Abstract Cytochrome P450 (CYP) enzymes play an important role in the metabolism of xenobiotics. Since they are connected to drug interactions, screening for potential inhibitors is of utmost importance in drug discovery settings. Our study provides an extensive classification model for P450-drug interactions with one of the most prominent members, the 2C9 isoenzyme. Our model involved the largest set

Abstract Targeting the mu opioid receptor (MOR) by applying orthosteric ligands is the most frequently employed method to treat opioid use disorder (OUD). Unfortunately, most of MOR orthosteric ligands produce severe side effects, mainly due to their low selectivity over other opioid receptors. In contrast, some G protein-coupled receptor allosteric modulators have been reported to exhibit high subtype

Abstract Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein–ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-metallo and metallo PL complexes. Bappl+ outperforms other state-of-the-art scoring functions, achieving a high Pearson correlation coefficient of

Abstract The programmed cell death protein 1 (PD-1) and its ligand, PD-L1, constitute an important co-inhibitory immune checkpoint leading to downregulation of immune system. Tumor cells developed a strategy to trigger PD-1/PD-L1 pathway reducing the T cell anticancer activity. Anti-PD-L1 small drugs, generally with improved pharmacokinetic and technological profiles than monoclonal antibodies, became

Abstract Cell-penetrating peptides (CPPs) are short length permeable proteins have emerged as drugs delivery tool of therapeutic agents including genetic materials and macromolecules into cells. Recently, CPP has become a hotspot avenue for life science research and paved a new way of disease treatment without harmful impact on cell viability due to nontoxic characteristic. Therefore, the correct identification

Abstract Valproic acid (VPA) is a compound currently used in clinical practice for the treatment of epilepsy as well as bipolar and mood disorders. VPA targets histone deacetylases (HDACs), which participate in the removal of acetyl groups from lysine in several proteins, regulating a wide variety of functions within the organism. An imbalance or malfunction of these enzymes is associated with the

Reaction-based de novo design refers to the in-silico generation of novel chemical structures by combining reagents using structural transformations derived from known reactions. The driver for using reaction-based transformations is to increase the likelihood of the designed molecules being synthetically accessible. We have previously described a reaction-based de novo design method based on reaction

The decoupling approach to solvation free energy calculations requires scaling the interactions between the solute and the solution with all intramolecular interactions preserved. This paper reports a new procedure that makes it possible to these calculations in LAMMPS. The procedure is tested against built-in GROMACS capabilities. The model compounds chosen to test our methodology are ethanol and

Among still comparatively few G protein-coupled receptors, the adenosine A2A receptor has been co-crystallized with several ligands, agonists as well as antagonists. It can thus serve as a template with a well-described orthosteric ligand binding region for adenosine receptors. As not all subtypes have been crystallized yet, and in order to investigate the usability of homology models in this context

In this study, a new method is proposed for calculating the relative binding free energy between a ligand and a protein, derived from a free energy variational principle (FEVP). To address the shortcomings of the method used in our previous study, we incorporate the dynamical fluctuation of a ligand in the FEVP calculation. The present modified method is applied to the Pim-1-kinase-ligand system and

The SAMPL Challenges aim to focus the biomolecular and physical modeling community on issues that limit the accuracy of predictive modeling of protein-ligand binding for rational drug design. In the SAMPL5 log D Challenge, designed to benchmark the accuracy of methods for predicting drug-like small molecule transfer free energies from aqueous to nonpolar phases, participants found it difficult to make

In this work, we analyze the structure-activity relationships (SAR) of epigenetic inhibitors (lysine mimetics) against lysine methyltransferase (G9a or EHMT2) using a combined activity landscape, molecular docking and molecular dynamics approach. The study was based on a set of 251 G9a inhibitors with reported experimental activity. The activity landscape analysis rapidly led to the identification

Accurately computing partition coefficients is a pivotal part of drug discovery. Specifically, octanol-water partition coefficients can provide information into hydrophobicity of drug-like molecules, as well as a de facto representation of membrane permeability. However, one challenge facing the computation of partition coefficients is the need to encapsulate various microscopic environments. These

Classical molecular simulation methods were used for a description of an arrangement of intercalated molecules N-(pyridin-4-yl)pyridin-4-amine (AH) and its derivatives, 3-methyl-N-(pyridin-4-yl)pyridin-4-amine (AMe), and 3-nitro-N-(pyridin-4-yl)pyridin-4-amine (ANO2) within a layered structure of zirconium 4-sulfophenylphosphonate. The intercalated molecules were placed between SO3H groups of the host

The pKa is the standard measure used to describe the aqueous proton affinity of a compound, indicating the proton concentration (pH) at which two protonation states (e.g. A- and AH) have equal free energy. However, compounds can have additional protonation states (e.g. AH2+), and may assume multiple tautomeric forms, with the protons in different positions (microstates). Macroscopic pKas give the pH

The c-Jun N-terminal kinase 3 (JNK3) signaling cascade is activated during cerebral ischemia leading to neuronal damage. The present study was carried out to identify and evaluate novel JNK3 inhibitors using in-silico and in-vitro approach. A total of 380 JNK3 inhibitors belonging to different organic groups was collected from the previously reported literature. These molecules were used to generate

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

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

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

Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed using molecular fingerprints and a deep neural network. The machine learning model was trained on a dataset of 12,000 molecules and tested on 2000 molecules

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these

Results are reported for octanol-water partition coefficients (log P) of the neutral states of drug-like molecules provided during the SAMPL6 (Statistical Assessment of Modeling of Proteins and Ligands) blind prediction challenge from applying the "embedded cluster reference interaction site model" (EC-RISM) as a solvation model for quantum-chemical calculations. Following the strategy outlined during

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and

Host-guest binding is a challenging problem in computer simulation. The prediction of binding affinities between hosts and guests is an important part of the statistical assessment of the modeling of proteins and ligands (SAMPL) challenges. In this work, the volume-based variant of well-tempered metadynamics is employed to calculate the binding affinities of the host-guest systems in the SAMPL6 challenge

Macrocycles represent an important class of medicinally relevant small molecules due to their interesting biological properties. Therefore, a firm understanding of their conformational preferences is important for drug design. Given the importance of macrocycle-protein modelling in drug discovery, we envisaged that a systematic study of both classical and recent specialized methods would provide guidance

The rapid development of new machine learning techniques led to significant progress in the area of computer-aided drug design. However, despite the enormous predictive power of new methods, they lack explainability and are often used as black boxes. The most important decisions in drug discovery are still made by human experts who rely on intuitions and simplified representation of the field. We used

Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchmarked and validated. We reanalyze the data generated by a recently published large-scale comparison of machine learning models for bioactivity prediction

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

In molecular modeling the description of the interactions between molecules forms the basis for a correct prediction of macroscopic observables. Here, we derive atomic charges from the implicitly polarized electron density of 11 molecules in the SAMPL6 challenge using the Hirshfeld-I and Minimal Basis Set Iterative Stockholder (MBIS) partitioning method. These atomic charges combined with other parameters

The water-octanol partition coefficient is an important physicochemical property for small molecule drug design. Here, we report our participation in the SAMPL6 logP prediction challenge with free energy perturbation (FEP) calculations in the water phase and in the 1-octanol phase using Drude polarizable force fields. Root mean square error (RMSE) and mean absolute error (MAE) of our prediction are

Bending of double-stranded (ds) DNA plays a crucial role in many important biological processes and is relevant for nanotechnological applications. Among all the elements that have been studied in relation to dsDNA bending, A-tracts stand out as one of the most controversial. The "ApA wedge" theory was disproved when a series of linear polynucleotides containing phased 5'-A4T4-3' or 5'-T4A4-3' runs

In this study quantum mechanical methods were used to predict the solvation energies of a series of drug-like molecules both in water and in octanol, in the context of the SAMPL6 n-octanol/water partition coefficient challenge. In pharmaceutical design, n-octanol/water partition coefficient, LogP, describes the drug's hydrophobicity and membrane permeability, thus, a well-established theoretical method

This work presents a quantum mechanical model for predicting octanol-water partition coefficients of small protein-kinase inhibitor fragments as part of the SAMPL6 LogP Prediction Challenge. The model calculates solvation free energy differences using the M06-2X functional with SMD implicit solvation and the def2-SVP basis set. This model was identified as dqxk4 in the SAMPL6 Challenge and was the

Effective representation of a molecule is required to develop useful quantitative structure-property relationships (QSPR) for accurate prediction of chemical properties. The octanol-water partition coefficient logP, a measure of lipophilicity, is an important property for pharmacological and toxicological endpoints used in the pharmaceutical and regulatory spheres. We compare physicochemical descriptors

Small molecules binding at any of the multiple regulatory sites on the molecular surface of a protein kinase may stabilize or disrupt the corresponding interaction, leading to consequent modulation of the kinase cellular activity. As such, each of these sites represents a potential drug target. Even targeting sites outside the immediate ATP site, the so-called exosites, may cause desirable biological

Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded manner. We participated in the beta-secretase 1 (BACE) Subchallenge which is comprised of cross-docking and redocking of 20 macrocyclic ligands to BACE and predicting binding affinity for 154 macrocyclic

We have developed an algorithm that enables simplified box orbital functions (SBO) to be obtained with optimized coefficients by fitting them to functions of many types. SBOs are a linear combination of radial functions useful in quantum chemistry calculations which can be spatially restricted (defined in [Formula: see text] interval, and zero for [Formula: see text]). The algorithm proposed makes

In the construction of activity prediction models, the use of feature ranking methods is a useful mechanism for extracting information for ranking features in terms of their significance to develop predictive models. This paper studies the influence of feature rankers in the construction of molecular activity prediction models; for this purpose, a comparative study of fourteen rankings methods for

We describe a new template-based method for docking flexible ligands such as macrocycles to proteins. It combines Monte-Carlo energy minimization on the manifold, a fast manifold search method, with BRIKARD for complex flexible ligand searching, and with the MELD accelerator of Replica-Exchange Molecular Dynamics simulations for atomistic degrees of freedom. Here we test the method in the Drug Design

Partition coefficients describe the equilibrium partitioning of a single, defined charge state of a solute between two liquid phases in contact, typically a neutral solute. Octanol-water partition coefficients ([Formula: see text]), or their logarithms (log P), are frequently used as a measure of lipophilicity in drug discovery. The partition coefficient is a physicochemical property that captures

Linezolid, an antibiotic of oxazolidinone family, is a translation inhibitor. The mechanism of its action that consists in preventing the binding of aminoacyl-tRNA to the A-site of the large subunit of a ribosome was embraced on the basis of the X-ray structural analysis of the linezolid complexes with vacant bacterial ribosomes. However, the known structures of the linezolid complexes with bacterial

Abnormalities in the expression levels of EGFR/HER2 are found in many different types of human cancer; therefore, the design of dual inhibitors of EGFR/HER2 is a recognized anti-cancer strategy. Some lapatinib derivatives have been previously synthesized by modification at the methylsulfonylethylaminomethylfuryl group and biologically evaluated, demonstrating that the 2i compound shows potent inhibitory

DNA is an essential target for the treatment of various pathologies, especially cancer. Hence targeting DNA double helix for alteration of its function has been attempted by several ways. Drug-DNA intercalation, one such biophysical process, could not be studied extensively as this requires significant deformation of the receptor DNA. Here we report thorough theoretical investigation of intercalation

Escherichia coli (E. coli) K1 is the most common Gram-negative bacteria cause of neonatal meningitis. The penetration of E. coli through the blood-brain barrier is a key step of the meningitis pathogenesis. A host receptor protein, Caspr1, interacts with the E. coli virulence factor IbeA and thus facilitates bacterial penetration through the blood-brain barrier. Based on this result, we have now predicted

Attachment of envelope glycoprotein gp120 to the host cell receptor CD4 is the first step during the human immunodeficiency virus-1 (HIV-1) entry into the host cells that makes it a promising target for drug design. To elucidate the crucial three dimensional (3D) structural features of reported HIV-1 gp120 CD4 binding inhibitors, 3D pharmacophores were generated and receptor based approach was employed

Small molecules with multi-target activity, also termed promiscuous compounds, are increasingly considered for pharmaceutical applications. The use of promiscuous chemical entities represents a departure from the compound specificity paradigm, one of the pillars of modern drug discovery. The popularity of promiscuous compounds is due to the concept of polypharmacology; another more recent drug discovery

The D3R Grand Challenge 4 provided a brilliant opportunity to test macrocyclic docking protocols on a diverse high-quality experimental data. We participated in both pose and affinity prediction exercises. Overall, we aimed to use an automated structure-based docking pipeline built around a set of tools developed in our team. This exercise again demonstrated a crucial importance of the correct local

The Drug Design Data Resource (D3R) Grand Challenges present an opportunity to assess, in the context of a blind predictive challenge, the accuracy and the limits of tools and methodologies designed to help guide pharmaceutical drug discovery projects. Here, we report the results of our participation in the D3R Grand Challenge 4 (GC4), which focused on predicting the binding poses and affinity ranking

Targeting of MDM2-p53 protein-protein interaction is a current approach for the development of potent anticancer agents. The classical pharmacophore hypothesis for the design of such molecules describes the three point binding of a small molecule inhibitor to the MDM2 protein. However, this hypothesis is not confirmed when considering the activity of a number of known potent MDM2 inhibitors. Here we

Accurate solvation free energy ΔGsolv predictions require well parametrized force fields. In order to refit Lennard-Jones (LJ) parameters for improved ΔGsolv predictions for a variety of compound classes and chemical environments, a large number of ΔGsolv calculations is required. As the calculation of ΔGsolv is computational expensive, there is need for efficient but precise calculation methods. In

The IEFPCM/MST continuum solvation model is used for the blind prediction of n-octanol/water partition of a set of 11 fragment-like small molecules within the SAMPL6 Part II Partition Coefficient Challenge. The partition coefficient of the neutral species (log P) was determined using an extended parametrization of the B3LYP/6-31G(d) version of the Miertus–Scrocco–Tomasi continuum solvation model in

Influenza epidemics are responsible for an average of 3-5 millions of severe cases and up to 500,000 deaths around the world. One of flu pandemic types is influenza A(H1N1)pdm09 virus (pdm09H1N1). Oseltamivir is the antiviral drug used to treat influenza targeting at neuraminidase (NA) located on the viral surface. Influenza virus undergoes high mutation rates and leads to drug resistance, and thus

Within the framework of the 6th physical property blind challenge (SAMPL6) the authors have participated in predicting the octanol–water partition coefficients (logP) for several small drug like molecules. Those logP values where experimentally known by the organizers but only revealed after the submissions of the predictions. Two different sets of predictions were submitted by the authors, both based

Application of a small radius of the hydrogen atom in molecular-mechanical models of hydrogen bonding improves the estimate of the solvation free energy of organic substances. At the same time, the density and evaporation heat of the bulk water vary slightly and are close to experimental values. Blind testing drug candidates in the SAMPL6 simulation competition showed that using the same Lennard-Jones

Abstract Imbalanced datasets, comprising of more inactive compounds relative to the active ones, are a common challenge in ligand-based model building workflows for drug discovery. This is particularly true for neglected tropical diseases since efforts to identify therapeutics for these diseases are often limited. In this report, we analyze the performance of several undersampling strategies in modeling

We investigated the Gi-coupled A3 adenosine receptor (A3AR) activation mechanism by running 7.2 µs of molecular dynamics (MD) simulations. Based on homology to G protein-coupled receptor (GPCR) structures, three constitutively active mutant (CAM) and the wild-type (WT) A3ARs in the apo form were modeled. Conformational signatures associated with three different receptor states (inactive R, active R*

The Glucagon-like peptide 1 receptor (GLP-1R) is a well-established target for the treatment of type 2 diabetes and GLP-1R agonist-based therapies represent an effective approach which results in several GLP-1 analog drugs. However, the development of nonpeptidic agonist drugs targeting GLP-1R remains unsuccessful. A promising strategy aims to develop orally bioavailable, small-molecule positive allosteric

The in silico prediction of partition coefficients is an important task in computer-aided drug discovery. In particular the octanol–water partition coefficient is used as surrogate for lipophilicity. Various computational approaches have been proposed, ranging from simple group-contribution techniques based on the 2D topology of a molecule to rigorous methods based molecular dynamics (MD) or quantum

Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from non-inhibitors using molecular solvation theory with excellent accuracy and precision. The excess chemical potential and partial molar volume in various