Identification of the natural compound inhibitors against Plasmodium falciparum plasmepsin-II via common feature based screening and molecular dynamics simulations

Malaria is counted amongst the deadly disease caused by Plasmodium falciparum. Recently, plasmepsin-II enzyme has gained much importance as an attractive drug target for the exploration of antimalarials. Therefore, the common feature pharmacophore models were generated from the crystallized complexes of the plasmepsin-II proteome. These models were subjected to a series of validation procedures, i.e. test set and Güner Henry studies to enlist the representative models. The selected representative hypotheses incorporating the most essential chemical features (common ZHHA) were screened against the natural product database to retrieve the potential candidates. To ensure the selection of the drug-like candidates, prior to screening, filtering steps (Drug-likeness and ADMET filters) were employed on the selected database. To study the interaction pattern of the candidates within the protein, these molecules were advanced to the molecular docking studies. Subsequently, based on the selected cut-off criteria obtained via redocking of the reference (4Z22), 15 compounds showed higher docking score (> -16.05 kcal/mol), and displayed the presence of hydrogen bonding with the crucial amino acids, i.e. Asp34 and Asp214. Further, the stability of the docked molecules was scrutinized via molecular dynamics simulations, and the results were compared with the reference compound 4Z22. All the docked compounds showed stable dynamics behaviour. Thus, in the present contribution, the combination of screening and stability procedures resulted in the identification of 15 hits that can serve as a new chemical space in the designing of the novel antimalarials.Communicated by Ramaswamy H. Sarma.

Molecular docking and CoMFA studies of thiazoloquin(az)olin(on)es as CD38 inhibitors: determination of inhibitory mechanism, pharmacophore interactions, and design of new inhibitors

In this research, molecular docking and 3D-QSAR studies were carried out on a series of 79 thiazoloquin(az)olin(on)es as CD38 inhibitors. Based on docking results, four interactions including hydrogen bonding with main chain of GLU-226 (H-M-GLU-226), Van der Waals interactions with side chain of TRP-125 (V-S-TRP-125), TRP-189 (V-S-TRP-189), and THR-221 (V-S-THR-221) were considered as pharmacological interactions. Active conformation of each ligand was extracted from docking studies and was used for carrying out 3D-QSAR modeling. Comparative molecular field analysis (CoMFA) was performed on CD38 inhibitory activities of these compounds on human and mouse. We developed CoMFA models with five components as optimum models for both data-sets. For human data-set, a model with high predictive power was developed. R², RMSE, and F-test values for training set of this model were .94, .24, and 179.58, respectively, and R² and RMSE for its test set were .92 and .32, respectively. The q² and RMSE values for leave-one-out cross validation test on training set were .78 and .46, respectively, that demonstrate created model is robust. Based on extracted steric and electrostatic contour maps for this model, three inhibitors with pIC₅₀ larger than 8.85 were designed.

Investigation of Binding Characteristics of Phosphoinositide-dependent Kinase-1 (PDK1) Co-crystallized Ligands Through Virtual Pharmacophore Modeling Leading to Novel Anti-PDK1 Hits

BACKGROUND

3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits.

OBJECTIVE

This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.5 (DS 4.5).

METHODS

Accordingly, 35 crystals for PDK1 were collected and studied. Every single receptorligand interaction was validated and the significant ones were converted into their corresponding pharmacophoric features. The generated pharmacophores were scored by the Receiver Operating Characteristic (ROC) curve analysis.

RESULTS

Consequently, 169 pharmacophores were generated and sorted, 11 pharmacophores acquired good ROC-AUC results of 0.8 and a selectivity value above 8. Pharmacophore 1UU3_2_01 was used in particular as a searching filter to screen NCI database because of its acceptable validity criteria and its distinctive positive ionizable feature. Several low micromolar PDK1 inhibitors were revealed. The most potent hit illustrated anti-PDK1 IC50 values of 200 nM with 70% inhibition against SW480 cell lines.

CONCLUSION

Eventually, the active hits were docked inside the PDK1 binding pocket and the recognition points between the active hits and the receptor were analyzed that led to the discovery of new scaffolds as potential PDK1 inhibitors.

A computer aided drug discovery based discovery of lead-like compounds against KDM5A for cancers using pharmacophore modeling and high-throughput virtual screening

KDM5A over-expression mediates cancer cell proliferation and promotes resistance toward chemotherapy through epigenetic modifications. As its complete mechanism of action is still unknown, there is no KDM5A specific drug available at clinical level. In the current study, lead compounds for KDM5A were determined through pharmacophore modeling and high-throughput virtual screening from Asinex libraries containing 0.5 million compounds. These virtual hits were further evaluated and filtered for ADMET properties. Finally, 726 compounds were used for docking analysis against KDM5A. On the basis of docking score, 10 top-ranked compounds were selected and further evaluated for non-central nervous system (CNS) and CNS drug-like properties. Among these compounds, N-{[(7-Methyl-4-oxo-1,2,3,4-tetrahydrocyclopenta [c] chromen-9-yl) oxy]acetyl}-l-phenylalanine (G-score: -11.363 kcal/mol) was estimated to exhibit non-CNS properties while 2-(3,4-Dimethoxy-phenyl)-7-methoxy-chromen-4-one (G-score: -7.977 kcal/mol) was evaluated as CNS compound. Docked complexes of both compounds were finally selected for molecular dynamic simulation to examine the stability. This study concluded that both these compounds can serve as lead compounds in the quest of finding therapeutic agents against KDM5A associated cancers.

Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational- Genetic Algorithm Method

OBJECTIVE

The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity.

METHODS

The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically.

RESULTS

The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905.

CONCLUSION

Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes.

In silico modeling studies of N9-substituted harmine derivatives as potential anticancer agents: combination of ligand-based and structure-based approaches

A computational study was carried out to develop quantitative-structure activity relationship (QSAR), pharmacophore, molecular docking and molecular dynamics simulations of a series of N9-substituted harmine derivatives in order to investigate the structural factors involved in the cytotoxic activity and thus design new active derivatives. A valid 3 D-QSAR (R²= 0.89, q²=0.67, R²pred = 0.72) and 2 D-QSAR (R²= 0.81, q²=0.69, R²pred = 0.76) models were obtained correlating the cytotoxic activity with hydrophobic and hydrogen bond acceptor (HBA) features for 3 D-QSAR and SlogP and a_acc descriptors for 2 D-QSAR. Analysis of the selected descriptors for both models highlighted that lipophilicity and hydrogen bonding acceptor atoms remain the crucial properties and those on which cytotoxic activity depends. Also, these findings are in agreement with the characteristics of the generated pharmacophore. Furthermore, molecular docking revealed that the binding energy (-9.74 kcal/mol) and inhibition constant (0.071 µmol) correlate with the activity of the most active compound that forms hydrophobic interactions and two hydrogen bonds with the the dual specificity tyrosine phosphorylation regulated kinase 1 A (DYRK1A). The molecular dynamics simulations revealed that the protein-ligand equilibrium is stable after 100000 fs of trajectories. Based on these results, we designed new N⁹-substituted harmine derivatives with improved properties: predicted cytotoxic activities, estimated binding energies, estimated inhibition constants and interaction modes with amino acid residues of DYRK1A, compared to the best compound in the studied dataset. Additionally, these newly designed inhibitors showed promising results in the preliminary in silico Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) evaluations.Communicated by Ramaswamy H. Sarma.

Cinnamamide pharmacophore for anticonvulsant activity: evidence from crystallographic studies

A number of cinnamamide derivatives possess anticonvulsant activity due to the presence of a number of important pharmacophore elements in their structures. In order to study the correlations between anticonvulsant activity and molecular structure, the crystal structures of three new cinnamamide derivatives with proven anticonvulsant activity were determined by X-ray diffraction, namely (R,S)-(2E)-N-(2-hydroxybutyl)-3-phenylprop-2-enamide-water (3/1), C₁₃H₁₇NO₂·0.33H₂O, (1), (2E)-N-(1-hydroxy-2-methylpropan-2-yl)-3-phenylprop-2-enamide, C₁₃H₁₇NO₂, (2), and (R,S)-(2E)-N-(1-hydroxy-3-methyl-butan-2-yl)-3-phenylprop-2-enamide, C₁₄H₁₉NO₂, (3). Compound (1) crystallizes in the space group P-1 with three molecules in the asymmetric unit, whereas compounds (2) and (3) crystallize in the space group P2₁/c with one and two molecules, respectively, in their asymmetric units. The carbonyl group of (2) is engaged in an intramolecular hydrogen bond with the hydroxy group. This type of interaction is observed for the first time in these kinds of derivatives. A disorder of the substituent at the N atom occurs in the crystal structures of (2) and (3). The crystal packing of all three structures is dominated by a network of O-H...O and N-H...O hydrogen bonds, and leads to the formation of chains and/or rings. Furthermore, the crystal structures are stabilized by numerous C-H...O contacts. We analyzed the molecular structures and intermolecular interactions in order to propose a pharmacophore model for cinnamamide derivatives.

Searching for Chymase Inhibitors among Chamomile Compounds Using a Computational-Based Approach

Inhibitors of chymase have good potential to provide a novel therapeutic approach for the treatment of cardiovascular diseases. We used a computational approach based on pharmacophore modeling, docking, and molecular dynamics simulations to evaluate the potential ability of 13 natural compounds from chamomile extracts to bind chymase enzyme. The results indicated that some chamomile compounds can bind to the active site of human chymase. In particular, chlorogenic acid had a predicted binding energy comparable or even better than that of some known chymase inhibitors, interacted stably with key amino acids in the chymase active site, and appeared to be more selective for chymase than other serine proteases. Therefore, chlorogenic acid is a promising starting point for developing new chymase inhibitors.

Discovery of Potent Natural-Product-Derived SIRT2 Inhibitors Using Structure-Based Exploration of SIRT2 Pharmacophoric Space Coupled With QSAR Analyses

BACKGROUND

SIRT2 belongs to a class III of histone deacetylase (HDAC) and has crucial roles in neurodegeneration and malignancy.

OBJECTIVE

Discover structurally novel natural-product-derived SIRT2 inhibitors.

METHODS

Structure-based pharmacophore modeling integrated with validated QSAR analysis were implemented to discover structurally novel SIRT2 inhibitors from natural products database. The targeted QSAR model combined molecular descriptors with structure-based pharmacophore capable of explaining bioactivity variation of structurally diverse SIRT2 inhibitors. Manually built pharmacophore model, validated with receiver operating characteristic curve, and selected using the statistically optimum QSAR equation, was applied as a 3D-search query to mine AnalytiCon Discovery database of natural products.

RESULTS

Experimental in vitro testing of highest-ranked hits identified asperphenamate and salvianolic acid B as active SIRT2 inhibitors with IC50 values in low micromolar range.

CONCLUSION

New chemical scaffolds of SIRT2 inhibitors have been identified that could serve as a starting point for lead-structure optimization.

Identification of potent human carbonic anhydrase IX inhibitors: a combination of pharmacophore modeling, 3D-QSAR, virtual screening and molecular dynamics simulations

Human carbonic anhydrase IX (hCA IX) is a promising target for the development of potential anticancer agents. In the current study, pharmacophore and 3D-QSAR models have been developed using SLC-0111 derivatives. The developed models have been further utilized for the virtual screening process to develop potent hCA IX inhibitors. Thirteen different models have been developed by employing various combinations of training and test set molecules. Based on this, a model, AADDR.135, comprising two H-bond acceptors, two H-bond donors and one aromatic ring, has been found as the best QSAR model. The proposed model exhibits high robustness (R² = 0.9789), with good predictive ability (Q² = 0.6872). An external library of drug-like compounds (∼10000 molecules) imported from the ZINC15 database has been screened over the model AADDR.135. In total, 1601 compounds were obtained as hits. Molecular docking studies and molecular dynamics simulations have been performed on the obtained hits and, based on these computations, two unique molecules have been identified as potential hCA IX inhibitors. These show higher binding energies compared to the parent molecule and its most potent analogue.Communicated by Ramaswamy H. Sarma.

Pharmacophore-Based Virtual Screening of Novel Competitive Inhibitors of the Neurodegenerative Disease Target Kynurenine-3-Monooxygenase

The pathogenesis of several neurodegenerative diseases such as Alzheimer’s or Huntington’s disease has been associated with metabolic dysfunctions caused by imbalances in the brain and cerebral spinal fluid levels of neuroactive metabolites. Kynurenine monooxygenase (KMO) is considered an ideal therapeutic target for the regulation of neuroactive tryptophan metabolites. Despite significant efforts, the known KMO inhibitors lack blood–brain barrier (BBB) permeability and upon the mimicking of the substrate binding mode, are subject to produce reactive oxygen species as a side reaction. The computational drug design is further complicated by the absence of complete crystal structure information for human KMO (hKMO). In the current work, we performed virtual screening of readily available compounds using several protein–ligand complex pharmacophores. Each of the pharmacophores accounts for one of three distinct reported KMO protein-inhibitor binding conformations. As a result, six novel KMO inhibitors were discovered based on an in vitro fluorescence assay. Compounds VS1 and VS6 were predicted to be BBB permeable and avoid the hydrogen peroxide production dilemma, making them valuable, novel hit compounds for further drug property optimization and advancement in the drug design pipeline.

FGO: a novel ontology for identification of ligand functional group

Small molecules play crucial role in the modulation of biological functions by interacting with specific macromolecules. Hence small molecule interactions are captured by a variety of experimental methods to estimate and propose correlations between molecular structures to their biological activities. The tremendous expanse in publicly available small molecules is also driving new efforts to better understand interactions involving small molecules particularly in area of drug docking and pharmacogenomics. We have studied and designed a functional group identification system with the associated ontology for it. The functional group identification system can detect the functional group components from given ligand structure with specific coordinate information. Functional group ontology (FGO) proposed by us is a structured classification of chemical functional group which acts as an important source of prior knowledge that may be automatically integrated to support identification, categorization and predictive data analysis tasks. We have used a new annotation method which can be used to construct the original structure from given ontological expression using exact coordinate information. Here, we also discuss about ontology-driven similarity measure of functional groups and uses of such novel ontology for pharmacophore searching and de-novo ligand designing.

Computational screening of natural and natural-like compounds to identify novel ligands for sigma-2 receptor

Sigma-2 (σ₂) receptor is a transmembrane protein shown to be linked with neurodegenerative diseases and cancer development. Thus, it emerges as a potential biological target for the advancement of anticancer and anti-Alzheimer's agents. The current study was aimed to identify potential σ₂ receptor ligands using integrated computational approaches including homology modelling, combined pharmacophore- and docking-based virtual screening, and molecular dynamics (MD) simulation. Pharmacophore-based screening was conducted against a database composed of 20,523 small natural and natural-like products. In total, 1200 structures were found to satisfy the required pharmacophore features and were then exposed to docking-based screening against the generated homology model of σ₂ receptor. On the basis of the pharmacophore fit scores, docking scores, and mechanism of binding interaction, 20 potential hits were retained. Five promising candidates were selected (SR84, SR823, SR300, SR413, and SR530) on the basis of their binding score and interaction. Further, in silico ADMET profiling of these compounds showed that the selected compounds possess favourable ADME properties with low toxicity risk. The mechanism of interaction of these compounds with σ₂ receptor as well as their binding stability were characterized by MD simulation.

A novel hybrid method named electron conformational genetic algorithm as a 4D QSAR investigation to calculate the biological activity of the tetrahydrodibenzazosines

To understand the structure-activity correlation of a group of tetrahydrodibenzazocines as inhibitors of 17β-hydroxysteroid dehydrogenase type 3, we have performed a combined genetic algorithm (GA) and four-dimensional quantitative structure-activity relationship (4D-QSAR) modeling study. The computed electronic and geometry structure descriptors were regulated as a matrix and named as electron-conformational matrix of contiguity (ECMC). A chemical property-based pharmacophore model was developed for series of tetrahydrodibenzazocines by EMRE software package. GA was employed to choose an optimal combination of parameters. A model has been developed for estimating anticancer activity quantitatively. All QSAR models were established with 40 compounds (training set), then they were considered for selective capability with additional nine compounds (test set). A statistically valid 4D-QSAR ( R training 2 = 0.856 , R test 2 = 0.851 and q² = 0.650) with good external set prediction was obtained.

A Review of the Therapeutic Importance of Indole Scaffold in Drug Discovery

Indole is known as a versatile heterocyclic building block for its multiple pharmacological activities and has a high probability of success in the race for drug candidates. Many natural products, alkaloids, and bioactive heterocycles contain indole as the active principle pharmacophore. These encourage the researchers to explore it as a lead in the drug development process. The current manuscript will serve as a torchbearer for understanding the structurally diverse class of indole derivatives with extensive pharmacological activity. The current manuscript describes the intermediates and their functional groups responsible for superior biological activity compared to the standard. The review is written to help researchers to choose leads against their target but also to provide crucial insight into the design of a hybrid pharmacophore-based approach in drug design with enhanced potential. The present reviews on the indole derivatives correlate the structures with biological activities as well as essential pharmacophores, which were highlighted. The discussion was explored under challenging targets like dengue, chikungunya (anti-viral), antihypertensive, diuretic, immunomodulator, CNS stimulant, antihyperlipidemic, antiarrhythmic, anti-Alzheimer's, and neuroprotective, along with anticancer, antitubercular, antimicrobial, anti-HIV, antimalarial, anti-inflammatory, antileishmanial, antianthelmintic, and enzyme inhibitors. So, this review includes a discussion of 19 different pharmacological targets for indole derivatives that could be utilized to derive extensive information needed for ligand-based drug design. The article will guide the researchers in the selection, design of lead and pharmacophore, and ligand-based drug design using indole moiety.

Ligand based 3D-QSAR model, pharmacophore, molecular docking and ADME to identify potential fibroblast growth factor receptor 1 inhibitors

The FGF/FGFR system may affect tumor cells and stromal microenvironment through autocrine and paracrine stimulation, thereby significantly promoting oncogene transformation and tumor growth. Abnormal expression of FGFR1 in cells is considered to be the main cause of tumorigenesis and a potential target for the treatment of cancer. In this study, a combination of structure-based drug carriers and molecular docking-based virtual screening was used to screen new potential FGFR1 inhibitors. Forty eight known inhibitors were collected to establish 3 D-QSAR models and pharmacophore models, investigate the relationship between the activity and conformation of compounds, and verify the efficiency of pharmacophore. In Accelrys Discovery Studio 2016, the ZINC database was filtered by Lipinski's Rule of Five and SMART's filtration. Then, Hypo01 was used for virtual screening of ZINC database. Compounds with predicted activity values less than 1 μM were molecularly docked with FGFR1 protein crystals, the docking results were observed, and the interaction between compounds and targets was studied. The absorption, distribution, metabolism and excretion (ADME) and toxicity of potential inhibitors were studied, and a compound with new structural scaffolds were obtained. It could be further studied to explore their better therapeutic effects.Communicated by Ramaswamy H. Sarma.

Targeting pharmacophore with probe-reactivity-guided fractionation to precisely identify electrophilic sesquiterpenes and its activity of anti-TNBC

INTRODUCTION

Innovative strategy is urgently needed to precisely discover novel natural products as lead compounds for development of new drugs against orphan diseases such as triple-negative breast cancer (TNBC). Herein, we describe a targeting pharmacophore with probe-reactivity-guided strategy for the discovery of electrophilic sesquiterpene (ES), a class of bioactive natural product.

OBJECTIVE

This study aimed to identify pharmacophore, based on pharmacophore with probe-reactivity-guided strategy for precisely discovering ESs from ethyl acetate extract of Eupatorium chinense L. (EEEChL) METHODOLOGY: MTT assay combined with ultra-performance liquid chromatography (UPLC) analysis was used to identify pharmacophore. UPLC-mass spectrometry (MS) was applied to carefully compare the intrinsic reactivity characteristics of two chemoselective nucleophilic probes: glutathione (GSH) and 4-bromothiophenol (BTP) reaction with ESs. ESs was isolated and identified from EEEChL by phytochemical methods. Furthermore, stoichiometric ratio and binding site of one typical ES 8β-[4'-hydroxytigloyloxy]-5-desoxy-8-desacyleuparotin (HDDE) reaction with BTP were studied by UPLC-quadrupole time-of-flight (Q-TOF)-MS and two-dimensional nuclear magnetic resonance (NMR).

RESULTS

Eleven ESs were identified from EEEChL, MTT assay illustrated that all of the 11 ESs possess fairly good anti-TNBC activity CONCLUSIONS: Electrophilic groups were confirmed as pharmacophore of bioactive compounds contained in EEEChL. An optimised halogenated aromatic probe BTP furnishes ES-BTP conjugates that are highly conspicuous via MS by virtue of a unique isotopic bromine signature, conjugates also have a considerable separation on C18 column. The new probe-reactivity-guided strategy can effectively improve the traditional bioassay-guided approaches, and significantly increase the probability of obtaining designated bioactive compounds.

Kite-Shaped Molecules Block SARS-CoV-2 Cell Entry at a Post-Attachment Step

Anti-viral small molecules are currently lacking for treating coronavirus infection. The long development timescales for such drugs are a major problem, but could be shortened by repurposing existing drugs. We therefore screened a small library of FDA-approved compounds for potential severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) antivirals using a pseudovirus system that allows a sensitive read-out of infectivity. A group of structurally-related compounds, showing moderate inhibitory activity with IC₅₀ values in the 2–5 μM range, were identified. Further studies demonstrated that these “kite-shaped” molecules were surprisingly specific for SARS-CoV-1 and SARS-CoV-2 and that they acted early in the entry steps of the viral infectious cycle, but did not affect virus attachment to the cells. Moreover, the compounds were able to prevent infection in both kidney- and lung-derived human cell lines. The structural homology of the hits allowed the production of a well-defined pharmacophore that was found to be highly accurate in predicting the anti-viral activity of the compounds in the screen. We discuss the prospects of repurposing these existing drugs for treating current and future coronavirus outbreaks.

Synthesis and activity mechanism of some novel 2-substituted benzothiazoles as hGSTP1-1 enzyme inhibitors

Human GSTP1-1 is one of the most important proteins, which overexpresses in a large number of human tumours and is involved in the development of resistance to several anticancer drugs. So, it has become an important target in cancer treatment. In this study, 12 benzothiazole derivatives were synthesized and screened for their in vitro inhibitory activity for hGSTP1-1. Among these compounds, two of them (compounds #2 and #5) have been found to be the leads when compared with the reference drug etoposide. In order to analyse the structure-activity relationships (SARs) and to investigate the binding side interactions of the observed lead compounds, a HipHop pharmacophore model was generated and the molecular docking studies were performed by using CDocker method. In conclusion, it is observed that the lead compounds #2 and #5 possessed inhibitory activity on the hGSTP1-1 by binding to the H-site as a substrate in which the para position of the phenyl ring of the benzamide moiety on the benzothiazole ring is important. Substitution at this position with a hydrophobic group that reduces the electron density at the phenyl ring is required for the interaction with the H side active residue Tyr108.

Structure-Based Design and in Silico Screening of Virtual Combinatorial Library of Benzamides Inhibiting 2-trans Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis with Favorable Predicted Pharmacokinetic Profiles

Background: During the previous decade a new class of benzamide-based inhibitors of 2-trans enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (Mt) with unusual binding mode have emerged. Here we report in silico design and evaluation of novel benzamide InhA-Mt inhibitors with favorable predicted pharmacokinetic profiles. Methods: By using in situ modifications of the crystal structure of N-benzyl-4-((heteroaryl)methyl) benzamide (BHMB)-InhA complex (PDB entry 4QXM), 3D models of InhA-BHMBx complexes were prepared for a training set of 19 BHMBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the BHMB1-19, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation (∆∆HMM) of InhA-BHMBx complexes with the IC50exp. Further, taking into account the solvent effect and entropy changes upon ligand, binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of BHMBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds containing benzamide scaffolds. The VCL filtered by Lipinski’s rule-of-five was screened by the PH4 model to identify new BHMB analogs. Results: Gas phase QSAR model: −log₁₀(IC₅₀^exp) = pIC₅₀^exp = −0.2465 × ∆∆H_MM + 7.95503, R² = 0.94; superior aqueous phase QSAR model: pIC₅₀^exp = −0.2370 × ∆∆G_com + 7.8783, R² = 0.97 and PH4 pharmacophore model: pIC50exp = 1.0013 × pIC50exp − 0.0085, R² = 0.95. The VCL of more than 114 thousand BHMBs was filtered down to 73,565 analogs Lipinski’s rule. The five-point PH4 screening retained 90 new and potent BHMBs with predicted inhibitory potencies IC₅₀^pre up to 65 times lower than that of BHMB1 (IC₅₀^exp = 20 nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to current anti-tuberculotics. Conclusions: Combined use of QSAR models that considered binding of the BHMBs to InhA, pharmacophore model, and ADME properties helped to recognize bound active conformation of the benzamide inhibitors, permitted in silico screening of VCL of compounds sharing benzamide scaffold and identification of new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles.

Targeting SARS-CoV-2 RBD Interface: a Supervised Computational Data-Driven Approach to Identify Potential Modulators

Coronavirus disease 2019 (COVID-19) has spread out as a pandemic threat affecting over 2 million people. The infectious process initiates via binding of SARS-CoV-2 Spike (S) glycoprotein to host angiotensin-converting enzyme 2 (ACE2). The interaction is mediated by the receptor-binding domain (RBD) of S glycoprotein, promoting host receptor recognition and binding to ACE2 peptidase domain (PD), thus representing a promising target for therapeutic intervention. Herein, we present a computational study aimed at identifying small molecules potentially able to target RBD. Although targeting PPI remains a challenge in drug discovery, our investigation highlights that interaction between SARS-CoV-2 RBD and ACE2 PD might be prone to small molecule modulation, due to the hydrophilic nature of the bi-molecular recognition process and the presence of druggable hot spots. The fundamental objective is to identify, and provide to the international scientific community, hit molecules potentially suitable to enter the drug discovery process, preclinical validation and development.

Virtual design of novel Plasmodium falciparum cysteine protease falcipain-2 hybrid lactone-chalcone and isatin-chalcone inhibitors probing the S2 active site pocket

We report computer-aided design of new lactone–chalcone and isatin–chalcone (HLCIC) inhibitors of the falcipain-2 (PfFP-2). 3D models of 15 FP-2:HLCIC1-15 complexes with known observed activity (IC₅₀^exp) were prepared to establish a quantitative structure–activity (QSAR) model and linear correlation between relative Gibbs free energy of enzyme:inhibitor complex formation (ΔΔG_com) and IC₅₀^exp: pIC₅₀^exp = −0.0236 × ΔΔG_com+5.082(#); R² = 0.93. A 3D pharmacophore model (PH4) derived from the QSAR directed our effort to design novel HLCIC analogues. During the design, an initial virtual library of 2621440 HLCIC was focused down to 18288 drug-like compounds and finally, PH4 screened to identify 81 promising compounds. Thirty-three others were added from an intuitive substitution approach intended to fill better the enzyme S2 pocket. One hundred and fourteen theoretical IC₅₀ (IC₅₀^pre) values were predicted by means of (#) and their pharmacokinetics (ADME) profiles. More than 30 putative HLCICs display IC₅₀^pre 100 times superior to that of the published most active training set inhibitor HLCIC1.

Exploration of New and Potent Lead Molecules Against CAAX Prenyl Protease I of Leishmania donovani Through Pharmacophore Based Virtual Screening Approach

AIM AND OBJECTIVE

Visceral leishmaniasis is a deadly disease left untreated in over 95% of cases. It is characterized by irregular bouts of fever, weight loss, enlargement of the spleen and liver, and anemia. It is highly endemic in the Indian subcontinent. CAAX prenyl protease I of Leishmania donovani is one of the important targets regulating the post translational modification process. Hence identifying potent drug candidate against the target is essential. This study mainly focuses on developing new and potent inhibitors against CAXX prenyl protease I of Leishmania donovani.

MATERIALS AND METHODS

Pharmacophore based virtual screening was carried out using derivatives of bi-substrate analog farnesyl transferase inhibitors reported against CAAX prenyl proteases I. On the basis of ligand based pharmacophore model we have obtained 5 point pharmacophore AAADR with three hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatic ring. The newly identified hits through pharmacophore model were further docked into the active site of the modeled protein. To get further insights of protein ligand interaction we have performed induced fit docking followed by molecular dynamics simulations. The DFT analysis depicts the electronic structure properties of the compounds. These results can be useful for the development of novel and potent CAAX prenyl protease I inhibitors.

RESULTS

Initially, we have obtained a large number of newly identified hits by screening four different databases further docked into the active site of the protein and 20 compounds were selected on the basis of docking score. Perhaps Induced fit docking was performed to infer protein ligand interaction in a dynamic state and top 5 compounds 7118044, 7806909, LEG12866807, 9208535, SYN 19867403 were found to have good protein ligand interactions with key amino acid residues such as Glu287, His290 and additional interaction like Ile197, Asn209 Tyr253, Phe254, Gly256, Tyr266 with better binding energy -59.794 Kcal/mol, -66.305 Kcal/mol, -70.467 Kcal/mol, -82.474 Kcal/mol, -64.045. The predicted ADME properties are in desirable range and the HOMO/LUMO gap clearly indicates the electrons behavior of the ligands. Molecular dynamics simulations of the protein ligand complex for 20 ns clearly depicts the compounds are stable throughout the simulation time.

CONCLUSION

The newly identified hits through pharmacophore based screening could be used as potential CAAX prenyl protease I inhibitors of Leishmania donovani.

In Silico Screening of Novel α1-GABAA Receptor PAMs towards Schizophrenia Based on Combined Modeling Studies of Imidazo [1,2-a]-Pyridines

The ionotropic GABAA receptor (GABAAR) has been proven to be an important target of atypical antipsychotics. A novel series of imidazo [1,2-a]-pyridine derivatives, as selective positive allosteric modulators (PAMs) of α1-containing GABAARs with potent antipsychotic activities, have been reported recently. To better clarify the pharmacological essentiality of these PAMs and explore novel antipsychotics hits, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) were performed on 33 imidazo [1,2-a]-pyridines. The constructed 3D-QSAR models exhibited good predictive abilities. The dockings results and MD simulations demonstrated that hydrogen bonds, π-π stackings, and hydrophobic interactions play essential roles in the binding of these novel PAMs in the GABAAR binding pocket. Four hit compounds (DS01-04) were then screened out by the combination of the constructed models and computations, including the pharmacophore model, Topomer Search, molecular dockings, ADME/T predictions, and MD simulations. The compounds DS03 and DS04, with higher docking scores and better predicted activities, were also found to be relatively stable in the binding pocket by MD simulations. These results might provide a significant theoretical direction or information for the rational design and development of novel α1-GABAAR PAMs with antipsychotic activities.

Engineered protein-small molecule conjugates empower selective enzyme inhibition

Potent, specific ligands drive precision medicine and fundamental biology. Proteins, peptides, and small molecules constitute effective ligand classes. Yet greater molecular diversity would aid the pursuit of ligands to elicit precise biological activity against challenging targets. We demonstrate a platform to discover protein-small molecule (PriSM) hybrids to combine unique pharmacophore activities and shapes with constrained, efficiently engineerable proteins. In this platform, a fibronectin protein library is displayed on yeast with a single cysteine coupled to acetazolamide via a maleimide-poly(ethylene glycol) linker. Magnetic and flow cytometric sorts enrich specific binders to carbonic anhydrase isoforms. Isolated PriSMs exhibit potent, specific inhibition of carbonic anhydrase isoforms with efficacy superior to that of acetazolamide or protein alone, including an 80-fold specificity increase and 9-fold potency gain. PriSMs are engineered with multiple linker lengths, protein conjugation sites, and sequences against two different isoforms, which reveal platform flexibility and impacts of molecular designs. PriSMs advance the molecular diversity of efficiently engineerable ligands.