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 …

[HTML][HTML] Exploring the Chemical Features and Biomedical Relevance of Cell-Penetrating Peptides

LM Moreno-Vargas, D Prada-Gracia - International Journal of Molecular …, 2024 - mdpi.com
Cell-penetrating peptides (CPPs) are a diverse group of peptides, typically composed of 4 to
40 amino acids, known for their unique ability to transport a wide range of substances—such …

DPI_CDF: druggable protein identifier using cascade deep forest

M Arif, G Fang, A Ghulam, S Musleh, T Alam - BMC bioinformatics, 2024 - Springer
Background Drug targets in living beings perform pivotal roles in the discovery of potential
drugs. Conventional wet-lab characterization of drug targets is although accurate but …

DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists

N Schaduangrat, N Anuwongcharoen… - Journal of …, 2023 - Springer
Drug resistance represents a major obstacle to therapeutic innovations and is a prevalent
feature in prostate cancer (PCa). Androgen receptors (ARs) are the hallmark therapeutic …

PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation

M Arif, S Musleh, H Fida, T Alam - Scientific Reports, 2024 - nature.com
Anticancer peptides (ACPs) perform a promising role in discovering anti-cancer drugs. The
growing research on ACPs as therapeutic agent is increasing due to its minimal side effects …

Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance

MN Asim, T Asif, F Mehmood, A Dengel - Computers in Biology and …, 2025 - Elsevier
Peptides are gaining significant attention in diverse fields such as the pharmaceutical
market has seen a steady rise in peptide-based therapeutics over the past six decades …

PredAoDP: Accurate identification of antioxidant proteins by fusing different descriptors based on evolutionary information with support vector machine

S Ahmed, M Arif, M Kabir, K Khan, YD Khan - Chemometrics and Intelligent …, 2022 - Elsevier
Antioxidant proteins play a vital role in diseases prevention caused by free radical
intermediates. Accurate identification of antioxidant proteins may provide significant clues to …

ACP-ML: A sequence-based method for anticancer peptide prediction

J Bian, X Liu, G Dong, C Hou, S Huang… - Computers in Biology and …, 2024 - Elsevier
Cancer is a serious malignant tumor and is difficult to cure. Chemotherapy, as a primary
treatment for cancer, causes significant harm to normal cells in the body and is often …

[HTML][HTML] StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features

M Arif, S Musleh, A Ghulam, H Fida, Y Alqahtani… - Methods, 2024 - Elsevier
Host defense or antimicrobial peptides (AMPs) are promising candidates for protecting host
against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type …

A computational predictor for Accurate Identification of Tumor homing peptides by integrating sequential and deep BiLSTM features

R Arif, S Kanwal, S Ahmed, M Kabir - … Sciences: Computational Life …, 2024 - Springer
Cancer remains a severe illness, and current research indicates that tumor homing peptides
(THPs) play an important part in cancer therapy. The identification of THPs can provide …