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Open-ComBind: harnessing unlabeled data for improved binding pose prediction
Open-ComBind: harnessing unlabeled data for improved binding pose prediction
Determination of the bound pose of a ligand is a critical first step in many in silico drug discovery tasks. Molecular doc...
Correction: Exploring DrugCentral: from molecular structures to clinical effects
Correction: Exploring DrugCentral: from molecular structures to clinical effects
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, whi...
Binding of small molecule inhibitors to RNA polymerase-Spt5 complex impacts RNA and DNA stability
Binding of small molecule inhibitors to RNA polymerase-Spt5 complex impacts RNA and DNA stability
Spt5 is an elongation factor that associates with RNA polymerase II (Pol II) during transcription and has important functi...
Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information
Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information
In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attent...
Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study
Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study
Correction to: Journal of Computer-Aided Molecular Design In the original publication of the articl...
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state
In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to...
Mur ligase F as a new target for the flavonoids quercitrin, myricetin, and (–)-epicatechin
Mur ligase F as a new target for the flavonoids quercitrin, myricetin, and (–)-epicatechin
MurC, D, E, and F are ATP-dependent ligases involved in the stepwise assembly of the tetrapeptide stem of forming peptidog...
The in silico identification of novel broad-spectrum antidotes for poisoning by organophosphate anticholinesterases
The in silico identification of novel broad-spectrum antidotes for poisoning by organophosphate anticholinesterases
Owing to their potential to cause serious adverse health effects, significant efforts have been made to develop antidotes ...
MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling
MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling
QSAR models capable of predicting biological, toxicity, and pharmacokinetic properties were widely used to search lead bio...
TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection
TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection
Drug discovery, especially virtual screening and drug repositioning, can be accelerated through deeper understanding and p...
Cooperative and structural relationships of the trimeric Spike with infectivity and antibody escape of the strains Delta (B.1.617.2) and Omicron (BA.2, BA.5, and BQ.1)
Cooperative and structural relationships of the trimeric Spike with infectivity and antibody escape of the strains Delta (B.1.617.2) and Omicron (BA.2, BA.5, and BQ.1)
Herein, we conducted simulations of trimeric Spike from several SARS-CoV-2 variants of concern (Delta and Omicron sub-vari...
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which...
Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals
Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals
Polarization and charge transfer strongly characterize the ligand-receptor interaction when metal atoms are present, as fo...
Exploring DrugCentral: from molecular structures to clinical effects
Exploring DrugCentral: from molecular structures to clinical effects
DrugCentral, accessible at https://drugcentral.org , is an open-access online drug information repository. It covers over ...
Discovery of novel and potent InhA direct inhibitors by ensemble docking-based virtual screening and biological assays
Discovery of novel and potent InhA direct inhibitors by ensemble docking-based virtual screening and biological assays
Multidrug-resistant tuberculosis (MDR-TB) continues to spread worldwide and remains one of the leading causes of death amo...
ChemFlow_py: a flexible toolkit for docking and rescoring
ChemFlow_py: a flexible toolkit for docking and rescoring
The design of accurate virtual screening tools is an open challenge in drug discovery. Several structure-based methods hav...
Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study
Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study
STAT3 belongs to a family of seven transcription factors. It plays an important role in activating the transcription of va...
Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory
Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory
We selected 145 reference organic molecules that include model fragments used in computer-aided drug design. We calculated...
A least-squares-fitting procedure for an efficient preclinical ranking of passive transport across the blood–brain barrier endothelium
A least-squares-fitting procedure for an efficient preclinical ranking of passive transport across the blood–brain barrier endothelium
The treatment of various disorders of the central nervous system (CNS) is often impeded by the limited brain exposure of d...
Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation
Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation
Generative approaches to molecular design are an area of intense study in recent years as a method to generate new pharmac...
Investigating the role of glycans in Omicron sub-lineages XBB.1.5 and XBB.1.16 binding to host receptor using molecular dynamics and binding free energy calculations
Investigating the role of glycans in Omicron sub-lineages XBB.1.5 and XBB.1.16 binding to host receptor using molecular dynamics and binding free energy calculations
Omicron derived lineages viz. BA.2, BA.3, BA.4 BA.5, BF.7 and XBBs show prominence with improved immune escape, transmissi...
Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design
Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design
Systematic optimization of large macrocyclic peptide ligands is a serious challenge. Here, we describe an approach for lea...
PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams
PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams
In this article, we present PoseEdit, a new, interactive frontend of the popular pose visualization tool PoseView. PoseEdi...
Exploring binding positions and backbone conformations of peptide ligands of proteins with a backbone-centred statistical energy function
Exploring binding positions and backbone conformations of peptide ligands of proteins with a backbone-centred statistical energy function
When designing peptide ligands based on the structure of a protein receptor, it can be very useful to narrow down the poss...
Enhancement by pyrazolones of colistin efficacy against mcr-1-expressing E. coli: an in silico and in vitro investigation
Enhancement by pyrazolones of colistin efficacy against mcr-1-expressing E. coli: an in silico and in vitro investigation
Owing to the emergence of antibiotic resistance, the polymyxin colistin has been recently revived to treat acute, multidru...
Correction to: Assessing the performance of docking, FEP, and MM/GBSA methods on a series of KLK6 inhibitors
Correction to: Assessing the performance of docking, FEP, and MM/GBSA methods on a series of KLK6 inhibitors
Cite this articleLima Silva, W., Ferreira de Freitas, R. Correction to: Assessing the performance of docking, FEP, and MM/...
Polygalic acid inhibits african swine fever virus polymerase activity: findings from machine learning and in vitro testing
Polygalic acid inhibits african swine fever virus polymerase activity: findings from machine learning and in vitro testing
African swine fever virus (ASFV), an extremely contagious virus with high mortality rates, causes severe hemorrhagic viral...
ADis-QSAR: a machine learning model based on biological activity differences of compounds
ADis-QSAR: a machine learning model based on biological activity differences of compounds
Drug candidates identified by the pharmaceutical industry typically have unique structural characteristics to ensure they ...
COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge
COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge
The SAMPL8 blind prediction challenge, which addresses the acid/base dissociation constants (pKa) and the distribution coe...
Insight on the mechanism of hexameric Pseudin-4 against bacterial membrane-mimetic environment
Insight on the mechanism of hexameric Pseudin-4 against bacterial membrane-mimetic environment
As an alternative to antibiotics, Antimicrobial Peptides (AMPs) possess unique properties including cationic, amphipathic ...
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