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Journal of Computer-aided Molecular Design

Yiğitcan Eken, Prajay Patel, Thomas Díaz, Michael R Jones, Angela K Wilson
In this effort in the SAMPL6 host-guest binding challenge, a combination of molecular dynamics and quantum mechanical methods were used to blindly predict the host-guest binding free energies of a series of cucurbit[8]uril (CB8), octa-acid (OA), and tetramethyl octa-acid (TEMOA) hosts bound to various guest molecules in aqueous solution. Poses for host-guest systems were generated via molecular dynamics (MD) simulations and clustering analyses. The binding free energies for the structures obtained via cluster analyses of MD trajectories were calculated using the MMPBSA method and density functional theory (DFT) with the inclusion of Grimme's dispersion correction, an implicit solvation model to model the aqueous solution, and the resolution-of-the-identity (RI) approximation (MMPBSA, RI-B3PW91-D3, and RI-B3PW91, respectively)...
September 17, 2018: Journal of Computer-aided Molecular Design
Xibing He, Viet H Man, Beihong Ji, Xiang-Qun Xie, Junmei Wang
We participated in the Cathepsin S (CatS) sub-challenge of the Drug Design Data Resource (D3R) Grand Challenge 3 (GC3) in 2017 to blindly predict the binding poses of 24 CatS-bound ligands, the binding affinity ranking of 136 ligands, and the binding free energies of a subset of 33 ligands in Stage 1A and Stage 2. Our submitted predictions ranked relatively well compared to the submissions from other participants. Here we present our methodologies used in the challenge. For the binding pose prediction, we employed the Glide module in the Schrodinger Suite 2017 and AutoDock Vina...
September 14, 2018: Journal of Computer-aided Molecular Design
Irena Majerz
Dimers of furan, 2,3-dihydrofuran, 2,5-dihydrofuran and tetrahydrofuran were investigated with the use of theoretical methods to determine the interactions that keep the molecules together. The QTAIM and NCI methods confirmed that for furan dimers the C-H⋯O hydrogen bond and stacking interactions can form the dimers with similar energy. For 2,3-dihydrofuran, 2,5-dihydrofuran and tetrahydrofuran, the decisive mechanism of dimer formation is the stacking interaction between the furan rings.
September 14, 2018: Journal of Computer-aided Molecular Design
Ludovic Chaput, Edithe Selwa, Eddy Elisée, Bogdan I Iorga
During the last few years, we have developed a docking protocol involving two steps: (i) the choice of the most appropriate docking software and parameters for the system of interest using structural and functional information available in public databases (PDB, ChEMBL, PubChem Assay, BindingDB, etc.); (ii) the docking of ligand dataset to provide a prediction for the binding modes and ranking of ligands. We applied this protocol to the D3R Grand Challenge 3 dataset containing cathepsin S (CatS) inhibitors...
September 11, 2018: Journal of Computer-aided Molecular Design
Octav Caldararu, Martin A Olsson, Majda Misini Ignjatović, Meiting Wang, Ulf Ryde
We have estimated free energies for the binding of eight carboxylate ligands to two variants of the octa-acid deep-cavity host in the SAMPL6 blind-test challenge (with or without endo methyl groups on the four upper-rim benzoate groups, OAM and OAH, respectively). We employed free-energy perturbation (FEP) for relative binding energies at the molecular mechanics (MM) and the combined quantum mechanical (QM) and MM (QM/MM) levels, the latter obtained with the reference-potential approach with QM/MM sampling for the MM → QM/MM FEP...
September 10, 2018: Journal of Computer-aided Molecular Design
Noriyuki Yamaotsu, Shuichi Hirono
Here, we propose an in silico fragment-mapping method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this method, we created a database named Canonical Subsite-Fragment DataBase (CSFDB) and developed a knowledge-based fragment-mapping program, Fsubsite. CSFDB consists of various pairs of subsite-fragments derived from X-ray crystal structures of known protein-ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB...
September 8, 2018: Journal of Computer-aided Molecular Design
Yaping Li, Yinglan Pu, Hui Liu, Li Zhang, Xingyong Liu, Yan Li, Zhili Zuo
Wee1 plays a critical role in the arrest of G2/M cell cycle for DNA repair before entering mitosis. Many cancer cells have been identified as overexpression of Wee1. In this research, pharmacophore modeling, molecular docking and molecular dynamics simulation approaches were constructed to identify novel potential Wee1 inhibitors. A compound 8 was found to have a novel skeleton against Wee1 with an IC50 value of 22.32 µM and a Ki value of 13.11 µM. Kinetic assays were employed to evaluate the compound 8 as a competitive inhibitor...
September 4, 2018: Journal of Computer-aided Molecular Design
Piya Patra, Mahua Ghosh, Raja Banerjee, Jaydeb Chakrabarti
Anion binding Cα NN motif is found in functionally important regions of protein structures. This motif based only on backbone atoms from three adjacent residues, recognizes free sulphate or phosphate ion as well as phosphate groups in nucleotides and in a variety of cofactors. The mode of anion recognition and microscopic picture of binding interaction remains unclear. Here we perform self-consistent quantum chemical calculations considering sulphate and phosphate bound Cα NN motif fragments from crystal structures of functional proteins in order to figure out microscopic basis of anion recognition...
September 4, 2018: Journal of Computer-aided Molecular Design
Michael Zhenin, Malkeet Singh Bahia, Gilles Marcou, Alexandre Varnek, Hanoch Senderowitz, Dragos Horvath
Ligand affinity prediction from docking simulations is usually performed by means of highly empirical and diverse protocols. These protocols often involve the re-scoring of poses generated by a force field (FF) based Hamiltonian to provide either estimated binding affinities-or alternatively, some empirical goodness score. Re-scoring is performed by so-called scoring functions-typically, a reweighted sum of FF terms augmented by additional terms (e.g., desolvation/entropic penalty, hydrophobicity, aromatic interactions etc...
September 1, 2018: Journal of Computer-aided Molecular Design
Jie Chen, Xiao Lin, Kyoung Jin Park, Kang Ro Lee, Hyun-Ju Park
The protein lysine methyltransferase G9a, which controls gene expression by epigenetic regulation of H3K9 methylation, is related to various human diseases, including cancer, drug addiction, and mental retardation. In recent years, genetic, biological, and physiological evidence has established G9a inhibitors as potential chemotherapeutic agents for cancer treatment. In this study, we identified protoberberine alkaloid pseudodehydrocorydaline (CT13) as a novel G9a inhibitor, by structure-based virtual screening of in-house library containing natural product compounds...
August 31, 2018: Journal of Computer-aided Molecular Design
Michail Papadourakis, Stefano Bosisio, Julien Michel
In the context of the SAMPL6 challenges, series of blinded predictions of standard binding free energies were made with the SOMD software for a dataset of 27 host-guest systems featuring two octa-acids hosts (OA and TEMOA) and a cucurbituril ring (CB8) host. Three different models were used, ModelA computes the free energy of binding based on a double annihilation technique; ModelB additionally takes into account long-range dispersion and standard state corrections; ModelC additionally introduces an empirical correction term derived from a regression analysis of SAMPL5 predictions previously made with SOMD...
August 29, 2018: Journal of Computer-aided Molecular Design
Lin Frank Song, Nupur Bansal, Zheng Zheng, Kenneth M Merz
Accurately predicting receptor-ligand binding free energies is one of the holy grails of computational chemistry with many applications in chemistry and biology. Many successes have been reported, but issues relating to sampling and force field accuracy remain significant issues affecting our ability to reliably calculate binding free energies. In order to explore these issues in more detail we have examined a series of small host-guest complexes from the SAMPL6 blind challenge, namely octa-acids (OAs)-guest complexes and Curcurbit[8]uril (CB8)-guest complexes...
August 24, 2018: Journal of Computer-aided Molecular Design
Philipp Pracht, Rainer Wilcken, Anikó Udvarhelyi, Stephane Rodde, Stefan Grimme
Recent advances in the development of low-cost quantum chemical methods have made the prediction of conformational preferences and physicochemical properties of medium-sized drug-like molecules routinely feasible, with significant potential to advance drug discovery. In the context of the SAMPL6 challenge, macroscopic pKa values were blindly predicted for a set of 24 of such molecules. In this paper we present two similar quantum chemical based approaches based on the high accuracy calculation of standard reaction free energies and the subsequent determination of those pKa values via a linear free energy relationship...
August 23, 2018: Journal of Computer-aided Molecular Design
Tom Dixon, Samuel D Lotz, Alex Dickson
Interest in ligand binding kinetics has been growing rapidly, as it is being discovered in more and more systems that ligand residence time is the crucial factor governing drug efficacy. Many enhanced sampling methods have been developed with the goal of predicting ligand binding rates ([Formula: see text]) and/or ligand unbinding rates ([Formula: see text]) through explicit simulation of ligand binding pathways, and these methods work by very different mechanisms. Although there is not yet a blind challenge for ligand binding kinetics, here we take advantage of experimental measurements and rigorously computed benchmarks to compare estimates of [Formula: see text] calculated as the ratio of two rates: [Formula: see text]...
August 23, 2018: Journal of Computer-aided Molecular Design
Panagiotis I Koukos, Li C Xue, Alexandre M J J Bonvin
We report the performance of HADDOCK in the 2018 iteration of the Grand Challenge organised by the D3R consortium. Building on the findings of our participation in last year's challenge, we significantly improved our pose prediction protocol which resulted in a mean RMSD for the top scoring pose of 3.04 and 2.67 Å for the cross-docking and self-docking experiments respectively, which corresponds to an overall success rate of 63% and 71% when considering the top1 and top5 models respectively. This performance ranks HADDOCK as the 6th and 3rd best performing group (excluding multiple submissions from a same group) out of a total of 44 and 47 submissions respectively...
August 20, 2018: Journal of Computer-aided Molecular Design
Piero Procacci, Massimiliano Guarrasi, Guido Guarnieri
In this paper, we compute, by means of a non equilibrium alchemical technique, called fast switching double annihilation methods (FSDAM), the absolute standard dissociation free energies of the the octa acids host-guest systems in the SAMPL6 challenge initiative. FSDAM is based on the production of canonical configurations of the bound and unbound states via enhanced sampling and on the subsequent generation of hundreds of fast non-equilibrium ligand annihilation trajectories. The annihilation free energies of the ligand when bound to the receptor and in bulk solvent are obtained from the collection of work values using an estimate based on the Crooks theorem for driven non equilibrium processes...
August 20, 2018: Journal of Computer-aided Molecular Design
Qiao Zeng, Michael R Jones, Bernard R Brooks
In this work, quantum mechanical methods were used to predict the microscopic and macroscopic pKa values for a set of 24 molecules as a part of the SAMPL6 blind challenge. The SMD solvation model was employed with M06-2X and different basis sets to evaluate three pKa calculation schemes (direct, vertical, and adiabatic). The adiabatic scheme is the most accurate approach (RMSE = 1.40 pKa units) and has high correlation (R2  = 0.93), with respect to experiment. This approach can be improved by applying a linear correction to yield an RMSE of 0...
August 20, 2018: Journal of Computer-aided Molecular Design
D Sam Paul, N Gautham
We have earlier reported the iMOLSDOCK technique to perform 'induced-fit' peptide-protein docking. iMOLSDOCK uses the mutually orthogonal Latin squares (MOLSs) technique to sample the conformation and the docking pose of the small molecule ligand and also the flexible residues of the receptor protein, and arrive at the optimum pose and conformation. In this paper we report the extension carried out in iMOLSDOCK to dock nonpeptide small molecule ligands to receptor proteins. We have benchmarked and validated iMOLSDOCK with a dataset of 34 protein-ligand complexes as well as with Astex Diverse dataset, with nonpeptide small molecules as ligands...
August 20, 2018: Journal of Computer-aided Molecular Design
Duc Duy Nguyen, Zixuan Cang, Kedi Wu, Menglun Wang, Yin Cao, Guo-Wei Wei
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affinity prediction and ranking in the last two D3R Grand Challenges in computer-aided drug design and discovery. D3R Grand Challenge 2 focused on the pose prediction, binding affinity ranking and free energy prediction for Farnesoid X receptor ligands. Our models obtained the top place in absolute free energy prediction for free energy set 1 in stage 2...
August 16, 2018: Journal of Computer-aided Molecular Design
Polo C-H Lam, Ruben Abagyan, Maxim Totrov
In context of D3R Grand Challenge 3 we have investigated several ligand activity prediction protocols that combined elements of a physics-based energy function (ICM VLS score) and the knowledge-based Atomic Property Field 3D QSAR approach. Activity prediction models utilized poses produced by ICM-Dock with ligand bias and 4D receptor conformational ensembles (LigBEnD). Hybrid APF/P (APF/Physics) models were superior to pure physics- or knowledge-based models in our preliminary tests using rigorous three-fold clustered cross-validation and later proved successful in the blind prediction for D3R GC3 sets, consistently performing well across four different targets...
August 9, 2018: Journal of Computer-aided Molecular Design
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