Shahid Ali
School of Biology, Hunan University, Hainan University, South China University of Technology, Jamia Millia Islamia, Yeungnam University, University of Delhi
Research areas: Biochemistry, Genetics and Molecular Biology · Molecular Biology · Computational Drug Discovery Methods · Muscle Physiology and Disorders · Enzyme Catalysis and Immobilization
0000-0002-4724-5086
About
Dr. Shahid Ali is a Postdoctoral Fellow in the School of Biology at Hunan University, China, where his research centres on de novo peptide design for plant immunity and the engineering of synthetic receptor-like kinases. His current work combines generative protein design with all-atom molecular dynamics to build peptide agonists capable of engaging multi-receptor immune complexes — an approach aimed at producing biologically active molecules rather than computational predictions alone.
He trained as a botanist, holding a B.Sc. (Hons.) in Botany, before moving into computation with a Master's degree in Bioinformatics and a Ph.D. from the South China University of Technology, where his doctoral research addressed enzyme engineering and computational biology. This trajectory from organismal biology through to structural computation shapes his research style: he works on problems where the computational result must ultimately be answerable to experiment.
Prior to his current appointment, Dr. Ali was a Postdoctoral Researcher at the School of Cyberspace Security, Hainan University (2024–2026). Before that, he spent three years at Yeungnam University, Republic of Korea, in the Department of Medical Biotechnology, first as a Postdoctoral Researcher (2021–2022) and subsequently as a Research Professor (2022–2024), where he led projects, supervised graduate students, and coordinated collaborations with experimental groups.
His research spans structural bioinformatics, machine learning, molecular dynamics, and computer-aided drug discovery. He has developed graph neural network architectures — including graph attention and heterogeneous graph networks built on protein language model embeddings — paired with explainable AI methods to make model predictions interpretable rather than merely accurate. Alongside this, he maintains an active programme in virtual screening, binding free energy estimation, and protein engineering, with recent work on inhibitor discovery and the redesign of plant transport proteins.
Dr. Ali has published more than 30 peer-reviewed articles, which have attracted approximately 1,200 citations, giving him an h-index of 19 and an i10-index of 23. He holds six patents, including three granted in Korea and one PCT international filing, and has completed two technology transfers to industry through Neo Crema Co., Ltd. — outcomes he regards as the natural endpoint of computational work that is meant to be used.
He continues to work at the intersection of protein design, machine learning, and molecular simulation, with a particular interest in extending generative design methods to receptor systems of agricultural and therapeutic importance.
Employment
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School of Biology, Hunan University Research Fellow2026 - Present
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Hainan University Research Associate2024 - 2026
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Yeungnam University Assistant professor2022 - 2024
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Yeungnam University Postdoc2021 - 2022
Education
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South China University of Technology Doctorate2016 - 2019
- 2014 - 2016
- 2011 - 2014
Projects & Funding
Projects & funding information is unavailable.
Publications (27)
- Ensemble Machine Learning- and Deep Learning-Driven Identification and Validation of Sennidin B as a Novel Dipeptidyl Peptidase-4 Inhibitor Save
- Global burden of lower respiratory infections and aetiologies, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023 Save
- Identification of FDA-Approved Drugs as Potential Inhibitors of WEE2: Structure-Based Virtual Screening and Molecular Dynamics with Perspectives for Machine Learning-Assisted Prioritization Save
- Large Language Models in Genomics—A Perspective on Personalized Medicine Save
- Mss51 protein inhibition serves as a novel target for type 2 diabetes: a molecular docking and simulation study Save
- Virtual Insights into Natural Compounds as Potential 5α-Reductase Type II Inhibitors: A Structure-Based Screening and Molecular Dynamics Simulation Study Save
- The roles of growth factors and hormones in the regulation of muscle satellite cells for cultured meat production Save
- IgLON4 Regulates Myogenesis via Promoting Cell Adhesion and Maintaining Myotube Orientation Save
- Dipeptidyl peptidase-4 inhibitory potentials of Glycyrrhiza uralensis and its bioactive compounds licochalcone A and licochalcone B: An in silico and in vitro study Save
- Identification and Evaluation of Traditional Chinese Medicine Natural Compounds as Potential Myostatin Inhibitors: An In Silico Approach Save
- Myostatin and its Regulation: A Comprehensive Review of Myostatin Inhibiting Strategies Save
- Tetranectin targeting by epigallocatechin gallate suppresses colon cancer cell proliferation Save
- Molecular Mechanisms and Current Treatment Options for Cancer Cachexia Save
- MIF1 and MIF2 Myostatin Peptide Inhibitors as Potent Muscle Mass Regulators Save
- High-resolution MD Simulation Studies to Get Mechanistic Insights into the Urea-induced Denaturation of Human Sphingosine Kinase 1 Save
- Extracellular Matrix and the Production of Cultured Meat Save
- Sequence and structure-based method to predict diacylglycerol lipases in protein sequence Save
- The increasing hunger concern and current need in the development of sustainable food security in the developing countries Save
- A Thermolabile Phospholipase B from Talaromyces marneffei GD-0079: Biochemical Characterization and Structure Dynamics Study Save
- Natural Deep Eutectic Solvents as Performance Additives for Peroxygenase Catalysis Save