Identification of Conserved Water Sites in Protein Structures for Drug Design

Water and chloride as allosteric inhibitors in WNK kinase osmosensing

Previous observations showed that chloride and osmotic stress regulate the autophosphorylation and activity of the kinase domains of WNK1 and WNK3. Further, prior crystallography on the asymmetric dimeric of the unphosphorylated WNK1 kinase domain (WNK1/S382A, WNK1/SA) revealed conserved waters in the active site. Here we show by crystallography that PEG400 applied to crystals of dimeric WNK1/SA grown in space group P1 induces de-dimerization with a change in space group to P2 1 . Both the conserved waters, referred to here as conserved water network 1 (CWN1) and the chloride binding site are disrupted by PEG400. CWN1 is surrounded and stabilized by a pan-WNK-conserved cluster of charged residues. Here we mutagenized these charges in WNK3 to probe the importance of the CWN1 to WNK regulation. Two mutations at E314 in the Activation Loop (WNK3/E314Q and WNK3/E314A) enhanced activity, consistent with the idea that the CWN1 is inhibitory. Mutations of other residues in the cluster had similar or less activity than wild-type. PEG400 activation of WNK3 was not significantly reduced in the point mutants tested. The crystallographic and assay data support a role for CWN1 and the charged cluster in stabilizing an inactive configuration of WNKs and suggest that water functions as an allosteric inhibitor of WNKs.

Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach

In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.

Ultra-high resolution X-ray structure of orthorhombic bovine pancreatic Ribonuclease A at 100K

The crystal structure of orthorhombic Bovine Pancreatic Ribonuclease A has been determined to 0.85 Å resolution using low temperature, 100 K, synchrotron X-ray data collected at 16000 keV (λ = 0.77 Å). This is the first ultra-high-resolution structure of a native form of Ribonuclease A to be reported. Refinement carried out with anisotropic displacement parameters, stereochemical restraints, inclusion of H atoms in calculated positions, five [Formula: see text] moieties, eleven ethanol molecules and 293 water molecules, converged with final R values of R1(Free) = 0.129 (4279 reflections) and R1 = 0.112 (85,346 reflections). The refined structure was deposited in the Protein Data Bank as structure 7p4r. Conserved waters, using four high resolution structures, have been investigated. Cluster analysis identified clusters of water molecules that are associated with the active site of Bovine Ribonuclease A. Particular attention has been paid to making detailed comparisons between the present structure and other high quality Bovine Pancreatic Ribonuclease A X-ray crystal structures with special reference to the deposited classic monoclinic structure 3RN3 Howlin et al. (Acta Crystallogr A 45:851-861, 1989). Detailed studies of various aspects of hydrogen bonding and conformation have been carried out with particular reference to active site residues Lys-1, Lys-7, Gln-11, His-12, Lys-41, Asn-44, Thr-45, Lys-66, His-119 and Ser-123. For the two histidine residues in the active site the initial electron density map gives a clear confirmation that the position of His-12 is very similar in the orthorhombic structure to that in 3RN3. In 3RN3 His-119 exhibited poor electron density which was modelled and refined as two distinct sites, A (65%) and B (35%) but with respect to His-119 in the present ultra-high resolution orthorhombic structure there is clear electron density which was modelled and refined as a single conformation distinct from either conformation A or B in 3RN3. Other points of interest include Serine-32 which is disordered at the end of the sidechain in the present orthorhombic form but has been modelled as a single form in 3RN3. Lysine-66: there is density indicating a possible conformation for this residue. However, the density is relatively weak, and the conformation is unclear. Three types of amino acid representation in the ultra-high resolution electron density are examined: (i) sharp with very clearly resolved features, for example Lys-37; (ii) well resolved but clearly divided into two conformations which are well behaved in the refinement, both having high quality geometry, for example Tyr-76; (iii) poor density and difficult or impossible to model, an example is Lys-31 for which density is missing except for Cβ. The side chains of Gln-11, His-12, Lys-41, Thr-45 and His-119 are generally recognised as being closely involved in the enzyme activity. It has also been suggested that Lys-7, Asp-44, Lys-66, Phe-120, Asp-121 and Ser-123 may also have possible roles in this mechanism. A molecular dynamics study on both structures has investigated the conformations of His-119 which was modelled as two conformations in 3RN3 but is observed to have a single clearly defined conformation in the present orthorhombic structure. MD has also been used to investigate Lys-31, Lys-41 and Ser32. The form of the Ribonuclease A enzyme used in both the present study and in 3RN3 (Howlin et al. in Acta Crystallogr A 45:851-861, 1989) includes a sulphate anion which occupies approximately the same location as the [Formula: see text] phosphate group in protein nucleotide complexes (Borkakoti et al. in J Mol Biol 169:743-755, 1983). The present structure contains 5 [Formula: see text] groups SO41151-SO41155 two of which, SO41152 and SO41153 are disordered, SO41152 being in the active site, and 11 EtOH molecules, EOH A 201-EOH A 211 all of which have good geometry. H atoms were built into the EtOH molecules geometrically. Illustrations of these features in the present structure are included here. The sulphates are presumably present in the material purchased for use in the present study. 293 water molecules are included in the present structure compared to 134 in 3RN3 (Howlin et al. in Acta Crystallogr A 45:851-861, 1989).

The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering

Water is a key actor of various processes of nature and, therefore, molecular engineering has to take the structural and energetic consequences of hydration into account. While the present review focuses on the target-ligand interactions in drug design, with a focus on biomolecules, these methods and applications can be easily adapted to other fields of the molecular engineering of molecular complexes, including solid hydrates. The review starts with the problems and solutions of the determination of water structures. The experimental approaches and theoretical calculations are summarized, including conceptual classifications. The implementations and applications of water models are featured for the calculation of the binding thermodynamics and computational ligand docking. It is concluded that theoretical approaches not only reproduce or complete experimental water structures, but also provide key information on the contribution of individual water molecules and are indispensable tools in molecular engineering.

Structure-Based Identification of Naphthoquinones and Derivatives as Novel Inhibitors of Main Protease Mpro and Papain-like Protease PLpro of SARS-CoV-2

The worldwide COVID-19 pandemic caused by the coronavirus SARS-CoV-2 urgently demands novel direct antiviral treatments. The main protease (Mpro) and papain-like protease (PLpro) are attractive drug targets among coronaviruses due to their essential role in processing the polyproteins translated from the viral RNA. In this study, we virtually screened 688 naphthoquinoidal compounds and derivatives against Mpro of SARS-CoV-2. Twenty-four derivatives were selected and evaluated in biochemical assays against Mpro using a novel fluorogenic substrate. In parallel, these compounds were also assayed with SARS-CoV-2 PLpro. Four compounds inhibited Mpro with half-maximal inhibitory concentration (IC50) values between 0.41 μM and 9.0 μM. In addition, three compounds inhibited PLpro with IC50 ranging from 1.9 μM to 3.3 μM. To verify the specificity of Mpro and PLpro inhibitors, our experiments included an assessment of common causes of false positives such as aggregation, high compound fluorescence, and inhibition by enzyme oxidation. Altogether, we confirmed novel classes of specific Mpro and PLpro inhibitors. Molecular dynamics simulations suggest stable binding modes for Mpro inhibitors with frequent interactions with residues in the S1 and S2 pockets of the active site. For two PLpro inhibitors, interactions occur in the S3 and S4 pockets. In summary, our structure-based computational and biochemical approach identified novel naphthoquinonal scaffolds that can be further explored as SARS-CoV-2 antivirals.

Protein binding sites for drug design

Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules-ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov.

ProBiS-Fold Approach for Annotation of Human Structures from the AlphaFold Database with No Corresponding Structure in the PDB to Discover New Druggable Binding Sites

ProBiS (Protein Binding Sites), a local structure-based comparison algorithm, is used in the new ProBiS-Fold web server to annotate human structures from the AlphaFold database without a corresponding structure in the Protein Data Bank (PDB) to discover new druggable binding sites. The ProBiS algorithm is used to compare each query protein structure predicted by the AlphaFold approach with the protein structures from the PDB to identify similarities between known binding sites found in the PDB and yet unknown binding sites in the AlphaFold database. Ligands bound in these identified similar PDB sites are then transferred to each query protein from the AlphaFold database, and binding sites are identified as ligand clusters on an AlphaFold protein. Small molecule binding sites are assigned druggability scores based on the similarity of their ligands to known drugs, allowing them to be ranked according to their perceived and actual potential for drug development. ProBiS-Fold provides interactive and downloadable binding sites for the entire human structural proteome, including more than 3000 new druggable binding sites that have no corresponding structure in the PDB, taking into account AlphaFold's model quality, to enable protein structure-function relationship studies and pharmaceutical drug discovery research. The web server is freely accessible to academic users at http://probis-fold.insilab.org.

Boosting the Full Potential of PyMOL with Structural Biology Plugins

Over the past few decades, the number of available structural bioinformatics pipelines, libraries, plugins, web resources and software has increased exponentially and become accessible to the broad realm of life scientists. This expansion has shaped the field as a tangled network of methods, algorithms and user interfaces. In recent years PyMOL, widely used software for biomolecules visualization and analysis, has started to play a key role in providing an open platform for the successful implementation of expert knowledge into an easy-to-use molecular graphics tool. This review outlines the plugins and features that make PyMOL an eligible environment for supporting structural bioinformatics analyses.

Rational Design of Chitin Deacetylase Inhibitors for Sustainable Agricultural Use Based on Molecular Topology

Fungicide resistance is a major concern in modern agriculture; therefore, there is a pressing demand to develop new, greener chemicals. Chitin is a major component of the fungal cell wall and a well-known elicitor of plant immunity. To overcome chitin recognition, fungal pathogens developed different strategies, with chitin deacetylase (CDA) activity being the most conserved. This enzyme is responsible for hydrolyzing the N-acetamido group in N-acetylglucosamine units of chitin to convert it to chitosan, a compound that can no longer be recognized by the plant. In previous works, we observed that treatments with CDA inhibitors, such as carboxylic acids, reduced the symptoms of cucurbit powdery mildew and induced rapid activation of chitin-triggered immunity, indicating that CDA could be an interesting target for fungicide development. In this work, we developed an in silico strategy based on QSAR (quantitative structure-activity relationship) and molecular topology (MT) to discover new, specific, and potent CAD inhibitors. Starting with the chemical structures of few carboxylic acids, with and without disease control activity, three predictive equations based on the MT paradigm were developed to identify a group of potential molecules. Their fungicidal activity was experimentally tested, and their specificity as CDA inhibitors was studied for the three best candidates by molecular docking simulations. To our knowledge, this is the first time that MT has been used for the identification of potential CDA inhibitors to be used against resistant powdery mildew strains. In this sense, we consider of special interest the discovery of molecules capable of stimulating the immune system of plants by triggering a defensive response against fungal species that are highly resistant to fungicides such as powdery mildew.

Imidazole and nitroimidazole derivatives as NADH-fumarate reductase inhibitors: Density functional theory studies, homology modeling, and molecular docking

Chagas disease is caused by Trypanosoma cruzi. Benznidazole and nifurtimox are drugs used for its therapy; nevertheless, they have collateral effects. NADH-fumarate (FUM) reductase is a potential pharmacological target since it is essential for survival of parasite and is not found in humans. The objectives are to design and characterize the electronic structure of imidazole and nitroimidazole derivatives at DFT-M06-2X level in aqueous solution; also, to model the NADH-FUM reductase and analyze its intermolecular interactions by molecular docking. Quantum-chemical descriptors allowed to select the molecules with the best physicochemical properties and lowest toxicity. A high-quality three-dimensional structure of NADH-FUM reductase was obtained by homology modeling. Water molecules do not have influence in the interaction between FUM and NADH-FUM reductase. The main hydrogen-binding interactions for FUM were identified in NADH, Lys172, and Arg89; while hydrophobic interactions in Phe479, Thr174, Met63. The molecules S3-8, S2-8, and S1-8 could be inhibitors of NADH-FUM reductase.

Structure-based identification of naphthoquinones and derivatives as novel inhibitors of main protease Mpro and papain-like protease PLpro of SARS-CoV-2

The worldwide COVID-19 pandemic caused by the coronavirus SARS-CoV-2 urgently demands novel direct antiviral treatments. The main protease (Mpro) and papain-like protease (PLpro) are attractive drug targets among coronaviruses due to their essential role in processing the polyproteins translated from the viral RNA. In the present work, we virtually screened 688 naphthoquinoidal compounds and derivatives against Mpro of SARS-CoV-2. Twenty-four derivatives were selected and evaluated in biochemical assays against Mpro using a novel fluorogenic substrate. In parallel, these compounds were also assayed with SARS-CoV-2 PLpro. Four compounds inhibited Mpro with half-maximal inhibitory concentration (IC ₅₀ ) values between 0.41 µM and 66 µM. In addition, eight compounds inhibited PLpro with IC ₅₀ ranging from 1.7 µM to 46 µM. Molecular dynamics simulations suggest stable binding modes for Mpro inhibitors with frequent interactions with residues in the S1 and S2 pockets of the active site. For two PLpro inhibitors, interactions occur in the S3 and S4 pockets. In summary, our structure-based computational and biochemical approach identified novel naphthoquinonal scaffolds that can be further explored as SARS-CoV-2 antivirals.

Water molecules at protein-drug interfaces: computational prediction and analysis methods

The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.

ProBiS-Dock Database: A Web Server and Interactive Web Repository of Small Ligand-Protein Binding Sites for Drug Design

We have developed a new system, ProBiS-Dock, which can be used to determine the different types of protein binding sites for small ligands. The binding sites identified this way are then used to construct a new binding site database, the ProBiS-Dock Database, that allows for the ranking of binding sites according to their utility for drug development. The newly constructed database currently has more than 1.4 million binding sites and offers the possibility to investigate potential drug targets originating from different biological species. The interactive ProBiS-Dock Database, a web server and repository that consists of all small-molecule ligand binding sites in all of the protein structures in the Protein Data Bank, is freely available at http://probis-dock-database.insilab.org. The ProBiS-Dock Database will be regularly updated to keep pace with the growth of the Protein Data Bank, and our anticipation is that it will be useful in drug discovery.

MHCBI: a pipeline for calculating peptide-MHC binding energy using semi-empirical quantum mechanical methods with explicit/implicit solvent models

Experimentally estimating peptide-major histocompatibility complex (pMHC) binding affinity has been quite challenging due to the many receptors and the many potential ligands implicated in it. We have thus proposed a straightforward computational methodology considering the different mechanisms involved in pMHC binding to facilitate studying such receptor-ligand interactions. We have developed a pipeline using semi-empirical quantum mechanical methods for calculating pMHC class I and II molecules' binding energy (BE). This pipeline can systematize the methodology for calculating pMHC system BE, enabling the rational design of T-cell epitopes to be used as pharmaceuticals and vaccines.

Assessment of CYP2C9 Structural Models for Site of Metabolism Prediction

Structure-based prediction of a compound's potential sites of metabolism (SOMs) mediated by cytochromes P450 (CYPs) is highly advantageous in the early stage of drug discovery. However, the accuracy of the SOMs prediction can be influenced by several factors. CYP2C9 is one of the major drug-metabolizing enzymes in humans and is responsible for the metabolism of ∼13 % of clinically used drugs. In this study, we systematically evaluated the effects of protein crystal structure models, scoring functions, heme forms, conserved active-site water molecules, and protein flexibility on SOMs prediction of CYP2C9 substrates. Our results demonstrated that, on average, ChemScore and GlideScore outperformed four other scoring functions: Vina, GoldScore, ChemPLP, and ASP. The performance of the crystal structure models with pentacoordinated heme was generally superior to that of the hexacoordinated iron-oxo heme (referred to as Compound I) models. Inclusion of the conserved active-site water molecule improved the prediction accuracy of GlideScore, but reduced the accuracy of ChemScore. In addition, the effect of the conserved water on SOMs prediction was found to be dependent on the receptor model and the substrate. We further found that one of snapshots from molecular dynamics simulations on the apo form can improve the prediction accuracy when compared to the crystal structural model.

Tuning Local Hydration Enables a Deeper Understanding of Protein-Ligand Binding: The PP1-Src Kinase Case

Water plays a key role in biomolecular recognition and binding. Despite the development of several computational and experimental approaches, it is still challenging to comprehensively characterize water-mediated effects on the binding process. Here, we investigate how water affects the binding of Src kinase to one of its inhibitors, PP1. Src kinase is a target for treating several diseases, including cancer. We use biased molecular dynamics simulations, where the hydration of predetermined regions is tuned at will. This computational technique efficiently accelerates the SRC-PP1 binding simulation and allows us to identify several key and yet unexplored aspects of the solvent's role. This study provides a further perspective on the binding phenomenon, which may advance the current drug design approaches for the development of new kinase inhibitors.

Indoleamine and tryptophan 2,3-dioxygenases as important future therapeutic targets

Conversion of tryptophan to N-formylkynurenine is the first and rate-limiting step of the tryptophan metabolic pathway (i.e., the kynurenine pathway). This conversion is catalyzed by three enzyme isoforms: indoleamine 2,3-dioxygenase 1 (IDO1), indoleamine 2,3-dioxygenase 2 (IDO2), and tryptophan 2,3-dioxygenase (TDO). As this pathway generates numerous metabolites that are involved in various pathological conditions, IDOs and TDO represent important targets for therapeutic intervention. This pathway has especially drawn attention due to its importance in tumor resistance. Over the last decade, a large number of IDO and TDO inhibitors have been developed, many of which have entered clinical trials. Here, detailed structural comparisons of these three enzymes (with emphasis on their active sites), their involvement in cellular signaling, and their role(s) in pathological conditions are discussed. Furthermore, the most important recent inhibitors described in papers and patents and involved in clinical trials are reviewed, with a focus on both selective and multiple inhibitors. A short overview of the biochemical and cellular assays used for inhibitory potency evaluation is also presented. This review summarizes recent advances on IDO and TDO as potential drug targets, and provides the key features and perspectives for further research and development of potent inhibitors of the kynurenine pathway.

Comparing Fragment Binding Poses Prediction Using HSP90 as a Key Study: When Bound Water Makes the Difference

Fragment-Based Drug Discovery (FBDD) approaches have gained popularitynot only in industry but also in academic research institutes. However, the computational prediction of the binding mode adopted by fragment-like molecules within a protein binding site is still a very challenging task. One of the most crucial aspects of fragment binding is related to the large amounts of bound waters in the targeted binding pocket. The binding affinity of fragmentsmay not be sufficientto displace the bound water molecules. In the present work, we confirmed the importance of the bound water molecules in the correct prediction of the fragment binding mode. Moreover, we investigate whether the use of methods based on explicit solvent molecular dynamics simulations can improve the accuracy of fragment posing. The protein chosen for this study is HSP-90.

HomolWat: a web server tool to incorporate 'homologous' water molecules into GPCR structures

Internal water molecules play an essential role in the structure and function of membrane proteins including G protein-coupled receptors (GPCRs). However, technical limitations severely influence the number and certainty of observed water molecules in 3D structures. This may compromise the accuracy of further structural studies such as docking calculations or molecular dynamics simulations. Here we present HomolWat, a web application for incorporating water molecules into GPCR structures by using template-based modelling of homologous water molecules obtained from high-resolution structures. While there are various tools available to predict the positions of internal waters using energy-based methods, the approach of borrowing lacking water molecules from homologous GPCR structures makes HomolWat unique. The tool can incorporate water molecules into a protein structure in about a minute with around 85% of water recovery. The web server is freely available at http://lmc.uab.es/homolwat.

ProBiS H2O MD Approach for Identification of Conserved Water Sites in Protein Structures for Drug Design

The ProBiS H2O MD approach for identification of conserved waters and water sites of interest in macromolecular systems, which is becoming a typical step in a structure-based drug design or macromolecular study in general, is described. This work explores an extension of the ProBiS H2O approach introduced by Jukič et al. Indeed, water molecules are key players in the interaction mechanisms of macromolecules and small molecules and play structural roles. Our earlier developed approach, ProBiS H2O, is a simple and transparent workflow for conserved water detection. Here we have considered generalizing the idea by supplementing the experimental data with data derived from molecular dynamics to facilitate work on less known systems. Newly developed ProBiS H2O MD workflow uses trajectory data, extracts and identifies interesting water sites, and visualizes the results. ProBiS H2O MD can thus robustly process molecular dynamic trajectory snapshots, perform local superpositions, collect water location data, and perform density-based clustering to identify discrete sites with high conservation of water molecules. This is a new approach that uses experimental data in silico to identify interesting water sites. Methodology is fast and water-model or molecular dynamics software independent. Trends in the conservation of water molecules can be followed over a variety of trajectories, and our approach has been successfully validated using reported protein systems with experimentally observed conserved water molecules. ProBiS H2O MD is freely available as PyMOL plugin at http://insilab.org.

Applications of water molecules for analysis of macromolecule properties

Water molecules maintain proteins' structures, functions, stabilities and dynamics. They can occupy certain positions or pass quickly via a protein's interior. Regardless of their behaviour, water molecules can be used for the analysis of proteins' structural features and biochemical properties. Here, we present a list of several software programs that use the information provided by water molecules to: i) analyse protein structures and provide the optimal positions of water molecules for protein hydration, ii) identify high-occupancy water sites in order to analyse ligand binding modes, and iii) detect and describe tunnels and cavities. The analysis of water molecules' distribution and trajectories sheds a light on proteins' interactions with small molecules, on the dynamics of tunnels and cavities, on protein composition and also on the functionality, transportation network and location of functionally relevant residues. Finally, the correct placement of water molecules in protein crystal structures can significantly improve the reliability of molecular dynamics simulations.

Allosteric Binding Sites On Nuclear Receptors: Focus On Drug Efficacy and Selectivity

Nuclear receptors (NRs) are highly relevant drug targets in major indications such as oncologic, metabolic, reproductive, and immunologic diseases. However, currently, marketed drugs designed towards the orthosteric binding site of NRs often suffer from resistance mechanisms and poor selectivity. The identification of two superficial allosteric sites, activation function-2 (AF-2) and binding function-3 (BF-3), as novel drug targets sparked the development of inhibitors, while selectivity concerns due to a high conservation degree remained. To determine important pharmacophores and hydration sites among AF-2 and BF-3 of eight hormonal NRs, we systematically analyzed over 10 μ s of molecular dynamics simulations including simulations in explicit water and solvent mixtures. In addition, a library of over 300 allosteric inhibitors was evaluated by molecular docking. Based on our results, we suggest the BF-3 site to offer a higher potential for drug selectivity as opposed to the AF-2 site that is more conserved among the selected receptors. Detected similarities among the AF-2 sites of various NRs urge for a broader selectivity assessment in future studies. In combination with the Supplementary Material, this work provides a foundation to improve both selectivity and potency of allosteric inhibitors in a rational manner and increase the therapeutic applicability of this promising compound class.

Gold-Hybridized Zinc Oxide Nanorods as Real-Time Low-Cost NanoBiosensors for Detection of virulent DNA signature of HPV-16 in Cervical Carcinoma

Detection of host integrated viral oncogenes are critical for early and point-of-care molecular diagnostics of virus-induced carcinoma. However, available diagnostic approaches are incapable of combining both cost-efficient medical diagnosis and high analytical performances. To circumvent this, we have developed an improved IDE-based nanobiosensor for biorecognition of HPV-16 infected cervical cancer cells through electrochemical impedance spectroscopy. The system is fabricated by coating gold (Au) doped zinc oxide (ZnO) nanorods interfaced with HPV-16 viral DNA bioreceptors on top of the Interdigitated Electrode (IDE) chips surface. Due to the concurrently improved sensitivity and biocompatibility of the designed nanohybrid film, Au decorated ZnO-Nanorod biosensors demonstrate exceptional detection of HPV-16 E6 oncogene, the cancer biomarker for HPV infected cervical cancers. This sensor displayed high levels of sensitivity by detecting as low as 1fM of viral E6 gene target. The sensor also exhibited a stable functional life span of more than 5 weeks, good reproducibility and high discriminatory properties against HPV-16. Sensor current responses are obtained from cultured cervical cancer cells which are close to clinical cancer samples. Hence, the developed sensor is an adaptable tool with high potential for clinical diagnosis especially useful for economically challenged countries/regions.

A Fragmenting Protocol with Explicit Hydration for Calculation of Binding Enthalpies of Target-Ligand Complexes at a Quantum Mechanical Level

Optimization of the enthalpy component of binding thermodynamics of drug candidates is a successful pathway of rational molecular design. However, the large size and missing hydration structure of target-ligand complexes often hinder such optimizations with quantum mechanical (QM) methods. At the same time, QM calculations are often necessitated for proper handling of electronic effects. To overcome the above problems, and help the QM design of new drugs, a protocol is introduced for atomic level determination of hydration structure and extraction of structures of target-ligand complex interfaces. The protocol is a combination of a previously published program MobyWat, an engine for assigning explicit water positions, and Fragmenter, a new tool for optimal fragmentation of protein targets. The protocol fostered a series of fast calculations of ligand binding enthalpies at the semi-empirical QM level. Ligands of diverse chemistry ranging from small aromatic compounds up to a large peptide helix of a molecular weight of 3000 targeting a leukemia protein were selected for systematic investigations. Comparison of various combinations of implicit and explicit water models demonstrated that the presence of accurately predicted explicit water molecules in the complex interface considerably improved the agreement with experimental results. A single scaling factor was derived for conversion of QM reaction heats into binding enthalpy values. The factor links molecular structure with binding thermodynamics via QM calculations. The new protocol and scaling factor will help automated optimization of binding enthalpy in future molecular design projects.

Binding site comparisons for target-centered drug discovery

INTRODUCTION

The success of binding site comparisons in drug discovery is based on the recognized fact that many different proteins have similar binding sites. Indeed, binding site comparisons have found many uses in drug development and have the potential to dramatically cut the cost and shorten the time necessary for the development of new drugs. Areas covered: The authors review recent methods for comparing protein binding sites and their use in drug repurposing and polypharmacology. They examine emerging fields including the use of binding site comparisons in precision medicine, the prediction of structured water molecules, the search for targets of natural compounds, and their application in the development of protein-based drugs by loop modeling and for comparison of RNA binding sites. Expert opinion: Binding site comparisons have produced many interesting results in drug development, but relatively little work has been done on protein-protein interaction sites, which are particularly relevant in view of the success of biological drugs. Growth of protein loop modeling for modulating biological drugs is anticipated. The fusion of currently distinct methods for the comparison of RNA and protein binding sites into a single comprehensive approach could allow the search for new selective ribosomal antibiotics and initiate pharmaceutical research into other nucleoproteins.

Evaluation of Chemotherapeutic Activity of the Selected Bases' Analogues of Nucleic Acids Supported by ab initio Various Quantum Chemical Calculations

BACKGROUND

Pharmacological and physicochemical classification of bases' selected analogues of nucleic acids is proposed in the study.

OBJECTIVE

Structural parameters received by the PCM (Polarizable Continuum Model) with several types of calculation methods for the structures in vacuo and in the aquatic environment together with the huge set of extra molecular descriptors obtained by the professional software and literature values of biological activity were used to search the relationships.

METHODS

Principal Component Analysis (PCA) together with Factor Analysis (FA) and Multiple Linear Regressions (MLR) as the types of the chemometric approach based on semi-empirical ab initio molecular modeling studies were performed.

RESULTS

The equations with statistically significant descriptors were proposed to demonstrate both the common and differentiating characteristics of the bases' analogues of nucleic acids based on the quantum chemical calculations and biological activity data.

CONCLUSION

The obtained QSAR models can be used for predicting and explaining the activity of studied molecules.

Ligand Binding Free Energies with Adaptive Water Networks: Two-Dimensional Grand Canonical Alchemical Perturbations

Computational methods to calculate ligand binding affinities are increasing in popularity, due to improvements in simulation algorithms, computational resources, and easy-to-use software. However, issues can arise in relative ligand binding free energy simulations if the ligands considered have different active site water networks, as simulations are typically performed with a predetermined number of water molecules (fixed N ensembles) in preassigned locations. If an alchemical perturbation is attempted where the change should result in a different active site water network, the water molecules may not be able to adapt appropriately within the time scales of the simulations—particularly if the active site is occluded. By combining the grand canonical ensemble (μVT) to sample active site water molecules, with conventional alchemical free energy methods, the water network is able to dynamically adapt to the changing ligand. We refer to this approach as grand canonical alchemical perturbation (GCAP). In this work we demonstrate GCAP for two systems; Scytalone Dehydratase (SD) and Adenosine A_2A receptor. For both systems, GCAP is shown to perform well at reproducing experimental binding affinities. Calculating the relative binding affinities with a naïve, conventional attempt to solvate the active site illustrates how poor results can be if proper consideration of water molecules in occluded pockets is neglected. GCAP results are shown to be consistent with time-consuming double decoupling simulations. In addition, by obtaining the free energy surface for ligand perturbations, as a function of both the free energy coupling parameter and water chemical potential, it is possible to directly deconvolute the binding energetics in terms of protein–ligand direct interactions and protein binding site hydration.

Cryo-EM for Small Molecules Discovery, Design, Understanding, and Application

We present a perspective of our view of the application of cryoelectron microscopy (cryo-EM) to structure-based drug design (SBDD). We discuss the basic needs and requirements for SBDD, the current state of cryo-EM, and the challenges that need to be overcome for this technique to reach its full potential in facilitating the process of drug discovery.