scholarly journals DLAB - Deep learning methods for structure-based virtual screening of antibodies

2021 ◽  
Author(s):  
Constantin Schneider ◽  
Andrew Buchanan ◽  
Bruck Taddese ◽  
Charlotte M. Deane
Keyword(s):  
Deep Learning ◽  
Virtual Screening ◽  
Drug Discovery Process ◽  
Learning Methods ◽  
Drug Candidates ◽  
Specific Antigens ◽  
High Throughput Screens ◽  
Selection Of

AbstractAntibodies are one of the most important classes of pharmaceuticals, with over 80 approved molecules currently in use against a wide variety of diseases. The drug discovery process for antibody therapeutic candidates however is time- and cost-intensive and heavily reliant on in-vivo and in-vitro high throughput screens. Here, we introduce a framework for structure-based deep learning for antibodies (DLAB) which can virtually screen putative binding antibodies against antigen targets of interest. DLAB is built to be able to predict antibody-antigen binding for antigens with no known antibody binders.We demonstrate that DLAB can be used both to improve antibody-antigen docking and structure-based virtual screening of antibody drug candidates. DLAB enables improved pose ranking for antibody docking experiments as well as selection of antibody-antigen pairings for which accurate poses are generated and correctly ranked. DLAB also outperforms baseline methods at identifying binding antibodies against specific antigens in a series of case studies. Our results demonstrate the promise of deep learning methods for structure-based virtual screening of antibodies.

Selection of Active Antiviral Compounds Against Covid-19 Disease Targeting Coronavirus Endoribonuclease Nendou/NSP15 Via Ligand- Based Virtual Screening and Molecular Docking

2020 ◽  
Vol 17 ◽  
Author(s):  
Gaurav Joshi ◽  
Ramarao Poduri
Keyword(s):  
Virtual Screening ◽  
Drug Repurposing ◽  
Antiviral Compounds ◽  
Clinical Level ◽  
Rapid Spread ◽  
Approved Drugs ◽  
Fda Approved Drugs ◽  
Selection Of

Background: The rapid spread of SARS-CoV-2 has caused havoc and panic among individuals, which has further worsened due to the unavailability of a proven drug(s) regime. Objective: The current work involves drug repurposing from the pool of USFDA approved drugs involving in silico virtual screening technique against Covid-19. Methods: Methodology involves virtual screening of 8548 FDA approved drugs against target protein endoribonuclease NendoU (Nsp15) (PDB ID: 6VWW). Results: Virtual screening-based analysis enabled us to identify four drugs, Eprosartan, Inarigivir soproxil, Foretinib, and DB01813 that could plausibly target Nsp15 against Covid-19 disease. Conclusion: The work offers the scope to corroborate the findings via in vitro and in vivo techniques to identify the potential of selected leads against Covid-19. The outcome may also help in tracing their molecular mechanism(s) in addition to their development at the clinical level in the future.

scholarly journals Structure-Based Virtual Screening and Molecular Dynamics of Phytochemicals Derived from Saudi Medicinal Plants to Identify Potential COVID-19 Therapeutics

2020 ◽  
Author(s):  
MUBARAK ALAMRI ◽  
Ali Altharawi ◽  
Alhumaidi B. Alabbas ◽  
Manal A. Alossaimi ◽  
Safar M. Alqahtani
Keyword(s):  
Virtual Screening ◽  
Medicinal Plants ◽  
In Vivo Studies ◽  
Effective Vaccine ◽  
Traditional Medicines ◽  
Drug Candidates ◽  
Computational Screening ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) has affected almost every country in the world by causing a global pandemic with a high mortality rate. Lack of an effective vaccine and/or antiviral drugs against SARS-CoV-2, the causative agent, has severely hampered the response to this novel coronavirus. Natural products have long been used in traditional medicines to treat various diseases, and purified phytochemicals from medicinal plants provide a valuable scaffold for the discovery of new drug leads. In the present study, we performed a computational screening of an in-house database composed of ~1000 phytochemicals derived from traditional Saudi medicinal plants with recognised antiviral activity. Structure-based virtual screening was carried out against three druggable SARS-CoV-2 targets, viral RNAdependent RNA polymerase (RdRp), 3-chymotrypsin-like cysteine protease (3CLpro) and papain like protease (PLpro) to identify putative inhibitors that could facilitate the development of potential anti-COVID-19 drug candidates. Computational analyses identified three compounds inhibiting each target, with binding affinity scores ranging from-9.9 to -6.5 kcal/mol. Among these, luteolin 7-rutinoside, chrysophanol 8-(6-galloylglucoside) and kaempferol 7-(6’’-galloylglucoside) bound efficiently to RdRp, while chrysophanol 8-(6galloylglucoside), 3,4,5-tri-O-galloylquinic acid and mulberrofuran G interacted strongly with 3CLpro, and withanolide A, isocodonocarpine and calonysterone bound tightly to PLpro. These potential drug candidates will be subjected to further in vitro and in vivo studies and may assist the development of effective anti-COVID-19 drugs.

scholarly journals Structure-Based Virtual Screening and Molecular Dynamics of Phytochemicals Derived from Saudi Medicinal Plants to Identify Potential COVID-19 Therapeutics

2020 ◽  
Author(s):  
MUBARAK ALAMRI ◽  
Ali Altharawi ◽  
Alhumaidi B. Alabbas ◽  
Manal A. Alossaimi ◽  
Safar M. Alqahtani
Keyword(s):  
Virtual Screening ◽  
Medicinal Plants ◽  
In Vivo Studies ◽  
Effective Vaccine ◽  
Traditional Medicines ◽  
Drug Candidates ◽  
Computational Screening ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) has affected almost every country in the world by causing a global pandemic with a high mortality rate. Lack of an effective vaccine and/or antiviral drugs against SARS-CoV-2, the causative agent, has severely hampered the response to this novel coronavirus. Natural products have long been used in traditional medicines to treat various diseases, and purified phytochemicals from medicinal plants provide a valuable scaffold for the discovery of new drug leads. In the present study, we performed a computational screening of an in-house database composed of ~1000 phytochemicals derived from traditional Saudi medicinal plants with recognised antiviral activity. Structure-based virtual screening was carried out against three druggable SARS-CoV-2 targets, viral RNAdependent RNA polymerase (RdRp), 3-chymotrypsin-like cysteine protease (3CLpro) and papain like protease (PLpro) to identify putative inhibitors that could facilitate the development of potential anti-COVID-19 drug candidates. Computational analyses identified three compounds inhibiting each target, with binding affinity scores ranging from-9.9 to -6.5 kcal/mol. Among these, luteolin 7-rutinoside, chrysophanol 8-(6-galloylglucoside) and kaempferol 7-(6’’-galloylglucoside) bound efficiently to RdRp, while chrysophanol 8-(6galloylglucoside), 3,4,5-tri-O-galloylquinic acid and mulberrofuran G interacted strongly with 3CLpro, and withanolide A, isocodonocarpine and calonysterone bound tightly to PLpro. These potential drug candidates will be subjected to further in vitro and in vivo studies and may assist the development of effective anti-COVID-19 drugs.

Flavonoids as P-gp Inhibitors: A Systematic Review of SARs

2019 ◽  
Vol 26 (25) ◽  
pp. 4799-4831 ◽  
Author(s):  
Jiahua Cui ◽  
Xiaoyang Liu ◽  
Larry M.C. Chow
Keyword(s):  
Molecular Mechanisms ◽  
Metastatic Cancer ◽  
Drug Candidates ◽  
Chemical Structures ◽  
Transporter Family ◽  
Promising Area ◽  
New Generation ◽  
Nontoxic Inhibitors

P-glycoprotein, also known as ABCB1 in the ABC transporter family, confers the simultaneous resistance of metastatic cancer cells towards various anticancer drugs with different targets and diverse chemical structures. The exploration of safe and specific inhibitors of this pump has always been the pursuit of scientists for the past four decades. Naturally occurring flavonoids as benzopyrone derivatives were recognized as a class of nontoxic inhibitors of P-gp. The recent advent of synthetic flavonoid dimer FD18, as a potent P-gp modulator in reversing multidrug resistance both in vitro and in vivo, specifically targeted the pseudodimeric structure of the drug transporter and represented a new generation of inhibitors with high transporter binding affinity and low toxicity. This review concerned the recent updates on the structure-activity relationships of flavonoids as P-gp inhibitors, the molecular mechanisms of their action and their ability to overcome P-gp-mediated MDR in preclinical studies. It had crucial implications on the discovery of new drug candidates that modulated the efflux of ABC transporters and also provided some clues for the future development in this promising area.

Current Approaches to Drug Discovery for Chagas Disease: Methodological Advances

2019 ◽  
Vol 22 (8) ◽  
pp. 509-520
Author(s):  
Cauê B. Scarim ◽  
Chung M. Chin
Keyword(s):  
Drug Discovery ◽  
Chagas Disease ◽  
Drug Candidates ◽  
Lead Compounds ◽  
New Drug ◽  
Compound Libraries ◽  
Screening Assays ◽  
Cruzi Infection

Background: In recent years, there has been an improvement in the in vitro and in vivo methodology for the screening of anti-chagasic compounds. Millions of compounds can now have their activity evaluated (in large compound libraries) by means of high throughput in vitro screening assays. Objective: Current approaches to drug discovery for Chagas disease. Method: This review article examines the contribution of these methodological advances in medicinal chemistry in the last four years, focusing on Trypanosoma cruzi infection, obtained from the PubMed, Web of Science, and Scopus databases. Results: Here, we have shown that the promise is increasing each year for more lead compounds for the development of a new drug against Chagas disease. Conclusion: There is increased optimism among those working with the objective to find new drug candidates for optimal treatments against Chagas disease.

scholarly journals In vitro and in vivo inhibition of malaria parasite infection by monoclonal antibodies against Plasmodium falciparum circumsporozoite protein (CSP)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Merricka C. Livingstone ◽  
Alexis A. Bitzer ◽  
Alish Giri ◽  
Kun Luo ◽  
Rajeshwer S. Sankhala ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Monoclonal Antibodies ◽  
Disease Burden ◽  
Vaccine Candidate ◽  
Specific Binding ◽  
Circumsporozoite Protein ◽  
Target Epitope ◽  
Selection Of

AbstractPlasmodium falciparum malaria contributes to a significant global disease burden. Circumsporozoite protein (CSP), the most abundant sporozoite stage antigen, is a prime vaccine candidate. Inhibitory monoclonal antibodies (mAbs) against CSP map to either a short junctional sequence or the central (NPNA)n repeat region. We compared in vitro and in vivo activities of six CSP-specific mAbs derived from human recipients of a recombinant CSP vaccine RTS,S/AS01 (mAbs 317 and 311); an irradiated whole sporozoite vaccine PfSPZ (mAbs CIS43 and MGG4); or individuals exposed to malaria (mAbs 580 and 663). RTS,S mAb 317 that specifically binds the (NPNA)n epitope, had the highest affinity and it elicited the best sterile protection in mice. The most potent inhibitor of sporozoite invasion in vitro was mAb CIS43 which shows dual-specific binding to the junctional sequence and (NPNA)n. In vivo mouse protection was associated with the mAb reactivity to the NANPx6 peptide, the in vitro inhibition of sporozoite invasion activity, and kinetic parameters measured using intact mAbs or their Fab fragments. Buried surface area between mAb and its target epitope was also associated with in vivo protection. Association and disconnects between in vitro and in vivo readouts has important implications for the design and down-selection of the next generation of CSP based interventions.

scholarly journals Preclinical Testing of Radiopharmaceuticals for the Detection and Characterization of Osteomyelitis: Experiences from a Porcine Model

Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4221
Author(s):  
Aage Kristian Olsen Alstrup ◽  
Svend Borup Jensen ◽  
Ole Lerberg Nielsen ◽  
Lars Jødal ◽  
Pia Afzelius
Keyword(s):  
Animal Model ◽  
Animal Models ◽  
Porcine Model ◽  
Animal Experiments ◽  
Radioactive Tracers ◽  
The Individual ◽  
Selection Of

The development of new and better radioactive tracers capable of detecting and characterizing osteomyelitis is an ongoing process, mainly because available tracers lack selectivity towards osteomyelitis. An integrated part of developing new tracers is the performance of in vivo tests using appropriate animal models. The available animal models for osteomyelitis are also far from ideal. Therefore, developing improved animal osteomyelitis models is as important as developing new radioactive tracers. We recently published a review on radioactive tracers. In this review, we only present and discuss osteomyelitis models. Three ethical aspects (3R) are essential when exposing experimental animals to infections. Thus, we should perform experiments in vitro rather than in vivo (Replacement), use as few animals as possible (Reduction), and impose as little pain on the animal as possible (Refinement). The gain for humans should by far exceed the disadvantages for the individual experimental animal. To this end, the translational value of animal experiments is crucial. We therefore need a robust and well-characterized animal model to evaluate new osteomyelitis tracers to be sure that unpredicted variation in the animal model does not lead to a misinterpretation of the tracer behavior. In this review, we focus on how the development of radioactive tracers relies heavily on the selection of a reliable animal model, and we base the discussions on our own experience with a porcine model.

scholarly journals Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2505
Author(s):  
Raheem Remtulla ◽  
Sanjoy Kumar Das ◽  
Leonard A. Levin
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
In Silico ◽  
Disulfide Bonds ◽  
Oral Absorption ◽  
In Vivo Studies ◽  
Drug Candidates ◽  
In Silico Methods

Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated in the downstream effects of axonal injury. A difficulty in using standard in silico methods for studying these drugs is that most computational tools are not designed for borane-containing compounds. Using in silico and machine learning methodologies, the absorption-distribution properties of these unique compounds were assessed. Features examined with in silico methods included cellular permeability, octanol-water partition coefficient, blood-brain barrier permeability, oral absorption and serum protein binding. The resultant neural networks demonstrated an appropriate level of accuracy and were comparable to existing in silico methodologies. Specifically, they were able to reliably predict pharmacokinetic features of known boron-containing compounds. These methods predicted that phosphine-borane compounds and their metabolites meet the necessary pharmacokinetic features for orally active drug candidates. This study showed that the combination of standard in silico predictive and machine learning models with neural networks is effective in predicting pharmacokinetic features of novel boron-containing compounds as neuroprotective drugs.

scholarly journals Ways into Understanding HIF Inhibition

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 159
Author(s):  
Tina Schönberger ◽  
Joachim Fandrey ◽  
Katrin Prost-Fingerle
Keyword(s):  
Protein Interactions ◽  
Target Genes ◽  
Protein Protein Interactions ◽  
Low Oxygen ◽  
Drug Candidates ◽  
Open Questions ◽  
Wide Range ◽  
Hif Pathway

Hypoxia is a key characteristic of tumor tissue. Cancer cells adapt to low oxygen by activating hypoxia-inducible factors (HIFs), ensuring their survival and continued growth despite this hostile environment. Therefore, the inhibition of HIFs and their target genes is a promising and emerging field of cancer research. Several drug candidates target protein–protein interactions or transcription mechanisms of the HIF pathway in order to interfere with activation of this pathway, which is deregulated in a wide range of solid and liquid cancers. Although some inhibitors are already in clinical trials, open questions remain with respect to their modes of action. New imaging technologies using luminescent and fluorescent methods or nanobodies to complement widely used approaches such as chromatin immunoprecipitation may help to answer some of these questions. In this review, we aim to summarize current inhibitor classes targeting the HIF pathway and to provide an overview of in vitro and in vivo techniques that could improve the understanding of inhibitor mechanisms. Unravelling the distinct principles regarding how inhibitors work is an indispensable step for efficient clinical applications and safety of anticancer compounds.

scholarly journals Insights in Behavior of Variably Formulated Alginate-Based Microcapsules for Cell Transplantation

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Pia Montanucci ◽  
Silvia Terenzi ◽  
Claudio Santi ◽  
Ilaria Pennoni ◽  
Vittorio Bini ◽  
...  
Keyword(s):  
Divalent Cations ◽  
Chemical Properties ◽  
Live Cells ◽  
High Performing ◽  
Physical Chemical ◽  
Degenerative Disorders ◽  
Selection Of ◽  
Better Than

Alginate-based microencapsulation of live cells may offer the opportunity to treat chronic and degenerative disorders. So far, a thorough assessment of physical-chemical behavior of alginate-based microbeads remains cloudy. A disputed issue is which divalent cation to choose for a high performing alginate gelling process. Having selected, in our system, high mannuronic (M) enriched alginates, we studied different gelling cations and their combinations to determine their eventual influence on physical-chemical properties of the final microcapsules preparation,in vitroandin vivo. We have shown that used of ultrapure alginate allows for high biocompatibility of the formed microcapsules, regardless of gelation agents, while use of different gelling cations is associated with corresponding variable effects on the capsules’ basic architecture, as originally reported in this work. However, only the final application which the capsules are destined to will ultimately guide the selection of the ideal, specific gelling divalent cations, since in principle there are no capsules that are better than others.

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