In structural biology, similarity analysis of protein structure is a crucial step in studying the relationship between proteins. Despite the considerable number of techniques that have been explored within the past two decades, the development of new alternative methods is still an active research area due to the need for high performance tools.
The structural comparison of proteins is a vital step in structural biology that is used to predict and analyse a new unknown protein function. Although a number of different techniques have been explored, the study to develop new alternative methods is still an active research area. The present paper introduces a text modelling-based technique for the structural comparison of proteins. The method models the secondary and tertiary structure of proteins in two linear sequences and then applies them to the comparison of two structures. The technique used for pairwise comparison of the sequences has been adopted from computational linguistics and its well-known techniques for analysing and quantifying textual sequences. To this end, an n-gram modelling technique is used to capture regularities between sequences, and then, the cross-entropy concept is employed to measure their similarities. Several experiments are conducted to evaluate the performance of the method and compare it with other commonly used programs. The assessments for information retrieval evaluation demonstrate that the technique has a high running speed, which is similar to other linear encoding methods, such as 3D-BLAST, SARST, and TS-AMIR, whereas its accuracy is comparable to CE and TM-align, which are high accuracy comparison tools. Accordingly, the results demonstrate that the algorithm has high efficiency compared with other state-of-the-art methods.
A hidden Markov model (HMM) has been utilized to predict and generate artificial secretory signal peptide sequences. The strength of signal peptides of proteins from different subcellular locations via Lactococcus lactis bacteria correlated with their HMM bit scores in the model. The results show that the HMM bit score +12 are determined as the threshold for discriminating secreteory signal sequences from the others. The model is used to generate artificial signal peptides with different bit scores for secretory proteins. The signal peptide with the maximum bit score strongly directs proteins secretion.
Psychrophiles are cold-living microorganisms synthesizing enzymes that are permanently active at almost near-zero temperatures. Psychrozymes are supposed to be structurally more flexible than their homologous proteins. This structural flexibility enables these proteins to undergo conformational changes during catalysis and improve catalytic efficiency at low temperatures. The outstanding characteristics of the psychrophilic enzymes have attracted the attention of the scientific community to utilize them in a wide variety of industrial and pharmaceutical applications. In this review, we first highlight the current knowledge of the cold-adaptation mechanisms of the psychrophiles. In the sequel, we describe the potential applications of the enzymes in different biotechnological processes specifically, in the production of industrial and pharmaceutical products. KEY POINTS: • Methods that organisms have evolved to survive and proliferate at cold environments. • The economic benefits due to their high activity at low and moderate temperatures. • Applications of the psychrophiles in biotechnological and pharmaceutical industry.
Dehalogenases are of high interest due to their potential applications in bioremediation and in synthesis of various industrial products. DehL is an L-2-haloacid dehalogenase (EC 18.104.22.168) that catalyses the cleavage of halide ion from L-2-halocarboxylic acid to produce D-2-hydroxycarboxylic acid. Although DehL utilises the same substrates as the other L-2-haloacid dehalogenases, its deduced amino acid sequence is substantially different (<25%) from those of the rest L-2-haloacid dehalogenases. To date, the 3D structure of DehL is not available. This limits the detailed understanding of the enzyme's reaction mechanism. The present work predicted the first homology-based model of DehL and defined its active site. The monomeric unit of the DehL constitutes α/β structure that is organised into two distinct structural domains: main and subdomains. Despite the sequence disparity between the DehL and other L-2-haloacid dehalogenases, its structural model share similar fold as the experimentally solved L-DEX and DehlB structures. The findings of the present work will play a crucial role in elucidating the molecular details of the DehL functional mechanism.
Congenital myopathy is a broad category of muscular diseases with symptoms appearing at the time of birth. One type of congenital myopathy is Congenital Fiber Type Disproportion (CFTD), a severely debilitating disease. The G48D and G48C mutations in the D-loop and the actin-myosin interface are the two causes of CFTD. These mutations have been shown to significantly affect the structure and function of muscle fibers. To the author's knowledge, the effects of these mutations have not yet been studied. In this work, the power stroke structure of the head domain of myosin and the wild and mutated types of actin were modeled. Then, a MD simulation was run for the modeled structures to study the effects of these mutations on the structure, function, and molecular dynamics of actin. The wild and mutated actins docked with myosin showed differences in hydrogen bonding patterns, free binding energies, and hydrogen bond occupation frequencies. The G48D and G48C mutations significantly impacted the conformation of D-loops because of their larger size compared to Glycine and their ability to interfere with the polarity or hydrophobicity of this neutralized and hydrophobic loop. Therefore, the mutated loops were unable to fit properly into the hydrophobic groove of the adjacent G-actin. The abnormal structure of D-loops seems to result in the abnormal assembly of F-actins, giving rise to the symptoms of CFTD. It was also noted that G48C and G48D did not form hydrogen bonds with myosin in the residue 48 location. Nevertheless, in this case, muscles are unable to contract properly due to muscle atrophy.
Worldwide, breast cancer is the leading type of cancer among women. Overexpression of various prognostic indicators, including nuclear receptors, is linked to breast cancer features. To date, no effective drug has been discovered to block the proliferation of breast cancer cells. This study has been designed to discover target-based small molecular-like natural drug candidates that have anti-cancer potential without causing any serious side effects. A comprehensive substrate-based drug design was carried out to discover the potential plant compounds against the target breast cancer biomarkers including phytochemicals screening, active site identification, molecular docking, pharmacokinetic (PK) properties prediction, toxicity prediction, and molecular dynamics (MD) simulation approaches. Twenty plant compounds extracted from the rambutan (Nephelium lappaceum) were obtained from PubChem Database; and screened against the breast cancer biomarkers including estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR). The best docking interaction was chosen based on the higher binding affinity. Analyzing the pharmacokinetic properties and toxicity prediction results indicated that the fifteen selected plant compounds have good potency without toxicity and are safe for humans. Four phytochemicals with a higher binding affinity were chosen for each breast cancer biomarker to study their stability in interaction with the target proteins using MD simulation. Among the above compounds, Ellagic acid showed the high binding affinity against all three breast cancer biomarkers.Communicated by Ramaswamy H. Sarma.
Here, we present a novel psychrophilic β-glucanase from Glaciozyma antarctica PI12 yeast that has been structurally modeled and analyzed in detail. To our knowledge, this is the first attempt to model a psychrophilic laminarinase from yeast. Because of the low sequence identity (<40%), a threading method was applied to predict a 3D structure of the enzyme using the MODELLER9v12 program. The results of a comparative study using other mesophilic, thermophilic, and hyperthermophilic laminarinases indicated several amino acid substitutions on the surface of psychrophilic laminarinase that totally increased the flexibility of its structure for efficient catalytic reactions at low temperatures. Whereas several structural factors in the overall structure can explain the weak thermal stability, this research suggests that the psychrophilic adaptation and catalytic activity at low temperatures were achieved through existence of longer loops and shorter or broken helices and strands, an increase in the number of aromatic and hydrophobic residues, a reduction in the number of hydrogen bonds and salt bridges, a higher total solvent accessible surface area, and an increase in the exposure of the hydrophobic side chains to the solvent. The results of comparative molecular dynamics simulation and principal component analysis confirmed the above strategies adopted by psychrophilic laminarinase to increase its catalytic efficiency and structural flexibility to be active at cold temperature.
The structure of a novel psychrophilic β-mannanase enzyme from Glaciozyma antarctica PI12 yeast has been modelled and analysed in detail. To our knowledge, this is the first attempt to model a psychrophilic β-mannanase from yeast. To this end, a 3D structure of the enzyme was first predicted using a threading method because of the low sequence identity (<30%) using MODELLER9v12 and simulated using GROMACS at varying low temperatures for structure refinement. Comparisons with mesophilic and thermophilic mannanases revealed that the psychrophilic mannanase contains longer loops and shorter helices, increases in the number of aromatic and hydrophobic residues, reductions in the number of hydrogen bonds and salt bridges and numerous amino acid substitutions on the surface that increased the flexibility and its efficiency for catalytic reactions at low temperatures.
We report a detailed structural analysis of the psychrophilic exo-β-1,3-glucanase (GaExg55) from Glaciozyma antarctica PI12. This study elucidates the structural basis of exo-1,3-β-1,3-glucanase from this psychrophilic yeast. The structural prediction of GaExg55 remains a challenge because of its low sequence identity (37 %). A 3D model was constructed for GaExg55. Threading approach was employed to determine a suitable template and generate optimal target-template alignment for establishing the model using MODELLER9v15. The primary sequence analysis of GaExg55 with other mesophilic exo-1,3-β-glucanases indicated that an increased flexibility conferred to the enzyme by a set of amino acids substitutions in the surface and loop regions of GaExg55, thereby facilitating its structure to cold adaptation. A comparison of GaExg55 with other mesophilic exo-β-1,3-glucanases proposed that the catalytic activity and structural flexibility at cold environment were attained through a reduced amount of hydrogen bonds and salt bridges, as well as an increased exposure of the hydrophobic side chains to the solvent. A molecular dynamics simulation was also performed using GROMACS software to evaluate the stability of the GaExg55 structure at varying low temperatures. The simulation result confirmed the above findings for cold adaptation of the psychrophilic GaExg55. Furthermore, the structural analysis of GaExg55 with large catalytic cleft and wide active site pocket confirmed the high activity of GaExg55 to hydrolyze polysaccharide substrates.