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Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental costs, specifically for Coronavirus Disease 2019 (COVID-19),…

Biomolecules · Quantitative Biology 2022-02-11 Xiaoqin Pan , Xuan Lin , Dongsheng Cao , Xiangxiang Zeng , Philip S. Yu , Lifang He , Ruth Nussinov , Feixiong Cheng

Deep generative models are attracting great attention for molecular design with desired properties. Most existing models generate molecules by sequentially adding atoms. This often renders generated molecules with less correlation with…

Machine Learning · Computer Science 2021-11-29 Seonghwan Seo , Jaechang Lim , Woo Youn Kim

Structure-Based Drug Design (SBDD) has revolutionized drug discovery by enabling the rational design of molecules for specific protein targets. Despite significant advancements in improving docking scores, advanced 3D-SBDD generative models…

Biomolecules · Quantitative Biology 2025-03-04 Bowen Gao , Yanwen Huang , Yiqiao Liu , Wenxuan Xie , Wei-Ying Ma , Ya-Qin Zhang , Yanyan Lan

Surges that have been observed at different periods in the number of COVID-19 cases are associated with the emergence of multiple SARS-CoV-2 (Severe Acute Respiratory Virus) variants. The design of methods to support laboratory detection…

Network medicine has been pursued for Covid-19 drug repurposing. One such approach adopts structural controllability, a theory for controlling a network (the cell). Motivated to protect the cell from viral infections, we extended this…

Molecular Networks · Quantitative Biology 2024-03-28 Xinru Wei , Chunyu Pan , Xizhe Zhang , Weixiong Zhang

COVID-19 is a devastating respiratory and inflammatory illness caused by a new coronavirus that is rapidly spreading throughout the human population. Over the past 6 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the…

Simultaneously optimizing molecules against multiple therapeutic targets remains a profound challenge in drug discovery, particularly due to sparse rewards and conflicting design constraints. We propose a structured active learning (AL)…

Machine Learning · Computer Science 2025-06-24 Júlia Vilalta-Mor , Alexis Molina , Laura Ortega Varga , Isaac Filella-Merce , Victor Guallar

A new coronavirus identified as SARS-CoV-2 virus has brought the world to a state of crisis, causing a major pandemic, claiming more than 433,000 lives and instigating major financial damage to the global economy. Despite current efforts,…

Biomolecules · Quantitative Biology 2020-06-18 Mohsen Chitsaz

The Corona Virus Disease 2019 (COVID-19) belongs to human coronaviruses (HCoVs), which spreads rapidly around the world. Compared with new drug development, drug repurposing may be the best shortcut for treating COVID-19. Therefore, we…

Machine Learning · Computer Science 2021-07-21 Shuting Jin , Xiangxiang Zeng , Wei Huang , Feng Xia , Changzhi Jiang , Xiangrong Liu , Shaoliang Peng

The pharmaceutical Research and development (R&D) process is lengthy and costly, taking nearly a decade to bring a new drug to the market. However, advancements in biotechnology, computational methods, and machine learning algorithms have…

Biomolecules · Quantitative Biology 2024-01-24 Damilola Oshunyinka

Is there a unified model for generating molecules considering different conditions, such as binding pockets and chemical properties? Although target-aware generative models have made significant advances in drug design, they do not consider…

Artificial Intelligence · Computer Science 2023-02-15 Zhangyang Gao , Yuqi Hu , Cheng Tan , Stan Z. Li

Deep generative models are rapidly advancing structure-based drug design, offering substantial promise for generating small molecule ligands that bind to specific protein targets. However, most current approaches assume a rigid protein…

Biomolecules · Quantitative Biology 2025-11-19 Xinzhe Zheng , Shiyu Jiang , Gustavo Seabra , Chenglong Li , Yanjun Li

Although machine learning has been successfully used to propose novel molecules that satisfy desired properties, it is still challenging to explore a large chemical space efficiently. In this paper, we present a conditional molecular design…

Machine Learning · Computer Science 2019-04-02 Seokho Kang , Kyunghyun Cho

Predicting molecular properties with data-driven methods has drawn much attention in recent years. Particularly, Graph Neural Networks (GNNs) have demonstrated remarkable success in various molecular generation and prediction tasks. In…

Quantitative Methods · Quantitative Biology 2021-10-19 Zaixi Zhang , Qi Liu , Hao Wang , Chengqiang Lu , Chee-Kong Lee

Molecular optimization is a key challenge in drug discovery and material science domain, involving the design of molecules with desired properties. Existing methods focus predominantly on single-property optimization, necessitating…

Machine Learning · Computer Science 2024-09-13 Aye Phyu Phyu Aung , Jay Chaudhary , Ji Wei Yoon , Senthilnath Jayavelu

The widespread availability of large amounts of genomic data on the SARS-CoV-2 virus, as a result of the COVID-19 pandemic, has created an opportunity for researchers to analyze the disease at a level of detail unlike any virus before it.…

Machine Learning · Computer Science 2021-10-20 Zahra Tayebi , Sarwan Ali , Murray Patterson

Global coronavirus disease pandemic (COVID-19) caused by newly identified SARS- CoV-2 coronavirus continues to claim the lives of thousands of people worldwide. The unavailability of specific medications to treat COVID-19 has led to drug…

Quantitative Methods · Quantitative Biology 2020-06-12 Romeo Cozac , Nazim Medzhidov , Shinya Yuki

The novelty of new human coronavirus COVID-19/SARS-CoV-2 and the lack of effective drugs and vaccines gave rise to a wide variety of strategies employed to fight this worldwide pandemic. Many of these strategies rely on the repositioning of…

Molecular Networks · Quantitative Biology 2021-06-09 Giulia Fiscon , Federica Conte , Lorenzo Farina , Paola Paci

While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge. Here, we introduce a…

Computation and Language · Computer Science 2024-10-11 Peng Zhou , Jianmin Wang , Chunyan Li , Zixu Wang , Yiping Liu , Siqi Sun , Jianxin Lin , Leyi Wei , Xibao Cai , Houtim Lai , Wei Liu , Longyue Wang , Yuansheng Liu , Xiangxiang Zeng

Multimodal molecular representation learning, which jointly models molecular graphs and their textual descriptions, enhances predictive accuracy and interpretability by enabling more robust and reliable predictions of drug toxicity,…

Machine Learning · Computer Science 2025-10-21 Yingxu Wang , Kunyu Zhang , Jiaxin Huang , Nan Yin , Siwei Liu , Eran Segal