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Journal of Computer-aided Molecular Design

Michio Iwaoka, Toshiki Suzuki, Yuya Shoji, Kenichi Dedachi, Taku Shimosato, Toshiya Minezaki, Hironobu Hojo, Hiroyuki Onuki, Hiroshi Hirota
Single amino acid potential (SAAP) would be a prominent factor to determine peptide conformations. To prove this hypothesis, we previously developed SAAP force field for molecular simulation of polypeptides. In this study, the force field was renovated to SAAP3D force field by applying more accurate three-dimensional main-chain parameters, instead of the original two-dimensional ones, for the amino acids having a long side-chain. To demonstrate effectiveness of the SAAP3D force field, replica-exchange Monte Carlo (REMC) simulation was performed for two benchmark short peptides, chignolin (H-GYDPETGTWG-OH) and C-peptide (CHO-AETAAAKFLRAHA-NH2)...
November 17, 2017: Journal of Computer-aided Molecular Design
Antonia S J S Mey, Jordi Juárez Jiménez, Julien Michel
The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets...
November 13, 2017: Journal of Computer-aided Molecular Design
Oleksandr Yakovenko, Steven J M Jones
We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource ( ). The challenge was focused on the ligands of the farnesoid X receptor (FXR), a highly flexible nuclear receptor of the cholesterol derivative chenodeoxycholic acid. FXR is considered an important therapeutic target for metabolic, inflammatory, bowel and obesity related diseases (Expert Opin Drug Metab Toxicol 4:523-532, 2015), but in the context of this competition it is also interesting due to the significant ligand-induced conformational changes displayed by the protein...
November 13, 2017: Journal of Computer-aided Molecular Design
Yu Wang, Yanzhi Guo, Xuemei Pu, Menglong Li
Various bacterial pathogens can deliver their secreted substrates also called as effectors through type IV secretion systems (T4SSs) into host cells and cause diseases. Since T4SS secreted effectors (T4SEs) play important roles in pathogen-host interactions, identifying them is crucial to our understanding of the pathogenic mechanisms of T4SSs. A few computational methods using machine learning algorithms for T4SEs prediction have been developed by using features of C-terminal residues. However, recent studies have shown that targeting information can also be encoded in the N-terminal region of at least some T4SEs...
November 10, 2017: Journal of Computer-aided Molecular Design
Rui Duan, Xianjin Xu, Xiaoqin Zou
D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound...
November 10, 2017: Journal of Computer-aided Molecular Design
Matthew P Baumgartner, David A Evans
Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds...
November 10, 2017: Journal of Computer-aided Molecular Design
Christina Athanasiou, Sofia Vasilakaki, Dimitris Dellis, Zoe Cournia
Computer-aided drug design has become an integral part of drug discovery and development in the pharmaceutical and biotechnology industry, and is nowadays extensively used in the lead identification and lead optimization phases. The drug design data resource (D3R) organizes challenges against blinded experimental data to prospectively test computational methodologies as an opportunity for improved methods and algorithms to emerge. We participated in Grand Challenge 2 to predict the crystallographic poses of 36 Farnesoid X Receptor (FXR)-bound ligands and the relative binding affinities for two designated subsets of 18 and 15 FXR-bound ligands...
November 8, 2017: Journal of Computer-aided Molecular Design
Miki Akamatsu, Tudor I Oprea
This is the obituary for Toshio Fujita, pioneer of the quantitative structure activity relationship (QSAR) paradigm.
November 8, 2017: Journal of Computer-aided Molecular Design
Dzmitry Padhorny, David R Hall, Hanieh Mirzaei, Artem B Mamonov, Mohammad Moghadasi, Andrey Alekseenko, Dmitri Beglov, Dima Kozakov
Fast Fourier transform (FFT) based approaches have been successful in application to modeling of relatively rigid protein-protein complexes. Recently, we have been able to adapt the FFT methodology to treatment of flexible protein-peptide interactions. Here, we report our latest attempt to expand the capabilities of the FFT approach to treatment of flexible protein-ligand interactions in application to the D3R PL-2016-1 challenge. Based on the D3R assessment, our FFT approach in conjunction with Monte Carlo minimization off-grid refinement was among the top performing methods in the challenge...
November 3, 2017: Journal of Computer-aided Molecular Design
Arik Dahan, Milica Markovic, Shahar Keinan, Igor Kurnikov, Aaron Aponick, Ellen M Zimmermann, Shimon Ben-Shabat
Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation...
November 3, 2017: Journal of Computer-aided Molecular Design
Edson R A Oliveira, Ricardo B de Alencastro, Bruno A C Horta
Diseases caused by flaviviruses, such as dengue and zika, are globally recognized as major threats. During infection, a critical point in their replicative cycle is the maturation step, which occurs throughout the cellular exocytic pathway. This step is a pH-dependent process that involves the modification of the viral envelope by converting prM (pre-membrane) into M (membrane) proteins with the release of a "pr peptide". After this reaction, the pr peptides remain bound to the viral envelope while the virions cross the acidic trans-Golgi network, and are released only at neutral pH after secretion of the virus particles...
October 24, 2017: Journal of Computer-aided Molecular Design
Soumendranath Bhakat, Emil Åberg, Pär Söderhjelm
Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge...
October 20, 2017: Journal of Computer-aided Molecular Design
Phani Ghanakota, Heather A Carlson
NMR and X-ray crystallography are the two most widely used methods for determining protein structures. Our previous study examining NMR versus X-Ray sources of protein conformations showed improved performance with NMR structures when used in our Multiple Protein Structures (MPS) method for receptor-based pharmacophores (Damm, Carlson, J Am Chem Soc 129:8225-8235, 2007). However, that work was based on a single test case, HIV-1 protease, because of the rich data available for that system. New data for more systems are available now, which calls for further examination of the effect of different sources of protein conformations...
October 19, 2017: Journal of Computer-aided Molecular Design
Yushu Ge, Marc van der Kamp, Maturos Malaisree, Dan Liu, Yi Liu, Adrian J Mulholland
Cdc25 phosphatase B, a potential target for cancer therapy, is inhibited by a series of quinones. The binding site and mode of quinone inhibitors to Cdc25B remains unclear, whereas this information is important for structure-based drug design. We investigated the potential binding site of NSC663284 [DA3003-1 or 6-chloro-7-(2-morpholin-4-yl-ethylamino)-quinoline-5, 8-dione] through docking and molecular dynamics simulations. Of the two main binding sites suggested by docking, the molecular dynamics simulations only support one site for stable binding of the inhibitor...
October 9, 2017: Journal of Computer-aided Molecular Design
Ying-Duo Gao, Yuan Hu, Alejandro Crespo, Deping Wang, Kira A Armacost, James I Fells, Xavier Fradera, Hongwu Wang, Huijun Wang, Brad Sherborne, Andreas Verras, Zhengwei Peng
The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively...
October 6, 2017: Journal of Computer-aided Molecular Design
Shilva Kayastha, Ryo Kunimoto, Dragos Horvath, Alexandre Varnek, Jürgen Bajorath
The analysis of structure-activity relationships (SARs) becomes rather challenging when large and heterogeneous compound data sets are studied. In such cases, many different compounds and their activities need to be compared, which quickly goes beyond the capacity of subjective assessments. For a comprehensive large-scale exploration of SARs, computational analysis and visualization methods are required. Herein, we introduce a two-layered SAR visualization scheme specifically designed for increasingly large compound data sets...
October 6, 2017: Journal of Computer-aided Molecular Design
Hervé Hogues, Traian Sulea, Francis Gaudreault, Christopher R Corbeil, Enrico O Purisima
The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB...
October 5, 2017: Journal of Computer-aided Molecular Design
Bentley M Wingert, Rick Oerlemans, Carlos J Camacho
The goal of virtual screening is to generate a substantially reduced and enriched subset of compounds from a large virtual chemistry space. Critical in these efforts are methods to properly rank the binding affinity of compounds. Prospective evaluations of ranking strategies in the D3R grand challenges show that for targets with deep pockets the best correlations (Spearman ρ ~ 0.5) were obtained by our submissions that docked compounds to the holo-receptors with the most chemically similar ligand. On the other hand, for targets with open pockets using multiple receptor structures is not a good strategy...
September 16, 2017: Journal of Computer-aided Molecular Design
Maria Kadukova, Sergei Grudinin
The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein-ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments...
September 14, 2017: Journal of Computer-aided Molecular Design
Manon Réau, Florent Langenfeld, Jean-François Zagury, Matthieu Montes
The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4...
September 14, 2017: Journal of Computer-aided Molecular Design
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