2,046 results match your criteria Journal of Computer-Aided Molecular Design [Journal]


Water molecules in protein-ligand interfaces. Evaluation of software tools and SAR comparison.

J Comput Aided Mol Des 2019 Feb 12. Epub 2019 Feb 12.

Genentech, 1 DNA Way, South San Francisco, CA, 94080, USA.

Targeting the interaction with or displacement of the 'right' water molecule can significantly increase inhibitor potency in structure-guided drug design. Multiple computational approaches exist to predict which waters should be targeted for displacement to achieve the largest gain in potency. However, the relative success of different methods remains underexplored. Read More

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http://dx.doi.org/10.1007/s10822-019-00187-yDOI Listing
February 2019

AZT acts as an anti-influenza nucleotide triphosphate targeting the catalytic site of A/PR/8/34/H1N1 RNA dependent RNA polymerase.

J Comput Aided Mol Des 2019 Feb 9. Epub 2019 Feb 9.

Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB, Canada.

To develop potent drugs that inhibit the activity of influenza virus RNA dependent RNA polymerase (RdRp), a set of compounds favipiravir, T-705, T-1105 and T-1106, ribavirin, ribavirin triphosphate viramidine, 2FdGTP (2'-deoxy-2'-fluoroguanosine triphosphate) and AZT-TP (3'-Azido-3'-deoxy-thymidine-5'-triphosphate) were docked with a homology model of IAV RdRp from the A/PR/8/34/H1N1 strain. These compounds bind to four pockets A-D of the IAV RdRp with different mechanism of action. In addition, AZT-TP also binds to the PB1 catalytic site near to the tip of the priming loop with a highest ΔG of - 16. Read More

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http://dx.doi.org/10.1007/s10822-019-00189-wDOI Listing
February 2019

Multi-task generative topographic mapping in virtual screening.

J Comput Aided Mol Des 2019 Feb 9. Epub 2019 Feb 9.

Laboratory of Chemoinformatics, Faculty of Chemistry, University of Strasbourg, 4, Blaise Pascal Str., 67081, Strasbourg, France.

The previously reported procedure to generate "universal" Generative Topographic Maps (GTMs) of the drug-like chemical space is in practice a multi-task learning process, in which both operational GTM parameters (example: map grid size) and hyperparameters (key example: the molecular descriptor space to be used) are being chosen by an evolutionary process in order to fit/select "universal" GTM manifolds. After selection (a one-time task aimed at optimizing the compromise in terms of neighborhood behavior compliance, over a large pool of various biological targets), for any further use the manifolds are ready to provide "fit-free" predictive models. Using any structure-activity set-irrespectively whether the associated target served at map fitting stage or not-the generation or "coloring" a property landscape enables predicting the property for any external molecule, with zero additional fitable parameters involved. Read More

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http://dx.doi.org/10.1007/s10822-019-00188-xDOI Listing
February 2019

Optimisation of human V domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3).

J Comput Aided Mol Des 2019 Jan 28. Epub 2019 Jan 28.

Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Minden, 11800, Penang, Malaysia.

Mycobacterium tuberculosis (Mtb) 16.3 kDa heat shock protein 16.3 (HSP16. Read More

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http://dx.doi.org/10.1007/s10822-019-00186-zDOI Listing
January 2019

Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight.

J Comput Aided Mol Des 2019 Jan 28. Epub 2019 Jan 28.

Dalton Cardiovascular Research Center, University of Missouri, 65211, Columbia, MO, USA.

Drug Design Data Resource (D3R) continues to release valuable benchmarking datasets to promote improvement and development of computational methods for new drug discovery. We have developed several methods for protein-ligand binding mode prediction during the participation in the D3R challenges. In the present study, these methods were integrated, automated, and systematically tested using the large-scale data from Continuous Evaluation of Ligand Pose Prediction (CELPP) and a subset of Grand challenge 3 (GC3). Read More

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http://dx.doi.org/10.1007/s10822-019-00185-0DOI Listing
January 2019
2 Reads

Discovery and evaluation of novel Mycobacterium tuberculosis ketol-acid reductoisomerase inhibitors as therapeutic drug leads.

J Comput Aided Mol Des 2019 Jan 21. Epub 2019 Jan 21.

Department of Pharmacy, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Jawahar Nagar, Hyderabad, 500078, India.

Tuberculosis (TB) remains a major threat to human health. This due to the fact that current drug treatments are less than optimal and the increasing occurrence of multi drug-resistant strains of etiological agent, Mycobacterium tuberculosis (Mt). Given the wide-spread significance of this disease, we have undertaken a design and evaluation program to discover new anti-TB drug leads. Read More

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http://dx.doi.org/10.1007/s10822-019-00184-1DOI Listing
January 2019
5 Reads
2.990 Impact Factor

D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.

J Comput Aided Mol Des 2019 Jan 10;33(1):1-18. Epub 2019 Jan 10.

Drug Design Data Resource, University of California, San Diego, La Jolla, CA, 92093, USA.

The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-2018, GC3 centered on the protein Cathepsin S and the kinases VEGFR2, JAK2, p38-α, TIE2, and ABL1, and included both pose-prediction and affinity-ranking components. Read More

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http://dx.doi.org/10.1007/s10822-018-0180-4DOI Listing
January 2019
1 Read

Uncovering abnormal changes in logP after fluorination using molecular dynamics simulations.

J Comput Aided Mol Des 2019 Jan 2. Epub 2019 Jan 2.

Medicinal Chemistry Research Laboratories, Pharmaceutical Research Division, Takeda Pharmaceutical Company Limited, 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-8555, Japan.

The fluorination-induced changes in the logP (1-octanol/water partition coefficient) of ligands were examined by molecular dynamics simulations. The protocol and force field parameters were first evaluated by calculating the logP values for n-alkanes, and their monofluorinated and monochlorinated analogs. Then, the logP values of several test sets (1-butanol, 3-propyl-1H-indole, and analogs fluorinated at the terminal methyl group) were calculated. Read More

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http://dx.doi.org/10.1007/s10822-018-0183-1DOI Listing
January 2019

First virtual screening and experimental validation of inhibitors targeting GES-5 carbapenemase.

J Comput Aided Mol Des 2019 Jan 2. Epub 2019 Jan 2.

Department of Life Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125, Modena, Italy.

The worldwide spread of beta-lactamases with hydrolytic activity extended to last resort carbapenems is aggravating the antibiotic resistance problem and endangers the successful antimicrobial treatment of clinically relevant pathogens. As recently highlighted by the World Health Organization, new strategies to contain antimicrobial resistance are urgently needed. Class A carbapenemases include members of the KPC, GES and SFC families. Read More

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http://dx.doi.org/10.1007/s10822-018-0182-2DOI Listing
January 2019

Active learning strategies with COMBINE analysis: new tricks for an old dog.

J Comput Aided Mol Des 2018 Dec 18. Epub 2018 Dec 18.

Data Science and Computational Chemistry, Galchimia S.A. Severo Ochoa 2, Tres Cantos, 28760, Spain.

The COMBINE method was designed to study congeneric series of compounds including structural information of ligand-protein complexes. Although very successful, the method has not received the same level of attention than other alternatives to study Quantitative Structure Active Relationships (QSAR) mainly because lack of ways to measure the uncertainty of the predictions and the need for large datasets. Active learning, a semi-supervised learning approach that makes use of uncertainty to enhance models' performance while reducing the size of the training sets, has been used in this work to address both problems. Read More

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http://link.springer.com/10.1007/s10822-018-0181-3
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http://dx.doi.org/10.1007/s10822-018-0181-3DOI Listing
December 2018
7 Reads

Structural characterization and molecular dynamics simulations of the caprine and bovine solute carrier family 11 A1 (SLC11A1).

J Comput Aided Mol Des 2018 Dec 12. Epub 2018 Dec 12.

Section of Cell Biology and Biophysics, Department of Biology, School of Sciences, National and Kapodistrian University of Athens, Panepistimiopolis, 15701, Athens, Greece.

Natural Resistance-Associated Macrophage Proteins are a family of transmembrane divalent metal ion transporters, with important implications in life of both bacteria and mammals. Among them, the Solute Carrier family 11 member A1 (SLC11A1) has been implicated with susceptibility to infection by Mycobacterium avium subspecies paratuberculosis (MAP), potentially causing Crohn's disease in humans and paratuberculosis (PTB) in ruminants. Our previous research had focused on sequencing the mRNA of the caprine slc11a1 gene and pinpointed polymorphisms that contribute to caprine SLC11A1's susceptibility to infection by MAP in PTB. Read More

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http://dx.doi.org/10.1007/s10822-018-0179-xDOI Listing
December 2018

Force field development phase II: Relaxation of physics-based criteria… or inclusion of more rigorous physics into the representation of molecular energetics.

Authors:
A T Hagler

J Comput Aided Mol Des 2018 Nov 30. Epub 2018 Nov 30.

Department of Chemistry, University of Massachusetts, Amherst, MA, 01003, USA.

In the previous paper, we reviewed the origins of energy based calculations, and the early science of FF development. The initial efforts spanning the period from roughly the early 1970s to the mid to late 1990s saw the development of methodologies and philosophies of the derivation of FFs. The use of Cartesian coordinates, derivation of the H-bond potential, different functional forms including diagonal quadratic expressions, coupled valence FFs, functional form of combination rules, and out of plane angles, were all investigated in this period. Read More

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http://dx.doi.org/10.1007/s10822-018-0134-xDOI Listing
November 2018

Biomolecular force fields: where have we been, where are we now, where do we need to go and how do we get there?

J Comput Aided Mol Des 2018 Nov 30. Epub 2018 Nov 30.

Department of Chemistry, University of Massachusetts, Amherst, MA, 01003, USA.

In this perspective, we review the theory and methodology of the derivation of force fields (FFs), and their validity, for molecular simulations, from their inception in the second half of the twentieth century to the improved representations at the end of the century. We examine the representations of the physics embodied in various force fields, their accuracy and deficiencies. The early days in the 1950s and 60s saw FFs first introduced to analyze vibrational spectra. Read More

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http://dx.doi.org/10.1007/s10822-018-0111-4DOI Listing
November 2018

Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction.

J Comput Aided Mol Des 2018 Dec 26;32(12):1363-1373. Epub 2018 Nov 26.

College of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, People's Republic of China.

Identifying protein-RNA binding residues is essential for understanding the mechanism of protein-RNA interactions. So far, rigid distance thresholds are commonly used to define protein-RNA binding residues. However, after investigating 182 non-redundant protein-RNA complexes, we find that it would be unsuitable for a certain amount of complexes since the distances between proteins and RNAs vary widely. Read More

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http://dx.doi.org/10.1007/s10822-018-0177-zDOI Listing
December 2018

Structural explanation for the tunable substrate specificity of an E. coli nucleoside hydrolase: insights from molecular dynamics simulations.

J Comput Aided Mol Des 2018 Dec 26;32(12):1375-1388. Epub 2018 Nov 26.

Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive West, Lethbridge, AB, T1K 3M4, Canada.

Parasitic protozoa rely on nucleoside hydrolases that play key roles in the purine salvage pathway by catalyzing the hydrolytic cleavage of the N-glycosidic bond that connects nucleobases to ribose sugars. Cytidine-uridine nucleoside hydrolase (CU-NH) is generally specific toward pyrimidine nucleosides; however, previous work has shown that replacing two active site residues with Tyr, specifically the Thr223Tyr and Gln227Tyr mutations, allows CU-NH to process inosine. The current study uses molecular dynamics (MD) simulations to gain atomic-level insight into the activity of wild-type and mutant E. Read More

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http://dx.doi.org/10.1007/s10822-018-0178-yDOI Listing
December 2018

Monte Carlo on the manifold and MD refinement for binding pose prediction of protein-ligand complexes: 2017 D3R Grand Challenge.

J Comput Aided Mol Des 2019 Jan 12;33(1):119-127. Epub 2018 Nov 12.

Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.

Manifold representations of rotational/translational motion and conformational space of a ligand were previously shown to be effective for local energy optimization. In this paper we report the development of the Monte-Carlo energy minimization approach (MCM), which uses the same manifold representation. The approach was integrated into the docking pipeline developed for the current round of D3R experiment, and according to D3R assessment produced high accuracy poses for Cathepsin S ligands. Read More

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http://link.springer.com/10.1007/s10822-018-0176-0
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http://dx.doi.org/10.1007/s10822-018-0176-0DOI Listing
January 2019
6 Reads

Overview of the SAMPL6 host-guest binding affinity prediction challenge.

J Comput Aided Mol Des 2018 Oct 10;32(10):937-963. Epub 2018 Nov 10.

Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.

Accurately predicting the binding affinities of small organic molecules to biological macromolecules can greatly accelerate drug discovery by reducing the number of compounds that must be synthesized to realize desired potency and selectivity goals. Unfortunately, the process of assessing the accuracy of current computational approaches to affinity prediction against binding data to biological macromolecules is frustrated by several challenges, such as slow conformational dynamics, multiple titratable groups, and the lack of high-quality blinded datasets. Over the last several SAMPL blind challenge exercises, host-guest systems have emerged as a practical and effective way to circumvent these challenges in assessing the predictive performance of current-generation quantitative modeling tools, while still providing systems capable of possessing tight binding affinities. Read More

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http://link.springer.com/10.1007/s10822-018-0170-6
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http://dx.doi.org/10.1007/s10822-018-0170-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6301044PMC
October 2018
9 Reads

pK measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments.

J Comput Aided Mol Des 2018 Oct 7;32(10):1117-1138. Epub 2018 Nov 7.

Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.

Determining the net charge and protonation states populated by a small molecule in an environment of interest or the cost of altering those protonation states upon transfer to another environment is a prerequisite for predicting its physicochemical and pharmaceutical properties. The environment of interest can be aqueous, an organic solvent, a protein binding site, or a lipid bilayer. Predicting the protonation state of a small molecule is essential to predicting its interactions with biological macromolecules using computational models. Read More

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http://link.springer.com/10.1007/s10822-018-0168-0
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http://dx.doi.org/10.1007/s10822-018-0168-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6367941PMC
October 2018
5 Reads

Using steered molecular dynamics to study the interaction between ADP and the nucleotide-binding domain of yeast Hsp70 protein Ssa1.

J Comput Aided Mol Des 2018 Nov 3;32(11):1217-1227. Epub 2018 Nov 3.

School of Environmental Science, College of Environment, Liaoning University, No. 66 Chongshan Middle Road, Huanggu District, Shenyang, 110036, Liaoning, China.

Genetics experiments have identified six mutations located in the subdomain IA (A17V, R23H, G32D, G32S, R34K, V372I) of Ssa1 that influence propagation of the yeast [PSI] prion. However, the underlining molecular mechanisms of these mutations are still unclear. The six mutation sites are present in the IA subdomain of the nucleotide-binding domain (NBD). Read More

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http://link.springer.com/10.1007/s10822-018-0136-8
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http://dx.doi.org/10.1007/s10822-018-0136-8DOI Listing
November 2018
7 Reads

Investigating cyclic peptides inhibiting CD2-CD58 interactions through molecular dynamics and molecular docking methods.

J Comput Aided Mol Des 2018 Nov 28;32(11):1295-1313. Epub 2018 Oct 28.

University of Nantes, CEISAM UMR CNRS 6230, UFR Sciences et Techniques, 2 Rue de la Houssinière, BP 92208, 44322, Nantes Cedex 03, France.

The CD2-CD58 protein-protein interaction is known to favor the recognition of antigen presenting cells by T cells. The structural, energetics, and dynamical properties of three known cyclic CD58 ligands, named P6, P7, and RTD-c, are studied through molecular dynamics (MD) simulations and molecular docking calculations. The ligands are built so as to mimic the C and F β-strands of protein CD2, connected via turn inducers. Read More

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http://dx.doi.org/10.1007/s10822-018-0172-4DOI Listing
November 2018
2 Reads

Quantum chemical and molecular mechanics studies on the assessment of interactions between resveratrol and mutant SOD1 (G93A) protein.

J Comput Aided Mol Des 2018 Dec 28;32(12):1347-1361. Epub 2018 Oct 28.

Bioinformatics Lab, Department of Biotechnology, School of Bio Sciences and Technology, VIT (Deemed to be University), Vellore, Tamil Nadu, 632014, India.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that has been associated with mutations in metalloenzyme superoxide dismutase (SOD1) causing protein structural destabilization and aggregation. However, the mechanistic action and the cure for the disease still remain obscure. Herein, we initially studied the conformational preferences of SOD1 protein structures upon substitution of Ala at Gly93 in comparison with that of wild type. Read More

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http://dx.doi.org/10.1007/s10822-018-0175-1DOI Listing
December 2018
1 Read

Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates.

J Comput Aided Mol Des 2018 Nov 26;32(11):1273-1294. Epub 2018 Oct 26.

Department of Computing and Numerical Analysis, University of Córdoba, Campus de Rabanales, Albert Einstein Building, 14071, Córdoba, Spain.

Feature selection is commonly used as a preprocessing step to machine learning for improving learning performance, lowering computational complexity and facilitating model interpretation. This paper proposes the application of boosting feature selection to improve the classification performance of standard feature selection algorithms evaluated for the prediction of P-gp inhibitors and substrates. Two well-known classification algorithms, decision trees and support vector machines, were used to classify the chemical compounds. Read More

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http://dx.doi.org/10.1007/s10822-018-0171-5DOI Listing
November 2018
14 Reads

Mycobacterium tuberculosis serine/threonine protein kinases: structural information for the design of their specific ATP-competitive inhibitors.

J Comput Aided Mol Des 2018 Dec 26;32(12):1315-1336. Epub 2018 Oct 26.

Centro de Bioinformática y Simulación Molecular (CBSM), Universidad de Talca, 1 Poniente No. 1141, Casilla 721, Talca, Chile.

In the last decades, human protein kinases (PKs) have been relevant as targets in the development of novel therapies against many diseases, but the study of Mycobacterium tuberculosis PKs (MTPKs) involved in tuberculosis pathogenesis began much later and has not yet reached an advanced stage of development. To increase knowledge of these enzymes, in this work we studied the structural features of MTPKs, with focus on their ATP-binding sites and their interactions with inhibitors. PknA, PknB, and PknG are the most studied MTPKs, which were previously crystallized; ATP-competitive inhibitors have been designed against them in the last decade. Read More

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http://link.springer.com/10.1007/s10822-018-0173-3
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http://dx.doi.org/10.1007/s10822-018-0173-3DOI Listing
December 2018
5 Reads

Could the presence of sodium ion influence the accuracy and precision of the ligand-posing in the human A adenosine receptor orthosteric binding site using a molecular docking approach? Insights from Dockbench.

J Comput Aided Mol Des 2018 Dec 25;32(12):1337-1346. Epub 2018 Oct 25.

Molecular Modeling Section (MMS), Dipartimento di Scienze del Farmaco, Università di Padova, via Marzolo 5, 35131, Padova, Italy.

The allosteric modulation of G protein-coupled receptors (GPCRs) by sodium ions has received considerable attention as crystal structures of several receptors, in their inactive conformation, show a Na ion bound to specific residues which, in the human A adenosine receptor (hA AR), are Ser91, Trp246, Asn280, and Asn284. A cluster of water molecules completes the coordination of the sodium ion in the putative allosteric site. It is absolutely consolidated that the progress made in the field of GPCRs structural determination has increased the adoption of docking-driven approaches for the identification or the optimization of novel potent and selective ligands. Read More

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https://link.springer.com/journal/10822/onlineFirst
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https://www.researchgate.net/publication/222625875_Iterative
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http://link.springer.com/10.1007/s10822-018-0174-2
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http://dx.doi.org/10.1007/s10822-018-0174-2DOI Listing
December 2018
3 Reads

SAMPL6 challenge results from [Formula: see text] predictions based on a general Gaussian process model.

J Comput Aided Mol Des 2018 Oct 15;32(10):1165-1177. Epub 2018 Oct 15.

OpenEye Scientific Software, Inc., 9 Bisbee Court, Suite D, Santa Fe, NM, 87508, USA.

A variety of fields would benefit from accurate [Formula: see text] predictions, especially drug design due to the effect a change in ionization state can have on a molecule's physiochemical properties. Participants in the recent SAMPL6 blind challenge were asked to submit predictions for microscopic and macroscopic [Formula: see text]s of 24 drug like small molecules. We recently built a general model for predicting [Formula: see text]s using a Gaussian process regression trained using physical and chemical features of each ionizable group. Read More

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http://dx.doi.org/10.1007/s10822-018-0169-zDOI Listing
October 2018

Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges.

J Comput Aided Mol Des 2018 Oct 15;32(10):1075-1086. Epub 2018 Oct 15.

Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.

We calculate the absolute binding free energies of tetra-methylated octa-acids host-guest systems as a part of the SAMPL6 blind challenge (receipt ID vq30p). We employed two different free energy simulation methods, i.e. Read More

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http://dx.doi.org/10.1007/s10822-018-0166-2DOI Listing
October 2018
2.990 Impact Factor

Absolute binding free energies for the SAMPL6 cucurbit[8]uril host-guest challenge via the AMOEBA polarizable force field.

J Comput Aided Mol Des 2018 Oct 15;32(10):1087-1095. Epub 2018 Oct 15.

Department of Chemistry, Washington University in St. Louis, Saint Louis, MO, 63130, USA.

As part of the SAMPL6 host-guest blind challenge, the AMOEBA force field was applied to calculate the absolute binding free energy for a cucurbit[8]uril host complexed with 14 diverse guests, ranging from small, rigid structures to drug molecules. The AMOEBA results from the initial submission prompted an investigation into aspects of the methodology and parameterization employed. Lessons learned from the blind challenge include: a double annihilation scheme (electrostatics and van der Waals) is needed to obtain proper sampling of guest conformations, annihilation of key torsion parameters of the guest are recommended for flexible guests, and a more thorough analysis of torsion parameters is warranted. Read More

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http://dx.doi.org/10.1007/s10822-018-0147-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240481PMC
October 2018
1 Read

An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge.

J Comput Aided Mol Des 2018 Oct 1;32(10):1191-1201. Epub 2018 Oct 1.

Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA.

In this work we have developed a hybrid QM and MM approach to predict pKa of small drug-like molecules in explicit solvent. The gas phase free energy of deprotonation is calculated using the M06-2X density functional theory level with Pople basis sets. The solvation free energy difference of the acid and its conjugate base is calculated at MD level using thermodynamic integration. Read More

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http://link.springer.com/10.1007/s10822-018-0167-1
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http://dx.doi.org/10.1007/s10822-018-0167-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342563PMC
October 2018
1 Read

Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale.

J Comput Aided Mol Des 2018 Oct 1;32(10):983-999. Epub 2018 Oct 1.

Department of Chemistry, University of South Florida, Tampa, Florida, 33620, USA.

Use of quantum mechanical/molecular mechanical (QM/MM) methods in binding free energy calculations, particularly in the SAMPL challenge, often fail to achieve improvement over standard additive (MM) force fields. Frequently, the implementation is through use of reference potentials, or the so-called "indirect approach", and inherently relies on sufficient overlap existing between MM and QM/MM configurational spaces. This overlap is generally poor, particularly for the use of free energy perturbation to perform the MM to QM/MM free energy correction at the end states of interest (e. Read More

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http://dx.doi.org/10.1007/s10822-018-0165-3DOI Listing
October 2018
2.990 Impact Factor

Parameterization of a coarse-grained model of cholesterol with point-dipole electrostatics.

J Comput Aided Mol Des 2018 Nov 26;32(11):1259-1271. Epub 2018 Sep 26.

Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo (USP), Av. Bandeirantes, 3900, Ribeirão Preto, SP, 14040-901, Brazil.

We present a new coarse-grained (CG) model of cholesterol (CHOL) for the electrostatic-based ELBA force field. A distinguishing feature of our CHOL model is that the electrostatics is modeled by an explicit point dipole which interacts through an ideal vacuum permittivity. The CHOL model parameters were optimized in a systematic fashion, reproducing the electrostatic and nonpolar partitioning free energies of CHOL in lipid/water mixtures predicted by full-detailed atomistic molecular dynamics simulations. Read More

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http://dx.doi.org/10.1007/s10822-018-0164-4DOI Listing
November 2018

SAMPL6 host-guest challenge: binding free energies via a multistep approach.

J Comput Aided Mol Des 2018 Oct 17;32(10):1097-1115. Epub 2018 Sep 17.

Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA.

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). Read More

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http://dx.doi.org/10.1007/s10822-018-0159-1DOI Listing
October 2018

Calculate protein-ligand binding affinities with the extended linear interaction energy method: application on the Cathepsin S set in the D3R Grand Challenge 3.

J Comput Aided Mol Des 2019 Jan 14;33(1):105-117. Epub 2018 Sep 14.

Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, 15261, USA.

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. Read More

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http://link.springer.com/10.1007/s10822-018-0162-6
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http://dx.doi.org/10.1007/s10822-018-0162-6DOI Listing
January 2019
12 Reads

Weak interactions in furan dimers.

Authors:
Irena Majerz

J Comput Aided Mol Des 2018 Sep 14. Epub 2018 Sep 14.

Faculty of Pharmacy, Wroclaw Medical University, Borowska 211a, 50-556, Wrocław, Poland.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0163-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6267657PMC
September 2018
2 Reads

Blinded evaluation of cathepsin S inhibitors from the D3RGC3 dataset using molecular docking and free energy calculations.

J Comput Aided Mol Des 2019 Jan 11;33(1):93-103. Epub 2018 Sep 11.

Institut de Chimie des Substances Naturelles, CNRS UPR 2301, LabEx LERMIT, 91198, Gif-sur-Yvette, France.

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. Read More

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http://link.springer.com/10.1007/s10822-018-0161-7
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http://dx.doi.org/10.1007/s10822-018-0161-7DOI Listing
January 2019
34 Reads

Binding free energies in the SAMPL6 octa-acid host-guest challenge calculated with MM and QM methods.

J Comput Aided Mol Des 2018 Oct 10;32(10):1027-1046. Epub 2018 Sep 10.

Department of Theoretical Chemistry, Lund University, Chemical Centre, P. O. Box 124, 221 00, Lund, Sweden.

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. The semiempirical QM method PM6-DH+ was employed for the ligand in the latter calculations. Read More

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http://dx.doi.org/10.1007/s10822-018-0158-2DOI Listing
October 2018
3 Reads

In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery.

J Comput Aided Mol Des 2018 Nov 8;32(11):1229-1245. Epub 2018 Sep 8.

Department of Pharmaceutical Sciences, School of Pharmacy, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo, 108-8641, Japan.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0160-8DOI Listing
November 2018
1 Read

Discovery of novel wee1 inhibitors via structure-based virtual screening and biological evaluation.

J Comput Aided Mol Des 2018 Sep 4;32(9):901-915. Epub 2018 Sep 4.

State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, Yunnan, China.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0122-1DOI Listing
September 2018
2 Reads
2.990 Impact Factor

Quantum chemical studies on anion specificity of CNN motif in functional proteins.

J Comput Aided Mol Des 2018 Sep 4;32(9):929-936. Epub 2018 Sep 4.

Department of Chemical, Biological and Macro-Molecular Sciences, S.N. Bose National Centre for Basic Sciences, Sector III, Block JD, Salt Lake, Kolkata, 700106, India.

Anion binding CNN 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. Read More

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http://dx.doi.org/10.1007/s10822-018-0157-3DOI Listing
September 2018

Rescoring of docking poses under Occam's Razor: are there simpler solutions?

J Comput Aided Mol Des 2018 Sep 1;32(9):877-888. Epub 2018 Sep 1.

Université de Strasbourg, 1 rue B. Pascal, 67000, Strasbourg, France.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0155-5DOI Listing
September 2018
7 Reads

Identification of protoberberine alkaloids as novel histone methyltransferase G9a inhibitors by structure-based virtual screening.

J Comput Aided Mol Des 2018 Sep 31;32(9):917-928. Epub 2018 Aug 31.

School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi, 16419, South Korea.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0156-4DOI Listing
September 2018
8 Reads

Blinded predictions of standard binding free energies: lessons learned from the SAMPL6 challenge.

J Comput Aided Mol Des 2018 Oct 29;32(10):1047-1058. Epub 2018 Aug 29.

EaStCHEM School of Chemistry, Joseph Black Building, King's Buildings, Edinburgh, EH9 3FJ, UK.

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. The performance of each model was evaluated with two different setups; buffer explicitly matches the ionic strength from the binding assays, whereas no-buffer merely neutralizes the host-guest net charge with counter-ions. Read More

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http://dx.doi.org/10.1007/s10822-018-0154-6DOI Listing
October 2018

Detailed potential of mean force studies on host-guest systems from the SAMPL6 challenge.

J Comput Aided Mol Des 2018 Oct 24;32(10):1013-1026. Epub 2018 Aug 24.

Department of Chemistry and the Department of Biochemistry and Molecular Biology, Michigan State University, 578 S. Shaw Lane, East Lansing, MI, 48824, USA.

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. Read More

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http://link.springer.com/10.1007/s10822-018-0153-7
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http://dx.doi.org/10.1007/s10822-018-0153-7DOI Listing
October 2018
8 Reads

High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge.

J Comput Aided Mol Des 2018 Oct 23;32(10):1139-1149. Epub 2018 Aug 23.

Mulliken Center for Theoretical Chemistry, Institute of Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115, Bonn, Germany.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0145-7DOI Listing
October 2018
11 Reads

Predicting ligand binding affinity using on- and off-rates for the SAMPL6 SAMPLing challenge.

J Comput Aided Mol Des 2018 Oct 23;32(10):1001-1012. Epub 2018 Aug 23.

Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA.

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]. Read More

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http://dx.doi.org/10.1007/s10822-018-0149-3DOI Listing
October 2018

Protein-ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3.

J Comput Aided Mol Des 2019 Jan 20;33(1):83-91. Epub 2018 Aug 20.

Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0148-4DOI Listing
January 2019
11 Reads

SAMPL6 host-guest blind predictions using a non equilibrium alchemical approach.

J Comput Aided Mol Des 2018 Oct 20;32(10):965-982. Epub 2018 Aug 20.

ENEA, Portici Research Centre, DTE-ICT-HPC, P.le E. Fermi, 1, 80055, Portici, NA, Italy.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0151-9DOI Listing
October 2018

Absolute and relative pK predictions via a DFT approach applied to the SAMPL6 blind challenge.

J Comput Aided Mol Des 2018 Oct 20;32(10):1179-1189. Epub 2018 Aug 20.

Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, 12 South Drive, Building 12A Room 3053, Bethesda, MD, 20814, USA.

In this work, quantum mechanical methods were used to predict the microscopic and macroscopic pK 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 pK calculation schemes (direct, vertical, and adiabatic). The adiabatic scheme is the most accurate approach (RMSE = 1. Read More

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http://dx.doi.org/10.1007/s10822-018-0150-xDOI Listing
October 2018
1 Read

Protein-small molecule docking with receptor flexibility in iMOLSDOCK.

J Comput Aided Mol Des 2018 Sep 20;32(9):889-900. Epub 2018 Aug 20.

Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai, 600025, India.

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. Read More

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http://link.springer.com/10.1007/s10822-018-0152-8
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http://dx.doi.org/10.1007/s10822-018-0152-8DOI Listing
September 2018
13 Reads

Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

J Comput Aided Mol Des 2019 Jan 16;33(1):71-82. Epub 2018 Aug 16.

Department of Mathematics, Michigan State University, East Lansing , MI, 48824, USA.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0146-6DOI Listing
January 2019
12 Reads

Hybrid receptor structure/ligand-based docking and activity prediction in ICM: development and evaluation in D3R Grand Challenge 3.

J Comput Aided Mol Des 2019 Jan 9;33(1):35-46. Epub 2018 Aug 9.

Molsoft L.L.C., 11199 Sorrento Valley Road, S209, San Diego, CA, 92121, USA.

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. Read More

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http://dx.doi.org/10.1007/s10822-018-0139-5DOI Listing
January 2019
1 Read