The following books are those I think I should read or re-read and would like to recommend to new graduates interested in computational biophysics/biochemistry, especially molecular simulations. Bolded ones are highly recommended! 

Physics:

• Statistical Mechanics, by Donald A. McQuarrie.

• Statistical Mechanics, Entropy, Order Parameters, and Complexity, by James P. Sethna. [PDF]

• Statistical Mechanics, by R. K. Pathria & Paul D. Beale.

• Nonequilibrium Statistical Mechanics, by Robert Zwanzig. 

• Theoretical Concepts in Physics: An Alternative View of Theoretical Reasoning in Physics, by Malcolm S. Longair.

• 统计物理学 (in Chinese), by 苏汝铿.

• 热力学与统计物理 (in Chinese), by 汪志诚.

• 热力学与统计物理 (in Chinese), by 周子舫 & 曹烈兆.

• Capillarity and Wetting Phenomena by Pierre-Gilles de Gennes et al.

• Soft Mater Physics, by Maso Doi. 

Interdisciplinary:

• Molecular Driving Forces, by Ken A. Dill and Sarina Bromberg.

• Statistical Physics of Biomolecules, by Daneil M. Zuckerman. 

• Protein Physics, by Alexei V. Finkelstein and Oleg B. Ptitsyn. 

• The Theory of Intermolecular Forces, by Anthony Stone. 

• Intermolecular and Surface Forces, by Jacob N. Israelachvili. 

Polymer:

• Polymer Physics, by Micheal Rubinstein and Ralph H. Colby.

• Polymer Chemistry, by Paul C. Hiemenz and Timothy P. Lodge.

• Scaling Concepts in Polymer Physics, by Pierre-Gilles de Gennes. 

Liquid theory:

• Molecular theory of solutions, by Arieh Ben-Naim. 

• Theory of Simple Liquids with Applications to Soft Matter, by Jean-Pierre Hansen and Ian R. McDonald.

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Chemistry:

• Physical Chemistry: Thermodynamic, Structure and Change, by Peter Atkins and Julio de Paula. 

• Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory, by Attila Szabo and Neil S. Ostlund.

• Molecular Orbitals and Organic Chemical Reactions, by Ian Fleming. 

• Introduction to computational chemistry, by Frank Jensen. 

MD & MC:

• Computer Simulations of Liquids, by Michael P. Allen & Dominic J. Tildesley. 

• Understanding Molecular Simulation: From Algorithms to Applications, by Berend Smit and Daan Frenkel.

• A Guide to Monte Carlo Simulations in Statistical Physics, by David P. Landau and Kurt Binder.

• Free Energy Calculations: Theory and Applications in Chemistry and Biology, Editors: Ch. Chipot and A. Pohorille.

Markov State Models:

• An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation, Editors: Gregory R. Bowman, Vijay S. Pande and Frank Noé.

Biology:

• Molecular Biology of  the Cell, by Alberts, Johnson, Lewis, Morgan Raff, Boberts and Walter.

• Cell Biology by Pollard, Earnshaw, Lippincott-Schwartz and Johnson. 

• Pricinples of Biochemistry, by David L. Nelson and Michael M. Cox. 

Computer Science:

• Algorithms in C, by Robert Sedgewick.

• Gaussian Processes for Machine Learning, by Carl Edward Rasmussen & Christopher K. I. Williams.

• 统计学习方法 (in Chinese), by 李航.

• 机器学习 (in Chinese), by 周志华.

• C 语言点滴(in Chinese), by 赵岩.

Misc:

• Virial Expansion – A Brief Introduction, by Frank Schreiber, Fabio Zanini & Felix Roosen-Runge. 

• Statistical mechanics textbooks recommended by others.

[To be updated]