scholarly journals Designing Feature-Controlled Humanoid Antibody Discovery Libraries Using Generative Adversarial Networks

2020 ◽  
Author(s):  
Tileli Amimeur ◽  
Jeremy M. Shaver ◽  
Randal R. Ketchem ◽  
J. Alex Taylor ◽  
Rutilio H. Clark ◽  
...  
Keyword(s):  
Mhc Class Ii ◽  
In Silico ◽  
De Novo ◽  
Variable Region ◽  
Generative Adversarial Networks ◽  
Human Antibody ◽  
Generative Adversarial Network ◽  
Effective Response

ABSTRACTWe demonstrate the use of a Generative Adversarial Network (GAN), trained from a set of over 400,000 light and heavy chain human antibody sequences, to learn the rules of human antibody formation. The resulting model surpasses common in silico techniques by capturing residue diversity throughout the variable region, and is capable of generating extremely large, diverse libraries of novel antibodies that mimic somatically hypermutated human repertoire response. This method permits us to rationally design de novo humanoid antibody libraries with explicit control over various properties of our discovery library. Through transfer learning, we are able to bias the GAN to generate molecules with key properties of interest such as improved stability and developability, lower predicted MHC Class II binding, and specific complementarity-determining region (CDR) characteristics. These approaches also provide a mechanism to better study the complex relationships between antibody sequence and molecular behavior, both in vitro and in vivo. We validate our method by successfully expressing a proof-of-concept library of nearly 100,000 GAN-generated antibodies via phage display. We present the sequences and homology-model structures of example generated antibodies expressed in stable CHO pools and evaluated across multiple biophysical properties. The creation of discovery libraries using our in silico approach allows for the control of pharmaceutical properties such that these therapeutic antibodies can provide a more rapid and cost-effective response to biological threats.

scholarly journals Ficus benghalensis as Potential Inhibitor of 5α-Reductase for Hair Growth Promotion: In Vitro, In Silico, and In Vivo Evaluation

2021 ◽  
Vol 12 ◽  
Author(s):  
Jawaria Iltaf ◽  
Sobia Noreen ◽  
Muhammad Fayyaz ur Rehman ◽  
Shazia Akram Ghumman ◽  
Fozia Batool ◽  
...  
Keyword(s):  
In Silico ◽  
Hair Growth ◽  
De Novo ◽  
Growth Promotion ◽  
Hair Follicles ◽  
Binding Energies ◽  
Ficus Benghalensis ◽  
Rp Hplc

The screening of hair follicles, dermal papilla cells, and keratinocytes through in vitro, in vivo, and histology has previously been reported to combat alopecia. Ficus benghalensis has been used conventionally to cure skin and hair disorders, although its effect on 5α-reductase II is still unknown. Currently, we aim to analyze the phytotherapeutic impact of F. benghalensis leaf extracts (FBLEs) for promoting hair growth in rabbits along with in vitro inhibition of the steroid isozyme 5α-reductase II. The inhibition of 5α-reductase II by FBLEs was assessed by RP-HPLC, using the NADPH cofactor as the reaction initiator and Minoxin (5%) as a positive control. In silico studies were performed using AutoDock Vina to visualize the interaction between 5α-reductase II and the reported phytoconstituents present in FBLEs. Hair growth in female albino rabbits was investigated by applying an oral dose of the FBLE formulation and control drug to the skin once a day. The skin tissues were examined by histology to see hair follicles. Further, FAAS, FTIR, and antioxidants were performed to check the trace elements and secondary metabolites in the FBLEs. The results of RP-HPLC and the binding energies showed that FBLEs reduced the catalytic activity of 5α-reductase II and improved cell proliferation in rabbits. The statistical analysis (p < 0.05 or 0.01) and percentage inhibition (>70%) suggested that hydroalcoholic FBLE has more potential in increasing hair growth by elongating hair follicle’s anagen phase. FAAS, FTIR, and antioxidant experiments revealed sufficient concentrations of Zn, Cu, K, and Fe, together with the presence of polyphenols and scavenging activity in FBLE. Overall, we found that FBLEs are potent in stimulating hair follicle maturation by reducing the 5α-reductase II action, so they may serve as a principal choice in de novo drug designing to treat hair loss.

scholarly journals In vivo, in vitro and in silico correlations of four de novo SCN1A missense mutations

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0211901 ◽  
Author(s):  
Andreea Nissenkorn ◽  
Yael Almog ◽  
Inbar Adler ◽  
Mary Safrin ◽  
Marina Brusel ◽  
...  
Keyword(s):  
In Silico ◽  
De Novo ◽  
Missense Mutations

scholarly journals In Silico Analysis of Sea Urchin Pigments as Potential Therapeutic Agents Against SARS-CoV-2: Main Protease (Mpro) as a Target.

2020 ◽  
Author(s):  
Tamara Rubilar ◽  
Elena Susana Barbieri ◽  
Ayelén Gázquez ◽  
Marisa Avaro ◽  
Mercedes Vera-Piombo ◽  
...  
Keyword(s):  
Sea Urchin ◽  
In Silico ◽  
De Novo ◽  
Drug Repurposing ◽  
In Silico Analysis ◽  
Promising Alternative ◽  
In Silico Docking ◽  
Main Protease

The SARS-CoV-2 outbreak has spread rapidly and globally generating a new coronavirus disease (COVID-19) since December 2019 that turned into a pandemic. Effective drugs are urgently needed and drug repurposing strategies offer a promising alternative to dramatically shorten the process of traditional de novo development. Based on their antiviral uses, the potential affinity of sea urchin pigments to bind main protease (Mpro) of SARS-CoV-2 was evaluated in silico. Docking analysis was used to test the potential of these sea urchin pigments as therapeutic and antiviral agents. All pigment compounds presented high molecular affinity to Mpro protein. However, the 1,4-naphtoquinones polihydroxilate (Spinochrome A and Echinochrome A) showed high affinity to bind around the Mpro´s pocket target by interfering with proper folding of the protein mainly through an H-bond with Glu166 residue. This interaction represents a potential blockage of this protease´s activity. All these results provide novel information regarding the uses of sea urchin pigments as antiviral drugs and suggest the need for further in vitro and in vivo analysis to expand all therapeutic uses against SARS-CoV-2. <br>

scholarly journals In Silico Analysis of Sea Urchin Pigments as Potential Therapeutic Agents Against SARS-CoV-2: Main Protease (Mpro) as a Target.

2020 ◽  
Author(s):  
Tamara Rubilar ◽  
Elena Susana Barbieri ◽  
Ayelén Gázquez ◽  
Marisa Avaro ◽  
Mercedes Vera-Piombo ◽  
...  
Keyword(s):  
Sea Urchin ◽  
In Silico ◽  
De Novo ◽  
Drug Repurposing ◽  
In Silico Analysis ◽  
Promising Alternative ◽  
In Silico Docking ◽  
Main Protease

The SARS-CoV-2 outbreak has spread rapidly and globally generating a new coronavirus disease (COVID-19) since December 2019 that turned into a pandemic. Effective drugs are urgently needed and drug repurposing strategies offer a promising alternative to dramatically shorten the process of traditional de novo development. Based on their antiviral uses, the potential affinity of sea urchin pigments to bind main protease (Mpro) of SARS-CoV-2 was evaluated in silico. Docking analysis was used to test the potential of these sea urchin pigments as therapeutic and antiviral agents. All pigment compounds presented high molecular affinity to Mpro protein. However, the 1,4-naphtoquinones polihydroxilate (Spinochrome A and Echinochrome A) showed high affinity to bind around the Mpro´s pocket target by interfering with proper folding of the protein mainly through an H-bond with Glu166 residue. This interaction represents a potential blockage of this protease´s activity. All these results provide novel information regarding the uses of sea urchin pigments as antiviral drugs and suggest the need for further in vitro and in vivo analysis to expand all therapeutic uses against SARS-CoV-2. <br>

scholarly journals In Silico Determined Properties of Designed Superoxide Dismutase-1 Mutants Predict ALS-like Phenotypes In Vitro and In Vivo

2018 ◽  
Author(s):  
Michèle G. DuVal ◽  
Luke McAlary ◽  
Mona Habibi ◽  
Pranav Garg ◽  
Mine Sher ◽  
...  
Keyword(s):  
Superoxide Dismutase ◽  
Motor Neuron ◽  
In Silico ◽  
De Novo ◽  
Experimental Tests ◽  
Developmental Model ◽  
Theoretical Predictions ◽  
Dynamics Simulations

AbstractThe underlying physical causes of SOD1-related ALS are still not well-understood. We address this problem here by computationally designing two de novo mutants, A89R and K128N, which were predicted theoretically to be either significantly destabilizing or stabilizing respectively. We subjected these in silico designed mutants to a series of experimental tests, including in vitro measures of thermodynamic stability, cell-based aggregation and toxicity assays, and an in vivo developmental model of zebrafish motor neuron axonopathy. The experimental tests validated the theoretical predictions: A89R is an unstable, highly-deleterious mutant, and K128N is a stable, non-toxic mutant. Moreover, K128N is predicted computationally to form an unusually stable heterodimer with the familial ALS mutant A4V. Consistent with this prediction, co-injection of K128N and A4V into zebrafish shows profound rescue of motor neuron pathology. The demonstrated success of these first principles calculations to predict the physical properties of SOD1 mutants holds promise for rationally designed therapies to counter the progression of ALS.SignificanceMutations in the protein superoxide dismutase cause ALS, and many of these mutants have decreased folding stability. We sought to pursue this thread using a synthetic biology approach, where we designed two de novo mutations, one stabilizing and one destabilizing, as predicted using computational molecular dynamics simulations. We then tested these mutants using in vitro, cell-based, and in vivo zebrafish models. We found that the unstable mutant was toxic, and induced a severe ALS phenotype in zebrafish; the predicted stable mutant, on the other hand, behaved even better than WT. In fact, it was able to rescue the ALS phenotype caused by mutant SOD1. We propose a mechanism for this rescue, which may provide an avenue for therapeutic intervention.

scholarly journals Evaluation of Drug Repositioning by Molecular Docking of Pharmaceutical Resources to Identification of Potential SARS-CoV-2 Viral Inhibitors

2022 ◽  
Author(s):  
Fatemeh Hosseini ◽  
Mehrdad Azin ◽  
Hamideh Ofoghi ◽  
Tahereh Alinejad
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
In Silico ◽  
De Novo ◽  
Drug Repositioning ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Future Perspective

Unfortunately, to date, there is no approved specific antiviral drug treatment against COVID-19. Due to the costly and time-consuming nature of the de novo drug discovery and development process, in recent days, the computational drug repositioning method has been highly regarded for accelerating the drug-discovery process. The selection of drug target molecule(s), preparation of an approved therapeutics agent library, and in silico evaluation of their affinity to the subjected target(s) are the main steps of a molecular docking-based drug repositioning process, which is the most common computational drug re-tasking process. In this chapter, after a review on origin, pathophysiology, molecular biology, and drug development strategies against COVID-19, recent advances, challenges as well as the future perspective of molecular docking-based drug repositioning for COVID-19 are discussed. Furthermore, as a case study, the molecular docking-based drug repurposing process was planned to screen the 3CLpro inhibitor(s) among the nine Food and Drug Administration (FDA)-approved antiviral protease inhibitors. The results demonstrated that Fosamprenavir had the highest binding affinity to 3CLpro and can be considered for more in silico, in vitro, and in vivo evaluations as an effective repurposed anti-COVID-19 drug.

scholarly journals Ubiquitous Aberration in Cholesterol Metabolism across Pancreatic Ductal Adenocarcinoma

Metabolites ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 47
Author(s):  
Venugopal Gunda ◽  
Thiago C. Genaro-Mattos ◽  
Jyoti B. Kaushal ◽  
Ramakanth Chirravuri-Venkata ◽  
Gopalakrishnan Natarajan ◽  
...  
Keyword(s):  
In Silico ◽  
Free Cholesterol ◽  
Cholesterol Synthesis ◽  
De Novo ◽  
Cholesterol Metabolism ◽  
Ductal Adenocarcinoma ◽  
Preclinical Models ◽  
Clinical Specimens

Pancreatic cancer (PC) is characterized by metabolic deregulations that often manifest as deviations in metabolite levels and aberrations in their corresponding metabolic genes across the clinical specimens and preclinical PC models. Cholesterol is one of the critical metabolites supporting PC, synthesized or acquired by PC cells. Nevertheless, the significance of the de novo cholesterol synthesis pathway has been controversial in PC, indicating the need to reassess this pathway in PC. We utilized preclinical models and clinical specimens of PC patients and cell lines and utilized mass spectrometry-based sterol analysis. Further, we also performed in silico analysis to corroborate the significance of de novo cholesterol synthesis pathway in PC. Our results demonstrated alteration in free sterol levels, including free cholesterol, across in vitro, in vivo, and clinical specimens of PC. Especially, our sterol analyses established consistent alterations in free cholesterol across the different PC models. Overall, this study demonstrates the significance and consistency in deviation of cholesterol synthesis pathway in PC while showing the aberrations in sterol metabolite intermediates and the related genes using preclinical models, in silico platforms, and the clinical specimens.

scholarly journals Expanding functional protein sequence space using generative adversarial networks

2019 ◽  
Author(s):  
Donatas Repecka ◽  
Vykintas Jauniskis ◽  
Laurynas Karpus ◽  
Elzbieta Rembeza ◽  
Jan Zrimec ◽  
...  
Keyword(s):  
Protein Design ◽  
Sequence Space ◽  
Protein Sequence ◽  
Protein Function ◽  
De Novo ◽  
Protein Sequences ◽  
Generative Adversarial Networks ◽  
Functional Protein ◽  
Generative Adversarial Network

ABSTRACTDe novo protein design for catalysis of any desired chemical reaction is a long standing goal in protein engineering, due to the broad spectrum of technological, scientific and medical applications. Currently, mapping protein sequence to protein function is, however, neither computationionally nor experimentally tangible 1,2. Here we developed ProteinGAN, a specialised variant of the generative adversarial network 3 that is able to ‘learn’ natural protein sequence diversity and enables the generation of functional protein sequences. ProteinGAN learns the evolutionary relationships of protein sequences directly from the complex multidimensional amino acid sequence space and creates new, highly diverse sequence variants with natural-like physical properties. Using malate dehydrogenase as a template enzyme, we show that 24% of the ProteinGAN-generated and experimentally tested sequences are soluble and display wild-type level catalytic activity in the tested conditions in vitro, even in highly mutated (>100 mutations) sequences. ProteinGAN therefore demonstrates the potential of artificial intelligence to rapidly generate highly diverse novel functional proteins within the allowed biological constraints of the sequence space.

Recent In Vitro and In Silico Advances in the Understanding of Intranasal Drug Delivery

2020 ◽  
Vol 26 ◽  
Author(s):  
John Chen ◽  
Andrew Martin ◽  
Warren H. Finlay
Keyword(s):  
Drug Delivery ◽  
In Silico ◽  
Local Drug Delivery ◽  
In Vivo Studies ◽  
Intranasal Drug Delivery ◽  
Nasal Sprays ◽  
In Silico Studies ◽  
Drug Delivery Devices

Background: Many drugs are delivered intranasally for local or systemic effect, typically in the form of droplets or aerosols. Because of the high cost of in vivo studies, drug developers and researchers often turn to in vitro or in silico testing when first evaluating the behavior and properties of intranasal drug delivery devices and formulations. Recent advances in manufacturing and computer technologies have allowed for increasingly realistic and sophisticated in vitro and in silico reconstructions of the human nasal airways. Objective: To perform a summary of advances in understanding of intranasal drug delivery based on recent in vitro and in silico studies. Conclusion: The turbinates are a common target for local drug delivery applications, and while nasal sprays are able to reach this region, there is currently no broad consensus across the in vitro and in silico literature concerning optimal parameters for device design, formulation properties and patient technique which would maximize turbinate deposition. Nebulizers are able to more easily target the turbinates, but come with the disadvantage of significant lung deposition. Targeting of the olfactory region of the nasal cavity has been explored for potential treatment of central nervous system conditions. Conventional intranasal devices, such as nasal sprays and nebulizers, deliver very little dose to the olfactory region. Recent progress in our understanding of intranasal delivery will be useful in the development of the next generation of intranasal drug delivery devices.

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