Application Of Molecular Docking Research Articles

Identify of promising isoquinolone JNK1 inhibitors by combined application of 3D-QSAR, molecular docking and molecular dynamics simulation approaches

JNK1 has been suggested to play a key mediator in metabolic disorders, especially been considered to be a drug target for treatment of type-2 diabetes in recent years. Therefore, inhibiting the activity of JNK1 is a promising way for drug development. In the study, in order to design and identify the potential compounds targeting JNK1, a series of isoquinolone analogs were used to develop 3D-QSAR models. Here, two methods of docking-based and minimization-based were adopted for generation of molecular poses and the subsequent model construction. CoMFA model #5 and CoMSIA model #6 based on docking method were selected due to their informative and satisfactory internal and external validation results. An in-house library containing 113 new designs was built based on contour maps analyzes and then designated for screening. Compound 20JX82 was focused for its preferable predicted activity and docking score. Detailed interactions with JNK1 of compound 20JX82 was investigated via deep analyze of docking results and molecular dynamics simulation. Strong interactions and extra hydrogen bonds which were consistent with the summarized design principles were observed. From MD analyzes, greater stability of the 20JX82 bound complex was found when using sole protein as reference. Thus, compound 20JX82 was successfully identified as promising JNK1 inhibitor.

Binding properties of marine bromophenols with human protein tyrosine phosphatase 1B: Molecular docking, surface plasmon resonance and cellular insulin resistance study

Protein tyrosine phosphatase 1B (PTP1B) is a highly validated target for the treatment of type 2 diabetes and obesity. Previous studies have shown that bromophenols from marine red alga Rhodomela confervoides can inhibit PTP1B activity. However, traditional in vitro enzymatic assays may result in false positive activity. Here, we reported a successful application of molecular docking and surface plasmon resonance (SPR) assay for the characterization of small-molecule PTP1B inhibitors with high affinity. First, molecular docking study indicated that six bromophenol compounds preferred to bind PTP1B with open conformation rather than one with closed conformation. Next, SPR study indicated that compound 3 was the most potent and stable PTP1B inhibitor at the nanomolar level. Then Lineweaver–Burk plot data showed that compound 3 was a competitive PTP1B inhibitor. Moreover, compound 3 could improve palmitate-induced insulin resistance in HepG2 cells. Taken together, molecular docking and SPR-based methodology could apply in the development of PTP1B inhibitors with high affinity.

Application of Molecular Docking for the Development of Improved HIV-1 Reverse Transcriptase Inhibitors

Inhibition of the reverse transcriptase (RT) enzyme of the human immunodeficiency virus (HIV) by low molecular weight inhibitors is still an active area of research. Here, protein-ligand interactions and possible binding modes of novel compounds with the HIV-1 RT binding pocket (the wild-type as well as Y181C and K103N mutants) were obtained and discussed. A molecular fragment-based approach using FDA-approved drugs were followed to design novel chemical derivatives using delavirdine, efavirenz, etravirine and rilpivirine as the scaffolds. The drug-likeliness of the derivatives was evaluated using Swiss-ADME. The parent molecule and derivatives were then docked into the binding pocket of related crystal structures (PDB ID: 4G1Q, 1IKW, 1KLM and 3MEC). Genetic Optimization for Ligand Docking (GOLD) Suite 5.2.2 software was used for docking and the results analyzed in the Discovery Studio Visualizer 4. A derivative was chosen for further analysis, if it passed drug-likeliness and the docked energy was more favorable than that of its parent molecule. Out of the fifty-seven derivatives, forty-eight failed in drug-likeness screening by Swiss-ADME or at the docking stage. The final results showed that the selected compounds had higher predicted binding affinities than their parent scaffolds in both wild-type and the mutants. Binding energy improvement was higher for the structures designed based on second-generation NNRTIs (etravirine and rilpivirine) than the first-generation NNRTIs (delavirdine and efavirenz). For example, while the docked energy for rilpivirine was -51 KJ/mol, it was improved for its derivatives RPV01 and RPV15 up to - 58.3 and -54.5 KJ/mol, respectively. In this study, we have identified and proposed some novel molecules with improved binding capacity for HIV RT using a fragment-based approach.

Ayurveda and Siddha systems polyherbal formulations to treat COVID-19 caused by SARS-CoV-2 and brief insight on application of Molecular Docking and SWISS Target prediction tools to study efficacy of active molecules

Ayurveda and Siddha systems are the two ancient medical systems originated in India more than 4000 years ago had given many formulary and treatment methods against influenza like infections. Kabasura churan from Siddha system and Maha sudharshan churan from the Ayurvedic system are the two major formulations along with many other individual herbs mentioned in the texts to treat Influenza like infections. Kabasura churan and Maha Sudarshan churan both have antipyretic, analgesic and anti-inflammatory effects. Both formulations were prepared according to Siddha and Ayurvedic texts. Herbs mentioned in both formulations like Turmeric, Tulsi (Basil), Kalmegh (Andrographis), Black Pepper, Liquorice (Mulethi), and Dronapushpi (Leucas) etc., had direct antiviral effect. Herbs like Aswagandha, Ginger, Guduchi (Tinospora), Kulanjan (Galangal) etc., had immunomodulatory and anti-inflammatory effect. Active compounds from different herbs were selected to study their antiviral activity through molecular docking algorithm. Application of modern of tools like Bioinformatics and Highthroughput screening methods can predict the efficacy of the ancient documented formulations and can be compared as per their literature. Compounds like curcumin, Glycyrrhizin, Ursolic acid, Quercetin, Andrographolide, Coumarins etc. were showed polyspecific activity like inhibition of Spike protein, Furin, Main Protease (Mpro) and Papain like Proteases (PLpro). Thus we propose use of Kabasura churan and Maha Sudharshan churan as alternative complementary medicine as a palliative treatment against COVID-19 caused by SARS-CoV-2 by conducting proper Randomized Clinical Trials

Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App

The drug discovery process involves several tasks to be performed in vivo, in vitro and in silico. Molecular docking is a task typically performed in silico. It aims at finding the three-dimensional pose of a given molecule when it interacts with the target protein binding site. This task is often done for virtual screening a huge set of molecules to find the most promising ones, which will be forwarded to the later stages of the drug discovery process. Given the huge complexity of the problem, molecular docking cannot be solved by exploring the entire space of the ligand poses. State-of-the-art approaches face the problem by sampling the space of the ligand poses to generate results in a reasonable time budget. In this work, we improve the geometric approach to molecular docking by introducing tunable approximations. In particular, we analysed and enriched the original implementation with tunable software knobs to explore and control the performance-accuracy trade-offs. We modelled time-to-solution of the virtual screening task as a function of software knobs, input data features, and available computational resources. Therefore, the application can autotune its configuration according to a user-defined time budget. We used a Mini-App derived by LiGenDock—a state-of-the-art molecular docking application—to validate the proposed approach. We run the enhanced Mini-App on a high-performance computing system by using a very large database of pockets and ligands. The proposed approach exposes a time-to-solution interval spanning more than one order of magnitude with accuracy degradation up to 30%, more in general providing different accuracy levels according to the needs of the virtual screening campaign.

AhR Agonist Activity Confirmation of Polyhalogenated Carbazoles (PHCZs) Using an Integration of in Vitro, in Vivo, and in Silico Models.

Polyhalogenated carbazoles (PHCZs) are a kind of rising environmental pollutant that has been reported to pose high risk to human beings and the natural environment. PHCZs are of a similar molecular structure with of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and exhibited some dioxin-like toxicity. Dioxin-like compounds (DLCs) are banned by the Stockholm Convention due to their potential adverse impacts to the environment and public health. However, a few efforts have been made toward the regulation of PHCZs. Herein, we initiated multimodels to systematically determine and validate the dioxin-like effects of PHCZs on a large scale. Transgenic zebrafish line-Tg(cyp1a-12DRE:EGFP) and stably transfected HepG2 cell line with luciferase reporter plasmids were used to screen and evaluate the aryl hydrocarbon receptor (AhR) agonist effects of the target PHCZs, which were then verified by application of molecular docking and expression levels of AhR downstream genes. Results of the two bioassays showed that most of the tested PHCZs could pose dioxin-like AhR agonist effects, change the expression levels of AhR downstream genes, and interact with AhR in accordance with TCDD. In summary, data presented here can help to guide the safe use and regulation of PHCZs.

Characterization of new Pt(IV)–thiazole complexes: Analytical, spectral, molecular modeling and molecular docking studies and applications in two opposing pathways

New thiazole derivatives were synthesized and fully characterized, then coordinated with PtCl4 salt. Also, the newly synthesized Pt(IV) complexes were investigated analytically (elemental and thermogravimetric analyses), spectrally (infrared, UV–visible, mass, 1H NMR, 13C NMR, X‐ray diffraction) as well as theoretically (kinetics, modeling and docking). The data extracted led to the establishment of the best chemical and structural forms. Octahedral geometry was the only formula proposed for all complexes, which is favorable for d6 systems. The molecular ion peaks from mass spectral analysis coincide with all analytical data, confirming the molecular formula proposed. X‐ray diffraction (XRD) and scanning electron microscopy (SEM) allowed discrimination of features between crystalline particles and other amorphous morphology. By applying Gaussian09 as well as HyperChem 8.2 programs, the best structural forms were obtained, as well as computed significant parameters. Computed parameters such as softness, hardness, surface area and reactivity led us towards application in two opposing pathways: tumor inhibition and oxidation activation. The catalytic oxidation for CO was conducted over PtO2, which was yielded from calcination of the most reactive complex. The success of catalytic role for synthesized PtO2 was due to its particulate size and surface morphology, which were estimated from XRD patterns and SEM images, respectively. The antitumor activity was tested versus HCT‐116 and HepG‐2 cell lines. Mild toxicity was recorded for two of the derivatives and their corresponding complexes. This degree of toxicity is more favorable in most cases, due to exclusion of serious side effects, which is coherently attached with known antitumor drugs.

Corrigendum: Regioselective Synthesis, Antibacterial, Molecular Docking and Fingerprint Applications of 1‐Benzhydrylpiperazine Derivatized 1,4‐Disubstituted 1,2,3‐Triazoles

ChemistrySelectVolume 4, Issue 23 p. 6887-6887 CorrigendumFree Access Corrigendum: Regioselective Synthesis, Antibacterial, Molecular Docking and Fingerprint Applications of 1-Benzhydrylpiperazine Derivatized 1,4-Disubstituted 1,2,3-Triazoles This article corrects the following: Regioselective Synthesis, Antibacterial, Molecular Docking and Fingerprint Applications of 1-Benzhydrylpiperazine Derivatized 1,4-Disubstituted 1,2,3-Triazoles Shivaraja Govindaiah Swamy Sreenivasa Ramesha Andagar Ramakrishna Tadimety Madhu Chakrapani Rao Hanumanthappa Nagabhushana Volume 3Issue 28ChemistrySelect pages: 8111-8117 First Published online: July 25, 2018 Shivaraja Govindaiah, Search for more papers by this authorDr. Swamy Sreenivasa, Search for more papers by this authorDr. Ramesha Andagar Ramakrishna, Search for more papers by this authorTadimety Madhu Chakrapani Rao, Search for more papers by this authorProf. Hanumanthappa Nagabhushana, Search for more papers by this author Shivaraja Govindaiah, Search for more papers by this authorDr. Swamy Sreenivasa, Search for more papers by this authorDr. Ramesha Andagar Ramakrishna, Search for more papers by this authorTadimety Madhu Chakrapani Rao, Search for more papers by this authorProf. Hanumanthappa Nagabhushana, Search for more papers by this author First published: 18 June 2019 https://doi.org/10.1002/slct.201902075AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume4, Issue23June 21, 2019Pages 6887-6887 RelatedInformation

Exploiting OpenMP and OpenACC to accelerate a geometric approach to molecular docking in heterogeneous HPC nodes

In drug discovery, molecular docking is the task in charge of estimating the position of a molecule when interacting with the docking site. This task is usually used to perform screening of a large library of molecules, in the early phase of the process. Given the amount of candidate molecules and the complexity of the application, this task is usually performed using high-performance computing (HPC) platforms. In modern HPC systems, heterogeneous platforms provide a better throughput with respect to homogeneous platforms. In this work, we ported and optimized a molecular docking application to a heterogeneous system, with one or more GPU accelerators, leveraging a hybrid OpenMP and OpenACC approach. The target application focuses on the virtual screening phases in the drug discovery process, and it is based on geometric transformations of the target ligands. We prove that our approach has a better exploitation of the node compared to pure CPU/GPU data splitting approaches, reaching a throughput improvement up to 25% while considering the same computing node.

Development and design of novel cardiovascular therapeutics based on Rho kinase inhibition—In silico approach

Rho kinases, one of the best-known members of the serine/threonine (Ser/Thr) protein kinase family, can be used as target enzymes for the treatment of many diseases such as cancer or multiple sclerosis, and especially for the treatment of cardiovascular diseases. This study presents QSAR modeling for a series of 41 chemical compounds as Rho kinase inhibitors based on the Monte Carlo method. QSAR models were developed for three random splits into the training and test set. Molecular descriptors used for QSAR modeling were based on the SMILES notation and local invariants of the molecular graph. The statistical quality of the developed model, including robustness and predictability, was tested with different statistical approaches and satisfying results were obtained. The best calculated QSAR model had the following statistical parameters: r2 = 0.8825 and q2 = 0.8626 for the training set and r2 = 0.9377 and q2 = 0.9124 for the test set. Novel statistical metric entitled as the index of ideality of correlation was used for the final model assessment, and the obtained results were 0.6631 for the training and 0.9683 for the test set. Molecular fragments responsible for the increases and decreases of the studied activity were defined and they were further used for the computer-aided design of new compounds as potential Rho kinase inhibitors. The final assessment of the developed QSAR model and designed inhibitors was achieved with the application of molecular docking. An excellent correlation between the results from QSAR and molecular docking studies was obtained.

Novel Synthesized Benzesulfonamide Nanosized Complexes; Spectral Characterization, Molecular Docking, Molecular Modeling and Analytical Application

New series, for sulfa drug complexes, was prepared from Cu(II), Ag(I), Cd(II) and Hg(II) ions. The new sulfisoxazole derivative and its corresponding complexes were fully characterized through all, analytical, spectral and theoretical tools. The mode of bonding, is pentadentate mode, in all complexes, which having bi-central atoms. The coordination number four, was proposed with all complexes, except Cu(II) complex, which has square-pyramidal geometry. XRD patterns and SEM images, introduce, the nanocrystalline nature for all investigated compounds. Molecular modeling, was carried out for all compounds, to modulate the structural forms, the best method execute the aim, was, DFT/B3LYP. Utilizing frontier energy gaps, the following parameters, electronegativity (χ), chemical potential (μ), global hardness (η), global softness (S), global electrophilicity index (ω) and absolute softness (ϭ) were computed. The docking process, was executed from sulfa drug ligand, against pathogen proteins as, 1jm7, 2hq6 and 3lvq, which attributing for, breast, colon and liver tumors, respectively. The computed parameters, among them, the inhibition constant (1.09 KCal/uM), which displayed that, the tested sulfa drug derivative, is considered a promising anti-colon cancer. The antitumor screening against, MCF-7, HEPG-2 and HCT-116cell lines, displays promising results with Hg(II) and Cd(II) complexes covered all cell lines. IC50 values for them were ˂ 4, which considered, best toxic feature against tumor cells. A specific analytical application, was done, upon the use of sulfa drug ligand as an acid- base indicator. This study was carried out versus, different types of titrations, in comparing with referenced indicators (Me.O and Ph.Ph). High conformity in the titration end point, using the proposed indicator with that known, was obtained. It is worthy to note that, the compound achieved the exact end point for weak acid- weak base titration, which is considered a shining spot in the study.

An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes.

Unraveling the structure of lectin-carbohydrate complexes is vital for understanding key biological recognition processes and development of glycomimetic drugs. Molecular Docking application to predict them is challenging due to their low affinity, hydrophilic nature and ligand conformational diversity. In the last decade several strategies, such as the inclusion of glycan conformation specific scoring functions or our developed solvent-site biased method, have improved carbohydrate docking performance but significant challenges remain, in particular, those related to receptor conformational diversity. In the present work we have analyzed conventional and solvent-site biased autodock4 performance concerning receptor conformational diversity as derived from different crystal structures (apo and holo), Molecular Dynamics snapshots and Homology-based models, for 14 different lectin-monosaccharide complexes. Our results show that both conventional and biased docking yield accurate lectin-monosaccharide complexes, starting from either apo or homology-based structures, even when only moderate (45%) sequence identity templates are available. An essential element for success is a proper combination of a middle-sized (10-100 structures) conformational ensemble, derived either from Molecular dynamics or multiple homology model building. Consistent with our previous works, results show that solvent-site biased methods improve overall performance, but that results are still highly system dependent. Finally, our results also show that docking can select the correct receptor structure within the ensemble, underscoring the relevance of joint evaluation of both ligand pose and receptor conformation.

Regioselective Synthesis, Antibacterial, Molecular Docking and Fingerprint Applications of 1‐Benzhydrylpiperazine Derivatized 1,4‐Disubstituted 1,2,3‐Triazoles

AbstractA series of ten 1,4‐Disubstituted 1,2,3‐Triazoles having 1‐benzhydrylpiperazine chemical scaffold were synthesized by one pot Cu (I) catalyzed click reaction and evaluated for their antibacterial activity against Escherichia Coli and Staphylococcus aureus by agar well diffusion method. Amongst all, 2‐chloro‐6‐fluorobenzyl substituted 1,2,3‐Triazole 7 e and 2,4‐dichlorobenzyl Triazole 7 f found to be more active compared to the Ciprofloxacin. To rationalize the binding interaction of compounds and the protein at active site, we performed Molecular docking study using a bacterial DNA Gyrase B protein. The docking energy of 2‐chloro‐6‐fluorobenzyl substituted Triazole 7 e and 2,4‐dichlorobenzyl Triazole 7 f was observed as −22.498 and −22.569 kcalmol−1 in comparison to reference drug Ciprofloxacin whose docking energy is −22.072 kcal mol−1. It also makes several hydrogen bonds with our conserved residue Ser55, Asp81 and Ile86. Furthermore, several hydrophobic contacts were also observed within the pocket. Finally, Latent fingerprint detection study indicated that the compound unsubstituted Triazole 7 a powder shows good adhesion and finger ridge details without back ground staining. The demonstrated method can be applied to detect fingerprints on all types of smooth surfaces and hence, it can be easily adopted for latent fingerprint detection. The in vitro and in silico activities conclusively revealed that our lead compounds may be used as a novel antibacterial agents.

Application of 3D-QSAR, Pharmacophore, and Molecular Docking in the Molecular Design of Diarylpyrimidine Derivatives as HIV-1 Nonnucleoside Reverse Transcriptase Inhibitors.

Diarylpyrimidines (DAPYs), acting as HIV-1 nonnucleoside reverse transcriptase inhibitors (NNRTIs), have been considered to be one of the most potent drug families in the fight against acquired immunodeficiency syndrome (AIDS). To better understand the structural requirements of HIV-1 NNRTIs, three-dimensional quantitative structure–activity relationship (3D-QSAR), pharmacophore, and molecular docking studies were performed on 52 DAPY analogues that were synthesized in our previous studies. The internal and external validation parameters indicated that the generated 3D-QSAR models, including comparative molecular field analysis (CoMFA, = 0.679, = 0.983, and = 0.884) and comparative molecular similarity indices analysis (CoMSIA, = 0.734, = 0.985, and = 0.891), exhibited good predictive abilities and significant statistical reliability. The docking results demonstrated that the phenyl ring at the C4-position of the pyrimidine ring was better than the cycloalkanes for the activity, as the phenyl group was able to participate in π–π stacking interactions with the aromatic residues of the binding site, whereas the cycloalkanes were not. The pharmacophore model and 3D-QSAR contour maps provided significant insights into the key structural features of DAPYs that were responsible for the activity. On the basis of the obtained information, a series of novel DAPY analogues of HIV-1 NNRTIs with potentially higher predicted activity was designed. This work might provide useful information for guiding the rational design of potential HIV-1 NNRTI DAPYs.

Vitamin D receptor (VDR) non-synonymous single nucleotide polymorphisms (nsSNPs) affect the calcitriol drug response - A theoretical insight

Pharmacogenetics and pharmacogenomics have become presumptive with advancements in next-generation sequencing technology. In complex diseases, distinguishing the feasibility of pathogenic and neutral disease-causing variants is a time consuming and expensive process. Recent drug research and development processes mainly rely on the relationship between the genotype and phenotype through Single nucleotide polymorphisms (SNPs). The SNPs play an indispensable role in elucidating the individual's vulnerability to disease and drug response. The understanding of the interplay between these leads to the establishment of personalized medicine. In order to address this issue, we developed a computational pipeline of vitamin D receptor (VDR) for SNP centered study by application of elegant molecular docking and molecular dynamics simulation approaches. In a few SNPs the volume of the binding cavities has increased in mutant structures when compared to the wild type, indicating a weakening in interaction (699.1 Å3 in wild type Vs. 738.8 in Leu230Val, 820.7 Å3 in Arg247Leu). This also differently reflected in the H-bond interactions and binding free energies −169.93 kcal/mol (wild type) Vs −156.43 kcal/mol (R154W), −105.49 kcal/mol (R274L) in Leu230Val and Arg247Leu respectively. Although we could not find noteworthy changes in the binding free energies and binding pocket in the remaining mutations, the H-bond interactions made these SNPs deleterious. Thus, we further analyzed the H-bond interactions and distances using molecular dynamics (MD) simulation studies.

Design and development of novel antibiotics based on FtsZ inhibition – in silico studies

QSAR models, computer-aided drug design and the application of molecular docking were used to evaluate benzamide analogues as FtsZ inhibitors.

In Silico Molecular Docking Studies on the Chemical Constituents of Clerodendrum phlomidis for its Cytotoxic Potential against Breast Cancer Markers

Despite considerable efforts, cancer still remains an aggressive killer worldwide. Indian Council of Medical Research reports that India is likely to have over 17.3 lakh new cases of cancer and over 8.8 lakh deaths due to the disease by 2020 with cancers of breast, lung and cervix topping the list. During the last decade, novel synthetic chemotherapeutic agents currently in use clinically have not succeeded in fulfilling expectations despite the considerable cost of their development. Natural products have received increasing attention over the past 30 years for their potential as novel cancer preventive and therapeutic agents. Plant extracts in future may provide more effective medicines than the synthetic drugs and this study helps to design and develop novel drug for breast cancer. Clerodendrum phlomidis is a shrub common in India and Sri Lanka with valuable medicinal properties. Molecular docking plays an important role in the rational drug designing and discovery. Main application of molecular docking lies in structure-based virtual screening for identification of new active compounds towards a particular target protein, in which it has produced a number of success stories. In present study, we aimed to investigate the chemotherapeutic potential of chemical constituents identified from the methanol extract of Clerodendrum phlomidis leaf with the motive of developing in silico protocol against breast cancer markers ErbB2 Receptor, BRCA1 Protein, Human cyclooxgenase-2, Human 5-lipoxygenase and 15-hydroxyprostaglandin dehydrogenase. In silico docking studies were carried out using Schrodinger software, based on the GLIDE. The results showed that most of the chemical constituents of Clerodendrum phlomidis binds with the enzyme of Human Cyclooxgenase-2 (PDB: 1V0X) and 15-hydroxyprostaglandin dehydrogenase (PDB: 2GDZ) effectively with the docking score using GLIDE varying between -3.93 Kcal/mol to -9.58 Kcal/mol and -3.63 Kcal/mol to -9.99 Kcal/mol respectively. Among the docked molecules compounds 3,6,7-trihydroxy-2-(3-methoxyphenyl)-4H-chromen-4-one, 1-(2,4,5-trihydroxyphenyl)-1-butanone, Isopropyl Linoleate and Ethyl linoleate was found to be more potent when compared to the other molecules.

Structural requirements for molecular design of positive allosteric modulators of AMPA receptor

Positive allosteric modulators of AMPA receptor are prospective for the development of safe and efficacious agents for the correction of disruption of the central nervous system functions. Joint application of molecular docking, MFTA and CoMFA QSAR modelling, and pharmacophore analysis affords a consistent picture of structural requirements for molecular design of novel promising bivalent modulators with high activity, including overall twisted-staple shape of a molecule, hydrophobic central core, and polar hydrogen bond acceptor groups in peripheral parts of a molecule.

Enhancing large-scale docking simulation on heterogeneous systems: An MPI vs rCUDA study

Virtual Screening (VS) methods can considerably aid clinical research by predicting how ligands interact with pharmacological targets, thus accelerating the slow and critical process of finding new drugs. VS methods screen large databases of chemical compounds to find a candidate that interacts with a given target. The computational requirements of VS models, along with the size of the databases, containing up to millions of biological macromolecular structures, means computer clusters are a must. However, programming current clusters of computers is no easy task, as they have become heterogeneous and distributed systems where various programming models need to be used together to fully leverage their resources. This paper evaluates several strategies to provide peak performance to a GPU-based molecular docking application called METADOCK in heterogeneous clusters of computers based on CPU and NVIDIA Graphics Processing Units (GPUs). Our developments start with an OpenMP, MPI and CUDA METADOCK version as a baseline case of cluster utilization. Next, we explore the virtualized GPUs provided by the rCUDA framework in order to facilitate the programming process. rCUDA allows us to use remote GPUs, i.e. installed in other nodes of the cluster, as if they were installed in the local node, so enabling access to them using only OpenMP and CUDA. Finally, several load balancing strategies are analyzed in a search to enhance performance. Our results reveal that the use of middleware like rCUDA is a convincing alternative to leveraging heterogeneous clusters, as it offers even better performance than traditional approaches and also makes it easier to program these emerging clusters.

Multi-structure docking analysis of BACE1 crystal structures and non-peptidic ligands

In order to design novel non-peptidic inhibitors of BACE1, many research groups have attempted using computational studies including docking analyses. Since there are too many 3D structures for BACE1 in the protein database, the selection of suitable crystal structures is a key prerequisite for the successful application of molecular docking. We employed a multi-structure docking protocol. In which 615 ligands’ structures were docked into 150 BACE1 structures. The large number of the resultant docking scores were post-processed by different data analysis methods including exploratory data analysis, regression analysis and discriminant analysis. It was found that using one crystal structure for docking did not result in high accuracy for predicting activity of the BACE1 inhibitors. Instead, using of the multi-structural docking scores, post-processed by chemometrics methods arrived to highly accurate predictive models. In this regards, the PDB accession codes of 4B70, 4DVF and 2WEZ could discriminate between active and inactive compounds, with higher accuracy. Clustering of the BACE1 structures based on principal component analysis of the crystallographic structures the revealed that the discriminant structures are in the center of the clusters. Thus, these structures can be selected as predominant crystal structures for docking studies of non-peptidic BACE1 inhibitors.