Deep Learning Applied to Ligand-Based De Novo Drug Design.

In the latest years, the application of deep generative models to suggest virtual compounds is becoming a new and powerful tool in drug discovery projects. The idea behind this review is to offer an updated view on de novo design approaches based on artificial intelligent (AI) algorithms, with a particular focus on ligand-based methods. We start this review by reporting a brief overview of the most relevant de novo design approaches developed before the use of AI techniques.

BIreactive: A Machine-Learning Model to Estimate Covalent Warhead Reactivity.

In the past decade, the pharmaceutical industry has paid closer attention to covalent drugs. Differently from standard noncovalent drugs, these compounds can exhibit peculiar properties, such as higher potency or longer duration of target inhibition with a potentially lower dosage. These properties are mainly driven by the reactive functional group present in the compound, the so-called warhead that forms a covalent bond with a specific nucleophilic amino-acid on the target.

Folding intermediate states of the parallel human telomeric G-quadruplex DNA explored using Well-Tempered Metadynamics.

An increasingly comprehension of the folding intermediate states of DNA G-quadruplexes (G4s) is currently an important scientific challenge, especially for the human telomeric (h-tel) G4s-forming sequences, characterized by a highly polymorphic nature. Despite the G-triplex conformation was proposed as one of the possible folding intermediates for the antiparallel and hybrid h-tel G4s, for the parallel h-tel topology with an all-anti guanine orientation, a vertical strand-slippage involving the G-triplets was proposed in previous works through microseconds-long standard molecular dynamics simulations (MDs). Here, in order to get further insights into the vertical strand-slippage and the folding intermediate states of the parallel h-tel G4s, we have carried out a Well-Tempered Metadynamics simulation (WT-MetaD), which allowed us to retrieve an ensemble of six G4s having two/G-tetrad conformations derived by the G-triplets vertical slippage.

A Fast Ab Initio Predictor Tool for Covalent Reactivity Estimation of Acrylamides.

Thanks to their unique mode of action, covalent drugs represent an exceptional opportunity for drug design. After binding to a biologically relevant target system, covalent compounds form a reversible or irreversible covalent bond with a nucleophilic amino acid. Due to the inherently large binding energy of a covalent bond, covalent binders exhibit higher potencies and thus allow potentially lower drug dosages.

Conformational Entropy as Collective Variable for Proteins.

Many enhanced sampling methods rely on the identification of appropriate collective variables. For proteins, even small ones, finding appropriate descriptors has proven challenging. Here we suggest that the NMR S order parameter can be used to this effect.

Correction: Facile synthesis of stable, water soluble, dendron-coated gold nanoparticles.

Correction for 'Facile synthesis of stable, water soluble, dendron-coated gold nanoparticles' by Alan E. Enciso, et al., Nanoscale, 2017, 9, 3128-3132.

The impact of methylphenidate and its enantiomers on dopamine synthesis and metabolism in vitro.

Methylphenidate (MPH), a psychostimulant, is an effective first-line treatment for the symptoms associated with Attention-Deficit/Hyperactivity Disorder (ADHD). Although most MPH formulations are composed of the racemic 1:1 mixture of the two enantiomers (d- and l-threo), converging lines of evidence indicate that d-threo MPH seems to be superior to the l-isomer. We aimed to investigate whether MPH racemic mixture or pure enantiomers influence the enzyme activity of tyrosine hydroxylase (TH), monoamine oxidase B (MAO-B), catechol-O-methyltransferase (COMT), and aldehyde dehydrogenase (ALDH) in vitro in homogenates of rat PC12 cells incubated with racemic, d- and l-threo MPH (1nM up to 100μM), or a vehicle for control.

Facile synthesis of stable, water soluble, dendron-coated gold nanoparticles.

Upon reduction with sodium borohydride, diazonium tetrachloroaurate salts of triazine dendrons yield dendron-coated gold nanoparticles connected by a gold-carbon bond. These robust nanoparticles are stable in water and toluene solutions for longer than one year and present surface groups that can be reacted to change surface chemistry and manipulate solubility. Molecular modeling was used to provide insight on the hydration of the nanoparticles and their observed solubilties.

Focus on PNA Flexibility and RNA Binding using Molecular Dynamics and Metadynamics.

Peptide Nucleic Acids (PNAs) can efficiently target DNA or RNA acting as chemical tools for gene regulation. Their backbone modification and functionalization is often used to increase the affinity for a particular sequence improving selectivity. The understanding of the trading forces that lead the single strand PNA to bind the DNA or RNA sequence is preparatory for any further rational design, but a clear and unique description of this process is still not complete.

Dimer Metadynamics.

Sampling complex potential energies is one of the most pressing challenges of contemporary computational science. Inspired by recent efforts that use quantum effects and discretized Feynman's path integrals to overcome large barriers we propose a replica exchange method that we expect to be effective at least for systems of up to 150 atoms roughly. In each replica two copies of the same system with halved potential strengths interact via inelastic springs.

Communication: Role of explicit water models in the helix folding/unfolding processes.

In the last years, it has become evident that computer simulations can assume a relevant role in modelling protein dynamical motions for their ability to provide a full atomistic image of the processes under investigation. The ability of the current protein force-fields in reproducing the correct thermodynamics and kinetics systems behaviour is thus an essential ingredient to improve our understanding of many relevant biological functionalities. In this work, employing the last developments of the metadynamics framework, we compare the ability of state-of-the-art all-atom empirical functions and water models to consistently reproduce the folding and unfolding of a helix turn motif in a model peptide.

General Protein Data Bank-Based Collective Variables for Protein Folding.

New, automated forms of data analysis are required to understand the high-dimensional trajectories that are obtained from molecular dynamics simulations on proteins. Dimensionality reduction algorithms are particularly appealing in this regard as they allow one to construct unbiased, low-dimensional representations of the trajectory using only the information encoded in the trajectory. The downside of this approach is that a different set of coordinates are required for each different chemical system under study precisely because the coordinates are constructed using information from the trajectory.

de Broglie Swapping Metadynamics for Quantum and Classical Sampling.

This paper builds on our previous work on Path Integral Metadynamics [ Ruge et al. J. Chem.

Accuracy of current all-atom force-fields in modeling protein disordered states.

Molecular Dynamics (MD) plays a fundamental role in characterizing protein disordered states that are emerging as crucial actors in many biological processes. Here we assess the accuracy of three current force-fields in modeling disordered peptides by combining enhanced-sampling MD simulations with NMR data. These force-fields generate significantly different conformational ensembles, and AMBER03w [ Best and Mittal J.

The allosteric communication pathways in KIX domain of CBP.

Allosteric regulation plays an important role in a myriad of biomacromolecular processes. Specifically, in a protein, the process of allostery refers to the transmission of a local perturbation, such as ligand binding, to a distant site. Decades after the discovery of this phenomenon, models built on static images of proteins are being reconsidered with the knowledge that protein dynamics plays an important role in its function.