Identification of binding interaction between Curcumin derivative and PERK13 Proline rich receptor like protein kinase protein using In silico docking techniques – to help plants tackle salt water

Introduction: Arabidopsis thaliana, mouse ear cress or thale cress are small flowering plants included in the cruciferae family. They comprise of various characteristics such as diploid genetics, small genome size, rapid growth cycle, and relatively low repetitive DNA content, making it a perfect model for plant genome projects. Objective: The aim of this present Insilico research study is to carry out molecular drug docking studies between PERK13 Proline rich receptor like protein kinase and De O Acetylated Curcumin Di Galactose or digalactosylated curcumin, a derivative of curcumin. PERK13 protein is considered to play a significant role in helping plants tackle salinity levels in water. Methods: In this study, protein modelling tools and servers are used to model the 3D structure and the same is validated using Protein structure validation tools. Automated drug docking servers were used to dock the modelled protein with the chemical compound to analyse the electrostatic (H bond) interaction between PERK13 and De O Acetylated Curcumin Di Galactose, a better water soluble compound than curcumin. The docked structure was visualized using an advanced molecular visualization tool. Results and Discussion: The overall results obtained from this study on De O Acetylated Curcumin Di Galactose and PERK13 protein shows that De O Acetylated Curcumin Di Galactose, directly binds with the active site and other potentially binding regions of PERK13. Hence, it is concluded that De O Acetylated Curcumin Di Galactose could potentially play a vital role in future research related to the problem of helping the plants tackle increased saline levels in water. Keywords: A. thaliana, De O Acetylated Curcumin Di Galactose, Drug Docking, Insilico, PERK13, Protein Modelling.

Pepblock Builder VR – An Open-Source Tool for Gaming-Based Bio-Edutainment in Interactive Protein Design

Proteins mediate and perform various fundamental functions of life. This versatility of protein function is an attribute of its 3D structure. In recent years, our understanding of protein 3D structure has been complemented with advances in computational and mathematical tools for protein modelling and protein design. 3D molecular visualisation is an essential part in every protein design and protein modelling workflow. Over the years, stand-alone and web-based molecular visualisation tools have been used to emulate three-dimensional view on computers. The advent of virtual reality provided the scope for immersive control of molecular visualisation. While these technologies have significantly improved our insights into protein modelling, designing new proteins with a defined function remains a complicated process. Current tools to design proteins lack user-interactivity and demand high computational skills. In this work, we present the Pepblock Builder VR, a gaming-based molecular visualisation tool for bio-edutainment and understanding protein design. Simulating the concepts of protein design and incorporating gaming principles into molecular visualisation promotes effective game-based learning. Unlike traditional sequence-based protein design and fragment-based stitching, the Pepblock Builder VR provides a building block style environment for complex structure building. This provides users a unique visual structure building experience. Furthermore, the inclusion of virtual reality to the Pepblock Builder VR brings immersive learning and provides users with “being there” experience in protein visualisation. The Pepblock Builder VR works both as a stand-alone and VR-based application, and with a gamified user interface, the Pepblock Builder VR aims to expand the horizons of scientific data generation to the masses.

Guidelines for reporting protein modelling studies

Computational modelling tools are widely used, however, articles describing modelling studies frequently do not contain sufficient details to allow the reader to comprehend the modelling procedure, quality of the produced model and validity of interpretations and predictions made based on the model. Here, guidelines were developed for items that have to be included when reporting studies and results based on protein modelling. A brief and concise checklist of required data items was compiled. These guidelines are simple to follow and apply, but require meticulous description of details, many of which can be placed to supplementary material. Authors have to pay attention to details when reporting modelling process. The generated structural models should be made publicly available, preferably by submitting to one of the existing repositories.

Increasing Hydrolytic Activity of Lipase on Palm Oil by PCR-Based Random Mutagenesis

ABSTRACT Random mutagenesis technique is a powerful technique capable of producing enzymes with desired biocatalytic activity. This study aims to obtain a mutant lipase with improved hydrolytic activity on palm oil substrate using random mutagenesis technique. Random mutagenesis by error-prone PCR was used to generate mutant lipases. A total of 1101 mutants were obtained, out of which two mutants, Lip M14.25, and Lip M14.57, showed an increased relative hydrolytic activity. Lip M14.25 and Lip M14.57 demonstrated a 14% and 16% increased activity respectively. A comparison of the mutants' hydrolytic activities using p-nitrophenyl esters showed a significantly high preference for p-nitrophenyl palmitate. Furthermore, the mutant, Lip M14.25 showed its highest activity at pH 5, and Lip M14.57 exhibited a 10 oC decrease in optimum temperature. The two mutants' protein modelling showed the substitution of N44S/S202N on M14.25 and F154L/S265C on M14.57 lipase, which caused changes in conformation and active site residue distance of the lipase. The study found two mutants of lipase, M14.25 and M14.57, which showed improved hydrolytic activity on palm oil substrate.

Investigation on phytochemical composition, anti-oxidant and anticancer properties of methanolic extract of Phyllanthus niruri schumach & thonn. And protein modelling and drug docking

The study aims to investigate the Phytochemical Composition, Anti-oxidant and Anticancer properties of methanolic extract of Phyllanthus niruri Schumach & Thonn And the Protein Modelling and drug docking. The research deals with the methanolic extraction and phytochemical screening, determination of total phenolic and flavonoids contents and anti-oxidant assay. By performing GC-MS characterisation, various active metabolites are analysed. Thin-layer chromatography profiling of the Phyllanthus niruri methanolic extract was performed. The IC50 of the Phyllanthus niruri methanolic extract against PA-1 Cell lines(Ovarian cancer) was calculated. Docking studies also performed for antitumor activity by using Bioinformatics and Cheminformatics software on corilagin and cisplatin. The results suggested that the methanolic extract of Phyllanthus niruri leaves has the anticancer cancer effect on the ovarian cell line. The docking studies also performed that Corilagin interaction with T.F. receptor shows a high binding score when compared to cisplatin. Our future research can be done in this area to optimise anticancer activity efficacy. Our results can be further tested Clinico-pharmacologically to prove its efficiency in human beings.

A Novel Nonsense Mutation in FGB (c.1421G>A; p.Trp474Ter) in the Beta Chain of Fibrinogen Causing Hypofibrinogenemia with Bleeding Phenotype

Congenital hypofibrinogenemia is a rare bleeding disorder characterized by a proportional decrease of functional and antigenic fibrinogen levels. Hypofibrinogenemia can be considered the phenotypic expression of heterozygous loss of function mutations occurring within one of the three fibrinogen genes (FGA, FGB, and FGG). Clinical manifestations are highly variable; most patients are usually asymptomatic, but may appear with mild to severe bleeding or thrombotic complications. We have sequenced all exons of the FGA, FGB, and FGG genes using the DNA isolated from the peripheral blood in two unrelated probands with mild hypofibrinogenemia. Coagulation screening, global hemostasis, and functional analysis tests were performed. Molecular modeling was used to predict the defect of synthesis and structural changes of the identified mutation. DNA sequencing revealed a novel heterozygous variant c.1421G>A in exon 8 of the FGB gene encoding a Bβ chain (p.Trp474Ter) in both patients. Clinical data from patients showed bleeding episodes. Protein modelling confirmed changes in the secondary structure of the molecule, with the loss of three β sheet arrangements. As expected by the low fibrinogen levels, turbidity analyses showed a reduced fibrin polymerisation and imaging difference in thickness fibrin fibers. We have to emphasize that our patients have a quantitative fibrinogen disorder; therefore, the reduced function is due to the reduced concentration of fibrinogen, since the Bβ chains carrying the mutation predicted to be retained inside the cell. The study of fibrinogen molecules using protein modelling may help us to understand causality and effect of novel genetic mutations.

In silico molecular modelling and docking of allicin, epigallocatechin-3-gallate and gingerol against colon cancer cell proteins

Globally, colon cancer is the second most common cancer among men and women. There is an urgent need to search for a cure for colon cancer. Phytocomponents have shown to exhibit chemoprevention and chemotherapeutic effects related to colon cancer. Thus, phytocomponents can be used as the lead for new drug discovery. Computational biology approaches such as protein modelling and docking have helped in designing substrate-based drugs. In this study, three dimensional (3-D) models of tumour protein (p53), adenomatous polyposis coli (APC) and epidermal growth factor receptor (EGFR) were built using SWISS-MODEL; and their interaction with allicin, epigallocatechin-3-gallate and gingerol through blind docking were evaluated using BSP-SLIM server. These three target proteins are from colon cancer. Physiochemical characters of protein models were assessed through ExPASy’s ProtParam tool. Moreover, the protein structures were validated using PROCHECK, ProQ, ERRAT and VERIFY 3D servers. The protein models’ scores were within normal range. It also showed that the protein models were stable to proceed with the docking approach. Finally, the protein structures (target proteins) were docked successfully with allicin, epigallocatechin-3-gallate and gingerol (phytocomponent). The protein models had a strong interaction with the phytocomponents due to their good binding scores. The best docking scores of the protein-phytocomponent complexes (p53-allicin, APC-Epigallocatechin-3-Gallate and EGFR-gingerol) were 4.968, 6.490, and 6.034, respectively. Protein p53 had the strongest interaction with allicin due to its lowest binding score among all the protein-plant compound complexes. Thus, the results of this study can be used to design and develop a more powerful structure-based drug.

A Further Case of Larsen's Syndrome: Clinical and Genotypic Challenges in Diagnosis

Larsen's syndrome is characterized by dislocation of multiple large joints, digital anomalies, craniofacial dysmorphism, and short stature. In this paper, we describe a case of a 5-month-old boy with a triad of cardinal features in association with other signs. The diagnosis was confirmed by exome sequencing, which led to the identification of a novel missense variant NM_001457.4:c.4928C > G (p.Ala1643Gly) in the FLNB gene. We describe the role of protein modelling for the establishment of pathogenicity of this variant. We also outline the challenges in genetic diagnosis due to variable expressivity of the variant and discuss the clinicogenetic profile of previously reported patients with Larsen's syndrome in India.