Advertisement

Topics

PubMed Journal Database | Journal of chemical information and modeling RSS

00:55 EDT 21st October 2018 | BioPortfolio

The US National Library of Medicine and National Institutes of Health manage PubMed.gov which comprises of more than 21 million records, papers, reports for biomedical literature, including MEDLINE, life science and medical journals, articles, reviews, reports and  books.  BioPortfolio aims to publish relevant information on published papers, clinical trials and news associated with users selected topics.

For example view all recent relevant publications on Epigenetics and associated publications and clincial trials.

Showing PubMed Articles 1–25 of 416 from Journal of chemical information and modeling

Binding residence time through scaled molecular dynamics: a prospective application to hDAAO inhibitors.

Traditionally, a drug potency is expressed in terms of thermodynamic quantities, mostly Kd, and empirical IC50 values. While binding affinity as an estimate of drug activity remains relevant, it is increasingly clear that it is also important to include (un)binding kinetic parameters in the characterization of potential drug-like molecules. Herein, we used standard in silico screening to identify a series of structurally related inhibitors of hDAAO, a flavoprotein involved in schizophrenia and neuropathic p...

Overcoming convergence issues in free-energy calculations of amide-to-ester mutations in the Pin1-WW domain.

Relative folding free energies for a series of amide-to-ester mutations in the Pin1-WW domain are calculated using molecular dynamics simulations. Special focus is given to the identification and elimination of a simulation-related bias which was observed in previous work (Eichenberger et al., Biochim. Biophys. Acta 1850 (2015) 983) by comparing simulation results obtained with two different starting structures. Subtle local variations in the protein starting structure may lead to substantial deviations in ...

A Structural Approach to Identify a Lead Scaffold that Targets the Translesion Synthesis Polymerase Rev1.

Translesion synthesis (TLS) is a mechanism of replication past damaged DNA through which multiple forms of human cancer survive and acquire resistance to first-line genotoxic chemotherapies. As such, TLS is emerging as a promising target for the development of a new class of anti-cancer agents. The C-terminal domain of the DNA polymerase Rev1 (Rev1-CT) mediates assembly of the functional TLS complex through protein-protein interactions (PPIs) with Rev1 interacting regions (RIRs) of several other TLS DNA pol...

CRISPro: An Automated Pipeline for Protein Conformation Stabilization by Proline.

Recent studies have shown that the yield, antigenicity, and immunogenicity of an immunogen can be enhanced by stabilizing it into a specific conformation. Such stabilization often involves the engineering of proline mutations at residue positions where a proline is structurally compatible with the target conformation, but not with the alternative conformation. However, there is no publicly available tool that can design proline mutations for this purpose automatically. Here we implemented an automated tool,...

Women in Computational Chemistry.

FINDSITE: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules.

Computational approaches for predicting protein-ligand interactions can facilitate drug lead discovery and drug target determination. We have previously developed a threading/structural-based approach, FINDSITEcomb, for the virtual ligand screening of proteins that has been extensively experimentally validated. Even when low resolution predicted protein structures are employed, FINDSITEcomb has the advantage of being faster and more accurate than traditional high-resolution structure-based docking methods. ...

Protein Family-specific Models using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data.

Machine learning has shown enormous potential for computer-aided drug discovery. Here we show how modern convolutional neural networks (CNNs) can be applied to structure-based virtual screening. We have coupled our densely connected CNN (DenseNet) with a transfer learning approach which we use to produce an ensemble of protein family-specific models. We conduct an in-depth empirical study and provide the first guidelines on the minimum requirements for adopting a protein family-specific model. Our method al...

Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.

In this study, we developed two cancer-specific machine learning classifiers for prediction of driver mutations in cancer-associated genes that were validated on canonical datasets of functionally validated mutations and applied to a large cancer genomics dataset. By examining sequence, structure and ensemble-based integrated features, we have shown that evolutionary conservation scores play a critical role in classification of cancer drivers and provide the strongest signal in the machine learning predicti...

Kinematic Flexibility Analysis: Hydrogen Bonding Patterns Impart a Spatial Hierarchy of Protein Motion.

Elastic network models (ENM) and constraint-based, topological rigidity analysis are two distinct, coarse-grained approaches to study conformational flexibility of macromolecules. In the two decades since their introduction, both have contributed significantly to insights into protein molecular mechanisms and function. However, despite a shared purpose of these approaches, the topological nature of rigidity analysis, and thereby the absence of motion modes, has impeded a direct comparison. Here, we present ...

In Silico Identification of JMJD3 Demethylase Inhibitors.

In the search for new demethylase inhibitors we have developed a multi-step protocol for in silico screening. Millions of poses generated by high-throughput docking or 3D-pharmacophore search are first minimized by a classical force field and then filtered by semiempirical quantum mechanical calculations of the interaction energy with a selected set of functional groups in the binding site. The final ranking includes solvation effects, which are evaluated in the continuum dielectric approximation (finite-di...

Unique Physicochemical Patterns of Residues in Protein-Protein Interfaces.

Protein-protein interactions can be characterized by high-resolution structures of complexes, from which diverse features of the interfaces can be derived. For the majority of protein-protein interactions identified, however, there is no information on the structure of the complex or the interface involved in the interaction. Understanding what surface properties drive certain interactions is crucial in the functional evaluation of protein complexes. Here we show that the local patterning of the physicochem...

Trans and Cis Conformations of the Antihypertensive Drug Valsartan Respectively Lock the Inactive and Active-Like States of Angiotensin II Type 1 Receptor: A Molecular Dynamics Study.

Angiotensin II type 1 receptor (AT1R) is the principal regulator of blood pressure in humans. The overactivation of AT1R by the stimulation of angiotensin II would result in high blood pressure. To prevent hypertension, non-peptide 'sartan' drugs, such as valsartan (VST), have been developed to competitively block the access of angiotensin II to the receptor. Nuclear magnetic resonance spectroscopy and molecular modeling studies have identified that VST in solution and in lipid micelles (a mimic membrane en...

An Analysis of Different Components of a High-Throughput Screening Library.

Since many projects at pharmaceutical organizations get their start from a high-throughput screening (HTS) campaign, improving the quality of the HTS deck can improve the likelihood of discovering a high-quality lead molecule that can be progressed to a drug candidate. Over the last decade, Janssen has implemented several strategies for external compound acquisition to augment the screening deck beyond the chemical space and number of molecules synthesized for internal projects. In this report, we analyzed ...

GPU-accelerated molecular dynamics and free energy methods in Amber18: performance enhancements and new features.

We report progress in GPU-accelerated molecular dynamics and free energy methods in Amber18. Of particular interest is the development of alchemical free energy algorithms, including free energy perturbation and thermodynamic integration methods with support for non-linear softcore potential and parameter interpolation transformation pathways. These methods can be used in conjunction with enhanced sampling techniques such as replica exchange, constant pH molecular dynamics and new 12-6-4 potentials for meta...

pywindow: Automated Structural Analysis of Molecular Pores.

Structural analysis of molecular pores can yield important information on their behaviour in solution and in the bulk. We developed pywindow, a python package that allows for the automated analysis of structural features of porous molecular materials, such as molecular cages. Our analysis includes the cavity diameter, number of windows, window diameters and average molecular diameter. Molecular dynamics trajectories of molecular pores can also be analysed to explore the influence of flexibility. We present ...

AFLOW-CHULL: Cloud-Oriented Platform for Autonomous Phase Stability Analysis.

A priori prediction of phase stability of materials is a challenging practice, requiring knowledge of all energetically-competing structures at formation conditions. Large materials repositories - housing properties of both experimental and hypothetical compounds - offer a path to prediction through the construction of informatics-based, ab-initio phase diagrams. However, limited access to relevant data and software infrastructure has rendered thermodynamic characterizations largely peripheral, despite thei...

Only a Subset of Normal Modes is Sufficient to Identify Linear Correlations in Proteins.

Identification of correlated residues in proteins is very important for many areas on protein research such as drug design, protein classification, signal transmission, allostery and mutational studies. Pairwise residue correlations in proteins can be obtained from experimental and theoretical ensembles. Since it is difficult to obtain proteins in various conformational states experimentally, theoretical methods such as all-atom molecular dynamics simulations and normal mode analysis are commonly used metho...

Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening.

The versatility of similarity searching and QSAR to model the activity of compound sets within given bioactivity ranges (i.e., interpolation) is well established. However, their relative performance in the common scenario in early-stage drug discovery where lots of inactive data is available, but no active data points (i.e., extrapolation from the low-activity to the high-activity range) has not been thoroughly examined yet. To this aim, we have designed an iterative virtual screening strategy which was eva...

Determinants of Oligonucleotide Selectivity of APOBEC3B.

APOBEC3B (A3B) is a prominent source of mutation in many cancers. To date, it has been difficult to capture the native protein-DNA interactions that confer A3B's substrate specificity by crystallography due to the highly dynamic nature of wild-type A3B active site. We use computational tools to restore a recent crystal structure of a DNA-bound A3B C-terminal domain mutant construct to its wild type sequence, and run molecular dynamics simulations to study its substrate recognition mechanisms. Analysis of th...

Hydration Free Energies in the FreeSolv Database Calculated with Polarized Iterative Hirshfeld Charges.

Computer simulations of bio-molecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in bio-molecular systems and are therein described by atomic p...

Prospectively Validated Proteochemometric Models for the Prediction of Small Molecule Binding to Bromodomain Proteins.

The bromodomain-containing proteins are a ligandable family of epigenetic readers, which play important roles in oncological, cardiovascular and inflammatory diseases. Achieving selective inhibition of specific bromodomains is challenging, due to the limited understanding of compound and target selectivity features. In this study we build and benchmark proteochemometric (PCM) classification models on bioactivity data for 15,350 data points across 31 bromodomains, using both compound fingerprints and binding...

How Reactive are Druggable Cysteines in Protein Kinases?

Targeted covalent-inhibitors (TCIs) have been successfully developed as high-affinity and selective inhibitors of enzymes of the protein kinase family. These drugs typically act by undergoing an electrophilic addition with an active site cysteine residue, so design of a TCI begins with the identification of a "druggable" cysteine. These electrophilic additions generally require the deprotonation of the thiol to form a reactive anionic thiolate, so the acidity of the residue is a critical factor. Few experim...

Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery.

The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, method comparison is difficult because of various flaws of the currently employed evaluation metrics. We propose an evaluation metric for generative models called Fréchet ChemblNet distance (FCD). The FCD's advantage over previous metrics is that it can detect whether generated molecules are diverse and have similar chemical and biological properties as real mole...

Detecting Proline and Non-Proline Cis-Isomers In Protein Structures from Sequences Using Deep Residual Ensemble Learning.

It has been long established that cis conformations of amino acid residues play many biologically important roles despite their rare occurrence in protein structure. Due to this rarity, few methods have been developed for predicting cis-isomers from protein sequences, most of which are based on outdated datasets and lack the means for independent testing. In this work, using a database of >10000 high-resolution protein structures, we update the statistics of cis-isomers and develop a sequence-based predicti...

Assimilating Radial Distribution Functions to Build Water Models with Improved Structural Properties.

The structural properties of three and four site water models are improved by extending the ForceBalance parameterization code to include a new methodology allowing for the targeting of any radial distribution function (RDF) during the parametrization of a force field. The mean squared difference (MSD) between the experimental and simulated RDFs contributes to an objective function, allowing for the systematic optimization of force field parameters to reach closer overall agreement with experiment. RDF fitt...


Advertisement
Quick Search
Advertisement
Advertisement