METADOCK 2: a high-throughput parallel metaheuristic scheme for molecular docking

[EN] Motivation Molecular docking methods are extensively used to predict the interaction between protein-ligand systems in terms of structure and binding affinity, through the optimization of a physics-based scoring function. However, the computational requirements of these simulations grow exponentially with: (i) the global optimization procedure, (ii) the number and degrees of freedom of molecular conformations generated and (iii) the mathematical complexity of the scoring function. Results In this work, we introduce a novel molecular docking method named METADOCK 2, which incorporates several novel features, such as (i) a ligand-dependent blind docking approach that exhaustively scans the whole protein surface to detect novel allosteric sites, (ii) an optimization method to enable the use of a wide branch of metaheuristics and (iii) a heterogeneous implementation based on multicore CPUs and multiple graphics processing units. Two representative scoring functions implemented in METADOCK 2 are extensively evaluated in terms of computational performance and accuracy using several benchmarks (such as the well-known DUD) against AutoDock 4.2 and AutoDock Vina. Results place METADOCK 2 as an efficient and accurate docking methodology able to deal with complex systems where computational demands are staggering and which outperforms both AutoDock Vina and AutoDock 4.This work was partially supported by the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia [Projects 20813/PI/ 18, 20988/PI/18, 20524/PDC/18] and by the Spanish Ministry of Science, Innovation and Universities [TIN2016-78799-P (AEI/FEDER, UE), CTQ2017-87974-R]. The authors thankfully acknowledge the computer resources at CTE-POWER and the technical support provided by Barcelona Supercomputing Center - Centro Nacional de Supercomputación [RES-BCV2018-3-0008].Imbernón, B.; Serrano, A.; Bueno-Crespo, A.; Abellán, JL.; Pérez-Sánchez, H.; Cecilia-Canales, JM. (2020). METADOCK 2: a high-throughput parallel metaheuristic scheme for molecular docking. Bioinformatics. 1-6. https://doi.org/10.1093/bioinformatics/btz958S16Bianchi, L., Dorigo, M., Gambardella, L. M., & Gutjahr, W. J. (2008). A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing, 8(2), 239-287. doi:10.1007/s11047-008-9098-4Cecilia, J. M., Llanes, A., Abellán, J. L., Gómez-Luna, J., Chang, L.-W., & Hwu, W.-M. W. (2018). High-throughput Ant Colony Optimization on graphics processing units. Journal of Parallel and Distributed Computing, 113, 261-274. doi:10.1016/j.jpdc.2017.12.002Desiraju, G., & Steiner, T. (2001). The Weak Hydrogen Bond. doi:10.1093/acprof:oso/9780198509707.001.0001Eisenberg, D., & McLachlan, A. D. (1986). Solvation energy in protein folding and binding. Nature, 319(6050), 199-203. doi:10.1038/319199a0Ewing, T. J. A., Makino, S., Skillman, A. G., & Kuntz, I. D. (2001). Journal of Computer-Aided Molecular Design, 15(5), 411-428. doi:10.1023/a:1011115820450Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T. A., Klicic, J. J., Mainz, D. T., … Shenkin, P. S. (2004). Glide:  A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy. Journal of Medicinal Chemistry, 47(7), 1739-1749. doi:10.1021/jm0306430Guerrero, G. D., Imbernón, B., Pérez-Sánchez, H., Sanz, F., García, J. M., & Cecilia, J. M. (2014). A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing. BioMed Research International, 2014, 1-8. doi:10.1155/2014/474219Hauser, A. S., & Windshügel, B. (2016). LEADS-PEP: A Benchmark Data Set for Assessment of Peptide Docking Performance. Journal of Chemical Information and Modeling, 56(1), 188-200. doi:10.1021/acs.jcim.5b00234Llanes, A., Muñoz, A., Bueno-Crespo, A., García-Valverde, T., Sánchez, A., Arcas-Túnez, F., … M. Cecilia, J. (2016). Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures. Current Drug Targets, 17(14), 1626-1648. doi:10.2174/1389450117666160201114028McIntosh-Smith, S., Price, J., Sessions, R. B., & Ibarra, A. A. (2014). High performance in silico virtual drug screening on many-core processors. The International Journal of High Performance Computing Applications, 29(2), 119-134. doi:10.1177/1094342014528252Mehler, E. L., & Solmajer, T. (1991). Electrostatic effects in proteins: comparison of dielectric and charge models. «Protein Engineering, Design and Selection», 4(8), 903-910. doi:10.1093/protein/4.8.903Morris, G. M., Goodsell, D. S., Halliday, R. S., Huey, R., Hart, W. E., Belew, R. K., & Olson, A. J. (1998). Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry, 19(14), 1639-1662. doi:10.1002/(sici)1096-987x(19981115)19:143.0.co;2-bMysinger, M. M., Carchia, M., Irwin, J. J., & Shoichet, B. K. (2012). Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking. Journal of Medicinal Chemistry, 55(14), 6582-6594. doi:10.1021/jm300687eO’Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. Journal of Cheminformatics, 3(1). doi:10.1186/1758-2946-3-33Sakurai, Y., Kolokoltsov, A. A., Chen, C.-C., Tidwell, M. W., Bauta, W. E., Klugbauer, N., … Davey, R. A. (2015). Two-pore channels control Ebola virus host cell entry and are drug targets for disease treatment. Science, 347(6225), 995-998. doi:10.1126/science.1258758Sánchez-Linares, I., Pérez-Sánchez, H., Cecilia, J. M., & García, J. M. (2012). High-Throughput parallel blind Virtual Screening using BINDSURF. BMC Bioinformatics, 13(S14). doi:10.1186/1471-2105-13-s14-s13Sliwoski, G., Kothiwale, S., Meiler, J., & Lowe, E. W. (2013). Computational Methods in Drug Discovery. Pharmacological Reviews, 66(1), 334-395. doi:10.1124/pr.112.007336Sörensen, K. (2013). Metaheuristics-the metaphor exposed. International Transactions in Operational Research, 22(1), 3-18. doi:10.1111/itor.12001Yuan, S., Chan, J. F.-W., den-Haan, H., Chik, K. K.-H., Zhang, A. J., Chan, C. C.-S., … Yuen, K.-Y. (2017). Structure-based discovery of clinically approved drugs as Zika virus NS2B-NS3 protease inhibitors that potently inhibit Zika virus infection in vitro and in vivo. Antiviral Research, 145, 33-43. doi:10.1016/j.antiviral.2017.07.00

Targeting allosteric sites of Escherichia coli heat shock protein 70 for antibiotic development

Hsp70s are members of the heat shock proteins family with a molecular weight of 70-kDa and are the most abundant group in bacterial and eukaryotic systems, hence the most extensively studied ones. These proteins are molecular chaperones that play a significant role in protein homeostasis by facilitating appropriate folding of proteins, preventing proteins from aggregating and misfolding. They are also involved in translocation of proteins into subcellular compartments and protection of cells against stress. Stress caused by environmental or biological factors affects the functionality of the cell. In response to these stressful conditions, up-regulation of Hsp70s ensures that the cells are protected by balancing out unfolded proteins giving them ample time to repair denatured proteins. Hsp70s is connected to numerous illnesses such as autoimmune and neurodegenerative diseases, bacterial infection, cancer, malaria, and obesity. The multi-functional nature of Hsp70s predisposes them as promising therapeutic targets. Hsp70s play vital roles in various cell developments, and survival pathways, therefore targeting this protein will provide a new avenue towards the discovery of active therapeutic agents for the treatment of a wide range of diseases. Allosteric sites of these proteins in its multi-conformational states have not been explored for inhibitory properties hence the aim of this study. This study aims at identifying allosteric sites that inhibit the ATPase and substrate binding activities using computational approaches. Using E. coli as a model organism, molecular docking for high throughput virtual screening was carried out using 623 compounds from the South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/) against identified allosteric sites. Ligands with the highest binding affinity (good binders) interacting with critical allosteric residues that are druggable were identified. Molecular dynamics (MD) simulation was also performed on the identified hits to assess for protein-inhibitor complex stability. Finally, principal component analysis (PCA) was performed to understand the structural dynamics of the ligand-free and ligand-bound structures during MD simulation

AtomLbs: An Atom Based Convolutional Neural Network for Druggable Ligand Binding Site Prediction

Despite advances in drug research and development, there are few and ineffective treatments for a variety of diseases. Virtual screening can drastically reduce costs and accelerate the drug discovery process. Binding site identification is one of the initial and most important steps in structure-based virtual screening. Identifying and defining protein cavities that are likely to bind to a small compound is the objective of this task. In this research, we propose four different convolutional neural networks for predicting ligand-binding sites in proteins. A parallel optimized data pipeline is created to enable faster training of these neural network models on minimal hardware. The effectiveness of each method is assessed on well-established ligand binding site datasets. It is then compared with the state-of-the-art and widely used methods for ligand binding site identification. The result shows that our methods outperform most of the other methods and are comparable to the state-of-the-art methods

Targeting the Poly (ADP-Ribose) Polymerase-1 Catalytic Pocket Using AutoGrow4, a Genetic Algorithm for De Novo Design

AutoGrow4 is a free and open-source program for de novo drug design that uses a genetic algorithm (GA) to create novel predicted small-molecule ligands for a given protein target without the constraints of a finite, pre-defined virtual library. By leveraging recent computational and cheminformatic advancements, AutoGrow4 is faster, more stable, and more modular than previous versions. Features such as docking-software compatibility, chemical filters, multithreading options, and selection methods have been expanded to support a wide range of user needs. This dissertation will cover the development and validation of AutoGrow4, as well as its application to poly (ADP-ribose) polymerase-1 (PARP-1). PARP-1 is a well-characterized DNA-damage recognition protein, and PARP-1 inhibition is an effective treatment for ovarian and breast cancers that are homologous-recombination (HR) deficient1–5. As a well-studied protein, PARP-1 is also an excellent drug target with which to validate AutoGrow4. Multiple crystallographic structures of PARP-1 bound to various PARP-1 inhibitors (PARPi) serve as positive controls for assessing the quality of AutoGrow4-generated compounds in terms of predicted binding affinity, chemical structure, and predicted protein-ligand interactions. This dissertation describes how I (1) generated novel potential PARPi with predicted binding affinities that surpass those of known PARPi; (2) validated AutoGrow4 as a tool for de novo drug design, lead optimization, and hypothesis generation, using PARP-1 as a test target; (3) contributed support to the growing notion that there is a need for HR-deficient cancer chemotherapies that do not rely on the same set of protein-ligand interactions typical of current PARPi; (4) generated novel potential PARPi that are predicted to bind to PARP-1 independent of a post-translational modification that is known to cause PARPi resistance; and (5) generated novel potential PARPi that are predicted to bind a secondary PARP-1 pocket that is distant from the primary catalytic site

An in-silico study of the type II NADH: Quinone Oxidoreductase (ndh2). A new anti-malaria drug target

Malaria is caused by Plasmodium parasites, spread to people through the bites of infected female Anopheles mosquitoes. This study focuses on all 5 (Plasmodium falciparum, Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale and Plasmodium vivax) parasites that cause malaria in humans. Africa is a developing continent, and it is the most affected with an estimation of 90% of more than 400 000 malaria-related deaths reported by the World Health Organization (WHO) report in 2020, in which 61% of that number are children under the ages of five. Malaria resistance was initially observed in early 1986 and with the progression of time anti-malarial drug resistance has only increased. As a result, there is a need to study the malarial proteins mechanism of action and identify alternative treatment strategies for this disease. Type II NADH: quinone oxidoreductase (NDH2) is a monotopic protein that catalyses the electron transfer from NADH to quinone via FAD without a proton-pumping activity, and functions as an initial enzyme, either in addition to or as an alternative to proton-pumping NADH dehydrogenase (complex I) in the respiratory chain of bacteria, archaea, and fungal and plant mitochondrial. The structures for the Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale and Plasmodium vivax were modelled from the crystal structure of Plasmodium falciparum (5JWA). Compounds from the South African natural compounds database (SANCDB) were docked against both the NDH2 crystal structure and modelled structures. By performing in silico screening the study aimed to find potential compounds that might interrupt the electron transfer to quinone therefore disturbing the enzyme‟s function and thereby possibly eliminating the plasmodium parasite. CHARMM-GUI was used to create the membrane (since this work is with membrane-bound proteins) and to orient the protein on the membrane using OPM server guidelines, the interface produced GROMACS topology files that were used in molecular dynamics simulations. Molecular dynamics simulations were performed in the Centre for high performance computing (CHPC) cluster under the CHEM0802 project and the trajectories produced were further analysed. In this work not only were hit compounds from SANCDB identified, but also differences in behaviour across species and in the presence or absence of the membrane were described. This highlights the need to include the correct protein environment when studying these systems.Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 202

Bioaccumulation potential of 'Meeker' and 'Willamette' raspberry (Rubus idaeus L.) fruits towards macro- and microelements and their nutritional evaluation

Raspberry (Rubus idaeus L.) is the most important type of berry fruit in the Republic of Serbia. The bioaccumulation factor (BF) for the elements detected in the fruits of the raspberry cultivars 'Willamette' and 'Meeker' was calculated to determine their bioaccumulation potential. In addition, the nutritional quality of fruits in relation to nutritionally essential elements was evaluated and compared with the recommended daily intake. For determining the concentrations of 19 macro- and microelements in fruits and the soil, the analytical technique of optical emission spectrometry with inductively coupled plasma was used. Among the analyzed elements, As, Cd, Co, Cr, Li and Mo were below the limit of detection in the fruits of both raspberry cultivars, whereas Na and Ni were detected only in fruits of the 'Meeker' cultivar. All analyzed elements were detected in the soil. The results of the work indicated the high potential of the studied cultivars to accumulate nutritional elements K and Ca. In both raspberry cultivars, there were no substantial differences in the bioaccumulation of most elements. However, two elements (B and Mn) can be singled out; the BF for B in the 'Willamette' fruit was 3 times lower compared to the BF in the 'Meeker' fruit, whereas, the BF value for Mn in the 'Willamette' fruit was almost 8 times higher compared to the BF value for the 'Meeker' fruit. Furthermore, the cultivars did not tend to accumulate potentially toxic elements such as Ba, Co, Cu and Ni. The nutritional evaluation revealed that the studied raspberry fruits are a good source of K, Ca, Mg, Fe, Mn and Cu. Based on the BF values, differences observed in the accumulation of B, Ba, Na, Ni and Mn may be attributed to the characteristics of the cultivars

Removal of antagonistic spindle forces can rescue metaphase spindle length and reduce chromosome segregation defects

Regular Abstracts - Tuesday Poster Presentations: no. 1925Metaphase describes a phase of mitosis where chromosomes are attached and oriented on the bipolar spindle for subsequent segregation at anaphase. In diverse cell types, the metaphase spindle is maintained at a relatively constant length. Metaphase spindle length is proposed to be regulated by a balance of pushing and pulling forces generated by distinct sets of spindle microtubules and their interactions with motors and microtubule-associated proteins (MAPs). Spindle length appears important for chromosome segregation fidelity, as cells with shorter or longer than normal metaphase spindles, generated through deletion or inhibition of individual mitotic motors or MAPs, showed chromosome segregation defects. To test the force balance model of spindle length control and its effect on chromosome segregation, we applied fast microfluidic temperature-control with live-cell imaging to monitor the effect of switching off different combinations of antagonistic forces in the fission yeast metaphase spindle. We show that spindle midzone proteins kinesin-5 cut7p and microtubule bundler ase1p contribute to outward pushing forces, and spindle kinetochore proteins kinesin-8 klp5/6p and dam1p contribute to inward pulling forces. Removing these proteins individually led to aberrant metaphase spindle length and chromosome segregation defects. Removing these proteins in antagonistic combination rescued the defective spindle length and, in some combinations, also partially rescued chromosome segregation defects. Our results stress the importance of proper chromosome-to-microtubule attachment over spindle length regulation for proper chromosome segregation.postprin