the vital functional, phylogenetic, and conserved residues across the active site of the DXS protein, the key rate-limiting controller of the entire pathway. It would aid to computationally understand the evolutionary landscape of this industrially useful enzyme and would allow us to widen its substrate repertoire to increase the enzymatic yield of unnatural molecules for in vivo and in vitro applications.

In silico structural homology modelling of EST073 motif coding protein of tea Camellia sinensis (L)

Background

Tea (Camellia sinensis (L). O. Kuntze) is known as the oldest, mild stimulating caffeine containing non-alcoholic beverage. One of the major threats in south Asian tea industry is the blister blight leaf disease (BB), caused by the fungus Exobasidium vexans Masse. SSR DNA marker EST SSR 073 is used as a molecular marker to tag blister blight disease resistance trait of tea. The amino acid sequences were derived from cDNA sequences related to EST SSR 073 of BB susceptible (TRI 2023) and BB resistant (TRI 2043) cultivars. An attempt has been made to understand the structural characteristics and variations of EST SSR 073 locus that may reveal the factors influencing the BB resistance of tea with multiple bioinformatics tools such as ORF finder, ExPasy ProtParam tools, modeler V 9.17, Rampage server, UCSF-Chimera, and HADDOCK docking server.

Results

The primary, secondary, and tertiary structures of EST SSR 073 coding protein were analyzed using the amino acid sequences of both BB resistant TRI 2043 and BB susceptible TRI 2023 tea cultivars. The coding amino acid sequences of both the cultivars were homologous to photosystem I subunit protein (PsaD I) of Pisum sativum. The predicted 3D structures of proteins were validated and considered as an acceptable overall stereochemical quality. The BB resistant protein showed CT repeat extension and did not involve in topology of the PsaD I subunit. The C terminal truncation of BB resistance caused the formation of hydrogen bonds interacting with PsaD I and other subunits of photosystem I in the modeled three-dimensional protein structure.

Conclusions

Camellia sinensis EST 073 SSR motif coding protein was identified as the PsaD I subunit of photosystem I. The exact mechanism of PsaD I conferring the resistance for blister blight in tea needs to be further investigated.

High throughput virtual screening reveals SARS-CoV-2 multi-target binding natural compounds to lead instant therapy for COVID-19 treatment

The present-day world is severely suffering from the recently emerged SARS-CoV-2. The lack of prescribed drugs for the deadly virus has stressed the likely need to identify novel inhibitors to alleviate and stop the pandemic. In the present high throughput virtual screening study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), and ADME properties to screen natural compounds. It has been documented that many natural compounds display antiviral activities, including anti–SARS-CoV effect. The present study deals with compounds of Natural Product Activity and Species Source (NPASS) database with known biological activity that probably impedes the activity of six essential enzymes of the virus. Promising drug-like compounds were identified, demonstrating better docking score and binding energy for each druggable targets. After an extensive screening analysis, three novel multi-target natural compounds were predicted to subdue the activity of three/more major drug targets simultaneously. Concerning the utility of natural compounds in the formulation of many therapies, we propose these compounds as excellent lead candidates for the development of therapeutic drugs against SARS-CoV-2.

Small design from big alignment: engineering proteins with multiple sequence alignment as the starting point

Multiple sequence alignment (MSA) is a fundamental way to gain information that cannot be obtained from the analysis of any individual sequence included in the alignment. It provides ways to investigate the relationship between sequence and function from a perspective of evolution. Thus, the MSA of proteins can be employed as a reference for protein engineering. In this paper, we reviewed the recent advances to highlight how protein engineering was benefited from the MSA of proteins. These methods include (1) engineering the thermostability or solubility of proteins by making it closer to the consensus sequence of the alignment through introducing site mutations; (2) structure-based engineering proteins with comparative modeling; (3) creating paleoenzymes featured with high thermostability and promiscuity by constructing the ancestral sequences derived from multiple sequence alignment; and (4) incorporating site-mutations targeting the evolutionarily coupled sites identified from multiple sequence alignment.

Repurposing Modular Polyketide Synthases and Non-ribosomal Peptide Synthetases for Novel Chemical Biosynthesis

In nature, various enzymes govern diverse biochemical reactions through their specific three-dimensional structures, which have been harnessed to produce many useful bioactive compounds including clinical agents and commodity chemicals. Polyketide synthases (PKSs) and non-ribosomal peptide synthetases (NRPSs) are particularly unique multifunctional enzymes that display modular organization. Individual modules incorporate their own specific substrates and collaborate to assemble complex polyketides or non-ribosomal polypeptides in a linear fashion. Due to the modular properties of PKSs and NRPSs, they have been attractive rational engineering targets for novel chemical production through the predictable modification of each moiety of the complex chemical through engineering of the cognate module. Thus, individual reactions of each module could be separated as a retro-biosynthetic biopart and repurposed to new biosynthetic pathways for the production of biofuels or commodity chemicals. Despite these potentials, repurposing attempts have often failed owing to impaired catalytic activity or the production of unintended products due to incompatible protein–protein interactions between the modules and structural perturbation of the enzyme. Recent advances in the structural, computational, and synthetic tools provide more opportunities for successful repurposing. In this review, we focused on the representative strategies and examples for the repurposing of modular PKSs and NRPSs, along with their advantages and current limitations. Thereafter, synthetic biology tools and perspectives were suggested for potential further advancement, including the rational and large-scale high-throughput approaches. Ultimately, the potential diverse reactions from modular PKSs and NRPSs would be leveraged to expand the reservoir of useful chemicals.