
显示样式: 排序: IF: - GO 导出
-
In silico and in vitro anti-AChE activity investigations of constituents from Mytragyna speciosa for Alzheimer’s disease treatment J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-13 Wansiri Innok, Asadhawut Hiranrat, Netnapa Chana, Thanyada Rungrotmongkol, Panita Kongsune
-
Towards a converged strategy for including microsolvation in reaction mechanism calculations J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-09 Rebecca Sure, Moad el Mahdali, Alex Plajer, Peter Deglmann
A major part of chemical conversions is carried out in the fluid phase, where an accurate modeling of the involved reactions requires to also take into account solvation effects. Implicit solvation models often cover these effects with sufficient accuracy but can fail drastically when specific solvent–solute interactions are important. In those cases, microsolvation, i.e., the explicit inclusion of
-
Comparing predictive ability of QSAR/QSPR models using 2D and 3D molecular representations J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-04 Akinori Sato, Tomoyuki Miyao, Swarit Jasial, Kimito Funatsu
Quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) models predict biological activity and molecular property based on the numerical relationship between chemical structures and activity (property) values. Molecular representations are of importance in QSAR/QSPR analysis. Topological information of molecular structures is usually utilized (2D
-
Predicting PAMPA permeability using the 3D-RISM-KH theory: are we there yet? J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-04 Dipankar Roy, Devjyoti Dutta, David S. Wishart, Andriy Kovalenko
The parallel artificial membrane permeability assay (PAMPA), a non-cellular lab-based assay, is extensively used to measure the permeability of pharmaceutical compounds. PAMPA experiments provide a working mimic of a molecule passing through cells and PAMPA values are widely used to estimate drug absorption parameters. There is an increased interest in developing computational methods to predict PAMPA
-
Overview of the SAMPL6 p K a challenge: evaluating small molecule microscopic and macroscopic p K a predictions J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-04 Mehtap Işık, Ariën S. Rustenburg, Andrea Rizzi, M. R. Gunner, David L. Mobley, John D. Chodera
The prediction of acid dissociation constants (pKa) is a prerequisite for predicting many other properties of a small molecule, such as its protein–ligand binding affinity, distribution coefficient (log D), membrane permeability, and solubility. The prediction of each of these properties requires knowledge of the relevant protonation states and solution free energy penalties of each state. The SAMPL6
-
SAMPL7 blind predictions using nonequilibrium alchemical approaches J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-04 Piero Procacci, Guido Guarnieri
In the context of the SAMPL7 challenge, we computed, employing a non-equilibrium (NE) alchemical technique, the standard binding free energy of two series of host-guest systems, involving as a host the Isaac’s TrimerTrip, a Cucurbituril-like open cavitand, and the Gilson’s Cyclodextrin derivatives. The adopted NE alchemy combines enhanced sampling molecular dynamics simulations with driven fast out-of-equilibrium
-
IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-04 Md Mehedi Hasan, Md Ashad Alam, Watshara Shoombuatong, Hiroyuki Kurata
Redox-sensitive cysteine (RSC) thiol contributes to many biological processes. The identification of RSC plays an important role in clarifying some mechanisms of redox-sensitive factors; nonetheless, experimental investigation of RSCs is expensive and time-consuming. The computational approaches that quickly and accurately identify candidate RSCs using the sequence information are urgently needed.
-
SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2021-01-04 Martin Amezcua, Léa El Khoury, David L. Mobley
The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in test sets selected, and even lack of high quality experimental data. SAMPL blind challenges
-
QSAR and molecular docking for the search of AOX inhibitors: a rational drug discovery approach J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-12-08 Alicia Rosell-Hidalgo, Luke Young, Anthony L. Moore, Taravat Ghafourian
The alternative oxidase (AOX) is a monotopic diiron carboxylate protein that catalyses the oxidation of ubiquinol and the reduction of oxygen to water. Although a number of AOX inhibitors have been discovered, little is still known about the ligand–protein interaction and essential chemical characteristics of compounds required for a potent inhibition. Furthermore, owing to the rapidly growing resistance
-
Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-11-24 Yuriy Khalak, Gary Tresadern, Bert L. de Groot, Vytautas Gapsys
In the current work we report on our participation in the SAMPL7 challenge calculating absolute free energies of the host–guest systems, where 2 guest molecules were probed against 9 hosts-cyclodextrin and its derivatives. Our submission was based on the non-equilibrium free energy calculation protocol utilizing an averaged consensus result from two force fields (GAFF and CGenFF). The submitted prediction
-
SAMPL7: Host–guest binding prediction by molecular dynamics and quantum mechanics J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-11-05 Yiğitcan Eken, Nuno M. S. Almeida, Cong Wang, Angela K. Wilson
Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges provide routes to compare chemical quantities determined using computational chemistry approaches to experimental measurements that are shared after the competition. For this effort, several computational methods have been used to calculate the binding energies of Octa Acid (OA) and exo-Octa Acid (exoOA) host–guest systems
-
AMOEBA binding free energies for the SAMPL7 TrimerTrip host–guest challenge J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-11-03 Yuanjun Shi, Marie L. Laury, Zhi Wang, Jay W. Ponder
As part of the SAMPL7 host–guest binding challenge, the AMOEBA force field was applied to calculate the absolute binding free energy for 16 charged organic ammonium guests to the TrimerTrip host, a recently reported acyclic cucurbituril-derived clip host structure with triptycene moieties at its termini. Here we report binding free energy calculations for this system using the AMOEBA polarizable atomic
-
The critical role of QM/MM X-ray refinement and accurate tautomer/protomer determination in structure-based drug design J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-27 Oleg Y. Borbulevych, Roger I. Martin, Lance M. Westerhoff
Conventional protein:ligand crystallographic refinement uses stereochemistry restraints coupled with a rudimentary energy functional to ensure the correct geometry of the model of the macromolecule—along with any bound ligand(s)—within the context of the experimental, X-ray density. These methods generally lack explicit terms for electrostatics, polarization, dispersion, hydrogen bonds, and other key
-
Supervised molecular dynamics for exploring the druggability of the SARS-CoV-2 spike protein J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-26 Giuseppe Deganutti, Filippo Prischi, Christopher A. Reynolds
The recent outbreak of the respiratory syndrome-related coronavirus (SARS-CoV-2) is stimulating an unprecedented scientific campaign to alleviate the burden of the coronavirus disease (COVID-19). One line of research has focused on targeting SARS-CoV-2 proteins fundamental for its replication by repurposing drugs approved for other diseases. The first interaction between the virus and the host cell
-
Combined experimental and quantum mechanical elucidation of the synthetically accessible stereoisomers of Hydroxyestradienone (HED), the starting material for vilaprisan synthesis J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-23 Tobias A. Plöger, Stefan Koep, Hans-Christian Militzer, Andreas H. Göller
Selective progesterone receptor modulators are promising therapeutic options for the treatment of uterine fibroids. Vilaprisan, a new chemical entity that was discovered at Bayer is currently in clinical development. In this study we provide a combined experimental and quantum chemical approach providing the data that allowed to present hydroxyestradienone as an acceptable starting material for drug
-
Quantum–mechanical property prediction of solvated drug molecules: what have we learned from a decade of SAMPL blind prediction challenges? J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-20 Nicolas Tielker, Lukas Eberlein, Gerhard Hessler, K. Friedemann Schmidt, Stefan Güssregen, Stefan M. Kast
Joint academic–industrial projects supporting drug discovery are frequently pursued to deploy and benchmark cutting-edge methodical developments from academia in a real-world industrial environment at different scales. The dimensionality of tasks ranges from small molecule physicochemical property assessment over protein–ligand interaction up to statistical analyses of biological data. This way, method
-
Mutation-mediated influences on binding of anaplastic lymphoma kinase to crizotinib decoded by multiple replica Gaussian accelerated molecular dynamics J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-19 Jianzhong Chen, Wei Wang, Haibo Sun, Laixue Pang, Baohua Yin
Anaplastic lymphoma kinase (ALK) has been thought to be a prospective target of anti-drug resistance design in treatment of tumors and specific neuron diseases. It is highly useful for the seeking of possible strategy alleviating drug resistance to probe the mutation-mediated effect on binding of inhibitors to ALK. In the current work, multiple replica Gaussian accelerated molecular dynamics (MR-GaMD)
-
Application of target repositioning and in silico screening to exploit fatty acid binding proteins (FABPs) from Echinococcus multilocularis as possible drug targets J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-17 Julián A. Bélgamo, Lucas N. Alberca, Jorge L. Pórfido, Franco N. Caram Romero, Santiago Rodriguez, Alan Talevi, Betina Córsico, Gisela R. Franchini
Fatty acid binding proteins (FABPs) are small intracellular proteins that reversibly bind fatty acids and other hydrophobic ligands. In cestodes, due to their inability to synthesise fatty acids and cholesterol de novo, FABPs, together with other lipid binding proteins, have been proposed as essential, involved in the trafficking and delivery of such lipophilic metabolites. Pharmacological agents that
-
Experimental characterization of the association of β-cyclodextrin and eight novel cyclodextrin derivatives with two guest compounds J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-10 K. Kellett, D. R. Slochower, M. Schauperl, B. M. Duggan, M. K. Gilson
We investigate the binding of native β-cyclodextrin (β-CD) and eight novel β-CD derivatives with two different guest compounds, using isothermal calorimetry and 2D NOESY NMR. In all cases, the stoichiometry is 1:1 and binding is exothermic. Overall, modifications at the 3′ position of β-CD, which is at the secondary face, weaken binding by several kJ/mol relative to native β-CD, while modifications
-
SAMPL7 TrimerTrip host–guest binding affinities from extensive alchemical and end-point free energy calculations J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-10 Zhe Huai, Huaiyu Yang, Xiao Li, Zhaoxi Sun
The prediction of host–guest binding affinities with computational modelling is still a challenging task. In the 7th statistical assessment of the modeling of proteins and ligands (SAMPL) challenge, a new host named TrimerTrip was synthesized and the thermodynamic parameters of 16 structurally diverse guests binding to the host were characterized. In the TrimerTrip-guest challenge, only structures
-
Combining fragment docking with graph theory to improve ligand docking for homology model structures J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-09 Sara Sarfaraz, Iqra Muneer, Haiyan Liu
Computational protein–ligand docking is well-known to be prone to inaccuracies in input receptor structures, and it is challenging to obtain good docking results with computationally predicted receptor structures (e.g. through homology modeling). Here we introduce a fragment-based docking method and test if it reduces requirements on the accuracy of an input receptor structures relative to non-fragment
-
Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-09 Tobias Morawietz, Nongnuch Artrith
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in the use of machine learning (ML) methods for accelerated simulations based on a quantum mechanical (QM) description of the system. We show how recent
-
DeepCOMO: from structure-activity relationship diagnostics to generative molecular design using the compound optimization monitor methodology J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-05 Dimitar Yonchev, Jürgen Bajorath
The compound optimization monitor (COMO) approach was originally developed as a diagnostic approach to aid in evaluating development stages of analog series and progress made during lead optimization. COMO uses virtual analog populations for the assessment of chemical saturation of analog series and has been further developed to bridge between optimization diagnostics and compound design. Herein, we
-
Covalent inhibitor reactivity prediction by the electrophilicity index—in and out of scope J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-05 Markus R. Hermann, Alexander Pautsch, Marc A. Grundl, Alexander Weber, Christofer S. Tautermann
Drug discovery is an expensive and time-consuming process. To make this process more efficient quantum chemistry methods can be employed. The electrophilicity index is one property that can be calculated by quantum chemistry methods, and if calculated correctly gives insight into the reactivity of covalent inhibitors. Herein we present the usage of the electrophilicity index on three common warheads
-
Interactions of GF-17 derived from LL-37 antimicrobial peptide with bacterial membranes: a molecular dynamics simulation study J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-10-03 Hossein Aghazadeh, Mokhtar Ganjali Koli, Reza Ranjbar, Kamran Pooshang Bagheri
Human cathelicidin LL-37 has recently attracted interest as a potential therapeutic agent, mostly because of its ability to kill a wide variety of pathogens and cancer cells. In this study, we used molecular dynamics simulation aimed to get insights that help to correlate with the antibacterial activity of previously designed LL-37 anticancer derivative (i.e. GF-17). Two independent molecular dynamics
-
Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-09-24 Teresa Danielle Bergazin,Ido Y Ben-Shalom,Nathan M Lim,Sam C Gill,Michael K Gilson,David L Mobley
Water molecules can be found interacting with the surface and within cavities in proteins. However, water exchange between bulk and buried hydration sites can be slow compared to simulation timescales, thus leading to the inefficient sampling of the locations of water. This can pose problems for free energy calculations for computer-aided drug design. Here, we apply a hybrid method that combines nonequilibrium
-
ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-09-23 Mst Shamima Khatun,Md Mehedi Hasan,Watshara Shoombuatong,Hiroyuki Kurata
A proinflammatory peptide (PIP) is a type of signaling molecules that are secreted from immune cells, which contributes to the first line of defense against invading pathogens. Numerous experiments have shown that PIPs play an important role in human physiology such as vaccines and immunotherapeutic drugs. Considering high-throughput laboratory methods that are time consuming and costly, effective
-
An online repository of solvation thermodynamic and structural maps of SARS-CoV-2 targets. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-09-12 Brian Olson,Anthony Cruz,Lieyang Chen,Mossa Ghattas,Yeonji Ji,Kunhui Huang,Steven Ayoub,Tyler Luchko,Daniel J McKay,Tom Kurtzman
SARS-CoV-2 recently jumped species and rapidly spread via human-to-human transmission to cause a global outbreak of COVID-19. The lack of effective vaccine combined with the severity of the disease necessitates attempts to develop small molecule drugs to combat the virus. COVID19_GIST_HSA is a freely available online repository to provide solvation thermodynamic maps of COVID-19-related protein small
-
Prediction of ligand binding mode among multiple cross-docking poses by molecular dynamics simulations. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-09-01 Kai Liu,Hironori Kokubo
We propose a method to identify the correct binding mode of a ligand with a protein among multiple predicted docking poses. Our method consists of two steps. First, five independent MD simulations with different initial velocities are performed for each docking pose, in order to evaluate its stability. If the root-mean-square deviations (RMSDs) of heavy atoms from the docking pose are larger than a
-
Addressing free fatty acid receptor 1 (FFAR1) activation using supervised molecular dynamics. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-27 Silvia Atanasio,Giuseppe Deganutti,Christopher A Reynolds
The free fatty acid receptor 1 (FFAR1, formerly GPR40), is a potential G protein-coupled receptor (GPCR) target for the treatment of type 2 diabetes mellitus (T2DM), as it enhances glucose-dependent insulin secretion upon activation by endogenous long-chain free fatty acids. The presence of two allosterically communicating binding sites and the lack of the conserved GPCR structural motifs challenge
-
Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR-Bench dataset. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-27 Mei Qian Yau,Abigail L Emtage,Jason S E Loo
Recent breakthroughs in G protein-coupled receptor (GPCR) crystallography and the subsequent increase in number of solved GPCR structures has allowed for the unprecedented opportunity to utilize their experimental structures for structure-based drug discovery applications. As virtual screening represents one of the primary computational methods used for the discovery of novel leads, the GPCR-Bench
-
Design and tests of prospective property predictions for novel antimalarial 2-aminopropylaminoquinolones. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-24 Robert D Clark,Denise N Morris,Gary Chinigo,Michael S Lawless,Jacques Prudhomme,Karine G Le Roch,Maria José Lafuente,Santiago Ferrer,Francisco Javier Gamo,Robert Gadwood,Walter S Woltosz
There is a pressing need to improve the efficiency of drug development, and nowhere is that need more clear than in the case of neglected diseases like malaria. The peculiarities of pyrimidine metabolism in Plasmodium species make inhibition of dihydroorotate dehydrogenase (DHODH) an attractive target for antimalarial drug design. By applying a pair of complementary quantitative structure–activity
-
Pattern-free generation and quantum mechanical scoring of ring-chain tautomers. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-24 Daniel S Levine,Mark A Watson,Leif D Jacobson,Claire E Dickerson,Haoyu S Yu,Art D Bochevarov
In contrast to the computational generation of conventional tautomers, the analogous operation that would produce ring-chain tautomers is rarely available in cheminformatics codes. This is partly due to the perceived unimportance of ring-chain tautomerism and partly because specialized algorithms are required to realize the non-local proton transfers that occur during ring-chain rearrangement. Nevertheless
-
Monomer structure fingerprints: an extension of the monomer composition version for peptide databases. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-19 Ammar Abdo,Eissa Ghaleb,Naser K A Alajmi,Maude Pupin
Previously a fingerprint based on monomer composition (MCFP) of nonribosomal peptides (NRPs) has been introduced. MCFP is a novel method for obtaining a representative description of NRP structures from their monomer composition in a fingerprint form. An effective screening and prediction of biological activities has been obtained from Norine NRPs database. In this paper, we present an extension of
-
ReSCoSS: a flexible quantum chemistry workflow identifying relevant solution conformers of drug-like molecules. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-17 Anikó Udvarhelyi,Stephane Rodde,Rainer Wilcken
-
SAMPL7 TrimerTrip host-guest binding poses and binding affinities from spherical-coordinates-biased simulations. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-08-10 Zhaoxi Sun
Host–guest binding remains a major challenge in modern computational modelling. The newest 7th statistical assessment of the modeling of proteins and ligands (SAMPL) challenge contains a new series of host–guest systems. The TrimerTrip host binds to 16 structurally diverse guests. Previously, we have successfully employed the spherical coordinates as the collective variables coupled with the enhanced
-
Benchmarking GPCR homology model template selection in combination with de novo loop generation. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-31 Gregory L Szwabowski,Paige N Castleman,Chandler K Sears,Lee H Wink,Judith A Cole,Daniel L Baker,Abby L Parrill
G protein-coupled receptors (GPCR) comprise the largest family of membrane proteins and are of considerable interest as targets for drug development. However, many GPCR structures remain unsolved. To address the structural ambiguity of these receptors, computational tools such as homology modeling and loop modeling are often employed to generate predictive receptor structures. Here we combined both
-
Modeling Epac1 interactions with the allosteric inhibitor AM-001 by co-solvent molecular dynamics. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-22 Marianna Bufano,Marion Laudette,Jean-Paul Blondeau,Frank Lezoualc'h,Marianna Nalli,Romano Silvestri,Andrea Brancale,Antonio Coluccia
The exchange proteins activated by cAMP (EPAC) are implicated in a large variety of physiological processes and they are considered as promising targets for a wide range of therapeutic applications. Several recent reports provided evidence for the therapeutic effectiveness of the inhibiting EPAC1 activity cardiac diseases. In that context, we recently characterized a selective EPAC1 antagonist named
-
Flexi-pharma: a molecule-ranking strategy for virtual screening using pharmacophores from ligand-free conformational ensembles. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-12 Isaias Lans,Karen Palacio-Rodríguez,Claudio N Cavasotto,Pilar Cossio
Computer-aided strategies are useful for reducing the costs and increasing the success-rate in drug discovery. Among these strategies, methods based on pharmacophores (an ensemble of electronic and steric features representing the target active site) are efficient to implement over large compound libraries. However, traditional pharmacophore-based methods require knowledge of active compounds or ligand–receptor
-
Phenylalkylamines in calcium channels: computational analysis of experimental structures. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-10 Denis B Tikhonov,Lianyun Lin,Daniel S C Yang,Zhiguang Yuchi,Boris S Zhorov
Experimental 3D structures of calcium channels with phenylalkylamines (PAAs) provide basis for further analysis of atomic mechanisms of these important cardiovascular drugs. In the crystal structure of the engineered calcium channel CavAb with Br-verapamil and in the cryo-EM structure of the Cav1.1 channel with verapamil, the ligands bind in the inner pore. However, there are significant differences
-
A binding mode hypothesis for prothioconazole binding to CYP51 derived from first principles quantum chemistry. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-08 Michael Edmund Beck,Jacopo Negroni,Svend Matthiesen,Michael Kohnen,Christoph Riplinger
In order to assess safety and efficacy of small molecule drugs as well as agrochemicals, it is key to understanding the nature of protein–ligand interaction on an atomistic level. Prothioconazole (PTZ), although commonly considered to be an azole-like inhibitor of sterol 14-α demethylase (CYP51), differs from classical azoles with respect to how it binds its target. The available evidence is only indirect
-
An activity prediction model for steroidal and triterpenoidal inhibitors of Acetylcholinesterase enzyme. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-07 José L Borioni,Valeria Cavallaro,Adriana B Pierini,Ana P Murray,Alicia B Peñéñory,Marcelo Puiatti,Manuela E García
Nowadays, the importance of computational methods in the design of therapeutic agents in a more efficient way is indisputable. Particularly, these methods have been important in the design of novel acetylcholinesterase enzyme inhibitors related to Alzheimer’s disease. In this sense, in this report a computational model of linear prediction of acetylcholinesterase inhibitory activity of steroids and
-
Investigations on the E/Z-isomerism of neonicotinoids. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-02 Michael Schindler
We investigate the minimum-energy path for the rotation of formal C=N double bonds in molecules with guanidine-like substructures as present in the chemical class of neonicotinoids. The transitions between the E- and Z-isomers of several neonicotinoids using scans of the torsional potential energy hypersurfaces are quantified at the DFT-level of theory. The validity of using this ansatz is checked
-
Novel phosphatidylinositol 4-kinases III beta (PI4KIIIβ) inhibitors discovered by virtual screening using free energy models. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-30 Natalie M Colodette,Lucas S Franco,Rodolfo C Maia,Harold H Fokoue,Carlos Mauricio R Sant'Anna,Eliezer J Barreiro
Herein, the LASSBio Chemical Library is presented as a valuable source of compounds for screening to identify hits suitable for subsequent hit-to-lead optimization stages. A feature of the LASSBio Chemical Library worth highlighting is the fact that it is a smart library designed by medicinal chemists with pharmacological activity as the main priority. The great majority of the compounds part of this
-
Distinct binding of cetirizine enantiomers to human serum albumin and the human histamine receptor H1. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-23 Almudena Perona,M Piedad Ros,Alberto Mills,Antonio Morreale,Federico Gago
Cetirizine, a major metabolite of hydroxyzine, became a marketed second-generation H1 antihistamine that is orally active and has a rapid onset of action, long duration of effects and a very good safety record at recommended doses. The approved drug is a racemic mixture of (S)-cetirizine and (R)-cetirizine, the latter being the levorotary enantiomer that also exists in the market as a third-generation
-
Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-16 Phasit Charoenkwan,Chanin Nantasenamat,Md Mehedi Hasan,Watshara Shoombuatong
Phage virion protein (PVP) perforate the host cell membrane and eventually culminates in cell rupture thereby releasing replicated phages. The accurate identification of PVP is thus a crucial step towards improving our understanding of the biological function and mechanisms of PVPs. Therefore, it is desirable to develop a computational method that is capable of fast and accurate identification of PVPs
-
Predictive potential of eigenvalue-based topological molecular descriptors. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-13 Izudin Redžepović,Boris Furtula
This study is directed toward assessing the predictive potential of eigenvalue-based topological molecular descriptors. The graph energy, Estrada index, resolvent energy, and the Laplacian energy were tested as parameters for the prediction of boiling points, heats of formation, and octanol/water partition coefficients of alkanes. It was shown that an eigenvalue-based molecular descriptor cannot be
-
Predicting reactivity to drug metabolism: beyond P450s-modelling FMOs and UGTs. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-12 Mario Öeren,Peter J Walton,Peter A Hunt,David J Ponting,Matthew D Segall
We present a study based on density functional theory calculations to explore the rate limiting steps of product formation for oxidation by Flavin-containing Monooxygenase (FMO) and glucuronidation by the UDP-glucuronosyltransferase (UGT) family of enzymes. FMOs are responsible for the modification phase of metabolism of a wide diversity of drugs, working in conjunction with Cytochrome P450 (CYP) family
-
Plausible compounds drawn from plants as curative agents for neurodegeneration: An in-silico approach. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-12 Shalini Thiruchittampalam,Samantha Weerasinghe
Classification of chemical compounds of plants as a source of medicaments for neurodegenerative diseases through computer screening is an efficient process in drug discovery, in advance of laboratory testing and clinical trials. The onset of neurodegenerative disorders incarcerates both sufferers and their families mentally and financially. This investigation emphasises the search for potent compounds
-
Side chain virtual screening of matched molecular pairs: a PDB-wide and ChEMBL-wide analysis. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-12 Matthew P Baumgartner,David A Evans
Optimization in medicinal chemistry often involves designing replacements for a section of a molecule which aim to retain potency while improving other properties of the compound. In this study, we perform a retrospective analysis using a number of computational methods to identify active side chains amongst a pool of random decoy side chains, mimicking a similar procedure that might be undertaken
-
Simplified activity cliff network representations with high interpretability and immediate access to SAR information. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-05 Huabin Hu,Jürgen Bajorath
Activity cliffs (ACs) consist of structurally similar compounds with a large difference in potency against their target. Accordingly, ACs introduce discontinuity in structure-activity relationships (SARs) and are a prime source of SAR information. In compound data sets, the vast majority of ACs are formed by differently sized groups of structurally similar compounds with large potency variations. As
-
Computational exploration and experimental validation to identify a dual inhibitor of cholinesterase and amyloid-beta for the treatment of Alzheimer's disease. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-06-03 Manish Kumar Tripathi,Piyoosh Sharma,Avanish Tripathi,Prabhash Nath Tripathi,Pavan Srivastava,Ankit Seth,Sushant Kumar Shrivastava
The cholinesterases are essential targets implicated in the pathogenesis of Alzheimer’s disease (AD). In the present study, virtual screening and molecular docking are performed to identify the potential hits. Docking-post processing (DPP) and pose filtration protocols against AChE and BChE resulted in three hits (AW00308, HTS04089, and JFD03947). Molecular Mechanics-Generalized Born Surface Area (MM-GBSA)
-
Artificial intelligence in chemistry and drug design. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-07-01 Nathan Brown,Peter Ertl,Richard Lewis,Torsten Luksch,Daniel Reker,Nadine Schneider
-
Revisiting allostery in CREB-binding protein (CBP) using residue-based interaction energy. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-05-19 Metin Yazar,Pemra Ozbek
CREB-binding protein (CBP) is a multi-subunit scaffold protein complex in transcription regulation process, binding and interacting with ligands such as mixed-lineage leukemia (MLL) and c-Myb allosterically. Here in this study, we have revisited the concept of allostery in CBP via residue-based interaction energy calculation based on molecular dynamics (MD) simulations. To this end, we conducted MD
-
Advances in exploring activity cliffs. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-05-05 Dagmar Stumpfe,Huabin Hu,Jürgen Bajorath
The activity cliff (AC) concept is of comparable relevance for medicinal chemistry and chemoinformatics. An AC is defined as a pair of structurally similar compounds with a large potency difference against a given target. In medicinal chemistry, ACs are of interest because they reveal small chemical changes with large potency effects, a concept referred to as structure-activity relationship (SAR) discontinuity
-
Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-05-02 Raquel Rodríguez-Pérez,Jürgen Bajorath
Difficulties in interpreting machine learning (ML) models and their predictions limit the practical applicability of and confidence in ML in pharmaceutical research. There is a need for agnostic approaches aiding in the interpretation of ML models regardless of their complexity that is also applicable to deep neural network (DNN) architectures and model ensembles. To these ends, the SHapley Additive
-
Quantum chemical predictions of water-octanol partition coefficients applied to the SAMPL6 logP blind challenge. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-01-30 Michael R Jones,Bernard R Brooks
Theoretical approaches for predicting physicochemical properties are valuable tools for accelerating the drug discovery process. In this work, quantum chemical methods are used to predict water-octanol partition coefficients as a part of the SAMPL6 blind challenge. The SMD continuum solvent model was employed with MP2 and eight DFT functionals in conjunction with correlation consistent basis sets to
-
Predicting octanol/water partition coefficients for the SAMPL6 challenge using the SM12, SM8, and SMD solvation models. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-01-30 Jonathan A Ouimet,Andrew S Paluch
Blind predictions of octanol/water partition coefficients at 298 K for 11 kinase inhibitor fragment like compounds were made for the SAMPL6 challenge. We used the conventional, "untrained", free energy based approach wherein the octanol/water partition coefficient was computed directly as the difference in solvation free energy in water and 1-octanol. We additionally proposed and used two different
-
Prediction of octanol-water partition coefficients for the SAMPL6-[Formula: see text] molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-01-20 Shujie Fan,Bogdan I Iorga,Oliver Beckstein
All-atom molecular dynamics simulations with stratified alchemical free energy calculations were used to predict the octanol-water partition coefficient [Formula: see text] of eleven small molecules as part of the SAMPL6-[Formula: see text] blind prediction challenge using four different force field parametrizations: standard OPLS-AA with transferable charges, OPLS-AA with non-transferable CM1A charges
-
SAMPL6 logP challenge: machine learning and quantum mechanical approaches. J. Comput. Aid. Mol. Des. (IF 2.546) Pub Date : 2020-01-30 Prajay Patel,David M Kuntz,Michael R Jones,Bernard R Brooks,Angela K Wilson
Two different types of approaches: (a) approaches that combine quantitative structure activity relationships, quantum mechanical electronic structure methods, and machine-learning and, (b) electronic structure vertical solvation approaches, were used to predict the logP coefficients of 11 molecules as part of the SAMPL6 logP blind prediction challenge. Using electronic structures optimized with density