Structure-based Drug Design Approach Research Articles

Heterologous expression, biochemical characterisation and computational analysis of Bacteroides fragilis enolase

Bacteriodes fragilis is an anaerobic bacterium found in the human intestinal flora. In this study, BfEno was targeted with a structure-based drug design approach because inhibition of this enzyme may prevent both the aerobic and anaerobic pathways due to its role in the glycolytic pathway. First, the gene encoding BfEno was cloned, expressed and the protein produced over 95% purity. The Km and Vmax values of BfEno were determined as 314.9 µM and 256.2 µmol/min.mg, respectively. Drug-like chemicals were retrieved from the ZINC database for high-throughput virtual screening analyses. As a result of screening study, the ZINC91441604 has been proposed to bind to the active site of the enzyme and remain stable. The same compound exhibited weak binding to the human enolases than the bacterial enolase. Hence, ZINC91441604 may be proposed as a novel candidate for further in vitro and in vivo drug analysis towards the treatment of B. fragilis infections.

Discovery of Novel 3-Piperidinyl Pyridine Derivatives as Highly Potent and Selective Cholesterol 24-Hydroxylase (CH24H) Inhibitors.

Cholesterol 24-hydroxylase (CH24H or CYP46A1) is a brain-specific cytochrome P450 enzyme that metabolizes cholesterol into 24S-hydroxycholesterol (24HC) for regulating brain cholesterol homeostasis. For the development of a novel and potent CH24H inhibitor, we designed and synthesized 3,4-disubstituted pyridine derivatives using a structure-based drug design approach starting from compounds 1 (soticlestat) and 2 (thioperamide). Optimization of this series by focusing on ligand-lipophilicity efficiency value resulted in the discovery of 4-(4-methyl-1-pyrazolyl)pyridine derivative 17 (IC50 = 8.5 nM) as a potent and highly selective CH24H inhibitor. The X-ray crystal structure of CH24H in complex with compound 17 revealed a unique binding mode. Both blood-brain barrier penetration and reduction of 24HC levels (26% reduction) in the mouse brain were confirmed by oral administration of 17 at 30 mg/kg, indicating that 17 is a promising tool for the novel and selective inhibition of CH24H.

The design of TOPK inhibitors using structure-based pharmacophore modeling and molecular docking based on an MD-refined homology model.

The TOPK enzyme (also known as PBK) is a serine-threonine protein kinase that is rarely detected in normal tissues yet is found to be overexpressed and activated in a variety of cancers such as lung, colorectal, breast, and esophageal cancer. Its prevalence in cancerous cells is associated with their poor prognosis and responsiveness to treatment. This enzyme plays a vital role in cell division, specifically in regulating cytokinesis. Unlike drugs targeting early phases in mitosis, inhibition of cytokinesis by targeting biomolecules that are unique to multiplying cells poses no threat to the normal function of non-multiplying cells. Studies have shown that inhibition of cytokinesis is promising in suppressing the growth of proliferating cancerous cells as exemplified by the complete tumor regression seen with the suppression of TOPK. Herein, we report the identification of potent TOPK inhibitors with anticancer potential using a structure-based drug design approach. The only available crystal structure of TOPK corresponds to a double mutant (T9E and T198E) dimer with a distorted N-lobe conformation, thus 3D homology modeling was implemented to rebuild the enzyme's native conformation. The resulting refined model was used to generate 3D pharmacophore models for the virtual screening of small molecules databases. Retrieved hits were filtered, docked into the ATP binding site of the enzyme, rescored, and the binding free energies for the top consensually scoring hits were calculated. Consequently, 45 compounds were selected and their in vitro inhibitory activity against TOPK was tested revealing four potential hits with the most active compound having an IC50 of 3.85µM. This compound will be chosen as a lead compound to synthesize analogs aiming to enhance potency and drug-like properties and to enrich the SAR data.

Identification of natural DHFR inhibitors in MRSA strains: Structure-based drug design study

Methicillin-resistant Staphylococcus aureus (MRSA) is also known as a superbug because of its resistance against multiple antibiotics. It is an opportunistic pathogen that targets immune-compromised people with higher fatality rate and is difficult to treat. This study targets DHFR protein of Staphylococcus aureus (saDHFR), which is a crucial enzyme for its survival and is involved in the synthesis of 5,6,7,8-tetrahydrofolate, an essential cofactor involved in multiple metabolic pathways. In this study, a library of compounds with antimicrobial activity produced by Streptomyces sp. was screened for inhibitory activity towards saDHFR. Through structure-based drug design approach, the compounds showing higher affinity towards saDHFR active site and lower affinity towards human DHFR (huDHFR) were selected, which were further screened down based on their ADMET properties. Two compounds, BRN-1354521 and CHEMBL487191 were identified as the lead molecules exhibiting higher affinity towards saDHFR validated by MD simulations and binding energy calculations using MMGBSA method. This study could lay the foundation for the discovery of novel inhibitors of saDHFR with high therapeutic index to tackle the emerging resistance in Staphylococcus aureus.

Discovery of Pyrazolo[1,5-a]pyrazin-4-ones as Potent and Brain Penetrant GluN2A-Selective Positive Allosteric Modulators Reducing AMPA Receptor Binding Activity

N-Methyl-d-aspartate receptors (NMDARs) are members of the ionotropic glutamate receptor family and play a crucial role in learning and memory by regulating synaptic plasticity. Activation of NMDARs containing GluN2A, one of the NMDAR subunits, has recently attracted attention as a promising therapeutic approach for neuropsychiatric diseases such as schizophrenia, depression, and epilepsy. In the present study, we developed potent and brain-penetrable GluN2A-selective positive allosteric modulators. Lead compound 2b was generated by scaffold hopping of hit compound 1, identified from the internal alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-focused compound library through a high-throughput screening campaign. Subsequent optimization of the lead compound, including a structure-based drug design approach, resulted in the identification of a potent GluN2A PAM (R)-9, which possessed high selectivity against both subtypes of AMPAR and NMDAR. Furthermore, (R)-9 significantly enhanced long-term potentiation in the rat hippocampus 24 h after oral administration, indicating that this molecule is a potentially useful in vivo pharmacological tool for treating psychiatric diseases.

Discovery of Spiro-azaindoline Inhibitors of Hematopoietic Progenitor Kinase 1 (HPK1).

Hematopoietic progenitor kinase 1 (HPK1) is implicated as a negative regulator of T-cell receptor-induced T-cell activation. Studies using HPK1 kinase-dead knock-in animals have demonstrated the loss of HPK1 kinase activity resulted in an increase in T-cell function and tumor growth inhibition in glioma models. Herein, we describe the discovery of a series of small molecule inhibitors of HPK1. Using a structure-based drug design approach, the kinase selectivity of the molecules was significantly improved by inducing and stabilizing an unusual P-loop folded binding mode. The metabolic liabilities of the initial 7-azaindole high-throughput screening hit were mitigated by addressing a key metabolic soft spot along with physicochemical property-based optimization. The resulting spiro-azaindoline HPK1 inhibitors demonstrated improved in vitro ADME properties and the ability to induce cytokine production in primary human T-cells.

Molecular Docking Simulation Studies Identifies Potential Natural Product Derived-Antiwolbachial Compounds as Filaricides against Onchocerciasis.

Onchocerciasis is the leading cause of blindness and severe skin lesions which remain a major public health problem, especially in tropical areas. The widespread use of antibiotics and the long duration required for effective treatment continues to add to the increasing global menace of multi-resistant pathogens. Onchocerca volvulus harbors the endosymbiont bacteria Wolbachia, essential for the normal development of embryos, larvae and long-term survival of the adult worm, O. volvulus. We report here results of using structure-based drug design (SBDD) approach aimed at identifying potential novel Wolbachia inhibitors from natural products against the Wolbachia surface protein (WSP). The protein sequence of the WSP with UniProtKB identifier Q0RAI4 was used to model the three-dimensional (3D) structure via homology modelling techniques using three different structure-building algorithms implemented in Modeller, I-TASSER and Robetta. Out of the 15 generated models of WSP, one was selected as the most reasonable quality model which had 82, 15.5, 1.9 and 0.5% of the amino acid residues in the most favored regions, additionally allowed regions, generously allowed regions and disallowed regions, respectively, based on the Ramachandran plot. High throughput virtual screening was performed via Autodock Vina with a library comprising 42,883 natural products from African and Chinese databases, including 23 identified anti-Onchocerca inhibitors. The top six compounds comprising ZINC000095913861, ZINC000095486235, ZINC000035941652, NANPDB4566, acetylaleuritolic acid and rhemannic acid had binding energies of −12.7, −11.1, −11.0, −11, −10.3 and −9.5 kcal/mol, respectively. Molecular dynamics simulations including molecular mechanics Poisson-Boltzmann (MMPBSA) calculations reinforced the stability of the ligand-WSP complexes and plausible binding mechanisms. The residues Arg45, Tyr135, Tyr148 and Phe195 were predicted as potential novel critical residues required for ligand binding in pocket 1. Acetylaleuritolic acid and rhemannic acid (lantedene A) have previously been shown to possess anti-onchocercal activity. This warrants the need to evaluate the anti-WSP activity of the identified molecules. The study suggests the exploitation of compounds which target both pockets 1 and 2, by investigating their potential for effective depletion of Wolbachia. These compounds were predicted to possess reasonably good pharmacological profiles with insignificant toxicity and as drug-like. The compounds were computed to possess biological activity including antibacterial, antiparasitic, anthelmintic and anti-rickettsials. The six natural products are potential novel antiwolbachial agents with insignificant toxicities which can be explored further as filaricides for onchocerciasis.

Part-II- in silico drug design: application and success

Abstract In silico tools have indeed reframed the steps involved in traditional drug discovery and development process and the term in silico has become a familiar term in pharmaceutical sector like the terms in vitro and in vivo. The successful design of HIV protease inhibitors, Saquinavir, Indinavir and other important medicinal agents, initiated interest of researchers in structure based drug design approaches (SBDD). The interactions between biomolecules and a ligand, binding energy, free energy and stability of biomolecule-ligand complex can be envisioned and predicted by applying molecular docking studies. Protein-ligand, protein-protein, DNA-ligand interactions etc. aid in elucidating molecular level mechanisms of drug molecules. In the Ligand based drug design (LBDD) approaches, QSAR studies have tremendously contributed to the development of antimicrobial, anticancer, antimalarial agents. In the recent years, multiQSAR (mt-QSAR) approaches have been successfully employed for designing drugs against multifactorial diseases. Output of a research in several instances is rewarding when both SBDD and LBDD approaches are combined. Application of in silico studies for prediction of pharmacokinetics was once a real challenge but one can see unlimited number publications comprising tools, data bases which can accurately predict almost all the pharmacokinetic parameters. Absorption, distribution, metabolism, transporters, blood brain barrier permeability, hERG toxicity, P-gp affinity and several toxicological end points can be accurately predicted for a candidate molecule before its synthesis. In silico approaches are greatly encouraged a result of growing limitations and new legislations related to the animal use for research. The combined use of in vitro data and in silico tools will definitely decrease the use of animal testing in the future.In this chapter, in silico approaches and their applications are reviewed and discussed giving suitable examples.

Identification of dual inhibitor of phosphodiesterase 1B/10A using structure-based drug design approach

Schizophrenia is a neuropsychiatric disorder characterised by positive symptoms, negative symptoms, and cognitive impairment. Dopamine system dysfunction is strongly implicated in the aetiology of schizophrenia, where the hyperactivity in striatal dopamine and hypoactivity in cortical dopamine is considered the key feature of this serious mental disorder. Recent research has been directed toward finding new therapeutic agents to potentiate the D1-receptor signalling and inhibit the D2-receptor signalling. Two enzymes in the phosphodiesterase (PDE) family, PDE1B and PDE10A, have become desirable drug targets for psychiatric disorders in general and schizophrenia in particular due to their high expression in brain regions involved in schizophrenia. The PDE1B enzyme represents the major inactivation mechanism of D1-receptors; therefore, the inhibition of PDE1B activity will potentiate the D1-receptor signalling and mitigate the negative symptoms and cognitive impairments. Whereas the inhibition of PDE10A activity has generated much excitement as a potentially novel mechanism to treat the positive symptoms of schizophrenia, which are attributed to the increased dopamine D2-receptor signalling. In which the inhibition of PDE10A activity will block the D2-receptor signalling and improve the positive symptoms. Therefore, in the quest of searching for a new treatment for schizophrenia, we report here the identification of a novel inhibitor with dual action on PDE1B and PDE10A. A sequential pharmacophore-based virtual screening, molecular docking and molecular dynamic simulations; were combined to identify the new inhibitor. After a detailed analysis of the results, two ligands were selected for the biological evaluation, in which one of the two ligands showed significant inhibitory activity against both PDE1B and PDE10A. The newly identified inhibitor can be explored for further optimisation and evaluated in vivo for its antipsychotic-like effects.

Structure prediction and discovery of inhibitors against phosphopantothenoyl cysteine synthetase of Acinetobacter baumannii

Acinetobacter baumannii is an extremely dangerous multidrug-resistant (MDR) gram-negative pathogen which poses a serious life-threatening risk in immunocompromised patients. Phosphopantothenoyl cysteine synthetase (PPCS) catalyzes the formation of an amide bond between L-cysteine and phosphopantothenic acid (PPA) to form 4′- Phosphopantothenoylcysteine during Coenzyme A (CoA) biosynthesis. CoA is a crucial cofactor for cellular survival and inhibiting its synthesis will result in cell death. Bacterial PPCS differs from eukaryotic PPCS in a number of ways like it exists as a C-terminal domain of a PPCDC/PPCS fusion protein whereas eukaryotic PPCS exists as an independent protein. This difference makes it an attractive drug target. For which a conventional iterative approach of SBDD (structure-based drug design) was used, which began with three-dimensional structure prediction of AbPPCS using PHYRE 2.0. A database of FDA-approved compounds (Drug Bank) was then screened against the target of interest by means of docking score and glide energy, leading to the identification of 6 prominent drug candidates. The shortlisted 6 molecules were further subjected to all-atom MD simulation studies in explicit-solvent conditions (using AMBER force field). The MD simulation studies revealed that the ligands DB65103, DB449108 and DB443210, maintained several H-bonds with intense van der Waals contacts at the active site of the protein with high binding free energies: −11.42 kcal/mol, −10.49 kcal/mol and −10.98 kcal/mol, respectively, calculated via MM-PBSA method. Overall, binding of these compounds at the active site was found to be the most stable and robust highlighting the potential of these compounds to serve as antibacterials. Communicated by Ramaswamy H. Sarma

Improved machine learning scoring functions for identification of Electrophorus electricus's acetylcholinesterase inhibitors.

Structure-based drug design (SBDD) is an important in silico technique, used for the identification of enzyme inhibitors. Acetylcholinesterase (AChE), obtained from Electrophorus electricus (ee), is widely used for the screening of AChE inhibitors. It shares structural homology with the AChE of human and other organisms. Till date, the three-dimensional crystal structure of enzyme from ee is not available that makes it challenging to use the SBDD approach for the identification of inhibitors. A homology model was developed for eeAChE in the present study, followed by its structural refinement through energy minimisation. The docking protocol was developed using a grid dimension of 84 × 66 × 72 and grid point spacing of 0.375 Å for eeAChE. The protocol was validated by redocking a set of co-crystallised inhibitors obtained from mouse AChE, and their interaction profiles were compared. The results indicated a poor performance of the Autodock scoring function. Hence, a batch of machine learning-based scoring functions were developed. The validation results displayed an accuracy of 81.68 ± 1.73% and 82.92 ± 3.05% for binary and multiclass classification scoring function, respectively. The regression-based scoring function produced [Formula: see text] and [Formula: see text] values of 0.94, 0.635 and 0.634, respectively.

In silico molecular docking studies of oxadiazole and pyrimidine bearing heterocyclic compounds as potential antimicrobial agents.

Microbial resistance is a major problem faced by the scientific community. It has created an urgent need to develop antimicrobial agents with novel structures and mechanisms of action. With this aim, a series of novel 1,3,4-oxadiazoles bearing 3,4-dihydropyrimidine heterocyclic motifs 4a-l were designed and synthesized. One-pot Biginelli synthesis is pivotal due to the use of readily available chemicals, shorter reaction time, and ecofriendly synthesis with a good yield. The structures of the synthesized molecules were characterized and confirmed by infrared, 1 H nuclear magnetic resonance (NMR), 13 C NMR, and mass spectroscopic techniques. The title compounds were screened against Gram-positive and -negative strains of bacteria and fungi using the Mueller-Hinton broth method. Compound 4d was found to be the most promising against Escherichia coli (12.5 µg/ml), whereas the same compound showed good activity against Staphylococcus aureus at a concentration of 50 µg/ml. Other compounds of the same series, 4c and 4h, displayed moderate activity against Streptococcus pyogenes at a concentration of 50 µg/ml. Furthermore, results of the antifungal activity tests revealed that compound 4i showed promising activity against all the strains of fungi, Candida albicans, Aspergillus niger, and Aspergillus clavatus, at concentrations of 100, 50, and 100 µg/ml, respectively. Molecular docking also showed that these compounds had a significant binding affinity (Glide docking score: -7.74 to -6.531) for DNA gyrase, engaging in a series of bonded and nonbonded interactions with residues lining the active site. The results of molecular docking study validated the experimental findings, thereby providing an initiation mark to optimize this motif using a structure-based drug design approach.

Histone Deacetylase Inhibitors as Potential COVID-19 Virus RNA-Dependent RNA Polymerase Inhibitors: A Molecular Docking and Dynamics Study

The novel coronavirus disease that initially appeared in 2019, commonly identified as COVID-19 is an acute infectious disease precipitated by the SARSCoV- 2 and has become a severe pandemic health crisis. People stricken with a severe case of COVID-19 are subject to a relatively higher mortality rate, which is brought about predominantly by the difficulty of having potent and specific antiviral drugs for its treatment. In this context, the viral RNA-dependent RNA polymerase (RdRp) is an attractive target for antiviral inhibitors, mainly because of its essential role in processing the polyproteins translated from viral RNA. Moreover, histone deacetylases inhibitors represent one of the most promising antiviral agents. Therefore, in this contribution, the in silico structure-based drug design approach was employed to identify novel structural characteristics for the potential repurposed activity of HDACIs as antivirals against COVID-19. Herein, 12 HDAC inhibitors were screened to explore their potential anti-viral activity against RNA-dependent RNA polymerase (RdRp) (6NUR). Results revealed that large number of the screened HDAC inhibitors are strongly bound into the active binding site of crystallographic structure of RNA-dependent RNA polymerase (RdRp) (6NUR) with lowest CDOCKER energy and CDOCKER interaction energy are very close to those of the control drug remdesivir. Importantly, the virtually screened HDAC inhibitors, particularly, Givinostat, Pracinostat, Panobinostat, Romidepsin (FK228) and its active metabolite (RedF) could be promising candidates for COVID-19 RNA-dependent RNA polymerase (RdRp) inhibitors. Significantly, these inhibitors should be evaluated on their effectivity when treating COVID-19, specifically using the drugs that have been approved for clinical trials with limited toxicity.

Abstract P-25: High-Resolution Cryo-Electron Microscopy Structure of the Staphylococcus Aureus Ribosome Brings to Light New Possible Drug Targets

Background: Antibiotic resistance is a growing worldwide problem. One of the major resistant bacterial pathogens is Staphylococcus aureus, which became a burden of healthcare systems around the world. To overcome the issue, more drug discovery studies are needed. One of the main antibiotic targets is a ribosome – the central hub of protein synthesis. Structural data of the ribosome and its features are a crucial milestone for the effective development of new drugs, especially using structure-based drug design approaches. Apart from many small structural features, ribosome possesses rRNA modifications that play a role in the fine-tuning of protein synthesis. Detailed species-specific structural data of the S. aureus ribosome is also a useful model for understanding the resistance mechanisms. This information could help with the design of new antibiotics and the upgrading of old ones. The data on S. aureus ribosomal RNA modifications and corresponding modification enzymes are very limited. Our aim was to improve the current models of the S. aureus ribosome by determining its structure with functional ligands at a much higher resolution - thereby creating a foundation for structure-based drug design experiments and research of new drug targets. Methods: The S. aureus ribosome complex consists of three components: ribosome, fMet-tRNAfMet, mRNA and 70S ribosome. The complex from purified components was formed in vitro and applied to cryo-EM grids. Data was collected at Titan Krios with Gatan K2 detector (IGBMC, France). The data was processed and modeled in Relion 2.1, Chimera, Coot, and Phenix. Results: We determined the cryo-EM reconstruction at 3.2 Å resolution of the S. aureus ribosome with P-site tRNA, messenger RNA. Based on the experimental map and existing bioinformatic data, we at the first time identified and assigned 10 modifications of S. aureus rRNA. We analyzed the positions of rRNA modifications and their possible functions. Conclusion: In this study, we describe our structure of S. aureus ribosome with functional ligands. The present model is the highest resolution and most precise that is available at the moment. We propose a set of methyltransferases as targets for future drug discovery studies. The proposed methyltransferases and corresponding modifications may play an important role in protein synthesis and its regulation.

A Computational and Literature-Based Evaluation for a Combination of Chiral Anti-CoV Drugs to Block and Eliminate SARS-CoV-2 Safely

It has been a great challenge for scientists to develop an anti-Covid drug/vaccine with fewer side effects, since the coronavirus pandemic began. Of course, the prescription of chiral drugs (chloroquine or hydroxychloroquine) has been proved wrong because these chiral drugs neither kill the virus nor eliminate it from the body, but block SARS-CoV-2 from binding to human cells. Another hurdle facing the world is not only the positive test of the patient recovered from coronavirus, but also the second wave of Covid-19. Hence, the world demands such a drug or drug combination which not only prevents the entry of SARS-CoV-2 in the human cell but also ejects it or its material from the body completely. The current computational study not only utilizes a structure-based drug design approach to find possible drug candidates but also explains (i) why the prescription of chiral drugs was not satisfactory, (ii) what types of modification can make their prescription satisfactory, (iii) the mechanism of action of chiral drugs (chloroquine and hydroxychloroquine) to block SARS-CoV-2 from binding to human cells, and (iv) the strength of mefloquine to eliminate SARS-CoV-2. As the main protease (M[Formula: see text]) of microbes is considered as an effective target for drug design and development, the binding affinities of mefloquine with the M[Formula: see text] of JC virus and SARS-CoV-2 were calculated, and then compared to know the eliminating strength of mefloquine against SARS-CoV-2. The M[Formula: see text] of JC virus was taken because mefloquine has already shown a tremendous result of eliminating it from the body. The prescription of a combination of S-[Formula: see text]-hydroxychloroquine and [Formula: see text]-mefloquine is considered as a boon by the predicted study.

Dual Glycolate Oxidase/Lactate Dehydrogenase A Inhibitors for Primary Hyperoxaluria.

Both glycolate oxidase (GO) and lactate dehydrogenase A (LDHA) influence the endogenous synthesis of oxalate and are clinically validated targets for treatment of primary hyperoxaluria (PH). We investigated whether dual inhibition of GO and LDHA may provide advantage over single agents in treating PH. Utilizing a structure-based drug design (SBDD) approach, we developed a series of novel, potent, dual GO/LDHA inhibitors. X-ray crystal structures of compound 15 bound to individual GO and LDHA proteins validated our SBDD strategy. Dual inhibitor 7 demonstrated an IC50 of 88 nM for oxalate reduction in an Agxt-knockdown mouse hepatocyte assay. Limited by poor liver exposure, this series of dual inhibitors failed to demonstrate significant PD modulation in an in vivo mouse model. This work highlights the challenges in optimizing in vivo liver exposures for diacid containing compounds and limited benefit seen with dual GO/LDHA inhibitors over single agents alone in an in vitro setting.

Structure-Based SAR in the Design of Selective or Bifunctional Nociceptin (NOP) Receptor Agonists.

The nociceptin opioid receptor (NOP), the fourth member of the opioid receptor family, and its endogenous peptide ligand, nociceptin or orphanin FQ (N/OFQ), play a vital role in several central nervous system pathways regulating pain, reward, feeding, anxiety, motor control and learning/memory. Both selective NOP agonists as well as bifunctional agonists at the NOP and mu opioid receptor (MOP) have potential therapeutic applications in CNS disorders related to these processes. Using Surflex-Dock protocols, we conducted a computational structure-activity study of four scaffold classes of NOP ligands with varying NOP-MOP selectivity. By docking these compounds into the orthosteric binding sites within an active-state NOP homology model, and an active-state MOP crystal structure, the goal of this study was to use a structure-based drug design approach to modulate NOP affinity and NOP vs. MOP selectivity. We first docked four parent compounds (no side chain) to determine their binding interactions within the NOP and MOP binding pockets. Various polar sidechains were added to the heterocyclic A-pharmacophore to modulate NOP ligand affinity. The substitutions mainly contained a 1-2 carbon chain with a polar substituent such as an amine, alcohol, sulfamide, or guanidine. The SAR analysis is focused on the impact of structural changes in the sidechain, such as chain length, hydrogen bonding capability, and basic vs neutral functional groups on binding affinity and selectivity at both NOP and MOP receptors. This study highlights structural modifications that can be leveraged to rationally design both selective NOP and bifunctional NOP-MOP agonists with different ratios of functional efficacy.

New InhA Inhibitors Based on Expanded Triclosan and Di-Triclosan Analogues to Develop a New Treatment for Tuberculosis.

The emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) has reinforced the need for the development of new anti-TB drugs. The first line drug isoniazid inhibits InhA. This is a prodrug requiring activation by the enzyme KatG. Mutations in KatG have largely contributed to clinical isoniazid resistance. We aimed to design new ‘direct’ InhA inhibitors that obviate the need for activation by KatG, circumventing pre-existing resistance. In silico molecular modelling was used as part of a rational structure-based drug-design approach involving inspection of protein crystal structures of InhA:inhibitor complexes, including the broad spectrum antibiotic triclosan (TCS). One crystal structure exhibited the unusual presence of two triclosan molecules within the Mycobacterium tuberculosis InhA binding site. This became the basis of a strategy for the synthesis of novel inhibitors. A series of new, flexible ligands were designed and synthesised, expanding on the triclosan structure. Low Minimum Inhibitory Concentrations (MICs) were obtained for benzylphenyl compounds (12, 43 and 44) and di-triclosan derivative (39), against Mycobacterium bovis BCG although these may also be inhibiting other enzymes. The ether linked di-triclosan derivative (38) displayed excellent in vitro isolated enzyme inhibition results comparable with triclosan, but at a higher MIC (125 µg mL−1). These compounds offer good opportunities as leads for further optimisation.

Molecular modeling of potent novel sulfonamide derivatives as non-peptide small molecule anti-COVID 19 agents

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for the COVID-19. The Sulfonamides groups have been widely introduced in several drugs, especially for their antibacterial activities and generally prescribed for respiratory infections. On the other hand, imidazole groups have the multipotency to act as drugs, including antiviral activity. We have used a structure-based drug design approach to design some imidazole derivatives of sulfonamide, which can efficiently bind to the active site of SARS-CoV-2 main protease and thus may have the potential to inhibit its proteases activity. We conducted molecular docking and molecular dynamics simulation to observe the stability and flexibility of inhibitor complexes. We have checked ADMET (absorption, distribution, metabolism, excretion and toxicity) and drug-likeness rules to scrutinize toxicity and then designed the most potent compound based on computational chemistry. Our small predicted molecule non-peptide protease inhibitors could provide a useful model in the further search for novel compounds since it has many advantages over peptidic drugs, like lower side effects, toxicity and less chance of drug resistance. Further, we confirmed the stability of our inhibitor-complex and interaction profile through the Molecular dynamics simulation study. Our small predicted molecule Communicated by Ramaswamy H. Sarma

A computational study on active constituents of Habb-ul-aas and Tabasheer as inhibitors of SARS-CoV-2 main protease

A respiratory pandemic known as coronavirus disease-19 (COVID-19) has created havoc since it emerged from Wuhan, China. COVID-19 is caused by a newly emerged SARS coronavirus (SARS-CoV) with increased pathogenicity named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Due to the lack of understanding of the mechanism of pathogenesis, an effective therapeutic option is unavailable. Epidemics described in Unani ancient literature include nazla-e-wabai and humma-e-wabai, and most of the symptoms of COVID-19 resemble nazla-e-wabai. Hence, in light of Unani literature, the treatment of COVID-19 can be managed with the composites prescribed in Unani medicine for nazla-e-wabai. In this study, a structure-based drug design approach was carried out to check the effectiveness of the pharmacologically active constituents of the Unani composites prescribed to treat nazla-e-wabai against SARS-CoV-2. We performed molecular docking of the active constituents of these composites against the main protease (Mpro), a potential drug target in SARS-CoV-2. Using detailed molecular docking analysis, Habb-ul-aas and Tabasheer were identified as potential inhibitors of SARS-CoV-2 Mpro. The active constituents of both these composites bind to the substrate-binding pocket of SARS-CoV-2 Mpro, forming interactions with key residues of the binding pocket. Molecular dynamics (MD) simulation suggested the binding of active constituents of Habb-ul-aas with SARS-CoV-2 Mpro with a strong affinity as compared to the constituents of Tabasheer. Thus, this study sheds light on the use of these Unani composites in COVID-19 therapeutics. Communicated by Ramaswamy H. Sarma