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Molecular Docking in Drug Design II

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A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 14036

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Special Issue Editor

Prof. Dr. Jianping Lin

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Guest Editor

College of Pharmacy, Nankai University, Tianjin, China
Interests: computer-aided drug design; simulations of bio-systems including GPCRs, DNA nanostructures, viral proteins; computer-aided (redox) enzyme design; biological macromolecule simulation; protein electron transfer

Special Issue Information

Dear Colleagues,

Molecular docking has been one of the most widely employed tools in modern drug design and discovery. In this Special Issue, we will focus on the application of this technique to identify novel therapeutic molecules including small molecules and antibodies.

The major challenges in any docking program is the ability to recognize the right pose among the generated conformations. To solved this problem, several algorithms including fragment-based approaches have been addressed to delineate the correct poses from incorrect poses, together with the capability of computing and hardware, to eventually accomplish the full potential research of this area.

For this Special Issue, we invite the submission from contributors that describe the application of simulation. We encourage the submission of purely in silico studies, as well as computational studies with experimental validations.

Articles addressing the topics listed below are particularly welcome.

Prof. Dr. Jianping Lin
Guest Editor

Manuscript Submission Information

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Keywords

drug discovery
drug design
lead optimization
molecular modelling
structure-based drug design
ligand-based drug design
computer-aided drug design
protein–protein interactions
small molecule drugs
protein–drug conjugates (ADCs/PDCs)
fragment-based drug discovery
structure–activity relationships
ADMET
virtual screening (VS)

Published Papers (6 papers)

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Research

29 pages, 7800 KiB

Open AccessArticle

Structure-Based Identification of Natural-Product-Derived Compounds with Potential to Inhibit HIV-1 Entry

by Nneka Ugwu-Korie, Osbourne Quaye, Edward Wright, Sylvester Languon, Odame Agyapong, Emmanuel Broni, Yash Gupta, Prakasha Kempaiah and Samuel K. Kwofie

Molecules 2023, 28(2), 474; https://doi.org/10.3390/molecules28020474 - 04 Jan 2023

Cited by 3 | Viewed by 1962

Abstract

Broadly neutralizing antibodies (bNAbs) are potent in neutralizing a wide range of HIV strains. VRC01 is a CD4-binding-site (CD4-bs) class of bNAbs that binds to the conserved CD4-binding region of HIV-1 envelope (env) protein. Natural products that mimic VRC01 bNAbs by interacting with the conserved CD4-binding regions may serve as a new generation of HIV-1 entry inhibitors by being broadly reactive and potently neutralizing. This study aimed to identify compounds that mimic VRC01 by interacting with the CD4-bs of HIV-1 gp120 and thereby inhibiting viral entry into target cells. Libraries of purchasable natural products were virtually screened against clade A/E recombinant 93TH057 (PDB: 3NGB) and clade B (PDB ID: 3J70) HIV-1 env protein. Protein–ligand interaction profiling from molecular docking and dynamics simulations showed that the compounds had intermolecular hydrogen and hydrophobic interactions with conserved amino acid residues on the CD4-binding site of recombinant clade A/E and clade B HIV-1 gp120. Four potential lead compounds, NP-005114, NP-008297, NP-007422, and NP-007382, were used for cell-based antiviral infectivity inhibition assay using clade B (HXB2) env pseudotype virus (PV). The four compounds inhibited the entry of HIV HXB2 pseudotype viruses into target cells at 50% inhibitory concentrations (IC₅₀) of 15.2 µM (9.7 µg/mL), 10.1 µM (7.5 µg/mL), 16.2 µM (12.7 µg/mL), and 21.6 µM (12.9 µg/mL), respectively. The interaction of these compounds with critical residues of the CD4-binding site of more than one clade of HIV gp120 and inhibition of HIV-1 entry into the target cell demonstrate the possibility of a new class of HIV entry inhibitors. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Design II)

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20 pages, 2236 KiB

Open AccessArticle

The Impact of Software Used and the Type of Target Protein on Molecular Docking Accuracy

by Larisa Ivanova and Mati Karelson

Molecules 2022, 27(24), 9041; https://doi.org/10.3390/molecules27249041 - 18 Dec 2022

Cited by 6 | Viewed by 2309

Abstract

The modern development of computer technology and different in silico methods have had an increasing impact on the discovery and development of new drugs. Different molecular docking techniques most widely used in silico methods in drug discovery. Currently, the time and financial costs for the initial hit identification can be significantly reduced due to the ability to perform high-throughput virtual screening of large compound libraries in a short time. However, the selection of potential hit compounds still remains more of a random process, because there is still no consensus on what the binding energy and ligand efficiency (LE) of a potentially active compound should be. In the best cases, only 20–30% of compounds identified by molecular docking are active in biological tests. In this work, we evaluated the impact of the docking software used as well as the type of the target protein on the molecular docking results and their accuracy using an example of the three most popular programs and five target proteins related to neurodegenerative diseases. In addition, we attempted to determine the “reliable range” of the binding energy and LE that would allow selecting compounds with biological activity in the desired concentration range. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Design II)

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17 pages, 4152 KiB

Open AccessArticle

Structural Homology-Based Drug Repurposing Approach for Targeting NSP12 SARS-CoV-2

by Abdulelah Aljuaid, Abdus Salam, Mazen Almehmadi, Soukayna Baammi, Fahad M. Alshabrmi, Mamdouh Allahyani, Khadijah M. Al-Zaydi, Abdullah M. Izmirly, Sarah Almaghrabi, Bandar K. Baothman and Muhammad Shahab

Molecules 2022, 27(22), 7732; https://doi.org/10.3390/molecules27227732 - 10 Nov 2022

Cited by 11 | Viewed by 2018

Abstract

The severe acute respiratory syndrome coronavirus 2, also known as SARS-CoV-2, is the causative agent of the COVID-19 global pandemic. SARS-CoV-2 has a highly conserved non-structural protein 12 (NSP-12) involved in RNA-dependent RNA polymerase (RdRp) activity. For the identification of potential inhibitors for NSP-12, computational approaches such as the identification of homologous proteins that have been previously targeted by FDA-approved antivirals can be employed. Herein, homologous proteins of NSP-12 were retrieved from Protein DataBank (PDB) and the evolutionary conserved sequence and structure similarity of the active site of the RdRp domain of NSP-12 was characterized. The identified homologous structures of NSP-12 belonged to four viral families: Coronaviridae, Flaviviridae, Picornaviridae, and Caliciviridae, and shared evolutionary conserved relationships. The multiple sequences and structural alignment of homologous structures showed highly conserved amino acid residues that were located at the active site of the RdRp domain of NSP-12. The conserved active site of the RdRp domain of NSP-12 was evaluated for binding affinity with the FDA-approved antivirals, i.e., Sofosbuvir and Dasabuvir in a molecular docking study. The molecular docking of Sofosbuvir and Dasabuvir with the active site that contains conserved motifs (motif A-G) of the RdRp domain of NSP-12 revealed significant binding affinity. Furthermore, MD simulation also inferred the potency of Sofosbuvir and Dasabuvir. In conclusion, targeting the active site of the RdRp domain of NSP-12 with Dasabuvir and Sofosbuvir might reduce viral replication and pathogenicity and could be further studied for the treatment of SARS-CoV-2. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Design II)

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12 pages, 1380 KiB

Open AccessArticle

PacDOCK: A Web Server for Positional Distance-Based and Interaction-Based Analysis of Docking Results

by Jacopo Carbone, Alessia Ghidini, Antonio Romano, Luca Gentilucci and Francesco Musiani

Molecules 2022, 27(20), 6884; https://doi.org/10.3390/molecules27206884 - 14 Oct 2022

Cited by 9 | Viewed by 2582

Abstract

Molecular docking is a key method for structure-based drug design used to predict the conformations assumed by small drug-like ligands when bound to their target. However, the evaluation of molecular docking studies can be hampered by the lack of a free and easy to use platform for the complete analysis of results obtained by the principal docking programs. To this aim, we developed PacDOCK, a freely available and user-friendly web server that comprises a collection of tools for positional distance-based and interaction-based analysis of docking results, which can be provided in several file formats. PacDOCK allows a complete analysis of molecular docking results through root mean square deviation (RMSD) calculation, molecular visualization, and cluster analysis of docked poses. The RMSD calculation compares docked structures with a reference structure, also when atoms are randomly labelled, and their conformational and positional differences can be visualised. In addition, it is possible to visualise a ligand into the target binding pocket and investigate the key receptor–ligand interactions. Moreover, PacDOCK enables the clustering of docking results by identifying a restrained number of clusters from many docked poses. We believe that PacDOCK will contribute to facilitating the analysis of docking results to improve the efficiency of computer-aided drug design. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Design II)

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16 pages, 13693 KiB

Open AccessArticle

Homology Modeling, Molecular Docking, Molecular Dynamic Simulation, and Drug-Likeness of the Modified Alpha-Mangostin against the β-Tubulin Protein of Acanthamoeba Keratitis

by Tassanee Ongtanasup, Anisha Mazumder, Anupma Dwivedi and Komgrit Eawsakul

Molecules 2022, 27(19), 6338; https://doi.org/10.3390/molecules27196338 - 26 Sep 2022

Cited by 14 | Viewed by 2071

Abstract

Acanthamoeba species are capable of causing amoebic keratitis (AK). As a monotherapy, alpha-mangostin is effective for the treatment of AK; however, its bioavailability is quite poor. Moreover, the efficacy of therapy is contingent on the parasite and virulent strains. To improve readiness against AK, it is necessary to find other derivatives with accurate target identification. Beta-tubulin (BT) has been used as a target for anti-Acanthamoeba (A. keratitis). In this work, therefore, a model of the BT protein of A. keratitis was constructed by homology modeling utilizing the amino acid sequence from NCBI (GenBank: JQ417907.1). Ramachandran Plot was responsible for validating the protein PDB. The verified BT PDB was used for docking with the specified ligand. Based on an improved docking score compared to alpha-mangostin (AM), two modified compounds were identified: 1,6-dihydroxy-7-methoxy-2,8-bis(3-methylbut-2-en-1-yl)-9H-xanthen-9-one (C1) and 1,6-dihydroxy-2,8-bis(3-methylbut-2-en-1-yl)-9H-xanthen-9-one (C2). In addition, molecular dynamics simulations were conducted to analyze the interaction characteristics of the two bound BT–new compound complexes. During simulations, the TRP9, ARG50, VAL52, and GLN122 residues of BT-C1 that align to the identical residues in BT-AM generate consistent hydrogen bond interactions with 0–3 and 0–2. However, the BT-C2 complex has a different binding site, TYR 258, ILE 281, and SER 302, and can form more hydrogen bonds in the range 0–4. Therefore, this study reveals that C1 and C2 inhibit BT as an additive or synergistic effect; however, further in vitro and in vivo studies are needed. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Design II)

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15 pages, 5014 KiB

Open AccessArticle

Design of Novel IRAK4 Inhibitors Using Molecular Docking, Dynamics Simulation and 3D-QSAR Studies

by Swapnil P. Bhujbal, Weijie He and Jung-Mi Hah

Molecules 2022, 27(19), 6307; https://doi.org/10.3390/molecules27196307 - 24 Sep 2022

Cited by 4 | Viewed by 1936

Abstract

Treatment of several autoimmune diseases and types of cancer has been an intense area of research over the past two decades. Many signaling pathways that regulate innate and/or adaptive immunity, as well as those that induce overexpression or mutation of protein kinases, have been targeted for drug discovery. One of the serine/threonine kinases, Interleukin-1 Receptor Associated Kinase 4 (IRAK4) regulates signaling through various Toll-like receptors (TLRs) and interleukin-1 receptor (IL1R). It controls diverse cellular processes including inflammation, apoptosis, and cellular differentiation. MyD88 gain-of-function mutations or overexpression of IRAK4 has been implicated in various types of malignancies such as Waldenström macroglobulinemia, B cell lymphoma, colorectal cancer, pancreatic ductal adenocarcinoma, breast cancer, etc. Moreover, over activation of IRAK4 is also associated with several autoimmune diseases. The significant role of IRAK4 makes it an interesting target for the discovery and development of potent small molecule inhibitors. A few potent IRAK4 inhibitors such as PF-06650833, RA9 and BAY1834845 have recently entered phase I/II clinical trial studies. Nevertheless, there is still a need of selective inhibitors for the treatment of cancer and various autoimmune diseases. A great need for the same intrigued us to perform molecular modeling studies on 4,6-diaminonicotinamide derivatives as IRAK4 inhibitors. We performed molecular docking and dynamics simulation of 50 ns for one of the most active compounds of the dataset. We also carried out MM-PBSA binding free energy calculation to identify the active site residues, interactions of which are contributing to the total binding energy. The final 50 ns conformation of the most active compound was selected to perform dataset alignment in a 3D-QSAR study. Generated RF-CoMFA (q² = 0.751, ONC = 4, r² = 0.911) model revealed reasonable statistical results. Overall results of molecular dynamics simulation, MM-PBSA binding free energy calculation and RF-CoMFA model revealed important active site residues of IRAK4 and necessary structural properties of ligand to design more potent IRAK4 inhibitors. We designed few IRAK4 inhibitors based on these results, which possessed higher activity (predicted pIC₅₀) than the most active compounds of the dataset selected for this study. Moreover, ADMET properties of these inhibitors revealed promising results and need to be validated using experimental studies. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Design II)

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