In silico methods and tools for drug discovery

B Shaker, S Ahmad, J Lee, C Jung, D Na - Computers in biology and …, 2021 - Elsevier
In the past, conventional drug discovery strategies have been successfully employed to
develop new drugs, but the process from lead identification to clinical trials takes more than …

Integration of molecular docking analysis and molecular dynamics simulations for studying food proteins and bioactive peptides

A Vidal-Limon, JE Aguilar-Toalá… - Journal of agricultural …, 2022 - ACS Publications
In silico tools, such as molecular docking, are widely applied to study interactions and
binding affinity of biological activity of proteins and peptides. However, restricted sampling of …

Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations

P Das, T Sercu, K Wadhawan, I Padhi… - Nature Biomedical …, 2021 - nature.com
The de novo design of antimicrobial therapeutics involves the exploration of a vast chemical
repertoire to find compounds with broad-spectrum potency and low toxicity. Here, we report …

ToxinPred2: an improved method for predicting toxicity of proteins

N Sharma, LD Naorem, S Jain… - Briefings in …, 2022 - academic.oup.com
Proteins/peptides have shown to be promising therapeutic agents for a variety of diseases.
However, toxicity is one of the obstacles in protein/peptide-based therapy. The current study …

Machine learning for antimicrobial peptide identification and design

F Wan, F Wong, JJ Collins… - Nature Reviews …, 2024 - nature.com
Artificial intelligence (AI) and machine learning (ML) models are being deployed in many
domains of society and have recently reached the field of drug discovery. Given the …

Bioactive peptides derived from plant origin by-products: Biological activities and techno-functional utilizations in food developments–A review

A Görgüç, E Gençdağ, FM Yılmaz - Food Research International, 2020 - Elsevier
Agro-industrial by-products containing considerable amounts of protein (10–50%) such as
soybean meal, rice bran and coconut pulp are promising bioactive peptide sources with …

ToxinPred 3.0: An improved method for predicting the toxicity of peptides

AS Rathore, S Choudhury, A Arora, P Tijare… - Computers in Biology …, 2024 - Elsevier
Toxicity emerges as a prominent challenge in the design of therapeutic peptides, causing
the failure of numerous peptides during clinical trials. In 2013, our group developed …

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study

Z Yang, P Bogdan, S Nazarian - Scientific reports, 2021 - nature.com
The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over
the world has led to over millions of deaths, and devastated the social, financial and political …

AntiCP 2.0: an updated model for predicting anticancer peptides

P Agrawal, D Bhagat, M Mahalwal… - Briefings in …, 2021 - academic.oup.com
Increasing use of therapeutic peptides for treating cancer has received considerable
attention of the scientific community in the recent years. The present study describes the in …

ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning

L Wei, X Ye, T Sakurai, Z Mu, L Wei - Bioinformatics, 2022 - academic.oup.com
Motivation Recently, peptides have emerged as a promising class of pharmaceuticals for
various diseases treatment poised between traditional small molecule drugs and therapeutic …