Hello! I'm Odin. My English name closely resembles the pronunciation of my Chinese name and carries a double meaning: 昊天, akin to a deity in Chinese Taoism, and Odin, the chief god in Norse mythology. I earned a dual B.S. in Physics and Pharmaceutics from Zhejiang University in 2022, advised by Prof. Tingjun Hou, focusing on Computer-aided Drug Design. I currently collaborate closely with Prof. Shuangjia Zheng at SJTU. From now on, I will be a CS PhD at UW, advised by Prof. David Baker for general molecule design. My experience spans nearly every aspect of AIDD, including molecular docking, ADMET prediction, and molecular generation. I'm always open to potential collaborations and am passionate about crazy ideas. My CV could be found here.
Previously, I interned at Carbon Silicon AI in Hangzhou, and worked as an AI consultant for Pledge Therapeutics in Boston. Currently, I am endeavoring to establish a startup to realize my ambitious vision for the next generation of AIDD: a system that is driven by generative AI, underpinned by physical constraints and domain knowledge, all tailored to serve the needs of expert molecular designers.
Since 2019, I have been actively involved in AIDD research and never stopped exploring its challenges and advancements. Keep an eye on my research—I welcome discussions about these topics. I am also a geek at heart and have open-sourced all my study materials and code scripts Github. I hope you find these resources helpful. By the way, I'm working on a book titled "GNN and Modern Drug Discovery." During this period, I call myself the ancient Greek god overseeing graph neural networks.
Beyond my professional pursuits, I am a contemporary hippie. I continually question the meaning of life and engage in dialogues with the ancient Greek philosophers, Buddha, Romantic poets, and hermits. I am on a perpetual quest for truth. I aim to bring a vision of eternal freedom to all beings through acts of kindness and bizarre behaviors. If you share similar thoughts, please talk to me. I am glad to meet you on the road. As Albert Camus said, "Do not walk behind me, for I may not lead; do not walk in front of me, for I may not follow; just walk beside me and be my friend."
——在众神当中只有我最易朽
Structure-based Molecular Generation: A New Paradigm Enables Efficient Design of Potent CLIP1-LTK Inhibitors
Peichen Pan*, ShiCheng Chen*, Odin Zhang*, ..., Tingjun Hou
Cell, Submitted
We extend the Delete model to Casual-Delete model, scussfully design a potent inhibitors targeting to LTK
Delete: Deep Lead Optimization Enveloped in Protein Pocket through unified Deleting Strategies and a Structure-aware Network
Odin Zhang*, Huifeng Zhao*, Xujun Zhang*, ..., Chang-yu Hsieh, Tingjun Hou.
Nat. Commun. Second-round Peer Review
When you face some problems in drug discovery, just delete!
SurfGen: Learning on Topological Surface and Geometric Structure for 3D Molecular Generation
Odin Zhang*, Tianyue Wang*, Gaoqi Weng, ..., Chang-yu Hsieh, Tingjun Hou.
Nat. Compt. Sci, 3, 849–859 (2023)
Inspired from key-and-lock model, we build a 3D molecular design model directly on topological protein surface through Geodesic-GNN and Geoatton-GNN, which satisfy the physical equivariance.
ResGen: Learning the Interaction Patterns through Multiscale Modeling and SE(3)-Framework for 3D-Pocket Molecular Generation
Odin Zhang, Jintu Zhang, Xujun Zhang, ..., Chang-yu Hsieh, Tingjun Hou.
Nat. Mach. Intell., 5, 1020–1030 (2023)
We construct a novel 3D Pocket-aware molecular generation model via multi-scale modeling, achieving SOTA performance on CrossDock dataset and our curated real-world dataset.
Multi-Objective Structure-Based Molecule Generation with Pareto MCTS
Yaodong Yang*, Guangyong Chen, Jinpeng Li, Odin Zhang*, ..., Pheng-Ann Heng
AAAI
A MCTS-based method for molecular generation
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration
Haitao Lin, Yufei Huang, Odin Zhang, ..., Stan Z. Li.
NIPS2023
We use diffusion model to grow fragments and link fragments for lead optimization
DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
Haitao Lin*, Yufei Huang*, Liu Meng, Odin Zhang, Xuanjing Li, Shuiwang Ji, Tingjun Hou, Stan Z. Li
We propose a one-shot approach to capture global interatomic forces for growing molecules directly within protein pockets
A Flexible Data-Free Framework for Structure-Based De Novo Drug Design with Reinforcement Learning
Hongyan Du*, Dejun Jiang*, Odin Zhang, ..., TingjunHou.
Chemical Science
A MCTS-based approach enables de novo design according to the chemicts' requirement
FFLOM: a flow-based autoregressive model for fragment-to-lead optimization. Journal of Medicinal Chemistry
Jieyu Jin, Dong Wang, Odin Zhang, ..., Yu Kang, Tingjun Hou
Journal of Medicinal Chemistry 14(8), 2054-2069
We develop a flow-based model for fragment elaboration and linker design, achieving the SOTA performance regarding 2D metrics
KarmaDock: a deep learning paradigm for ultra-large library docking with fast speed and high accuracy
Xujun Zhang*, Odin Zhang*, ..., Chang-yu Hsieh, Tingjun Hou.
Nat. Compt. Sci.,3, 739–740 (2023).
A Deep Learning-based docking method, from binding pose to virtual screening
Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoop
Tianyue Wang*, Xujun Zhang*, Odin Zhang*, ..., Chang-yu Hsieh, Tingjun Hou.
Nat. Mach. Intell., Major Revision
A SOTA method for the geometry prediction of the loop domain in proteins
SDEGen: Learning to Evolve Molecular Conformations from Thermodynamic Noise for Conformation Generation
Odin Zhang*, ShengMing Li*, Jintu Zhang, .., Yu Kang, Tingjun Hou.
Chem. Sci., 14, 1557-1568
We construct a novel conformation generation model via the stochastic differential equation-based generative model, which is a kind of diffusion process.
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction
Yufei Huang*, ..., Odin Zhang, ..., Stan. Z. Li.
AAAI 2024
In this paper, we first investigate the rea- son behind the decrease in prediction accuracy when utilizing predicted structures, attributing it to the structural distribution bias from the perspective of structure representation learning
Infinite Physical Monkey: Do Deep Learning Methods Really Perform Better in Conformation Generation?
Odin Zhang, Jintu Zhang, Huifeng Zhao, Dejun Jiang, Yafeng Deng.
Bio Arxiv
We present our opinions on conformation generation, discussing another two papers on arxiv platform
MetalProGNet: A Structure-based Deep Graph Model for Metalloprotein–ligand Interaction Predictions
Dejun Jiang, Zhaofeng Ye, Chang-yu Hsieh, Odin Zhang, ..., Jian Wu, Tingjun Hou
Chem. Sci. 14(8), 2054-2069
We develop a novel and accurate scoring function for metalloproteins, the main methodology is bi-partite graph and GNN
Explainable Fragment-Based Molecular Property Attribution
Linxiang Jia, Zunlei Feng, Odin Zhang, Jie Song, Zipeng Zhong, Shaolun Yao, Mingli Song.
Adv. Intell. Syst. 4(10), 2200104
I led the experimental validation of the model throught collection of pharmacological data, this is my early-stage participation in undergraduate period
Quasiclassical Trajectory Simulation as a Protocol to Build Locally Accurate Machine Learning Potentials
Jintu Zhang*, Odin Zhang*, Zhixin Qin, Yu Kang, Xin Hong, Tingjun Hou.
J. Chem. Inf. Model. 2023, 63, 4, 1133–1142
We show that quasiclassical trajectory (QCT) calculations can be invoked to efficiently obtain locally accurate ML-PESs, thus accelearing molecular dynamics
An Engineered Design of Self-Assembly Nanomedicine Guided by Molecular Dynamic Simulation for Photodynamic and Hypoxia-Directed Therapy
Yu Wang, Odin Zhang, Jianwei Wang, Guping Tang, Hongzhen Bai.
Mol. Pharmaceutics, 2023, 20, 4, 2128–2137
I conduct the MD and DPD to guide the design of the nanomedicine ISDNN, which achieves uniform size distribution and high drug loading up to 90%
Sigmoid Accelerated Molecular Dynamics: An Efficient Enhanced Sampling Method for Biosystems
Yihao Zhao, Jintu Zhang, Odin Zhang, Shukai Gu, Yafeng Deng, Yaoquan Tu, Tingjun Hou, Yu Kang.
J. Phys. Chem. Lett. 2023, 14, 4, 1103–1112
We propose sigmoid accelerated molecular dynamics (SaMD), which can produce the free energy landscape with better accuracy and efficiency compared with GaMD.
Amphiphilic porphyrin-based supramolecular self-assembly for photochemotherapy: From molecular design to application
Shuping Wang, Xuechun Huang, Yunhong He, Odin Zhang*, Jun Zhou, Guping Tang, Shijun Li, Hongzhen Bai.
Nano Today, 48, 101732
I conduct the Disspative Particle Dynamics (DPD) to study the stability of CPT@P complex, this is my early-stage work in undergraduate period
How Good Are Current Docking Programs at Nucleic acids-ligand Docking? a Comprehensive Evaluation
Dejun Jiang, Huifeng Zhao, ...,Odin Zhang, Tingjun Hou
Journal of Chemical Theory and Computation 14(8), 2054-2069
We conducted a comprehensive evaluation of molecular docking programs for NA–ligand systems, contributing to the future research about virtual screening on such a system
I am also a boxing enthusiast, because "faced with the overpowering savagery of a king-like force, truth, knowledge, thought, understanding, and wit all flee, banished from the battlefield."
I am a thorough hippie, and I like to describe myself with rock and roll. Research, boxing, and religion are merely metaphors of my existence. I pursue freedom, absurdity, and the impossible eternity.
Dedicate to HanShan and The Dharma Bums
山中何太冷,自古非今年。
沓嶂恒凝雪,幽林每吐烟。
草生芒种后,叶落立秋前。
此有沉迷客,窥窥不见天。
It's cold in the mountains, and not just this year.
The jagged cliffs are always piled high with snow, and the deep canyon species of trees are always spitting mist outward.
The grass is still sprouting in June, and the leaves start falling in August when they first arrive.
And here I was, mesmerized like a drug addict who had just finished a hit.
从明天起,做一个幸福的人
喂马,劈柴,周游世界
从明天起,关心粮食和蔬菜
我有一所房子,面朝大海,春暖花开
从明天起,和每一个亲人通信
告诉他们我的幸福
那幸福的闪电告诉我的
我将告诉每一个人
给每一条河每一座山取一个温暖的名字
陌生人,我也为你祝福
愿你有一个灿烂的前程
愿你有情人终成眷属
愿你在尘世获得幸福
我只愿面朝大海,春暖花开
Face to the sea,spring blossoms
From tomorrow,be a felicific man.
Feed a horse,split firewood,
and travel around the world.
From tomorrow,only care about cereal and vegerable.
I have a house facing to the sea.
There is spring all the year around and all is blooming.
From tomorrow,communciate with every kinsfolk.
Tell them my happiness.
What the felicific lightning has told me is
what I will tell everyone.
Give every river and every mountain a fragant name.
Stranger,I also bless you.
Hope you have boundless prospects.
Hope you have your Jack or Jill.
Hope you find your happiness in the world.
I only shall face to the sea and long for spring blossoms.
A conversation at the bottom of the heart
You have fulfilled your long-standing dream, and broken through all obstacles.
Why do you still feel so painful?
At the moment I realise my dream,
I really felt great satisfaction at the bottom of my heart.
But almost in an instant,
I felt the endless nothingness.
What did the aurora bring to me?
There seems to be nothing.
I still clearly remember the palpitation in my heart when I dreamed of seeing the aurora as a child,
but when I grew up, the throbbing became lighter and lighter.
I was overwhelmed by life, and was no longer able to complete the so-called dream.
But when I buried my dream,
my heart was unwilling.
So, I' ve tried my best,
and came here with the body that I didn't know how long I could live,
I long for the aurora to bring me an eternal meaning,
so that I can fight (against) life bravely.
But that doesn't exist.
It has no meaning at all.
My life will not change, and my story will not fly to the blue sky.
In that case, what is the meaning of life?
The dream that can be moved for it will be dull after it is realized.
All our pursues will turn into nothingness in the end.
Why should we purse it?
So, I'm not going to go on.
Since life has no meaning, let me go.
Let me go to the abyss, to embrace the eternal nothingness,
to embrace the eternal death.