Proteins, which regulate most of the biological activities, perform their functions through their unique three-dimensional structures. The folding process of this three dimensional structure from one dimensional sequence is not well understood. The available facts infer that the protein structures are mostly conserved while sequences are more tolerant to mutations i.e. a number of sequences can adopt the same fold. These arch of optimal sequences for a chosen conformation is known as inverse protein folding and this thesis takes this approach to solve the enigmatic problem. This thesis presents a protein sequence design method based on the native state topology of protein structure. The structural importance of the amino acid positions has been converted into the topological parameter of the protein conformation. This scheme of extraction of topology of structures has been successfully applied on three dimensional lattice structures and in turn sequences with minimum energy for a given structure are obtained. This technique along with the reduced amino cid alphabet(A reduced amino acid alphabet is any clustering of twenty amino acids based on some measure of the irrelative similarity) has been applied on the protein structures and hence designed optimal amino acid sequences for a given structure. These designed sequences are energetically much better than the native amino acid sequence. The utility of this method is further confirmed by showing the similarity between naturally occurring and the designed sequences. In summary, a computationally efficient method of designing optimal sequences for a given structure is given. The physical interaction energy between the amino acids is an important part of study of protein-protein interaction, structure prediction, modeling and docking etc. The local environment of amino acids makes a difference between the same amino acid pairs in the protein structure and so the pair-wise interaction energy of amino acid residues should depend on the irrespective environment. A local environment depended knowledge based potential energy function is developed in this thesis. Two different environments, one of these is the local degree (number of contacts) and the other is the secondary structural element of amino acids, have been considered. The investigations have shown that the environment-based interaction preferences for amino acids is able to provide good potential energy functions which perform exceedingly well in discriminating the native structure from the structures with random interactions. Further, the membrane proteins are located in a completely different physico-chemical environment with different amino acid composition than the water soluble proteins. This work provides reliable potential energy functions which take care of different environment for the investigation(model/predict) of the structure of helical membrane proteins. Three different environments, parallel and perpendicular to the lipid bilayer and number of amino acid contacts, are explored to analyze the environmental effects on the potential functions. These environment dependent scoring functions perform exceedingly well indiscriminating the native sequence from a set of random sequences. Hydrophobicity of amino acids is a measure of buriedness or exposure to the aqueous environment. The lack of uniformity within the protein environment gives rise to the different values of hydrophobicity for the same amino acids, which completely depends on its location inside the protein.The contact based environment dependent hydrophobicity values of all amino acids, separately for globular and membrane proteins, have also been evaluated in this thesis. Apart from developing scoring functions, the packing of helices in membrane proteins is investigated by an approach based on the local backbone geometry and side chain atom-atom contacts of amino acids. A parameter defined in this study is able to capture the essential features of inter-helical packing, which may prove to be useful in modeling of helical membrane proteins. In conclusion, this thesis has described a novel technique to design the energetically minimized amino acid sequences which can fold in to a given conformation. Also the environment dependent interaction preference of amino acids in globular proteins is captured an efficient manner. Specially, the environment dependent scoring function for helical membrane proteins is a first successful attempt in this direction.