虚拟生物实验室实例

虚拟生物实验室在生物课程资源中有巨大并且尚未开发的潜力。它对于不同级别学生的学习都是有利的。介绍了虚拟生物实验室的一些实例。并展望了其应用前景。     

Visualizing biomolecular electrostatics in virtual reality with UnityMol‐APBS

Virtual reality is a powerful tool with the ability to immerse a user within a completely external environment. This immersion is particularly useful when visualizing and analyzing interactions between small organic molecules, molecular inorganic complexes, and biomolecular systems such as redox proteins and enzymes. A common tool used in the biomedical community to analyze such interactions is the Adaptive Poisson‐Boltzmann Solver (APBS) software, which was developed to solve the equations of continuum electrostatics for large biomolecular assemblages. Numerous applications exist for using APBS in the biomedical community including analysis of protein ligand interactions and APBS has enjoyed widespread adoption throughout the biomedical community. Currently, typical use of the full APBS toolset is completed via the command line followed by visualization using a variety of two‐dimensional external molecular visualization software. This process has inherent limitations: visualization of three‐dimensional objects using a two‐dimensional interface masks important information within the depth component. Herein, we have developed a single application, UnityMol‐APBS, that provides a dual experience where users can utilize the full range of the APBS toolset, without the use of a command line interface, by use of a simple graphical user interface (GUI) for either a standard desktop or immersive virtual reality experience.     

Apps for angiosperms: the usability of mobile computers and printed field guides for UK wild flower and winter tree identification

We investigated usability of mobile computers and field guide books with adult botanical novices, for the identification of wildflowers and deciduous trees in winter. Identification accuracy was significantly higher for wildflowers using a mobile computer app than field guide books but significantly lower for deciduous trees. User preference followed a similar pattern. These results suggest that the identification method and its design are more important for a field guide than its presentation medium (electronic or printed). We discuss the relative advantages of the presentation media used and their value as engagement tools for botany.     

Discovery of VEGFR inhibitors through virtual screening and energy assessment

Vascular endothelial growth factor receptor-2 (VEGFR-2) is crucial in promoting tumor angiogenesis and cancer metastasis. Thus, inhibition of VEGFR-2 has appeared as a good tactic for cancer treatment. To find out novel VEGFR-2 inhibitors, first, the PDB structure of VEGFR-2, 6GQO, was selected based on atomic nonlocal environment assessment (ANOLEA) and PROCHECK assessment. 6GQO was then further used for structure-based virtual screening (SBVS) of different molecular databases, including US-FDA approved drugs, US-FDA withdrawn drugs, may bridge, MDPI, and Specs databases using Glide. Based on SBVS, receptor fit, drug-like filters, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of 427877 compounds, the best 22 hits were selected. From the 22 hits, hit 5 complex with 6GQO was put through molecular mechanics/generalized born surface area (MM/GBSA) study and hERG binding. The MM/GBSA study revealed that hit 5 possesses lesser binding free energy with more inferior stability in the receptor pocket than the reference compound. The VEGFR-2 inhibition assay of hit 5 disclosed an IC₅₀ of 165.23 nM against VEGFR-2, which can be possibly enhanced through structural modifications.     

Homology modeling,docking and structure-based virtual screening for new inhibitor identification of Klebsiella pneumoniae heptosyltransferase-III

Abstract

Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative opportunistic pathogen commonly associated with hospital-acquired infections that are often resistant even to antibiotics. Heptosyltransferase (HEP) belongs to the family of glycosyltransferase-B (GT-B) and plays an important in the synthesis of lipopolysaccharides (LPS) essential for the formation of bacterial cell membrane. HEP-III participates in the transfer of heptose sugar to the outer surface of bacteria to synthesize LPS. LPS truncation increases the bacterial sensitivity to hydrophobic antibiotics and detergents, making the HEP as a novel drug target. In the present study, we report the 3D homology model of K. pneumoniae HEP-III and its structure validation. Active site was identified based on similarities with known structures using Dali server, and structure-based pharmacophore model was developed for the active site substrate ADP. The generated pharmacophore model was used as a 3D search query for virtual screening of the ASINEX database. The hit compounds were further filtered based on fit value, molecular docking, docking scores, molecular dynamics (MD) simulations of HEP-III complexed with hit molecules, followed by binding free energy calculations using Molecular Mechanics-Poisson–Boltzmann Surface Area (MM-PBSA). The insights obtained in this work provide the rationale for design of novel inhibitors targeting K. pneumoniae HEP-III and the mechanistic aspects of their binding.

Communicated by Ramaswamy H. Sarma     

3D QSAR pharmacophore-based virtual screening for the identification of potential inhibitors of tyrosinase

Abstract

Tyrosinase plays an important role in melanin biosynthesis and protects skin against ultraviolet radiations. Functional deficiency of tyrosinase results in serious dermatological diseases. Tyrosinase also participates in neuromelanin formation in the human brain, which leads to neurodegeneration resulting in Parkinson’s disease. In fruits and vegetables, tyrosinase plays a critical role in senescence, causing undesired browning that results in faster deterioration and shorter shelf lines. The only commercially available tyrosinase is mushroom tyrosinase and it shows the highest homology to the mammalian tyrosinase. Although kojic acid is currently used as a tyrosinase inhibitor, they have serious side effects such as dermatitis, carcinogenesis and hepatotoxicity. Therefore, in order to develop a more active and safer tyrosinase inhibitor, 3D QSAR pharmacophore models were generated based on experimentally known inhibitors. The pharmacophore model, Hypo1, was developed with a large cost difference, high correlation coefficient and low RMS deviation. Hypo1 showed a good spatial arrangement; consisting of five-point features including two hydrogen bond acceptor, one hydrogen bond donor and two hydrophobic features. Hypo1 was further validated by cost analysis, test set and Fisher’s randomisation method. Hypo1 was used as a 3D query for screening the in-house drug-like databases, and the hits were further selected by applying ADMET, Lipinski’s rule of five and fit value criteria. To identify binding conformations, the obtained hits were subjected to molecular docking. Finally, molecular dynamics simulations revealed the appropriate binding modes of hit compounds. To conclude, we propose the final three hit compounds with new structural scaffolds as a virtual candidate as tyrosinase inhibitors.

Communicated by Ramaswamy H. Sarma     

Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.     

New potential inhibitors of mTOR: a computational investigation integrating molecular docking,virtual screening and molecular dynamics simulation

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.     

Homology modeling,virtual screening and dynamics study of proteins involved in Pebrine - Serine protease inhibitor 106 and spore wall protein 26

Abstract

Pebrine is a microsporidian disease caused by Nosema bombycis in Bombyx mori (silk worm) which results in brown/black spots. The affected larvae either spin cocoons which are flimsy with low silk content or not spin a cocoon. It has been hypothesised that Serine Protease Inhibitor 106 (SPN106) is responsible for evasion of host immune system by inhibiting the melanization process in silkworms. Also, Spore Wall Protein 26 (SWP26) has been observed to bind with Ig- like protein Bombyx mori turtle-like protein (Bm-TLP) facilitating the attachment of the microsporidian to the host and contributing to infectivity. Till date, there is no crystal structure of the proteins SPN106, SWP26 and Bm-TLP available. In this study, we performed homology modeling of the three structures using Modeller v9.18 and the binding pockets were identified. Virtual screening was conducted using AutoDock Vina on a ligand library consisting of 28,870 lead-like molecules. The protein stability, compactness, fluctuations and protein-ligand interactions were investigated through Molecular Dynamics (MD) simulations studies using Desmond Maestro 11.3 and a potential lead molecule was identified.

Communicated by Ramaswamy H. Sarma     

Identification of novel acetylcholinesterase inhibitors through e-pharmacophore-based virtual screening and molecular dynamics simulations

Alzheimer’s disease (AD), a progressive neurodegenerative disorder is the most common cause of dementia among elderly people. To date, the successful therapeutic strategy to treat AD is maintaining the levels of acetylcholine via inhibiting acetylcholinesterase (AChE). The present study involves identification of newer AChE inhibitors by dual approach of e-pharmacophore and structure-based virtual screening of Asinex library. Robustness of docking protocol was validated by enrichment calculation with ROC value .71 and BEDROC value .028. Among 11 selected hits, ZINC72338524 with best MM-GBSA dG binding shows optimal range of CNS properties and ligand–AChE complex stability. Further, molecular dynamics study revealed its molecular interactions with Trp86, Phe338, and Tyr341 amino acid residues of catalytic anionic site and Tyr124, Ser125, and Trp286 amino acid residues of peripheral anionic site. Physicochemical properties and ADMET risk prediction indicates their potential in druggability and safety.     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

Refined homology model of cytochrome bcc complex B subunit for virtual screening of potential anti-tuberculosis agents

Abstract

Cytochrome bcc complex is important for ATP synthesis and cellular activity, as a crucial step in the terminal reduction of oxygen in aerobic electron transport chains. The b subunit of cytochrome bcc complex (QcrB) has been reported as a promising anti-tuberculosis target, with many novel anti-tuberculosis scaffolds reported. However, the 3D structure of mycobacterium tuberculosis (M. tuberculosis) QcrB has not been released, making it hard to understand the interactions between QcrB and its inhibitors as well as to develop novel anti-tuberculosis scaffolds. Herein we built the optimal homology model of M. tuberculosis QcrB using the M. smegmatis QcrB structure as template, which was refined through all-atom molecular dynamics simulation. Then, the binding modes of known inhibitors were predicted through molecular docking method, along with molecular dynamics simulation and binding free energy calculation to verify the accuracy of docking results and stability of the protein-inhibitor complexes. The informative key residues within QcrB site enabled us to perform structure-based virtual library screening to obtain potential M. tuberculosis QcrB inhibitors, which were validated through molecular dynamics simulation and MM-GBSA calculation and analyzed through pharmacokinetic properties prediction. Our research would provide a deeper insight into the interactions between M. tuberculosis QcrB and its inhibitors, which boosts to develop novel therapy against tuberculosis.

Communicated by Ramaswamy H. Sarma     

计算机虚拟筛选技术在害虫行为调节剂研究中的应用

害虫行为调节剂是一种以嗅觉系统为靶标的绿色农药,在害虫的田间管理中发挥着重要的作用。然而,其先导化合物的发现通常依赖一系列生物测定的方法,不仅费时费力,且发现效率低。近年来,随着昆虫嗅觉功能数据的积累和结构生物学的飞速发展,以机器学习技术和分子对接为代表的2种基于计算机的药物虚拟筛选方法在害虫行为调节剂的先导化合物研究中发挥着重要的作用,极大地促进了先导化合物的发现效率,减少了筛选的盲目性。本文系统综述了2种虚拟筛选方法及其在害虫行为调节剂先导化合物研究中的应用,并对2种筛选策略在实际应用中存在的问题及应用前景进行了讨论。     

Evaluation and characterization of fetal exposures to low frequency magnetic fields generated by laptop computers

Portable – or “laptop” – computers (LCs) are widely and increasingly used all over the world. Since LCs are often used in tight contact with the body even by pregnant women, fetal exposures to low frequency magnetic fields generated by these units can occur. LC emissions are usually characterized by complex waveforms and are often generated by the main AC power supply (when connected) and by the display power supply sub-system.In the present study, low frequency magnetic field emissions were measured for a set of five models of portable computers. For each of them, the magnetic flux density was characterized in terms not just of field amplitude, but also of the so called “weighted peak” (WP) index, introduced in the 2003 ICNIRP Statement on complex waveforms and confirmed in the 2010 ICNIRP Guidelines for low frequency fields. For the model of LC presenting the higher emission, a deeper analysis was also carried out, using numerical dosimetry techniques to calculate internal quantities (current density and in-situ electric field) with reference to a digital body model of a pregnant woman. Since internal quantities have complex waveforms too, the concept of WP index was extended to them, considering the ICNIRP basic restrictions defined in the 1998 Guidelines for the current density and in the 2010 Guidelines for the in-situ electric field. Induced quantities and WP indexes were computed using an appropriate original formulation of the well known Scalar Potential Finite Difference (SPFD) numerical method for electromagnetic dosimetry in quasi-static conditions.     

Structural insight into Mycobacterium tuberculosis maltosyl transferase inhibitors: pharmacophore-based virtual screening,docking, and molecular dynamics simulations

Pharmacophore-based virtual screening, subsequent docking, and molecular dynamics (MD) simulations have been done to identify potential inhibitors of maltosyl transferase of Mycobacterium tuberculosis (mtb GlgE). Ligand and structure-based pharmacophore models representing its primary binding site (pbs) and unique secondary binding site 2 (sbs2), respectively, were constructed based on the three dimensional structure of mtb GlgE. These pharmacophore models were further used for screening of ZINC and antituberculosis compounds database (ATD). Virtually screened molecules satisfying Lipinski’s rule of five were then analyzed using docking studies and have identified 23 molecules with better binding affinity than its natural substrate, maltose. Four top scoring ligands from ZINC and ATD that either binds to pbs or sbs2 have been subjected to 10 ns each MD simulations and binding free energy calculations. Results of these studies have confirmed stable protein ligand binding. Results reported in the article are likely to be helpful in antitubercular therapeutic development research.     

Exploring dual inhibitory role of febrifugine analogues against Plasmodium utilizing structure-based virtual screening and molecular dynamic simulation

Malaria is an endemic disease caused by the protozoan parasite Plasomodium falciparum. Febrifugine analogues are natural compound obtained from the traditional Chinese herbs have shown significant antimalarial and anticancerous efficacy in experimental model. Development of resistance against the existing antimalarial drug has alarmed the scientific innovators to find a potential antimalarial molecule which can be further used by endemic countries for the elimination of this disease. In this study, structure-based virtual screening and molecular dynamics (MD) base approaches were used to generate potential antimalarial compound against plasmepsin II and prolyl-tRNA synthetase of Plasmodium. Here, we have docked series of febrifugine analogues (n = 11,395) against plasmepsin II in three different docking modes and then it was compared with previously reported target prolyl-tRNA synthetase. Extra precision docking resulted into 235 ligands having better docking score were subject for QikProp analysis. Better ligands (n = 39) obtained from QikProp analysis were subject for ADMET prediction and docking protocol validation through the estimation of receiver operator characteristics. In the later stage, 24 ligands obtained from ADMET study were subject for the estimation of binding energy through MM-GBSA and same were also docked against prolyl-tRNA synthetase to get compounds with dual inhibitor role. Finally, MD simulation and 2D fingerprint MACCS study of two best ligands have shown significant interaction with plasmepsin II and homology against known active ligand with noteworthy MACCS index, respectively. This study concludes that FA12 could be potential drug candidate to fight against Plasmodium falciparum parasites.     

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r?=?0.96) and Fisher’s randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski’s rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.     

A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors

A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors.     

Discovering novel carbonic anhydrase type IX (CA IX) inhibitors from seven million compounds using virtual screening and in vitro analysis

Carbonic anhydrase type IX (CA IX) enzyme is mostly over expressed in different cancer cell lines and tumor tissues. Potent CA IX inhibitors can be effective for adjusting the pH imbalance in tumor cells. In the present work, we represented the successful application of high throughput virtual screening (HTVS) of large dataset from ZINC database included of ～7 million compounds to discover novel inhibitors of CA IX. HTVS and molecular docking were performed using consequence Glide/standard precision (SP), extra precision (XP) and induced fit docking (IFD) molecular docking protocols. For each compound, docking code calculates a set of low-energy poses and then exhaustively scans the binding pocket of the target with small compounds. Novel CA IX inhibitor candidates were suggested based on molecular modeling studies and a few of them were tested using in vitro analysis. These compounds were determined as good inhibitors against human CA IX target with K_i in the range of 0.85–1.58?μM. In order to predict the pharmaceutical properties of the selected compounds, ADME (absorption, distribution, metabolism and excretion) analysis was also carried out.