Protein Binding Pocket Research Articles

Taxifolin and Lucidin as Potential E6 Protein Inhibitors: p53 Function Re-Establishment and Apoptosis Induction in Cervical Cancer Cells.

Simple SummaryHuman papillomavirus (HPV)-related cancers continue to be a major medical concern, and there exists an urgent need to improve the current therapeutic approaches by combining strategies or proposing new compounds to offer more specific and less invasive treatments. The aim of this work was to discover potential inhibitors of the E6/E6AP/p53 complex formation. We started this work with an initial in silico approach including molecular docking and molecular dynamics simulations, and these tools allowed us to select potential inhibitors, using E6 protein as a target. In addition, we found that lucidin and taxifolin were able to selectively decrease the viability of HPV-positive cells to re-establish p53 protein levels and to induce apoptosis. These findings represent a promising starting point for the development of anti-HPV drugs.Cervical cancer is the fourth leading cause of death in women worldwide, with 99% of cases associated with a human papillomavirus (HPV) infection. Given that HPV prophylactic vaccines do not exert a therapeutic effect in individuals previously infected, have low coverage of all HPV types, and have poor accessibility in developing countries, it is unlikely that HPV-associated cancers will be eradicated in the coming years. Therefore, there is an emerging need for the development of anti-HPV drugs. Considering HPV E6’s oncogenic role, this protein has been proposed as a relevant target for cancer treatment. In the present work, we employed in silico tools to discover potential E6 inhibitors, as well as biochemical and cellular assays to understand the action of selected compounds in HPV-positive cells (Caski and HeLa) vs. HPV-negative (C33A) and non-carcinogenic (NHEK) cell lines. In fact, by molecular docking and molecular dynamics simulations, we found three phenolic compounds able to dock in the E6AP binding pocket of the E6 protein. In particular, lucidin and taxifolin were able to inhibit E6-mediated p53 degradation, selectively reduce the viability, and induce apoptosis in HPV-positive cells. Altogether, our data can be relevant for discovering promising leads for the development of specific anti-HPV drugs.

In silico comparative structural and compositional analysis of glycoproteins of RSV to study the nature of stability and transmissibility of RSV A.

The current scenario of COVID-19 makes us to think about the devastating diseases that kill so many people every year. Analysis of viral proteins contributes many things that are utterly useful in the evolution of therapeutic drugs and vaccines. In this study, sequence and structure of fusion glycoproteins and major surface glycoproteins of respiratory syncytial virus (RSV) were analysed to reveal the stability and transmission rate. RSV A has the highest abundance of aromatic residues. The Kyte–Doolittle scale indicates the hydrophilic nature of RSV A protein which leads to the higher transmission rate of this virus. Intra-protein interactions such as carbonyl interactions, cation–pi, and salt bridges were shown to be greater in RSV A compared to RSV B, which might lead to improved stability. This study discovered the presence of a network aromatic–sulphur interaction in viral proteins. Analysis of ligand binding pocket of RSV proteins indicated that drugs are performing better on RSV B than RSV A. It was also shown that increasing the number of tunnels in RSV A proteins boosts catalytic activity. This study will be helpful in drug discovery and vaccine development.

Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors.

Rift valley fever virus (RVFV) is the causative agent of a viral zoonosis that causes a significant clinical burden in domestic and wild ruminants. Major outbreaks of the virus occur in livestock, and contaminated animal products or arthropod vectors can transmit the virus to humans. The viral RNA-dependent RNA polymerase (RdRp; L protein) of the RVFV is responsible for viral replication and is thus an appealing drug target because no effective and specific vaccine against this virus is available. The current study reported the structural elucidation of the RVFV-L protein by in-depth homology modeling since no crystal structure is available yet. The inhibitory binding modes of known potent L protein inhibitors were analyzed. Based on the results, further molecular docking-based virtual screening of Selleckchem Nucleoside Analogue Library (156 compounds) was performed to find potential new inhibitors against the RVFV L protein. ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity analysis of these compounds was also performed. Besides, the binding mechanism and stability of identified compounds were confirmed by a 50 ns molecular dynamic (MD) simulation followed by MM/PBSA binding free energy calculations. Homology modeling determined a stable multi-domain structure of L protein. An analysis of known L protein inhibitors, including Monensin, Mycophenolic acid, and Ribavirin, provide insights into the binding mechanism and reveals key residues of the L protein binding pocket. The screening results revealed that the top three compounds, A-317491, Khasianine, and VER155008, exhibited a high affinity at the L protein binding pocket. ADME analysis revealed good pharmacodynamics and pharmacokinetic profiles of these compounds. Furthermore, MD simulation and binding free energy analysis endorsed the binding stability of potential compounds with L protein. In a nutshell, the present study determined potential compounds that may aid in the rational design of novel inhibitors of the RVFV L protein as anti-RVFV drugs.

Nobiletin as a Neuroprotectant against NMDA Receptors: An In Silico Approach.

Excitotoxicity is a type of neurodegenerative disorder. It caused by excessive glutamate receptor activation, which leads to neuronal malfunction and fatality. The N-methyl-D-aspartate (NMDA) receptors are found in glutamatergic neurons, and their excessive activation is primarily responsible for excitotoxicity. They are activated by both glutamate binding and postsynaptic depolarization, facilitating Ca2+ entry upon activation. Therefore, they are now widely acknowledged as being essential targets for excitotoxicity issues. Molecular docking and molecular dynamics (MD) simulation analyses have demonstrated that nobiletin efficiently targets the binding pocket of the NMDA receptor protein and exhibits stable dynamic behavior at the binding site. In this study, five potential neuroprotectants, nobiletin, silibinin, ononin, ginkgolide B, and epigallocatechin gallate (EGCG), were screened against the glutamate NMDA receptors in humans via computational methods. An in silico ADMET study was also performed, to predict the pharmacokinetics and toxicity profile for the expression of good drug-like behavior and a non-toxic nature. It was revealed that nobiletin fulfills the criteria for all of the drug-likeness rules (Veber, Lipinski, Ghose, Muegge, and Egan) and has neither PAINS nor structural alerts (Brenks). In conclusion, nobiletin demonstrated a possible promising neuroprotectant activities compared to other selected phytochemicals. Further, it can be evaluated in the laboratory for promising therapeutic approaches for in vitro and in vivo studies.

FastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation.

Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein-ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein-ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of >80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/.

Molecular docking analysis reveals the functional inhibitory effect of Genistein and Quercetin on TMPRSS2: SARS-COV-2 cell entry facilitator spike protein

BackgroundThe Transmembrane Serine Protease 2 (TMPRSS2) of human cell plays a significant role in proteolytic cleavage of SARS-Cov-2 coronavirus spike protein and subsequent priming to the receptor ACE2. Approaching TMPRSS2 as a therapeutic target for the inhibition of SARS-Cov-2 infection is highly promising. Hence, in the present study, we docked the binding efficacy of ten naturally available phyto compounds with known anti-viral potential with TMPRSS2. The aim is to identify the best phyto compound with a high functional affinity towards the active site of the TMPRSS2 with the aid of two different docking software. Molecular Dynamic Simulations were performed to analyse the conformational space of the binding pocket of the target protein with selected molecules.ResultsDocking analysis using PyRx version 0.8 along with AutoDockVina reveals that among the screened phyto compounds, Genistein shows the maximum binding affinity towards the hydrophobic substrate-binding site of TMPRSS2 with three hydrogen bonds interaction ( − 7.5 kcal/mol). On the other hand, molecular docking analysis using Schrodinger identified Quercetin as the most potent phyto compound with a maximum binding affinity towards the hydrophilic catalytic site of TMPRSS2 ( − 7.847 kcal/mol) with three hydrogen bonds interaction. The molecular dynamics simulation reveals that the Quercetin-TMPRSS complex is stable until 50 ns and forms stable interaction with the protein ( − 22.37 kcal/mol of MM-PBSA binding free energy). Genistein creates a weak interaction with the loop residues and hence has an unstable binding and exits from the binding pocket.ConclusionThe compounds, Quercetin and Genistein, can inhibit the TMPRSS2 guided priming of the spike protein. The compounds could reduce the interaction of the host cell with the type I transmembrane glycoprotein to prevent the entry of the virus. The critical finding is that compared to Genistein, Quercetin exhibits higher binding affinity with the catalytic unit of TMPRSS2 and forms a stable complex with the target. Thus, enhancing our innate immunity by consuming foods rich in Quercetin and Genistein or developing a novel drug in the combination of Quercetin and Genistein could be the brilliant choices to prevent SARS-Cov-2 infection when we consider the present chaos associated with vaccines and anti-viral medicines.

Indexing Ultrafast Shape-Based Descriptors in MongoDB to Identify TLR4 Pathway Agonists.

A method is presented for an ultrafast shape-based search workflow for the screening of large compound collections, i.e., those of vendors. The three-dimensional shape of a molecule dictates its biological activity by enabling the molecule to fit into binding pockets of proteins. Quite often, distinctly different chemical compounds that have similar shapes can bind in a similar way. OpenEye pioneered an algorithm for comparing shapes of molecules by overlaying them in a computer and measuring differences between a query molecule and a target molecule. Overlaying shapes is a computationally intensive process and represents a bottleneck in searching for similar molecules. More recent publications describe alternative methods of overlaying molecules, which are accomplished by comparing shape-based descriptors. These methods were implemented in the Open Drug Discovery Toolkit (ODDT) package. We utilized a combination of open-source software packages like ODDT and RDkit to implement a workflow for ultrafast conformer generation and matching that does not require storing precomputed conformers on the file system or in memory. Moreover, the generated descriptors could be optionally stored in MongoDB for performing searches in the future. To speed up the search, we created a set of indexes from the transformed shape-based descriptors. We are in the process of calculating descriptors for multiple vendors, including Enamine's "REAL" collection of 1.2 billion compounds. Currently, the shape similarity search on more than 70 million compounds takes less than 8 s! We exemplified our methodology with the screen of compounds that can act as putative TLR4 agonists. The search was based on a literature-known small-molecule TLR4 agonist series. In due course, we identified compounds with novel structural motifs that were active in mouse and human TLR4 reporter cell lines.

Conformationally Constrained Sialyl Analogues as New Potential Binders of h-CD22.

Here, two conformationally constrained sialyl analogues were synthesized and characterized in their interaction with the inhibitory Siglec, human CD22 (h‐CD22). An orthogonal approach, including biophysical assays (SPR and fluorescence), ligand‐based NMR techniques, and molecular modelling, was employed to disentangle the interaction mechanisms at a molecular level. The results showed that the Sialyl‐TnThr antigen analogue represents a promising scaffold for the design of novel h‐CD22 inhibitors. Our findings also suggest that the introduction of a biphenyl moiety at position 9 of the sialic acid hampers canonical accommodation of the ligand in the protein binding pocket, even though the affinity with respect to the natural ligand is increased. Our results address the search for novel modifications of the Neu5Ac‐α(2‐6)‐Gal epitope, outline new insights for the design and synthesis of high‐affinity h‐CD22 ligands, and offer novel prospects for therapeutic intervention to prevent autoimmune diseases and B‐cell malignancies.

Elucidating novel antibacterial compounds from the NPASS database against the FimH lectin domain for the treatment of urinary tract infections: an in-silico study

The increase in multidrug-resistant pathogens in urinary tract infections (UTIs) among communities and hospitals threatens our ability to treat these common pathogens. Uropathogenic Escherichia coli (UPEC) strains are the most frequent uropathies linked to the development of UTIs. This work aims to introduce bioactive natural products via virtual screening of small molecules from a public database to prevent biofilm formation by inhibiting FimH, a type 1 fimbriae that plays a crucial role in UPEC pathogenicity. A total of 30926 small molecules from the NPASS database were subjected to screening via molecular docking. Followed by performing in silico ADME studies, seven molecules showed promising docking results ranging from −6.8 to −8.7 kcal/mol. As a result of the docking score findings, 100 ns Molecular dynamics (MD) simulations were performed. Based on MM-PBSA analysis, NPC313334 ligand showed high binding affinity −42 and stability with the binding pocket of FimH protein during molecular dynamic simulations. DFT calculations were also performed on the ligands to calculate the HOMO-LUMO energies of the compounds in order to an idea about their structure and reactivity. This research suggests that NPC313334 may be a possible antibacterial drug candidate that targets FimH to reduce the number of UPEC-related urinary tract infections. Communicated by Ramaswamy H. Sarma

Conserved protein targets for developing pan-coronavirus drugs based on sequence and 3D structure similarity analyses

There are 7 known human pathogenic coronaviruses, which are HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1, MERS-CoV, SARS-CoV and SARS-CoV-2. While SARS-CoV-2 is currently caused a severe epidemic, experts believe that new pathogenic coronavirus would emerge in the future. Therefore, developing broad-spectrum anti-coronavirus drugs is of great significance. In this study, we performed protein sequence and three-dimensional structure analyses for all the 20 virus-encoded proteins across all the 7 coronaviruses, with the purpose to identify highly conserved proteins and binding sites for developing pan-coronavirus drugs. We found that nsp5, nsp10, nsp12, nsp13, nsp14, and nsp16 are highly conserved both in protein sequences (with average identity percentage higher than 52%, average amino acid conservation scores higher than 5.2) and binding pockets (with average amino acid conservation scores higher than 5.8). We also performed the similarity comparison between these 6 proteins and all the human proteins, and found that all the 6 proteins have similarity less than 25%, indicating that the drugs targeting the 6 proteins should have little interference of human protein function. Accordingly, we suggest that nsp5, nsp10, nsp12, nsp13, nsp14, and nsp16 are potential targets for pan-coronavirus drug development.

In-silico studies on wild orange (Citrus macroptera Mont.) compounds against COVID-19 pro-inflammation targets

One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an in silico approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of Citrus macroptera against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski’s rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our in silico results suggest that all the natural phyto-compounds derived from C. macroptera could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation. Communicated by Ramaswamy H. Sarma

Design, synthesis, and molecular modeling of coumarin derivatives as MDM2 inhibitors targeting breast cancer.

The coumarin ring was used as a central scaffold that was substituted with a variety of bioactive functional groups, for designing and synthesizing novel MDM2 inhibitors targeting breast cancer. The synthesized derivatives, 3c, 3d, 3g, 7b, 7c and 8 with IC50s ranging from 9.4 to 9.9µM were evaluated for their safety on MCF10a normal breast cell line. The compounds showed selectivity indices of 2.15, 3.85, 2.75, 1.38, 3.72 and 5.20 respectively. 7c was selected for further investigation, the compound was capable of down-regulating MDM2 and the anti-apoptosis proteins Bcl-2 and Bcl-xL, up-regulating the level of p53 and the pro-apoptosis protein BAX, causing cell cycle arrest at G2/M phase and activating Caspase-9 to induce apoptosis. Molecular docking study revealed the capability of derivative 7c to interact with the key amino acids in p53 binding pocket of MDM2 protein. Moreover, the physicochemical properties of compound 7c were studied in silico.

Complexation of Green and Red Kaede Fluorescent Protein Chromophores by a Zwitterion to Probe Electrostatic and Induction Field Effects.

The photophysics of green fluorescent protein (GFP) and red Kaede fluorescent protein (rKFP) are defined by the intrinsic properties of the light-absorbing chromophore and its interaction with the protein binding pocket. This work deploys photodissociation action spectroscopy to probe the absorption profiles for a series of synthetic GFP and rKFP chromophores as the bare anions and as complexes with the betaine zwitterion, which is assumed as a model for dipole microsolvation. Electronic structure calculations and energy decomposition analysis using Symmetry-Adapted Perturbation Theory are used to characterize gas-phase structures and complex cohesion forces. The calculations reveal a preponderance for coordination of betaine to the phenoxide deprotonation site predominantly through electrostatic forces. Calculations using the STEOM-DLPNO-CCSD method are able to reproduce absolute and relative vertical excitation energies for the bare anions and anion-betaine complexes. On the other hand, treatment of the betaine molecule with a point-charge model, in which the charges are computed from some common electron density population analysis schemes, show that just electrostatic and point-charge induction interactions are unable to account for the betaine-induced spectral shift. The present methodology could be applied to investigate cluster forces and optical properties in other gas-phase ion-zwitterion complexes.

Target and candidate agents for diabetes treatment in the framework of the food nexus

Diabetes mellitus is a chronic disease affected by scarcity in the production of insulin. In the present study, we used the bioinformatics approach to examine the possible inhibitory abilities of phytochemical constituents of Tecoma stans towards thioredoxin interacting protein. All the phytochemicals showed good binding attraction to the binding pocket of thioredoxin-interacting protein. pkCSM server was used to detect pharmacodynamics, pharmacokinetics and toxicological profiles of phytochemical compounds. The amino acids Lysin 117, Lysin 115 and Glycine 119 were exhibited as the key residues for the phytochemicals of Tecoma stans and binding to inhibit the thioredoxin-interacting protein. However further studies are needed to identify the efficacies and activities of Tecoma stans compounds against thioredoxin-interacting protein.

Molecular Docking and QSAR Studies for Modeling the Inhibitory Activity of Pyrazole-benzimidazolone Hybrids as Novel Inhibitors of Human 4-hydroxyphenylpyruvate dioxygenase Against Type I Tyrosinemia Disease

Pyrazole-benzimidazolone is a novel inhibitor of human 4-Hydroxyphenylpyruvate dioxygenase of the HPPD receptor. To analyze this inhibitory activity, a QSAR study was performed using 33 compounds. The MLR multiple linear regression method and the NN neural network were used to establish the predicted model. This model was validated by the external validation method. The molecular electronic descriptors were calculated by the DFT method. This study shows that the activity of the compounds is strongly correlated with the five descriptors selected by the MLR method. The correlation coefficients calculated by MLR and then by NN are R =0.878 and R =0.978; they allow us to evaluate the proposed quantitative model. The latter allowed us to predict the activity of new HPPD receptor inhibitors and to show the good predictive competence of the established QSAR model. Based on these results, we performed docking in the active site of HPPD protein with the most active compound (12), and we deduced that this compound specifically interacts with are GLN 307, ASN 423, and PHE 392 at the HPPD protein binding pocket; thus, it showed additional interactions with VAL 228, PRO 280, SER 267, LEU 265, LYS 421, GLN 379, GLY 420, and LEU 368, This interaction is similar to that of NTBC with the active site.

Synthesis, in silico ADME, toxicity prediction and molecular docking studies of N-substituted [1,2,4]triazolo[4,3-a]pyrazine derivatives as potential anticonvulsant agents

Two new series of N-substituted [1,2,4]triazolo[4,3-a]pyrazine derivatives, 2a-e and 3a-e were synthesized by coupling substituted acid chlorides/benzyl chlorides with 3-(trifluoromethyl)-5,6,7,8-tetrahydro-[1,2,4]triazolo[4,3-a]pyrazine and investigated for antioxidant, anticonvulsant effect and neurotoxicity. The in vitro antioxidant activity was assessed using the DPPH and hydroxyl radical scavenging assays. The anticonvulsant potential of the synthesised molecules was assessed using MES and PTZ tests, and their neurotoxicity was evaluated using a rotorod test in mice. Compounds 2a, 2b, 2e, and 3d were identified to have a good anti-seizure action while causing minimal neurotoxicity. The most effective anticonvulsants were compounds 2a, 2b, and 2e, with median effective dosages of 0.38, 0.36, and 0.25 mg/kg, respectively. A computational analysis was also conducted, which included drug-likeness and docking studies, as well as prediction of pharmacokinetic parameters. Docking studies of potent compounds in the binding pocket of the 4-aminobutyrate aminotransferase protein (PDB ID: 1OHV) reveal strong binding interactions and high docking scores. From these findings, the potent compounds 2a, 2b, and 2e might be a promising lead in the quest for safer and more effective anticonvulsants with neuroprotective properties.

Hinge region mediates signal transmission of luteinizing hormone and chorionic gonadotropin receptor

Luteinizing hormone-choriogonadotropin receptor (LHCGR), a class A G protein-coupled receptor (GPCR), plays a pivotal role in the maturation of reproductive organs and embryonic development. Compared with other GPCRs, the subfamily of LHCGR has a large extracellular domain (ECD) to interact with glycoprotein hormones. A unique hinge region connects the ECD and transmembrane domain (TMD) to transfer the activation signal. However, the signal transmission mechanism remains largely unknown. Here, both molecular dynamics simulation and evolutional analysis were applied to explore the effect of the hinge region on signal transmission. The glycoprotein hormone determined specific hinge region conformations, including the position of a long hinge loop and the ECD-TMD interface. With the hormone, the hinge region showed a characteristic rotation and displayed an active-like conformational landscape of the ECD-TMD interface with an extended TMD. The active-like hinge region conformation transduces the hormone binding signal downwards from ECD to TMD. The relationship between the hinge region and the intracelluar G protein-binding pocket was also inferred. The hinge region-mediated signal transmission mechanism offers a deeper understanding of LHCGR and provides insights into the elucidation of GPCR activation.

Computational analysis of altered one- and two-photon CD of sterols inside a protein binding pocket

Niemann Pick C2 (NPC2) is a small glycoprotein involved in cellular trafficking of cholesterol. Its dysfunction causes accumulation of cholesterol in the lysosomal organelles, a hallmark of Niemann Pick type C disease. Therefore, understanding cholesterol transport and the accumulation mechanism that may result is essential to understand the occurrence of this neurodegenerative disease. Cholestatrienol (CTL) is a fluorescent sterol widely used as an alternative to cholesterol because of its improved optical properties in spectroscopy and live-cell imaging. In this paper, the electronic circular dichroism (ECD) and the two-photon circular dichroism (TPCD) of CTL within the NPC2 binding pockets are simulated using response theory employing time-dependent density functional theory (TD-DFT). Moreover, an explicit embedding method has been used to include the effect of the protein residues and the water solvent in calculating the spectroscopic properties. In both cases, an alteration of the CD signal is observed.

An open-source molecular builder and free energy preparation workflow

Automated free energy calculations for the prediction of binding free energies of congeneric series of ligands to a protein target are growing in popularity, but building reliable initial binding poses for the ligands is challenging. Here, we introduce the open-source FEgrow workflow for building user-defined congeneric series of ligands in protein binding pockets for input to free energy calculations. For a given ligand core and receptor structure, FEgrow enumerates and optimises the bioactive conformations of the grown functional group(s), making use of hybrid machine learning/molecular mechanics potential energy functions where possible. Low energy structures are optionally scored using the gnina convolutional neural network scoring function, and output for more rigorous protein–ligand binding free energy predictions. We illustrate use of the workflow by building and scoring binding poses for ten congeneric series of ligands bound to targets from a standard, high quality dataset of protein–ligand complexes. Furthermore, we build a set of 13 inhibitors of the SARS-CoV-2 main protease from the literature, and use free energy calculations to retrospectively compute their relative binding free energies. FEgrow is freely available at https://github.com/cole-group/FEgrow, along with a tutorial.

4-AMINOQUINOLINE DERIVATIVES AS ANTIMALARIAL AGENTS: MOLECULAR DOCKING STUDI

Malaria is a parasite disease that can be lethal and is carried by mosquitoes. Scoring techniques that can evaluate intermolecular binding affinity or binding free energy are used to optimise and rank the molecular docking process. 15 variants of 4-aminoquinoline were docked in the binding pocket of the Oxidoreductase protein using the docking server's Ligand fit module (1ldg.pdb). The results demonstrated that the binding energies of compounds (N-(2-amino propyl)-7-chloro-quinoline-4-amine), (3-(3-(7-chloroquinolin-4-yl amino)propyl)-2-phenyl-1,3thiazinan-4-one), and (3-(3-(7-chloroquinolin -4-ylamino)propoyl)-2-(4-nitrophenyl)-1,3thiazinan-4-one). As a result, three of the fifteen compounds will effectively combat various plasmodium strains. Future attempts by other researchers to produce new antimalarial drugs may benefit from additional study to synthesise these powerful compounds and assess their performance.