Discovery Of Novel Inhibitors Research Articles

Computational Insight into the Mechanism of Action of DNA Gyrase Inhibitors; Revealing a New Mechanism.

Discovery of novel antimicrobial agents is in need to deal with antibiotic resistance. Elucidating the mechanism of action for established drugs contributes to this endeavor. DNA gyrase is a therapeutic target used in the design and development of new antibacterial agents. Selective antibacterial gyrase inhibitors are available; however, resistance development against them is a big challenge. Hence, novel gyrase inhibitors with novel mechanisms are required. In this study, the mechanism of action for selected DNA gyrase inhibitors available was carried out through molecular docking and molecular dynamics (MD) simulation. In addition, pharmacophore analysis, density functional theory (DFT) calculations, and computational pharmacokinetics analysis of the gyrase inhibitors were performed. This study demonstrated that all the DNA gyrase inhibitors investigated, except compound 14, exhibit their activity by inhibiting gyrase B at a binding pocket. The interaction of the inhibitors at Lys103 was found to be essential for the binding. The molecular docking and MD simulation results revealed that compound 14 could act by inhibiting gyrase A. A pharmacophore model that consisted of the features that would help the inhibition effect was generated. The DFT analysis demonstrated 14 had relatively high chemical stability. Computational pharmacokinetics analysis revealed that most of the explored inhibitors were estimated to have good drug-like properties. Furthermore, most of the inhibitors were found to be non-mutagenic. In this study, mode of action elucidation through molecular docking and MD simulation, pharmacophore model generation, pharmacokinetic property prediction, and DFT study for selected DNA gyrase inhibitors were carried out. The outcomes of this study are anticipated to contribute to the design of novel gyrase inhibitors.

Abstract PO3-26-04: Discovery of novel inhibitors of the epigenetic regulatory KAT6A histone acetyl transferase and their anti-tumor activity in breast cancer cells

Abstract KAT6A is a histone acetyltransferase (HAT) which directs chromatin structural rearrangement and subsequent changes in gene transcription through acetylation of histones, primarily specific lysine residues on histone H3. KAT6A is modified in cancer, including genomic amplification, overexpression, mutation, as well as genetic rearrangement resulting in the production of fusion proteins. Dysregulation of this MYST family member and its acetyl transferase activity is known to drive gene expression and tumorigenic progression in cancers. An inhibitor of KAT6A and related MYST family member KAT6B has entered phase 1 clinical trials with durable partial responses seen in a variety of tumor types, including estrogen-receptor positive (ER+) breast cancer previously treated with a CDK4/6 inhibitor (Sommerhalder, ASCO2023). Evidence of dose dependent pharmacodynamics (H3K23Ac inhibition) was observed in peripheral blood mononuclear cells and paired tumor biopsies. Isosterix has developed 2 distinct series of KAT6A selective inhibitors which engage in the active site of KAT6A in the acetyl CoA substrate binding pocket and inhibit histone acetylation activity. The kinetics of target enzyme binding and inhibition will be discussed for both series of inhibitors. These compounds have been characterized for potency and cellular activity in a variety of assays. Both series of compounds inhibit KAT6A-mediated histone acetylation with single digit nM potency in a biochemical assay as well as significant potency in the breast cancer tumor cell line ZR-75-1, inhibiting H3K23 acetylation. Using a thermal shift assay (CETSA) and mass spectrometry-based protein quantitation, direct target engagement of KAT6A within cells has been shown. These compounds reduce cell viability of a number of breast cancer cell lines with 10 days of compound administration confirming the dependence of these tumor cell lines on KAT6A acetyl transferase activity for proliferation and cell cycle progression. Compounds are orally bioavailable with excellent pharmacokinetic (PK) properties in mice including half-lives >5 hours with oral administration. Finally, Isosterix inhibitors demonstrated anti-tumor efficacy with oral administration in a ZR-75-1 mouse xenograft tumor model. Inhibitors against this novel epigenetic target demonstrate the potential for efficacy in ER+ breast cancer as well as other tumor indications through suppression of KAT6A-directed transcriptional induction and chromatin remodeling. Table. Compound Kat6A Biochemical IC50 (µM) ZR-75-1 H3K23 Acetylation EC50 (µM) Mouse PK (p.o.) Mouse PK (i.v.) Inhibitor class %F T½ (h) Cl (mL/min/kg) SL-IST-001 0.007 0.01 100 5.2 0.47 Series 1 SL-IST-002 0.007 0.005 100 6 0.48 Series 2 Citation Format: Leslie Holsinger, Roopa RaI, Rahul R. Nagawade, Benoy Pal, Samir Pawar, Pankaj Singh, Krishna Putta, Mahaboobi Jaleel, Tove Bostrom, Jakob Karen, Qianyang Huang, Alison Hannah. Discovery of novel inhibitors of the epigenetic regulatory KAT6A histone acetyl transferase and their anti-tumor activity in breast cancer cells [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-26-04.

Abstract 3217: Discovery of novel inhibitors of the epigenetic regulator Kat6a histone acetyl transferase and characterization of their anti-tumor activity

Abstract KAT6A and its paralog KAT6B are histone acetyltransferases (HATs) which direct chromatin structural rearrangement and subsequent changes in gene transcription through acetylation of histones, primarily specific lysine residues on histone H3. KAT6A is modified in cancer, including genomic amplification, overexpression, mutation, as well as genetic rearrangement, resulting in the production of fusion proteins. Dysregulation of this MYST family member and its acetyl transferase activity is known to drive gene expression and tumorigenic progression in cancers. An inhibitor of KAT6A and KAT6B entered phase 1 clinical trials (NCT04606446). With continuous daily dosing, durable partial responses were seen in estrogen-receptor positive (ER+) breast cancer patients who had progressed on a prior endocrine therapy and CDK4/6 inhibitor. In that study, evidence of dose dependent pharmacodynamics (H3K23Ac inhibition) was observed in peripheral blood mononuclear cells and paired tumor biopsies (Sommerhalder, ASCO2023). Isosterix has developed a series of structurally diverse small molecule KAT6A-selective inhibitors which engage at the active site in the acetyl CoA substrate binding pocket. Lead compounds are selective for KAT6A and have significant potency and cellular activity in a variety of assays; they inhibit KAT6A-mediated histone acetylation in a biochemical assay as well as pharmacodynamic dose-dependent inhibition of histone acetylation in the breast cancer tumor cell line ZR-75-1. These compounds reduce cell viability of ZR-75-1 in 10 days with continuous compound administration, confirming the dependence of this cell line on KAT6A acetyl transferase activity for proliferation and cell cycle progression. Lead inhibitors are orally bioavailable with excellent pharmacokinetic properties in rodents. They demonstrate dose-dependent anti-tumor efficacy with minimal weight loss with continuous daily dosing in mouse xenograft tumor models. Inhibitors against this novel epigenetic target demonstrate the potential for efficacy in not only ER+ breast cancer but also other tumor indications which exhibit transcriptional induction dependent on KAT6A-directed chromatin remodeling. Selection of a lead candidate is planned for early 2024 with IND enabling studies to follow. Citation Format: Leslie J. Holsinger, Roopa Rai, Rahul R. Nagawade, Benoy K. Pal, Samir G. Pawar, Krishna Anand Putta, Somashekar S.C., Mahaboobi Jaleel, Jianhong Wang, Alison L. Hannah. Discovery of novel inhibitors of the epigenetic regulator Kat6a histone acetyl transferase and characterization of their anti-tumor activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3217.

Insights into nucleoside hydrolase from Leishmania donovani inhibition: A new bioaffinity chromatography-based screening assay and docking studies

Leishmaniasis, a group of neglected infectious diseases, encompasses a serious health concern, particularly with visceral leishmaniasis exhibiting potentially fatal outcomes. Nucleoside hydrolase (NH) has a fundamental role in the purine salvage pathway, crucial for Leishmania donovani survival, and presents a promising target for developing new drugs for visceral leishmaniasis treatment. In this study, LdNH was immobilized into fused silica capillaries, resulting in immobilized enzyme reactors (IMERs). The LdNH-IMER activity was monitored on-flow in a multidimensional liquid chromatography system, with the IMER in the first dimension. A C18 analytical column in the second dimension furnished the rapid separation of the substrate (inosine) and product (hypoxanthine), enabling direct enzyme activity monitoring through product quantification. LdNH-IMER exhibited high stability and was characterized by determining the Michaelis-Menten constant. A known inhibitor (1-(β-d-Ribofuranosyl)-4-quinolone derivative) was used as a model to validate the established method in inhibitor recognition. Screening of three additional derivatives of 1-(β-d-Ribofuranosyl)-4-quinolone led to the discovery of novel inhibitors, with compound 2a exhibiting superior inhibitory activity (Ki = 23.37 ± 3.64 µmol/L) compared to the employed model inhibitor. Docking and Molecular Dynamics studies provided crucial insights into inhibitor interactions at the enzyme active site, offering valuable information for developing new LdNH inhibitors. Therefore, this study presents a novel screening assay and contributes to the development of potent LdNH inhibitors.

Discovery of the 2,4-disubstituted quinazoline derivative as a novel neddylation inhibitor for tumor therapy

Overactivation of neddylation has been found in a number of common human tumor-related diseases. In recent years, targeting the neddylation pathway has become an appealing anti-cancer strategy, and it is critical to find neddylation inhibitors with novel structures and higher efficacy. Here, we present the discovery of novel inhibitors of the NEDD8-activating enzyme (NAE) and their antitumor activity in vitro. All synthesized 1,4-disubstituted piperidine compounds were evaluated for antiproliferative activity against MGC-803, MCF-7, A549, and KYSE-30 cells. Among five representative compounds, III-26 bearing a quinazoline motif was identified as the lead one due to the fact that it significantly hindered the neddylation of Cullin1. Cellular mechanisms elucidated that III-26 inhibited the proliferation, migration, and invasion of UBC12-overexpressed MGC-803 cell lines, as well as induced apoptosis and arrested the cell cycle at G2/M phase. Importantly, III-26 reduced NAE activity, thus selectively preventing neddylation of Cullin3 and Cullin1 over other Cullin members. At a dose of 4 μM, III-26 virtually entirely blocked UBC12-NEDD8 conjugation in MGC-803 cells. Our molecular modeling and kinetic investigation suggested that this compound may function as a non-covalent inhibitor of NAE.

Discovery of novel inhibitor via molecular dynamics simulations against D-alanyl-D-alanine carboxypeptidase of Enterobacter cloacae

Antibiotics resistance by bacterial pathogens is a major concern to public health worldwide resulting in high health care costs and rising mortality. Subtractive proteomics prioritized D-alanyl-D-alanine carboxypeptidas (DacB) enzyme from Enterobacter cloacae ATCC 13047 as a potential candidate for drugs designing to block pathogen cell wall biosynthesis. Virtual screening of an antibacterial library against the target unraveled a hit compound (2-[(1-methylsulfonylpiperidin-3-yl)methyl]-6-(1H-pyrazol-4-yl) pyrazine) showing high affinity and stability with the target. The N-methyl-N-propyl-methanesulfonamide of the compound is seen as a closed affinity towards domain involving strong hydrogen bonds with Ser41, Lys44, Ser285, and Asn287. The 4-methyl-1H-pyrazole is posed towards the open cavity of domain I and II and formed hydrophobic and hydrophilic contacts. The system is highly stable with average carbon-alpha deviations of 1.69 Å over trajectories of 400-ns. Three vital residues projected: Arg437, Arg438 and Leu400 from enzyme pocket via Radial distribution function (RDF) assay, which actively engaged the inhibitor. Further confirmation is done by estimating binding free energies, which confirms the very low delta energy of −7.24 kcal/mol in Generalized Born (GB) method and −7.4363 kcal/mol in Poisson-Boltzmann (PB) method. WaterSwap calculations were performed that revealed the energies highly converged, an agreement on good system stability. Lastly, three DacB mutants were created to investigate the role of functional active residues and a decline in binding affinity of the residues was noticed. These computational results provide a gateway for experimentalists to further confirm their efficacy both in-vitro and in-vivo. Communicated by Ramaswamy H. Sarma

Challenges in distinguishing functional proteins from polyproteins in databases: implications for drug discovery.

This opinion article addresses a major issue in molecular biology and drug discovery by highlighting the complications that arise from combining polyproteins and their functional products within the same database entry. This problem, exemplified by the discovery of novel inhibitors for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease, has an influence on our ability to retrieve precise data and hinders the development of targeted therapies. It also emphasizes the need for improved database practices and underscores their significance in advancing scientific research. Furthermore, it emphasizes the need of learning from the SARS-CoV-2 pandemic in order to improve global preparedness for future health crises.

AI-based Virtual Screening of Traditional Chinese Medicine and the Discovery of Novel Inhibitors of TCTP.

Translationally controlled tumour protein (TCTP) is associated with tumor diseases, such as breast cancer, and its inhibitor can reduce the growth of tumor cells. Unfortunately, there is currently no effective medication available for treating TCTP-related breast cancer. The objective of this study was to explore the inhibitor candidates among natural compounds for the treatment of breast cancer related to TCTP protein. To explore the potential inhibitors of TCTP, we first screened out four potential inhibitors in the Traditional Chinese Medicine (TCM) for cancer based on AI virtual screening using the docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCM with molecular docking and molecular dynamics (MD) methods. Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with the AI method using MolAICal software. Our MD simulations have revealed that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, and the VDW and hydrophobic interactions are crucial in the interactions between TCTP and ligands. We have proposed the candidate inhibitor of TCTP. Our study has provided a potential new method for exploring inhibitors from Traditional Chinese Medicine (TCM).

Discovery of novel inhibitors of histone deacetylase 6: Structure-based virtual screening, molecular dynamics simulation, enzyme inhibition and cell viability assays

Histone deacetylase 6 (HDAC6) contributes to cancer metastasis in several cancers, including triple-negative breast cancer (TNBC)—the most lethal form that lacks effective therapy. Although several efforts have been invested to develop selective HDAC6 inhibitors, none have been approved by the FDA. Toward this goal, existing computational studies used smaller compound libraries and shorter MD simulations. Here, we conducted a structure-based virtual screening of ZINC “Druglike” library containing 17,900,742 compounds using a Glide virtual screening protocol comprising various filters with increasing accuracy. The top 20 hits were subjected to molecular dynamics simulation, MM-GBSA binding energy calculations, and further ADMET prediction. Furthermore, enzyme inhibition assay and cell viability assay were performed on six available compounds from the identified hits. C4 (ZINC000077541942) with a good profile of predicted drug properties was found to inhibit HDAC6 (IC50: 4.7 ± 11.6 μM) with comparative affinity to that of the known HDAC6 selective inhibitor Tubacin (TA) in our experiments. C4 also demonstrated cytotoxic effects against triple-negative breast cancer (TNBC) cell line MDA-MB-231 with EC50 of 40.6 ± 12.7 μM comparable to that of TA (2–20 μM). Therefore, this compound, with pharmacophore features comprising a non-hydroxamic acid zinc-binding group, heteroaromatic linker, and cap group, is proposed as a novel HDAC6 inhibitor.

Discovery of Novel Inhibitors of BRD4 for Treating Prostate Cancer: A Comprehensive Case Study for Considering Water Networks in Virtual Screening and Drug Design.

Androgen receptor (AR) is the primary target for treating prostate cancer (PCa), which inevitably progresses due to drug-resistant mutations. Bromodomain-containing protein 4 (BRD4) has been a new potential drug target for PCa treatment. Herein, we report the rational design and discovery of novel BRD4 inhibitors through computer-aided drug design (CADD), and a hit compound SQ-1 (IC50 = 676 nM) was identified by structure-based virtual screening (SBVS) with the conserved water network. To optimize the structure of SQ-1, the free energy landscape was constructed, and the binding mechanism was explored by characterizing the water profile and the dissociation mechanism. Finally, the compound SQ-17 with improved inhibitory activity (IC50 < 100 nM) was discovered, which showed potent antiproliferative activity against LNCaP. These data highlighted a successful attempt to identify and optimize a small molecule by comprehensive CADD application and provided essential clues for developing novel therapeutics for PCa treatment.

Computational identification and exploration of novel FGFR tyrosine kinase inhibitors for the treatment of cholangiocarcinoma

Tyrosine kinase inhibitors are a specific drug class revolutionizing cancer treatment. FGFR (Fibroblast Growth Factor Receptor) is a member of the receptor tyrosine kinase family that has been involved in various alterations which have been increasingly recognized as critical molecular drivers in cholangiocarcinoma, a malignant tumor originating from bile duct epithelial cells. The paper focuses on stepwise computational investigations for the discovery of novel inhibitors of FGFR using pharmacophore modeling, virtual screening, docking, ADMET analysis, molecular dynamics, and knowledge-based structure-activity relationship. To begin with, we have considered a library of 120314868 compounds from the ZINC 15 database through pharmacophore modeling, which was narrowed down to 110 having binding affinity >−8.0 kcal mol−1. The 110 compounds were analyzed using virtual screening and compared with the FDA-approved drug pemigatinib, which provided the 34 hits with binding affinities >−6.5 kcal mol−1. Finally, the top 4 hits were considered for docking, and ADMET property analysis for drug-likeness. MD and MM-GBSA analysis were performed to predict the binding free energy of these chemicals and determine their stability. To gain insight into the structure and binding interactions of these compounds, knowledge-based SAR analyses were performed using their electrostatic potential maps computed with DFT. Several techniques were employed to build improved inhibitors based on these SAR, and they were then analyzed utilizing ADMET, MD studies, and MM-GBSA analyses. Finally, the results suggested that the identified four compounds and developed inhibitors from this current work can be employed effectively as prospective FGFR inhibitors for treating Cholangiocarcinoma. Communicated by Ramaswamy H. Sarma

A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3.

The JAKs protein family is composed of four isoforms, and JAK3 has been regarded as a druggable target for the development of drugs to treat various diseases, including hematologic tumors, cancer, and neuronal death. Therefore, the discovery of JAK3 inhibitors with novel scaffolds possesses the potential to provide additional options for drug development. This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. These techniques were used to identify inhibitors of JAK3 with a novel sketch from a specific "In-house" database. Using molecular docking with varying precision, MM/GBSA, geometric deep learning scoring, and manual selection, 10 compounds were obtained for subsequent biological evaluation. One of these 10 compounds, compound 8, was found to have inhibitory potency against JAK3 and the MOLM-16 cell line, providing a valuable lead compound for further development of JAK3 inhibitors. To gain a better understanding of the interaction between compound 8 and JAK3, molecular dynamics (MD) simulations were conducted to provide more details on the binding conformation of compound 8 with JAK3 to guide the subsequent structure optimization. In this article, we achieved compound 8 with a novel sketch possessing inhibitory bioactivity against JAK3, and it would provide an acceptable "hit" for further structure optimization and modification to develop JAK3 inhibitors.

Structure based exploration of potential lead molecules against the extracellular cysteine protease (EcpA) of Staphylococcus epidermidis: a therapeutic halt

Nosocomial infection caused by Staphylococcus epidermidis is one of the most widely spread diseases affecting the world’s population. No strategies have been developed to overcome this infection and inhibit its spread in immunocompromised patients or patients with indwelling medical devices. EcpA is an extracellular cysteine protease protein involved in biofilm formation on medical devices. Thus, blocking this mechanism may be viable for developing a drug against S. epidermidis. The current research aimed to find new, potent inhibitors that could stop the S. epidermidis EcpA protein from functioning. This study attempted to identify the most promising drug candidates using structure-based virtual screening (SBVS) from libraries of natural ligands. The top-scored molecules were shortlisted based on their IC50 values and pharmacophore properties and further validated through density functional theory (DFT) studies. We found five inhibitors using virtual screening, and the results indicate that these drugs had the highest energy binding potential towards the EcpA targets when compared to the reference molecule E-64, a known cysteine protease inhibitor. In order to evaluate the binding conformational stability of protein-ligand complexes, molecular dynamics (MD) simulations were performed in triplicate for 100 ns, revealing the significant stability of anticipated molecules at the docked site. Furthermore, principal component analysis and binding free energy calculations were performed to understand the dynamics and stability of the complexes. The current study indicated that these compounds looked to be suitable novel inhibitors of the EcpA protein and pave the path for further discovery of novel inhibitors of EcpA. Communicated by Ramaswamy H. Sarma

AI-Powered Virtual Screening of Large Compound Libraries Leads to the Discovery of Novel Inhibitors of Sirtuin-1.

The discovery of new scaffolds and chemotypes via high-throughput screening is tedious and resource intensive. Yet, there are millions of small molecules commercially available, rendering comprehensive in vitro tests intractable. We show how smart algorithms reduce large screening collections to target-specific sets of just a few hundred small molecules, allowing for a much faster and more cost-effective hit discovery process. We showcase the application of this virtual screening strategy by preselecting 434 compounds for Sirtuin-1 inhibition from a library of 2.6 million compounds, corresponding to 0.02% of the original library. Multistage in vitro validation ultimately confirmed nine chemically novel inhibitors. When compared to a competitive benchmark study for Sirtuin-1, our method shows a 12-fold higher hit rate. The results demonstrate how AI-driven preselection from large screening libraries allows for a massive reduction in the number of small molecules to be tested in vitro while still retaining a large number of hits.

Structure based virtual screening and discovery of novel inhibitors against FabD protein of Mycobacterium tuberculosis

The highly flexible nature of Mycobacterium tuberculosis (Mtb) can be owed to its tough cell wall and multiple gene interaction system which makes it resistant to frontline TB drugs. Mycolic acids are the key components of the unique cell wall that protects the organism from external threats. Proteins of the fatty acid synthesis pathway are evolutionarily conserved that enables cellular survival in harsh conditions and hence have become attractive targets. Malonyl Co-A Acyl carrier protein transacylase (FabD; MCAT, EC2.3.1.39) is an enzyme in the branching point of the unique and vast fatty acid synthase (FAS-I and FAS-II) systems of Mtb. In the present investigation, in-silico structure based drug discovery with the compounds from an open source library (NPASS) is used for target fishing and employed to understand the interaction with the target protein FabD. The potential hit compounds were filtered using exhaustive docking, considering the binding energy, key residue interaction and drug likeness property. Three compounds from the library namely NPC475074 (Hit 1), NPC260631 (Hit 2) and NPC313985 (Hit 3) with binding energies −14.45, −13.29 and −12.37 respectively were taken for molecular dynamic simulation. The results suggested that Hit 3 (NPC313985) has stable interaction with FabD protein. This article further elaborates the interaction of the identified novel compounds Hit 1 and Hit 3 along with the other known compound (Hit 2) against Mtb FabD protein. The hit compounds identified from this study could be further evaluated against mutated FabD protein and considered for in-vitro evaluation. Communicated by Ramaswamy H. Sarma

In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pneumoniae Strain D39.

Streptococcus pneumoniae is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in S. pneumoniae is raising considerable concern around the world. There is an immediate need to address the major issues that have arisen as a result of persistent infections caused by S. pneumoniae. In the present study, subtractive proteomics was used in which the entire proteome of the pathogen consisting of 1947 proteins is effectively decreased to a finite number of possible targets. Various kinds of bioinformatics tools and software were applied for the discovery of novel inhibitors. The CD-HIT analysis revealed 1887 non-redundant sequences from the entire proteome. These non-redundant proteins were submitted to the BLASTp against the human proteome and 1423 proteins were screened as non-homologous. Further, databases of essential genes (DEGG) and J browser identified almost 171 essential proteins. Moreover, non-homologous, essential proteins were subjected in KEGG Pathway Database which shortlisted six unique proteins. In addition, the subcellular localization of these unique proteins was checked and cytoplasmic proteins were chosen for the druggability analysis, which resulted in three proteins, namely DNA binding response regulator (SPD_1085), UDP-N-acetylmuramate-L-alanine Ligase (SPD_1349) and RNA polymerase sigma factor (SPD_0958), which can act as a promising potent drug candidate to limit the toxicity caused by S. pneumoniae. The 3D structures of these proteins were predicted by Swiss Model, utilizing the homology modeling approach. Later, molecular docking by PyRx software 0.8 version was used to screen a library of phytochemicals retrieved from PubChem and ZINC databases and already approved drugs from DrugBank database against novel druggable targets to check their binding affinity with receptor proteins. The top two molecules from each receptor protein were selected based on the binding affinity, RMSD value, and the highest conformation. Finally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were carried out by utilizing the SWISS ADME and Protox tools. This research supported the discovery of cost-effective drugs against S. pneumoniae. However, more in vivo/in vitro research should be conducted on these targets to investigate their pharmacological efficacy and their function as efficient inhibitors.

Discovery of novel inhibitors for Pseudomonas aeruginosa lipase enzyme from in silico and in vitro studies

Pseudomonas aeruginosa is an opportunistic pathogen prone to developing drug-resistance and is a major cause of infection for burn patients and patients suffering from cystic fibrosis or are hospitalized in intensive care units. One of the virulence factors of this bacterium is the lipase enzyme that degrades the extracellular matrix of the host tissue and promotes invasion. Bromhexine is a mucolytic drug and has recently been reported to function as a competitive inhibitor of lipase with an IC50 value of 49 µM. In the present study, an attempt was made to identify stronger inhibitors from the ChEMBL database of bioactive compounds, as compared to the reference compound Bromhexine. Following docking and MD simulations, four hit compounds (N1-N4) were selected that showed promising binding modes and low RMSD values indicative of stable protein-ligand complexes. From subsequent binding pose metadynamics (BPMD) simulations, two of these (N2 and N4) stood out as more potent than Bromhexine, displaying stable interactions with residues in the catalytic site of the enzyme. Biological investigations were performed for all four compounds. Among them, the same two hit compounds were found to be the most effective binders with IC50 values of 22.1 and 27.5 µM, respectively; i.e. roughly twice as efficient as the reference Bromhexine. Taken together, our results show that these hits can be promising new candidates to use as leads for the development of drugs targeting the P. aeruginosa lipase enzyme. Communicated by Ramaswamy H. Sarma

Novel Reversible Inhibitors of Xanthine Oxidase Targeting the Active Site of the Enzyme.

Xanthine oxidase (XO) is a flavoprotein catalysing the oxidation of hypoxanthine to xanthine and then to uric acid, while simultaneously producing reactive oxygen species. Altered functions of XO may lead to severe pathological diseases, including gout-causing hyperuricemia and oxidative damage of tissues. These findings prompted research studies aimed at targeting the activity of this crucial enzyme. During the course of a virtual screening study aimed at the discovery of novel inhibitors targeting another oxidoreductase, superoxide dismutase, we identified four compounds with non-purine-like structures, namely ALS-1, -8, -15 and -28, that were capable of causing direct inhibition of XO. The kinetic studies of their inhibition mechanism allowed a definition of these compounds as competitive inhibitors of XO. The most potent molecule was ALS-28 (Ki 2.7 ± 1.5 µM), followed by ALS-8 (Ki 4.5 ± 1.5 µM) and by the less potent ALS-15 (Ki 23 ± 9 µM) and ALS-1 (Ki 41 ± 14 µM). Docking studies shed light on the molecular basis of the inhibitory activity of ALS-28, which hinders the enzyme cavity channel for substrate entry consistently with the competitive mechanism observed in kinetic studies. Moreover, the structural features emerging from the docked poses of ALS-8, -15 and -1 may explain the lower inhibition power with respect to ALS-28. All these structurally unrelated compounds represent valuable candidates for further elaboration into promising lead compounds.

Discovery of novel inhibitor of 11 beta-hydroxysteroid dehydrogenase type 1 using in silico structure-based screening approach for the treatment of type 2 diabetes.

The current study is aimed to perform structure-based screening of FDA-approved drugs that can act as novel inhibitor of the 11beta- hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme. Structural analogs of carbenoxolone (CBX) were selected from DrugBank database and their Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) parameters were investigated by SwissADME. Molecular docking of CBX analogs against 11β-HSD1 was performed by AutoDock tool, their binding patterns were visualized using PyMOL and the interacting amino acids were determined by ProteinPlus tool. Molecular dynamics simulation was performed on the docked structure of 11β-HSD1 (Protein Data Bank (PDB) code: 2ILT) using GROMACS 2018.1. The binding energies of hydrocortisone succinate, medroxyprogesterone acetate, testolactone, hydrocortisone cypionate, deoxycorticosterone acetate, and hydrocortisone probutate were lower than that of substrate corticosterone. The molecular dynamics simulation of 11β-HSD1 and hydrocortisone cypionate docked structure showed that it formed a stable complex with the inhibitor. The Root mean square deviation (RMSD) of the protein (0.37 ± 0.05nm) and ligand (0.41 ± 0.06nm) shows the stability of the ligand-protein interaction. The docking study revealed that hydrocortisone cypionate has a higher binding affinity than carbenoxolone and its other analogs. The molecular dynamics simulation indicated the stability of the docked complex of 11β-HSD1 and hydrocortisone cypionate. These findings indicate the potential use of this FDA approved drug in the treatment of type 2 diabetes. However, validation by in vitro inhibitory studies and clinical trials on type 2 diabetes patients is essential to confirm the current findings.

Machine learning facilitated structural activity relationship approach for the discovery of novel inhibitors targeting EGFR

This research manuscript aims to find the most effective epidermal growth factor receptor (EGFR) inhibitors from millions of in house compounds through Machine Learning (ML) techniques. ML-based structure activity relationship (SAR) models were validated to predict biological activity of untested novel molecules. Six ML algorithms, including k nearest neighbour (KNN), decision tree (DT), Logistic Regression, support vector machine (SVM), multilinear regression (MLR), and random forest (RF), were used to build for activity prediction. Among these, RF classifier (accuracy for train and test set is 90% and 81%) and RF regressor (R2 and MSE for trainset is 0.83 and 0.29 and for test set, 0.69 and 0.46) showed good predictive performance. Also, the six most essential features that affect the biological activity parameter and highly contribute to model development were successfully selected by the variable importance technique. RF regression model was used to predict the biological activity expressed as pIC50 of nearly ten million molecules while RF classification model classifies those molecules into active, moderately active, and least active according to their predicted pIC50. Based on two models, thousand molecules from million molecules with higher predicted pIC50 values and classified as active were selected for molecular docking. Based on the docking scores, predicted pIC50, and binding interactions with MET769 residue, compounds, i.e., Zinc257233137, Zinc257232249, and Zinc101379788, were identified as potential EGFR inhibitors with predicted pIC50 7.72, 7.85, and 7.70. Dynamics studies were also performed on Zinc257233137 to illustrate that it has good binding free energy and stable hydrogen bonding interactions with EGFR. These molecules can be used for further research and proved to be the novel drugs for EGFR in cancer treatment. Communicated by Ramaswamy H. Sarma