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1.
Int J Mol Sci ; 22(9)2021 Apr 28.
Artigo em Inglês | MEDLINE | ID: mdl-33925236

RESUMO

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.


Assuntos
Desenho de Fármacos , Doenças Neurodegenerativas/tratamento farmacológico , Doença de Alzheimer , Esclerose Amiotrófica Lateral , Humanos , Doença de Huntington , Simulação de Acoplamento Molecular/métodos , Simulação de Acoplamento Molecular/tendências , Doença de Parkinson
2.
Molecules ; 26(6)2021 Mar 14.
Artigo em Inglês | MEDLINE | ID: mdl-33799356

RESUMO

The process of modern drug design would not exist in the current form without computational methods. They are part of every stage of the drug design pipeline, supporting the search and optimization of new bioactive substances. Nevertheless, despite the great help that is offered by in silico strategies, the power of computational methods strongly depends on the input data supplied at the stage of the predictive model construction. The studies on the efficiency of the computational protocols most often focus on global efficiency. They use general parameters that refer to the whole dataset, such as accuracy, precision, mean squared error, etc. In the study, we examined machine learning predictions obtained for opioid receptors (mu, kappa, delta) and focused on cases for which the predictions were the most accurate and the least accurate. Moreover, by using docking, we tried to explain prediction errors. We attempted to develop a rule of thumb, which can help in the prediction of compound activity towards opioid receptors via docking, especially those that have been incorrectly predicted by machine learning. We found out that although the combination of ligand- and structure-based path can be beneficial for the prediction accuracy, there still remain cases that cannot be reliably predicted by any available modeling method. In addition to challenging ligand- and structure-based predictions, we also examined the role of the application of machine-learning methods in comparison to simple statistical methods for both standard ligand-based representations (molecular fingerprints) and interaction fingerprints. All approaches were confronted in both classification (where compounds were assigned to the group of active and inactive group constructed on the basis of Ki values) and regression (where exact Ki value was predicted) experiments.


Assuntos
Receptores Opioides/metabolismo , Desenho de Fármacos , Ligantes , Aprendizado de Máquina , Simulação de Acoplamento Molecular/métodos
3.
Molecules ; 26(6)2021 Mar 16.
Artigo em Inglês | MEDLINE | ID: mdl-33809679

RESUMO

A series of novel coumarin-3-carboxamide derivatives were designed and synthesized to evaluate their biological activities. The compounds showed little to no activity against gram-positive and gram-negative bacteria but specifically showed potential to inhibit the growth of cancer cells. In particular, among the tested compounds, 4-fluoro and 2,5-difluoro benzamide derivatives (14b and 14e, respectively) were found to be the most potent derivatives against HepG2 cancer cell lines (IC50 = 2.62-4.85 µM) and HeLa cancer cell lines (IC50 = 0.39-0.75 µM). The activities of these two compounds were comparable to that of the positive control doxorubicin; especially, 4-flurobenzamide derivative (14b) exhibited low cytotoxic activity against LLC-MK2 normal cell lines, with IC50 more than 100 µM. The molecular docking study of the synthesized compounds revealed the binding to the active site of the CK2 enzyme, indicating that the presence of the benzamide functionality is an important feature for anticancer activity.


Assuntos
Cumarínicos/síntese química , Cumarínicos/farmacologia , Antibacterianos/síntese química , Antibacterianos/farmacologia , Antineoplásicos/síntese química , Antineoplásicos/farmacologia , Benzamidas/farmacologia , Linhagem Celular , Linhagem Celular Tumoral , Doxorrubicina/farmacologia , Bactérias Gram-Negativas/efeitos dos fármacos , Bactérias Gram-Positivas/efeitos dos fármacos , Células HeLa , Células Hep G2 , Humanos , Testes de Sensibilidade Microbiana/métodos , Simulação de Acoplamento Molecular/métodos
4.
Methods Mol Biol ; 2266: 39-72, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759120

RESUMO

The interaction between a protein and its ligands is one of the basic and most important processes in biological chemistry. Docking methods aim to predict the molecular 3D structure of protein-ligand complexes starting from coordinates of the protein and the ligand separately. They are widely used in both industry and academia, especially in the context of drug development projects. AutoDock4 is one of the most popular docking tools and, as for any docking method, its performance is highly system dependent. Knowledge about specific protein-ligand interactions on a particular target can be used to successfully overcome this limitation. Here, we describe how to apply the AutoDock Bias protocol, a simple and elegant strategy that allows users to incorporate target-specific information through a modified scoring function that biases the ligand structure towards those poses (or conformations) that establish selected interactions. We discuss two examples using different bias sources. In the first, we show how to steer dockings towards interactions derived from crystal structures of the receptor with different ligands; in the second example, we define and apply hydrophobic biases derived from Molecular Dynamics simulations in mixed solvents. Finally, we discuss general concepts of biased docking, its performance in pose prediction, and virtual screening campaigns as well as other potential applications.


Assuntos
Simulação de Acoplamento Molecular/métodos , Proteínas/química , Solventes/química , Sítios de Ligação , Cristalografia por Raios X , Quinase 2 Dependente de Ciclina/química , Interações Hidrofóbicas e Hidrofílicas , Ligantes , Conformação Molecular , Simulação de Dinâmica Molecular , Ligação Proteica , Software , Eletricidade Estática
5.
Vascul Pharmacol ; 138: 106856, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-33746069

RESUMO

COVID-19, a global-pandemic binds human-lung-ACE2. ACE2 causes vasodilatation. ACE2 works in balance with ACE1. The vaso-status maintains blood-pressure/vascular-health which is demolished in Covid-19 manifesting aldosterone/salt-deregulations/inflammations/endothelial-dysfunctions/hyper-hypo- tension, sepsis/hypovolemic-shock and vessel-thrombosis/coagulations. Here, nigellidine, an indazole-alkaloid was analyzed by molecular-docking for binding to different Angiotensin-binding-proteins (enzymes, ACE1(6en5)/ACE2(4aph)/receptors, AT1(6os1)/AT2(5xjm)) and COVID-19 spike-glycoprotein(6vsb). Nigellidine strongly binds to the spike-protein at the hinge-region/active-site-opening which may hamper proper-binding of nCoV2-ACE2 surface. Nigellidine effectively binds in the Angiotensin- II binding-site/entry-pocket (-7.54 kcal/mol, -211.76, Atomic-Contact-Energy; ACE-value) of ACE2 (Ki 8.68 and 8.3 µmol) in comparison to known-binder EGCG (-4.53) and Theaflavin-di-gallate (-2.85). Nigellidine showed strong-binding (Ki, 50.93 µmol/binding-energy -5.48 kcal/mol) to mono/multi-meric ACE1. Moreover, it binds Angiotensin-receptors, AT1/AT2 (Ki, 42.79/14.22 µmol, binding-energy, -5.96/-6.61 kcal/mol) at active-sites, respectively. This article reports the novel binding of nigellidine and subsequent blockage of angiotensin-binding proteins. The ACEs-blocking could restore Angiotensin-level, restrict vaso-turbulence in Covid patients and receptor-blocking might stop inflammatory/vascular impairment. Nigellidine may slowdown the vaso-fluctuations due to Angiotensin-deregulations in Covid patients. Angiotensin II-ACE2 binding (ACE-value -294.81) is more favorable than nigellidine-ACE2. Conversely, nigellidine-ACE1 binding-energy/Ki is lower than nigellidine-ACE2 values indicating a balanced-state between constriction-dilatation. Moreover, nigellidine binds to the viral-spike, closer-proximity to its ACE2 binding-domain. Taken together, Covid patients/elderly-patients, comorbid-patients (with hypertensive/diabetic/cardiac/renal-impairment, counting >80% of non-survivors) could be greatly benefited.


Assuntos
/metabolismo , Nigella sativa , Peptidil Dipeptidase A/metabolismo , Extratos Vegetais/metabolismo , Receptor Tipo 1 de Angiotensina/metabolismo , Receptor Tipo 2 de Angiotensina/metabolismo , /química , /prevenção & controle , Comorbidade , Simulação por Computador/tendências , Avaliação Pré-Clínica de Medicamentos/métodos , Humanos , Simulação de Acoplamento Molecular/métodos , Peptidil Dipeptidase A/química , Extratos Vegetais/isolamento & purificação , Extratos Vegetais/uso terapêutico , Ligação Proteica/fisiologia , Estrutura Secundária de Proteína , Estrutura Terciária de Proteína , Receptor Tipo 1 de Angiotensina/química , Receptor Tipo 2 de Angiotensina/química , /metabolismo
6.
Int J Mol Sci ; 22(4)2021 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-33669738

RESUMO

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious global health threat. Since no specific therapeutics are available, researchers around the world screened compounds to inhibit various molecular targets of SARS-CoV-2 including its main protease (Mpro) essential for viral replication. Due to the high urgency of these discovery efforts, off-target binding, which is one of the major reasons for drug-induced toxicity and safety-related drug attrition, was neglected. Here, we used molecular docking, toxicity profiling, and multiple molecular dynamics (MD) protocols to assess the selectivity of 33 reported non-covalent inhibitors of SARS-CoV-2 Mpro against eight proteases and 16 anti-targets. The panel of proteases included SARS-CoV Mpro, cathepsin G, caspase-3, ubiquitin carboxy-terminal hydrolase L1 (UCHL1), thrombin, factor Xa, chymase, and prostasin. Several of the assessed compounds presented considerable off-target binding towards the panel of proteases, as well as the selected anti-targets. Our results further suggest a high risk of off-target binding to chymase and cathepsin G. Thus, in future discovery projects, experimental selectivity assessment should be directed toward these proteases. A systematic selectivity assessment of SARS-CoV-2 Mpro inhibitors, as we report it, was not previously conducted.


Assuntos
Antivirais/química , Antivirais/farmacologia , Inibidores de Proteases/química , Inibidores de Proteases/farmacologia , /efeitos dos fármacos , /enzimologia , /química , Descoberta de Drogas/métodos , Humanos , Simulação de Acoplamento Molecular/métodos , Peptídeo Hidrolases/química , Peptídeo Hidrolases/metabolismo , /enzimologia
7.
Chem Biol Interact ; 340: 109453, 2021 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-33785314

RESUMO

Gut bacterial ß-glucuronidase (GUS) plays a pivotal role in the metabolism and reactivation of a vast of glucuronide conjugates of both endogenous and xenobiotic compounds in the gastrointestinal tract of human, which has been implicated in certain drug-induced gastrointestinal tract (GI) toxicity in clinic. Inhibitors of gut microbial GUS exhibited great potentials in relieving the drug-induced GI toxicity. In this study, Selaginella tamariscina and its major biflavonoid amentoflavone (AMF) were evaluated for their inhibitory activity against Escherichia coli GUS. Two selective probe substrates for GUS (a specific fluorescent probe substrate for GUS, DDAOG and a classical drug substrate for GUS, SN38G) were used in parallel for charactering the inhibition behaviors. Both the extract of S. tamariscina and its major biflavonoid AMF displayed evident inhibitory effects on GUS, and the IC50 values of AMF against GUS mediated DDAOG and SN-38G hydrolysis were 0.62 and 0.49 µM, respectively. Inhibition kinetics studies indicated that AMF showed mixed type inhibition for GUS-mediated DDAOG hydrolysis, while displayed competitive type inhibition against GUS-mediated SN-38G hydrolysis, with the Ki values of 0.24 and 1.25 µM, respectively. Molecular docking studies and molecular dynamics stimulation results clarified the role of amino acid residues Leu361, Ile363, and Glu413 in the inhibition of AMF on GUS. These results provided some foundations for the potential clinical utility of S. tamariscina and its major biflavonoid AMF for treating drug-induced enteropathy.


Assuntos
Biflavonoides/farmacologia , Microbioma Gastrointestinal/efeitos dos fármacos , Glucuronidase/antagonistas & inibidores , Selaginellaceae/química , Aminoácidos/metabolismo , Bactérias/efeitos dos fármacos , Bactérias/metabolismo , Escherichia coli/efeitos dos fármacos , Escherichia coli/metabolismo , Trato Gastrointestinal/microbiologia , Glucuronídeos/metabolismo , Hidrólise/efeitos dos fármacos , Cinética , Simulação de Acoplamento Molecular/métodos , Simulação de Dinâmica Molecular
8.
Int J Mol Sci ; 22(4)2021 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-33672042

RESUMO

The interactions of epoxiconazole and prothioconazole with human serum albumin and bovine serum albumin were investigated using spectroscopic methods complemented with molecular modeling. Spectroscopic techniques showed the formation of pesticide/serum albumin complexes with the static type as the dominant mechanism. The association constants ranged from 3.80 × 104-6.45 × 105 L/mol depending on the pesticide molecule (epoxiconazole, prothioconazole) and albumin type (human or bovine serum albumin). The calculated thermodynamic parameters revealed that the binding of pesticides into serum albumin macromolecules mainly depended on hydrogen bonds and van der Waals interactions. Synchronous fluorescence spectroscopy and the competitive experiments method showed that pesticides bind to subdomain IIA, near tryptophan; in the case of bovine serum albumin also on the macromolecule surface. Concerning prothioconazole, we observed the existence of an additional binding site at the junction of domains I and III of serum albumin macromolecules. These observations were corroborated well by molecular modeling predictions. The conformation changes in secondary structure were characterized by circular dichroism, three-dimensional fluorescence, and UV/VIS absorption methods.


Assuntos
Compostos de Epóxi/química , Simulação de Acoplamento Molecular/métodos , Praguicidas/química , Soroalbumina Bovina/química , Albumina Sérica Humana/química , Triazóis/química , Animais , Sítios de Ligação , Bovinos , Dicroísmo Circular/métodos , Humanos , Ligação de Hidrogênio , Interações Hidrofóbicas e Hidrofílicas , Ligação Proteica , Estrutura Secundária de Proteína , Espectrometria de Fluorescência/métodos , Eletricidade Estática , Temperatura
9.
Cancer Sci ; 112(5): 1772-1784, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33682294

RESUMO

Traditional Chinese medicine treatment of diseases has been recognized, but the material basis and mechanisms are not clear. In this study, target prediction of the antigastric cancer (GC) effect of Guiqi Baizhu (GQBZP) and the analysis of potential key compounds, key targets, and key pathways for the therapeutic effects against GC were carried out based on the method of network analysis and Kyoto Encyclopedia of Genes and Genomes enrichment. There were 33 proteins shared between GQBZP and GC, and 131 compounds of GQBZP had a high correlation with these proteins, indicating that the PI3K-AKT signaling pathway might play a key role in GC. From these studies, we selected human epidermal growth factor receptor 2 (HER2) and programmed cell death 1-ligand 1 (PD-L1) for docking; the results showed that 385 and 189 compounds had high docking scores with HER2 and PD-L1, respectively. Six compounds were selected for microscale thermophoresis (MST). Daidzein/quercetin and isorhamnetin/formononetin had the highest binding affinity for HER2 and PD-L1, with Kd values of 3.7 µmol/L and 490, 667, and 355 nmol/L, respectively. Molecular dynamics simulation studies based on the docking complex structures as the initial conformation yielded the binding free energy between daidzein/quercetin with HER2 and isorhamnetin/formononetin with PD-L1, calculated by molecular mechanics Poisson-Boltzmann surface area, of -26.55, -14.18, -19.41, and -11.86 kcal/mol, respectively, and were consistent with the MST results. In vitro experiments showed that quercetin, daidzein, and isorhamnetin had potential antiproliferative effects in MKN-45 cells. Enzyme activity assays showed that quercetin could inhibit the activity of HER2 with an IC50 of 570.07 nmol/L. Our study provides a systematic investigation to explain the material basis and molecular mechanism of traditional Chinese medicine in treating diseases.


Assuntos
Antígeno B7-H1/metabolismo , Medicamentos de Ervas Chinesas/metabolismo , Proteínas de Neoplasias/metabolismo , Receptor ErbB-2/metabolismo , Neoplasias Gástricas/metabolismo , Antígeno B7-H1/química , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Medicamentos de Ervas Chinesas/uso terapêutico , Humanos , Isoflavonas/metabolismo , Isoflavonas/farmacologia , Simulação de Acoplamento Molecular/métodos , Proteínas de Neoplasias/química , Fosfatidilinositol 3-Quinases/metabolismo , Estrutura Quaternária de Proteína , Estrutura Terciária de Proteína , Proteínas Proto-Oncogênicas c-akt/metabolismo , Quercetina/análogos & derivados , Quercetina/metabolismo , Quercetina/farmacologia , Receptor ErbB-2/antagonistas & inibidores , Receptor ErbB-2/química , Transdução de Sinais , Neoplasias Gástricas/tratamento farmacológico
10.
Methods Mol Biol ; 2266: 73-88, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759121

RESUMO

The mechanism of action of covalent drugs involves the formation of a bond between their electrophilic warhead group and a nucleophilic residue of the protein target. The recent advances in covalent drug discovery have accelerated the development of computational tools for the design and characterization of covalent binders. Covalent docking algorithms can predict the binding mode of covalent ligands by modeling the bonds and interactions formed at the reaction site. Their scoring functions can estimate the relative binding affinity of ligands towards the target of interest, thus allowing virtual screening of compound libraries. However, most of the scoring schemes have no specific terms for the bond formation, and therefore it prevents the direct comparison of warheads with different intrinsic reactivity. Herein, we describe a protocol for the binding mode prediction of covalent ligands, a typical virtual screening of compound sets with a single warhead chemistry, and an alternative approach to screen libraries that include various warhead types, as applied in recently validated studies.


Assuntos
Química Computacional/métodos , Descoberta de Drogas/métodos , Simulação de Acoplamento Molecular/métodos , Proteínas/química , Algoritmos , Sítios de Ligação , Bases de Dados de Proteínas , Ligantes , Modelos Moleculares , Conformação Molecular , Ligação Proteica , Proteínas Proto-Oncogênicas p21(ras)/antagonistas & inibidores , Proteínas Proto-Oncogênicas p21(ras)/química , Software , Relação Estrutura-Atividade
11.
Methods Mol Biol ; 2266: 89-104, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759122

RESUMO

In silico rational drug design is one of the major pylons in the drug discovery process. Drugs usually act on specific targets such as proteins, DNA, and lipid bilayers. Thus, molecular docking is an essential part of the rational drug design process. Molecular docking uses specific algorithms and scoring functions to reveal the strength of the interaction of the ligand to its target. AutoDock is a molecular docking suite that offers a variety of algorithms to tackle specific problems. These algorithms include Monte Carlo Simulated Annealing (SA), a Genetic Algorithm (GA), and a hybrid local search GA, also known as the Lamarckian Genetic Algorithm (LGA). This chapter aims to acquaint the reader with the docking process using AutoDockTools (GUI of AutoDock). Furthermore, herein is described the docking process of calf thymus DNA with three metal complexes, as a potential metallo-therapeutics as also the docking process of the plant flavonoid quercetin to the antiapoptotic protein BcL-xL.


Assuntos
DNA/química , Descoberta de Drogas/métodos , Metais/química , Simulação de Acoplamento Molecular/métodos , Proteínas/química , Algoritmos , Simulação por Computador , Desenho de Fármacos , Ligantes , Ligação Proteica , Quercetina/química , Software , Proteína bcl-X/química
12.
Methods Mol Biol ; 2266: 105-124, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759123

RESUMO

Interactions between enzymes and small molecules lie in the center of many fundamental biochemical processes. Their analysis using molecular dynamics simulations have high computational demands, geometric approaches fail to consider chemical forces, and molecular docking offers only static information. Recently, we proposed to combine molecular docking and geometric approaches in an application called CaverDock. CaverDock is discretizing enzyme tunnel into discs, iteratively docking with restraints into one disc after another and searching for a trajectory of the ligand passing through the tunnel. Here, we focus on the practical side of its usage describing the whole method: from getting the application, and processing the data through a workflow, to interpreting the results. Moreover, we shared the best practices, recommended how to solve the most common issues, and demonstrated its application on three use cases.


Assuntos
Descoberta de Drogas/métodos , Simulação de Acoplamento Molecular/métodos , Proteínas/química , Ácido Araquidônico/química , Sítios de Ligação , Cloridrinas/química , Sistema Enzimático do Citocromo P-450/química , Desenho de Fármacos , Etanol/análogos & derivados , Etanol/química , Dibrometo de Etileno/química , Hidrolases/química , Ligantes , Simulação de Dinâmica Molecular , Ligação Proteica , Software , Relação Estrutura-Atividade , Termodinâmica
13.
Methods Mol Biol ; 2266: 125-140, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759124

RESUMO

Rational drug discovery relies heavily on molecular docking-based virtual screening, which samples flexibly the ligand binding poses against the target protein's structure. The upside of flexible docking is that the geometries of the generated docking poses are adjusted to match the residue alignment inside the target protein's ligand-binding pocket. The downside is that the flexible docking requires plenty of computing resources and, regardless, acquiring a decent level of enrichment typically demands further rescoring or post-processing. Negative image-based screening is a rigid docking technique that is ultrafast and computationally light but also effective as proven by vast benchmarking and screening experiments. In the NIB screening, the target protein cavity's shape/electrostatics is aligned and compared against ab initio-generated ligand 3D conformers. In this chapter, the NIB methodology is explained at the practical level and both its weaknesses and strengths are discussed candidly.


Assuntos
Descoberta de Drogas/métodos , Simulação de Acoplamento Molecular/métodos , Proteínas/química , Algoritmos , Sítios de Ligação , Cristalografia por Raios X , Ciclo-Oxigenase 2/química , Bases de Dados de Proteínas , Ligantes , Modelos Moleculares , Conformação Molecular , Ligação Proteica , Curva ROC , Bibliotecas de Moléculas Pequenas/química , Software , Eletricidade Estática , Interface Usuário-Computador
14.
Methods Mol Biol ; 2266: 141-154, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759125

RESUMO

Molecular docking produces often lackluster results in real-life virtual screening assays that aim to discover novel drug candidates or hit compounds. The problem lies in the inability of the default docking scoring to properly estimate the Gibbs free energy of binding, which impairs the recognition of the best binding poses and the separation of active ligands from inactive compounds. Negative image-based rescoring (R-NiB) provides both effective and efficient way for re-ranking the outputted flexible docking poses to improve the virtual screening yield. Importantly, R-NiB has been shown to work with multiple genuine drug targets and six popular docking algorithms using demanding benchmark test sets. The effectiveness of the R-NiB methodology relies on the shape/electrostatics similarity between the target protein's ligand-binding cavity and the docked ligand poses. In this chapter, the R-NiB method is described with practical usability in mind.


Assuntos
Descoberta de Drogas/métodos , Simulação de Acoplamento Molecular/métodos , Proteínas/química , Algoritmos , Área Sob a Curva , Sítios de Ligação , Cristalografia por Raios X , Ciclo-Oxigenase 2/química , Bases de Dados de Proteínas , Ligantes , Conformação Molecular , Neuraminidase/química , Ligação Proteica , Software , Eletricidade Estática
15.
Methods Mol Biol ; 2266: 155-170, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759126

RESUMO

Medicinal chemistry society has enough arguments to justify the usage of fragment-based drug design (FBDD) methodologies for the identification of lead compounds. Since the FDA approval of three kinase inhibitors - vemurafenib, venetoclax, and erdafitinib, FBDD has become a challenging alternative to high-throughput screening methods in drug discovery. The following protocol presents in silico drug design of selective histone deacetylase 6 (HDAC6) inhibitors through a fragment-based approach. To date, structural motifs that are important for HDAC inhibitory activity and selectivity are described as: surface recognition group (CAP group), aliphatic or aromatic linker, and zinc-binding group (ZBG). The main idea of this FBDD method is to identify novel and target-selective CAP groups by virtual scanning of publicly available fragment databases. Template structure used to search for novel heterocyclic and carbocyclic fragments is 1,8-naphthalimide (CAP group of scriptaid, a potent HDAC inhibitor). Herein, the design of HDAC6 inhibitors is based on linking the identified fragments with the aliphatic or aromatic linker and hydroxamic acid (ZBG) moiety. Final selection of potential selective HDAC6 inhibitors is based on combined structure-based (molecular docking) and ligand-based (three-dimensional quantitative structure-activity relationships, 3D-QSAR) techniques. Designed compounds are docked in the active site pockets of human HDAC1 and HDAC6 isoforms, and their docking conformations used to predict their HDAC inhibitory and selectivity profiles through two developed 3D-QSAR models (describing HDAC1 and HDAC6 inhibitory activities).


Assuntos
Descoberta de Drogas/métodos , Desacetilase 6 de Histona/química , Inibidores de Histona Desacetilases/química , Simulação de Acoplamento Molecular/métodos , Naftalimidas/química , Motivos de Aminoácidos , Domínio Catalítico , Bases de Dados de Compostos Químicos , Desenho de Fármacos , Histona Desacetilase 1/antagonistas & inibidores , Histona Desacetilase 1/química , Desacetilase 6 de Histona/antagonistas & inibidores , Técnicas In Vitro , Ligantes , Conformação Molecular , Simulação de Dinâmica Molecular , Relação Quantitativa Estrutura-Atividade , Bibliotecas de Moléculas Pequenas , Relação Estrutura-Atividade
16.
Methods Mol Biol ; 2266: 187-202, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759128

RESUMO

Multicanonical molecular dynamics (McMD)-based dynamic docking has been applied to predict the native binding configurations for several protein receptors and their ligands. Due to the enhanced sampling capabilities of McMD, it can exhaustively sample bound and unbound ligand configurations, as well as receptor conformations, and thus enables efficient sampling of the conformational and configurational space, not possible using canonical MD simulations. As McMD samples a wide configurational space, extensive analysis is required to study the diverse ensemble consisting of bound and unbound structures. By projecting the reweighted ensemble onto the first two principal axes obtained via principal component analysis of the multicanonical ensemble, the free energy landscape (FEL) can be obtained. Further analysis produces representative structures positioned at the local minima of the FEL, where these structures are then ranked by their free energy. In this chapter, we describe our dynamic docking methodology, which has successfully reproduced the native binding configuration for small compounds, medium-sized compounds, and peptide molecules.


Assuntos
Anticorpos/química , Simulação de Acoplamento Molecular/métodos , Simulação de Dinâmica Molecular , Peptídeos/química , Proteínas/química , Secretases da Proteína Precursora do Amiloide/química , Anticorpos Monoclonais Humanizados/química , Ácido Aspártico Endopeptidases/química , Quinase 2 Dependente de Ciclina/química , Bases de Dados de Proteínas , Ligantes , Modelos Moleculares , Conformação Molecular , Análise de Componente Principal , Ligação Proteica , Temperatura
17.
Methods Mol Biol ; 2266: 263-277, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759132

RESUMO

Although science and technology have progressed rapidly, de novo drug development has been a costly and time-consuming process over the past decades. In this scenario, drug repurposing has appeared as an alternative tool to accelerate the drug development process. Herein, we applied such an approach to the highly popular human Carbonic Anhydrase (hCA) VA drug target, that is involved in ureagenesis, gluconeogenesis, lipogenesis, and in the metabolism regulation. Albeit several hCA inhibitors have been designed and are currently in clinical use, serious drug interactions have been reported due to their poor selectivity. In this perspective, the drug repurposing approach could be a useful tool for investigating the drug promiscuity/polypharmacology profile. In this chapter, we describe a combination of virtual screening techniques and in vitro assays aimed to identify novel selective hCA VA inhibitors and to repurpose drugs known for other clinical indications.


Assuntos
Fármacos Antiobesidade/química , Inibidores da Anidrase Carbônica/química , Reposicionamento de Medicamentos/métodos , Simulação de Acoplamento Molecular/métodos , Desenho de Fármacos , Técnicas In Vitro , Ligantes , Modelos Químicos , Simulação de Dinâmica Molecular , Estrutura Molecular , Bibliotecas de Moléculas Pequenas , Software , Relação Estrutura-Atividade
18.
Methods Mol Biol ; 2266: 313-322, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33759135

RESUMO

Molecular docking is commonly used for identification of drug candidates targeting a specified protein of known structure. With the increasing emphasis on drug repurposing over recent decades, molecular inverse docking has been widely applied to prediction of the potential protein targets of a specified molecule. In practice, inverse docking has many advantages, including early supervision of drugs' side effects and toxicity. MDock developed from our laboratory is a protein-ligand docking software based on a knowledge-based scoring function and has numerous applications to lead identification. In addition to its computational efficiency on ensemble docking for multiple protein conformations, MDock is well suited for inverse docking. In this chapter, we focus on introducing the protocol of inverse docking with MDock. For academic users, the MDock package is freely available at http://zoulab.dalton.missouri.edu/mdock.htm .


Assuntos
Desenho de Fármacos , Simulação de Acoplamento Molecular/métodos , Proteínas/química , Software , Sítios de Ligação , Bases de Dados de Proteínas , Técnicas In Vitro , Ligantes , Progesterona/química , Ligação Proteica , Conformação Proteica
19.
Biomed Res Int ; 2021: 1596834, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33728324

RESUMO

Background: Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2. Methods: In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis. Results: The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant. Conclusion: Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2.


Assuntos
/imunologia , Imunogenicidade da Vacina/imunologia , Vacinas de Subunidades/imunologia , Sequência de Aminoácidos , Epitopos de Linfócito B/imunologia , Epitopos de Linfócito T/imunologia , Humanos , Simulação de Acoplamento Molecular/métodos
20.
Sci Rep ; 11(1): 5543, 2021 03 10.
Artigo em Inglês | MEDLINE | ID: mdl-33692377

RESUMO

The COVID-19 caused by the SARS-CoV-2 virus was declared a pandemic disease in March 2020 by the World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and drug repurposing to find effective treatments against this disease. In this work, we present the developments implemented in the DockThor-VS web server to provide a virtual screening (VS) platform with curated structures of potential therapeutic targets from SARS-CoV-2 incorporating genetic information regarding relevant non-synonymous variations. The web server facilitates repurposing VS experiments providing curated libraries of currently available drugs on the market. At present, DockThor-VS provides ready-for-docking 3D structures for wild type and selected mutations for Nsp3 (papain-like, PLpro domain), Nsp5 (Mpro, 3CLpro), Nsp12 (RdRp), Nsp15 (NendoU), N protein, and Spike. We performed VS experiments of FDA-approved drugs considering the therapeutic targets available at the web server to assess the impact of considering different structures and mutations to identify possible new treatments of SARS-CoV-2 infections. The DockThor-VS is freely available at www.dockthor.lncc.br .


Assuntos
/tratamento farmacológico , Desenho de Fármacos , Reposicionamento de Medicamentos/métodos , Antivirais/farmacologia , Humanos , Internet , Simulação de Acoplamento Molecular/métodos , Pandemias , /patogenicidade
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