In Silico Drug Screening Analysis against the Overexpression of PGAM1 Gene in Different Cancer Treatments

Phosphoglycerate mutase 1 (PGAM1) is considered as a novel target for multiple types of cancer drugs for the upregulation in tumor, cell prefoliation, and cell migration. During aerobic glycolysis, PGAM1 plays a critical role in cancer cell metabolism by catalyzing the conversion of 3-phosphoglycerate (3PG) to 2-phosphoglycerate (2PG). In this computational-based study, the molecular docking approach was used with the best binding active sites of PGAM1 to screen 5,000 Chinese medicinal phytochemical library. The docking results were three ligands with docking score, RMSD-refine, and residues. Docking scores were -16.57, -15.22, and -15.74. RMSD values were 0.87, 2.40, and 0.98, and binding site residues were Arg 191, Arg 191, Arg 116, Arg 90, Arg 10, and Tyr 92. The best compounds were subjected to ADMETsar, ProTox-2 server, and Molinspiration analysis to evaluate the toxicological and drug likeliness potential of such selected compounds. The UCSF-Chimera tool was used to visualize the results, which shows that the three medicinal compounds named N-Nitrosohexamethyleneimine, Subtrifloralactone-K, and Kanzonol-N in chain-A were successfully binding with the active pockets of PGAM1. The study might facilitate identifying the hit molecules that could be beneficial in the development of antidrugs against various types of cancer treatment. These hit phytochemicals could be beneficial for further investigation of a novel target for cancer.

Prediction of Anti-COVID 19 Therapeutic Power of Medicinal Moroccan Plants Using Molecular Docking

The emerging pathogen SARS-CoV2 causing coronavirus disease 2019 (COVID-19) is a global public health challenge. To the present day, COVID-19 had affected more than 40 million people worldwide. The exploration and the development of new bioactive compounds with cost-effective and specific anti-COVID 19 therapeutic power is the prime focus of the current medical research. Thus, the exploitation of the molecular docking technique has become essential in the discovery and development of new drugs, to better understand drug-target interactions in their original environment. This work consists of studying the binding affinity and the type of interactions, through molecular docking, between 54 compounds from Moroccan medicinal plants, dextran sulfate and heparin (compounds not derived from medicinal plants), and 3CLpro-SARS-CoV-2, ACE2, and the post fusion core of 2019-nCoV S2 subunit. The PDB files of the target proteins and prepared herbal compounds (ligands) were subjected for docking to AutoDock Vina using UCSF Chimera, which provides a list of potential complexes based on the criteria of form complementarity of the natural compound with their binding affinities. The results of molecular docking revealed that Taxol, Rutin, Genkwanine, and Luteolin-glucoside have a high affinity with ACE2 and 3CLpro. Therefore, these natural compounds can have 2 effects at once, inhibiting 3CLpro and preventing recognition between the virus and ACE2. These compounds may have a potential therapeutic effect against SARS-CoV2, and therefore natural anti-COVID-19 compounds.

Analisis In-Silico Struktur Tiga Dimensi Reseptor Trk A dan Trk B Protein Neurotrophin 3 Pada Gallus gallus (Chicken)

NT3 protein is expressed by Neurotrophin 3 (NTF-3) which plays a role in the process of differentiation, survival of peripheral and neuropathological of neurons. The information of structure and function of NT-3 proteins is still very limited, especially in Gallus gallus. This study aims to predict the three-dimensional structure of the Trk A and Trk B proteins in Gallus gallus. The target protein obtained from the UniProt server with access codes Q91009 (Trk A) and Q91987 (Trk B) using the 6kzc 1.A (PDB ID) template was analyzed in silico through a homology approach and describing the structural assessment using Chimera UCSF software. The analysis showed that the Trk A protein had a QMEAN value of -0.08, composed of 778 amino acids, mass 87334.30 Daltons, and Seq Identity 79.93%. Trk B had a QMEAN value of 0.16, consisting of 818 amino acids, mass 91732.05 Daltons, and Seq Identity 84.30%. Key words: NT3; homology; UCSF chimera; G. gallus

Molecular Docking Using Chimera and Autodock Vina Software for Nonbioinformaticians

In the field of drug discovery, many methods of molecular modeling have been employed to study complex biological and chemical systems. Experimental strategies are integrated with computational approaches for the identification, characterization, and development of novel drugs and compounds. In modern drug designing, molecular docking is an approach that explores the confirmation of a ligand within the binding site of a macromolecule. To date, many software and tools for docking have been employed. AutoDock Vina (in UCSF [University of California, San Francisco] Chimera) is one of the computationally fastest and most accurate software employed in docking. In this paper, a sequential demonstration of molecular docking of the ligand fisetin with the target protein Akt has been provided, using AutoDock Vina in UCSF Chimera 1.12. The first step involves target protein ID retrieval from the protein database, the second step involves visualization of the protein structure in UCSF Chimera, the third step involves preparation of the target protein for docking, the fourth step involves preparation of the ligand for docking, the fifth step involves docking of the ligand and the target protein as Mol.2 files in Chimera by using AutoDock Vina, and the final step involves interpretation and analysis of the docking results. By following the guidelines and steps outlined in this paper, researchers with no previous background in bioinformatics research can perform computational docking in an easier and more user-friendly manner.

In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China in December 2019. Since then, COVID-19, the disease caused by SARS-CoV-2, has become a rapidly spreading pandemic that has reached most countries in the world. So far, there are no vaccines or therapeutics to fight this virus. Here, I present an in silico analysis of the virus spike glycoprotein (recently determined at atomic resolution) and provide insights into how antibodies against the 2002 virus SARS-CoV might be modified to neutralize SARS-CoV-2. I ran docking experiments with Rosetta Dock to determine which substitutions in the 80R and m396 antibodies might improve the binding of these to SARS-CoV-2 and used molecular visualization and analysis software, including UCSF Chimera and Rosetta Dock, as well as other bioinformatics tools, including SWISS-MODEL. Supercomputers, including Bridges Large, Stampede and Frontera, were used for macromolecular assemblies and large scale analysis and visualization.

Molecular Structure Properties of Heme Group in the Oxymyoglobin Protein (1mbo.pdb) Using PyMOL & UCSF Chimera

PyMOL and UCSF Chimera are open source multifunctional molecular visualization system developed for the use in structural biology. Both of these tools are well designed with various visualization options available for the user; with the help of such options, we have observed that the iron core binds oxygen in the heme group of oxymyoglobin. Also, various molecular surfaces, internal structures as well as bond lengths between the iron core & molecular oxygen in the heme group and that to the histidine-93 of the oxymyoglobin protein have been calculated. Implementing structural analysis feature of UCSF Chimera, the distance between iron core of heme group and molecular oxygen and that between iron core and histidine 93(H93) have been estimated and found to be 1.827 Å and 2.065 Å respectively which are in good agreement (within 0.5% error) with the bond lengths calculated by x-ray diffraction method [4] .The small value of bond length between Fe and O2 suggests the higher stability of oxygen which is important for transportation, activation and storage of enzymes to support life of living organisms on the Earth. So, it provides an insight in enzymology like oxygenase. Interestingly, oxymyoglobin protein or its constituent amino acid chain may have important role in the origin of early life on the Earth.

Antiviral potential of phytoligands against chymotrypsin-like protease of COVID‐19 virus using molecular docking studies: An optimistic approach

A recent outbreak of the novel coronavirus, COVID‐19, in the city of Wuhan, Hubei province, China and its ensuing worldwide spread have resulted in lakhs of infections and thousands of deaths. As of now, there are no registered therapies for treating the contagious COVID‐19 infections, henceforth drug repositioning may provide a fast way out. In the present study, a total of thirty-five compounds including commonly used anti-viral drugs were screened against chymotrypsin-like protease (3CLpro) using SwissDock. Interaction between amino acid of targeted protein and ligands was visualized by UCSF Chimera. Docking studies revealed that the phytochemicals such as cordifolin, anisofolin A, apigenin 7-glucoside, luteolin, laballenic acid, quercetin, luteolin-4-glucoside exhibited significant binding energy with the enzyme viz. - 8.77, -8.72, -8.36, -8.35, -8.13, -8.04 and -7.87 Kcal/Mol respectively. Therefore, new lead compounds can be used for drug development against SARS‐CoV‐2 infections.

Computational approach to identify potential antileishmanial activity of reported inhibitor, E5700 and two natural alkaloids against Leishmania donovani Squalene Synthase

Leishmania species are the causative agents for Leishmaniasis which is one of the neglected tropical diseases causing 70,000 deaths worldwide each year. Squalene synthase enzyme plays a vital role in sterol metabolism which is essential for Leishmania parasite viability. Therefore squalene synthase of Leishmania donovani is a therapeutic target to inhibit growth of parasite. The 3D model of Leishmania donovani Squalene Synthase (LdSQS) was generated by homology modeling and validated through PROCHECK, ERRAT, VERIFY3D and PROSA tools. Virtual screening of the protein was performed by AutoDock with reported inhibitor, E5700 and two natural alkaloids. Molecular interactions were explored to understand the nature of intermolecular bonds between active ligand and the protein binding site residues using UCSF Chimera and PLIP server. The reported inhibitor showed the best binding affinity (-9.75 kcal/mol) closely followed by Ancistrotanzanine B (-9.55 kcal/mol) and Holamine (-8.79 kcal/mol). Ancistrotanzanine B showed low binding energy and permissible ADMET properties. Based on the present study, homology model of LdSQS and Ancistrotanzanine B can be used to design inhibitors with antileishmanial activity.

In Silico Antituberculosis Drug Designing using UCSF Chimera

For the humans’ well-being, Mycobacterium Tuberculosis (MTB) is a fatal and adversary disease since years because of if its multidrug straining. MTB consumes nitrate as a substitute during breathing mechanism due to malingering of oxygen, therefore it increases the chances of survival. The nitrate/nitrite response (NarL) is a transcriptional governing protein. It is a two-constituent signal alteration mechanism used to stabilize nitrate enzyme that promote chemical drop and plan dehydrogenation. In this work, molecular docking using in-silico technique by benzofuran and naphthofuran byproducts has been performed. In-silico interaction of phosphodonors to NarL has been done. From the simulation results it is noticed that all compounds are binding to active site, therefore it is concluded that all benzofuran and naphthofuran byproducts partake on the dynamic site of NarL and are able to perform as leading molecule. To obtain results, SwissDock, UCSF Chimera and Protein–ligand Docking is majorly utilized.

IN SILICO STUDY OF MONOSACCHARIDE COMPOUNDS EFFECT ON B CELL RECEPTORS (BCR) FROM NONI FRUIT (MORINDA CITRIFOLIA)

Objective: Noni fruit has been widely used as a treatment. The content of saccharides in noni can affect the immune system, especially as independent antigens (TI) against B cell receptors (BCR). TI can produce antibodies without being influenced by T cells. Therefore, this study aims to look at the effect of IT on BCR with the in silico method approach. Methods: Ligands were obtained from Zink Web and macromolecules were obtained from Protein Data Bank with code 2H32. Ligand optimization using VegaZZ software and macromolecules is optimized using UCSF Chimera software. Ligands and macromolecules are docking using MOE software. Result: The results showed that monosaccharide compounds have an interaction with BCR, which is characterized by a decrease in free energy. The D-Galactose compound has the largest binding affinity of-4.80 kcal/mol. Conclusion: Monosaccharide compounds are independent antigens (TI) of noni (Morinda citrifolia) that can affect on B cell receptors (BCR), which have identical epitopes.