pK(a) based protonation states and microspecies for protein-ligand docking

Design, synthesis, and evaluation of a pyrazole-based corrosion inhibitor: a computational and experimental study

By employing a synergistic blend of experimental and theoretical methodologies, we investigated the corrosion inhibition efficacy of a synthesized pyrazole derivative (BM-01) in a solution of hydrochloric acid (1 M). We utilized molecular dynamics (MD) simulations, scanning electron microscopy (SEM), density functional theory (DFT), complexation, plus electrochemical impedance spectroscopy (EIS). We conducted weight loss (WL) measurements from 298 to 328 K. Inhibition efficacy reached a maximum at a BM-01 concentration of 10-3 M, achieving 90.0% (EIS), 90.40% (WL), and 90.38% (potentiodynamic polarization (PDP)). SEM unveiled the shielding of the carbon-steel surface from acid-induced damage by BM-01. The Langmuir adsorption isotherm exhibited a robust fit with a low sum of squares, standard deviation, and a high correlation coefficient. PDP findings indicated that BM-01 acted as a mixed-type inhibitor, predominantly favoring the cathodic process, suggesting potential corrosion-mitigation properties. Theoretical analyses involving DFT, MD simulations, and radial distribution function were conducted to postulate a mechanism and identify an inhibitory layer. Theoretical outcomes aligned closely with experimental data, thereby reinforcing the validity of our findings.

Conformational coupling of redox-driven Na+-translocation in Vibrio cholerae NADH:quinone oxidoreductase

In the respiratory chain, NADH oxidation is coupled to ion translocation across the membrane to build up an electrochemical gradient. In the human pathogen Vibrio cholerae, the sodium-pumping NADH:quinone oxidoreductase (Na+-NQR) generates a sodium gradient by a so far unknown mechanism. Here we show that ion pumping in Na+-NQR is driven by large conformational changes coupling electron transfer to ion translocation. We have determined a series of cryo-EM and X-ray structures of the Na+-NQR that represent snapshots of the catalytic cycle. The six subunits NqrA, B, C, D, E, and F of Na+-NQR harbor a unique set of cofactors that shuttle the electrons from NADH twice across the membrane to quinone. The redox state of a unique intramembranous [2Fe-2S] cluster orchestrates the movements of subunit NqrC, which acts as an electron transfer switch. We propose that this switching movement controls the release of Na+ from a binding site localized in subunit NqrB.

Design of electron-donating group substituted 2-PAM analogs as antidotes for organophosphate insecticide poisoning

The use of organophosphate (OPs) pesticides is widespread in agriculture and horticulture, but these chemicals can be lethal to humans, causing fatalities and deaths each year. The inhibition of acetylcholinesterase (AChE) by OPs leads to the overstimulation of cholinergic receptors, ultimately resulting in respiratory arrest, seizures, and death. Although 2-pralidoxime (2-PAM) is the FDA-approved drug for treating OP poisoning, there is difficulty in blood-brain barrier permeation. To address this issue, we designed and evaluated a series of 2-PAM analogs by substituting electron-donating groups on the para and/or ortho positions of the pyridinium core using in silico techniques. Our PCM-ONIOM2 (MP2/6-31G*:PM7//B3LYP/6-31G*:UFF) binding energy results demonstrated that 13 compounds exhibited higher binding energy than 2-PAM. The analog with phenyl and methyl groups substituted on the para and ortho positions, respectively, showed the most favorable binding characteristics, with aromatic residues in the active site (Y124, W286, F297, W338, and Y341) and the catalytic residue S203 covalently bonding with paraoxon. The results of DS-MD simulation revealed a highly favorable apical conformation of the potent analog, which has the potential to enhance reactivation of AChE. Importantly, newly designed compound demonstrated appropriate drug-likeness properties and blood-brain barrier penetration. These results provide a rational guide for developing new antidotes to treat organophosphate insecticide toxicity.

Isothiocyanates as Tubulin Polymerization Inhibitors-Synthesis and Structure-Activity Relationship Studies

Among the various substances that interfere with the microtubule formation process, isothiocyanates (ITCs) are the group of compounds for which the binding mode and mechanism of action have not yet been explained. To better understand the structure-activity relationship of tubulin-isothiocyanate interactions, we designed and synthesized a series of sixteen known and novel, structurally diverse ITCs, including amino acid ester-derived isothiocyanates, bis-isothiocyanates, analogs of benzyl isothiocyanate, and phosphorus analogs of sulforaphane. All synthesized compounds and selected natural isothiocyanates (BITC, PEITC, AITC, and SFN) were tested in vitro to evaluate their antiproliferative activity, tubulin polymerization inhibition potential, and influence on cell cycle progression. The antiproliferative activity of most of the newly tested compounds exceeded the action of natural isothiocyanates, with four structures being more potent as tubulin polymerization inhibitors than BITC. As a confirmation of anti-tubulin activity, the correlation between polymerization inhibition and cell cycle arrest in the G2/M phase was observed for the most active compounds. In light of the biological results indicating significant differences in the impact of structurally diverse isothiocyanate on tubulin polymerization, in silico analysis was conducted to analyze the possible mode of isothiocyanate-tubulin binding and to show how it can influence the polymerization reaction.

Recent Developments in Ultralarge and Structure-Based Virtual Screening Approaches

Drug development is a wide scientific field that faces many challenges these days. Among them are extremely high development costs, long development times, and a small number of new drugs that are approved each year. New and innovative technologies are needed to solve these problems that make the drug discovery process of small molecules more time and cost efficient, and that allow previously undruggable receptor classes to be targeted, such as protein-protein interactions. Structure-based virtual screenings (SBVSs) have become a leading contender in this context. In this review, we give an introduction to the foundations of SBVSs and survey their progress in the past few years with a focus on ultralarge virtual screenings (ULVSs). We outline key principles of SBVSs, recent success stories, new screening techniques, available deep learning-based docking methods, and promising future research directions. ULVSs have an enormous potential for the development of new small-molecule drugs and are already starting to transform early-stage drug discovery.

In Silico Targeting of Fascin Protein for Cancer Therapy: Benchmarking, Virtual Screening and Molecular Dynamics Approaches

Fascin is an actin-bundling protein overexpressed in various invasive metastatic carcinomas through promoting cell migration and invasion. Therefore, blocking Fascin binding sites is considered a vital target for antimetastatic drugs. This inspired us to find new Fascin binding site blockers. First, we built an active compound set by collecting reported small molecules binding to Fascin's binding site 2. Consequently, a high-quality decoys set was generated employing DEKOIS 2.0 protocol to be applied in conducting the benchmarking analysis against the selected Fascin structures. Four docking programs, MOE, AutoDock Vina, VinaXB, and PLANTS were evaluated in the benchmarking study. All tools indicated better-than-random performance reflected by their pROC-AUC values against the Fascin crystal structure (PDB: ID 6I18). Interestingly, PLANTS exhibited the best screening performance and recognized potent actives at early enrichment. Accordingly, PLANTS was utilized in the prospective virtual screening effort for repurposing FDA-approved drugs (DrugBank database) and natural products (NANPDB). Further assessment via molecular dynamics simulations for 100 ns endorsed Remdesivir (DrugBank) and NANPDB3 (NANPDB) as potential binders to Fascin binding site 2. In conclusion, this study delivers a model for implementing a customized DEKOIS 2.0 benchmark set to enhance the VS success rate against new potential targets for cancer therapies.

Structural dynamics and kinase inhibitory activity of three generations of tyrosine kinase inhibitors against wild-type, L858R/T790M, and L858R/T790M/C797S forms of EGFR

Mutations in the tyrosine kinase domain of epidermal growth factor receptor (EGFR), including L858R/T790M double and L858R/T790M/C797S triple mutations, are major causes of acquired resistance towards EGFR targeted drugs. In this work, a combination of comprehensive molecular modeling and in vitro kinase inhibition assay was used to unravel the mutational effects of EGFR on the susceptibility of three generations of EGFR tyrosine kinase inhibitors (erlotinib, gefitinib, afatinib, dacomitinib, and osimertinib) in comparison with the wild-type EGFR. The binding affinity of all studied inhibitors towards the double and triple EGFR mutations was in good agreement with the experimental data, ranked in the order of osimertinib > afatinib > dacomitinib > erlotinib > gefitinib. Three hot-spot residues at the hinge region (M790, M793, and C797) were involved in the binding of osimertinib and afatinib, enhancing their inhibitory activity towards mutated EGFRs. Both double and triple EGFR mutations causing erlotinib and gefitinib resistance are mainly caused by the low number of H-bond occupations, the low number of surrounding atoms, and the high number of water molecules accessible to the enzyme active site. According to principal component analysis, the molecular complexation of osimertinib against the two mutated EGFRs was in a closed conformation, whereas that against wild-type EGFR was in an open conformation, resulting in drug resistance. This work paves the way for further design of the novel EGFR inhibitors to overcome drug resistance mechanisms.

Protein-Ligand Docking in the Machine-Learning Era

Molecular docking plays a significant role in early-stage drug discovery, from structure-based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive power is critically dependent on the protein-ligand scoring function. In this review, we give a broad overview of recent scoring function development, as well as the docking-based applications in drug discovery. We outline the strategies and resources available for structure-based VS and discuss the assessment and development of classical and machine learning protein-ligand scoring functions. In particular, we highlight the recent progress of machine learning scoring function ranging from descriptor-based models to deep learning approaches. We also discuss the general workflow and docking protocols of structure-based VS, such as structure preparation, binding site detection, docking strategies, and post-docking filter/re-scoring, as well as a case study on the large-scale docking-based VS test on the LIT-PCBA data set.

Multiple actions of NMS-P715, the monopolar spindle 1 (MPS1) mitotic checkpoint inhibitor in liver fluke-associated cholangiocarcinoma cells

AIM

NMS-P715 is a potent inhibitor of monopolar spindle 1 (MPS1) mitotic checkpoint kinase. Overexpression of MPS1 is associated with short survival times in patients with cholangiocarcinoma (CCA). This study investigated the anti-cancer effects of NMS-P715 in human CCA cell lines.

MAIN METHODS

KKU-100 and KKU-213A CCA cell lines were treated with NMS-P715 and cell viability was determined using MTT and colony formation assays. Inhibitory effects of NMS-P715 on cell cycle and apoptosis were evaluated using flow cytometry. Expression of underlying mechanism-related proteins was examined by Western blotting. Mitotic catastrophe was assessed by counting abnormal nuclei. Transwell assays were used to examine cell migration and invasion.

KEY FINDINGS

Molecular docking showed that the NMS-P715/MPS1 complex was driven by an induced-fit mechanism. We provide new evidence that NMS-P715 potently inhibited cell proliferation and colony formation in both CCA cell lines. This was accompanied by induction of G2/M arrest and the consequent induction of mitotic catastrophe, a process that occurs during defective mitosis. The recent study showed that NMS-P715 activated caspase-dependent apoptosis and autophagosome formation with an increase of LC3 A/B-II protein expression in CCA cell lines. NMS-P715 also greatly impeded cell migration and invasion in CCA cell lines. The combination of NMS-P715 and gemcitabine or cisplatin showed synergistic effects on CCA cell proliferation.

SIGNIFICANCE

This study revealed for the first time that NMS-P715 is a promising candidate for combating CCA owing via multiple actions and may be suitable for further development in a clinical study.

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

Facilitating SARS CoV-2 RNA-Dependent RNA polymerase (RdRp) drug discovery by the aid of HCV NS5B palm subdomain binders: In silico approaches and benchmarking

Corona Virus 2019 Disease (COVID-19) is a rapidly emerging pandemic caused by a newly discovered beta coronavirus, called Sever Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2). SARS CoV-2 is an enveloped, single stranded RNA virus that depends on RNA-dependent RNA polymerase (RdRp) to replicate. Therefore, SARS CoV-2 RdRp is considered as a promising target to cease virus replication. SARS CoV-2 polymerase shows high structural similarity to Hepatitis C Virus-1b genotype (HCV-1b) polymerase.

Arising from the high similarity between SARS CoV-2 RdRp and HCV NS5B, we utilized the reported small-molecule binders to the palm subdomain of HCV NS5B (genotype 1b) to generate a high-quality DEKOIS 2.0 benchmark set and conducted a benchmarking analysis against HCV NS5B. The three highly cited and publicly available docking tools AutoDock Vina, FRED and PLANTS were benchmarked. Based on the benchmarking results and analysis via pROC-Chemotype plot, PLANTS showed the best screening performance and can recognize potent binders at the early enrichment. Accordingly, we used PLANTS in a prospective virtual screening to repurpose both the FDA-approved drugs (DrugBank) and the HCV-NS5B palm subdomain binders (BindingDB) for SARS CoV-2 RdRp palm subdomain. Further assessment by molecular dynamics simulations for 50 ns recommended diosmin (from DrugBank) and compound 3 (from BindingDB) to be the best potential binders to SARS CoV-2 RdRp palm subdomain. The best predicted compounds are recommended to be biologically investigated against COVID-19. In conclusion, this work provides in-silico analysis to propose possible SARS CoV-2 RdRp palm subdomain binders recommended as a remedy for COVID-19. Up-to-our knowledge, this study is the first to propose binders at the palm subdomain of SARS CoV2 RdRp. Furthermore, this study delivers an example of how to make use of a high quality custom-made DEKOIS 2.0 benchmark set as a procedure to elevate the virtual screening success rate against a vital target of the rapidly emerging pandemic.

Discovery of Novel CCR5 Ligands as Anticolorectal Cancer Agents by Sequential Virtual Screening

C-C chemokine receptor type 5 (CCR5) is a member of the G protein-coupled receptor. CCR5 and its interaction with chemokine ligands have been crucial for understanding and tackling human immunodeficiency virus (HIV)-1 entry into target cells. In recent years, the change in CCR5 expression has been related to the progression of different cancer types. Patients treated with the CCR5 ligand, maraviroc (MVC), showed a deceleration in tumor development especially for metastatic colorectal cancer. Based on the crystal structure of CCR5, we herein describe a multistage virtual screening protocol including pharmacophore screening, molecular docking, and protein-ligand interaction fingerprint (PLIF) postdocking filtration for discovery of novel CCR5 ligands. The applied virtual screening protocol led to the identification of four hits with binding modes showing access to the major and minor pockets of the MVC binding site. Compounds 2-4 showed a decrease in cellular proliferation upon testing on the metastatic colorectal cancer cell line, SW620, displaying 12, 16, and 4 times higher potency compared to MVC, respectively. Compound 3 induced apoptosis by arresting cells in the G0/G1 phase of the cell cycle similar to MVC. Further in vitro assays showed compound 3 drastically decreasing the CCR5 expression and cellular migration 48 h post treatment, indicating its ability to inhibit metastatic activity in SW620 cells. The discovered hits represent potential leads for the development of novel classes of anticolorectal cancer agents targeting CCR5.

C-2-Linked Dimeric Strychnine Analogues as Bivalent Ligands Targeting Glycine Receptors

Strychnine is the prototypic antagonist of glycine receptors, a family of pentameric ligand-gated ion channels. Recent high-resolution structures of homomeric glycine receptors have confirmed the presence of five orthosteric binding sites located in the extracellular subunit interfaces of the receptor complex that are targeted by strychnine. Here, we report the synthesis and extensive pharmacological evaluation of bivalent ligands composed of two strychnine pharmacophores connected by appropriate spacers optimized toward simultaneous binding to two adjacent orthosteric sites of homomeric α1 glycine receptors. In all bivalent ligands, the two strychnine units were linked through C-2 by amide spacers of various lengths ranging from 6 to 69 atoms. Characterization of the compounds in two functional assays and in a radioligand binding assay indicated that compound 11a, with a spacer consisting of 57 atoms, may be capable of bridging the homomeric α1 GlyRs by simultaneous occupation of two adjacent strychnine-binding sites. The findings are supported by docking experiments to the crystal structure of the homomeric glycine receptor. Based on its unique binding mode, its relatively high binding affinity and antagonist potency, and its slow binding kinetics, the bivalent strychnine analogue 11a could be a valuable tool to study the functional properties of glycine receptors.

A recursive molecular docking coupled with energy-based pose-rescoring and MD simulations to identify hsGC βH-NOX allosteric modulators for cardiovascular dysfunctions

Modulating the activity of human soluble guanylate cyclase (hsGC) through allosteric regulation of the βH-NOX domain has been considered as an immediate treatment for cardiovascular disorder (CVDs). Currently available βH-NOX domain-specific agonists including cinaciguat are unable to deal with the conundrum raised due to oxidative stress in the case of CVDs and their associated comorbidities. Therefore, the idea of investigating novel compounds for allosteric regulation of hsGC activation has been rekindled to circumvent CVDs. Current study aims to identify novel βH-NOX domain-specific compounds that can selectively turn on sGC functions by modulating the conformational dynamics of the target protein. Through a comprehensive computational drug-discovery approach, we first executed a target-based performance assessment of multiple docking (PLANTS, QVina, LeDock, Vinardo, Smina) scoring functions based on multiple performance metrices. QVina showed the highest capability of selecting true-positive ligands over false positives thus, used to screen 4.8 million ZINC15 compounds against βH-NOX domain. The docked ligands were further probed in terms of contact footprint and pose reassessment through clustering analysis and PLANTS docking, respectively. Subsequently, energy-based AMBER rescoring of top 100 low-energy complexes, per-residue energy decomposition analysis, and ADME-Tox analysis yielded the top three compounds i.e. ZINC000098973660, ZINC001354120371, and ZINC000096022607. The impact of three selected ligands on the internal structural dynamics of the βH-NOX domain was also investigated through molecular dynamics simulations. The study revealed potential electrostatic interactions for better conformational dialogue between βH-NOX domain and allosteric ligands that are critical for the activation of hsGC as compared to the reference compound.

Structural insight into the recognition of S-adenosyl-L-homocysteine and sinefungin in SARS-CoV-2 Nsp16/Nsp10 RNA cap 2'-O-Methyltransferase

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The binding affinity towards SARS-CoV-2 nsp16 of SFG is higher than that of SAH.

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Asp99 is a key binding residue for SAH and SFG via charge-charge attraction.

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SFG could electrostatically interact with the 2′-OH and N3 groups of adenosine moiety of RNA substrate.

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The distance between 2′-OH of RNA and –NH₃⁺ (at 6′ position) of SFG mimics the methyl transfer reaction.

The recent ongoing coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to rapidly spread across the world. To date, neither a specific antiviral drug nor a clinically effective vaccine is available. Among the 15 viral non-structural proteins (nsps), nsp16 methyltransferase has been considered as a potential target due to its crucial role in RNA cap 2′-O-methylation process, preventing the virus detection by cell innate immunity mechanisms. In the present study, molecular recognition between the two natural nucleoside analogs (S-adenosyl-l-homocysteine (SAH) and sinefungin (SFG)) and the SARS-CoV-2 nsp16/nsp10/^m7G_pppAC₅ was studied using all-atom molecular dynamics simulations and free energy calculations based on MM/GBSA and WaterSwap approaches. The binding affinity and the number of hot-spot residues, atomic contacts, and H-bond formations of SFG/nsp16 complex were distinctly higher than those of SAH/nsp16 system, consistent with the lower water accessibility at the enzyme active site. Notably, only SFG could electrostatically interact with the 2′-OH and N3 of RNA’s adenosine moiety, mimicking the methyl transfer reaction of S-adenosyl-l-methionine substrate. The atomistic binding mechanism obtained from this work paves the way for further optimizations and designs of more specific SARS-CoV-2 nsp16 inhibitors in the fight against COVID-19.

Structure-based design, synthesis, and evaluation of the biological activity of novel phosphoroorganic small molecule IAP antagonists

One of the strategies employed by novel anticancer therapies is to put the process of apoptosis back on track by blocking the interaction between inhibitor of apoptosis proteins (IAPs) and caspases. The activity of caspases is modulated by the caspases themselves in a caspase/procaspase proteolytic cascade and by their interaction with IAPs. Caspases can be released from the inhibitory influence of IAPs by proapoptotic proteins such as secondary mitochondrial activator of caspases (Smac) that share an IAP binding motif (IBM). The main purpose of the present study was the design and synthesis of phosphorus-based peptidyl antagonists of IAPs that mimic the endogenous Smac protein, which blocks the interaction between IAPs and caspases. Based on the structure of the IAP antagonist and recently reported thiadiazole derivatives, we designed and evaluated the biochemical properties of a series of phosphonic peptides bearing the N-Me-Ala-Val/Chg-Pro-OH motif (Chg: cyclohexylglycine). The ability of the obtained compounds to interact with the binding groove of the X-linked inhibitor of apoptosis protein baculovirus inhibitor of apoptosis protein repeat (XIAP BIR3) domain was examined by a fluorescence polarization assay, while their potential to induce autoubiquitination followed by proteasomal degradation of cellular IAP1 was examined using the MDA-MB-231 breast cancer cell line. The highest potency against BIR3 was observed among peptides containing C-terminal phosphonic phenylalanine analogs, which displayed nanomolar K_i values. Their antiproliferative potential as well as their proapoptotic action, manifested by an increase in caspase-3 activity, was examined using various cell lines.

Molecular Architect: A User-Friendly Workflow for Virtual Screening

Computer-assisted drug design (CADD) methods have greatly contributed to the development of new drugs. Among CADD methodologies, virtual screening (VS) can enrich the compound collection with molecules that have the desired physicochemical and pharmacophoric characteristics that are needed to become drugs. Many free tools are available for this purpose, but they are difficult to use and do not have a graphical user interface. Furthermore, several free tools must be used to carry out the entire VS process, requiring the user to process the results of one software program so that they can be used in another program, adding a potential source of human error. Moreover, some software programs require knowledge of advanced computational skills, such as programming languages. This context has motivated us to develop Molecular Architect (MolAr). MolAr is a workflow with a simple and intuitive interface that acts in an integrated and automated form to perform the entire VS process, from protein preparation (homology modeling and protonation state) to virtual screening. MolAr carries out VS through AutoDock Vina, DOCK 6, or a consensus of the two. Two case studies were conducted to demonstrate the performance of MolAr. In the first study, the feasibility of using MolAr for DNA-ligand systems was assessed. Both AutoDock Vina and DOCK 6 showed good results in performing VS in DNA-ligand systems. However, the use of consensus virtual screening was able to enrich the results. According to the area under the ROC curve and the enrichment factors, consensus VS was better able to predict the positions of the active ligands. The second case study was performed on 8 targets from the DUD-E database and 10 active ligands for each target. The results demonstrated that using the final ligand conformation provided by AutoDock Vina as an input for DOCK 6 improved the DOCK 6 ROC curves by up to 42% in VS. These case studies demonstrated that MolAr is capable conducting the VS process and is an easy-to-use and effective tool. MolAr is available for download free of charge at http: //www.drugdiscovery.com.br/software/.

Human proteinase 3 resistance to inhibition extends to alpha-2 macroglobulin

Polymorphonuclear neutrophils contain at least four serine endopeptidases, namely neutrophil elastase (NE), proteinase 3 (PR3), cathepsin G (CatG), and NSP4, which contribute to the regulation of infection and of inflammatory processes. In physiological conditions, endogenous inhibitors including α2-macroglobulin (α2-M), serpins [α1-proteinase inhibitor (α1-PI)], monocyte neutrophil elastase inhibitor (MNEI), α1-antichymotrypsin, and locally produced chelonianins (elafin, SLPI) control excessive proteolytic activity of neutrophilic serine proteinases. In contrast to human NE (hNE), hPR3 is weakly inhibited by α1-PI and MNEI but not by SLPI. α2-M is a large spectrum inhibitor that traps a variety of proteinases in response to cleavage(s) in its bait region. We report here that α2-M was more rapidly processed by hNE than hPR3 or hCatG. This was confirmed by the observation that the association between α2-M and hPR3 is governed by a k_ass in the ≤ 10⁵  m^-1 ·s^-1 range. Since α2-M-trapped proteinases retain peptidase activity, we first predicted the putative cleavage sites within the α2-M bait region (residues 690-728) using kinetic and molecular modeling approaches. We then identified by mass spectrum analysis the cleavage sites of hPR3 in a synthetic peptide spanning the 39-residue bait region of α2-M (39pep-α2-M). Since the 39pep-α2-M peptide and the corresponding bait area in the whole protein do not contain sequences with a high probability of specific cleavage by hPR3 and were indeed only slowly cleaved by hPR3, it can be concluded that α2-M is a poor inhibitor of hPR3. The resistance of hPR3 to inhibition by endogenous inhibitors explains at least in part its role in tissue injury during chronic inflammatory diseases and its well-recognized function of major target autoantigen in granulomatosis with polyangiitis.

Toxicities of 4,5-Dihydroisoxazoles Against Root-Knot Nematodes and in Silico Studies of Their Modes of Action

The present work sought to contribute to the development of new nematicides. Benzaldehydes were initially converted to nitrile oxides that underwent 1,3-dipolar cycloaddition reactions with methyl acrylate to generate 4,5-dihydroisoxazoles. In in vitro tests, methyl 3-phenyl-4,5-dihydroisoxazole-5-carboxylate (1) and methyl 3-(4-chlorophenyl)-4,5-dihydroisoxazole-5-carboxylate (4) increased the mortality of Meloidogyne exigua and Meloidogyne incognita second-stage juveniles (J2). Compounds 1 and 4 presented necessary concentrations of 398 and 501 μg mL^-1, respectively, to kill 50% of M. incognita J2 (LC₅₀ values), while the value for carbofuran (positive control) was 168 μg mL^-1. In in vivo tests, compounds 1 and 4 reduced the number of M. incognita galls in tomato roots by 70 and 40%, respectively, and the number of eggs by 89 and 44%. Using an in silico approach, we showed that compounds 1 and 4 were toxic to the nematodes by binding to the allosteric binding sites of the agonist-binding domains of the nematode nicotinic acetylcholine receptors. These results opened up possibilities for further investigations aimed at developing novel commercial nematicides.

Herbicidal activity of isobenzofuranones and in silico identification of their enzyme target

BACKGROUND

Given the weed resistance to various herbicides with different mechanisms of action, the search for new compounds that are more effective and exhibit low levels of impact to other species in nature has been imperative in the field of the agriculture. For this purpose, 16 phthalides, and furan-2(5H)-one were synthetized and evaluated for their effectiveness as herbicides in seeds of Sorghum bicolor (sorghum), Cucumis sativus (cucumber), and Allium cepa (onion). Furthermore, a preliminary in silico study was carried out to identify the enzyme target of the most active compounds.

RESULTS

In the assays with S. bicolor, the mixture rac-(3aR,4R,5S,6S,7S,7aS)-5,6-dibromohexahydro-4,7-methanoisobenzofuran-1(3H)-one + rac-(3aR,4R,5R,6R,7S,7aS)-5,6-dibromohexahydro-4,7-methanoisobenzofuran-1(3H)-one (15a + 15b) showed comparable inhibitory activity to (S)-metolachlor, which was used as control herbicide at concentrations ranging from 50 μm to 1000 μm. The developments of the seeds evaluated were altered by all 17 compounds, either stimulating or inhibiting. The best results were presented by compounds 15a, and 15b, either in their pure form or as a mixture.

CONCLUSION

The results presented by 15a, and 15b were superior to the activity of the commercial herbicide (S)-metolachlor in the assays with C. sativus, and A. cepa. The in silico study provides strong evidence that the most active compounds bind to strigolactones esterases D14 through the same binding site of (5R)-5-hydroxy-3-methylfuran-2(5H)-one (H3M), which is one of the strigolactones (SLs) cleavage products. © 2019 Society of Chemical Industry.

Comprehensive evaluation of the MM-GBSA method on bromodomain-inhibitor sets

MM-PB/GBSA methods represent a higher-level scoring theory than docking. This study reports an extensive testing of different MM-GBSA scoring schemes on two bromodomain (BRD) datasets. The first set is composed of 24 BRPF1 complexes, and the second one is a nonredundant set constructed from the PDBbind and composed of 28 diverse BRD complexes. A variety of MM-GBSA schemes were analyzed to evaluate the performance of four protocols with different numbers of minimization and MD steps, 10 different force fields and three different water models. Results showed that neither additional MD steps nor unfixing the receptor atoms improved scoring or ranking power. On the contrary, our results underscore the advantage of fixing receptor atoms or limiting the number of MD steps not only for a reduction in the computational costs but also for boosting the prediction accuracy. Among Amber force fields tested, ff14SB and its derivatives rather than ff94 or polarized force fields provided the most accurate scoring and ranking results. The TIP3P water model yielded the highest scoring and ranking power compared to the others. Posing power was further evaluated for the BRPF1 set. A slightly better posing power for the protocol which uses both minimization and MD steps with a fixed receptor than the one which uses only minimization with a fully flexible receptor-ligand system was observed. Overall, this study provides insights into the usage of the MM-GBSA methods for screening of BRD inhibitors, substantiating the benefits of shorter protocols and latest force fields and maintaining the crystal waters for accuracy.

Comparative Assessment of Seven Docking Programs on a Nonredundant Metalloprotein Subset of the PDBbind Refined

Extensive usage of molecular docking for computer-aided drug discovery resulted in development of numerous programs with versatile scoring and posing algorithms. Selection of the docking program among these vast number of options is central to the outcome of drug discovery. To this end, comparative assessment studies of docking offer valuable insights into the selection of the optimal tool. Despite the availability of various docking assessment studies, the performance difference of docking programs has not been well addressed on metalloproteins which comprise a substantial portion of the human proteome and have been increasingly targeted for treatment of a wide variety of diseases. This study reports comparative assessment of seven docking programs on a diverse metalloprotein set which was compiled for this study. The refined set of the PDBbind (2017) was screened to gather 710 complexes with metal ion(s) closely located to the ligands (<4 Å). The redundancy was eliminated by clustering and overall 213 complexes were compiled as the nonredundant metalloprotein subset of the PDBbind refined. The scoring, ranking, and posing powers of seven noncommercial docking programs, namely, AutoDock4, AutoDock4_Zn, AutoDock Vina, Quick Vina 2, LeDock, PLANTS, and UCSF DOCK6, were comprehensively evaluated on this nonredundant set. Results indicated that PLANTS (80%) followed by LeDock (77%), QVina (76%), and Vina (73%) had the most accurate posing algorithms while AutoDock4 (48%) and DOCK6 (56%) were the least successful in posing. Contrary to their moderate-to-high level of posing success, none of the programs was successful in scoring or ranking of the binding affinities (r² ≈ 0). Screening power was further evaluated by using active-decoy ligand sets for a large compilation of metalloprotein targets. PLANTS stood out among other programs to be able to enrich the active ligand for every target, underscoring its robustness for screening of metalloprotein inhibitors. This study provides useful information for drug discovery studies targeting metalloproteins.

Docking software performance in protein-glycosaminoglycan systems

We present a benchmarking study for protein-glycosaminoglycan systems with eight docking programs: Dock, rDock, ClusPro, PLANTS, HADDOCK, Hex, SwissDock and ATTRACT. We used a non-redundant representative dataset of 28 protein-glycosaminoglycan complexes with experimentally available structures, where a glycosaminoglycan ligand was longer than a trimer. Overall, the ligand binding poses could be correctly predicted in many cases by the tested docking programs, however the ranks of the docking poses are often poorly assigned. Our results suggest that Dock program performs best in terms of the pose placement, has the most suitable scoring function, and its performance did not depend on the ligand size. This suggests that the implementation of the electrostatics as well as the shape complementarity procedure in Dock are the most suitable for docking glycosaminoglycan ligands. We also analyzed how free energy patterns of the benchmarking complexes affect the performance of the evaluated docking software.

PeptoGrid-Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries

Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads.

Molecular docking and in silico studies of the physicochemical properties of potential inhibitors for the phosphotransferase system of Streptococcus mutans

This study identified potential inhibitory compounds of the phosphoenolpyruvate-sugar. Phosphotransferase system of S. mutans, specifically enzyme II mannose transporter (EII^Man) in its subunits IIA, IIB and IIC by means of a selection protocol and in silico molecular analysis. Intervening the phosphotransferase system would compromise the physiological behavior and the pathogenic expression of S. mutans, and possibly other acidogenic bacteria that use phosphotransferases in their metabolism-making the phosphotransferase system a therapeutic target for the selective control of acidogenic microorganisms in caries control. Several computational techniques were used to evaluate molecular, physicochemical, and toxicological aspects of various compounds. Molecular docking was used to calculate the binding potential (ΔG) between receptor protein subunits and more than 836,000 different chemical compounds from the ZINC database. Physicochemical parameters related to the compounds' pharmacokinetic and pharmacodynamic indicators were evaluated, including absorption, distribution, metabolism, excretion, and toxicity (ADMET), and chemical analysis characterized the compounds structures. Thirteen compounds with EII binding potential of the phosphotransferase system of S. mutans and favorable ADMET properties were identified. Six spirooxindoles and three pyrrolidones stand out from the found compounds; unique structural characteristics of spirooxindoles and pyrrolidones associated with various reported biological activities like anti-microbial, antiinflammatory, anticancer, nootropic, neuroprotective and antiepileptic effects, among other pharmacological effects with surprising differences in terms of mechanisms of action. Following studies will provide more evidence of the action of these compounds on the phosphotransferase system of S. mutans, and its possible applications.

In silico identification of inhibitors targeting N-Terminal domain of human Replication Protein A

Replication Protein A (RPA) mediates DNA Damage Response (DDR) pathways through protein-protein interactions (PPIs). Targeting the PPIs formed between RPA and other DNA Damage Response (DDR) mediators has become an intriguing area of research for cancer drug discovery. A number of studies applied different methods ranging from high throughput screening approaches to fragment-based drug design tools to discover RPA inhibitors. Although these methods are robust, virtual screening approaches may be allocated as an alternative to such experimental methods, especially for screening of large libraries. Here we report the comprehensive screening of the large database, ZINC15 composed of ∼750 M compounds and the comparison of the identified ligands with the previously known inhibitors by means of binding affinity and drug-likeness. Initially, a ligand library sharing similarity with a promising inhibitor of the N-terminal domain of the RPA70 subunit (RPA70N) was generated by screening of the ZINC15 library. 46,999 ligands were collected and screened by LeDock which produced a satisfactory correlation with the experimental values (R² = 0.77). 10 of the top-scoring ligands in LeDock were directly progressed to molecular dynamics (MD) simulations, while 10 additional ligands were also selected based on their LeDock scores and the presence of a functional group that could interact with the key amino acids in the RPA70N cleft. MD simulations were used to predict the binding free energy of the ligands by the MM-PBSA method which produced a high level of agreement with the experiments (R² = 0.85). Binding free energy predictions pointed out 2 ligands with higher binding affinity than any of the reference inhibitors. Particularly the ligand ZINC000753854163 exhibited superior drug-likeness features than any of the known inhibitors. Overall, this study reports ZINC000753854163 as a possible inhibitor of RPA70N, reflecting its possible use in RPA70N targeted cancer therapy.

One Step Beyond: Design of Substrates Spanning Primed Positions of Zika Virus NS2B-NS3 Protease

Although the mosquito-borne Zika virus was discovered in the late 1940s of the 20th century, for years it was neglected, as the disease in humans was rare and relatively mild. Viral NS2B-NS3 protease is essential for virus replication, and except for maturation of viral proteins, it also modulates the infection microenvironment to facilitate virus invasion. Here, we report the combinatorial chemistry approach for the synthesis of internally quenched substrates of the Zika virus NS2B-NS3 protease that were optimized in prime positions of the peptide chain. Final substrate ABZ-Val-Lys-Lys-Arg-Ala-Ala-Trp-Tyr(3-NO₂)-NH₂ displays an excellent kinetic parameter (k _cat/K _M reaching nearly 1.26 × 10⁸ M^-1 × s^-1), which is over 10 times greater than previously reported (7.7 × 10⁶ M^-1 × s^-1) substrate. Moreover, it was found to be selective over West Nile virus protease.

G-score: A function to solve the puzzle of modeling the protonation states of β-secretase binding pocket

The population density concept has emerged as a proposal for the analysis of molecular dynamics results, the key characteristic of population density is the evaluation of the simultaneous occurrence of a set of relevant parameters for a system. However, despite its statistical strength, selection of the tolerance level for the comparison of different models may appear as arbitrary. This work introduces the G-score, a function which summarizes and categorizes the results of population density analysis. Additionally, it incorporates parameters based on rmsd and dihedral angles, besides the protein-protein and protein-ligand interatomic distances conventionally used, which complement each other to provide a better description of the behavior of the system. These newly-proposed tools were applied to determine the most probable protonation state of the aspartic dyad of BACE1, Asp93 and Asp289, in the presence of three types of transition state inhibitors namely: reduced amides, tertiary carbinamines and hydroxyethylamines. The results show a full agreement between G-score values and population density charts, with the advantage of allowing a quick and direct comparison among all the considered models. We anticipate that the simplicity of calculating the parameters employed in this study will permit the extensive use of population density and the G-score for other molecular systems.

An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20 and 30%, compared to docking scoring or to standard MM-GBSA rescoring.

Exploiting the S4-S5 Specificity of Human Neutrophil Proteinase 3 to Improve the Potency of Peptidyl Di(chlorophenyl)-phosphonate Ester Inhibitors: A Kinetic and Molecular Modeling Analysis

The neutrophilic serine protease proteinase 3 (PR3) is involved in inflammation and immune response and thus appears as a therapeutic target for a variety of infectious and inflammatory diseases. Here we combined kinetic and molecular docking studies to increase the potency of peptidyl-diphenyl phosphonate PR3 inhibitors. Occupancy of the S1 subsite of PR3 by a nVal residue and of the S4-S5 subsites by a biotinylated Val residue as obtained in biotin-VYDnV^P(O-C₆H₄-4-Cl)₂ enhanced the second-order inhibition constant k_obs/[I] toward PR3 by more than 10 times ( k_obs/[I] = 73000 ± 5000 M^-1 s^-1) as compared to the best phosphonate PR3 inhibitor previously reported. This inhibitor shows no significant inhibitory activity toward human neutrophil elastase and resists proteolytic degradation in sputa from cystic fibrosis patients. It also inhibits macaque PR3 but not the PR3 from rodents and can thus be used for in vivo assays in a primate model of inflammation.

Chalcone Derivatives: Promising Starting Points for Drug Design

Medicinal chemists continue to be fascinated by chalcone derivatives because of their simple chemistry, ease of hydrogen atom manipulation, straightforward synthesis, and a variety of promising biological activities. However, chalcones have still not garnered deserved attention, especially considering their high potential as chemical sources for designing and developing new effective drugs. In this review, we summarize current methodological developments towards the design and synthesis of new chalcone derivatives and state-of-the-art medicinal chemistry strategies (bioisosterism, molecular hybridization, and pro-drug design). We also highlight the applicability of computer-assisted drug design approaches to chalcones and address how this may contribute to optimizing research outputs and lead to more successful and cost-effective drug discovery endeavors. Lastly, we present successful examples of the use of chalcones and suggest possible solutions to existing limitations.

VSPrep: A General KNIME Workflow for the Preparation of Molecules for Virtual Screening

Over the past decades, virtual screening has proved itself to be a valuable asset to identify new bioactive compounds. The vast majority of commonly used techniques can be described in three steps: pre-processing the dataset i. e. small (ligands) and eventually larger (receptors) molecules, execute the method and finally analyse the results. Hence, the preparation of ligands is a critical step for success of commonly used virtual screening approaches such as protein-ligand docking, similarity or pharmacophore search. We present here a new workflow, VSPrep, for the pre-processing of small molecules; it is based on freely accessible tools for academics and is integrated within the KNIME platform. It can be used to perform several chemoinformatics tasks such as molecular database cleaning, tautomer and stereoisomer enumeration, focused library design and conformer generation. Additionally, graphical reports of the results are provided to the user as a convenient analysis tool.

Methyl and p-Bromobenzyl Esters of Hydrogenated Kaurenoic Acid for Controlling Anthracnose in Common Bean Plants

Kaurenoic acid derivatives were prepared and submitted to in vitro assays with the fungus Colletotrichum lindemuthianum, which causes anthracnose disease in the common bean. The most active substances were found to be methyl and p-bromobenzylesters, 7 and 9, respectively, of the hydrogenated kaurenoic acid, which presented a minimum inhibitory concentration (MIC) of 0.097 and 0.131 mM, respectively, while the commercial fungicide methyl thiophanate (MT) presented a MIC of 0.143 mM. Substances 7 (1.401 mM) and 9 (1.886 mM) reduced the severity of anthracnose in common bean to values statistically comparable to MT (2.044 mM). According to an in silico study, both compounds 7 and 9 are inhibitors of the ketosteroid isomerase (KSI) enzyme produced by other organisms, the amino acid sequence of which could be detected in fungal genomes. These substances appeared to act against C. lindemuthianum by inhibiting its KSI. Therefore, substances 7 and 9 are promising for the development of new fungicides.

Oxime Ethers of (E)-11-Isonitrosostrychnine as Highly Potent Glycine Receptor Antagonists

A series of (E)-11-isonitrosostrychnine oxime ethers, 2-aminostrychnine, (strychnine-2-yl)propionamide, 18-oxostrychnine, and N-propylstrychnine bromide were synthesized and evaluated pharmacologically at human α1 and α1β glycine receptors in a functional fluorescence-based and a whole-cell patch-clamp assay and in [³H]strychnine binding studies. 2-Aminostrychnine and the methyl, allyl, and propargyl oxime ethers were the most potent α1 and α1β antagonists in the series, displaying IC₅₀ values similar to those of strychnine at the two receptors. Docking experiments to the strychnine binding site of the crystal structure of the α3 glycine receptor indicated the same orientation of the strychnine core for all analogues. For the most potent oxime ethers, the ether substituent was accommodated in a lipophilic receptor binding pocket. The findings identify the oxime hydroxy group as a suitable attachment point for linking two strychnine pharmacophores by a polymethylene spacer and are, therefore, important for the design of bivalent ligands targeting glycine receptors.

Computational methods in drug discovery

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

Updating molecular properties during early drug discovery

Current multiparameter optimization (MPO) strategies make use of few experimental physicochemical descriptors (i.e., solubility at physiological pH and lipophilicity in the octanol/water system). Here, we show how new trends in drug discovery (i.e., large and flexible molecules for 'difficult' targets) call for the integration of ad hoc descriptors in MPO approaches. In particular, to rank, select, and optimize drug candidates, it could be relevant to have experimental data relating to the acid-base properties and the folding of the molecule to mask polar groups (so-called 'chameleonic' properties). We propose two strategies to quantify ionization and chameleonic properties and discuss their practical integration in property criteria profiles.

Substrate profiling of Zika virus NS2B-NS3 protease

Zika virus (ZIKV), isolated from macaques in Uganda in 1947, was not considered to be a dangerous human pathogen. However, this view has recently changed as ZIKV infections are now associated with serious pathological disorders including microcephaly and Guillain-Barré syndrome. Similar to other viruses in the Flaviviridae family, ZIKV expresses the serine protease NS3 which is responsible for viral protein processing and replication. Herein, we report the expression of an active NS3^pro domain fused with the NS2B cofactor (NS2B_LN NS3^pro ) in a prokaryotic expression system and profile its specificity for synthesized FRET-type substrate libraries. Our findings pave way for screening potential intracellular substrates of NS3 and for developing specific inhibitors of this ZIKV protease.

The Rational Design, Synthesis, and Antimicrobial Properties of Thiophene Derivatives That Inhibit Bacterial Histidine Kinases

The emergence of multidrug-resistant bacteria emphasizes the urgent need for novel antibacterial compounds targeting unique cellular processes. Two-component signal transduction systems (TCSs) are commonly used by bacteria to couple environmental stimuli to adaptive responses, are absent in mammals, and are embedded in various pathogenic pathways. To attenuate these signaling pathways, we aimed to target the TCS signal transducer histidine kinase (HK) by focusing on their highly conserved adenosine triphosphate-binding domain. We used a structure-based drug design strategy that begins from an inhibitor-bound crystal structure and includes a significant number of structurally simplifiying "intuitive" modifications to arrive at the simple achiral, biaryl target structures. Thus, ligands were designed, leading to a series of thiophene derivatives. These compounds were synthesized and evaluated in vitro against bacterial HKs. We identified eight compounds with significant inhibitory activities against these proteins, two of which exhibited broad-spectrum antimicrobial activity. The compounds were also evaluated as adjuvants for the treatment of resistant bacteria. One compound was found to restore the sensivity of these bacteria to the respective antibiotics.

Docking Screens for Novel Ligands Conferring New Biology

It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.